DEVELOPMENT AND APPLICATION OF TRACER-BASED PLANAR …

DEVELOPMENT AND APPLICATION OF TRACER-BASED

PLANAR LASER-INDUCED FLUORESCENCE IMAGING

DIAGNOSTICS FOR HCCI ENGINES

A DISSERTATION

SUBMITTED TO THE DEPARTMENT OF MECHANICAL

ENGINEERING

AND THE COMMITTEE ON GRADUATE STUDIES

OF STANFORD UNIVERSITY

IN PARTIAL FULFILLMENT OF THE REQUIREMENTS

FOR THE DEGREE OF

DOCTOR OF PHILOSOPHY

Jordan A. Snyder

March 2011

This dissertation is online at: http://purl.stanford.edu/yf741qr0615

© 2011 by Jordan Andrew Snyder. All Rights Reserved.

Re-distributed by Stanford University under license with the author.

ii

http://purl.stanford.edu/yf741qr0615

I certify that I have read this dissertation and that, in my opinion, it is fully adequatein scope and quality as a dissertation for the degree of Doctor of Philosophy.

Ronald Hanson, Primary Adviser


Christopher Edwards


Mark Mungal

Approved for the Stanford University Committee on Graduate Studies.

Patricia J. Gumport, Vice Provost Graduate Education

This signature page was generated electronically upon submission of this dissertation in electronic format. An original signed hard copy of the signature page is on file inUniversity Archives.

iii

iv

Abstract

Homogeneous charge compression ignition (HCCI) is an emerging engine strategy

that can provide both high efficiency and low emissions, particularly in terms of

NOx and soot. An important challenge of HCCI is the inherent narrow load range,

bounded by combustion instability and misfires at low-load, and high pressure rise-

rate (PRR) at high-load. In response, researchers have devised a number of strate-

gies to expand the limits of HCCI operation.

Negative valve overlap (NVO) with pilot injection can extend the low-load gaso-

line HCCI operating limit by increasing sensible energy during main compression

through hot residual gas retention. Chemical effects due to reformation of the pi-

lot injection may further impact combustion. Similarly, the high-load limit can be

extended by increasing naturally occurring thermal stratification (TS) of the in-

cylinder charge. These non-uniformities result in sequential auto-ignition that can

effectively lower the PRR and thus expand the high-load limit. While demonstra-

tions of these strategies have been successful and multiple engine studies have been

completed, further characterization of key processes such as residual gas mixing and

TS development is needed. This motivates the development of quantitative imaging

diagnostics to improve the understanding of these complicated processes.

In this study, tracer-based planar laser-induced fluorescence (PLIF) diagnostics

for temperature and composition have been refined and optimized for application

in HCCI engines at both load extremes. Acetone and 3-pentanone (both ketones)

have been selected as seeded PLIF tracers as they provide good overall sensitivity

and performance. Single-line and two-line diagnostic variations have been inves-

tigated, with an emphasis on optimizing overall diagnostic performance through

v

excitation wavelength selection. Based on a detailed uncertainty analysis excitation

wavelengths of 277 nm and 308 nm were selected for subsequent studies. Resulting

single-shot temperature precisions were typically on the order 4 K and 12 K for the

single-line and two-line techniques respectively. The corresponding mole fraction

precision for the two-line technique was typically 4-5%. These results are consistent

with the uncertainty analysis and demonstrate the utility of the optimization.

HCCI studies were performed in two optically accessible engines, each configured

for a specific load extreme. Residual mixing for low-load HCCI operation with NVO

was first studied using the two-line technique to provide the simultaneous temper-

ature and composition distribution. These measurements indicated rapid mixing of

retained residuals during gas exchange and early compression, reaching a steady-

state value midway through compression. Temperature stratification gradually in-

creased throughout the remainder of compression while compositional stratification

effectively remained constant. Variation of operating parameters such as main and

NVO injection timing exhibited minimal differences in thermal or compositional

stratification during main compression. Measurement during NVO recompression

and re-expansion were also acquired to assess the in-cylinder temperatures stratifi-

cation prior to chemical reaction and gas exchange.

Next the development of thermal stratification for high-load HCCI with conven-

tional valve timing was investigated using the single-line technique. These studies

indicated a progressive increase in TS during compression, reaching a maximum

standard deviation of 10 K at top dead center. Comparison of results for motored

and fired operation exhibited similar trends. This finding indicates that the mech-

anism producing the TS is the same for both cases, although some differences in

magnitude can occur. A subsequent parametric study proved that these differences

can be attributed to the impact of both incomplete fuel mixing and cylinder-wall

temperature variation, depending on the type of engine operation (DI skipfiring or

premixed continuous firing). All measurements demonstrate the feasibility of quan-

titative tracer-based PLIF diagnostics in harsh engine environments and provide

useful information for future HCCI engine development.

vi

Acknowledgements

First and foremost I would like to thank my advisor, Professor Ronald K. Hanson,

for providing a wealth of opportunities at Stanford. His vast technical knowledge,

research vision and relentless drive continue to inspire. It truly has been a privilege

to be a part of the Hanson research group. I also wish to thank the members of

my reading committee, Professor M. Godfrey Mungal and Professor Christopher F.

Edwards for their continuing guidance and input. Thanks also to Professor Robert

L. Byer for chairing my examination committee and to Professor Craig T. Bowman

for serving as an examiner.

I owe a debt of gratitude to Dr. David F. Davidson and Dr. Jay B. Jeffries for

the countless discussions and the willingness to always answer questions or lend a

hand when needed. A special thanks to all the members of the Hanson group, both

current and former. It is a unique opportunity to work with such a large, talented

group of students with overlapping but diverse interests. Dr. Dave Rothamer has

been particularly helpful in shaping my research at Stanford, and remains both a

great friend and mentor.

A large portion of my research was performed at the Combustion Research Facil-

ity at Sandia National Laboratories in Livermore, CA. As a result, I was privileged

to work closely with Dr. Richard R. Steeper, Dr. John E. Dec, Dr. Russell Fitzger-

ald and Dr. Nicolas Dronniou. This rare opportunity to work closely with such

accomplished and talented researchers has been invaluable to my knowledge and

development.

I am sincerely grateful to my parents, Nick and Sharon, who have always sup-

ported me and instilled a work ethic and drive that has allowed me to be successful

vii

both personally and academically. Finally, and most importantly I would like to

thank my loving wife Christen whose support has been unwavering throughout my

academic journey. Anything I have achieved is a direct result of her patience, sac-

rifice and frequent reminders of the bigger picture in life.

viii

Contents

Abstract v

Acknowledgements vii

1 Introduction 1

1.1 Background and Motivation . . . . . . . . . . . . . . . . . . . . . . . 1

1.1.1 PLIF . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1

1.2 Overview of Dissertation . . . . . . . . . . . . . . . . . . . . . . . . . 6

2 PLIF Technique and Optimization 8

2.1 PLIF Theory . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 9

2.1.1 Single-Line PLIF . . . . . . . . . . . . . . . . . . . . . . . . . 10

2.1.2 Two-Line PLIF . . . . . . . . . . . . . . . . . . . . . . . . . . 11

2.2 Tracer Selection . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 14

2.3 Wavelength Optimization . . . . . . . . . . . . . . . . . . . . . . . . 17

2.3.1 Uncertainty Analysis Theory . . . . . . . . . . . . . . . . . . . 18

2.3.2 Uncertainty Analysis Parameters . . . . . . . . . . . . . . . . 20

2.3.3 Single-Line Analysis . . . . . . . . . . . . . . . . . . . . . . . 22

2.3.4 Two-line Analysis . . . . . . . . . . . . . . . . . . . . . . . . . 28

3 Tracer Photophysics 33

3.1 FQY Measurements in a Motored IC Engine . . . . . . . . . . . . . . 34

3.1.1 Measurement Technique . . . . . . . . . . . . . . . . . . . . . 35

3.2 3-Pentanone Photophysics . . . . . . . . . . . . . . . . . . . . . . . . 39

ix

3.3 Acetone Photophysics . . . . . . . . . . . . . . . . . . . . . . . . . . 41

3.4 FQY Model Comparisons . . . . . . . . . . . . . . . . . . . . . . . . . 43

3.4.1 3-Pentanone Modeling . . . . . . . . . . . . . . . . . . . . . . 45

3.4.2 Acetone Modeling . . . . . . . . . . . . . . . . . . . . . . . . . 46

4 Fluorescence Saturation 49

4.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 49

4.2 Experimental Approach . . . . . . . . . . . . . . . . . . . . . . . . . 50

4.2.1 Optical Setup . . . . . . . . . . . . . . . . . . . . . . . . . . . 50

4.2.2 Data Acquisition . . . . . . . . . . . . . . . . . . . . . . . . . 52

4.2.3 Beam Width Measurements . . . . . . . . . . . . . . . . . . . 53

4.3 Experimental Results . . . . . . . . . . . . . . . . . . . . . . . . . . . 59

4.4 Saturation Wavelength Dependence . . . . . . . . . . . . . . . . . . . 59

4.5 Pressure and Composition Dependence . . . . . . . . . . . . . . . . . 62

5 Low-Load HCCI with NVO 67

5.1 Experimental Setup . . . . . . . . . . . . . . . . . . . . . . . . . . . . 69

5.1.1 Motored Engine Operation . . . . . . . . . . . . . . . . . . . . 72

5.1.2 Fired NVO Engine Operation . . . . . . . . . . . . . . . . . . 73

5.1.3 Data Acquisition . . . . . . . . . . . . . . . . . . . . . . . . . 75

5.2 Validation Experiments . . . . . . . . . . . . . . . . . . . . . . . . . . 76

5.3 Measurement Interferences . . . . . . . . . . . . . . . . . . . . . . . . 78

5.4 Fired NVO Results . . . . . . . . . . . . . . . . . . . . . . . . . . . . 82

6 High-Load HCCI 97

6.1 Experimental Setup . . . . . . . . . . . . . . . . . . . . . . . . . . . . 99

6.1.1 Optical Engine . . . . . . . . . . . . . . . . . . . . . . . . . . 99

6.1.2 PLIF System . . . . . . . . . . . . . . . . . . . . . . . . . . . 102

6.2 Engine Operation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 105

6.3 Data Acquisition and Processing . . . . . . . . . . . . . . . . . . . . . 106

6.3.1 Conventional Data Acquisition . . . . . . . . . . . . . . . . . . 106

6.3.2 PLIF Data and Processing . . . . . . . . . . . . . . . . . . . . 107

x

6.3.3 PLIF Data Processing . . . . . . . . . . . . . . . . . . . . . . 109

6.3.4 Photophysics . . . . . . . . . . . . . . . . . . . . . . . . . . . 109

6.4 PLIF Measurement Uncertainty . . . . . . . . . . . . . . . . . . . . . 110

6.4.1 Accuracy . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 110

6.4.2 Precision . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 112

6.5 Motored Engine Thermal Stratification . . . . . . . . . . . . . . . . . 115

6.5.1 Motored Stratification Statistics . . . . . . . . . . . . . . . . . 118

6.6 Fired Engine Thermal Stratification . . . . . . . . . . . . . . . . . . . 122

6.6.1 Residual Mixing . . . . . . . . . . . . . . . . . . . . . . . . . . 123

6.6.2 Comparison of Motored and Fired TS . . . . . . . . . . . . . . 131

6.6.3 Correlation of Temperature and Reacting Zones . . . . . . . . 134

7 Summary and Future Work 139

7.1 PLIF Development . . . . . . . . . . . . . . . . . . . . . . . . . . . . 139

7.1.1 Future Work: PLIF Development . . . . . . . . . . . . . . . . 141

7.2 HCCI with NVO . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 142

7.2.1 Future Work: HCCI with NVO . . . . . . . . . . . . . . . . . 143

7.3 HCCI Thermal Stratification . . . . . . . . . . . . . . . . . . . . . . . 144

7.3.1 Future Work: HCCI TS . . . . . . . . . . . . . . . . . . . . . 145

A Ketone Photophysical Parameter Fits 147

B Uncertainty Analysis Theory 151

C Camera Noise Characterization 154

Bibliography 157

xi

List of Tables

2.1 Excitation wavelengths, energy and energy stability inputs used for

temperature and EGR precision calculations . . . . . . . . . . . . . . 22

2.2 Input parameters used for temperature and EGR precision calcula-

tions, same as . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 23

4.1 Excitation wavelength specifications for saturation experiments . . . . 57

4.2 Experimental measurements of 10% non-linear threshold for various

tracer and excitation wavelengths . . . . . . . . . . . . . . . . . . . . 61

5.1 HCCI engine specification for NVO operation . . . . . . . . . . . . . 70

5.2 Fired engine operating conditions. . . . . . . . . . . . . . . . . . . . . 75

6.1 Engine Specifications . . . . . . . . . . . . . . . . . . . . . . . . . . . 101

6.2 Engine Operating Conditions . . . . . . . . . . . . . . . . . . . . . . 103

A.1 Temperature dependent gaussian fit parameters for the absorption

cross section of acetone and 3-pentanone for 230-330 nm and 300-

1040 K, taken from [1]. Temperature in kelvin. . . . . . . . . . . . . . 147

A.2 Quadratic fit parameters of 3-pentanone absolute FQY in pure ni-

trogen measured in a motored engine. Fit parameters for a given

image time (pressure) are used in conjunction with Equation A.2 to

calculate the FQY for temperature within the stated range. . . . . . . 149

xii

A.3 Linear fit parameters of acetone absolute FQY in pure nitrogen mea-

sured in a motored engine. Fit parameters for a given image time

(pressure) are used in conjunction with Equation A.3 to calculate the

FQY for temperature within the stated range. . . . . . . . . . . . . . 150

xiii

List of Figures

2.1 3-Pentanone single-line PLIF measurement uncertainty estimates of

temperature for potential excitation wavelength pairs. All precision

is quoted based on ±1 standard deviation. . . . . . . . . . . . . . . . 25

2.2 Acetone single-line PLIF measurement uncertainty estimates of tem-

perature for potential excitation wavelength pairs. All precision is

quoted based on ±1 standard deviation. . . . . . . . . . . . . . . . . 27

2.3 Toluene single-line PLIF measurement uncertainty estimates of tem-

perature for potential wavelength pairs. Simulations are for an N2

intake stream. All precision is quoted based on ± 1 standard deviation. 29

2.4 3-Pentanone two-line PLIF measurement uncertainty estimates of

temperature (left) and EGR mole fraction (right) for potential excita-

tion wavelength pairs. All precision is quoted based on ±1 standard

deviation. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 31

2.5 Acetone two-line PLIF measurement uncertainty estimates of tem-

perature (left) and EGR mole fraction (right) for potential excitation

wavelength pairs. All precision is quoted based on ±1 standard devi-

ation. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 32

3.1 Absolute FQY of 3-pentanone in nitrogen at 277 nm and 308 nm,

measured under motored engine conditions. Each curve represents

experiments at a given image timing (pressure) for a range of intake

temperatures. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 40

xiv

3.2 Comparison of absolute FQY results from motored engine and flowing

cell . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 42

3.3 Absolute FQY of acetone in nitrogen at 277 nm and 308 nm, measured

under motored engine conditions. Each curve represents experiments

at a given image timing and pressure for a range of intake temperatures 43

3.4 Comparison of engine FQY data derived from quadratic fits and FQY

model simulations. (a) Absolute FQY, (b) Normalized FQY for better

comparison of slope. . . . . . . . . . . . . . . . . . . . . . . . . . . . 46

3.5 Comparison of engine FQY data derived from linear fits and FQY

model simulations. (a) Absolute FQY, (b) Normalized FQY for better

comparison of slope. . . . . . . . . . . . . . . . . . . . . . . . . . . . 47

4.1 Experimental setup for measurement of tracer saturation intensity . . 52

4.2 (a) Representative fluorescence images without focusing lens (top)

and with lens (bottom), laser propagation is from left to right. (b)

Corrected axial signal saturation profile indicating fraction deviation

from linearity. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 54

4.3 (a) Series of beam profile images acquired along beam focus. (b)

Measured beam half width along focus with fit results. . . . . . . . . 56

4.4 Percent deviation from linearity as a function of laser fluence, mea-

sured for 308 nm excitation of 3-pentanone at 1 bar in N2 (derived

from same data as Figure 4.2) . . . . . . . . . . . . . . . . . . . . . . 59

4.5 Comparison of deviation from linearity for acetone, 3-pentanone and

toluene at 248 nm excitation, and 1 bar of N2. . . . . . . . . . . . . . 60

4.6 Comparison of 10% non-linear threshold (top) and inverse absorption

cross-section (bottom) for all tracers and wavelengths . . . . . . . . . 62

4.7 (a) Pressure dependence of 3-pentanone saturation with 308 nm ex-

citation and a nitrogen bath gas. (b) Comparison of saturation char-

acteristics for nitrogen and air bath gases with 308 nm excitation

at 15 psi total pressure. Multiple curves included to demonstrate

measurement repeatability. . . . . . . . . . . . . . . . . . . . . . . . . 64

xv

4.8 Pressure dependence of acetone saturation in pure nitrogen for exci-

tation wavelengths of (a) 277 nm and (b) 248 nm. . . . . . . . . . . . 65

4.9 Pressure dependence of toluene saturation with 248 nm excitation

and a nitrogen bath gas. . . . . . . . . . . . . . . . . . . . . . . . . . 66

5.1 Experimental schematic . . . . . . . . . . . . . . . . . . . . . . . . . 71

5.2 Sample PLIF image with valve, injector and piston window positions

superimposed. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 71

5.3 Measured pressure for NVO engine operation, (a) pressure vs. CAD

showing valve events and measurement regimes; (b) pressure vs. vol-

ume (log-log scaling) . . . . . . . . . . . . . . . . . . . . . . . . . . . 74

5.4 (a) Measured average temperature and (b) air mole fraction measured

for motored engine conditions with air intake temperature of 412 K

and a manifold pressure of 1 bar. . . . . . . . . . . . . . . . . . . . . 77

5.5 (a) Measured temperature standard deviation and (b) air mole frac-

tion standard deviation for motored conditions with air intake tem-

perature of 412 K and manifold pressure of 1 bar. . . . . . . . . . . . 78

5.6 Single-shot 277 nm and 308 nm LIF images of (a) residual gas recorded

at +260 CD (no tracer), (b) carry-over 3P recorded at +260 CAD

(prior to fuel injection, and (c) 3P recorded at +285 CAD (following

DI fuel injection) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 80

5.7 Single-shot temperature and fuel mole fraction image pairs of carry-

over 3P signal during NVO recompression. Image capture timing

is +260 CAD for all images. Three main combustion loads: (a) 7

mg/cycle, (b) 8 mg/cycle, (c) 9.5 mg/cycle. . . . . . . . . . . . . . . 84

5.8 Single-shot temperature and fuel mole fraction images during NVO

recompression. Image capture time = +285 CAD. Three main com-

bustion loads: (a) 7 mg/cycle, (b) 8 mg/cycle, (c) 9.5 mg/cycle . . . 86

5.9 Single-shot temperature and fuel mole fraction images during NVO

expansion for early main injection at -320 CAD. Three NVO SOI

timings shown: (a) +260, (b) +300, and (c) +330 CAD. . . . . . . . 88

xvi

5.10 Single-shot temperature and EGR mole fraction images recorded at

three image timings: (a) -215, (b) -65, and (c) -24 CAD. NVO SOI

= +330 CAD; main SOI = -270 CAD. Images at -24 CAD (only) are

binned 2x2. Note variable temperature color scale. . . . . . . . . . . . 90

5.11 Demonstration of data correction for diagnostic uncertainty. . . . . . 92

5.12 (a) Measured average temperature and (b) temperature standard de-

viation for several engine operating conditions. The error bars shown

in (a) represent accuracy estimated from motored diagnostic charac-

terization experiments. . . . . . . . . . . . . . . . . . . . . . . . . . . 94

5.13 (a) Measured average EGR mole fraction and (b) EGR standard de-

viation for several engine operating conditions. Error bars represent

accuracy estimated from motored diagnostic characterization experi-

ments. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 96

6.1 Detailed schematic of optical HCCI engine showing location of laser

sheets and imaging camera. . . . . . . . . . . . . . . . . . . . . . . . 100

6.2 HCCI engine facility schematic. . . . . . . . . . . . . . . . . . . . . . 102

6.3 PLIF experimental schematic for high load HCCI experiments . . . . 104

6.4 PLIF image field of view with valves, injector, and piston window

positions superimposed. . . . . . . . . . . . . . . . . . . . . . . . . . 104

6.5 Measured absolute temperature for motored engine conditions with

N2 intake temperature of 170C and 1 bar manifold pressure . . . . . 111

6.6 (a) In-cylinder pressure and temperature (calculated) for the baseline

HCCI operating condition. (b) Temperature precision of single-line

and two-line diagnostics of 3-pentanone ad acetone, calculated for

baseline conditions . . . . . . . . . . . . . . . . . . . . . . . . . . . . 113

6.7 Single-shot temperature images of TS development during main com-

pression of motored engine. Diagnostic - 3-Pentanone, single-line 277

nm . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 117

6.8 Comparison of single-line and two-line image quality . . . . . . . . . 118

xvii

6.9 Demonstration of measurement uncertainty correction, comparing

corrected and uncorrect temperature standard deviation for single-

line 3-pentanone at 308 nm excitation. . . . . . . . . . . . . . . . . . 119

6.10 Temperature standard deviation (corrected) calculated from single-

shot temperature images for both 3-pentanone (3P) and acetone (Ac)

for different excitation wavelengths. . . . . . . . . . . . . . . . . . . . 120

6.11 Demonstration of image binarization and pocket detection (b) for a

single-shot temperature distribution (a) acquired in motored engine. . 121

6.12 Evolution of cold pocket frequency and effective diameter during mo-

tored compression at 170C intake temperature. Statistics derived

from single-line 3-pentanone measurements at 277 nm. . . . . . . . . 122

6.13 Measured cylinder pressure tracers for 17-3 skipfired operation. . . . . 124

6.14 In-cylinder conditions for fired studies. The core temperature is esti-

mated from measured pressure trace assuming adiabatic compression

with variable specific heats. Data points correspond to PLIF image

timings. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 125

6.15 Single-shot temperature (left) and air mole fraction (right) image pair

sequence showing evolution of residual gas mixing during the intake

and early compression for fired HCCI operation. Diagnostic: two-line

277/308nm, 3-pentanone. . . . . . . . . . . . . . . . . . . . . . . . . . 127

6.16 Single-shot PLIF temperature sequence of TS development for skip-

fired (cycle 20) HCCI engine operation. Diagnostic - single-line 277

nm, 3-pentanone. Engine conditions: skipfired, φ=0.4, Tin=198C,

Pin=100 kPa, 14% 3-pentanone in iso-octane. . . . . . . . . . . . . . 129

6.17 Noise-corrected temperature standard deviation for cycle 18 (no hot

residuals) and cycle 20 (hot residuals). Diagnostic: single-line 277nm,

3-pentanone. Engine conditions: skipfired, φ=0.4, Tin=198C, Pin=100

kPa, 14% 3-pentanone in iso-octane. . . . . . . . . . . . . . . . . . . 131

xviii

6.18 Impact of direct fuel injection on measured temperature standard

deviation for motored engine operation. Engine conditions are iden-

tical to skipfired experiments of Figure 6.16. Diagnostic: single-line

277nm, 3-pentanone. Engine conditions: skipfired, φ=0.4, Tin=198C,

Pin=100 kPa, 14% 3-pentanone in iso-octane. . . . . . . . . . . . . . 133

6.19 Impact of upper cylinder-wall temperature based on the noise cor-

rected temperature standard deviation for motored and fired op-

eration with varying coolant temperature. Diagnostic: single-line

277nm, 3-pentanone. Engine conditions: continuous fired, φ=0.32,

Tin=190C, 17% 3-pentanone in iso-octane. . . . . . . . . . . . . . . 134

6.20 (a) Inverse binarization of fluorescence signal highlighting reaction

zones. (b) Correlation between reaction area ratio (RAR) and CA10

combustion phasing. . . . . . . . . . . . . . . . . . . . . . . . . . . . 136

6.21 Spatial correlation of temperature distribution before TDC (left) and

early reaction zones (right) after TDC acquired for same cycle . . . . 138

C.1 Characterization of PIMAX2:1003 image SNR versus signal based on

the temporal SNR method. Polynomial fit results included for reference.156

xix

xx

Chapter 1

Introduction

1.1 Background and Motivation

1.1.1 PLIF

Planar laser-induced fluorescence (PLIF) is a non-intrusive, spatially resolved opti-

cal diagnostic that has evolved into a valuable tool for the investigation of flowfields

and combustion systems [2]. PLIF is most frequently employed to measure species

concentration (mole fraction) [3–7], however fluorescence sensitivities can be uti-

lized to develop diagnostic strategies for temperature [8–11], pressure [12–14] and

velocity [12, 15–17]. High characteristic signal levels make PLIF an appropriate

choice for quantitative single-shot imaging and can provide temporal resolution of

instantaneous flow phenomena. Alternative techniques such as Raman [18, 19] and

Rayleigh [20,21] scattering can also be utilized for quantitative measurements. How-

ever, these techniques typically must be highly averaged (spatially or temporally) to

overcome the inherently low signals and are less applicable when temporal resolution

is of interest.

PLIF is characterized by a two-stage process: laser-induced absorption which is

followed closely by spontaneous emission (fluorescence). A typical PLIF implemen-

tation consists of a pump laser, a collection camera, and the associated laser sheet

forming and collection optics. The laser output, tuned to an absorption feature of

1

2 CHAPTER 1. INTRODUCTION

the probed species, is formed into a thin sheet and used to illuminate the flowfield of

interest. A portion of the laser photons are absorbed, promoting a valence electron

of the probed molecule to an excited state. Electronic excitation using ultraviolet

wavelengths is most common, however excitation of vibrational transitions in the

infrared (IR-PLIF) has also been demonstrated [22,23]. A fraction of these excited

molecules will subsequently return to the ground state while simultaneously emit-

ting a photon, resulting in measurable fluorescence signal. This fluorescence signal

is captured at 90 by a CCD camera, providing a two-dimensional image of the

flow-field.

The probed species can either occur naturally in the flow (i.e. OH , CH, NO,

O2) or be artificially seeded into the flow as a tracer. Because a majority of the

electronically active species are combustion radicals, they can not be used to char-

acterize the flow prior to reaction. As a result, seeded organic tracers such as

acetone [24, 25], 3-pentanone [26, 27], and toluene [28, 29] are commonly used for

measurements in non-reacting flowfields or in combustion systems prior to chemical

reaction. To permit quantitative tracer-based techniques, substantial effort has gone

into characterizing the spectroscopic behavior of these tracers [30–35].

Tracer-based PLIF has historically been used in internal combustion (IC) engine

research with noted success and has helped to improve understanding of basic en-

gine processes as well as advanced engine concepts. Engine applications typically

focus on measuring in-cylinder fuel distribution [36–39]. Quantitative temperature

measurements have also been demonstrated but with less frequency [40–44]. While

these studies show favorable results, further technique refinement can improve mea-

surement accuracy and precision. Diagnostic precision is especially important when

studying small spatial fluctuations within the flowfield and limits the degree of non-

uniformity that can be resolved. The current work explores the optimization of

PLIF measurement precision through careful selection of tracer species and excita-

tion wavelength. The optimization focuses on thermodynamic conditions relevant

for homogeneous charge compression ignition engines (HCCI) as stratification has

been found to influence HCCI combustion.

1.1. BACKGROUND AND MOTIVATION 3

HCCI Engines

Homogeneous charge compression ignition (HCCI) is an emerging engine strategy

that can provide both high thermal efficiency and low emissions [45], particularly in

terms of soot and nitric oxide. HCCI is often characterized as combining benefits

from spark-ignition (SI) gasoline and compression-ignition (CI) diesel engines. Fun-

damentally, HCCI utilizes a premixed charge similar to an SI engine but operates

with a globally lean mixture that is ignited solely by compression similar to a diesel

engine. However, unlike SI or CI engines HCCI combustion occurs volumetrically

throughout the charge with no discernable flame-front propagation, thus reducing

the total reaction time. Overall, HCCI has the potential to provide near diesel-like

efficiencies with reduced emissions.

The concept of HCCI has been around for nearly 30 years, although HCCI has

only recently received substantial research attention as a viable and efficient engine

strategy. The concept of HCCI was first proposed by Onishi et al. [46] for two-stroke

engines and was later extended to the four-stroke cycle by Najt et al. [47] . Since

these early studies, substantial research effort has been focused on characterizing

overall HCCI performance and mapping out the load-speed operating range. Multi-

ple reviews of HCCI concepts and technologies are available and provide a detailed

discussion of current trends that will only be mentioned here briefly [48–50].

There are several factors that contribute to the improved efficiency of the HCCI

engine over conventional SI engines [45]. First, the lack of spark-ignition and a

propagating flame-front permits operation at fuel lean conditions and eliminates

the need to operate near stoichiometric fueling. This means that intake throttling

at partial load is no longer required thus reducing pumping losses and improving

efficiency. Second, the engine can generally be operated at higher compression

ratios as auto-ignition is actually a requirement. Third, the duration of combustion

is shorter which reduces heat transfer and further improves efficiency.

Attributes that improve engine efficiency also help to reduce the emission of

several regulated pollutants. Specifically, the lean fuel/air mixture results in lower


combustion temperatures and avoids the thermal formation of NOx. This is in con-

trast to diesel engines where peak in-cylinder temperatures can reach 2700 K [48],

resulting in high levels of NOx formation. In addition, the lean premixed charge

results in negligible soot formation due to the low combustion temperatures and

the avoidance of localized fuel rich regions that generate high polycyclic aromatic

hydrocarbons (PAHs) concentrations. Additional advantages of HCCI include the

potential for lower equipment cost by avoiding the need for a high-pressure injec-

tor system and costly exhaust after-treatments, as well as the scalability of the

engine stategy over a range of applications (light to heavy duty). HCCI engines

can operate with a range of fuels, however this research considers only gasoline-

type HCCI (single-stage fuel with no low temperature combustion) with a focus on

light/medium applications at partial-load.

Along with the benefits of HCCI come a number of technical challenges that must

be addressed prior to widespread implementation. A primary challenge is the control

of combustion phasing. Unlike SI or CI engines that utilize spark or direct fuel

injection to control phasing, there is no direct means to control the onset of HCCI

combustion. Instead the combustion phasing is kinetically-limited and is dependent

only on the mixture properties and the temperature and pressure time history. A

second challenge is the potential for elevated unburned hydrocarbons (UHC) and

CO emissions. This results from the low combustion and exhaust temperatures

associated with lean operation, and high fuel concentration in crevice volumes due

to the premixed fueling. A third challenge is the narrow HCCI load range that

is limited by combustion instabilities and misfires at the low-load limit, and high

pressure rise-rates and engine knock at the high-load limit. HCCI is likely to be

implemented in a hybrid system with spark ignition operation used for high-load,

and HCCI used for low-load. However, expanding the HCCI load range is still

important as it will maximize the benefit of the HCCI cycle and will reduce the

frequency of mode transitions. The current work focuses on potential strategies to

expand the HCCI operating range.

1.1. BACKGROUND AND MOTIVATION 5

Low-Load HCCI

Many strategies for low-load extension incorporate extensive exhaust gas recircula-

tion (EGR) to provide additional thermal energy during the compression stroke in

an effort to enhance combustion at lighter loads. A common approach to achieve

these high levels of internal EGR is through negative valve overlap (NVO) [51–53].

By advancing the exhaust valve closing (EVC) and delaying the intake valve open-

ing (IVO) a substantial fraction of hot exhaust gas can be retained in-cylinder.

Ignition may be further enhanced through pilot fuel injection during the NVO re-

compression [51,52,54,55]. Exothermic reaction of pilot fuel during NVO increases

charge temperature, and could produce reformed fuel species that may affect main

combustion phasing [55,56]. An advantage of this strategy is the potential for con-

trolling main combustion phasing by varying NVO parameters including the amount

of EGR, the NVO injection timing, and the NVO/main fuel-injection split.

While performance of low-load NVO operation has been demonstrated [51,52,57–

59], understanding of key processes can still be improved. Specifically, high residual

gas fraction may result in temperature and compositional stratification near top

dead center (TDC) that could further impact combustion. Currently, little is known

of the degree of stratification that persists throughout compression for HCCI with

NVO, motivating the development of in-situ visualization techniques to study this

complicated process.

High-Load HCCI

To overcome the high pressure rise-rates (PRR) associated with high-load operation

charge stratification has been investigated as it promotes sequential auto-ignition of

the in-cylinder charge [60–63]. Here, both induced and naturally occurring variations

in charge conditions (temperature and composition) can cause preferential ignition

in localized regions followed sequentially by remaining portions of the charge. Past

studies have shown that fuel stratification is only effective in altering the PRR when

operating with fuels that exhibit two-stage ignition (low temperature chemistry) [64].

This indicates that thermal stratification alone will dominate gasoline high-load


HCCI combustion.

Despite the importance of thermal stratification (TS), little quantitative data

is available regarding the distribution and evolution of TS. This provides further

motivation for the development of high-fidelity, single-shot imaging diagnostics ca-

pable of resolving the small temperature fluctuations relevant for HCCI. Based on

the challenging environment and the high measurement precision required for both

low- and high-load HCCI measurements, tracer-based PLIF techniques have been

selected.

1.2 Overview of Dissertation

The focus of this dissertation is the development and optimization of tracer-based

PLIF imaging diagnostics for specific application in HCCI engines. Chapter 2 pro-

vides the theoretical derivation of two PLIF diagnostic variations, a single excitation

(single-line) and dual-excitation (two-line) strategy. Optimization efforts to max-

imize diagnostic performance for the HCCI engine domain are also highlighted.

Chapter 3 focuses on engine-based measurements of tracer fluorescence quantum

yield (FQY), a critical spectroscopic parameter for quantitative PLIF measurements.

Chapter 4 investigates the fundamental fluorescence saturation behavior of common

organic tracers and provides limitations on pump laser energies to ensure linear

fluorescence behavior.

Application of the two-line PLIF diagnostic for simultaneous measurement of

temperature and composition in an HCCI engine with negative valve overlap (NVO)

is discussed in Chapter 5. Topics include the validation of the technique in a motored

engine, temperature and fuel concentration measurements during the NVO recom-

pression and re-expansion, and characterization of the residual gas mixing during

main compression. Chapter 6 concentrates on single-line PLIF measurements of

thermal stratification (TS) in a low-residual, high-load HCCI engine. Studies in-

clude characterization of TS development under both motored and fired operation,

and correlation between the temperature distribution and early chemical reaction.

1.2. OVERVIEW OF DISSERTATION 7

Lastly, Chapter 7 summarizes the overall development and application results and

proposes future directions in terms of diagnostic improvements and additional engine

studies.

Chapter 2

PLIF Technique and Optimization

Development of trace-based PLIF diagnostics includes the selection of the excita-

tion/collection strategy, tracer species, excitation wavelengths, and equipment. Po-

tential diagnostic variations include single tracer with dual-wavelength excitation,

dual tracer with single excitation and dual collection bands, and single tracer sin-

gle excitation with dual collection bands. A variety of these strategies have been

successfully demonstrated [26,36,44,65–71].

Single-line excitation of acetone, 3-pentanone and toluene has been frequently

used for fuel mole fraction or equivalence ratio measurements [36,65,66]. Similarly,

Thurber et al. [67] utilized 248 nm excitation of acetone to measure temperature

of mixing jets for isobaric, homogeneously seeded conditions. Kakuho et al. [68]

performed temperature measurements, using 266 nm excitation of a combination of

3-pentanone and triethylamine (TEA) followed by dual-band collection of the spec-

trally separated fluorescence, to investigate the correlation between temperature

and ignition time of HCCI combustion. Luong et al [69] utilized 266 nm excitation

of toluene with dual-band collection to infer temperature based on the fluorescence

emission spectral shift with temperature. Simultaneous measurements of tempera-

ture and fuel concentration were performed by Einecke et al. [26], through 248 nm

and 308 nm excitation of 3-pentanone. Rothamer et al. [44, 70] later refined this

two-line technique through optimization of excitation wavelengths at 277 nm and

308 nm. Additional examples of tracer-based PLIF techniques are available and are

8

2.1. PLIF THEORY 9

well-summarized by Schulz et al. [72].

Criteria for technique selection typically includes consideration of the application

requirements, equipment, and availability of tracer photophysical data. The current

development targets HCCI engines ranging from low-load HCCI with NVO, to high-

load HCCI with preheat. Based on these applications, a single-line temperature

measurement has been selected for specific use in high-load HCCI engines where

mixtures are expected to be compositionally homogeneous. To address the high

residual fraction present in low-load HCCI operation with NVO, a two-line technique

has been selected for simultaneous measurement of temperature and EGR mole

fraction. The following sections discuss the development of these techniques, with

emphasis on tracer and wavelength selection for optimized diagnostic performance.

2.1 PLIF Theory

All PLIF diagnostics in this study are based on interpretation of fluorescence signal

from various excitation wavelengths. The governing equation of fluorescence signal

in the linear (weak excitation) regime is given by

Sf =E

hcνdVc

[xtrP

kT

]σ (λ, T ) φ (λ, T, P, x)

Ω

4πηcoll (2.1)

where Sf is the number of photons incident [photons/pixel], E is the local laser

fluence [J/cm2], h is Planck’s constant [J s], c is the speed of light in a vacuum

[cm/s], ν is the excitation laser frequency [cm−1], dVc is the probed volume [cm3],

xtr is the tracer mole fraction, P is the total pressure [MPa], k is the Boltzmann

constant [J/K], T is the local temperature [K], σ is the absorption cross-section

[cm2], φ is the fluorescence quantum yield (FQY), Ω is the solid angle of collection,

and ηcoll is the collection efficiency of the imaging optics (including transmission and

collection efficiencies).

As indicated in Equation 2.1, fluorescence is dependent on temperature, pres-

sure, and composition through the absorption cross-section, fluorescence quantum

yield and tracer number density (ntr = xtrP/kt). These dependencies permit the

10 CHAPTER 2. PLIF TECHNIQUE AND OPTIMIZATION

development of various PLIF diagnostic strategies for measurement of temperature

and composition. The accuracy of any technique depends on knowledge of the

photophysical parameters (absorption cross-section, and FQY) over the range of

desired experimental conditions, and will be discussed further in Chapter 3. Quan-

titative measurements also require that the laser energy (E) and collection terms

(dVc, Ω/4π, ηcoll) either be known or correctable. As these parameters are often

difficult to measure accurately, suitable calibration schemes must be incorporated.

The following sections highlight the development of a single-line, and a two-line

PLIF technique, optimized for application in IC engines. While these diagnostics

are presented in the context of engine research, they apply equally as well to other

systems.

2.1.1 Single-Line PLIF

As the name implies, the single-line excitation strategy derives temperature from

the fluorescence signal of a single excitation wavelength. Application of this tech-

nique is restricted to conditions of uniform pressure and tracer mole fraction, as

variations in fluorescence signal due to temperature and tracer number density are

indistinguishable. The theoretical representation of the single-line scheme is shown

in Equation 2.2.

Sf

Scalf

=E

Ecal

P

P cal

T cal

T

σ(λ, T )

σcal(λ, T )

φ(λ, T, P, xi)

φcal(λ, T, P, xi)(2.2)

This relation was derived by normalizing the linear LIF relation, Equation 2.1, with

a calibration signal (indicated with the cal superscript) acquired under homogeneous

conditions of known temperature, pressure and tracer mole fraction. The calibration,

or flat-field image, eliminates the need to directly measure the collection terms

(dVc, Ω/4π, ηcoll). In addition, the calibration measurements correct for spatial

non-uniformities in laser sheet energy distribution, assuming minimal shot-to-shot

variations in laser profile (sheet cross-section) and mean energy during the time

between acquisition of calibration and data images. For engine experiments, the

2.1. PLIF THEORY 11

calibration images are typically acquired during motored operation at a time near

bottom dead center (BDC) where the in-cylinder conditions are known and the

mixture is homogeneous. The pressure term, P, in Equation 2.2 are assumed to

be known based on single-point in-cylinder pressure measurements recorded during

each cycle.

Equation 2.2 can be further simplified by combining temperature-dependent

terms and defining the single-line photophysical parameter, PPs, as shown in Equa-

tion 2.3. Substituting this relation into Equation 2.2 results in the principal equation

for single-line temperature calibration, Equation 2.4. Performing the calibration

correction in this fashion results in a measure of PPs, which itself is a function of

temperature, pressure, and to a lesser extent species mole fraction. PPs is calculated

as a function of these variables through knowledge of the absorption cross-section

and FQY (as described in Chapter 3), and temperature is determined by iteratively

solving Equation 2.4.

PPs(T, P, xi) =σ(λ, T )φ(λ, T, P, xi)

T(2.3)

PPs(T, P, xi) =Sf

Scalf

Ecal

E

P cal

PPP cal

s (2.4)

2.1.2 Two-Line PLIF

The two-line strategy derives temperature from the ratio of fluorescence signal re-

sulting from two excitation wavelengths. This ratio eliminates the dependence on

the tracer mole fraction, which increases the versatility of the technique and per-

mits application in systems with spatially varying composition. This technique is

particularly useful when investigating engine strategies utilizing significant residual

gas fraction such as HCCI with NVO. The signal ratio is given by Equation 2.5,

where subscripts 1 and 2 correspond to distinct excitation wavelengths λ1 and λ2.

As with the single-line technique, the signal ratio is normalized by a calibration ra-

tio acquired under known homogeneous conditions (T,P,xi) to account for collection


terms and the laser energy distribution.

Sf2/Sf1

Scalf2 /Scal

f1

=E2

E1

Ecal1

Ecal2

[σ2(λ2, T )φ2(λ2, T, P, xi)

σ1(λ1, T )φ1(λ1, T, P, xi)

] [σcal

1 (λ1, T )φcal1 (λ1, T, P, xi)

σcal2 (λ2, T )φcal

2 (λ2, T, P, xi)

](2.5)

Equation 2.5 is simplified by defining the ratio of photophysical parameters,

Rpp = σ2φ2

σ1φ1, as shown in Equation 2.6. Performing the two-line calibration in this

fashion results in a measurement of RPP which is itself a function of temperature,

pressure and to a lesser extend composition. Temperature is determined by calcu-

lating RP P as a function of these variables through knowledge of the photophysical

parameters (Chapter 3), and iteratively solving Equation 2.6.

Rpp(T, P, xi) =σ2φ2

σ1φ1

=Sf2

Sf1

Scal1

Scal2

RcalPP (2.6)

The use of two excitation wavelengths allows temperature and composition to

be measured simultaneously. Local composition is determined using the signal from

either of the two excitation wavelengths and the measured temperature. The com-

position quantity being measured depends on where the tracer is seeded and how

the data is processed. By seeding the fuel with tracer, measurement of the local

fuel mole fraction (or concentration) is possible. Similarly, seeding of the intake air

permits measurement of air mole fraction. If we further assume that in-cylinder

contents consist only of intake air, EGR, and fuel, negative imaging of the EGR

is possible by seeding both the fuel and air. Here, air-plus-fuel mole fraction is

measured directly and the EGR mole fraction is determine using Equation 2.7.

xEGR = 1− (xA + xf ) (2.7)

This approach assumes that all tracer in the air and fuel is consumed during com-

bustion and is not present in the EGR. A similar technique was first applied by De-

shamps et al. [40] to estimate average EGR distributions, and was termed negative-

PLIF due to the indirect method of measurement. Rothamer et al. [44] later refined

this technique for quantitative simultaneous EGR and temperature measurements

in HCCI engines. The same designation will be used throughout this work, but

2.1. PLIF THEORY 13

abbreviated to N-PLIF. Both direct fuel composition and N-PLIF measurements of

EGR results are discussed in Chapter 5.

To calibrate mole fraction measurements, the fluorescence signal for a given

excitation wavelength is normalized by the corresponding calibration image. Solving

this ratio for xtr results in Equation 2.8, where T is the measured temperature

determined above. Assuming laser energy terms cancel as previously stated, all other

variables in Equation 2.8 are known and the tracer mole fraction can be calculated

directly. For fuel-seeded measurements, the tracer and fuel mole fraction are related

by Equation 2.7, where xs is the mole fraction of tracer seeded into the liquid fuel.

For N-PLIF measurements of EGR mole fraction, the air-plus-fuel mole fraction is

first determined using Equation 2.10, where in this case xs is the tracer mole fraction

seeded into the air and fuel, and xcalA = 1 for motored calibration images with no fuel

present. Finally, EGR mole fraction is calculated using the characteristic N-PLIF

relation, Equation 2.7. For the low-load NVO experiments considered in Chapter 5

only the air was seeded with tracer. Because the fuel constitutes an insignificant

fraction of the total charge, seeding only the air does not introduce significant error

in the EGR mole fraction measurements.

xtr

xcaltr

=Ecal

E

P cal

P

T

T cal

σcal (λ, T )

σ (λ, T )

φcal (λ, T, P, x)

φ (λ, T, P, x)

Sf

Scalf

(2.8)

xf =xtr

xs

(2.9)

xtr

xcaltr

=xs(xA + xF )

xs(xcalA )

= xA + xF (2.10)

The preceding theoretical development outlines the general framework for the

two diagnostic variations. However, a number of additional selections must still be

made including the tracer species, and the excitation wavelengths. The following

sections detail these selections with particular emphasis on optimizing diagnostic

performance for application in HCCI engines.


2.2 Tracer Selection

When selecting suitable tracer molecules, a number of factors must be considered

including: (1) absorption spectrum optically accessible with high-power lasers, (2)

overall fluorescence signal and sensitivity to temperature, (3) fluorescence sensitiv-

ity to oxygen quenching, (4) availability of photophysical data, and (5) evaporation

characteristics (for fuel tracing). The relative importance of these criterion will vary

somewhat depending on the desired measurement quantity (i.e. temperature, EGR

mole fraction, fuel mole fraction). Ideally a tracer should be optically accessible

by a high-power laser source such as an excimer or Nd:YAG laser which eliminates

the need for more complex tunable laser sources. The tracer should also produce

high fluorescence signal levels (due to a combination of high FQY and absorption)

at reasonable seed concentrations, as well as exhibit good fluorescence sensitiv-

ity to temperature. These two factors are particularly important when single-shot

measurements are desired, as the combination of these factors is what ultimately

determines the diagnostic performance.

Fluorescence sensitivity to oxygen should ideally be minimal as this tends to re-

duce the maximum signal levels and complicates the signal interpretation for highly

stratified conditions. Availability of photophysical data is critical as this is required

for signal interpretation, and limits the accuracy of the processed results. Finally,

for cases when fuel tracing is of interest the tracer should exhibit evaporation char-

acteristics similar to the base fuel to avoid distillation effects. This is often thought

of in terms of matching the boiling point of the tracer and fuel, although more recent

studies have indicated that this is not an exact criterion [73].

Potential fluorescent tracers range in size from small atomic and diatomic species

(e.g. iodine, NO, SO2, NO2), up to larger hydrocarbons (e.g. aldehydes, aromat-

ics, amines and ketones). The class of large hydrocarbon tracer molecules fulfill a

majority of the selection criterion above, and will be considered here exclusively.

Comprehensive discussions of potential tracers are included in [72, 94]. Common

organic tracers used in engine research include acetone, 3-pentanone, biacetyl and

toluene. Other tracer molecules such as acetaldehyde, formaldehyde, triethylamine

2.2. TRACER SELECTION 15

(TEA), fluorobenzene, and naphthalene have been used in previous studies but are

not considered here due to either their toxicity or a lack of sufficient photophysi-

cal data. These larger molecules typically have broad-band absorption spectra due

to the high density of energy states, permitting the use of high-power lasers. The

potential excitation wavelengths include 248 nm (KrF Excimer), 266 nm (4th har-

monic of Nd:YAG), 308 nm (XeCl Excimer), 351 nm (XeF Excimer), and 355 nm

(3rd harmonic of Nd:YAG). Additional wavelengths can be derived through Raman

shifting, including 277 nm (248 nm 1st Stokes in H2), and 289 (266 nm 1st stokes

in D2).

Toluene (C6H5CH3) is a single-ring aromatic that is a component of commercial

gasoline fuels at the percent level. The S0-S1(π, π∗) absorption feature extends from

240 nm to 270 nm permitting excitation at 248 nm and 266 nm. The resulting fluo-

rescence emission extends from roughly 260 nm to 400 nm at room temperature, and

redshifts and widens as temperature is increased [74,75]. Toluene photophysics have

been investigated at either high temperature or high pressures by Koban et al. [74]

and Koch [75]. However, additional data at simultaneously high temperature and

pressure is needed to better quantify the regime of engine conditions. In general,

the toluene FQY is highly sensitive to temperature, decreasing by approximately

3 orders of magnitude or more from 300 K to 900 K [75]. As a result, toluene is

often utilized for PLIF measurements of temperature [29, 69, 71], typically in pure

N2 environments. Like most aromatics, the fluorescence signal decreases dramati-

cally in the presence of oxygen due to collisional quenching. The oxygen quenching

not only reduces diagnostic performance through reduced signal-to-noise, but also

complicates the signal interpretation. In general, toluene is a less suitable tracer

for engine studies with high EGR, where the oxygen concentration can vary dra-

matically across the field of view. While such measurements are possible in theory,

the correction for oxygen quenching effects at high temperatures and pressures is an

unnecessary complexity when considering other candidate tracers. Toluene is better

suited for PLIF measurements of temperature for a homogeneous composition field

such as HCCI strategies with low residuals, and early fuel injection [71]. Toluene is

also expected to be a good tracer for gasoline type fuels as the boiling point (B.P.)


of toluene (B.P.=383.8 K) is reasonably similar to that of iso-octane (B.P.=372.4

K)

Biacetyl (CH3(CO)2CH3) is a dione (diketone) that exhibits fluorescence behav-

ior somewhat similar to acetone. Absorption for the first excited state S0-S1 (n−π∗)

and second excited state S0-S2 (n− π∗) extend from 350 nm to 460 nm and 250 nm

to 300 nm, respectively. Near-UV excitation to the second excited state is not appli-

cable to fluorescence-based diagnostics as the second excited state is predissociative,

resulting in negligible fluorescence. Both fluorescence emission (440-520 nm) and

longer-lived phosphorescence emission (480-620 nm) are observed. Phosphorescence

based diagnostics are not considered here based on the desired temporal resolution

of the engine experiments. The fluorescence dependence on temperature, pressure

and composition has been studied at some engine relevant conditions [76], however

available data above 600 K is sparse. Biacetyl does exhibit oxygen quenching, but

to a lesser extent than toluene [70,76]. Rothamer et al. [77] concluded that biacetyl

may be inferior to other available tracers based on comparisons of expected signal

levels and general trends of temperature sensitivity. In addition, only two closely

spaced high-energy excitation wavelengths (351 nm - XeF excimer, and 355 nm -

3rd harmonic Hd:YAG) are readily available, making development of a two-line di-

agnostic variation impractical. Based on these factors, biacetyl was not considered

further for the optimization.

Acetone (CH3COCH3) and 3-pentanone (C2H5COC2H5), are both aliphatic ke-

tones with similar fluorescence behavior. Both exhibit S0-S1 (n−π∗) absorption from

approximately 225 nm to 320 nm, followed by fluorescence from 330 nm to 550 nm.

The near-UV absorption spectrum permits excitation at a number of easily accessi-

bly wavelengths including 248 nm, 266 nm, 277 nm, 289 nm, and 308 nm. The photo-

physics of these ketones have arguably received the most research interest over recent

years, particularly at high temperatures and pressures [1,30,31,33–35,44,66,78–82].

Further discussion of these studies is provided in Chapter 3. Both tracers provide ad-

equate fluorescence signal and temperature sensitivity, although typically less than

toluene (except at high temperatures). One discernable quality between ketones is

the evaporation characteristics. The boiling point of acetone (B.P.= 329 K) is much

2.3. WAVELENGTH OPTIMIZATION 17

lower than the typical gasoline reference fuel iso-octane (B.P.=373 K), indicating

that acetone is not an appropriate selection to accurately track fuel evaporation.

Conversely, 3-pentanone has a boiling point (B.P.=375 K) similar to iso-octane,

making it better suited for accurate fuel mole fraction measurements (additional

studies have shown that improvements over 3-pentanone can still be made ). This

does not exclude acetone completely, as many intended measurement applications

will utilize premixed seeding of pre-vaporized fuels. Given all these characteristics,

acetone and 3-pentanone are the most common selection for quantitative tracer-

based PLIF measurements. Based on the success of previous applications, and the

availability of photophysical data, acetone and 3-pentanone will be further consid-

ered for both single-line and two-line diagnostic optimization below. Additionally,

toluene will be included only in the single-line analysis for comparison.

2.3 Wavelength Optimization

Having narrowed down the list of potential tracer molecules, wavelength selection

can be performed to optimize overall diagnostic performance. The single-shot ran-

dom uncertainty, also referred to as spatial precision, is of particular importance as

this will dictate the minimum degree of stratification that can be resolved with a

given diagnostic scheme. These random uncertainties can be thought of as measure-

ment fluctuation over the imaged region, in the absence of any inhomogeneity. The

measurement precision will be impacted by a number of factors including the signal-

to-noise ratio of the image, the shot-to-shot laser energy profile fluctuations, and

the overall sensitivity of the fluorescence to temperature. In an effort to systemati-

cally account for all potential sources of random uncertainty a detailed uncertainty

analysis was performed. This uncertainty analysis was first applied by Rothamer et

al. [77] to optimize the wavelength selection for a two-line EGR/T diagnostic based

on 3-pentanone. The same general uncertainty analysis is adopted in this study and

is extended to the single-line PLIF scheme, and also to investigate different tracers

for the two-line technique.


2.3.1 Uncertainty Analysis Theory

The temperature and mole fraction measurement precision was determined by con-

sidering the propagation of uncertainties of individual measurement variables. Con-

sider the general case in which an experimental result Y is a function of independent

variable xn:

Y = f(x1, x2, . . . , xn) (2.11)

Equation 2.11 essentially represents the calibration relation for the measured quan-

tity such as Equation 2.4, 2.6 and 2.8. The uncertainty in measuring Y is determined

by the root sum of squared uncertainties for the individual variables [83,84] as shown

in Equation 2.12.

∆Y =

√(∂f

∂x1

∆x1

)2

+

(∂f

∂x2

∆x2

)2

+ . . . +

(∂f

∂xn

∆xn

)2

(2.12)

Here ∆Y is the random uncertainty of the measured quantity Y , and ∆xi is the

uncertainty of each independent variable. For all subsequent calculations these un-

certainties are assumed to be statistically well represented by the standard deviation.

Temperature for the single-line technique is determined through measurement

of the PPs, such that T = T (PPs). Applying the error propagation relation, Equa-

tion 2.12, to this functionality results in Equation 2.13, where ∆PPs is the random

uncertainty of the PPs parameter. As indicated by Equation 2.4, PPs is itself a

function of several measured quantities such that PPs = f(Sf , Scalf , E, P ). Ap-

plying the error propagation relation to PPs results in Equation 2.14. No pressure

terms are included in Equation 2.14 as the pressure is assumed to be constant across

the cylinder and thus does not contribute to the spatial precision of a single-shot

image.

∆T =

√(∂T

∂PPs

∆PPs

)2

(2.13)

∆PPs =

[(∂PPs

∂Sf

∆Sf

)2

+

(∂PPs

∂Scalf

∆Scalf

)2

+

(∂PPs

∂E∆E

)2]1/2

(2.14)


The partial derivatives in Equation 2.14 are determined by differentiating Equa-

tion 2.4, and are given by:

∂PPs

∂Sf

=1

Sf

PPs∂PPs

∂Scalf

= − 1

Scalf

PPs∂PPs

∂E= − 1

EPPs (2.15)

The collection of equations (2.13-2.15) above constitutes the theoretical frame-

work of the uncertainty analysis for the single-line PLIF technique. With these

equations, the diagnostic performance can be assessed over a wide range of exper-

imental conditions, as well as tracer species and excitation wavelengths. However,

the uncertainties of individual variables (∆E, ∆Sf ) still need to be determined.

The random uncertainty in laser energy, ∆E, is caused by shot-to-shot fluctuations

in both total laser energy and profile distribution. They are included as a source

of uncertainty because they are not being directly corrected for within the current

measurement scheme. While it is possible to correct for these laser profile fluc-

tuations on a shot-to-shot basis, the added complexity of a beam profiling system

(beam sampler and camera) and the overall difficulty of an accurate correction make

it prohibitive unless absolutely necessary. Many potential laser sources exhibit en-

ergy fluctuations on the order of ±1% and therefore have less impact on the overall

uncertainty in comparison with the image shot-noise.

Uncertainty estimates of the measured fluorescence signal, ∆Sf , are determined

by modeling the noise characteristics of an intensified CCD (ICCD) camera. Previ-

ous studies [85] have shown that the signal-to-noise ratio of an ICCD camera is well

represented by:

SNRICCD = fracηPCSfgtotsqrtηPCSfg2totFMCP + N2

CCD (2.16)

where SNR is the image signal-to-noise ratio, ηPC photocathode quantum efficiency,

Sf is the number of photons incident at the photocathode [photons/pixel], gtot is

the total photoelectron gain through the intensifier,FMCP is the characteristic noise

factor of the micro-channel plate (MCP), and NCCD is the CCD read and dark noise

[electrons/pixel].


The fluorescence signal per pixel used in Equation 2.16 is determined from the

linear LIF Equation 2.1. The LIF relation requires estimation of a number of physi-

cal parameters such as the laser fluence, probed volume, and solid angle of collection.

The laser fluence, E, is re-written in terms laser energy and beam dimensions as

E = Ep

nplowwhere Ep is the total laser energy, np is the number of pixels traversing

the imaged laser sheet profile, lo is the pixel size in the object plane, and w is the

sheet thickness. The probed volume is estimated based on square of the pixel size

lo and the laser sheet thickness. Finally the solid angle of collection is estimated

based on imaging parameters, as shown in Equation 2.17 where f/# is the imag-

ing f-number and M is the magnification. Substituting all these relations into the

linear LIF equation and simplifying results in Equation 2.18 [70]. In summary, the

single-line measurement uncertainty (precision) can be estimated by solving Equa-

tions 2.13-2.18.

Ω =π

4

1

f/#2

M2

(1 + M)2(2.17)

Sf =Ep

hcν

lonp

[xtrP

kT

]σ(λ, T )φ(λ, T, P, xi)

1

16

(1

f/#

)2M

(1 + M)2(2.18)

Derivation of the uncertainty analysis for the two-line PLIF diagnostic variation

follows a similar path to that shown for the single-line technique above. An in-

depth derivation has been previously presented [77] and will not be covered here

further. The general equations for the two-line uncertainty analysis are presented

in Appendix B for reference. Although the general equations differ, analysis of both

diagnostic variations utilize the same estimates of fluorescence signal, laser stability

and general equipment parameters.

2.3.2 Uncertainty Analysis Parameters

Accurate prediction of fluorescence signal and resulting SNR requires the estimation

of physical parameters of the diagnostic components. A list of excitation laser


wavelengths under consideration is shown in Table 2.1. The corresponding total

laser energy and profile stability used for all simulations is also provided. These

wavelengths were selected based on the absorption bands of the potential tracer

molecules, with an emphasis on turn-key high-energy laser sources. This includes

both fixed laser wavelengths (248 nm, 266 nm and 308 nm), and wavelengths derived

through Raman shifting (277 nm and 289 nm). Additional wavelengths of 332 nm

(XeCl 1st Stokes in N2) and 351 nm (XeF) have been considered in past optimization

studies [77], but were excluded for the current work. Attempts to generate sufficient

332 nm energy proved difficult with the current XeCl excimer (stable resonator).

This is unfortunate as simulations by Rothamer et al. [70] indicate that the 332 nm /

266 nm combination should provide good diagnostic performance. The XeF excimer

output at 351 nm was also excluded as this wavelength resides in the far wings of

most absorption features, and the FQY model predictions at this wavelength are

are not expected to be accurate given the limited experimental data.

Laser energies listed in Table 2.1 represent achievable pump energies and were

selected to be within the bounds of the linear excitation regime as discussed in

Chapter 4. The 266 nm excitation is somewhat high, but linear excitation can

be ensured by increasing the laser sheet thickness. This will reduce the overall

resolution of the system but will not affect the overall diagnostic performance. The

energy profile fluctuations in Table 2.1 are based on actual stability measurements

where available. Profile stability of the 289 nm wavelength was extrapolated from

the 266 nm data based on understanding of the impact of Raman shifting process.

Uncertainty simulations also require photophysical data to both estimate the

fluorescence signal and resulting camera SNR, and also to calculate the partial

derivatives (e.g. ∂T∂PPs

). Absorption cross-section data for all tracers was taken from

Koch et al. [1], and is considered to be well characterized. FQY data is generated

from available FQY models, provided by Koch et al. [75] for toluene, Thurber et

al. [86] for acetone (except at 248 nm, where the Braeuer et al. [87] updated model

was used), and Rothamer et al. [70] for 3-pentanone. These models exist with

varying degrees of refinement and accuracy. The 3-pentanone model has received

the most attention and refinement and is expected to be accurate over a wider range


of conditions. While perhaps less accurate, other models are still very useful in

studying the measurement precision and are able to capture the general uncertainty

trends.

Remaining physical parameters of the optical and imaging systems required for

simulation are listed in Table 2.2. The parameters are representative of realistic

equipment specifications and have been selected to optimize total signal intensity.

The parameters are identical to those used in previous work by Rothamer et al. [70],

as the diagnostic components are the same. Some of these parameters such as the

optical transmission and the solid angle of collection can be difficult to estimate,

and result in some errors in the uncertainty analysis estimates. However, this will

not influence comparison of the relative performance of diagnostic variations.

Table 2.1: Excitation wavelengths, energy and energy stability inputs used for tem-perature and EGR precision calculations

λ [nm] Laser Source Energy [mJ] Energy Stability [±%]

248 KrF excimer 60 1

266 Nd:YAG 4th harmonic 50 4

277 KrF 1st Stokes (H2) 60 2

289 Nd:YAG 1st Stokes (D2) 40 5

308 XeCl excimer 60 1

2.3.3 Single-Line Analysis

Simulations of temperature uncertainty for the single-line technique were performed

over a continuous range of temperature (300-1100 K) and pressure (1-50 bar) for

constant tracer mole fraction. Simulations were performed with 3-pentanone, ace-

tone and toluene for all potential excitation wavelengths listed in Table 2.1. Results

are plotted as contoured color images to permit easy comparison of performance

over the wide range of conditions. In general, these results are not limited to IC en-

gine conditions alone and correspond to any experimental application with constant


Table 2.2: Input parameters used for temperature and EGR precision calculations,same as

Camera Parameters Symbol Value

Camera type Dual-frame ICCD

CCD array size 1024 x 1024

Pixel binning (on chip) 8 x 8

Binned pixel in linear extent np 128

Binned pixel size in object plane lo 0.5 mm

Read Noise NICCD 25 e− per pixel

Photocathode quantum efficiency etaPC 0.20

Total photoelectron gain gtot 13

MCP noise factor FMCP 2.56

Optics Parameters Symbol Value

Lens f-number f/# 1.4

Image magnification M 0.21

Optical transmission ηopt 0.4

Laser Parameters Symbol Value

Sheet width 50 mm

Laser energy EP See table 2.1

Laser profile stability ∆E See table 2.1

Laser sheet thickness w 0.5 mm

Mixture Parameters Symbol Value

Tracer mole fraction in intake air xcaltr 1500 ppm

EGR mole fraction xEGR 50%

tracer mole fraction. Dashed curves in each plot represent bounding engine com-

pression curves, with the top curve corresponding to naturally aspirated HCCI with

high preheat, and the lower curve corresponding to boosted HCCI with minimal

preheat.

Temperature precision results for 3-pentanone are presented in Figure 2.1. All

plots depict a large dynamic range of diagnostic performance, ranging anywhere


from 3 K to 40 K. The thermodynamic conditions of best performance vary for

each wavelength and is related to the relative changes in total fluorescence sig-

nal and temperature sensitivity (∂T/∂PPS) with temperature and pressure. The

diagnostic performance improves with increasing pressure due to increased tracer

number density (constant mole fraction) and hence higher fluorescence signals. The

trends of diagnostic performance with increasing temperature varies for each excita-

tion wavelength, as there is typically a tradeoff between low and high temperature

performance. The shortest wavelength, 248 nm (Figure 2.1a), provides the best

performance at low temperature due to high signal levels and temperature sensitiv-

ity. Conversely, longer wavelengths such as 289 and 308 nm (Figure 2.1d and 2.1e)

perform poorly at low temperatures, but perform well at high temperatures. This

variation in performance demonstrates the utility of the wavelength optimization,

permitting thoughtful selection of excitation wavelength to maximize performance

over a specific range of conditions.

Close investigation of the 3-pentanone performance plots shown in Figure 2.1 in-

dicates that excitation at 277 nm (Figure 2.1c) provides the best overall performance

within the window of engine conditions. This wavelength is a good combination of

low and high temperature performance and is preferred over 266 nm excitation given

the lower laser profile energy fluctuations. In addition, the longer pulse duration of

the excimer versus the Nd:YAG (25 ns and 6-8 ns respectively) reduces the potential

for laser induced damage of windows and fluorescence saturation.

Similar performance plots for acetone are presented in Figure 2.2. The overall

acetone performance at all excitation wavelengths is lower than that of 3-pentanone.

This can be attributed to the lower overall fluorescence signal for acetone resulting

from lower absorption cross-section and FQY in comparison with 3-pentanone [1,75].

This was demonstrated by Koch et al. [75] who measured the absolute FQY for both

acetone and 3-pentanone, and found that the FQY of 3-pentanone is approximately

two times higher than for acetone (for 266 nm excitation at 300 K and 1 bar). At

these conditions the absorption cross-section is approximately equivalent. Overall,

this results in a fluorescence signal that is a factor of two higher for 3-pentanone,

and thus a diagnostic performance that is improved by a factor of√

2 assuming


Temperature Precision [K]0 10 20 30

3

3

3 3

5

5

55

5

8 8 8

8

8

8

8

88

10

10

1010

1010

10 10 10

15

15

1515

151515 15

25

25

25

Pressure [bar]

Tem

per

atu

re [

K]

10 20 30 40 50

400

600

800

1000

Engine Range

(a) 248 nm

5

5

5 55

8

8

8

88 8

10

10

10

10 10

15

15

1515

15

15 15 15

25

252525 25 25

Pressure [bar]

Tem

per

atu

re [

K]

10 20 30 40 50

400

600

800

1000

Engine Range

(b) 266 nm

3

3

33

5

5

55 5

8

8

88 8

10 10 10

10

10

1010 10

15

1515

15 15 15

25

2525 25 25

Pressure [bar]

Tem

per

atu

re [

K]

10 20 30 40 50

400

600

800

1000

Engine Range

(c) 277 nm

8

88 8

10

1010 10

15

1515 15

25

25 25 25

2525 25

Pressure [bar]

Tem

per

atu

re [

K]

10 20 30 40 50

400

600

800

1000

Engine Range

(d) 289 nm

5

5 5 5

10

10 10 10

15

15 15 1525 25 25

252525 25 25

Pressure [bar]

Tem

per

atu

re [

K]

10 20 30 40 50

400

600

800

1000

Engine Range

(e) 308 nm

Figure 2.1: 3-Pentanone single-line PLIF measurement uncertainty estimates oftemperature for potential excitation wavelength pairs. All precision is quoted basedon ±1 standard deviation.


shot-noise limited behavior. In addition, the temperature sensitivity of acetone is

generally lower than 3-pentanone for moderate to high temperatures.

Based on the performance data in Figure 2.2, 277 nm excitation again provides

the best overall performance followed by 248 nm and 266 nm. The overlap in

optimal excitation wavelength for acetone and 3-pentanone is not unexpected given

that they both exhibit generally similar photophysical behavior. There is however, a

large difference in absolute performance between tracers, and as a result, subsequent

single-line engine measurements will primarily utilize 3-pentanone as the ketone

tracer.

For comparison, single-line toluene-based temperature uncertainty simulations

were performed for 248 and 266 nm excitation. Additional wavelengths were omitted

due to little or no absorption for wavelengths longer than approximately 275 nm

(at low to moderate temperature). Several simulation parameters were adjusted

for the toluene study in an effort to make results more realistic. First, the toluene

mole fraction was reduced to 150 ppm to provide equivalent laser attenuation to

the 3-pentanone studies (matched at 1000 K and 20 bar). Second, the total laser

energy was reduced to 30 mJ for both wavelengths to avoid fluorescence saturation

(as described in Chapter 4). Third, the effective camera gain factor was reduced to

avoid detector saturation at the lower temperature conditions. Finally, the bath gas

was changed from air to N2 due to the significant impact of oxygen quenching for

toluene.

The single-line toluene results are given in Figure 2.3. Excitation at 248 nm pro-

vides good performance at low temperatures, but quickly degrades with increasing

temperature due to decreasing signal levels. This behavior highlights the perfor-

mance tradeoff between temperature sensitivity and fluorescence signal. Toluene is

often selected due to its high temperature sensitivity, however this can be detri-

mental under certain conditions due to the accompanying decrease in signal levels.

Toluene excitation at 248 nm is a good example of this, where the temperature sen-

sitivity is so high the fluorescence signal becomes the limiting factor as temperature

is increased. Temperature precision at 266 nm is quite good over the entire test



8

8 8

8 810

10

10

1515

2525

Pressure [bar]

Tem

per

atu

re [

K]

10 20 30 40 50

400

600

800

1000

Engine Range

(a) 248 nm

8

88

1010

10

1515

15

15

15

2525

Pressure [bar]

Tem

per

atu

re [

K]

10 20 30 40 50

400

600

800

1000

Engine Range

(b) 266 nm

88

8 88

1010 10

10 1010

15

1525

Pressure [bar]

Tem

per

atu

re [

K]

10 20 30 40 50

400

600

800

1000

Engine Range

(c) 277 nm

151525

25

25

25

25

25

Pressure [bar]

Tem

per

atu

re [

K]

10 20 30 40 50

400

600

800

1000

Engine Range

(d) 289 nm

10 1015 15 1525

25

2525

2525

Pressure [bar]

Tem

per

atu

re [

K]

10 20 30 40 50

400

600

800

1000

Engine Range

(e) 308 nm

Figure 2.2: Acetone single-line PLIF measurement uncertainty estimates of temper-ature for potential excitation wavelength pairs. All precision is quoted based on ±1standard deviation.


matrix, and specifically within the engine bounds. While the temperature sensitiv-

ity for 266 nm is somewhat smaller than for 248 nm, the signal levels are generally

higher, aided by the absorption cross-section increasing with temperature.

Overall the estimated temperature uncertainty for toluene at 266 nm is superior

to both acetone and 3-pentanone, however this is not the case when oxygen is added

to the bath gas. Simulations with air (not shown) exhibit a dramatic drop off in

performance, well below the performance of 3-pentanone. This shift in performance

is a result of the precipitous drop in toluene FQY due to oxygen quenching. Koban

et. al [88] measured a decrease in FQY of over two orders of magnitude (at 300 K

and 1 bar) when switching the bath gas from nitrogen to air. Because the intended

diagnostic application include both motored engine experiments with nitrogen and

fired experiments in air, toluene was not considered for the single-line PLIF scheme.

Based on the preceding uncertainty analysis, it is concluded that 3-pentanone

excitation at 277 nm is the optimal choice for the single-line scheme in terms of

both temperature precision and application versatility. Subsequently, this tech-

nique was used to investigate the thermal stratification development in a high-load

HCCI engine under both motored and fired operation. Diagnostic validation and

experimental results are presented in Chapter 6. Additional validation experiments

were also performed with acetone to verify the validity of the uncertainty analysis,

and to confirm the predictions of superior performance with 3-pentanone.

2.3.4 Two-line Analysis

An uncertainty analysis of the two-line technique based on Equations B.5 and B.2

was performed to minimize measurement uncertainty for both temperature and EGR

mole fraction measurements. This follows closely with the optimization performed

by Rothamer et al. [70], but is extended to include both 3-pentanone and acetone.

The assumed temperature and pressure matrix, excitation laser specifications (Ta-

ble 2.1), and system parameters (Table 2.2) are equivalent to those used for the

single-line analysis. All wavelength combinations considered utilize 308 nm as the

longer wavelength. It has been found that combinations where both wavelengths are



1 1 1

22 233

35

55

8

88

10

1010

15

1515

25

2525

Pressure [bar]

Tem

per

atu

re [

K]

10 20 30 40 50

400

600

800

1000

Engine Range

(a) 248 nm

55

5

5 5 5

1015

25

Pressure [bar]

Tem

per

atu

re [

K]

10 20 30 40 50

400

600

800

1000

Engine Range

(b) 266 nm

Figure 2.3: Toluene single-line PLIF measurement uncertainty estimates of temper-ature for potential wavelength pairs. Simulations are for an N2 intake stream. Allprecision is quoted based on ± 1 standard deviation.

below 308 nm results in a signal ratio that is not single-valued and complicates the

temperature calibration. Interpretation of the two-line results is somewhat more

complicated than for the single-line. Temperature uncertainty is dictated by the

fluorescence signal from each wavelength, and the sensitivity of the signal ratio to

temperature. Mole fraction uncertainty is dependent on the fluorescence signal from

a single wavelength, the temperature sensitivity of fluorescence at that wavelength,

and the accompanying temperature uncertainty.

Representative uncertainty contour maps of both temperature and EGR mole

fraction for 3-pentanone are presented in Figure 2.4. Again these results are very

similar to those of Rothamer et al. [77], with slight differences arising due to small

differences in simulation parameters. Considering temperature precision first, the

248/308 nm pair provides the best performance at low temperatures but quickly

degrades at higher temperatures due to low signal levels at 248 nm and low ratio

sensitivity. The 277/308 nm pair provides the best overall performance across the

engine range, with the 266/308 nm performing only slightly below. The EGR mole


fraction uncertainties follow a similar trend. The 248/308 nm results in poor perfor-

mance at higher temperatures, while the low temperature performance is compara-

ble to the other combinations. The 277/308 nm pair again provides slightly better

EGR mole fraction performance than 266/308 nm. Based on the combination of

these results the 277/308 nm pair is found to be the optimal wavelength combina-

tion for 3-pentanone. This wavelength combination has been applied successfully in

a number of studies [44,77,89] confirming the uncertainty analysis results.

Analogous uncertainty simulations were performed with acetone as the fluores-

cence tracer to assess any performance benefits. Based on the temperature uncer-

tainty results shown in Figure 2.5, the 248/308 nm combination provides the lowest

temperature uncertainty, followed by 277/308 nm. However, the absolute temper-

ature uncertainty for all acetone wavelength pairs are on average higher than for

3-pentanone. There may be some marginal benefits with acetone at high tempera-

tures, but this is unclear given the inaccuracies of the FQY models. Trends in EGR

mole fraction uncertainty, shown in Figure 2.5, are somewhat in contrast. Here the

277/308 nm combination provides the lowest EGR mole fraction uncertainty, while

248/308 nm is generally the highest. Overall, the EGR uncertainties achieved with

acetone are lower than uncertainties for 3-pentanone and likely results from the

lower temperature sensitivity of the acetone fluorescence. Because of the varying

temperature and mole fraction trends for acetone, the optimal wavelength selection

will depend on the relative importance of either measurements. The 277/308 nm

combination affords a reasonable compromise.

Based on the two-line uncertainty analysis results for all wavelengths and tracers,

the 277/308 nm excitation of 3-pentanone provides the best overall performance

and was used predominantly for the subsequent engine studies. Acetone was also

investigated briefly for the same wavelength combination to validate the uncertainty

results and to assess any high temperature benefits. It is interesting to note that the

optimal 3-pentanone wavelength selections for the single-line and two-line overlap at

277 nm. This fortuitous conclusion means that single-line and two-line techniques

can be performed within the same experimental setup, differing only in the data

processing. This only improves the versatility of the overall diagnostic technique.


Temperature Precision [K]0 10 20 30 40 50

EGR Precision [mole fraction %]0 10 20 30

5

55

5

10

10

10

10

10

10

15

1515

25

2525

50

5050100

100

Pressure [bar]

Tem

per

atu

re [

K]

10 20 30 40 50

400

600

800

1000

Engine Range 3

3

33

5

5

55

8

88

10

1010

15

151525

25

25

Pressure [bar]

Tem

per

atu

re [

K]

10 20 30 40 50

400

600

800

1000

Engine Range

(a) 248 nm / 308 nm

10

10

10

10

1010

15

15

15

15

15

15

25

25

25

50

5010

0

Pressure [bar]

Tem

per

atu

re [

K]

10 20 30 40 50

400

600

800

1000

Engine Range

33

3

5

5

58

88

10

1010

15

1525

Pressure [bar]

Tem

per

atu

re [

K]

10 20 30 40 50

400

600

800

1000

Engine Range

(b) 266 nm / 308 nm

10

10

10

10

10

10

15

15

15

15

15

15

15

15

25

2550

100

Pressure [bar]

Tem

per

atu

re [

K]

10 20 30 40 50

400

600

800

1000

Engine Range

33

3

5

5

5

8

8

10

1015

25

Pressure [bar]

Tem

per

atu

re [

K]

10 20 30 40 50

400

600

800

1000

Engine Range

(c) 277 nm / 308 nm

Figure 2.4: 3-Pentanone two-line PLIF measurement uncertainty estimates of tem-perature (left) and EGR mole fraction (right) for potential excitation wavelengthpairs. All precision is quoted based on ±1 standard deviation.


Temperature Precision [K]0 10 20 30 40 50

EGR Precision [mole fraction %]0 10 20 30

10 10

1515

15

15

15 15

15 15

2525

5050

Pressure [bar]

Tem

per

atu

re [

K]

10 20 30 40 50

400

600

800

1000

Engine Range

3

3

3 3

5

5

5

8

8

8

10

1015

1525

Pressure [bar]T

emp

erat

ure

[K

]

10 20 30 40 50

400

600

800

1000

Engine Range

(a) 248 nm / 308 nm

1010

1515

15

25

25 25 25

25

25

Pressure [bar]

Tem

per

atu

re [

K]

10 20 30 40 50

400

600

800

1000

Engine Range

3

3

3 3 35

5

5

5 5

810

Pressure [bar]

Tem

per

atu

re [

K]

10 20 30 40 50

400

600

800

1000

Engine Range

(b) 266 nm / 308 nm

10

15 151525

25

25 25 25

25

50

Pressure [bar]

Tem

per

atu

re [

K]

10 20 30 40 50

400

600

800

1000

Engine Range

2

2

2 2 2

33

3 3 3

58

Pressure [bar]

Tem

per

atu

re [

K]

10 20 30 40 50

400

600

800

1000

Engine Range

(c) 277 nm / 308 nm

Figure 2.5: Acetone two-line PLIF measurement uncertainty estimates of tempera-ture (left) and EGR mole fraction (right) for potential excitation wavelength pairs.All precision is quoted based on ±1 standard deviation.

Chapter 3

Tracer Photophysics

Accurate knowledge of tracer photophysical parameters, namely the absorption

cross-section and fluorescence quantum yield (FQY), is critical for diagnostic devel-

opment and quantitative tracer-based measurements. Both parameters have been

well studied for aliphatic ketones [1,30,31,33,80,86,87,90,91], but additional mea-

surements are still required to broaden the range of experimental conditions par-

ticularly at simultaneous high temperatures and pressures. For the current work, a

motored IC engine is employed as a test stand for measurements of FQY at engine

relevant conditions.

The near-UV absorption spectrum of the first excited singlet state of both ace-

tone and 3-pentanone ranges from 225 to 320 nm, and is consistent with many

cabonyl-containing compounds. Because of the high density of rovibronic transi-

tions, the absorption feature is broadband (except at very low temperatures) and

depends only on temperature and wavelength. Initial absorption measurements fo-

cused on room temperature conditions or below [92–96] and were later extended

to elevated temperatures relevant for engine experiments [1, 30, 86]. Koch et al. [1]

presents particularly useful absorption results in the form of gaussian fit coefficients

for accurate representation of absorption of acetone and 3-pentanone as a function

of wavelength and temperature. These fitting parameters were used for all data

processing in this work, and are presented in Appendix A. For both ketones the ab-

sorption generally increases with temperature and the spectrum red-shifts to longer

33

34 CHAPTER 3. TRACER PHOTOPHYSICS

wavelengths [1, 86].

The resulting fluorescence spectrum of acetone and 3-pentanone ranges from

350-550 nm respectively. The excited state lifetime is dominated by fast intersys-

tem crossing (S1 → T1) to the first excited triplet, limiting the overall fluorescence

quantum yield. The fluorescence has been shown to strongly depend on tempera-

ture, pressure and to a lesser extent composition. These functional dependencies

of fluorescence are a result of the product of the absorption cross section and the

fluorescence quantum yield (FQY). It is often easier to think of these quantities in-

dependently. In general, the FQY decreases with temperature (especially at shorter

wavelengths), increases with pressure (up to a high-pressure limit), and decreases

with decreasing excitation laser wavelength. These trends can be traced back to

the non-radiative decay rate of the excited singlet which has been found to increase

with excess vibrational energy in the excited state [75,78]. The FQY of ketones has

been investigated by a number of researchers [30–32,35,86] and has mostly focused

on FQY variation with independent changes in temperature or pressure (not simul-

taneous). More recent studies have expanded the measurement domain to include

simultaneous high temperature and pressure conditions [33, 34, 87, 90]. Despite nu-

merous FQY studies, the collection of data is still insufficient to accurately predict

the ketone FQY behavior, especially at elevated temperatures and pressure relevant

for engine experiments. This is especially problematic when investigating kinetically

limited combustion systems such as HCCI, where measurement of temperature and

composition distributions near TDC are critical. The following sections will in-

clude discussion about the measurement of FQY in a motored engine in an effort to

characterize the FQY dependence with temperature for a range of relevant engine

conditions.

3.1 FQY Measurements in a Motored IC Engine

A single-cylinder optical IC engine can be utilized as a compression machine. It

essentially represents a closed system reactor with time-varying temperature and

3.1. FQY MEASUREMENTS IN A MOTORED IC ENGINE 35

pressure. With sufficient optical access the IC engine can be used to study tracer

photophysics at conditions relevant for the study of HCCI engine operation. Al-

though the thermodynamic in-cylinder conditions are not as easily characterized as

in a shock tube, rapid compression machine, or steady flow reactor, it is possible

to use the engine facility as a test bench for a wide range of experiments including

chemical kinetics [97–100] and photophysics [70, 80, 101]. Engine based measure-

ments have the added benefit of fast data acquisition of up to 20 Hz (2400 RPM

engine speed) allowing for repeated measurements and cycle averaging. In addition,

the residence time at high temperature within the engine are typically much shorter

than can be achieved in steady flow reactors and reduces the likelihood of pyrol-

ysis and decomposition. This makes measurements at temperature extremes more

feasible and allows direct characterization of engine conditions.

3.1.1 Measurement Technique

In the current study, two different optical engines, both located at the Combustion

Research Facility of Sandia National Laboratory, were used to acquire ketone FQY

data. The specifics of each engine are described in detail in Chapters 5-6 and rele-

vant engine parameters are shown in Table 5.1 and Table 6.1. Engine A, presented

in Chapter 5, has a geometric compression ratio of 12:1 and imaging access limited

to 24 bTDC by the piston position. Engine B, presented in Chapter 6, has a higher

geometric compression ratio of 14:1 and imaging access through TDC permitting

data acquisition at higher temperatures and pressures. Intake pressure was held

constant at 1 bar for all tests as subsequent engine studies are focused on naturally

aspirated conditions. In each engine fluorescence images were acquired at various

times during the compression stroke to access a range of pressures and temperatures.

Similar measurements were repeated for a range of intake temperatures to determine

the relative signal dependence on temperature for a given crank angle. In the ab-

sence of heat transfer variations, measurements at each crank angle correspond to a

constant pressure. In reality, small pressure variations are seen near TDC as intake

temperature is increased due to increasing heat transfer. However, these affected


image times reside in the high pressure limit [75] where little variation in FQY with

pressure is observed. Engine measurements with constant intake temperature but

varying intake pressure (not shown) confirm the minimal influence of pressure on

FQY at crank angles near TDC. As a result, measurements at each crank angle are

assumed to be at constant pressure, with all reported values corresponding to the

average pressure.

The relative data was converted to absolute FQY through acquisition of reference

images at thermodynamic conditions where the FQY is already well characterized.

These reference images were acquired near bottom dead center (BDC) where the

pressure is effectively 1 bar, and the temperature can be well estimated [102]. The

reference conditions were chosen to take advantage of previous absolute ketone FQY

data acquired in a flowing cell for a range of temperatures and 1 bar pressure [31,35].

The calibration to absolute FQY is represented in Equation 3.1, where φ is the FQY,

S is the measured fluorescence signal, P is the measured pressure, T is the estimated

temperature, and σ is the absorption cross section at the corresponding wavelength

and temperature. The ref subscript denotes the references images with known

conditions and FQY.

φ(T, P, xi) =S

Sref

Pref

P

T

Tref

σref (Tref )

σ(T )φref (Tref , Pref , xi) (3.1)

Equation 3.1 was derived by ratioing the fluorescence signal from the data and

reference image given by the linear PLIF relation, Equation 2.1. The laser energy,

probed volume, and collection efficiency were all constant between data and refer-

ence condition, and are eliminated by the ratio. In addition, because the mixture

composition is constant throughout compression (in the absence of chemical reac-

tion), a measurement of the exact tracer seeding level is not required and does not

represent a source of error for the technique. This is contrary to flowing cell mea-

surements where the tracer number density is a dominant source of error [75, 79].

Based on this, all terms on the right hand side of Equation 3.1 are known, measured

or estimated, and thus the absolute FQY can be determined.

The specific experimental setups are presented in more detail in Chapters 5-6,

3.1. FQY MEASUREMENTS IN A MOTORED IC ENGINE 37

and was nearly identical for both engines. The in-cylinder pressure was measured in

each engine using a high-speed pressure sensor and recorded at 1/4 CA resolution

and averaged for 50-100 consecutive engine cycles. A premixed fueling system lo-

cated upstream of the intake surge tank was utilized to ensure a truly homogeneous

in-cylinder tracer distribution. All experiments were performed with both N2 and

air bath gases to study the impact of oxygen quenching.

Intake temperatures ranging from 30-205C were used to study the FQY depen-

dence on temperature as described above. The in-cylinder core gas temperatures

during compression were determined by first calculating the in-cylinder temperatures

at BDC. Temperatures at BDC for Engine A were estimated based on GT-Power

engine simulations tuned to match the measured pressure trace. Temperature at

BDC for Engine B were calculated using methods previously developed for that fa-

cility [102]. Finally, the in-cylinder core gas temperatures during compression were

calculated assuming adiabatic compression of the measured pressure trace with vari-

able specific heats recalculated at each time step. This calculation method indirectly

accounts for heat transfer effects through the measured pressure trace, but assumes

an adiabatic core region consistent with the interrogation region of the laser. The

thermodynamic data used to calculate mixture gamma was taken from the ther-

modynamic database employed in the Lawrence Livermore National Laboratory

(LLNL) iso-octane chemical kinetic mechanism [103].

Engine-based FQY measurements were performed for excitation wavelengths of

277 and 308 nm based on the detailed uncertainty analysis of Chapter 2. Laser

excitation at 277 nm was generated by Raman shifting the output of a 248 nm KrF

excimer in H2 (1st Stokes), while the 308 nm excitation was provided by a XeCl

excimer laser. The laser energy fluctuation was verified to be less than 1.5 % con-

sistent with the constant laser energy assumption implicit in Equation 3.1. Pump

laser energies were selected to be in the linear regime and are within the limits

set in Chapter 4. In addition, all experiments have been repeated with laser en-

ergies decreased by as much as a factor of 4 with minimal variation in processed

FQY results. The fluorescence signal was imaged using an intensified CCD camera

(PIMAX2-1003) equipped with a 85 mm f/1.4 glass lens. No additional collection


filter was used as the glass lens sufficiently rejected all scattered laser light. The

measured fluorescence signal is thus averaged over the entire fluorescence bandwidth,

although no correction for the wavelength dependent camera quantum efficiency has

been performed.

Three separate images sets were required for data processing at each crank angle.

First, background images were acquired in the motored engine with laser excitation

on but without tracer seeding to correct for dark current accumulation and any

fixed-pattern background signal. The tracer seeding system was then turned on, and

allowed to reach steady-state before additional data acquisition. Next 50 reference

(flat-field) images were acquired followed by 50 data images at the selected timing.

The reference and data images were acquired with minimal delay between sets to

further ensure minimal laser energy drift. All images and pressure measurements

were averaged over the 50 cycles prior to subsequent data processing.

After background correction, the data and reference images were corrected for

laser attenuation along the propagation direction assuming a Beer’s law dependence.

For this correction the absorption cross-section was calculated at the correspond-

ing core image temperature using the gaussian fit data in Appendix A. Finally a

spatially averaged signal was calculated over a subregion of the data and reference

images, and used as inputs in Equation 3.1. The FQY results were found to be

insensitive to the location of the averaging subregion (tested regions near entrance,

exit, center, right, left and total region), indicating that the influence of attenuation

is small and that there was no preferential variation in results based on spatial loca-

tion in-cylinder. Absolute uncertainty of these engine-based FQY measurements is

estimated to be ±6% based on error propagation analysis. This uncertainty is domi-

nated mostly by uncertainty in the in-cylinder temperature calculations required for

data processing. The following sections outline the results obtained for 3-pentanone

and acetone over the range of conditions tested.

3.2. 3-PENTANONE PHOTOPHYSICS 39

3.2 3-Pentanone Photophysics

Representative 3-pentanone absolute FQY results from both engine A and B are

shown in Figure 3.1a for a constant pressure of 12 bar in a nitrogen bath gas. Good

agreement in the FQY measurements is observed for the two engines in the nar-

row region of temperature overlap. Measurement agreement between engines was

typically within 5-7%. The consistency in the results from both engines is encour-

aging given the differences in facilities and demonstrates the robustness of the mea-

surement technique. The multiple data points for Engine B represent experiments

completed with varying laser intensities, slightly varying engine conditions, and

spanning several months in time. The low scatter of these repeated measurements

further demonstrates the consistency of the technique and results. The FQY mea-

surements from Engine A are nearly identical to those previously used by Rothamer

et al. [70] as targets for re-optimization of the 3-pentanone FQY model originally

formulated by Koch et al. [75, 104]. The remaining discussion will focus on the

higher temperature and pressure results from Engine B as these represent a larger

deviation from the parameter space of other studies.

Instead of using the FQY measurements as model optimization targets, simple

quadratic fits have been generated at each image timing (pressure). This method

is thought to be more accurate than model optimization, particularly when recent

studies have demonstrated that current FQY model functionality cannot accurately

predict trends over an extensive range of conditions and wavelengths [33, 59, 87].

While the FQY model can be optimized to match these wavelengths, pressures,

and temperatures the accuracy at other conditions is sure to be sacrificed. How-

ever, given that the quadratic fits have no physical significance, extrapolation to

conditions outside the fitting range was avoided.

Quadratic fitting results are shown in Figure 3.1a for 12 bar total pressure, and in

the compiled set of image timings in Figure 3.1b where each curve represents a differ-

ent image timing and thus pressure. The expected trends of FQY with temperature

can be seen in Figure 3.1b where the FQY decreases with increasing temperature.

The increase in FQY with increasing excitation wavelength is also captured. Finally


the influence of total pressure can be seen for the lower temperature images and is

indicated by the slight translation of curves to higher FQY as pressure is increased.

This is mostly seen for the 5-12 bar image sets, as higher pressures reside in the

high-pressure limit as indicated by [31]. Beyond this point there is good overlap be-

tween curves of increasing pressure, indicating that there is little influence of bath

gas total pressure when above 12-18 bar. Experiments with air bath gas exhibited

nearly identical trends with temperature. In general, there was a slight decrease in

the absolute FQY values consistent with the effect of oxygen quenching to reduce

FQY. All fitting results for the 3-pentanone FQY data are presented in Appendix A

and are accompanied by the range of applicable temperatures and pressures.

600 650 700 750 800 850 900 950

2

4

6

8

10

x 10−4

Temperature [K]

Abs

olut

e F

QY

Engine AEngine BData Fit

277 nm

308 nm

P=12 bar3−PentanoneN

2 Bath

(a)

500 600 700 800 900 1000 1100 12000

0.2

0.4

0.6

0.8

1x 10

−3

Temperature [K]

Abs

olut

e F

QY

305° 5bar320° 8bar330° 12bar340° 18bar345° 22bar350° 26bar355° 28bar360° 29bar

308 nm

277 nm

3−PentanoneN

2 Bath

(b)

Figure 3.1: Absolute FQY of 3-pentanone in nitrogen at 277 nm and 308 nm,measured under motored engine conditions. Each curve represents experiments ata given image timing (pressure) for a range of intake temperatures.

The absolute accuracy of the engine FQY measurements is dominated primar-

ily by the accuracy of the in-cylinder temperature calculations that relies on the

assumption of an adiabatic core region. Previous in-cylinder temperature measure-

ments using TDL absorption sensors [105–107] do provide some absolute tempera-

ture measurements but have not been refined to the extent that they can answer the

question of adiabaticity in the engine core. Past imaging studies do indicate that

thermal stratification does convect into the core due to convection and heat transfer

3.3. ACETONE PHOTOPHYSICS 41

in the near-wall region [71,108], thus indicating some degree of non-adiabatic behav-

ior. However this non-adiabatic behavior will likely shift the absolute FQY curves

with temperature, while maintaining the overall slope [71]. While this does result in

some inaccuracy for absolute temperature measurements, the degree of stratification

(related to the slope of the FQY curves) is the primary focus of the HCCI studies

here and should be well preserved. The accuracy of these measurements can further

be tested by comparing the motored engine FQY results with applicable FQY mea-

surements made in a flowing test cell. Cheung et al. [90] have recently completed

FQY measurements of 3-pentanone for excitation wavelengths of 248, 266, 277 and

308 nm from 300-750 K and 0-20 bar. While these experimental conditions are on

the low temperature extreme of the engine measurements, they do provide some

basis for comparison. Figure 3.2 presents a comparison of the engine FQY data

with measurements by Cheung et al. [90] for a total pressure of 4.5 bar in nitrogen.

The agreement between the measurement techniques is quite good, and well within

the quoted measurement uncertainty of ±7% for the Cheung et al. [90] data. Un-

fortunately higher temperature data (>800 K) is not available. Nevertheless, this

limited comparison does confirm the accuracy of the lower temperature engine FQY

measurements.

3.3 Acetone Photophysics

Similar engine FQY measurements were performed for acetone in both Engine A

and B, utilizing an identical technique and experimental setup with only a change

in the seeded tracer. Acetone FQY measurements are shown in Figure 3.3a at a

total pressure of 8 bar in air. The range of test conditions for Engine A is more

limited for the acetone experiments, however excellent agreement is again evident

where temperatures coincide. The acetone data was found to be well represented by

linear fits and the resulting fit parameters are presented in Appendix A. The linear

acetone FQY curves at each crank angle are presented in Figure 3.3b. As with 3-

pentanone, the acetone curves show the expected trend in FQY with temperature,


550 600 650 7004

5

6

7

8

9

10

11x 10

−4

Temperature [K]

Abs

olut

e F

QY

EngineCell − Cheung et al.Data fit

P=4.5 bar3−PentanoneN

2 Bath

277 nm

308 nm

Figure 3.2: Comparison of absolute FQY results from motored engine and flowingcell

wavelength and pressure. Acetone exhibits stronger pressure dependence at 277

nm in comparison with 3-pentanone as indicated by the larger spacing between

consecutive lower pressure FQY curves. The absolute FQY for 3-pentanone is found

to be higher than acetone at both wavelengths over the entire temperature range.

In addition the slope of the FQY curves is generally larger for 3-pentanone than

for acetone. Experiments performed with acetone in air again showed a decreased

magnitude of FQY, and a modest deviation in slope.

Only one applicable fundamental acetone FQY study at coincident elevated tem-

perature and pressure is available for comparison. Loffler et al. [33] acquired relative

acetone signal data for 248 and 308 nm excitation at 300-750 K and 1-20 bar, nor-

malized by the fluorescence signal at room temperature and pressure for constant

tracer number density. The relative 308 nm data was converted to absolute FQY

using known absorption cross section data and absolute FQY data at ambient con-

ditions [32]. The converted Loffler et al. [33] data are shown in Figure 3.3a in

comparison with engine FQY measurements at the same gas conditions. Similar to

3-pentanone, there is good agreement between the engine and cell FQY data for

acetone at 308 nm, well within the quoted 6% uncertainty for the Loffler et al. [33]

3.4. FQY MODEL COMPARISONS 43

data. Although no higher temperature cell data is available, this does confirm the

accuracy of the moderate temperature engine FQY measurements of acetone.

650 700 750 8002

3

4

5

6

7x 10

−4

Temperature [K]

Abs

olut

e F

QY

Engine AEngine BLöffler et al.Data Fit

277 nm

308 nm

P=8 barAcetoneAir Bath

(a)

500 600 700 800 900 1000 1100 12001

2

3

4

5

6

7

x 10−4

Temperature [K]

Abs

olut

e F

QY

305° 4bar320° 8bar330° 12bar340° 18bar345° 22bar350° 25bar355° 28bar360° 29bar

308 nm

277 nm

AcetoneAir Bath

(b)

Figure 3.3: Absolute FQY of acetone in nitrogen at 277 nm and 308 nm, measuredunder motored engine conditions. Each curve represents experiments at a givenimage timing and pressure for a range of intake temperatures

3.4 FQY Model Comparisons

In conjunction with experimental investigations of tracer photophysics, significant

research efforts have focused on the development of simplified models for accurate

prediction of absolute FQY dependencies. Photophysical models are particularly

helpful when developing new tracer-based diagnostic strategies that are optimized

for specific experimental conditions as was shown in Chapter 2. In addition, these

models provide useful insight into the key processes dominating energy transfer for

large complex molecules like ketones and aromatics. The first comprehensive photo-

physical model for acetone was proposed by Thurber et al. [86]. The semi-physical

model is based on excitation and multi-step decay of an ”average” molecule, simpli-

fying the need to model the complicated molecular energy distributions of the ground


and excited states. The model considers essential energy transfer mechanisms in-

cluding intramolecular non-radiative decay (combining intersystem crossing, internal

conversion and photodissociation), vibrational relaxation, and electronic quenching

of oxygen. The model was originally tuned to match experimental FQY data at

either elevated temperature at 1 bar, or elevated pressure at room temperature and

has been shown to accurately predict the behavior at these conditions [86]. Braeuer

et al. [87] expanded the measurement parameter space by measuring relative FQY at

248 nm for concurrent high temperatures and pressures ( 300-700 K and 1-20 bar).

Here comparison with the initial Thurber model indicated that the pressure-related

FQY increase was over-predicted by the model, and new rate parameters were sug-

gested. However the modeling work of Braeuer et al. [87] only included data at 248

nm excitation, and would likely not be as reliable at longer wavelengths.

The acetone photophysical model has since been adapted for 3-pentanone by

Koch et al. [75,104], using a similar formulation but with re-optimized rate parame-

ters to better match 3-pentanone behavior. As with acetone, the initial 3-pentanone

model tuning was based on FQY data at either high temperatures or high pressures.

Subsequent model comparisons with FQY data at simultaneous high temperature

and pressure [34,70,80] exhibited similar trends, but also highlighted errors in model

predictions for conditions far outside the original tuning range. Rothamer et al. [44]

later refined this model to better match 3-pentanone fluorescence behavior at 277

and 308 nm characterized in an IC engine. This refined 3-pentanone FQY model has

been successfully used for quantitative two-line PLIF data calibration to measure

temperature and composition in HCCI engines [44, 89]. Most recently, Cheung et

al. [90] have further refined the 3-pentanone FQY model using the most compre-

hensive set of experimental data, and includes both flowing cell and engine-derived

FQY data.

Collectively, modeling efforts for both ketones have improved the fundamental

understanding of FQY dependencies, however additional measurements and model-

ing refinements are required to expand the measurement domain and improve model

accuracy. Comparisons between the preceding engine FQY data and available mod-

els have been completed here to further elucidate current model performance at high


temperatures and pressures.

3.4.1 3-Pentanone Modeling

Comparison of engine-based 3-pentanone FQY measurements (quadratic data fits)

and available model simulations are provided in Figure 3.4a. Models derived by

Koch [75], Rothamer [44] and Cheung [90] have been included. In addition to

an absolute comparison, normalized FQY curves are presented in Figure 3.4b to

better access the relative slope which is important when considering measurements

of stratification. The absolute and normalized FQY data in Figure 3.4 is best

predicted by the Cheung model, followed by the Rothamer and Koch models. The

superior performance of the Cheung model is likely a result of the extensive FQY

database used for model optimization. This agreement is particularly impressive

given the wide range of excitation wavelengths (248-308 nm) included in the Cheung

model development. Despite small differences in absolute magnitude, the Chueng

model accurately predicts the normalized slope of FQY with temperature. As a

result, the Chueng model can be used for direct image calibration when performing

stratification measurements where absolute accuracy is not critical.

The Rothamer model captures general 3-pentanone FQY trends, but because

the initial model tuning at 277 and 308 nm only considered temperatures up to 800

K the accuracy is expected to degrade outside this range. The Rothamer model has

been successfully employed for data calibration [70, 89] at the moderate tempera-

tures and pressures considered during model tuning (300-800K, 1-12 bar). Similarly,

inaccuracies in the Koch model arise from the limited set of FQY data available

(asynchronous high temperature and pressure) during initial model development.

Although the Koch model captures the general trends and could be used for the-

oretical diagnostic development and optimization, it is not well suited for direct

image calibration.

The FQY comparisons in Figure 3.4 also provide insights into future model

refinements. In general the absolute FQY is under-predicted by both the Cheung

and Rothamer model, likely indicating that the impact of vibrational relaxation is


under-predicted or the non-radiative decay rate is over-predicted for this range of

conditions. Conversely the over-prediction of absolute FQY by the Koch model is

evidence of either an over-predicted vibrational relaxation or under-predicted non-

radiative decay rate.

277 Eng. 277 Koch 277 Rothamer 277 Cheung 308 Eng. 308 Koch 308 Rothamer 308 Cheung

850 900 950

0.1

0.2

0.3

0.4

0.5

Temperature [K]

Abs

olut

e F

QY

[10

−3]


2

(a)

850 900 9500.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

1

Temperature [K]

Nor

mal

ized

FQ

Y


2

(b)

Figure 3.4: Comparison of engine FQY data derived from quadratic fits and FQYmodel simulations. (a) Absolute FQY, (b) Normalized FQY for better comparisonof slope.

3.4.2 Acetone Modeling

A similar comparison between engine measurement and model is presented in Fig-

ure 3.5 for acetone. Simulation results for the original Thurber model [79], and

the refined Braeuer model [87] have been included. Here the absolute FQY is over-

predicted by all models, while the normalized slope is under-predicted. This is con-

sistent with the observations by Braeuer [87], who noted that the original Thurber

model over-predicted the relative importance of vibrational relaxation, resulting in

higher calculated FQY at high temperatures as pressure is increased. The impact of

model adjustments by Braeuer are not as apparent in Figure 3.5a for longer wave-

lengths. This is because the non-radiative decay rate in the Braeuer model was


altered for higher excess energies only (due to 248 nm excitation) and does not have

much impact on longer wavelengths. The overall deviation between acetone model

predictions and measurement is not unexpected given the limited degree of acetone

model refinement in comparison to 3-pentanone. Although no model improvements

are suggested here, the engine-based FQY measurements in conjunction with other

studies [33,87] provide an expanded database for future model refinement.

277 Eng. 277 Thurber 277 Braeuer 308 Eng. 308 Thurber 308 Braeuer

850 900 950 10000.2

0.25

0.3

0.35

0.4

0.45

0.5

0.55

Temperature [K]

Abs

olut

e F

QY

[10

−3]

P=18 barAcetoneN

2

(a)

850 900 950 1000

0.55

0.6

0.65

0.7

0.75

0.8

0.85

0.9

0.95

Temperature [K]

No

rmal

ized

FQ

Y

P=18 barAcetoneN

2

(b)

Figure 3.5: Comparison of engine FQY data derived from linear fits and FQY modelsimulations. (a) Absolute FQY, (b) Normalized FQY for better comparison of slope.

The preceding discussion demonstrates the utility of engine-based FQY mea-

surements as an alternative to fundamental flowing cell measurements. The close

agreement between engine and cell FQY data confirms the accuracy of the mea-

surement despite some uncertainty in the calculated in-cylinder temperature. Addi-

tional comparisons of engine data with FQY model predictions indicate that most

models predict general trends, however only a few provide sufficient accuracy to

be considered for direct image processing. Based on the success of past studies,

the Rothamer 3-pentanone model has been employed for data calibration of HCCI

engine measurements at moderate temperatures and pressures encountered in en-

gine A (Chapter 5). For the higher temperatures and pressures achieved in engine


B HCCI experiments (Chapter 6), direct FQY data fits for 3-pentanone and ace-

tone are used for data processing. The accuracy of these methods will be discussed

further for each application.

Chapter 4

Fluorescence Saturation

4.1 Introduction

A majority of PLIF strategies, including those presented in Chapter 2, assume lin-

ear fluorescence behavior. This implies that the excitation laser fluence (energy

per unit area) is sufficiently low such that the fluorescence signal is proportional to

laser energy. Operation in this regime is desirable as it reduces the complexity of

signal interpretation, particularly in comparison with intermediate excitation (be-

tween linearity and saturation). At high laser fluences fluorescence saturation can

occur due to substantial ground state depopulation. At these conditions the laser

absorption rate dominates the state to state energy transfer, resulting in a fluores-

cence signal that is independent of laser power and electronic quenching rates. As a

result, saturated LIF has been used to measure the concentration of minor species

such as OH, NO, CH, CN, C2 and NH [109–113] without substantial knowledge of

quenching rates.

Saturated LIF measurements are less common for seeded organic tracers such as

ketones and aromatics. Complete saturation is difficult to achieve for these species

due to the low absorption cross-sections associated with the symmetry-forbidden

transition of the carbonyl functional group. However, knowledge of the energy

threshold of non-linear behavior is particularly important for diagnostic development

49

50 CHAPTER 4. FLUORESCENCE SATURATION

as the threshold will limit either the diagnostic performance or minimum spatial

resolution that can be achieved. This chapter investigates the threshold of non-

linear fluorescence behavior for common tracers including acetone, 3-pentanone and

toluene at typical excimer excitation wavelengths of 248, 277 and 308nm. Although

toluene is not used for any PLIF diagnostics in the current work, it is included here

for completeness. Experiments were performed over a range of total pressures, for

both air and nitrogen bath gases to investigate the impact of vibrational energy

transfer and electronic quenching on saturation. The study highlights the 10% non-

linear threshold and sets bounds for peak laser intensities that result in linear LIF

excitation.

4.2 Experimental Approach

Saturated LIF can be studied by either varying the laser energy for fixed beam

dimensions, or by varying the beam dimensions (focusing) at constant energy. While

both techniques have merit, the focused beam technique will be used exclusively.

By focusing the laser beam to a waist inside a test cell, each acquired fluorescence

image contains data over a continuous range of laser fluences along the propagation

direction. This reduces the time for data acquisition and makes parametric studies

of tracer partial pressure, and total pressure more manageable. This technique was

first used by Petersen et al. [114] to study the saturation of 3-pentanone at 266nm

excitation. Petersen observed that the onset of fluorescence saturation occurs at

lower laser fluences than previously thought, motivating additional studies.

4.2.1 Optical Setup

The experimental setup used to study fluorescence saturation is shown in Figure

4.1. Laser excitation at 248nm and 308nm were provided by a KrF and XeCl

excimer laser respectively (both were Lambda Physik CompPexPro 102). The 277

nm excitation corresponds to the 1st Stokes Raman shift of 248 nm in H2 and

was generated by passing the KrF output through a high-pressure H2-filled Raman

4.2. EXPERIMENTAL APPROACH 51

cell (not shown). The pump laser beams were focused with a 150 mm cylindrical

fused silica lens and then passed through the test cell. Relevant specifications for all

excitation wavelengths are shown in Table 4.1. The relative laser energy fluctuations

were monitored by sampling the beam with a fused silica wedged beam sampler

located upstream of the test cell. The energy of the partial reflection was measured

by temporally integrating (via Tektronics TDS 7104 scope) the signal from a high

speed photo-detector (Thorlabs DET210). The absolute laser energy was calibrated

before each test run using a pyroelectric energy meter (Ophir PE50-BB). Each

wavelength was tested individually at all desired conditions before switching delivery

optics for a subsequent wavelength.

The large aperture test cell (152 mm long, 114 mm x 114 mm square cross-

section) is a custom design, fabricated from aluminum (6061-T6) with a maximum

pressure rating of 8 bar. Optical access in the test cell is provided by three fused

silica windows (58mm clear aperture, 12.5mm thick), two opposed for line of sight

laser access, and one orthogonal for imaging access. The static test cell is connected

to a vacuum and filling assembly that evacuates and fills the cell with tracer and

bath gas before each experiment. To generate a specific mixture, the evacuated cell

is first filled monometrically with tracer vapor to the desired partial pressure, before

being diluted with bath gas to the final total pressure. Sub-atomospheric pressures

were monitored with an isolated MKS Baratron (0-1000 torr), while pressures above

atmospheric were monitored with a Setra 280E pressure transducer (0-100 psia).

The induced fluorescence was imaged using an intensified CCD camera (Prince-

ton Instruments PIMAX2:1003) equipped with either a 50 mm f/1.2 lens (ketones)

or a 105 mm f/4.5 UV Nikkor lens (toluene) depending on the fluorescence emission

band of the tracer being tested. The images were binned 4x4 prior to readout, re-

sulting in a pixel size in the image plane of 0.255 mm and 0.277 mm for the ketone

and toluene experiments respectively. Black paint applied to the rear internal cell

wall minimized the impact of reflected fluorescence signal and resulted in an insignif-

icant background signal. No camera filters were used for the ketone experiments as

the glass camera lens sufficiently attenuated any scattered laser light. A band-pass

filter was used for the toluene experiments to reject elastically scattered excitation


at 248 nm. The excimer lasers and camera controller were syncronized using a delay

generator (SRS DG535) to ensure that the laser pulse was centered in the exposure

time.

P

Tracer Vapor

N2 / Air

Vacuum

ICCD Camera

Beam Profiling Camera

Photodiode

Integrating Sphere

Test

Cel

l

Focusing OpticsTranslation Stage

Excitation Laser

248 / 277 / 308nm

Figure 4.1: Experimental setup for measurement of tracer saturation intensity

4.2.2 Data Acquisition

For each experimental condition, the test cell is first evacuated and 50 background

images are acquired with laser emission but without tracer present. These images

are averaged and used to correct for dark signal accumulation, any analog to digital

offset, and any fixed pattern background noise. The cell is then monometrically

filled with tracer vapor to the desired partial pressure, followed by dilution gas to

the desired total pressure. A sufficient time delay between filling and data image

acquisition is used to ensure proper mixing. Comparison of saturation results using

the filling procedure described above, and those using a homogeneous premixed

mixture of tracer and diluent show no difference. This confirms that no significant

error is induced when preparing mixtures directly in the test cell. After mixture

preparation and mixing delay, 50 data images are acquired with the focused beam

traversing the cell. Finally, the focusing lens is removed, and 50 flat-field images

are acquired. These flat-fields provide an unsaturated (linear) reference image that


corrects for laser absorption and any inhomogeneities in the image. All image sets

are averaged before data processing. Representative background corrected flat (top)

and data (bottom) images are shown in Figure 4.2a. The effects of saturation are

represented in the data image by the darkened region towards the right side of the

bottom image and results from the ground state depopulation. The location of

the beam focus was adjusted horizontally in the test cell to ensure that the input

region (left side of image) was in the linear fluorescence regime. This ensures that

the resulting saturation profile originates in the linear regime. The linearity of the

input region was confirmed by matching the fluorescence signal of the data and flat-

field at the beam input (after correcting for the 8% reflection loss of the focusing

lens).

Fluorescence saturation profiles were generated by first ratioing the background-

corrected data and flat images. An axial 1-D profile was then generated by summing

20 horizontal line profiles centered around the vertical beam center. This profile

was then normalized to unity on the beam input side (left) where the data image is

known to be in the linear regime. A typical saturation profile is shown in Figure 4.2b,

and represents the fractional deviation from linearity along the beam propagation

direction. To convert this profile into more meaningful saturation data, the beam

width as a function of axial distance must be determined in order to calculate the

variation in laser fluence.

4.2.3 Beam Width Measurements

Beam width measurements were performed using a CCD-based beam profiling sys-

tem depicted in Figure 4.1. The system consists of a beam sampler (4 fused silica

wedge), a profiling CCD camera (Spiricon UBS-L230), and a linear translation stage.

The beam sampling wedge is positioned downstream of the focusing lens, and pro-

vides a partial surface reflection of the incoming beam that is directed towards the

camera. The reflected beam was then passed through a series of reflective neutral

density filters and was imaged directly on the CCD chip. Careful selection of the

ND filters ensured that the readout signal was sufficiently high but not saturated.


[mm]

[mm

]

10 20 30 40 50 60

10

20

30

40

50

60

(a) Fluorescence Images

0 10 20 30 40 50 600.5

0.6

0.7

0.8

0.9

1

1.1

Propagation Distance [mm]

Rel

ativ

e S

ign

al [

a.u

.]

(b) Corrected Profile

Figure 4.2: (a) Representative fluorescence images without focusing lens (top) andwith lens (bottom), laser propagation is from left to right. (b) Corrected axial signalsaturation profile indicating fraction deviation from linearity.

Camera dark noise was accounted for by performing Spiricon’s proprietary Ultracal

baseline correction algorithm before and periodically during experiments to reduce

the impact of the background noise. The entire camera and filter assembly was

attached to a precision linear translation stage, allowing measurements to be made

in numerous planes along the beam focus.

For beam profile images far from the focus where energy density was low, mul-

tiple laser pulse accumulations were captured to maximize signal. Jitter in the

pointing stability of the laser did not impact the profile measurements at these

locations. Profile images near the focus, where signal was sufficiently high, were

acquired on a single-shot basis. Prior to acquiring beam profile data, the camera

position was adjusted to locate the beam focus by minimizing the measured width

in real-time. Subsequent beam profile measurements were then performed at equal

distances before and after the focus location and extended well outside the Rayleigh

range. Finally the beam width was calculated for each image location, as described

in Section 4.2.3 below.

An alternative and common method of beam width measurement utilizes a scan-

ning knife edge. For this technique a knife edge, oriented perpendicular to the di-

mension of interest, is scanned across the beam to determine the distance between


the 10% and 90% clip locations. The 10-90 clip width is then converted into a beam

width using an appropriate scaling factor [115], and is typically assumed to be 1.561.

This measurement can be performed at various locations along the beam propaga-

tion direction to determine the beam width as a function of distance for a focused

beam. In general, the technique is straightforward and only requires a translation

stage and some means of measuring beam energy. This technique was applied by

Petersen et al. [114] for the study of 3-pentanone fluorescence saturation at 266 nm.

The scanning knife edge was used for initial test in the current study, but was found

to be too time intensive. In addition, the scaling factor used to convert from 10-90

clip width is only exact for a perfect gaussian beam (TEM00), and can vary for

higher order beams (e.g. excimers) depending on the mode content. As a result,

the CCD-based profiling system above was adopted. Generally, results acquired by

each method provided consistent results.

Beam Profile Image Processing

A series of representative beam profile images taken along the laser propagation

direction are shown in Figure 4.3a, where the bottom image corresponds to beam

focus. Each images was converted into an accumulated 1-D profile along the beam

width by summing 20-30 line profiles centered around the peak energy location in

the vertical direction. The beam width was then calculated from these profiles using

the second moment method, the accepted ISO standard for beam width (ISO 11146-

1:2005). The second moment (σ2x) in the x-direction is calculated using Equation 4.1:

σ2x =

∫ x2

x1(x− x)2 I (x) dx∫ x2

x1I (x) dx

(4.1)

where I(x) is the transverse intensity profile determined above, x is the distance

along the profile, and x is the beam centroid in the x-direction determined from

Equation 4.2. The resulting beam half width, w, is then twice the standard deviation


(a) Beam profile images

−40 −30 −20 −10 0 10 20 30 400

0.5

1

1.5

2

2.5

Propagation Distance [mm]B

eam

Hal

f−w

idth

[mm

]

Model FitMeas. Width

λ=308 nmw

0=0.076 mm

M2=45

(b) Measured beam widths

Figure 4.3: (a) Series of beam profile images acquired along beam focus. (b) Mea-sured beam half width along focus with fit results.

as shown in Equation 4.3

x =

∫ x2

x1I(x)xdx∫ x2

x1I(x)dx

(4.2)

wx = 2σx (4.3)

Camera-based beam width measurements using the second moment technique are

influenced by the CCD background noise, particularly in the wings of the beam

profile. The quadratic term in Equation 4.1 heavily weights the profile wings which

have low signal, and are often non-zero due to imperfect baseline subtraction. This

noise can result in significant errors in the beam width calculation if not eliminated

or accounted for. To address this issues the Spiricon UltrCal procedure, which

has been shown to reduce these errors [116], was performed frequently to improve

baseline correction. In addition, a truncated calculation of the second moment has

been performed using an adaptive aperture to set the bounds for integration. This

is represented in Equation 4.1 by the finite integral bounds, which are infinite for

the ideal second moment calculation.

After processing all images acquired along the propagation direction, the beam

half widths were plotted as a function of distance about the focus as shown in


Figure 4.3b. The data was then fit with Equation 4.4

wx (z) =

√w2

0 +

(λM2

πw0

)(z − z0)

2 (4.4)

where w0 is the half width of the beam waist, M2 is the beam propagation parameter,

and z0 is the location of the beam waist. Equation 4.4 is a form of the gaussian

beam spot size equation that has been modified for real laser beam propagation

through inclusion of the propagation parameter M2 [117]. M2 can be interpreted as

a measure of beam quality relating the real beam divergence to an ideal gaussian,

thus providing the ”number of times diffraction limited” (M=1 for ideal gaussian).

With the fit parameters determined, Equation 4.4 can be used to calculate the

beam width at any location, x, and is used to determine the variation in laser

cross-section area along the focus. Representative curve fit results are shown in

Figure 4.3b. This procedure was completed for each wavelength to determine the

propagation characteristics, and the results are shown in Table 4.1. The beam width

measurements were carried out multiple times during the measurement campaign

to assess the beam stability. Two sets of beam width data taken on different days

are shown in Figure 4.2b. The good agreement confirms the laser output stability,

which was assumed to be constant throughout all experiments.

Table 4.1: Excitation wavelength specifications for saturation experiments

Excitation Total Energy M2 Beam WaistWavelength [nm] [mJ] [mm]

248 65 33 0.058277 65 40 0.075308 65 45 0.075

Variation in laser fluence along the beam focus was determined from the total

laser energy measurement and the beam width data. As mentioned above the satu-

ration profiles generated in Figure 4.2b correspond to a subregion of the total vertical

beam dimension. The subregion height was determined based on the number of pix-

els used for summation and the measured spatial resolution of the imaging system.


This coupled with the beam width data determined the beam cross-sectional area

along the subregion focus. The corresponding fraction of total laser energy within

the beam subregion was determined by normalizing the integrated signal within the

subregion by the total integrated signal along the vertical direction. Finally, the

laser fluence, IL, was determined from IL = Ep/2whp where Ep is the laser energy

in the profile subregion, w is the beam half width, and hp is the height of the profile

subregion.

The metric used to describe saturation is the percent deviation from linearity,

δLin, and is determined from Equation 4.5. Here Sf is the axial fluorescence profile,

and SLinf is the corresponding linear fluorescence profile. The ratio of fluorescence

signals Sf/SLinf is exactly what is shown in Figure 4.2b.

δLin = 100× (1− Sf

SLinf

) (4.5)

The percent deviation is then plotted versus the variation in laser fluence and is

presented in Figure 4.4 for 308 nm excitation of 3-pentanone. At low laser fluence

(<70 mJ/cm2) the deviation is zero and thus the fluorescence is in the linear regime.

As the fluence is increased, the percent deviation is increased due to increasing

ground state depopulation.

Complete saturation is not achieved at the maximum fluence for the current

studies, as indicated by the continuously increasing percent deviation with increasing

fluence. At full saturation the percent deviation will asymptote to a constant value

other than 100%. The laser fluence was not increased to the point of saturation for

the current work, as the main focus was to determine the 10% non-linear threshold

value for each tracer molecule. This threshold has been selected as an indicator of

strong non-linear fluorescence behavior, assuming that deviations below 10% due

not significantly impact PLIF measurements. The 10% threshold is highlighted in

Figure 4.4, by the dashed red line and was found to be 320 mJ/cm2 for 3-pentanone

at the specified conditions. The aforementioned data acquisition and processing

procedure has been used to study the saturation characteristics of three common

tracers as discussed below.

4.3. EXPERIMENTAL RESULTS 59

101

102

103

104

0

10

20

30

40

50

Laser Fluence [mJ/cm2]

Dev

iati

on

fro

m L

inea

rity

[%

]

Figure 4.4: Percent deviation from linearity as a function of laser fluence, measuredfor 308 nm excitation of 3-pentanone at 1 bar in N2 (derived from same data asFigure 4.2)

4.3 Experimental Results

The saturation characteristics of acetone, 3-pentanone and toluene are studied us-

ing the experimental techniques described above. The investigation is considered in

two parts. First, the dependence of saturation intensity on excitation wavelength

is considered. Second, the dependence on total pressure and composition (air or

nitrogen) is presented. These parametric variables have been selected in an effort

to better understand the critical energy transfer processes and to assess the rela-

tive importance of absorption, vibrational relaxation, and electronic quenching of

oxygen. Effects of gas temperature, which is somewhat more complicated to vary

experimentally, is not considered in the current work.

4.4 Saturation Wavelength Dependence

Fluorescence saturation data similar to Figure 4.4 was acquired for acetone, 3-

pentanone and toluene over a range of wavelengths (248,277,308 nm) to assess the

functional dependence. All experiments were performed at a total pressure of 1


bar with nitrogen as the bath gas. Tracer partial pressures, which were selected

to provide high fluorescence signals, varied between species. These differences are

not expected to impact the results as initial data showed minimal sensitivity of

saturation to tracer partial pressure.

Saturation profiles for each tracer at an excitation wavelength of 308 nm are

presented in Figure 4.5 for comparison. Acetone and 3-pentanone exhibit very

similar saturation profiles, with difference in magnitude of only 10% for the highest

laser fluence achieved. The similarities between these ketones is not unexpected

given the analogous physical structure and photophysical behavior. Differences in

magnitude likely arise from the collective differences in absorption cross-section and

specific energy transfer rates. In comparison, the saturation intensities for toluene

are generally much lower. Specifically, toluene exhibits approximately 27% deviation

from linearity at a laser fluence of 100 mJ/cm2, while the ketone fluorescence is still

effectively linear at these conditions. This large difference in saturation intensity is

due in part to the high absorption cross-section of toluene which is factor of 14-16

times higher than for either ketone.

101

102

103

104

0

10

20

30

40

50

60

Laser Energy Density [mJ/cm 2]

Dev

iatio

n fr

om L

inea

rity

[%]

3−Pent.AcetoneToluene

248 nm

Figure 4.5: Comparison of deviation from linearity for acetone, 3-pentanone andtoluene at 248 nm excitation, and 1 bar of N2.

4.4. SATURATION WAVELENGTH DEPENDENCE 61

A comprehensive set of saturation data was acquired for each tracer at several

excitation wavelengths. The resulting 10% non-linear thresholds for these measure-

ments are summarized in Table 4.2. Both ketones exhibit a minimum in saturation

intensity at 277 nm (based only on the wavelengths tested), with intensity increasing

for longer and shorter wavelengths. These trends seem to follow an inverse relation-

ship with absorption cross-section, which attains a maximum between 275-280 nm at

room temperature . Overall, the saturation intensities of acetone are slightly higher

than for 3-pentanone. In contrast, the toluene saturation intensity was found to be

a at least factor of 10 less than the ketones for the same excitation wavelength of

248 nm.

Table 4.2: Experimental measurements of 10% non-linear threshold for varioustracer and excitation wavelengths

Tracer Excitation 10% Non-linearWavelength [nm] Threshold [mJ/cm2]

3-Pentanone 248 400277 250308 320

Acetone 248 540277 300308 520

Toluene 248 40

For all tracers tested, the excited state lifetime is dominated by fast intersystem

crossing, transfering excited state molecules from the excited singlet to the excited

triplet state. Due to the inherently long lifetime of the excited triplet state, mini-

mal ground state repopulation from the excited states occurs during the timescale

of the laser pulse. As a result, the saturation processes is likely more dominated

by the absorption rate than any other mechanism of ground state repopulation. To

demonstrate this, the saturation intensities for all three tracers are compared with

the inverse of absorption cross-section in Figure 4.6. As expected, the trends of both

saturation intensity and absorption cross-section are well correlated, confirming that

the absorption rate dominates the saturation intensity at these room temperature


248 277 308

0

200

400

600

10%

Dev

. [m

J/cm

2 ]

248 277 3080

2

4

6

Wavelength [nm]

1 / σ

[10

19 c

m−2

]

3−PentanoneAcetoneToluene

Figure 4.6: Comparison of 10% non-linear threshold (top) and inverse absorptioncross-section (bottom) for all tracers and wavelengths

and pressure conditions. However, the changes in saturation intensity and absorp-

tion cross-section are not exactly one to one (i.e. a 50% decrease in σ does not

correlate exactly with a 50% increase in saturation intensity), and indicates that

other secondary energy transfer processes are also influential. Potential secondary

mechanisms such as vibrational relaxation and electronic quenching are considered

below.

4.5 Pressure and Composition Dependence

The total pressure of the mixture increases the collision frequency of tracer molecules

with colliding partners and thus increases the potential for vibrational relaxation.

This in turn can increase the saturation intensity through competition with the non-

radiative decay rate that dominates the excited state for many tracer molecules. This

is analogous to the increase in FQY with increasing pressure [75]. Elevated pressure

can also increase the rate of intermolecular vibrational re-distribution (IVR) of the

4.5. PRESSURE AND COMPOSITION DEPENDENCE 63

ground-state and could help to avoid hole-burning effects due to high laser pumping.

Changes in bath gas composition, specifically the addition of oxygen, may further

increase the saturation intensity by adding an additional pathway for ground-state

re-population through electronic quenching. While these processes collectively can

impact saturation, the relative importance of each is unknown. To investigate these

effects, saturation data of each tracer species was acquired for a range of total

pressures (0-90 psi) in both nitrogen and air. All experiments were performed with

a constant partial pressure of seeder tracer for each species.

The pressure dependence of 3-pentanone saturation is explored in Figure 4.7a

for 308 nm excitation and nitrogen dilution. The increase in saturation intensity

with pressure follows intuition as the increased collision frequency is expected to

improve population re-distribution and enhance vibrational relaxation. For these

conditions, the saturation intensity increased from 320 to 680 mJ/cm2 when varying

the total pressure from 15-90 psi. The relative importance of oxygen quenching is

shown in Figure 4.7b through comparison of saturation profiles for nitrogen and

air at 15 psi total pressure. The close agreement between the air and nitrogen

data suggests that oxygen quenching does not impact saturation for 3-pentanone

with 308 nm excitation. Figure 4.7b includes several repeated data sets for both

bath gases and demonstrates the repeatability of the measurements. Interestingly,

the pressure dependence observed in Figure 4.7a for nitrogen is not seen in similar

data for air where instead the saturation characteristics are constant with increasing

pressure. Additional experiments at 277 and 248 nm showed no signs of pressure or

composition dependence. This implies that the pressure-related phenomenon shown

in Figure 4.7a are exclusive to excited states with low excess vibrational energy

(energy above thermal equilibrium in excited state) that are associated with long

excitation wavelengths such as 308 nm.

Similar to 3-pentanone, the pressure dependence of acetone is considered in

Figure 4.8a for 277 nm excitation and nitrogen dilution. Acetone data at 308 nm

exhibited minimal dependence on pressure or oxygen compositions and is not shown.

The results in Figure 4.8a are in stark contrast with the 3-pentanone results at 308

nm. For acetone the pressure dependence is reversed, with increasing pressures


101

102

103

104

0

10

20

30

40

50


Dev

iatio

n fr

om L

inea

rity

[%]

Ptot

=15

Ptot

=30

Ptot

=45

Ptot

=60

Ptot

=75

Ptot

=90

3−Pentanone308 nmN

2 Bath

(a) Nitrogen

101

102

103

104

0

10

20

30

40

50


Dev

iatio

n fr

om L

inea

rity

[%]

N2

Air

3−Pentanone308 nm

Ptot

=15 psi

(b) Nitrogen vs. Air

Figure 4.7: (a) Pressure dependence of 3-pentanone saturation with 308 nm ex-citation and a nitrogen bath gas. (b) Comparison of saturation characteristics fornitrogen and air bath gases with 308 nm excitation at 15 psi total pressure. Multiplecurves included to demonstrate measurement repeatability.

resulting in decreasing saturation intensity. Such behavior was unexpected and

conflicts with the notion of enhanced vibrational relaxation improving the saturation

characteristics. A similar inverse pressure dependence is also seen for acetone at

248 nm excitation, as shown in Figure 4.8b. In fact, the magnitude of the pressure

influence appears to increase at shorter wavelengths. In general, the inverse pressure

scaling indicates that other energy transfer mechanisms are at work.

One possible explanation is the existence of a collisionally assisted non-radiative

decay pathway. In a recent study of 3-pentanone photophysics by Cheung et al [90],

a pressure dependent knr term was added to the FQY model. This was done to

better match experimental data that exhibited a decrease in FQY with increasing

pressure. In addition, the effect of the collisionally assisted knr was found to increase

with excitation energy (excess vibrational energy in excited state). Assuming this

energy transfer pathway also holds true for acetone and with a larger magnitude,

it could result in the reversed pressure scaling shown here. Although not depicted

graphically, acetone saturation was found to have minimal dependence on oxygen

concentration as evidenced by nearly identical saturation behavior for both nitrogen

and air dilution.

4.5. PRESSURE AND COMPOSITION DEPENDENCE 65

101

102

103

104

0

10

20

30

40

50

Laser Energy Density [mJ/cm2]

Dev

iati

on

fro

m L

inea

rity

[%

]

Ptot

=0 psi

Ptot

=15 psi

Ptot

=30 psi

Ptot

=60 psi

Ptot

=90 psi

Acetone277 nmN

2 Bath

(a) 277 nm

101

102

103

104

0

10

20

30

40

50


Dev

iati

on

fro

m L

inea

rity

[%

]

Ptot

=0 psi

Ptot

=15 psi

Ptot

=30 psi

Ptot

=60 psi

Ptot

=90 psi

Acetone248 nmN

2 Bath

(b) 248 nm

Figure 4.8: Pressure dependence of acetone saturation in pure nitrogen for excitationwavelengths of (a) 277 nm and (b) 248 nm.

Saturation pressure dependence data was also acquired for toluene at 248 nm

excitation in nitrogen and is shown in Figure 4.9. A small decrease in saturation

intensity is observed at low pressures when transitioning from pure vapor pressure

to 15 psi total pressure. Increases in pressure beyond this have little influence. Com-

position dependence data for toluene in air is not considered here, as the acquisition

of high-quality data was difficult. Due to the dramatic impact of oxygen quench-

ing on fluorescence signal for toluene, the dynamic range between nitrogen and

air experiments was cumbersome. Toluene concentrations that provided reasonable

performance in air saturated the detection system, and conversely, concentrations

optimized for nitrogen experiments were not sufficient for the air bath gas. As a

result, no composition dependence data for toluene is considered here. In general,

toluene is expected to have larger compositional dependence in comparison with

ketones given the higher electronic quenching rates.

The preceding discussion provides additional insight into the fluorescence sat-

uration process for typical PLIF tracers. Specifically, the rate of absorption was

found to dominate the saturation behavior for the room temperature conditions

considered. Other processes such as vibration relaxation, ground-state population

re-distribution, and electronic quenching were found to be secondary. These sec-

ondary processes did impact the results for some conditions, but overall did not


101

102

103

104

0

10

20

30

40

50

60


Dev

iati

on

fro

m L

inea

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[%

]

Ptot

=0 psi

Ptot

=15 psi

Ptot

=30 psi

Ptot

=60 psi

Ptot

=90 psi

Toluene248 nmN

2 Bath

Figure 4.9: Pressure dependence of toluene saturation with 248 nm excitation anda nitrogen bath gas.

dramatically impact saturation characteristics for a majority of tracer, wavelength,

and pressure combinations. The 10% non-linear thresholds presented in Table 4.2

are particularly useful when designing PLIF experiments and ultimately sets the

limit of excitation energy for measurements in the linear regime. While it is gener-

ally preferred to assess fluorescence linearity in-situ for a given experimental setup,

these baseline numbers provide a general guideline and can be used if in-situ char-

acterization is difficult. Based on these results, the pump laser energies for the

HCCI engine applications presented in Chapter 5-6 have been chosen to be below

the measured linearity thresholds.

Chapter 5

Low-Load HCCI with NVO

Development of the gasoline homogeneous charge compression ignition (HCC) en-

gine is currently focused on extending the operating range at both low and high

load extremes. At the low limit, many strategies incorporate extensive internal ex-

haust gas recirculation (EGR, throughout this work refers to internal exhaust gas

recirculation), providing additional thermal energy that can help stabilize and con-

trol combustion phasing. A common approach is the negative valve overlap (NVO)

strategy based on injecting and reacting/reforming a small quantity of fuel during

NVO recompression [51, 52, 118]. An advantage of this strategy is the potential

for controlling main combustion phasing by varying NVO parameters such as the

amount of EGR, the NVO injection timing, and the NVO/main fuel-injection split.

While performance of low-load NVO operation has been demonstrated, our un-

derstanding of the strategy can still be improved. Fuel reformation during NVO pro-

vides both heat and reaction products that affect main combustion phasing. While

pressure records can provide an estimate of exothermicity during NVO, the extent of

reaction, the composition of reformed gases, and the relative importance of thermal

and chemical influences on main combustion are mostly unknown. Previous optical

diagnostic studies have provided some limited details of NVO chemistry such as

laser-induced fluorescence (LIF) detection of formaldehyde during low-temperature

reactions of two-stage fuels, and evidence of high-temperature reactions via OH

chemiluminescence [119]. The current work addresses the gap in understanding of

67

68 CHAPTER 5. LOW-LOAD HCCI WITH NVO

the NVO strategy through the development and application of an optical diagnos-

tic providing simultaneous temperature and composition distributions during HCCI

operation.

Planar laser-induced fluorescence (PLIF) is capable of measuring two-dimensional

temperature and concentration distributions with a high degree of accuracy and pre-

cision. PLIF of tracer molecules such as 3-pentanone, acetone, and toluene have seen

widespread use in IC engine research, typically for imaging of in-cylinder fuel distri-

bution. Tracer-based PLIF measurements of in-cylinder temperature distributions

have previously been demonstrated by Einecke et al. [26, 41], Fujikawa et al. [42]

and Kakuho et al. [43] among others. Although similar in theory, each diagnostic

method varies in terms of tracer, excitation wavelengths, excitation and collection

scheme, and calibration method.

In previous work by Rothamer et al. [44,70,120], a two-line (i.e., dual-wavelength)

PLIF technique using 3-pentanone (3P) as the fluorescent tracer was developed for

simultaneous measurements of temperature and composition. The technique was

optimized for in-cylinder engine conditions using available data for 3-pentanone

absorption cross-section and fluorescence quantum yield (FQY) at elevated temper-

ature and pressure [31, 34]. Wavelength selection was based on a comprehensive

uncertainty analysis that lead to the selection of 277nm and 308nm. Validation

of this technique was performed in a motored engine under known conditions to

assess measurement accuracy and precision. Additional demonstrations were also

performed under fired-engine operation for both conventional HCCI and HCCI with

NVO. The present work extends the application of the two-line PLIF technique

to portions of the NVO engine cycle that were previously unexplored, particularly

NVO recompression and re-expansion. Both fuel-seeded and air-seeded variations

of the technique are applied. Fuel-seeded measurements of temperature and fuel

mole fraction in the NVO recompression provide better understanding of in-cylinder

conditions at the end of exhaust and early in the NVO recompression period. Sim-

ilarly, measurements during NVO re-expansion help characterize gas temperatures

following recompression reactions that ultimately affect main combustion phasing.

Air-seeded measurements of temperature and EGR mole fraction during the main

5.1. EXPERIMENTAL SETUP 69

compression explore a range of NVO operating conditions, studying the effects of

main and NVO injection timing on in-cylinder charge evolution. This suite of mea-

surements is intended to address general aspects of NVO engine operation while

assessing the feasibility of the diagnostic technique. The focus of this work is more

on the application of the two-line PLIF technique and less about specifics of NVO

engine operation.

5.1 Experimental Setup

Measurements were performed in a single-cylinder optical engine configured for NVO

experiments. The pent-roof head is a GM prototype, housing two intake valves, a

single exhaust valve, and a vertical, near-centrally located 8-hole injector. The head

is also equipped with two spark plug ports that have been plugged for the current

HCCI experiments. The Bowditch piston is equipped with a 65-mm fused silica

window, providing imaging access from below. A sample PLIF image is shown in

Figure 5.2 with the valves, injector and piston window superimposed in the field

of view. For all PLIF images shown throughout this work, laser propagation is

from image bottom to top, with exhaust and intake valves on the left and right

respectively. Optical access for the laser sheets is provided by a 25-mm-tall fused

silica ring incorporated into the cylinder liner. Short dwell cams (145-CAD duration)

enable NVO operation, providing the high internal EGR levels required to burn high

octane fuels in this engine facility. Engine specifications are provided in Table 5.1,

with further details available in [121]. All engine measurements were performed at

1200 RPM, with iso-octane as the base fuel. Tracer was seeded in either the liquid

fuel (20% 3-Pentanone by volume), or the intake air as described below. The crank

angle convention for the NVO work is -360<CAD<360, with 0 crank-angle degrees

(CAD) corresponding to top dead center (TDC) of main compression

The basic PLIF diagnostic system consists of two lasers, a Raman cell, one dual-

frame ICCD camera, and associated optical components. A schematic of the PLIF

diagnostic setup is presented in Figure 5.1. The 308-nm laser pulse is generated


Table 5.1: HCCI engine specification for NVO operation

Bore 92 mmStroke 95.25 mmGeometric Compression Ratio 11.5IVO / IVC* -285 / -140 CADEVO / EVC* 140 / 285 CAD

*intake/exhaust valve open/close

by a Lambda Physik ComPexPro 102 XeCl excimer laser. The 277-nm pulse is

generated by Raman shifting the output of a 248-nm KrF excimer laser (Lambda

Physik ComPexPro 102, stable resonator) to the first Stokes wavelength (277nm) in

H2. The Raman cell (RC) used in the current experiments (custom LightAge RC)

is 72 cm in length, and is configured with a 60-cm focal length (f.l.) spherical lens

at the entrance and a 40-cm f.l. spherical lens at the exit. The RC is filled with

high-purity H2 to a total pressure of 57 bar, providing approximately 10% energy

conversion efficiency to the first Stokes wavelength. The output of the RC is passed

through an equilateral dispersing prism to spatially separate the residual pump and

shifted wavelengths, allowing the unwanted beams to be collected downstream with

a beam dump.

The current setup utilizes an extended beam path length of 5-6 m for each

excitation wavelength, allowing the inherent laser beam divergence to expand the

beam to the desired imaging sheet dimension. Each excitation beam is passed

through a 1-m f.l. cylindrical lens to form the beam waist, before being spatially

overlapped on a dichroic element coated to reflect 277 nm and transmit 308 nm.

Finally the beams pass through a ”vertical elevator” assembly that rotates the beam

90 and elevates the beam path to the desired location in the optical engine. The

resulting laser sheets are approximately 45-mm wide and 0.5-mm thick and are

aligned to be parallel to the fire deck, and displaced 3 mm below. The sheets

diverge slightly as they pass through the engine cylinder wall due to its effective

negative focal length. Typical laser energies per pulse during experiments were 30-

35 mJ for 277 nm and 45-50 mJ for 308 nm. Laser energies were measured several


248

nm

Exc

imer

Las

er

308

nm

Exc

imer

Las

er

Ram

an S

hif

ter

Optical Engine

248 nm

277 nm

308 nm

Laser Sheets

ICCD Camera

Figure 5.1: Experimental schematic

Figure 5.2: Sample PLIF image with valve, injector and piston window positionssuperimposed.


optical components upstream of the cylinder and an additional 4-6% energy loss is

included in the above laser energies. These laser fluences were selected to be below

the threshold values presented in Chapter 4, ensuring linear fluorescence behavior.

The resulting fluorescence signal is transmitted through the fused silica piston

window, and imaged onto the camera using a 85-mm f/1.4 Nikon lens. The ICCD

camera (Princeton Instruments PIMAX2:1003, P46 phosphor, SB slow-gate photo-

cathode) is equipped with an interline transfer CCD array allowing the collection of

two images with inter-frame timings as low as 2 µs. A sharp cut-on 325-nm long-pass

filter is used to reject scattered 308-nm laser light. The 1024x1024-pixel CCD array

is binned 8x8 on chip resulting in read-out images of 128x128 pixels (hereafter re-

ferred to as full-frame). This provides an image spatial resolution of approximately

0.5 mm, matching the out-of-plane resolution provided by the sheet thickness. In

some instances the images are binned an additional 2x2 during post-processing to

improve signal-to-noise ratio while sacrificing spatial resolution. For all experiments,

the ICCD camera inter-frame time is set to 5 µs, and the gate widths for the two

images are set to 800 ns. The camera and laser system were sychronized to the

engine by a quarter-crank-angle-degree-resolution crankshaft encoder.

5.1.1 Motored Engine Operation

Motored engine operation is used to generate a homogeneous tracer-air mixture of

known temperature, pressure and composition. The premixed seeding system con-

sists of a positive displacement pump delivering tracer to a heated cell mounted

on the intake air line upstream of the surge tank. The premix cell is maintained

at a temperature approximately 40 K above the boiling point of the tracer to en-

sure rapid evaporation. The tracer flow rate is determine by measuring the mass of

tracer delivered with a scale, and measuring the corresponding delivery time with a

stopwatch. The air flow rate to the engine was metered with a sonic orifice. Typical

seeding levels of 3-pentanone in the intake stream corresponded to a 3-pentanone

mole fraction of between 0.1-0.3% depending on engine conditions. The motored


operation mode is used for two purposes: diagnostic validation and image calibra-

tion. For purposes of diagnostic validation, motored experiments were performed

for a range of intake conditions with intake temperatures ranging from 300-460 K,

and manifold pressures from 0.7-1.4 bar. These experiments were carried out us-

ing more “conventional” cam phasing resulting in approximately zero valve overlap

(NVO 0). Results are described in Section 5.2. For the purpose of image calibration,

motored operation was employed between fired data sets to acquire homogeneous

calibration images required for data processing. In these experiments, cam phasing

was adjusted for valve overlap of -150 CAD (denoted NVO 150).

5.1.2 Fired NVO Engine Operation

The NVO operation scheme applied in this work utilizes a dual-injection strategy

to achieve HCCI combustion. A representative pressure trace for fired NVO op-

eration is shown in Figure 5.3, illustrating the valve events and range of injection

timings. The largest pressure peak, centered at 0 CAD, is associated with main

compression and combustion, and the lesser peak, centered at -360 CAD, is due to

NVO recompression resulting from early exhaust valve closing. Fuel injected during

the NVO mixes with hot exhaust gases from the previous main combustion and

undergoes compression during the NVO. If sufficient oxygen is present and ignition

temperatures are reached, exothermic reaction can occur. The exothermic reaction

can elevate residual temperatures enough to affect the subsequent main combustion

phasing. The NVO reactions also may produce partially reformed fuel species that

could further affect main combustion phasing.

For all conditions in the current experiments, appreciable apparent heat release

is observed during the NVO recompression stroke (seen in Figure 5.3b as an upturn

at the left end of the bottom pumping loop) due to relatively early NVO injection

and globally lean operating conditions. A list of fired engine operating conditions

is presented in Table 5.2. Main and NVO injection timings sweeps as well as main

combustion load sweeps were investigated. During the injection timing sweep ex-

periments, total fuel per cycle is held constant at 9.5 mg/cycle, with 1.5 mg/cycle


(a) (b)

Figure 5.3: Measured pressure for NVO engine operation, (a) pressure vs. CADshowing valve events and measurement regimes; (b) pressure vs. volume (log-logscaling)

injected during NVO and the remainder injected during main intake / compres-

sion. For the main load sweep experiments, NVO injections are held constant at

1.5 mg/cycle while varying the main injections from 7-9.5 mg/cycle. Average fuel

mass delivered per 50 cycles was measured using a positive displacement flow meter

(Max Machinery Model 213 Piston Meter) providing an estimated ±3% accuracy

for these low-load conditions.

Because the TB-PLIF diagnostic requires a fluorescence tracer, its application is

limited to times in the engine cycle when sufficient tracer is present. Tracer can be

seeded in the fuel or in the air. Considering fuel seeding first, NVO fuel injection

occurs as early as +260 CAD (see Figure 5.3a), and LIF images can be obtained

from +280 until the tracer decomposes during NVO reaction. The earliest main

fuel injection was at -320 CAD, allowing imaging as early as -300 CAD, prior to

intake valve opening (IVO). Again, imaging can continue throughout compression

until tracer decomposition and oxidation occurs. For all fuel seeded experiments,

tracer was mixed in the fuel at 20 vol%. For the air-seeded experiments, images can

be captured soon after IVO, once tracer-seeded air enters the cylinder, continuing

through the compression stroke. In addition, some measurements were made during


Table 5.2: Fired engine operating conditions.

Air Mass Flow Rate: 2.0-2.3 g/sIntake Air Temperature: 360 KManifold Pressure: 1 barMain Start of Injection (SOI): -320 to -100 CADMain Fuel Amount: 7-9.5 mg/cycleNVO Start of Injection (SOI): +260 to +330 CADNVO Fuel Amount 1.5 mg/cycleEngine Speed 1200 RPMCoolant Temperature: 90 CResidual Gas Fraction (mass): 48-54%Tracer Mass: 1-2 mg/cycle

NVO recompression based on residual tracer that escapes main combustion through

sequestration in cold crevice volumes.

The addition of 3-pentanone does impact the HCCI combustion characteristics

of iso-octane as has been previously studied [122]. In general, the addition of 3-

pentanone to the liquid DI fuel advances the combustion phasing in comparison

to pure iso-octane operating. The phasing is further advanced by pre-mixing the

tracer into the intake air due to the effective addition of the heat of vaporization

prior to delivery in-cylinder. For the current work, all quantitative comparisons are

made between experiments with like seeding methods, and as such the influence of

combustion does not alter any conclusions.

5.1.3 Data Acquisition

Quantitative PLIF measurements require three separate image sets for data pro-

cessing: a data set, calibration set and background set. Each data set consists of

100 images (50 images for each excitation wavelength) taken at the desired engie

condition and image timing. Calibration images (also referred to as flat-field im-

ages) are taken under homogeneous motored operation at known conditions. The

calibration images are taken shortly after acquisition of data images to minimize ef-

fects of laser profile fluctuations, ensuring accurate profile correction. Image timing


for the calibration images was carefully selected to ensure a uniform distribution

and minimal absolute temperature uncertainty. Background images are acquired

with laser emission, but without tracer seeding, to correct for any laser scatter or

fixed pattern signal. Cylinder pressure was recorded simultaneously with data and

calibration images to permit cycle-by-cycle corrections of any pressure fluctuations.

5.2 Validation Experiments

Homogeneous motored experiments provide a controlled means of validating the

PLIF diagnostic, as well as assessing measurement accuracy and precision. For

this purpose, motored data was recorded over a range of intake temperature and

pressure conditions. Figure 5.4 presents measured average temperature and air mole

fractions acquired under motored conditions with an air inlet temperature of 412

K and a manifold pressure of 1 bar. Average temperatures were calculated over

a 30x30 pixel region in the center of each image, and averaged among all 50 data

images. The measured temperatures in Figure 5.4a are compared to an isentropic

compression calculation based on the measured pressure trace and variable specific

heats. There is good agreement between measurement and prediction, as expected

since both represent the core region of the cylinder. For the full range of motored

operating conditions examined, the average temperature error is estimated to be

less than ±4%. Average air-mole-fraction measurements are shown in Figure 5.4b,

calculated in a similar fashion as the average temperatures. Because the motored

experiments contain no measurable EGR mole fraction, the expected value for these

conditions is 100% air. The measurements are systematically 4-5% higher than the

expected value and indicate an average mole fraction error of ±5% for the conditions

tested. This offset is likely due to a combination of inaccuracy in the 3-pentanone

FQY model and propagation of uncertainties in measured temperature that are used

to correct the mole fraction measurement. Given the systematic offset, it may be

reasonable in practice to apply a constant correction factor; however this has not

been applied here.

5.2. VALIDATION EXPERIMENTS 77

−140 −120 −100 −80 −60 −40 −20

400

500

600

700

800

Crank Angle [ ° CA]

Tem

pera

ture

[K]

Measured Average ( ± 4% error bars)Isentropic Compression

(a)

−140 −120 −100 −80 −60 −40 −200

20

40

60

80

100

120


Air

Mol

e F

ract

ion

[%]

Measured Average ( ± 5% error bars)

(b)

Figure 5.4: (a) Measured average temperature and (b) air mole fraction measuredfor motored engine conditions with air intake temperature of 412 K and a manifoldpressure of 1 bar.

Measurement precision is determined by calculating the standard deviation of

both temperature and mole fraction over the same 30x30 pixel region used above.

Measurement precision calculations corresponding to the same experimental con-

ditions as Figure 5.4 are presented in Figure 5.5. For these conditions, minimum

single-shot temperature and mole fraction precisions of ±7 K and ±3.7% have been

achieved, respectively. These standard deviation results are generally higher than

the theoretical estimates presented in Chapter 2 but do follow the predicted trends.

Deviations between simulation and experiment are attributed to inaccuracies in the

theoretical fluorescence signal estimates. Accuracy of the predictions could be fur-

ther improved through a more accurate characterization of system components (e.g.

collection efficiency, quantum efficiencies etc.). In general, the favorable agreement

in performance trends does demonstrate the utility of the uncertainty analysis and

the excitation wavelength selection.


−140 −120 −100 −80 −60 −40 −200

5

10

15

20


Tem

pera

ture

Std

. Dev

. [K

]

(a)

−140 −120 −100 −80 −60 −40 −200

2

4

6

8

10

Crank Angle [ ° CA]M

ole

Fra

ctio

n S

td. D

ev. [

%]

(b)

Figure 5.5: (a) Measured temperature standard deviation and (b) air mole fractionstandard deviation for motored conditions with air intake temperature of 412 K andmanifold pressure of 1 bar.

5.3 Measurement Interferences

When performing fired NVO engine experiments there are a number of possible

signal interferences that can make quantitative measurements difficult. Of partic-

ular importance for this work are fuel droplets and residual gas fluorescence. Fuel

droplets persisting after injection can cause laser extinction as the beam traverses

the cylinder, as well as excessively high signal levels if tracer is present in the fuel.

Unwanted fluorescence from exhaust gas species can cause problems by altering the

signal ratio and leading to erroneous measurements. This is particularly important

for NVO engine operation where high levels of exhaust gas residuals are retained

in-cylinder. Each of these interferences was investigated to ensure measurement

accuracy.

In-cylinder droplet lifetimes were assessed by measuring Mie-scattering over a

range of delay times following injection. The measurements were performed using

the 308 nm laser sheet alone in the configuration specified in Figure 5.1. A 45 mm

f/1.8 UV lens (Cerco 2073) was used for these experiments to transmit the elastically

scattered laser light. Initial measurements under cool, motored conditions indicate

5.3. MEASUREMENT INTERFERENCES 79

that a large fraction of droplets can persist for up to 80 CAD after injection for

early NVO and main injections at SOI +260 and -320 respectively. However, under

fired NVO engine conditions, droplet lifetimes fall dramatically due to substantially

higher temperature, allowing droplet-free LIF measurements much sooner after in-

jection. For fired operation, Mie images were acquired following NVO injection of

1.5 mg of fuel at +260 CAD, and main injection of 8 mg at -320 CAD. The latter

timing was selected to determine if fuel (and tracer) might evaporate fast enough

to allow LIF imaging during the re-expansion prior to IVO. Results of the fired

tests indicate that, at typical operating conditions, LIF images can be recorded as

early as 15 CAD after start of injection. The Mie images were recorded in the same

image plane location as the two-line PLIF measurements to ensure consistency. At

locations outside of this plane, droplet lifetimes could be different

Measurements of residual fluorescence were performed for a range of fired NVO

operating conditions to assess the significance of this interference in the three mea-

surement regimes (NVO recompression, NVO re-expansion, and main compression).

The experiments were performed at conditions identical to later parametric studies

of injection timing and combustion load to identify any operating conditions where

interferences may be substantial. Sources of residual interference include partial

products of combustion and unburned tracer. Since some combustion intermediates

such as aldehydes contain the same chromophore as 3-pentanone they can contribute

fluorescence to the measurements. The relative importance of interference from un-

burned tracer and residual fluorescence can be assessed by comparing results with

and without tracer seeding. Figure 5.6 presents this comparison. The single-cycle

image pairs were recorded during NVO recompression using the same setup shown

in Figure 5.1. Each pair comprises 277 nm and 308 nm fluorescence images that are

background corrected, but not corrected for laser profile variation.

Figure 5.6a shows the recorded signal with no tracer added, thereby represent-

ing partial combustion product fluorescence alone. A weak signal is seen in the 308

nm image, but minimal corresponding signal is visible at the same locations in the

277 nm image. Since the wavelength pair is optimized specifically for the tracer


Signal−277 nm [counts]

0

100

200

300Signal−308 nm [counts]

0

100

200

300

(a)

0

1000

2000

0

1000

2000

(b)

0

2000

4000

6000

5000

10000

15000

(c)

Figure 5.6: Single-shot 277 nm and 308 nm LIF images of (a) residual gas recordedat +260 CD (no tracer), (b) carry-over 3P recorded at +260 CAD (prior to fuelinjection, and (c) 3P recorded at +285 CAD (following DI fuel injection)

5.3. MEASUREMENT INTERFERENCES 81

3-pentanone, the uncorrelated fluorescence seen in the Figure 5.6a image pair is ev-

idence of fluorescence from non-tracer species. A likely candidate is formaldehyde

that photo-dissociates disproportionately at the shorter, 277 nm, wavelength. Fig-

ure 5.6b presents the signal for the case of tracer seeding of the fuel, but is acquired

before NVO injection, thus displaying any residual tracer fluorescence in addition

to combustion product fluorescence. Here the signals are approximately an order

of magnitude higher than Figure 5.6a with noticeable correlation between the two

wavelengths. These results indicate that, in this case, the signal is dominated by

unburned 3-pentanone, referred to henceforth as carry-over tracer. It should be

noted that this signal from carry-over tracer does not represent a source of error for

our fuel concentration measurements (NVO recompression and re-expansion) since

it can be interpreted in the same fashion as tracer from the NVO injection. Carry-

over signal is a potential source of error for EGR measurements (main compression)

as the technique accuracy relies on complete tracer consumption. However, for cur-

rent experimental conditions, the carry-over signal is weak and any resulting error

is insignificant.

The image pair in Figure 5.6c represents the same experiment as the previous

pair, but with image acquisition 25 CAD after fuel injection. Examination of gray

scales reveals that these signals are two orders of magnitude higher than those of

Figure 5.6a. Based on measurements for a range of operating conditions, we conclude

that residual-gas fluorescence is not a significant source of error for quantitative

PLIF measurements during NVO recompression. Similar measurements were also

performed during NVO re-expansion and main compression, indicating that residual

fluorescence does not present a problem in these regimes. Note however, that other

operating conditions do result in high interference signal levels from residual gas,

specifically conditions with later NVO injections (SOInvo >+345) where substantial

fuel reforming occurs during NVO reaction. The test for interfering fluorescence is

straightforward (i.e. LIF imaging without tracer addition) and should be applied

for any new operating conditions.


5.4 Fired NVO Results

Carry-over Tracer Measurements

The results of the above interference LIF measurements during NVO recompression

indicate that the main source of residual gas fluorescence is unburned 3-pentanone.

This tracer is carried over from the previous main combustion and likely originates

as unreacted crevice gases ejected into the measurement field of view during the

main expansion and exhaust strokes. This carry-over signal offers an opportunity

to make temperature and fuel mole-fraction measurements of unburned fuel during

the exhaust stroke. Such measurements require that the tracer faithfully follows

any unburned fuel through compression, expansion, and exhaust strokes. Simple

CHEMKIN simulations as well as prior studies [72] suggest that chemical reaction

of 3-pentanone tracer should parallel the reaction of the iso-octane fuel for engine

time scales. Thus, it is reasonable to assume that any unburned fuel in crevices, for

example, will be accompanied by a proportional amount of tracer. Any departure

from this constant ratio of tracer to unburned fuel affects only the composition

measurement and not temperature.

The following fired experiments illustrate the carry-over tracer measurements.

Three main combustion loads of 7, 8 and 9.5 mg/cycle were selected with a con-

stant NVO injection mass of 1.5 mg/cycle. Main injection was set at -270 CAD

and NVO injection at +260 CAD. Increases in main combustion load lead to an

increase in apparent main heat release and increased residual temperature. Higher

residual temperatures can in turn affect apparent heat release and phasing of the

subsequent NVO recompression, demonstrating the cyclic feedback of NVO engine

operation. Representative temperature and fuel mole fraction measurements of un-

burned fuel are presented in Figure 5.7 for a constant image timing of +260 CAD

(near EVC). Due to low tracer concentrations at these conditions, signal-to-noise

ratio (SNR) for these images is low. A 3x3 median filter has been applied to the

processed temperature and mole fraction images to improve clarity (applied to these

low-SNR images only). The images depict characteristic regions of unburned fuel

5.4. FIRED NVO RESULTS 83

that are formed as the crevice volume fluid is drawn across the field of view during

the exhaust. The unburned fuel is preferentially located on the right (intake) side

of the cylinder, likely due to the bulk flow toward the exhaust valves. The tem-

perature images in Figure 5.7 indicate a wide range of temperatures, with cooler

temperatures frequently located near the core of the fuel regions where fuel concen-

tration is higher, and hotter temperature located near the perimeter where crevice

fuel is mixed with hotter residuals. Average temperatures (calculated over regions

with sufficient tracer mole fraction) rise with increasing main combustion load as

expected. Fuel mole fraction measurements in Figure 5.7 indicate peak unburned

levels of 1000-1500 ppm. These values are difficult to verify but are at least con-

sistent with unburned hydrocarbon emissions measurements made during similar

experiments. Because the unburned fuel/tracer does not occupy a large portion

of the cylinder volume, the measured temperature may not represent the overall

average in-cylinder temperature. However the technique does provide insight into

temperature and concentration of unburned fuel prior to the NVO recompression.

NVO Recompression Measurements

The NVO recompression is an important regime that has received only modest op-

tical diagnostic attention [44,53,56,119,123,124]. Because exothermic reaction and

fuel reforming during the NVO can significantly affect the main combustion event

that follows, it is important to understand NVO reactions. The two-wavelength

PLIF diagnostic can contribute to understanding by characterizing temperature

and fuel distribution prior to recompression reactions. To demonstrate, we measured

temperature and fuel mole fraction during NVO recompression for main-combustion

loads of 7, 8 and 9.5 mg/cycle. Injection times for these experiments were +260 and

-270 CAD for the NVO and main injections respectively. The NVO fuel/tracer is

injected near EVC so that LIF images could be recorded during recompression.

Representative single-shot results are shown in Figure 5.8 for a constant image-

capture timing of +285 CAD. The spatial variation in local fuel mole fraction is

visibly high, consistent with the relatively short time between start of injection and


Temperature [K]

500

600

700

Fuel Mole Fraction [%]

0

0.1

0.2

(a)

500

600

700

0

0.1

0.2

(b)

500

600

700

0

0.1

0.2

(c)

Figure 5.7: Single-shot temperature and fuel mole fraction image pairs of carry-over3P signal during NVO recompression. Image capture timing is +260 CAD for allimages. Three main combustion loads: (a) 7 mg/cycle, (b) 8 mg/cycle, (c) 9.5mg/cycle.


image acquisition. High levels of temperature stratification are also seen, resulting

from both fuel evaporation in areas with high fuel fraction, and stratification orig-

inating from the exhaust event. (This extensive stratification masks somewhat the

typical strong correlation between temperature and mole fraction images as seen

for example in Figure 5.10 a, where high EGR regions correlate with high tempera-

tures.) Measured temperatures, averaged over the entire field of view (where tracer

is present) of 50 images, follow the expected increasing trend with main-combustion

load: the average values are 700 K (Figure 5.8 a), 730 K (Figure 5.8 b) and 780 K

(Figure 5.8 c). Concurrent thermocouple measurements of exhaust port temperature

were 549 K, 575 K and 604 K for the three loads. Any agreement in temperature

measurements may be fortuitous given the small fraction of total cylinder volume

being probed, but this does confirm the expected trend of increasing temperature

with load. Not surprisingly, the thermocouple values are significantly lower than

in-cylinder values since they are time averages of pulsating exhaust flows in a cooled

port. However, temperature differences (i.e. T-cylinder - T-port) match well for the

lower two loads, while for the highest load the difference increases. Additional mea-

surements were performed at later image capture times during NVO recompression,

but the extent of visible tracer signal decreases as fuel passes through the measure-

ment plane under these conditions, limiting the area over which temperatures can

be measured. The above results demonstrates the viability of PLIF measurements

during NVO; further work is warranted to push these measurements later in the

recompression.

NVO Re-expansion Measurements

NVO heat release and fuel reformation influence the residual temperature and com-

position, thereby affecting main combustion phasing. Experiments show that tracer

from the NVO fuel injection is consumed during NVO reactions. Thus, in order to

make PLIF measurements, we devised an alternative strategy based on advancing

the main fuel injection to -320 CAD. This allows PLIF imaging as early as -300

CAD (15 CAD before IVO). Temperatures obtained at this time could be useful


Temperature [K]

500

600

700

800

900Fuel Mole Fraction [%]

0

0.5

1

(a)

500

600

700

800

900

0

0.5

1

(b)

500

600

700

800

900

0

0.5

1

(c)

Figure 5.8: Single-shot temperature and fuel mole fraction images during NVOrecompression. Image capture time = +285 CAD. Three main combustion loads:(a) 7 mg/cycle, (b) 8 mg/cycle, (c) 9.5 mg/cycle


in understanding the relative importance of thermal and chemical effects of NVO

reactions. We verified that fuel injected at this time does not react until the end

of main compression, and does not change main combustion phasing compared to a

more conventional main-injection timing of -270 CAD. We tested this technique over

a range of operating conditions by varying NVO-SOI timing from +260, to +330

CAD. NVO and main fueling were held constant at 1.5 and 8 mg/cycle, respectively.

Sample temperature and fuel mole fraction results are shown in Figure 5.9.

As expected, there is a high spatial variation in fuel mole fraction due to the

short time scale for mixing between injection and image acquisition. A large degree

of stratification is also seen in the temperature images, in locations where tracer

is present and measurements are possible. This temperature stratification results

both from fuel evaporation in areas with high fuel fraction, and from stratification

produced during NVO reactions. Average temperatures for the +260, +300 and

+330 NVO SOI timings were calculated to be 790 K, 800 K and 800 K respectively.

These measurements indicate that there is not a significant change in residual tem-

peratures for the injection timings tested. However, because of the relatively large

image area without signal, these measurements may not be representative of the

entire field of view or cylinder volume. Additional measurements were performed at

later times in the NVO re-expansion, but the effective measurement area decreases

as fuel passes through the imaging plane. These measurements demonstrate the

feasibility of fuel-seeded measurements of temperature during NVO re-expansion,

providing a means to potentially correlate NVO SOI timing with NVO residual

temperatures and subsequent main-combustion phasing. Note also that the compo-

sition images obtained simultaneously could be used to compensate for evaporative

cooling as a way of estimating NVO average temperatures absent the effects of fuel

injection.

Main Combustion Measurements

Measurements of temperature and EGR mole fraction (utilizing the N-PLIF for-

mulation), were performed in the main-compression stroke using intake air seeded


Temperature [K]

600

700

800

900Fuel Mole Fraction [%]

0

1

2

(a)

600

700

800

900

0

1

2

(b)

600

700

800

900

0

1

2

(c)

Figure 5.9: Single-shot temperature and fuel mole fraction images during NVOexpansion for early main injection at -320 CAD. Three NVO SOI timings shown:(a) +260, (b) +300, and (c) +330 CAD.


with tracer. Being able to make such measurements is important when studying the

mixing of hot residual gases with fresh intake charge prior to combustion. We tested

our diagnostic over the following range of injection timings: with main injection held

constant at -270 CAD, NVO SOI timing was varied between +260 and +330 CAD;

and with NVO injection constant at +260 CAD, main SOI timing was varied between

-270 and -100 CAD. Image-capture timing ranged from intake through compression.

Representative results for a sweep of image timings are presented in Figure 5.10.

Injection timing for these experiments was NVO SOI = +330 CAD and main SOI

= -270 CAD. The amount of fuel injected during the NVO was 1.5 mg/cycle, with

a total injection of 9.5 mg/cycle. Typical single-shot images acquired during the

intake stroke, Figure 5.10 a, show large non-uniformities in both temperature and

EGR mole fraction as the hot residuals mix with cooler intake air. A characteristic

pattern is often observed, with cooler intake flow across the cylinder center from

right to left (intake to exhaust), and hotter residuals toward the rear of the cylinder

(top of image). Early in the compression stroke, Figure 5.10 b, much of the non-

uniformity is mixed out. Reduced levels of stratification in both temperature and

mole fraction persist through main compression, as evident in the late compression

images, Figure 5.10 c. These qualitative comparisons demonstrate the utility of

simultaneous EGR and temperature measurements, but a more quantitative means

of comparison is required.

In an effort to quantitatively compare PLIF measurements for varying operating

conditions, we calculated average and standard deviation statistics of temperature

and mole fraction for all pixels in the field of view, and averaged over all 50 data

images. Standard deviation was selected as an indicator of charge stratification-

although this eliminates any spatial information regarding stratification, it does

track overall fluctuations. Interpretation of standard deviation is further compli-

cated by the convolution of physical standard deviation (i.e., physical, in-cylinder

stratification) with diagnostic uncertainty. Because uncertainty varies with image-

capture timing and engine conditions, i.e. with changing signal levels and photo-

physical parameters, comparisons between engine conditions are challenging. Four

calculations of temperature standard deviation (for the experiment of Figure 5.10)


Temperature [K]

400

500

600EGR Mole Fraction [%]

0

50

100

(a)

500

600

700

0

50

100

(b)

750

800

850

900

0

50

100

(c)

Figure 5.10: Single-shot temperature and EGR mole fraction images recorded atthree image timings: (a) -215, (b) -65, and (c) -24 CAD. NVO SOI = +330 CAD;main SOI = -270 CAD. Images at -24 CAD (only) are binned 2x2. Note variabletemperature color scale.


are presented in the four data sets of Figure 5.11. Since the 2x2 binning pro-

cess suppresses diagnostic noise (which is characterized by a relatively short length

scale), we can estimate the magnitude of diagnostic uncertainty by looking at the

difference between the Full-Frame and Binned 2x2 data sets in Figure 5.11. This

difference is small at -215 CAD where the diagnostic uncertainty is low and statis-

tics are dominated by physical fluctuations in in-cylinder temperature. Conversely,

the difference is higher at -24 CAD due to increase diagnostic uncertainty at higher

cylinder temperatures. These results suggest that a method of correction is needed

as follows.

Two techniques to decouple physical standard deviation from diagnostic uncer-

tainty have been investigated. The first technique (labeled Corrected in Figure 5.11)

utilizes the difference of standard deviations for full-frame and 2x2 binned images

described above to estimate diagnostic uncertainty. For this technique we assume

that the physical standard deviation (∆T 2phys) and diagnostic uncertainty (∆T 2

diag)

sum in quadrature resulting in the measured standard deviation (∆T 2meas) as shown

in 5.1 written for the full-frame images. A similar relation also holds for the 2x2

binned images (subscript bin). Subtracting these relations, we arrive at Equa-

tion 5.2 which relates the diagnostic uncertainty and measured standard deviation

for the full-frame and 2x2 binned images. Equation 5.2 can be further simplified by

introducing f, the ratio of diagnostic uncertainty for the full-frame and 2x2 binned

images shown in Equation 5.3. Finally Equation 5.4 represents the diagnostic un-

certainty as a function of measured standard deviation of the full-frame and binned

images and f. Assuming the measurements are in the shot-noise-limited regime, and

that diagnostic uncertainty is dominated by camera shot noise, the factor f will be

exactly 2. When including additional sources of uncertainty such as laser energy

and profile fluctuations, the factor is slightly smaller.

∆T 2meas = ∆T s

phys + ∆T 2diag (5.1)

∆T 2meas −∆T 2

meas bin = ∆T 2diag −∆T 2

diag bin (5.2)


−250 −200 −150 −100 −50 00

10

20

30

40

50


Tem

pera

ture

Std

. Dev

. [K

]

Full−FrameBinned 2x2CorrectedBinned−Filt.

Figure 5.11: Demonstration of data correction for diagnostic uncertainty.

f =∆T 2

diag

∆T 2diag bin

(5.3)

The Corrected data set in Figure 5.11 represents physical standard deviation

calculated by subtracting the square of diagnostic uncertainty (Equation 5.4 from the

square of the measured standard deviation (full-frame data). The second technique

(labeled Binned-Filt. in Figure 5.11) represents a simpler decoupling method that

uses a 3x3 median filter (in addition to the 2x2 binning) to more completely suppress

the diagnostic noise. The large difference in Full-Frame and Corrected data near

TDC of Figure 5.11 indicates, as expected, that diagnostic uncertainty is high in this

regime, and that quantitative statistical comparison would be difficult without some

form of correction. The similar results of the Corrected and the Binned-and-Filtered

techniques indicate that both achieve the intended goal. Although not shown here,

the two techniques perform equally well for correction of mole fraction standard

deviation. With this correction, we are now in a position to compare average and

standard deviation statistics of the NVO test conditions.

Figures 5.12 and 5.13 compare data for three operating conditions selected pri-

marily to demonstrate a range of NVO-experiment data. The triangular data points


correspond to the same data from Figures 5.12 and 5.13; the others differ in NVO

and main-injection times. Looking first at Figure 5.12a, the closely spaced data

points indicate little variation of average temperatures for the three cases presented

at the latest image timing (-24 CAD); the temperature spread between the three

conditions amounts to 13 K. Examining the trend of the data through the cycle, one

sees temperatures dropping during intake (data at -215 through -140 CAD) as hot-

ter EGR mixes with cooler intake air. (Recall that for these N-PLIF experiments,

the air is seeded, so that image capture begins only after sufficient air is present in

the field of view.) This trend of decreasing average temperature during intake is

influenced by the measurement plane location and the relative proportion of EGR

and fresh intake. Average temperatures are expected to decrease through intake

for a measurement plane initially containing high EGR levels, and increase for a

measurement plane initially containing low EGR levels. Later during compression,

average temperatures climb rapidly due to compressive heating.

Temperature stratification, as represented by standard deviation in Figure 5.12b,

is highest early in the intake event before EGR and fresh charge are well mixed. The

stratification decreases through the end of intake and into compression, reaching

an apparent minimum value at -65 CAD. The stratification then increases slowly

through compression. The latter increase is due to both the charge compression,

which increases both average temperature and spatial temperature differences, as

well as heat transfer with the cylinder walls. Although there are visible differences in

stratification for the various engine conditions in Figure 5.12b, it is difficult to discern

any significant pattern given the data scatter. However, the standard deviation

trends for each of the operating conditions is comparable. The large spread in

temperature stratification for the earliest image timing in Figure 5.12b (-215 CAD)

merits additional comment. The spread is likely due to differences in the operating

conditions in terms of both injection timing and NVO heat release. For the data

points corresponding to a main SOI of -270, the fuel has been injected prior to

image acquisition, potentially adding temperature stratification through evaporative

cooling. Conversely, for the main SOI of -100 CAD, the fuel is injected well after the

image capture. NVO exothermicity also varies considerable between these operating


−250 −200 −150 −100 −50 0400

500

600

700

800

900


Tem

pera

ture

[K]

SOINVO

=−460 SOImain

=−270

SOINVO

=−390 SOImain

=−270

SOINVO

=−460 SOImain

=−100

(a)

−250 −200 −150 −100 −50 00

10

20

30

40

50

Crank Angle [ ° CA]T

empe

ratu

re S

td. D

ev. [

K]

SOINVO

=−460 SOImain

=−270

SOINVO

=−390 SOImain

=−270

SOINVO

=−460 SOImain

=−100

(b)

Figure 5.12: (a) Measured average temperature and (b) temperature standard devi-ation for several engine operating conditions. The error bars shown in (a) representaccuracy estimated from motored diagnostic characterization experiments.

conditions, understandably producing different stratification results.

∆Tdiag =

∆T 2

meas −∆T 2meas bin(

1− 1f2

)

12

(5.4)

EGR mole-fraction measurements for the selected engine conditions are shown

in Figure 5.13. Average EGR mole-fraction values in Figure 5.13a follow similar

trends as temperature during intake, where values decrease as EGR mixes with in-

take air. This indicates that at the current measurement plane, the distribution

at -215 CAD contains a high portion of EGR, resulting in decreasing temperature

and EGR mole fraction during intake as additional fresh charge is drawn into the

cylinder. The observed rise in EGR during late compression requires more expla-

nation. If our diagnostic field of view contains a representative sample of cylinder

contents, then average EGR fraction should remain constant. The contrary rise seen

in Figure 5.13a could be evidence of vertical stratification in the cylinder, with lay-

ers of different EGR fractions being swept through the imaging plane by the rising


piston. Some portion of the EGR fraction increase could also be associated with er-

rors in measured temperature as well as inaccuracies in the FQY model used during

calibration, since these propagate through to the mole-fraction calculations. In pre-

vious studies [44] , this error propagation has been shown to induce errors in average

mole fraction of up to 10%, particularly for extreme conditions near TDC. The mole

fraction accuracy of 5% reported above holds over a majority of the tested engine

range but may be larger at the extreme temperatures near TDC. Finally, decompo-

sition of the tracer would also lead to an apparent increase in EGR mole fraction

throughout compression. However, chemical simulations indicate that tracer and

fuel decomposition are well correlated, implying that no tracer decomposition is

expected prior to the main heat release. In addition, because iso-octane does not

exhibit any low-temperature chemistry and our latest image capture timing during

compression (-24 CAD) is much earlier than the onset of exothermic reaction, it is

expected that tracer decomposition at this time will be negligible. Similar to average

temperature data in Figure 5.12a, Figure 5.13a shows no significant differences in

average EGR mole fraction for the three conditions presented, indicating that this

is no substantial difference in engine breathing.

Each EGR standard deviation data set in Figure 5.13b follows a trend generally

similar to temperature standard deviation. Stratification is highest for the earliest

points, before substantial mixing has occurred. (The increase in stratification at -180

CAD is unexpected and will required a more refined study to determine the cause.)

Stratification then decreases, reaching a steady value after -42 CAD. This behavior

suggests that mixing has slowed by this point, and this conclusion is consistent with

the rising temperature stratification in Figure 5.12b (strong mixing would decrease

temperature stratification). As a final observation, comparing the three data sets

in Figure 5.13b indicates that there is little difference in EGR stratification for the

operating conditions tested. Again, this is not surprising - although injection timing

can significantly affect combustion phasing, it has less effect on engine breathing and

in-cylinder mixing.


−250 −200 −150 −100 −50 00

20

40

60

80

100


EG

R M

ole

Fra

ctio

n [%

]

SOINVO

=−460 SOImain

=−270

SOINVO

=−390 SOImain

=−270

SOINVO

=−460 SOImain

=−100

(a)

−250 −200 −150 −100 −50 00

2

4

6

8

10

12


EG

R M

ole

Fra

ctio

n S

td. D

ev. [

%]

SOINVO

=−460 SOImain

=−270

SOINVO

=−390 SOImain

=−270

SOINVO

=−460 SOImain

=−100

(b)

Figure 5.13: (a) Measured average EGR mole fraction and (b) EGR standard devia-tion for several engine operating conditions. Error bars represent accuracy estimatedfrom motored diagnostic characterization experiments.

Chapter 6

High-Load HCCI

The homogeneous charge compression ignition (HCCI) engine strategy can provide

both high efficiency and low emissions. However, the limited load range is a tech-

nical challenge that must be addressed prior to widespread implementation. The

high-load limit specifically is constrained by high cylinder pressure rise rates (PRR)

during combustion that can lead to engine knock as fueling is increased. Previous

research has shown that naturally occurring thermal stratification (TS) of the in-

cylinder charge is central to high-load HCCI operation [108, 125]. The dominant

mechanism for TS development is thought to result from wall heat transfer and

convection of the near-wall cold gas [108]. However, TS may also result from the

retained combustion residual gas, and fuel injection. The resulting localized temper-

ature variations in the bulk-gas results in sequential auto-ignition, a process in which

the hottest regions ignite first followed by progressively cooler regions [108,126]. This

effectively slows the combustion heat release rate (HRR) and could potentially be

exploited to expand the high-load limit.

While recent studies have begun to investigate the impact of thermal stratifi-

cation, additional characterization is still needed. Chemiluminescence was previ-

ously employed to indirectly study the effects of TS on HCCI combustion [108].

Here, the auto-ignition was found to occur in localized zones that are randomly dis-

persed within the bulk-gas despite operation with a fully premixed fuel/air charge.

97

98 CHAPTER 6. HIGH-LOAD HCCI

High-speed chemiluminescence image sequences further showed that reactions oc-

curred sequentially throughout the charge. Although this has been attributed to

TS [108, 126], this has not been directly verified. It was also found that TS in the

boundary layer has only a secondary effect on the reduction in PRR as the timing

of reactions in these regions is well after the maximum PRR [108].

Additionally, multi-zone Chemkin engine simulations demonstrated the necessity

of including thermal stratification in HCCI simulations to better match experimental

cylinder pressure measurements and apparent heat release (AHR) profiles [125]. In

addition, the benefit of a given amount of TS was found to be amplified by retarding

the combustion phasing [125]. While these studies do provide evidence of TS, they

do not specifically address the distribution, spatial-scale, and evolution of TS during

HCCI operation. This fact has motivated the development of several fluorescence-

based diagnostics to directly investigate TS.

In an initial work, Dec et al. [71] developed a single-line PLIF temperature

diagnostic using toluene as the fluorescence tracer with 266 nm excitation. This

diagnostic was used to study the distribution and evolution of TS in a motored

HCCI engine and represents the first direct quantification of TS. The current work

has developed similar single-line [127] and additional two-line [77,89,127] techniques

using either 3-pentanone or acetone (both ketones) with excitation at 277 nm and

308 nm. All single-line techniques provide sufficient temperature precision to resolve

small temperature fluctuations, and were used to study TS development in the

same motored HCCI engine as [71]. These experiments provided validation of the

diagnostic techniques, and aided further quantification of the TS development.

The current work further extends the application of the ketone-based diagnostics

to fired HCCI operation and investigates the differences and similarities between mo-

tored and fired conditions. First, a two-line diagnostic for temperature and compo-

sition is applied to study the residual mixing process and to determine the potential

impact of residuals on TS for low-residual HCCI operation. Low-residual conditions

are achieved with conventional valve timing, resulting in a small quantity of hot

combustion residuals. Strategies such as negative valve overlap (NVO) [89] that in-

crease residual gas retention are not considered. The impact of combustion residuals


is further studied by comparing single-line temperature results acquired for skipfired

cycles with and without hot residuals.

Next, single-line temperature measurements during the compression stroke are

used to characterize the TS development for motored and fired operation. The influ-

ence of early direct fuel injection is considered by comparing motored measurement

results with fully premixed fuel or early direct injection. In addition, the impact

of boundary wall temperature is investigated through comparison of premixed fired

results with varying coolant temperature. Finally, spatial correlation between the

temperature distribution and subsequent reaction zones are used to study the pro-

gression of reaction within the cylinder core, and to demonstrate the importance of

TS in HCCI combustion.

6.1 Experimental Setup

6.1.1 Optical Engine

The high-load HCCI experiments were performed in an optical engine located at

Sandia National Laboratories’ Combustion Research Facility in Livermore, Califor-

nia. The optically accessible engine is derived from a Cummins B-series medium-

duty diesel engine that has been converted for single-cylinder operation. Detailed

description of the engine and facility is available in [108, 128] , and will only be

summarized here. An engine schematic highlighting key components is shown in

Figure 6.1, and the relevant specifications are listed in Table 6.1.

The pancake style combustion chamber (flat head, flat piston-crown) has a 0.98

liter displacement, and a geometric compression ratio of 14:1. Laser sheet access is

provided by three windows integrated into a spacer ring that forms the top portion

of the cylinder wall. The spacer ring assembly is recessed into the head to provide

laser and imaging access up to the firedeck. Laser access through TDC was possi-

ble due to the simplified engine geometry (unlike previous experiments in pentroof

engine where image timing was limited to 24 bTDC due to piston position). A

Bowditch piston outfitted with a large piston-crown window (70 mm diameter) and


277 nm 308 nm

Figure 6.1: Detailed schematic of optical HCCI engine showing location of lasersheets and imaging camera.

right-angle mirror permits imaging access from below. A drop-down cylinder liner

with hydraulic-piston activation allowed rapid cleaning of internal window surfaces

between experiments.

A schematic of the engine facility and related subsystems is shown in Figure 6.2.

Intake flow of either air or nitrogen was metered with a sonic-nozzle orifice and

was continuously adjusted to maintain a constant intake pressure of 100 kPa for

all experiments. The intake stream was electrically heated by a main and auxiliary

heater to the desired intake temperature. The auxiliary heater, located near the

engine, provided precise temperature control and was used for fired experiments to

adjust combustion phasing in real-time. Intake temperatures ranging from 100C-

205C were used for calibration experiments, while a constant intake temperature of

170 was used for all motored studies. For fired experiments, the intake temperature

was adjusted to maintain CA50 combustion phasing at 367 CA, typically ranging

from 200C-210C. All motored and fired experiments were taken at an engine speed

of 1200 RPM. A summary of engine operating conditions is presented in Table 6.2

Both premixed and direct injection (DI) fuel delivery methods were employed


Table 6.1: Engine Specifications

Displacement 0.981 liters

Bore 102 mm

Stroke 120 mm

Connecting Rod Length 192 mm

Geometric Compression Ratio 14:1

Clearance Volume Height 8.05 mm

No. of Valves 4

IVO 0 CA

IVC 202 CA

EVO 482 CA

EVC 8 CA

Swirl Ratio 1.3

Engine Speed 1200 rpm

for this study. All motored experiments and a fraction of fired experiments uti-

lized the premixed operation. The premixed fueling system consisted of a positive-

displacement pump that delivered the fuel / tracer mixture to an electrically heated

fuel vaporizer shown in Figure 6.2. The vaporizing mixture chamber was located

upstream of the intake plenum to ensure a truly homogeneous mixture in-cylinder.

Fuel delivery rate was determined by monitoring the mass of fuel delivered (with

a lab scale) over 60-second intervals. Direct injection of fuel was also used for a

series of skipfired experiments. For this, fuel was supplied by a gasoline-type di-

rect injector (GDI 8-hole, 70 included angle) mounted in the center of the cylinder

head. A positive displacement fuel-flow meter was used to monitor the amount of

fuel supplied.


Figure 6.2: HCCI engine facility schematic.

6.1.2 PLIF System

The PLIF diagnostic system used for the high-load experiments is similar to the

system described in Chapter 5, differing only in overall optical path length and op-

tical components. The PLIF diagnostic system is shown schematically in Figure 6.3.

Excitation at 308 nm was provided by a XeCl excimer laser (Lambda Physik ComP-

exPro 102), providing 200mJ max energy output. The 277-nm pulse was generated

by Raman shifting the 248 nm output of a KrF excimer laser (Lambda Physik Com-

PexPro 102, 400 mJ max output) to the 1st Stokes wavelength in H2. The Raman

cell (custom fabrication) was 112 cm in length with a 37 mm clear aperture, and was

operated at a total pressure of 57 bar. A 600 mm focal length spherical lens focused


Table 6.2: Engine Operating Conditions

Intake Temperature 170-210C

Intake Pressure 100 kPa

Coolant Temperature 100C

Equivalence Ratio 0.32-0.4

Base Fuel Iso-Octane

Fuel Delivery Fully Premixed

Direct Injection

Tracer Seeding [% Liq. Vol.]:

3-Pentanone 17%

Acetone 14%

the 248 nm beam through the Raman cell, while an appropriately positioned 500

mm lens collimated the output. This configuration resulted in approximately 15%

energy conversion efficiency to the 1st Stokes, an improvement from past experi-

ments [44,89]. The resulting 277 nm beam was spatially separated from the residual

pump beam through a equilateral dispersing prism.

A long propagation distance for each wavelength was used to form the sheet width

dimension based on the inherent divergence of the laser outputs. After propagating

across the optical tables near the laser output, the beams were transported to the

engine optical table by two vertical periscopes. Each wavelength was then passed

through a 1 m focal length cylindrical lens to form the beam waist, before being

spatially overlapped with a dichroic mirror coated to reflect 277 nm and transmit

308 nm. Lastly the beams were sent through the ”vertical elevator” assembly that

rotates the beam 90 and elevates the laser sheet to the desired vertical location in

the engine.

The current engine windows were designed such that the inner and outer radius

of curvature is equal. Because of the thickness, the windows acts as a positive

cylindrical lens. To counteract the induced beam convergence, a 200 mm cyl. lens

was added to the optical path 650 mm upstream of the engine input window. The


Figure 6.3: PLIF experimental schematic for high load HCCI experiments

Figure 6.4: PLIF image field of view with valves, injector, and piston window posi-tions superimposed.

resulting laser sheet diverged slightly across the field of view, increasing in width by

approximately 4-5 mm. Final laser sheet dimensions were approximately 43 mm in

width and 0.5 mm in thickness. Typical laser energies per pulse during experiments

were 42-48 mJ for 277 nm and 45-50 mJ for 308 nm. Laser energies were measured

several optical components upstream of the engine, so the actually laser energies

in-cylinder are likely 8-10% lower due to surface reflection losses.

6.2. ENGINE OPERATION 105

The overlapped sheets were aligned nearly parallel to the firedeck, with a small

downward angle to avoid collinear back reflections from the rear engine window. As

shown in the inset in Figure 6.3, the last turning mirror in the vertical setup before

the engine was affixed to a vertical translation stage that allowed the laser sheet to

be adjusted to any desired position below the firedeck. Unless otherwise noted, the

laser sheet was positioned at the mid-plane of the combustion chamber for all image

timings, ranging from 4 to 16 mm below the firedeck.

The resulting fluorescence transmitted through the piston-crown window was

imaged onto the camera using an 85 mm f/1.4 Nikon lens. The intensified CCD

camera (Princeton Instruments, PIMAX2:1003) is equipped with an interline trans-

fer CCD array allowing the collection of both images with an interframe timing of

5µs (2µs minimum). The 1024x1024 pixel CCD array was binned 8x8 on chip to

increase signal level while sacrificing some spatial resolution. The resulting image

spatial resolution was approximately 0.55 mm per pixel, roughly matching the out-

of-plane resolution provided by the sheet thickness. The intensifier gate width for

all experiments was set to 900 ns, and was synchronized to the laser output using

a pulse delay generator (SRS DG535). The delay generator was itself synchronized

with the engine controller permitting image acquisition at any desired image timing.

The camera and laser systems were operated at 10 Hz for all experiments, allowing

one image acquisition per cycle at the 1200 RPM engine speed.

6.2 Engine Operation

Motored experiments with fully premixed seeding for a range of intake temperatures

were used to calibrate the fluorescence dependence on temperature for both excita-

tion wavelengths. More fundamentally, these measurements were used to character-

ize the FQY at elevated temperature and pressure as was presented in Chapter 3.

In addition, premixed motored operation was used to study the fundamental de-

velopment of thermal stratification for a constant intake temperature of 170C. For

all motored experiments the engine was statically preheated to 100 C by electrical


heaters on the cooling water and lubricating oil circulation systems. Prior to data

acquisition, the engine was motored until the measured cylinder wall temperature

reached steady-state, typically 3-5 minutes. During this time the intake mass flow

was adjusted to maintain a 1 bar intake pressure, and the flow of the premixed

fuel/tracer was adjusted to provide an equivalence ratio of 0.4 (based on intake

mass flow).

Thermal stratification was also studied under fired operation to assess any fun-

damental similarities and differences between motored and fired operation. Initial

experiments utilized a 17/3 skipfired (17 motored cycles followed by 3 fired cycles)

to minimize thermal loading on the optical engine. Before firing the engine a similar

warm up procedure was used as above to elevate the cylinder wall temperature prior

firing. Once fuel injection is initiated, the air flow and amount of injected fuel are

adjusted to maintain 1 bar intake pressure and an equivalence ratio of 0.4. Intake

temperature was also adjusted to set combustion phasing based on real-time calcu-

lations of CA50. Data acquisition was initiated once engine operation was stable.

Skipfired operation in this fashion resulting in reasonably steady fired operation,

and sufficiently long run times for data acquisition. Additional premixed fired ex-

periments were completed to eliminate any impact of the direct injection above. For

these experiments the equivalence ratio was lowered to 0.32 to reduce the thermal

loading on the engine for the continuous firing.

6.3 Data Acquisition and Processing

6.3.1 Conventional Data Acquisition

Several conventional (non-optical) diagnostics were used to monitor and character-

ize engine performance. In-cylinder pressure measurements were performed with a

transducer (AVL QC33C) mounted in the cylinder head. The pressure transducer

output was recorded for 50 consecutive cycles at 1/4 CA resolution and was ad-

justed (pegged) to match the intake pressure near BDC where the cylinder pressure

is effectively constant. A camera reference pulse was recorded with pressure to

6.3. DATA ACQUISITION AND PROCESSING 107

provide a cycle-specific indication of PLIF image acquisition. This allowed investi-

gation of relative trends in engine performance and PLIF data on a cycle-to-cycle

basis. For fired conditions, the calibrated pressure was used to calculate the appar-

ent heat-release rate (AHRR), and the 50% burn point (CA50) of the cumulative

AHRR. Calculations were performed for each cycle assuming constant specific heats

and negligible heat transfer [129], and then averaged for the 50 cycles. Real-time

calculations of AHRR and CA50 were used to adjust intake temperature to maintain

CA50 at approximately 367 CA (7 aTDC).

Intake temperatures were measured using thermocouples mounted in the two

intake runners near the cylinder head. Exhaust gas temperature was also monitored

with a similar thermocouple in the exhaust port. Based on these measurements, in-

cylinder BDC temperature was estimated following the procedure provided in [102].

Also, upper cylinder-wall temperatures were inferred from a thermocouple embedded

in the spacer ring approximately 2 mm beneath the surface and 5 mm below the

firedeck. The crank angle (CA) convention for all data presented is 0 <CA<720,

with 360CA corresponding to top dead center (TDC) of combustion.

6.3.2 PLIF Data and Processing

The current study of thermal stratification in HCCI engines includes application

of both single-line and two-line PLIF diagnostics. These measurements are derived

from the same experimental setup as shown in Figure 6.3. For all experiments the

signals from both excitation wavelengths are recorded, and implementation of either

diagnostic strategy is only a matter of post-processing. This provides an easy means

of comparing the diagnostic performance for identical conditions. The theoretical

derivation and post-processing for both PLIF diagnostic variations were described

in Chapter 2.

Three separate image sets were acquired for the quantitative PLIF image pro-

cessing: a data, flat-field and background set. Each data set consisted of 50 images

pairs taken over consecutive cycles at the desired imaging timing. Flat-field (calibra-

tion) images are taken for motored conditions of known temperature and pressure,


and are used to correct for fixed pattern (consistent shot-to-shot) non-uniformities

of the camera and laser sheet. The flat-field images are acquired shortly after the

data images to minimize the impact of laser profile fluctuations (typically within

30-40 seconds). Finally background images were acquired in the motored engine,

with laser emission, but without tracer present to correct for any laser scatter or

fixed pattern background. Both the flat-field and background images are averaged

over the 50 cycles prior to data processing.

The acquisition timing of the flat-field images requires additional discussion.

For the current work, two different flat-field images have been tested. The first

was acquired at BDC under motored conditions, and was verified to have a flat

and homogenous distribution at known in-cylinder conditions. This flat-field image

timing is held constant, and used to process subsequent data for all image timings.

Use of this flat-field provides an absolute temperature measurement at the desired

data image timing. Image processing in this fashion does require a laser attenuation

correction along the beam propagation, as the absorption cross-section and tracer

number density increase during compression. A similar calibration image timing

was applied in Chapter 5.

A second flat-field was derived from the average of the 50 data images. Use of

this flat-field results in measure of the relative fluctuations about the average tem-

perature for a given image timing. Here the average temperature is calculated based

on adiabatic compression of the measured pressure tracer assuming variable specific

heats. The flat-field normalization accurately corrects for laser attenuation (absorp-

tion identical for data and averaged data images), and no additional correction is

needed. However the uniformity of this average derived flat-field must be consid-

ered. If the temperature-induced fluctuations of fluorescence signal are relatively

small and completely random, sufficient averaging would eliminate any variation

producing a homogeneous flat-field. If the fluctuations are not random, a fixed

pattern in the averages would result, and normalization by this image would elimi-

nate the fixed pattern temperature distribution and alter the thermal stratification

statistics slightly. Comparison of the BDC flat-field and data-averaged flat-field (at-

tenuation corrected) show minimal differences. In addition, temperature statistics

6.3. DATA ACQUISITION AND PROCESSING 109

derived from the processed temperature data are very similar using either flat-field,

with only a slight difference associated with small errors in the attenuation correc-

tion. A similar flat-field normalization was applied by Dec et al. [71], who found

that the averaged data images were very uniform (no detectable repeating pattern)

and would not impact the measured thermal stratification. This average derived

flat-field is only applicable to the thermal stratification study where fluctuations are

expected to be random.

The main focus of the current study is to quantify the amount and evolution

of thermal stratification during compression. This is related more to the relative

fluctuations in temperature, making absolute measurement of temperature less crit-

ical. Therefore, the data-averaged flat-field will be used for a majority of the image

post-processing, and will be indicated by the relative temperature display (± 50 K).

Processing with the alternative flat-field provided nearly identical results. For the

fired measurements of residual gas mixing during intake and early compression, the

temperature distribution is not random, and the motored BDC temperature must

be used. These measurements can be differentiated by the absolute temperature

scale used for image presentation.

6.3.3 PLIF Data Processing

6.3.4 Photophysics

The accuracy and precision of quantitative PLIF measurements is highly dependent

on the photophysical data or model used to interpret variation in fluorescence sig-

nal. The absorption cross-section data is based on fit parameters summarized in

Appendix A. The FQY data was determined based on motored calibration exper-

iments performed in this engine over a range of intake temperatures. The results

of these calibration experiments were presented in Chapter 3. The current process-

ing routine utilizes FQY data fits at each image timing, instead of a tuned FQY

model as was previously employed in Chapter 5. This technique is assumed to be


more accurate. The in-cylinder temperature range of the FQY calibration measure-

ment conditions were carefully selected to bound the expected temperature range

for subsequent experiments, in an effort to avoid errors due to data fit extrapolation.

6.4 PLIF Measurement Uncertainty

6.4.1 Accuracy

Absolute temperature accuracy was initially assessed by comparing the measured

PLIF temperature with estimated temperatures assuming adiabatic compression

of the measured in-cylinder pressure trace. This temperature calculation method

indirectly accounts for global heat transfer through the measured pressure trace,

but assumes an adiabatic core region. Comparison results are shown in Figure 6.5,

for motored engine operation with a nitrogen intake temperature of 170C and

1 bar manifold pressure. The average PLIF temperatures were calculated over a

central 30x30 pixel subregion, and averaged over the 50 image sequence. The PLIF

derived temperatures are in excellent agreement with the adiabatic temperature

calculations for all diagnostic variations, and are within 1% throughout compression.

This result is not surprising given that the FQY fit data used for image processing

was generated from engine calibration experiments assuming the same adiabatic

temperatures within the cylinder core. Therefore, the temperature comparison in

Figure 6.5 does not completely characterize the absolute accuracy, but does confirm

the consistency of the FQY fits and image processing technique.

The absolute accuracy is mainly dominated by the adiabatic core assumption

used for engine FQY calibration, and is difficult to assess. Subsequent temperature

images (e.g. Figure 6.7) indicate that the core interrogation region is not com-

pletely adiabatic near TDC, as evidenced by the cold gas pockets within the field of

view. Because these pockets are randomly dispersed across the cylinder volume, the

average temperatures are likely somewhat lower than the adiabatic temperatures.

Assuming the hottest regions within each temperature image are effectively adia-

batic, the measured temperature spread provides some indication of error induced

6.4. PLIF MEASUREMENT UNCERTAINTY 111

300 310 320 330 340 350 360600

700

800

900

1000

Crank Angle [°CA]

Tem

per

atu

re [

K]

277 nm(±2% error bars)308 nm277 / 308 nmAdiabatic Comp.

Premixed

N2 Intake

Pin

=1 barT

in=170°C

φ=0.4

Figure 6.5: Measured absolute temperature for motored engine conditions with N2

intake temperature of 170C and 1 bar manifold pressure

by the adiabatic assumption. At 360CA, the highest temperature regions are typ-

ically 20-25 K above the average, meaning the measured average temperatures are

likely 20-25 K low at 1000 K. This error decreases for earlier image timings as the

adiabatic assumption is assumed to be more accurate at lower temperatures. Based

on this, the absolute accuracy is conservatively estimated to be ±2.5% throughout

compression, and is represented in the error bars in Figure 6.5. It should be noted

that the errors associated with the adiabatic assumption will only affect the absolute

value of temperature and will have little affect on the measured fluctuations about

the average. The accuracy could potentially be improved by altering the FQY cal-

ibration measurements to only consider the higher temperature regions where the

adiabatic assumption is more accurate. However, the main focus of the current

work is to assess the evolution and distribution of thermal stratification, making the

highly accurate absolute temperatures measurements less critical.


6.4.2 Precision

Measurement precision (spatial) is critical when studying thermal stratification as

this indicates the minimum detectable temperature fluctuation for a single-shot im-

age. If the precision limits are much greater than the actual in-cylinder temperature

fluctuations, resolution of the coherent structures will be poor and any statistical

analysis will be difficult. The thermal stratification for fully premixed HCCI is

expected to be relatively small, motivating the development of highly sensitive di-

agnostics. The theoretical temperature precision was investigated in Chapter 3 for

excitation wavelength optimization. This analysis indicated that the main factors

controlling the measurement precision were the image signal-to-noise ratio (SNR),

the inherent tracer temperature sensitivity, and the random fluctuations in laser

sheet profile. Similar precision calculations are provided here, but have been up-

dated to include the engine FQY measurements of Chapter 3, and actual fluorescence

signal levels achieved in HCCI engine experiments. The fluorescence signal was mea-

sured in the motored engine over a range of image timings (305-360) during the

compression stoke, for an intake temperature of 170 C. The measured cylinder pres-

sure trace and calculated temperature during compression are shown in Figure 6.6a.

The resulting image SNR was determined by a camera calibration, relating digitized

read out signal and SNR over the dynamic range of the camera. Results and further

discussion of the camera calibration are provided in Appendix C. The single-line

precision was calculated using Equations 2.13-2.15, while the two-line precision was

calculated applying Equations B.5-B.6. Precision calculations were performed for

both acetone and 3-pentanone for comparison.

The semi-empirical temperature precision results are presented in Figure 6.6b,

and provide a substantial amount of insight and information. The precision for most

diagnostic schemes varies significantly throughout the engine cycle, changing by a

factor of two or more in some cases. This variation is not unexpected given the large

span of in-cylinder conditions, but further emphasizes the importance of diagnostic

optimization for the intended range of experimental conditions. Considering the two-

line results first, the 3-pentanone based diagnostic provides the best performance at

6.4. PLIF MEASUREMENT UNCERTAINTY 113

300 310 320 330 340 350 3600

5

10

15

20

25

30

Crank Angle [°CA]

Pre

ssu

re [

bar

]

300 320 340 360500

600

700

800

900

1000

1100

Tem

per

atu

re [

K]

Premixed

N2 Intake

Pin

=1 barT

in=435 K

φ=0.4

(a) In-cylinder conditions

300 310 320 330 340 350 3600

10

20

30

40

Crank Angle [°CA]

Tem

per

atu

re P

reci

sio

n (

1σ)

[K]

3P 277 3P 308 3P 277/308

AC 277 AC 308 AC 277/308

(b) Temperature Precision

Figure 6.6: (a) In-cylinder pressure and temperature (calculated) for the baselineHCCI operating condition. (b) Temperature precision of single-line and two-linediagnostics of 3-pentanone ad acetone, calculated for baseline conditions

lower temperatures and pressures (early image timings) and progressively degrades

towards TDC. The increase in temperature uncertainty is due to a combination

of decreasing 277 nm signal, and reduced temperature sensitivity of the ratio of

photophysical parameters (Rpp). Conversely, highest acetone uncertainty occurs

early in the cycle, reaches a minimum (340 CA) and then increases slightly towards

TDC. This is a result of initially low fluorescence signal and sensitivity that increases

towards TDC. The performance cross-over point between acetone and 3-pentanone

is approximately 340 CA (890 K, 16 bar).

As shown in Figure 6.6b, single-line temperature precision is much improved over

the two-line technique (308 nm excitation of acetone excepted). The performance

improvement at high temperatures (late compression) is most significant, where the

temperature precision is improved by a factor of 4-5. Explanation for superior single-

line diagnostic performance are threefold. First, single-line temperature is derived

from one single-shot image, while the two-line technique involves the ratio of two

single-shot images (both are normalized by an averaged flat-field image with high

SNR, and does not contribute to the noise content). The resulting two-line ratioed

image will have a higher SNR, based on the square root of the sum of squares of SNR


for each image, leading to higher temperature precision. Secondly, the temperature

sensitivity of the two-line technique is inherently less than the single-line sensitivity.

Ketones generally exhibit decreasing fluorescence with temperature (per unit mole

fraction) at almost all wavelengths due to the increasing non-radiative decay rate

and thus decreasing FQY [75,79]. Ratioing these signals only reduces the sensitivity,

thus increasing the measurement uncertainty. Lastly, the single-line technique is

sensitive to density gradients through the inverse temperature dependence of PPs.

This density term is eliminated for the two-line technique through the signal ratio.

It should be stressed however that the two-line technique is more versatile, and can

be applied to systems with varying temperature and tracer concentration, while the

single-line technique is limited to compositionally homogenous mixtures.

Among the potential single-line variations, 277 nm excitation of 3-pentanone

provides the best overall performance, with temperature uncertainties of 5 K or

below throughout compression. Excitation of 3-pentanone at 308 nm also provides

excellent performance at higher temperatures. The high simultaneous performance

of both 3-pentanone excitation wavelengths at high temperature provides a unique

ability to acquire two temporally or spatially shifted temperature measurements

within a single engine cycle. This capability will be investigated further in Sec-

tion 6.6.3. Acetone excitation at 277 nm also provides good performance, while the

308 nm performance at low temperatures is inadequate. Based on these results,

all subsequent engine studies will focus on the application of 3-pentanone based

diagnostics at 277 and 308 nm. The theoretical uncertainty analysis in Chapter 2

indicated similar overall trends, but the absolute magnitude in temperature precision

was not exact due to over-predicted fluorescence signals and SNR, and inaccuracies

in the FQY models used for calculation. Despite this, the resulting optimized line

selection was the same for both calculations.

6.5. MOTORED ENGINE THERMAL STRATIFICATION 115

6.5 Motored Engine Thermal Stratification

Several mechanisms can contribute to the development of thermal stratification

including wall heat transfer and turbulent convection, direct fuel injection, and re-

tained residuals. Wall heat transfer is expected to be the most dominant. As the

in-cylinder temperatures begin to rise during compression, the temperature differen-

tial between the cylinder wall and bulk-gas provide a driving force for heat transfer.

This cooler near-wall fluid can subsequently convect into the cylinder core, resulting

in significant thermal stratification throughout the charge.

Direct fuel injection can further increase thermal stratification through evap-

orative cooling, and variable compression due to localized thermodynamic gamma

variation with fuel concentration. In addition, any retained residuals from a previous

fired cycle can also add to thermal stratification, depending on the mixing efficiency.

For the premixed motored experiments considered in this section, only the wall heat

transfer mechanism is active (no DI fuel or combustion). Other mechanisms will be

discussed further in the fired engine results section.

In-cylinder temperature distributions were measured using the single-line 3-

pentanone diagnostic for motored engine operation with a 170 C and 1 bar intake.

A pure nitrogen intake stream was used to suppress combustion, however premixed

fuel was added at an equivalence ratio of 0.4 to better represent the ratio of specific

heats (gamma) of the mixture and the resulting compression temperatures. These

conditions are identical to those used for the measurement precision assessments

above, and the pressure and temperatures profiles are represented in Figure 6.6a.

Because these conditions are run fully premixed with no hot retained residuals (mo-

tored), the temperature distribution is expected to be homogenous during early

compression. Thermal stratification induced by wall heat transfer will not be signif-

icant until the gas temperature is well above the wall boundary temperature, and

even then additional time is required for fluid motion to convect the cooler near-wall

fluid into the core region of the charge. As a result, the TS development is thought

to predominately occur in the latter portion of compression.

To assess the development of TS, a sequence of single-shot temperature images


from 305-360 CA are presented in Figure 6.7. Each image was selected to represent

the average extent of temperature fluctuations for that image timing, and are plotted

in terms of temperature difference about the average (∆T). A constant image color

scale of ±50 K was used for easy comparison of temperature fluctuations at each

timing. As expected, the measured temperature distribution early in compression

(305 - 320 CA) is essentially homogeneous. Initial emergence of localized hot and

cold pockets is seen at 330 and 340CA, followed by a progressive increase in TS

towards 360CA. Increase in TS during this time results from an increase in both the

frequency of the hot and cold regions, and the amount overall temperature difference

between these regions. These observations are consistent with previous temperature

measurements in this engine using a toluene-based, single-line PLIF diagnostic [108],

and supports related KIVA simulations of a matching all-metal engine [63].

It is important to note that the small variations in temperatures depicted in

Figure 6.7 would be difficult to discern without a diagnostic scheme with sufficient

performance. A visual demonstration of the superior resolving power of the single-

line technique is shown in Figure 6.8 for the 360CA image timing. Here single-shot

277 and 308 nm single-line temperature are compared with the corresponding two-

line 277/308 nm result processed from the same data images). The temperature

distribution between both single-line measurements is in good agreement, confirm-

ing the consistency of the FQY data used for calibration. Both variations provide

low temperature uncertainty on the order of 4 K, and the thermal stratification

structures are well resolved. This is in contrast to the two-line results, Figure 6.8c,

which has a substantially higher uncertainty of 25 K. Although the general hot and

cold structures can be observed, the increased measurement noise masks much of

the fine structure. In addition, the high noise level makes statistical analysis of the

two-line results difficult and inaccurate. As a result, single-line measurements have

been applied whenever possible (i.e. homogeneous tracer mole fraction distribution).


∆ T=T−TAVE

−50 −40 −30 −20 −10 0 10 20 30 40 50

(a) 305 CA (b) 320 CA (c) 330 CA

(d) 340 CA (e) 345 CA (f) 350 CA

(g) 355 CA (h) 360 CA

Figure 6.7: Single-shot temperature images of TS development during main com-pression of motored engine. Diagnostic - 3-Pentanone, single-line 277 nm


∆ T=T−TAVE

−50 −40 −30 −20 −10 0 10 20 30 40 50

(a) 277 nm (b) 308 nm (c) 277/308 nm

Figure 6.8: Comparison of single-line and two-line image quality

6.5.1 Motored Stratification Statistics

To facilitate a quantitative characterization of thermal stratification, a number of

statistical parameters have been employed to analyze the PLIF data. Standard

deviation has been selected as a metric to characterize the magnitude of temperature

fluctuations for each image timing. The standard deviation was calculated over

all active pixels (masked image area shown in Figure 6.8) within each image, and

averaged for the 50 image sequence. A statistical correction was also applied to

correct for the impact of measurement uncertainty on calculated image statistics.

Despite the good performance of the single-line diagnostics, evidence of measurement

noise can still be observed through the “speckle” or graininess that is particularly

evident in the 305 CA images. Although these shot-noise induced fluctuations

are small, they can have a large impact on statistics if not properly accounted for.

Fortunately the temperature uncertainty has already been well characterized, as

discussed in Section 6.4.2 and seen in Figure 6.6.

Assuming the measurement uncertainty is random and independent of the mea-

sured temperature field, it can be subtracted in quadrature from the averaged im-

age standard deviation, providing a better indication of the physical temperature

fluctuations in-cylinder. Without this correction, the varying noise content would


300 310 320 330 340 350 3600

5

10

15

Crank Angle [°CA]

Tem

per

atu

re S

td. D

ev. (

1σ)

[K]

Uncorrected Std. Dev.Meas. UncertaintyCorrected Std. Dev.

Figure 6.9: Demonstration of measurement uncertainty correction, comparing cor-rected and uncorrect temperature standard deviation for single-line 3-pentanone at308 nm excitation.

fictitiously alter the trends of thermal stratification, and would make comparison

of results from differing diagnostics and parametric studies difficult. A demonstra-

tion of the impact of this uncertainty de-convolution is shown in Figure 6.9, for the

single-line 3-pentanone measurement at 308 nm. Here the uncorrected standard de-

viation at early image timings (305-320CA) is dominated by measurement noise, as

indicated by the nearly equivalent uncorrected standard deviation and measurement

uncertainty. Upon deconvolution, the corrected standard deviation more accurately

follows the qualitative TS observations from images above. The impact of the noise

correction decreases towards TDC as both the measurement uncertainty improves

and the physical TS increases. This measurement uncertainty correction has been

applied to all subsequent standard deviation data to best quantify the TS develop-

ment.

The uncertainty-corrected temperature standard deviations are shown in Fig-

ure 6.10 for the baseline motored compression conditions. Data for 3-pentanone at

277 and 308 nm as well as acetone data at 277 nm have been included for comparison.


300 310 320 330 340 350 3600

2

4

6

8

10

12

14

Crank Angle [°CA]

Tem

per

atu

re S

td. D

ev. (

1σ)

[K]

3P 277 nm3P 308 nmAC 277 nm

Premixed

N2 Intake

Pin

=1 barT

in=170°C

φ=0.4

Figure 6.10: Temperature standard deviation (corrected) calculated from single-shot temperature images for both 3-pentanone (3P) and acetone (Ac) for differentexcitation wavelengths.

The standard deviations for all measurement techniques are in good agreement, par-

ticularly for later image timings, and confirm the consistency of the measurements

and noise correction. The slightly larger scatter in measurements at 305 and 320

CA is due to the increased error in noise correction when uncertainties are on the

order or larger than the physical temperature fluctuations. Overall, the qualitative

trends seen in the temperature images of Figure 6.7 are well represented. The stan-

dard deviation for all techniques are near 0 K at 305 and 320 CA, consistent with

the minimal stratification seen in images for these timings. The standard deviation

then progressively increases toward TDC, achieving a maximum of approximately

10 K at 360 CA. These general TS trends are consistent with single-line toluene-

based PLIF temperature measurements of Dec et al. [71] previously performed in

the same optical engine.

In an effort to characterize the spatial scale of the thermal stratification, a sim-

plified calculation of the cold region effective diameter has been performed. The cold

regions or “pockets” have been selected for study as they can reduce the pressure


(a) Single-shot tempera-ture

(b) Binary cold pocket

Figure 6.11: Demonstration of image binarization and pocket detection (b) for asingle-shot temperature distribution (a) acquired in motored engine.

rise rate through sequential auto-ignition, and are important for operation near the

high-load HCCI limit. To calculate the effective diameter, each single-shot tempera-

ture image was first binarized to highlight the cold pockets as seen in Figure 6.11. A

threshold of 10 K below the average temperature at each image timing was selected

for the binarization criterion. Next a pixel connectivity image processing routine was

applied to identify each object and determine the corresponding cold pocket area.

Sample results of the object detection scheme are presented as the green outlined

elements in Figure 6.11b. Lastly, the cold pocket diameter was calculated assuming

a circular cross-section of the calculated area. In actuality, the cold structures have

an irregular shape, and a more rigorous auto-correlation analysis would be required

to completely define the spatial scale, but has not been completed here. In addi-

tion, the effective diameter only considers the projected area within the probe laser

sheet, but is still thought to represent the general evolution of cold regions during

compression.

The frequency of cold pockets at each image timing was also calculated, based

on the cumulative sum of cold regions identified in the 50 image sequence. To

minimize the influence of small-scale measurement noise, only cold pockets with an

area greater than or equal to 3 mm2 were considered. The cold pocket effective

diameter and frequency during motored compression are shown in Figure 6.12. The

effective diameter shown here, is derived from the average of the top 5%.


300 310 320 330 340 350 3600

200

400

600

800

1000

Crank Angle [ °CA]

Col

d P

ocke

t Fre

quen

cy [a

.u.]

300 320 340 3600

2

4

6

8

10

Effe

ctiv

e D

iam

eter

[mm

]

Premixed

N2 Intake

Pin

=1 barT

in=170°C

φ=0.4

Tthres

=Tave

−10 K

Figure 6.12: Evolution of cold pocket frequency and effective diameter during mo-tored compression at 170C intake temperature. Statistics derived from single-line3-pentanone measurements at 277 nm.

6.6 Fired Engine Thermal Stratification

The TS studies described above were restricted to motored operation as it provided a

well-controlled measurement environment for initial diagnostic studies. The absence

of combustion in these studies was considered acceptable given that TS is formed

prior to combustion and is not directly influenced by subsequent chemical reactions.

However, these studies raise the question of exactly how the TS will vary when

transitioning to fired operation. Specifically, the presence of residual gases is a key

difference between motored and fired operation that could impact the relative TS

behavior. The current engine configuration is characterized as low-residual HCCI

due to the conventional valve timing and low residual gas fraction (4-6%). Additional

hot residuals are not intentially retained to enhance auto-ignition as was done in

Chapter 5. However, the small quantity of retained residuals could increase the TS

during compression if the charge mixing is incomplete. This is important because

any additional thermal stratification that persists near TDC will further reduce the

PRR and could alter the combustion phasing.

6.6. FIRED ENGINE THERMAL STRATIFICATION 123

6.6.1 Residual Mixing

This study of the residual mixing process was completed in two phases. First,

the two-line PLIF diagnostic was utilized to provide simultaneous temperature and

mole fraction distributions to directly visualize the residual mixing process. Second,

single-line PLIF measurements of temperature during the remainder of compression

were employed to characterize the overall TS development. Using these single-line

results, the impact of residual gas mixing was indirectly studied by comparing TS

results for cycles during the skipfired sequence with and without hot residuals.

The residual mixing study was performed using a 17-3 skipfired sequence (17

motored cycles followed by 3 fired cycles), as seen in the pressure traces in Fig-

ure 6.13. The skipfired sequence was selected to reduce the thermal loading on the

optical engine, and permitted prolonged, steady operation at the high-load equiv-

alence ratio of 0.4. Direct fuel injection occurred during cycles 18-20 only and

ensured skipfired operation. The three sequential fired cycles were chosen to en-

sure near steady-state retained-residual temperature and quantity. The importance

of using three fired cycles is reflected in the peak pressure of the fired cycles in

Figure 6.13, which increases significantly between cycles 18-19. Here the residual

temperature increases from cold air to hot combustion products which advances the

combustion phasing and thus increases the peak pressure. The small peak pres-

sure difference between cycle 19 and 20 confirms that near steady-state operation is

achieved. The in-cylinder temperatures and pressures for cycle 20 of the skipfired

sequence are shown in Figure 6.14. The core temperature was estimated based on

the measured pressure trace, assuming adiabatic compression with variable specific

heats, and is identical to the technique used for the FQY calibration experiments.

The open circles in Figure 6.14 correspond to the image timings used for the current

study. These temperature and pressure profiles are nearly identical to those for the

premixed motored and continuously fired experiments, with only a small variation

in magnitude.


Cycle 1 Cycles 2−16 Cycle 17 Cycle 18 Cycle 19 Cycle 20 Cycle 15

10

15

20

25

30

35

40

45

Cyl

inde

r P

ress

ure

[bar

]

MotoredFired

Figure 6.13: Measured cylinder pressure tracers for 17-3 skipfired operation.

Direct Imaging of Residual Gas Mixing

Simultaneous two-line temperature and air mole fraction measurements were per-

formed during intake and early compression to track the mixture evolution. Ap-

plication of the two-line technique was required during this portion of the engine

cycle as substantial compositional stratification is expected, particularly during in-

take stroke. The tracer was fully premixed with the intake air to provide a direct

measurement of air mole fraction, while pure iso-octane was directly injected with

a start of injection (SOI) of 80 CA. All images contained in the residual mixing

study were taken with a laser sheet positioned 16 mm below the firedeck.

Sample single-shot temperature and air mole fraction image pairs acquired dur-

ing the intake stroke from 20-320 CA are shown in Figure 6.15. Note that the

temperature and mole fraction color scale change for the latter images to better

emphasize the stratification. As expected, the earliest images show a high degree

of stratification in both temperature and mole fraction, as the colder inducted air

mixes with the hot retained residuals from the previous combustion event. The im-

age pairs exhibit good spatial correlation and exhibit an inverse relationship between

temperature and air mole fraction, where high-temperature regions correspond to


300 310 320 330 340 350 3600

5

10

15

20

25

30

Crank Angle [°CA]

Pre

ssur

e [b

ar]

300 320 340 360500

600

700

800

900

1000

1100

Tem

pera

ture

[K

]

SkipfiredP

in=1 bar

Tin

=198°C

φ=0.4

Figure 6.14: In-cylinder conditions for fired studies. The core temperature is esti-mated from measured pressure trace assuming adiabatic compression with variablespecific heats. Data points correspond to PLIF image timings.

lower air mole fraction (higher residuals) and vice versa. Additionally, the residual

gas mole fraction is systematically higher in the upper left corner of the images,

corresponding to the exhaust valve orientation within the field of view as shown in

Figure 6.4. As seen in Figure 6.15, the amount of stratification rapidly decreases

as image acquisition progresses through the intake stroke, and by 100 CA (middle

of intake event) only a small fraction of the initial stratification persists. Mixing

continues through intake valve closing (IVC) and into early compression but is less

dramatic.

By 220 CA the residual mixing process is essentially complete, and the tem-

perature and air mole fraction distributions are effectively homogeneous. Later in

compression, thermal stratification begins to develop, as seen by the hot and cold

regions in the 305 CA and 320 CA images. These variations are not due to hot

residual gases, as the air mole fraction distribution is homogeneous (see images)

and remains homogeneous for the rest of the compression stroke. Instead, these


temperature fluctuations presumably result from near-wall heat transfer and con-

vection [71]. The observed onset of TS development, is similar to the motored engine

data shown in Figure 6.7. The results of the two-line residual-mixing study have two

main implications. First, the residual mixing process for low-residual operation is

fast, so it is completed by early compression, and it is not likely a significant source

of TS near TDC. Second, because of the homogeneous composition after 220 CA,

single-line PLIF temperature measurements can be applied without significant error

due to mole fraction inhomogeneities. This is particularly useful given the dramatic

improvement in measurement precision for the single versus two-line techniques (5

K versus 20 K respectively) as previously demonstrated in Figure 6.6b. As a result,

additional single-line PLIF studies of TS development in the fired HCCI engine were

performed, as described below.

TS Development in Fired Engine

Single-line temperature results during compression for fired operation are presented

in Figure 6.16. These images correspond to the same skipfired conditions shown

above for the residual mixing study, with pure tracer seeded into the intake air

stream and iso-octane fuel directly injected early in the intake stroke (SOI=80

CA). The DI fueling does not impact the temperature measurements given the

small fuel mole fraction for the conditions tested. The fired image sequence has

been truncated at 350 CA (instead of TDC) as the onset of tracer decomposi-

tion is expected to occur during the early reactions after this crank angle. The

onset of decomposition has been indirectly validated through PLIF images of early

formaldehyde formation. Previous studies have demonstrated that formaldehyde

production can be a good indicator of tracer removal [89, 130]. A series of exper-

iments were performed without tracer seeding to image formaldehyde fluorescence

using 308 nm excitation (not shown). Images acquired for progressively advancing

image times near TDC indicated the onset of formaldehyde production to be after

350 CA, bounding the window for quantitative PLIF measurements. As shown in

Figure 6.16, small temperature non-uniformities are initially seen at 305 CA and


Temperature [K]

400 500 600

Air Mole Fraction [%]

0 50 100

Temperature [K]

400 500 600

Air Mole Fraction [%]

0 50 100

620 670 720

60 80 100 120

720 770 820

60 80 100 120

(a) 20°CA

(b) 40°CA

(c) 60°CA

(d) 100°CA

(e) 160°CA

(f) 220°CA

(g) 305°CA

(h) 320°CA

Figure 6.15: Single-shot temperature (left) and air mole fraction (right) image pairsequence showing evolution of residual gas mixing during the intake and early com-pression for fired HCCI operation. Diagnostic: two-line 277/308nm, 3-pentanone.


320 CA, and progressively increase in both magnitude and frequency during the

remainder of compression. By 350 CA a significant amount of thermal stratifica-

tion is observed, with peak-to-peak temperature fluctuations on the order of 25 K.

These large temperature variations presumably lead to sequential auto-ignition, and

are critical for high-load operation. A comparison with the motored engine images

in Figure 6.7 and those in Ref. [71] shows that the development of TS is similar for

fired and motored operation.

The 17-3 skipfiring sequence provides a unique opportunity to directly study

the impact of residuals on TS development. As previously mentioned, the 3rd fired

cycle (cycle 20) has a near steady-state amount of residuals due to the previous

two fired cycles. The first fired cycle (cycle 18) however, is preceded by a motored

cycle and does not contain any hot combustion residuals. Therefore, comparison of

images and statistics from cycle 18 and 20 can elucidate any fundamental impact

of hot residuals on TS. This comparison is particularly useful as the boundary wall

temperature is effectively constant for both cycles, and will not impact the relative

trends in TS. Single-line temperature measurements have been performed in both

cycle 18 and cycle 20 within the same skipfired sequence. For better quantitative

comparison, the temperature standard deviation was calculated for each individual

image and averaged over a 50 image series. A measurement uncertainty correction

was applied to the calculated standard deviation to de-convolve the physical tem-

perature fluctuations and the measurement precision. Without this correction, the

measurement noise would fictitiously increase the apparent stratification and the

calculated statistics would not reflect the actual in-cylinder temperature variation.

To apply this correction, the measurement precision was first estimated assuming

the dominant sources of measurement uncertainty arise for the image signal-to-noise

ratio (SNR) and the random laser energy profile fluctuations. Assuming these vari-

able are random and independent, their effect will combine in quadrature (square

root of the sum of squares), and the induced temperature precision can be deter-

mined using Equation 6.1, where ∆T is the temperature precision [K], SNR is the

image signal-to-noise ratio, E is the laser profile fluctuation [%], PPs is the single-line

photophysical parameter (defined in Equation 2.3) evaluated at the corresponding


∆ T=T−TAVE

−50 −40 −30 −20 −10 0 10 20 30 40 50

(a) 305 CA (b) 320 CA (c) 330 CA

(d) 340 CA (e) 345 CA (f) 350 CA

Figure 6.16: Single-shot PLIF temperature sequence of TS development for skipfired(cycle 20) HCCI engine operation. Diagnostic - single-line 277 nm, 3-pentanone.Engine conditions: skipfired, φ=0.4, Tin=198C, Pin=100 kPa, 14% 3-pentanone iniso-octane.


temperature and pressure, and ∂T∂PPs

is the relative change in temperature with the

single-line photophysical parameter. This equation was derived from the detailed

uncertainty analysis of the single-line PLIF technique presented in Chapter 2 (see

Equations 2.13-2.14).

∆Tmeas prec =∂T

∂PPs

((1

SNR

)2

+ ∆E2

) 12

PPs(T, P ) (6.1)

∆Tphy =(∆T 2

img std.dev. −∆T 2meas prec

) 12 (6.2)

To determine the image SNR, a separate camera noise characterization has been

completed to relate the SNR to measured fluorescence signal. This camera charac-

terization is presented in Appendix C. Here SNR was measured as a function of light

intensity to allow easy calculation of SNR based on the average fluorescence signal

measured in each image [127]. The laser profile fluctuation has previously been char-

acterized for these laser systems based on shot-to-shot profile variations measured for

a homogeneous distribution, and was found to be approximately 1% for the excimer

pump laser used for the current study. The photophysical parameter and partial

derivative in Equation 6.1 were calculated using the engine FQY quadratic fits and

absorption cross-section data described in the tracer photophysics section. Finally,

the temperature precision calculated with Equation 6.1 is subtracted in quadrature

from the image standard deviation (∆ Timg std.dev.) using Equation 6.2, providing a

metric for the physical temperature fluctuations in-cylinder (∆Tphys). All tempera-

ture standard deviations presented here have been corrected in this manner.

Comparison of the noise-corrected temperature standard deviation for cycle 18

and cycle 20 is shown in Figure 6.17. The close agreement in temperature standard

deviation for these cycles indicates that combustion residuals have little to no impact

on TS development, for low-residual HCCI operation with conventional valve timing.

This fact is consistent with the two-line visualization of residual mixing discussed

above, and it implies that any differences in TS development between motored and

fired operation is not related to the presence of combustion residuals.


300 310 320 330 340 350 3600

5

10

15

20

Crank Angle [°CA]

Tem

pera

ture

Std

. Dev

. [K

]

Cycle 20 − w/ ResidualsCycle 18 − w/o Residuals

Figure 6.17: Noise-corrected temperature standard deviation for cycle 18 (no hotresiduals) and cycle 20 (hot residuals). Diagnostic: single-line 277nm, 3-pentanone.Engine conditions: skipfired, φ=0.4, Tin=198C, Pin=100 kPa, 14% 3-pentanone iniso-octane.

6.6.2 Comparison of Motored and Fired TS

Comparison of results for motored and fired operation is helpful in assessing any

fundamental differences or similarities in TS development. It could also be helpful

for adjusting operating conditions of future motored data to ensure that they are

representative of fired conditions. Because the mixing study above showed minimal

impact of residuals for low-residual HCCI operation, any added differences in TS

can be attributed to other mechanisms. The motored versus fired discussion will be

given in two parts. First, differences in TS between early DI and premixed fueling are

considered. Second, direct comparisons between premixed motored and premixed

fired results are presented to investigate the influence of cylinder-wall temperature.

Impact of Early Direct Injection on TS

Previous studies have shown that early direct injection and fully premixed fueling re-

sult in nearly identical combustion performance [64], indicating that both techniques

provide an effectively homogeneous fuel distribution. As a result, the early DI used

for skipfired experiments was expected to have minimal impact on TS development.

However, comparison of temperature standard deviation results for skipfired (early


DI) and premixed motored conditions with identical intake temperatures exhibit

differences in the magnitude of TS, as seen in Figure 6.17. Here the skipfired TS is

systematically 2-3 K higher than premixed motored operation, indicating that the

early DI may impact TS development more than previously thought.

In order to test TS sensitivity to direct injection, a series of motored engine

experiments with either DI or premixed fueling were performed. Statistical results

from this study are shown in Figure 6.18, and they indicate that direct fuel injection

can result in higher TS during compression. This difference in TS between DI and

premixed is similar to that seen in the skipfired / premixed comparison, and likely

means that the difference in motored and skipfired statistics is mainly a result of

the direct injection. The systematic increase in standard deviation with direction

injection indicates that fuel/charge-gas mixing is not complete despite similar en-

gine performance noted in previous studies [64]. Apparently, a small amount of fuel

stratification persists which increases TS through evaporative cooling and variable

compression resulting from localized variation in the thermodynamic gamma (ratio

of specific heats) of the mixture. This slight fuel stratification has been confirmed

with supplemental fuel mole fraction measurements (not shown) made under iden-

tical in-cylinder conditions. These results showed some amount of fuel stratification

that persisted towards TDC despite the very early start of injection at 80 CA.

Impact of Wall Temperature on TS

To eliminate the problems associated with direct injection described above, single-

line temperature measurements were performed for fired operation with fully pre-

mixed fueling. The engine was continuously fired, since premixed operation does not

provide a means for skipfired operation. These continuously fired experiments were

performed with a reduced equivalence ratio of 0.32 (compared to 0.4 for previous

data) to avoid high thermal loading on the optical engine which can lead to contin-

uously advancing of combustion phasing. Complementary single-line temperature

measurements for motored operation with identical intake temperature and fueling

were performed for comparison. Noise-corrected temperature standard deviations


300 310 320 330 340 350 3600

5

10

15

20

Crank Angle [°CA]

Tem

pera

ture

Std

. Dev

. [K

]

PremixedDirection Injection

Figure 6.18: Impact of direct fuel injection on measured temperature standard de-viation for motored engine operation. Engine conditions are identical to skipfiredexperiments of Figure 6.16. Diagnostic: single-line 277nm, 3-pentanone. Engineconditions: skipfired, φ=0.4, Tin=198C, Pin=100 kPa, 14% 3-pentanone in iso-octane.

for the motored and fired operation at these conditions are compared in Figure 6.19.

Examination of Figure 6.19 reveals that for premixed operation the magnitude of

TS for motored operation is now systematically higher than fired operation for these

premixed conditions. One potential source of this difference is the internal surface

temperatures. The high gas temperatures achieved during combustion naturally

increase the wall temperature, especially for continuous fired operation. This is

particularly important for optical engines, which have less effective cooling systems

due to the cylinder windows and bowditch piston assembly. The increased surface

temperature for fired operation reduces the temperature differential driving near-

wall heat transfer, which could ultimately reduce the thermal stratification. For the

current study, the measured wall temperature increases from 127C to 141C between

motored and continuously fired operation respectively.

To assess the impact of wall temperature, additional single-line measurements

were performed for fired operation with the coolant temperature reduced to 60C,

compared to 100C for all other measurements. This reduced the wall temperature

for the fired operation to 121C (down from 141C), which is close to the 127C wall

temperature for motored operation (with 100C coolant). Figure 6.19 compares the


temperature standard deviation results for these data. As expected, the reduced

coolant and wall temperatures result in higher TS that is closer to, but does not

exactly match, the premixed motored data. These measurements confirm the sen-

sitivity of TS to boundary wall temperature, and provide an explanation for the

standard deviation differences between motored and fired operation. A potential

reason for the remaining difference in TS between motored and fired (low coolant)

data is that the piston-crown surface temperature, which is not strongly affected by

the coolant, is presumably still at a much higher temperature for fired operation.

It was initially thought that the difference in wall temperature would play a minor

role in TS development, given the already large temperature differential between

bulk-gas temperature and wall temperature late in compression. However, based

on the temperature statistics shown in Figure 6.19, changes in wall temperature of

only 20C can significantly impact TS development.

300 310 320 330 340 350 3600

5

10

15

20

Crank Angle [°CA]

Tem

pera

ture

Std

. Dev

. [K

]

Motored − T

cool=100°C, T

cyl=127°C

Fired − Tcool

=100°C, Tcyl

=141°C

Fired − Tcool

=60°C, Tcyl

=121°C

Figure 6.19: Impact of upper cylinder-wall temperature based on the noise correctedtemperature standard deviation for motored and fired operation with varying coolanttemperature. Diagnostic: single-line 277nm, 3-pentanone. Engine conditions: con-tinuous fired, φ=0.32, Tin=190C, 17% 3-pentanone in iso-octane.

6.6.3 Correlation of Temperature and Reacting Zones

As discussed above, it is generally considered that the temporal variation in the

auto-ignition timing of the various parts of the charge is the result of sequential


auto-ignition of progressively cooler regions. Considering the importance of ther-

mal stratification for HCCI combustion at all but the lowest loads, it is valuable

to investigate the validity of this hypothesis. This was done by comparing the

temperature distribution prior to TDC, with reaction zones after TDC. Such a com-

parison requires the ability to image areas of combustion reaction simultaneously

with temperature in the same engine cycle. Chemiluminescence imaging is a com-

mon technique used to visualize reaction zones [108,126], which is based on emission

from excited-state intermediate combustion species. However, such measurements

are line-of-sight averaged across the cylinder volume and may not exactly correlate

with planar temperature results within the thin laser sheet. An alternative fluo-

rescence based technique utilizes tracer consumption during combustion to indicate

reaction regions. This technique is often applied in spark-ignition engine studies to

visualize the remaining reactant areas during flame-front propagation [131–134]. For

the current study, images acquired after TDC contain regions of low fluorescence sig-

nal that are presumably indicative of early combustion reactions. These regions are

deemed “early” reaction zones as consumption of the large tracer molecules occurs

early in the combustion process and is coincident with iso-octane fuel decomposition.

A sample image of tracer consumption is shown in Figure 6.20a, where the darker

regions with low fluorescence intensity signify early reaction zones. These low-signal

regions were verified to correlate with exothermic reaction by comparing variations

in measured reaction zone area from the fluorescence images with variations in the

10% burn point (CA10) based on the cumulative AHRR. To facilitate the com-

parison, fluorescence images were first binarized based on a chosen threshold, and

inverted to highlight the reaction zones as shown in Figure 6.20a. The reaction area

was then calculated and normalized by the total PLIF measurement area, to deter-

mine the reaction area ratio (RAR). Finally, the RAR was compared with CA10,

calculated from the individual cycle cylinder-pressure trace, on a cycle-to-cycle basis

as seen in Figure 6.20b. The excellent correlation between RAR and CA10 shown

in Figure 6.20b confirms that the tracer consumption in the central bulk-gas regions

is representative of the early reactions of the total charge. This means that tracer

consumption after TDC can be used for reaction zone visualization as expected. In


(a) Fluorescence signal→ Binary reaction zone image

5 10 15 20 25 30 35 40363.5

364

364.5

365

365.5

366

Cycle Number

CA

10 [

° C

A]

5 10 15 20 25 30 35 40

−0.2

0

0.2

0.4

0.6

0.8R

eact

ion

Are

a R

atio

Correlation Coeff. = 0.91

(b) Combustion phasing correlation

Figure 6.20: (a) Inverse binarization of fluorescence signal highlighting reactionzones. (b) Correlation between reaction area ratio (RAR) and CA10 combustionphasing.

addition, because the TS distribution measurements prior to TDC result from a

single-line technique, the remaining excitation wavelength in the current setup can

be used for reaction imaging in the same cycle.

To investigate the spatial correlation between temperature and combustion zones,

single-line temperature distributions have been compared with the images of reac-

tion zones described above, and are presented in Figure 6.21. This comparison was

achieved by temporally shifting the 277 and 308 nm excitation laser pulses to pro-

vide a single-line 277 nm temperature image before TDC, and a 308 nm reaction


image after TDC, all within the same engine cycle. Temperature images 6.21a-c

were acquired at a constant imagine timing of 350 CA and provide individual-cycle

temperature distributions prior to the onset of reaction. The corresponding reac-

tion images were taken at times ranging from 362.5 CA to 367.5 CA and show

the progression of reaction throughout the measurement area. As expected, the re-

action area increases as the image timing is delayed from TDC due to the progress

of chemical reaction. It should be noted that charge motion between temperature

and reaction image acquisition does slightly affect the spatial correlations shown

in Figure 6.21 but does not significantly impact the general observations. The first

image pair 6.21a indicates that the earliest reactions are localized to the highest tem-

perature regions. As time progresses, the reaction zones spread to include cooler

regions as evidenced in pair 6.21b. As the reaction progresses further still (6.21c),

only the coolest temperature areas remain un-reacted. Earlier temperature images

acquired at 345 CA also show favorable spatial correlations with reaction zones as

shown in Figure 6.21d. Collectively these imagines directly confirm the progression

of sequential auto-ignition, in which reaction initiates in the highest temperature

regions followed by progressively cooler zones. Furthermore, it demonstrates the

overall importance of thermal stratification for high-load HCCI operation.


Temperature [K]

−40 −20 0 20 40 Early Reaction Zones

(a) 350CA / 362.5CA

(b) 350CA / 365CA

(c) 350CA / 367.5CA

(d) 345CA / 365CA

Figure 6.21: Spatial correlation of temperature distribution before TDC (left) andearly reaction zones (right) after TDC acquired for same cycle

Chapter 7

Summary and Future Work

This thesis presents the development and refinement of quantitative PLIF strate-

gies for measurement of temperature and composition. Both single-line and two-line

techniques have been optimized for best performance in HCCI engines. These PLIF

techniques have been applied in two separate optical HCCI engines to study poten-

tial engine strategies for extending the HCCI operating load range. The first engine

study focused on the use of HCCI with negative valve overlap (NVO) to extend

the low-load limit. The second engine study considered the role of naturally occur-

ring thermal stratification (TS) on high-load HCCI combustion. Overall this work

demonstrates the feasibility of the PLIF techniques for quantitative measurement in

harsh engine environments, and provides useful information for future HCCI engine

development. The following summarizes results for the general diagnostic develop-

ment, as well as both engine studies. Suggestions for future work are provided at

the end of each subsection.

7.1 PLIF Development

Diagnostic development began with determination of the general theoretical frame-

work for each diagnostic strategy. A single excitation (single-line), single collection

strategy was selected for temperature measurements in homogeneous mole fraction

environments (true HCCI) due to the excellent potential performance and overall

139

140 CHAPTER 7. SUMMARY AND FUTURE WORK

simplicity. A more versatile dual excitation (two-line), single collection strategy

was chosen to provide simultaneous temperature and mole fraction measurements

for environments with both thermal and compositional non-uniformity (HCCI with

NVO). For each diagnostic variation, specifics such as tracer species and excitation

wavelengths were selected to optimize diagnostic performance (precision). Acetone

and 3-pentanone were selected as the seeded tracers as they provide good over-

all performance, can be easily applied in both motored and fired studies (minimal

oxygen quenching behavior), and have been well studied spectroscopically.

Wavelength selection was based on detailed uncertainty calculations aimed at

minimizing measurement precision over the HCCI engine range. Simulations indi-

cated that 277 nm excitation provided the best overall single-line performance for

both ketones. Similarly, simulations of the two-line strategy resulted in selection of

the 277 / 308 nm wavelength pair. Overlap in the optimized wavelengths for the

two techniques affords the ability to perform single and two-line measurements with

the identical experimental setup, differentiated only in image post-processing.

Engine characterization measurements confirmed the general trends predicted

by the uncertainty analysis, although some differences in magnitude were apparent.

Based on this characterization, single-shot temperature precisions of 5 K or less

were achieved for the single-line, 277 nm 3-pentanone strategy. For the two-line

strategy, temperature and mole fraction precision varied dramatically over the range

of conditions experienced during compression. Here, minimum precisions of 8 K and

3 % (277/308 nm, 3-pentanone) were achieved for the temperature and mole fraction

measurements, respectively. In general, 3-pentanone provided better performance

than acetone over a majority of in-cylinder conditions, although acetone may be

preferable at high temperatures.

Additional topics related to diagnostic development were covered, including mea-

surements of the fluorescence quantum yield (FQY) and the laser energy threshold

of fluorescence saturation. A series of engine FQY calibration experiments expanded

the range of available FQY data and were utilized directly for subsequent data pro-

cessing. Such measurements were necessary as current FQY data does not cover

the high temperature and pressure regime of interest for high-load HCCI studies.

7.1. PLIF DEVELOPMENT 141

Comparisons of the engine-based FQY measurements and fundamental cell mea-

surements showed good agreement over the range of overlapped thermodynamic

conditions. Additional comparisons with FQY model predictions showed some con-

sistency, but also indicated that further model refinement is needed.

Fundamental measurements of fluorescence saturation behavior provided laser

energy bounds for the “linear” excitation regime. Trends in the 10% linearity

threshold with excitation wavelength and tracer species generally followed trends

in absorption cross-section. These 10% thresholds were found to be lower than pre-

viously reported, motivating further measurements and modeling efforts to better

understand the underlying physics. Measurements of the relative impact of oxygen

quenching and total pressure scaling were also completed, with mixed results.

7.1.1 Future Work: PLIF Development

The absolute accuracy of the PLIF techniques in this work are dominated by the

accuracy of in-cylinder temperature estimates used for the FQY engine calibration

experiments. Introducing an in-situ temperature measurement such as a tunable

diode-laser (TDL) based sensor would allow better characterization of the core tem-

peratures for motored operation, and would ultimately improve the diagnostic ac-

curacy. This would also open up the possibility for other spectroscopic studies in

the engine which has many advantages over alternative flowing cell measurements.

Accuracy could also be improved by expanding the range of available funda-

mental FQY cell data, specifically at high temperatures and pressures (>700 K,

>10 bar). Although the FQY behavior of acetone, 3-pentanone and toluene have

been well characterized, additional data are still needed for improved quantitative

diagnostics. Engine-based FQY measurements are also valuable, however cell-based

measurements provide an easier means of controlling the thermodynamic conditions

and the combinations of temperature and pressure are not bound by the engine

compression ratio. Such FQY measurements would also be particularly useful for

refinement of current FQY models, which are typically less accurate at these ex-

tremes.


7.2 HCCI with NVO

Two-line PLIF measurements were performed during fired HCCI with NVO opera-

tion to demonstrate the feasibility of the measurement technique, and to study the

evolution and impact of stratification. Simultaneous images of temperature and fuel

distributions were obtained during NVO recompression and re-expansion using fuel-

seeded PLIF. In addition, temperature/EGR mole fraction images were recorded

during main compression using air-seeded N-PLIF. Prior to quantitative data ac-

quisition, an examination of measurement interferences indicated that the impact of

droplet scattering is minor for PLIF during NVO. This is a result of high gas tem-

peratures and associated rapid evaporation. In addition, fluorescence interference

from non-tracer products of combustion was insignificant for the selected operating

conditions.

Imaging during the NVO recompression stroke demonstrated that fuel distribu-

tions and residual gas temperatures may be measured as early as 15 CAD after

fuel/tracer injection, once liquid droplets have evaporated. The short mixing time

between injection and imaging means that the tracer, and therefore signal, does not

entirely fill the field of view for these experiments; nonetheless, average measured

temperatures correlate with main combustion loading. Some measurements were

also possible during NVO recompression using unburned crevice gases (containing

tracer) carried over from the previous expansion stroke.

Generally, fuel/tracer injected during recompression reacts chemically, such that

PLIF imaging is not possible during re-expansion. However, it was determined that

the main fuel injection could be advanced as early as 320 CAD without significantly

affecting main combustion. This means that PLIF images could be captured prior to

IVC, providing a way to characterize temperatures at the end of NVO re-expansion.

Such measurements during a sweep of NVO injection timing indicated little change

in temperature while varying NVO SOI between +260 and +330 CAD. The fact that

main combustion phasing varied during the tests (while NVO temperatures did not)

is anecdotal evidence of a chemical effect of NVO reactions on main phasing.

7.2. HCCI WITH NVO 143

In addition to the above NVO measurements, temperatures and EGR distribu-

tions were captured during the main intake and compression strokes using air-seeded

N-PLIF. Observed trends in average temperature and temperature standard devi-

ation could be explained by mixing and compression heating processes. Trends in

EGR standard deviation could also be explained by mixing, however an observed

rise in average EGR mole fraction requires further study.

7.2.1 Future Work: HCCI with NVO

The current NVO study includes only a small subset of possible operating con-

ditions. Expanding the range of test conditions to include a wider range of fuel

loadings, injection timings, and injection splits between main and NVO will only

help to improve the understanding of NVO operation. Additional PLIF measure-

ments with a vertically oriented sheet could confirm the existence of any vertical

stratification not captured with the horizontal imaging arrangement. These verti-

cal measurements could also help explain the gradual increase in measured EGR

throughout compression that could be related to vertical stratification.

An important physical constraint of the current work is the inability to image

after -24CA (24 bTDC) due to a lack of optical access in the pentroof. Imaging

access after -24CA is important given that temperature distributions just prior to

reaction will directly impact HCCI combustion. Updated PLIF measurements with

pentroof access will further aide in the characterization of HCCI operation with

NVO and provide useful information about the locations of ignition relative to the

temperature and EGR mole fraction distributions.

Diagnostically speaking, the high temperatures and moderate pressures experi-

enced during fired NVO operation provide a challenging environment for quantita-

tive measurements. While the current diagnostic strategy was selected to provide

good overall performance, the temperature and mole fraction precision do degrade

late in compression. To address this issue, the diagnostic strategy could be re-

optimized for better performance at the high temperatures near TDC where mea-

sured distributions will more strongly impact combustion. Better maximization of


performance in this range will permit better resolution of fine temperature fluctua-

tions that can impact the localized reaction phasing.

7.3 HCCI Thermal Stratification

PLIF measurements were conducted in a high-load, low-residual HCCI engine to in-

vestigate the distribution and evolution of naturally occurring thermal stratification

(TS) for both motored and fired operation. Initial single-line measurements during

the compression stroke of a motored engine showed a progressive increase of TS to-

wards TDC. A quantitative investigation indicated that the temperature standard

deviation, calculated over the image field of view, ranged from 0 K at 305CA (55

bTDC) to 10 K at 360CA (TDC). Comparison of TS statistics, derived from single-

line strategies at 277 nm and 308 nm, for both acetone and 3-pentanone showed

excellent agreement and confirmed the consistency of the FQY measurements and

calibration strategies.

PLIF application was also extended to fired operation to assess potential sim-

ilarities and differences between motored and fired operation, specifically focusing

on the impact of hot combustion residuals, direct fuel injection, and cylinder wall

temperature. First, two-line PLIF measurements were performed during intake and

early compression to track the hot residual mixing process. Results showed that

residual mixing occurs rapidly, with minimal mixture stratification remaining by

BDC. These measurements confirmed that residual mixing does not significantly

impact TS development for low-residual HCCI measurements, and also indicate

that single-line measurements can be applied during fired cycles without significant

error.

Subsequent single-line fired measurements performed later in the compression

stroke exhibited similar TS evolution to previous motored experiments, although

differences in magnitude were present. These differences were attributed to either

incomplete fuel mixing (DI skipfired study) or cylinder wall temperature (premixed,

continuous fired study) depending on the mode of operation. While these factors

7.3. HCCI THERMAL STRATIFICATION 145

contributed to small variations in magnitude, wall heat transfer and convection is

the dominant mechanism for TS development in both motored and fired low-residual

HCCI operation.

Given the critical importance of TS on HCCI combustion, the correlation be-

tween the single-cycle temperature distribution and resulting reaction zones has been

investigated. Fluorescence images acquired after TDC provided a good indicator of

early reaction zones due to tracer consumption in these areas. Variation in measured

reaction area, calculated from these post-TDC reaction images, was well correlated

with CA10 on a cycle-to-cycle basis confirming that reaction progress was well rep-

resented. Comparison of temperature distributions before the onset of combustion

and reaction zone images after TDC showed good spatial correlation and indicate

that combustion initiates in the highest temperature regions followed by reaction in

progressively cooler zones. This study directly confirmed the suspected progression

of sequential auto-ignition and the importance of TS for HCCI combustion.

7.3.1 Future Work: HCCI TS

The current work demonstrates the resolving power of the single-line PLIF temper-

ature diagnostic, and presents initial results investigating TS development. More

refined parametric studies of the influence of cylinder wall temperature, intake tem-

perature, and direct fuel injection will help to better characterize the development

of naturally occurring TS. Additionally, strategies for increasing TS could be con-

sidered, as this has the potential to extend this high-load limit by further reducing

the pressure rise-rates. Potential strategies include special piston geometries, high

degrees of charge motion, and delayed direct injection.

All temperature images for this high-load study were acquired with a horizontal

laser sheet orientation providing temperature distributions parallel with the firedeck.

While this provides good imaging of the cylinder core region, imaging of the bound-

ary layer near the cylinder wall is limited by the piston window (70 mm diameter

window, in 102 mm bore). Reorientation of the laser delivery optics and imaging

system to acquire vertical temperature images would provide direct visualization


of the near-wall boundary layer region. Such images could be used to directly im-

age regions adjacent to the cylinder walls, firedeck, and piston crown which are all

expected to contribute to the in-cylinder TS.

Appendix A

Ketone Photophysical Parameter

Fits

The general photophysics of acetone and 3-pentanone were discussed in Chapter 3.

All absorption cross section data was taken from Koch et al. [1], where the absorp-

tion spectrum was approximated with a Gaussian profile given in Equation A.1. The

corresponding fit parameters A, λc and w are given in Table A.1 and were deter-

mine based on shock tube measurements of absorption cross-section over a range of

temperatures. Any small errors in absorption cross-section will propagate through

the FQY calculations, hence the data fits should be used in conjunction with the

processed engine FQY data to be self-consistent.

σ(λ, T ) = A(T ) exp

[−

(λ− λc(T )

w(T )

)2]

(A.1)

Table A.1: Temperature dependent gaussian fit parameters for the absorption crosssection of acetone and 3-pentanone for 230-330 nm and 300-1040 K, taken from [1].Temperature in kelvin.

Parameter A(T ), 1020cm2 λc(T ), nm w(T ), nmAcetone 3.43 + 0.00482× T 271.4 + 0.0156× T 26.8 + 0.00950× T

3-Pentanone 4.77 + 0.00487× T 273.7 + 0.0186× T 25.1 + 0.0101× T

147

148 APPENDIX A. KETONE PHOTOPHYSICAL PARAMETER FITS

The absolute fluorescence quantum yield (FQY) for both acetone and 3-pentanone

was measured in a motored IC engine for a range of temperatures and pressures rel-

evant for HCCI engine study. The FQY data was derived from relative fluorescence

signal measurements acquired at selected image timings during compression over

a range of intake temperatures. This data was then converted to absolute FQY

using the procedure described in Chapter 3, fit with a polynomial that best ap-

proximated the data and used for subsequent data processing. FQY quadratic fit

parameters for 3-pentanone in pure nitrogen are given in Table A.2 for 277 nm and

308 nm excitation. These fit parameters are used in conjunction with Equation A.2

to determine the absolute FQY. Similarly, linear FQY fit parameters for acetone

in nitrogen are presented in Table A.3 and the corresponding linear fit equation is

provided in Equation A.3.

φ(T, P ) = a1T2 + a2T + a3 (A.2)

φ(T, P ) = a1T + a2 (A.3)

149

Tab

leA

.2:

Quad

rati

cfitpar

amet

ersof

3-pen

tanon

eab

solu

teFQ

Yin

pure

nit

roge

nm

easu

red

ina

mot

ored

engi

ne.

Fit

par

amet

ers

for

agi

ven

imag

eti

me

(pre

ssure

)ar

euse

din

conju

nct

ion

wit

hE

quat

ion

A.2

toca

lcula

teth

eFQ

Yfo

rte

mper

ature

wit

hin

the

stat

edra

nge

.

Imag

eT

ime

[CA

]T

min

[K]

Tm

ax

[K]

Pave

[bar

]W

avel

engt

h[n

m]

a 1a 2

a 3T

ime

[CA

][K

][K

][b

ar]

[nm

]30

556

070

04.

527

7-4

.290

1e-0

93.

3940

e-06

1.71

08e-

0430

8-6

.778

5e-0

97.

0263

e-06

-8.8

108e

-04

320

660

810

7.7

277

1.11

76e-

09-3

.605

8e-0

62.

4541

e-03

308

-1.0

656e

-09

-5.1

161e

-07

1.60

65e-

0333

074

090

011

.727

73.

3672

e-09

-7.0

619e

-06

3.78

52e-

0330

82.

2563

e-09

-5.7

424e

-06

3.64

72e-

0334

082

010

0017

.927

72.

8675

e-09

-6.1

763e

-06

3.39

14e-

0330

83.

4964

e-09

-7.8

626e

-06

4.53

34e-

0334

586

010

5021

.627

72.

6979

e-09

-5.8

895e

-06

3.27

11e-

0330

83.

4158

e-09

-7.7

187e

-06

4.46

15e-

0335

089

010

9025

.227

72.

0671

e-09

-4.6

721e

-06

2.68

40e-

0330

82.

8716

e-09

-6.6

707e

-06

3.95

27e-

0335

592

011

1027

.727

71.

7365

e-09

-4.0

341e

-06

2.37

83e-

0330

82.

2157

e-09

-5.3

781e

-06

3.31

68e-

0336

092

011

2028

.427

71.

4300

e-09

-3.4

182e

-06

2.07

19e-

0330

81.

8495

e-09

-4.6

450e

-06

2.95

28e-

03

150 APPENDIX A. KETONE PHOTOPHYSICAL PARAMETER FITS

Tab

leA

.3:Lin

earfit

param

etersof

acetone

absolu

teFQ

Yin

pure

nitrogen

measu

redin

am

otoreden

gine.

Fit

param

etersfor

agiven

image

time

(pressu

re)are

used

incon

junction

with

Equation

A.3

tocalcu

lateth

eFQ

Yfor

temperatu

rew

ithin

the

statedran

ge.

Image

Tim

e[C

A]

Tm

in[K

]T

max

[K]

Pave

[bar]

Wavelen

gth[n

m]

a1

a2

305560

7004.5

277-7.9311e-07

9.8323e-04308

-6.4776e-071.0479e-03

320650

8107.7

277-9.2998e-07

1.1127e-03308

-6.9873e-071.0950e-03

330730

90011.8

277-9.9841e-07

1.1899e-03308

-8.1584e-071.1899e-03

340820

100018.0

277-9.4736e-07

1.1638e-03308

-8.8542e-071.2495e-03

345860

105021.7

277-9.1400e-07

1.1411e-03308

-9.4039e-071.3012e-03

350890

109025.3

277-8.4837e-07

1.0821e-03308

-9.5073e-071.3083e-03

355910

112027.9

277-8.3299e-07

1.0720e-03308

-9.3763e-071.2963e-03

360920

113028.7

277-7.6363e-07

1.0036e-03308

-9.0543e-071.2671e-03

Appendix B

Uncertainty Analysis Theory

The following outlines the general theoretical development used for the uncertainty

calculations for the two-line PLIF measurements of temperature and EGR mole

fraction. An in-depth derivation has been presented previously by Rothamer et

al. [70,77], and is outlined here for clarity. Based on the development of the two-line

PLIF technique, the characteristic equation for EGR mole fraction measurements is

provided by Equation B.1 (variable description provided in Chapter 2.

xtr

xcaltr

=Ecal

E

P cal

P

T

T cal

σcal (λ, T )

σ (λ, T )

φcal (λ, T, P, x)

φ (λ, T, P, x)

Sf

Scalf

(B.1)

The uncertainty in mole fraction ∆XEGR can be written as:

∆XEGR = −∆

(xtr

xcaltr

)(B.2)

Applying the error propagation relation, Equation 2.12, results in an expanded

relation for the mole fraction uncertainty:

∆XEGR =

[(∂XEGR

∂E∆E

)2

+

(∂XEGR

∂P∆P

)2

+

(∂XEGR

∂Sf

∆Sf

)2

+

(∂XEGR

∂Scalf

∆Scalf

)2

+

(∂XEGR

∂T∆T

)2]1/2

(B.3)

151

152 APPENDIX B. UNCERTAINTY ANALYSIS THEORY

The partial derivatives in Equation B.3 are determined by differentiating Equa-

tion B.1 and are shown below:

∂XEGR

∂E= − 1

EXEGR

∂XEGR

∂P= −φ(T, P ) + P ∂φ(T,P )

∂P

Pφ(T, P )XEGR

∂XEGR

∂Sf

=1

Sf

XEGR∂XEGR

∂Scalf

= − 1

Scalf

XEGR (B.4)

∂XEGR

∂T=

(1

T−

∂σ(T )∂T

φ(T, P ) + σ(T )∂φ(T,P )∂T

σ(T )φ(T, P )

)XEGR

The ∆XEGR uncertainty can thus be determine from Equation B.3 and B.4, and

with random uncertainties information about laser energy fluctuations, fluorescence

signal and temperature. Laser energy uncertainties are based on profile stability

measurements are vary depending on the laser source as shown in Table 2.1. Random

uncertainty in fluorescence signal is estimated based on fluorescence signal estimates

(Equation 2.18), and modeling of the intensified camera noise (Equation 2.16). Fi-

nally, the temperature uncertainty is derived from a similar uncertainty analysis of

the concurrent two-line temperature measurement described below.

The temperature derived from the two-line PLIF technique is determined from a

measure of the ratio of photophysical parameters, RPP , such that T = T (RPP , P ).

Assuming that the combined uncertainties of these individual variable sum in quadra-

ture, the temperature uncertainty can be represented by:

∆T =

√(∂T

∂RPP

∆RPP

)2

+

(∂T

∂P∆P

)2

(B.5)

where ∆RPP and ∆P are the random uncertainties in the RPP parameter and pres-

sure respectively. RPP itself is a function of laser energy, and fluorescence signal

given by: RPP = f(E1, E2, Sf1, Sf2, Scalf1 , Scal

f2 ). This functionality leads to the ran-

dom uncertainty of RPP shown in Equation B.6. The temperature uncertainty can

thus be calculated using Equation B.5 and B.6, with laser energy and fluorescence

signal uncertainties consistent with those used for the mole fraction analysis. All

153

photophysical data required to calculate the fluorescence signal and partial deriva-

tives were generated using available absorption cross-section data, and FQY models.

The specific FQY models used are listed in Chapter 2.

∆RPP =

[(∂RPP

∂E1

∆E1

)2

+

(∂RPP

∂E2

∆E2

)2

+

(∂RPP

∂Sf1

∆Sf1

)2

(∂RPP

∂Sf2

∆Sf2

)2

+

(∂RPP

∂Scalf1

∆Scalf1

)2

+

(∂RPP

∂Scalf2

∆Scalf2

)2]1/2

(B.6)

Appendix C

Camera Noise Characterization

A characterization of the imaging camera noise properties was required for the mea-

surement precision estimates described in Chapter 6 and for the measurement un-

certainty de-convolutions. This noise characterization essentially relates the image

signal-to-noise ratio (SNR) to the digitized signal over the dynamic range of the

camera. The camera testing is important for two main reasons. First, it provides an

accurate estimate of the image SNR based on average signal (camera specific) and

can be easily used to estimate SNR for inhomogeneous distributions encountered

in data images. Second, the characterization contains information about both the

camera read noise and the intensifier noise figure, and is not limited to estimates

only in the shot-noise limited regime as is sometimes assumed.

The camera tests were completed by imaging a nearly homogenous field for

signal intensities spanning the dynamic range of the camera. Two separate means

of generating the homogeneous field have been investigated.

First an internally illuminated integrating sphere was attached to the camera.

The diffuse light emitted by the sphere provided a nearly homogenous distribution

that could be varied in intensity by adjusting the driver voltage. This setup was

initially chosen as it allowed data to be acquired with exposure times similar to

those used for engine experiments. The second homogeneous field tested was derived

from a simple piece of white paper illuminated only by overhead lighting with the

lab space. For these measurements the collected signal was adjusted by varying the

154

155

camera exposure time.

For both measurement setups, 50 data were acquired at each illumination levels

over the camera dynamic range. Averaged background images were used to correct

for dark signal and fixed pattern noise. The signal-shot image SNR could then

be calculated by dividing the average signal over a small image subregion by the

calculated standard deviation of signal within the same region. However, despite

efforts to generate a homogeneous field, some fixed pattern was still apparent in the

images. To eliminate the impact of the fixed pattern on the measurements, SNR was

calculated based on temporal variations in signal instead of spatial variations. Here,

the standard deviation of signal at a given pixel was calculated over the 50 image

set. This standard deviation was averaged for a number of pixel locations. Dividing

the measured average signal with these temporal standard deviations constitutes

the temporal SNR method. In the absence of fixed pattern signal, the temporal and

spatial method will provide identical results.

Camera characterization results for the PI:MAX2:1003 camera used for all HCCI

measurements in presented in Figure C.1. Camera data was processed using the

temporal SNR method described above. A sixth order polynomial fit was applied

to the data to provide easy means of estimating camera SNR based on average

signals within an image. This polynomial was used for all measurement uncertainty

estimates, and provides the critical relationship of SNR with camera signal. This

characterization is particularly helpful when considering highly stratified flows, as

the image SNR would be hard to estimate otherwise.

156 APPENDIX C. CAMERA NOISE CHARACTERIZATION

0 1 2 3 4 5 6

x 104

0

20

40

60

80

100

Measured Signal [counts]

Imag

e S

NR

Temporal Method

Figure C.1: Characterization of PIMAX2:1003 image SNR versus signal based onthe temporal SNR method. Polynomial fit results included for reference.

Bibliography

[1] J. D. Koch, J. Gronki, and R. K. Hanson. Measurements of near-UV absorp-

tion spectra of acetone and 3-pentanone at high temperatures. Journal of

Quantitative Spectroscopy & Radiative Transfer, 109:2037–2044, 2008.

[2] A. C. Eckbreth. Laser diagnostics for combustion temperature and species.

Combustion Science and Technology. Gordon and Breach, Amsterdam, 2nd

edition, 1996.

[3] B. E. Battles and R. K. Hanson. Laser-induced fluorescence measurements

of NO and OH mole fractions in fuel-lean, high pressure (1-10 atm), methan

flames: fluorescence modeling and experimental validation. Journal of Quan-

titative Spectroscopy & Radiative Transfer, 54:521–537, 1995.

[4] W. G. Bessler, C. Schulz, T. Lee, D. I. Shin, M. Hofmann, J. B. Jeffries,

J. Wolfrum, and R. K. Hanson. Quantitative NO-LIF imaging in high-pressure

flames. Applied Physics B: Lasers and Optics, 75(1):97–102, 2002.

[5] M. J. Dyer and D. R. Crosley. Two-dimensional imaging of OH laser-induced

fluorescence in a flame. Optics Letters, 7(8):382–384, 1982.

[6] C. Gibaud, J. A. Snyder, V. Sick, and R. P. Lindstedt. Laser-induced fluores-

cence measurements and modeling of absolute ch concentrations in strained

laminar methane/air diffusion flames. Proceedings of the Combustion Institute,

30(1):455–463, 2005.

157

158 BIBLIOGRAPHY

[7] G. Kychakoff, R. D. Howe, R. K. Hanson, and J. C. McDaniel. Quantitative

visualization of combustion species in a plane. Applied Optics, 21:3225–3227,

1982.

[8] M. P. Lee, P. H. Paul, and R. K. Hanson. Quantitative imaging of temperature

fields in air using planar laser-induced fluorescence of O2. Optics Letters,

12:75–77, 1987.

[9] B. K. McMillin, J. L. Palmer, and R. K. Hanson. Temporally resolved, two-

line fluorescence imaging of NO temperature in a transverse jet in supersonic

cross flow. Applied Optics, 32:7532–7545, 1993.

[10] J. L. Palmer and R. K. Hanson. Temperature imaging in a supersonic free jet

of combustion gases using two-line OH fluorescence. Applied Optics, 35:485–

499, 1996.

[11] J. M. Seitzman, G. Kychakoff, and R. K. Hanson. Instantaneous temperature

field measurements using planar laser-induced fluorescence. Optics Letters,

10:439–441, 1985.

[12] B. Hiller and R. K. Hanson. Simultaneous planar measurements of velocity

and pressure fiels in gas-flows using laser-induced fluorescence. Applied Optics,

27(1):33–48, 1988.

[13] E. R. Lachney and N. T. Clemens. PLIF imaging of mean temperature and

pressure in a supersonic bluff wake. Experiments in Fluids, 24(4):354–363,

1998.

[14] D. A. Rothamer and R. K. Hanson. Visualization of high-speed flows using

infrared planar laser induced fluorescence (IRPLIF) of carbon dioxide. In

Proceedings of the 42nd AIAA Joint Propulsion Conference & Exhibit, number

2006-4300, Sacramento, CA, July 2006.

BIBLIOGRAPHY 159

[15] B. Hiller, J. C. McDaniel, E. C. Rea, and R. K. Hanson. Laser-induced fluores-

cence technique for velocity field measurements in subsonic gas flows. Optics

Letters, 8:474–479, 1983.

[16] J. C. McDaniel, B. Hiller, and R. K. Hanson. Simultaneous multiple-point

velocity measurements using laser-induced iodine fluorescence. Optics Letters,

8:51–53, 1983.

[17] P. H. Paul, M. P. Lee, and R. K. Hanson. Molecular velocity imaging of su-

personic flows using pulsed planar-induced fluorescence of NO. Optics Letters,

14:417–419, 1989.

[18] A. C. Eckbreth. CARS thermometry in practical combustors. Combustion

and Flame, 39(2):133–147, 1980.

[19] G. Vaughan, D. P. Wareing, S. J. Pepier, L. Thomas, and V. Mitev. At-

mospheric temperature measurements made by rotational Raman scattering.

Applied Optics, 32(15):2758–2764, 1993.

[20] X. Pan, P. F. Barker, A. Meschanov, J. H. Grinstead, M. N. Shneider, and

R. B. Miles. Temperature measurements by coherent Rayleigh scattering.

Optics Letters, 27(3):161–163, 2002.

[21] A. P. Yalin and R. B. Miles. Temperature measurements by ultraviolet filtered

Rayleigh scattering using mercury filter. Journal of Thermophysics and Heat

Transfer, 14(2):210–215, 2000.

[22] B. J. Kirby and R. K. Hanson. Planar laser-induced fluorescence imaging of

carbon monoxide using vibrational (infrared) transitions. Applied Physics B:

Lasers and Optics, 69(5):505–507, 1999.

[23] B. J. Kirby and R. K. Hanson. Linear excitation schemes for IR planar-induced

fluorescence imaging of CO and CO2. Applied Optics, 41(6):1190–1201, 2002.

160 BIBLIOGRAPHY

[24] A. Lozano, S. H. Smith, M. G. Mungal, and R. K. Hanson. Concentration mea-

surements in a transverse jet by planar laser-induced fluorescence of acetone.

AIAA Journal, 32(1):218–221, 1994.

[25] L. M. Pickett and J. B. Ghandhi. Passive scalar measurements in a planar

mixing layer by PLIF of acetone. Experiments in Fluids, 31(3):309–318, 2001.

[26] S. Einecke, C. Schulz, and V. Sick. Measurement of temperature, fiel concen-

tration and equivalence ratio fields using tracer LIF in IC engine combustion.

Applied Physics B, 71:717–723, 2000.

[27] D. F. Marran, B. Marshall, W. M. Studzinski, J. C. Swindal, and W. P. Acker.

Planar laser-induced fluorescence imaging of crevice hydrocarbon emissions in

a spark-ignited engine. Symposium (International) on Combustion, 2:2069–

2076, 1998.

[28] J. D. Smith and V. Sick. High-speed fuel tracer fluorescence and OH radical

chemiluminescence imaging in a spark-ignition direct-injection engine. Applied

Optics, 44:6682–6691, 2005.

[29] C. Strozzi, J. Sotton, A. Mura, and M. Bellenoue. Characterization of a

two-dimensional temperature field within a rapid compression machine using

toluene planar laser-induced fluorescence imaging technique. Measurement

Science and Technology, 20(12), 2009.

[30] F. Grossmann, P. B. Monkhouse, M. Ridder, V. Sick, and J. Wolfrum. Temper-

ature and pressure dependences of the laser-induced fluorescence of gas-phase

acetone and 3-pentanone. Applied Physics B, 62:249–253, 1996.

[31] J. D. Koch and R. K. Hanson. Temperature and excitation wavelength de-

pendencies of 3-pentanone absorption and fluorescence for PLIF applications.


BIBLIOGRAPHY 161

[32] J. D. Koch, R. K. Hanson, W. Koban, and C. Schulz. Rayleigh-calibrated

fluorescence quantum yield measurements of acetone and 3-pentanone. Applied

Optics, 43:5901–5910, 2004.

[33] M. Loffler, F. Beyrau, and A. Leipertz. Acetone laser-induced fluorescence

behavior for the simultaneous quantification of temperature and residual gas

distribution in fired spark-ignition engines. Applied Optics, 49:37–49, 2010.

[34] V. Modica, C. Morin, and P. Guibert. 3-pentanone LIF at elevated tem-

peratures and pressures: measurements and modeling. Applied Physics B,

87:193–204, 2007.

[35] M. C. Thurber and R. K. Hanson. Pressure and composition dependences of

acetone laser-induced fluorescence with excitation at 248, 266, and 308 nm.


[36] W. Hwang, J. E. Dec, and M. Sjoberg. Fuel stratification for low-load HCCI

combustion: performance & fuel-PLIF measurements. SAE Paper, 2007-01-

4130, 2007.

[37] K. S. Kim, M. S. Choi, C. H. Lee, and W. T. Kim. In-cylinder fuel distribution

measurements using PLIF in a SI engine. SAE Paper, 1997-02-24, 1997.

[38] H. Persson, J. Sjoholm, E. Kristensson, B. Johansson, M. Richter, and

M. Alden. Study of fuel stratification on spark assistend compression igni-

tion (SACI) combustion with ethanol using high speed fuel PLIF. SAE Paper,

2008-10-06, 2008.

[39] C. Weaver, S. Wooldridge, S. Johnson, V. Sick, and G. Lavoie. PLIF measure-

ments of fuel distribution in a PFI engine under cold start conditions. SAE

Paper, 2003-10-27, 2003.

[40] B. Deschamps and T. Baritaud. Visualization of gasoline and exhaust gases

distribution in a 4-valve SI engine; effects of stratification on combustion and

pollutants. SAE paper, 961928, 1996.

162 BIBLIOGRAPHY

[41] S. Einecke, C. Schulz, V. Sick, A. Dreizler, R. Schiesl, and U. Maas. Two-

dimensional temeprature measurements in an SI engine using two-line tracer

LIF. SAE Paper, 982468, 1998.

[42] T. Fujikawa, K. Fukui, Y. Hattori, and K. Akihama. 2-D temperature mea-

surements of unburned gas mixture in an engine by two-line excitation LIF

technique. SAE Paper, 2006-01-3336, 2006.

[43] A. Kakuho, M. Nagamine, Y. Amenomori, T. Urushiahara, and T. Itoh. 2-D

temperature measurements of unburned gas mixture in an engine by two-line

excitation LIF technique. SAE Paper, 2006-01-1202, 2006.

[44] D. A. Rothamer, J. A. Snyder, R. K. Hanson, and R. R. Steeper. Two-

wavelength PLIF diagnostic for temperature and composition. SAE Paper,

2008-01-1067, 2008.

[45] K. Epping, S. Aceves, R. Bechtold, and J. Dec. The potential of HCCI for

high efficiency and low emissions. SAE Paper, 2002-01-1923, 2002.

[46] S. Onishi, S. H. Jo, K. Shoda, P. D. Jo, and S. Kato. Active thermo-atmosphere

combustion (ATAC) - a new combustion process for internal combustion en-

gines. SAE Paper, 1979.

[47] P. M. Najt and D. E. Foster. Compression-ignited homogeneous charge com-

bustion. SAE Paper, 830264, 1983.

[48] M. Yao, Z. Zheng, and H. Liu. Progress and recent trends in homogeneous

charge compression ignition (HCCI) engines. Progress in Energy Combustion

Science, 35:398–437, 2009.

[49] F. Zhao, T. N. Asmus, D. Assanis, J. E. Dec, J. A. Eng, and P. M. Najt. Ho-

mogeneous charge compression ignition (HCCI) engines. SAE International,

2003.

[50] H. Zhao. HCCI and CAI engines for the automotive industry. Woodhead

Publishing, Cambridge, England, 2007.

BIBLIOGRAPHY 163

[51] L. Koopmans, R. Ogink, and I. Denbratt. Direct gasoline injection in the

negative valve overlap of a homogeneous charge compression ignition engine.

SAE Paper, 2003-01-1854, 2003.

[52] T. Urushiahara, K. Hiraya, A. Kakuho, and T. Itoh. Expansion of HCCI

operating region by the combination of direct fuel injection, negative valve

overlap and internal fuel reformation. SAE Paper, 2003-01-0749, 2003.

[53] H. H. Song and C. F. Edwards. Optimization of recompression reaction for

low-load operation of residual-effected HCCI. SAE Paper, 2008-01-0016, 2008.

[54] R. P. Fitzgerald and R. R. Steeper. Thermal and chemical effects of NVO

fuel injection on HCCI combustion. SAE International Journal of Engines,

3:46–64, 2010.

[55] H. H. Song and C. F. Edwards. Understanding chemical effects in low-load-

limit extension of homogeneous charge compression ignition engines via recom-

pression reaction. International Journal of Engine Research, 10(4):231–250,

2009.

[56] H. H. Song, A. Padmanabhan, N. B. Kaahaaina, and C. F. Edwards. Ex-

perimental study of recompression reaction for low-load operation in direct-

injection homogeneous charge compression ignition engines with n-heptane

and i-octane fuels. International Journal of Engine Research, 10(4):215–229,

2009.

[57] H. Santoso, J. Matthews, and W. Cheng. Characteristics of HCCI engine

operating in the negative-valve-overlap mode. SAE Paper, 2005-01-2133, 2005.

[58] Y. Urata, M. Awasaka, J. Takanashi, T. Kakinuma, T. Hakozaki, and

A. Umemoto. A study of gasoline-fuelled HCCI engine equipped with and

electromagnetic valve train. SAE Paper, 2004-01-1898, 2004.

164 BIBLIOGRAPHY

[59] N. Wermuth, H. Yun, and P. M. Najt. Enhancing light load HCCI combustion

in a direct injection gasoline engine by fuel reforming during recompression.

SAE International Journal of Engines, 2:823–836, 2009.

[60] T. Aroonsrisopon, P. Werner, J. O. Waldman, V. Sohm, D. E. Foster,

T. Morikawa, and M. Iida. Expanding the HCCI operation with the charge

stratification. SAE Paper, 2004-01-1756, 2004.

[61] A. W. Berntsson and I. Denbratt. HCCI combustion using charge stratification

for combustion control. SAE Paper, 2007-01-0210, 2007.

[62] H. Nakano, O. T. Lim, and M. Iida. An investigation on the effect of thermal

stratification on HCCI combustion by using rapid compression machine. SAE

Paper, 2007-01-1870, 2007.

[63] M. Sjoberg, J. E. Dec, A. Babajimopoulos, and D. Assanis. Comparing en-

hanced natural thermal stratification against retarded combustion phasing for

smoothing of HCCI heat-release rates. SAE Transactions, 113:1557–1575, pa-

per 2004-01-2994.

[64] J. E. Dec and M. Sjoberg. Isolating the effects of fuel chemistry on combustion

phasing in an HCCI engine and the potential of fuel stratification for ignition

control. SAE Transactions, 13(4):239–257, paper 2004-01-0557.

[65] S. De Zilwa and R. R. Steeper. Predicting NOx emissions from HCCI engines

using LIF imaging. SAE Paper, 2006-01-0025, 2006.

[66] T. Fujikawa, Y. Hattori, and K. Akihama. Quantitative 2-D fuel distribution

measurements in an SI engine using laser-induced fluorescence with suitable

combination of fluorescence tracer and excitation wavelength. SAE Paper,

972944, 1997.

[67] M. C. Thurber, F. Grisch, and R. K. Hanson. Temperature imaging with

single- and dual-wavelength acetone planar laser-induced fluorescence. Optics

Letters, 22:251–253, 1997.

BIBLIOGRAPHY 165

[68] A. Kakuho, M. Nagamine, Y. Amenomori, T. Urushiahara, and T. Itoh. In-

cylinder temperature distribution measurement and its application to HCCI

combustion. SAE Paper, 2006-01-1202, 2006.

[69] M. Luong, R. Zhang, C. Schulz, and V. Sick. Toluene laser-induced fluo-

rescence for in-cylinder temperature imaging in internal combustion engines.


[70] D. A. Rothamer. Development and application of infrared and tracer-based

planar laser-induced fluorescence imaging diagnostics. PhD thesis, Stanford

University, 2007.

[71] J. E. Dec and W. Hwang. Characterizing the development of thermal stratifica-

tion in an HCCI engine using planar-imaging thermometry. SAE International

Journal of Engines, 2(1):421–438, 2009.

[72] C. Schulz and V. Sick. Tracer-LIF diagnostics: quantitative measurement

of fuel concentration, temperature and fuel/air ratio in practical combustion

systems. Progress in Energy Combustion Science, 31:75–121, 2005.

[73] R. R. Steeper and S. De Zilwa. Co-evaporative tracer-PRF mixtures for LIF

measurements in optical HCCI engines. SAE Paper, 2005-01-0111, 2005.

[74] W. Koban, J. D. Koch, R. K. Hanson, and C. Schulz. Absorption and fluores-

cence of toluene vapor at elevated temperatures. Physical Chemistry Chemical

Physics, 6:2940–2945, 2004.

[75] J. D. Koch. Fuel Tracer Photophysics for Quantitative Planar Laser-Induced

Fluorescence. PhD thesis, Stanford University, 2005.

[76] P. Guibert, V. Modica, and C. Morin. Influence of pressure, temperature and

gas phase composition on biacetyl laser-induced fluorescence. Experiments in

Fluids, 40:245–256, 2006.

166 BIBLIOGRAPHY

[77] D. A. Rothamer, J. A. Snyder, R. K. Hanson, and R. R. Steeper. Optimiz-

ing of a tracer-based PLIF diagnostic for simultaneous imaging of EGR and

temperature in IC engines. Applied Physics B, 99:371–384, 2010.

[78] F. Ossler and M. Alden. Measurements of picosecond laser induced fluores-

cence from gas phase 3-pentanone and acetone: Implications to combustion

diagnostics. Applied Physics B-Lasers and Optics, 64(4):493–502, 1997.

[79] M. C. Thurber. Acetone Laser-Induced Fluorescence for Temperature and

Multiparameter Imaging in Gaseous Flows. PhD thesis, Stanford University,

1999.

[80] N. Wermuth and V. Sick. Absorption and fluorescence data of acetone, 3-

pentanone, biacetyl, and toluene at engine-specific combinations of tempera-

ture and pressure. SAE Paper, 2005-02-2090, 2005.

[81] L. S. Yuen, J. E. Peters, and R. P. Lucht. Pressure dependence of laser-induced

fluorescence from acetone. Applied Optics, 36(15):3271–3277, 1997.

[82] J. B. Ghandhi and P. G. Felton. On the fluorescence behavior of ketones at

high temperatures. Experiments in Fluids, 21:143–144, 1996.

[83] H. W. Coleman and W. G. Steele Jr. Experimentation and Uncertainty Anal-

ysis for Engineers. Wiley-Interscience, New York, 2nd edition, 1999.

[84] P.R. Bevington and D. K. Robinson. Data Reduction and Error Analysis for

the Physical Sciences. McGraw-Hill, New York, 1992.

[85] D. A. Rothamer and J. B. Ghandhi. On the calibration of single-shot planar

imaging techniques in engines. SAE Paper, 2002-01-0748, 2002.

[86] M. C. Thurber, F. Grisch, B. J. Kirby, M. Votsmeier, and R. K. Hanson.

Measurements and modeling of acetone laser-induced fluorescence with impli-

cations for temperature-imaging diagnostics. Applied Optics, 37:4963–4978,

1998.

BIBLIOGRAPHY 167

[87] F. Braeuer, A.and Beyrau and A. Leipertz. Laser-induced fluorescence of

ketones at elevated temperatures for pressure up to 20 bar by using 248 nm

excitation laser wavelength: experiments and model improvements. Applied

Optics, 45:4982–4989, 2006.

[88] W. Koban, J. D. Koch, R. K. Hanson, and C. Schulz. Oxygen quenching of

toluene fluorescence at elevated temperatures. Applied Physics B, 80:777–784,

2005.

[89] J. A. Snyder, R. K. Hanson, R. P. Fitzgerald, and R. R. Steeper. Dual-

wavelength PLIF measurements of temperature and composition in an optical

HCCI engine with negative valve overlap. SAE International Journal of En-

gines, 2:460–474, 2009.

[90] B. Cheung and R. K. Hanson. Photophysical measurements of 3-pentanone

at elevated temperatures and pressures. in preparation.

[91] A. Lozano, B. Yip, and R. K. Hanson. Acetone: a tracer for concentration

measurements in gaseous flows by planar laser-induced fluorescence. Experi-

ments in Fluids, 13:369–376, 1992.

[92] H. Zuckermann, B. Schmitz, and Y. Hass. Acetone photophysics in seeded

supersonic molecular beams. Journal of Physical Chemistry, 93:4083–4091,

1989.

[93] M. Baba and I. Hanazaki. The s1, 1a2(n,[pi]*) state of acetone in a supersonic

nozzle beam. methyl internal rotation. Chemical Physics Letters, 103(2):93 –

97, 1983.

[94] A. Lozano. Laser-Excited Luminescent Tracers for Planar Concentration Mea-

surements in Gaseous Jets. PhD thesis, Stanford University, 1992.

[95] D. A. Hansen and E. K. C. Lee. Radiative and nonradiative transitions in the

first excited singlet state of symmetrical methyl-substituted acetones. Journal

of Chemical Physics, 62:183–189, 1975.

168 BIBLIOGRAPHY

[96] R. D. Martinez, A. A. Buitrago, N. W. Howell, C. H. Hearn, and J. A. Joens.

The near U.V. absorption spectra of several aldehydes and ketones at 300 K.

Atmospheric Environment Par A: General Topics, 26:785–792, 1992.

[97] K. A. Sahetchian, R. Rigny, and S. Circan. Identification of the hydroperox-

ide formed by isomerization reactions during the oxidation of n-heptane in a

reactor and CFR engine. Combustion and Flame, 85:511–511, 1991.

[98] H. J. Curran, P. Gaffuri, W. J. Pitz, C. K. Westbrook, and Leppard W.

R. Autoignition chemistry in a motored engine: An experimental and ki-

netic modeling study. Symposium (International) on Combustion, 26(2):2669

– 2677, 1996.

[99] Y. Yang and A. Boehman. Experimental study of cyclohexane and methylcy-

clohexane oxidation at low to intermediate temperature in a motred engine.

Proceedings of the Combustion Institute, 32:419–426, 2009.

[100] Y. Zhang and A. Boehman. Experimental study of the autoignition of C8H16O2

ethyl and methyl esters in a motored engine. Combustion and Flame, 157:546–

555, 2010.

[101] W. Koban, J. D. Koch, V. Sick, N. Wermuth, R. K. Hanson, and C. Schulz.

Predicting LIF signal strength for toluene and 3-pentanone under engine-

related temperature and pressure conditions. Proceedings of the Combustion

Institute, 30:1545–1553, 2005.

[102] M. Sjoberg and J. E. Dec. An investigation of the relationship between mea-

sured intake temperature, BDC temperature, and combustion phasing for pre-

mixed and DI HCCI engines. SAE Transactions, 113:1557–1575, 2004-01-1900.

[103] H. J. Curran, P. Gaffuri, W. J. Pitz, and C. K. Westbrook. A comprehensive

modeling study of iso-octane oxidation. Combustion and Flame, 129:253–280,

2002.

BIBLIOGRAPHY 169

[104] J. D. Koch and R. K. Hanson. A photophysics model for 3-pentanone PLIF:

temperature, pressure and excitation wavelength dependences. Proceedings of

the 41st AIAA Aerospace Science Meeting and Exhibit (Reno 2003), Paper

2003-0403, 2003.

[105] L. A. Kranendonk, A. W. Caswell, A. M. Myers, and S. T. Sanders.

Wavelength-agile laser sensors for measuring gas properties in engines. SAE

Paper, 2003-01-1116, 2003.

[106] L. A. Kranendonk, J. W. Walewski, S. T. Sanders, R. Huber, and J. G. Fu-

jimoto. Measurements of gas temperature in a HCCI engine using a Fourier

Domain Mode Locking laser. SAE Paper, 2006-01-1366, 2006.

[107] D. W. Mattison, J. B. Jeffries, R. K. Hanson, R. R. Steeper, S. De Zilwa,

J. E. Dec, M. Sjoberg, and W. Hwang. In-cylinder gas temperature and water

concentration measurements in HCCI engines using a multiplexed wavelength

diode-laser system: sensor development and initial demonstration. Proceedings

of the Combustion Institute, 31:791–795, 2007.

[108] J. E. Dec, W. Hwang, and M. Sjoberg. An investigation of thermal stratifica-

tion in HCCI engines using chemiluminescence imaging. SAE Transactions,

115(3):759–776, paper 2006-01-1518.

[109] M. Schafer, W. Ketterle, and J. Wolfrum. Saturated 2D-LIF of OH and 2D

determination of effective collisional lifetimes in atmospheric pressure flames.


[110] C. D. Carter, G. B. King, and N. M. Laurendeau. Saturated fluorescence

measurements of the hydroxyl radical in laminar high pressure C2H6/O2/N2

flames. Applied Optics, 31:1511–1522, 1992.

[111] W. P. Partridge, J. R. Reisel, and N. M. Laurendeau. Laser-saturated fluores-

cence measurements of nitric oxide in an inverse diffusion flame. Combustion

and Flame, 116(1-2):282–290, 1999.

170 BIBLIOGRAPHY

[112] Y. Takubo, H. Yano, H. Matsuoka, and M. Shimaza. Saturation behavior of

laser-induced CH fluorescence in a propane-air flame. Journal of Quantitative

Spectroscopy and Radiative Transfer, 30:163–168, 1982.

[113] P. A. Bonczyk and J. A. Shirley. Measurement of CH and CN concentration

in flames by laser-induced saturated fluorescence. Combustion and Flame,

34:253–264, 1979.

[114] B. R. Petersen, J. B. Ghandhi, and J. D. Koch. Fluorescence saturation

measurements of 3-pentanone. Applied Physics B, 93:639–644, 2008.

[115] A. E. Siegman, M. W. Sasnett, and T. F. Johnston. Choice of clip levels

for beam width measurements using knife-edge techniques. IEEE Journal of

Quantum Electronics, 27(4):1098–1104, 1991.

[116] C. B. Roundy. CCD camera baseline calibration and its effects on imaging

processing and laser beam analysis. SPIE, 3110:860–879, 1997.

[117] A. E. Siegman, G. Nemes, and J. Serna. How to (maybe) measure laser beam

quality. In DPSS (Diode Pumped Solid State) Lasers: Applications and Issues,

page MQ1. Optical Society of America, 1998.

[118] K. Hiraya, K. Hasegawa, T. Urushuhara, A. Liyama, and T. Itoh. A study of

gasoline fueled compression ignition engine - a trial of peration region expan-

sion. SAE Paper, 2002-01-0416, 2002.

[119] A. W. Berntsson and I. Denbratt. Optical study of HCCI combustion using

NVO and an SI stratified charge. SAE Paper, 2007-01-0012, 2007.

[120] D. A. Rothamer, J. A. Snyder, R. K. Hanson, and R. R. Steeper. Simultane-

ous imaging of exhaust gas residuals and temperature during HCCI combus-

tion. Proceedings of the Combustion Institute, doi:10.1016/j.proci.2008.07.018,

2009.

BIBLIOGRAPHY 171

[121] S. De Zilwa and R. R. Steeper. Acquisition of corresponding fuel distribution

and emissions measurements in HCCI engines. SAE Paper, 2005-01-3748,

2005.

[122] R. P. Fitzgerald, R. R. Steeper, and J. A. Snyder. Effects of LIF tracers on

combustion in a DI HCCI engine. SAE Int. J. Fuels Lubr., 1(1):1491–1502,

2008.

[123] M Larsson, I. Denbratt, and L. Koopmans. Ion current sensing in an optical

HCCI engine with negative valve overlap. SAE Paper, 2007-01-0009, 2007.

[124] H. Persson, A. Hultqvist, B. Johansson, and A. Remon. Investigation of the

early flame development in spark-assisted HCCI combustion using high-speed

chemiluminescence. SAE Paper, 2007-01-0212, 2007.

[125] M. Sjoberg, J. E. Dec, and N. P. Cernansky. The potential of thermal strat-

ification and combustion retard for reducing pressure-rise rates in HCCI en-

gines, based on multi-zone modeling and experiments. SAE Transactions,

114(3):236–251, paper 2005-01-0113.

[126] A. Hultqvist, M. Christensen, B. Johansson, M. Richter, J. Nygren, H. Hult,

and M. Alden. The HCCI combustion process in a single cycle - high-speed fuel

tracer LIF and Chemiluminescence imaging. SAE Transactions, 111(3):913–

927, paper 2002-01-0424.

[127] J. A. Snyder, N. Dronniou, J. E. Dec, and R. K. Hanson. Development of

ketone-based PLIF temperature diagnostics for application in HCCI engines.

Applied Optics, (to be submitted), 2011.

[128] J. E. Dec and M. Sjoberg. A parametric study of HCCI combustion - the

sources of emission at low loads and the effects of GDI fuel injection. SAE

Transactions, 112:1119–1141, paper 2003-01-0752.

[129] J. B. Heywood. Internal combustion engine fundamentals. McGraw-Hill, 1988.

172 BIBLIOGRAPHY

[130] N. Graf, J. Gronki, C. Schulz, T. Baritaud, J. Cherel, P. Duret, and J. Lavy.

In-cylinder combustion visualization in an auto-igniting gasoline engine using

fuel tracer- and formaldehyde-LIF imaging. SAE Paper, 2001-01-1924, 2001.

[131] A. Arnold, A. Buschmann, B. Cousyn, M. Decker, F. Vannobel, V. Sick, and

J. Wolfrum. Simultaneous imaging of fuel and hydroxyl radicals in an in-line

four-cylinder SI engine. SAE Paper, 932696, 1993.

[132] D. Frieden and V. Sick. Investigation of the fuel injection, mixing and com-

bustion processes in an SIDI engine using quasi-3D LIF imaging. SAE Paper,

2003-01-0068, 2003.

[133] D. A. Knaus, F. C. Gouldin, P. C. Hinze, and P. C. Miles. Measurement of

instantaneous flamelet surface normals and the burning rate in a SI engine.

SAE Paper, 1999-01-3543, 1999.

[134] D. A. Rothamer and J. B. Ghandhi. Determination of flame-front equivalence

ratio during stratified combustion. SAE Paper, 2003-01-0069, 2003.

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DEVELOPMENT AND APPLICATION OF TRACER-BASED PLANAR …