The influence of nitrogen chemistry on the effectiveness ...8th US Combustion Meeting – Paper # 070RK-0371 Topic: Reaction Kinetics 2 be used to dynamically control fuel reactivity

Paper # 070RK-0371 Topic: Reaction Kinetics

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8th US National Combustion Meeting

Organized by the Western States Section of the Combustion Institute

and hosted by the University of Utah

May 19-22, 2012

The influence of nitrogen chemistry on the effectiveness of alkyl nitrates as cetane enhancers: a modeling study

S.S. Goldsborough1

1Center for Transportation Research, Argonne National Laboratory

Argonne, IL 60439-4815, USA

Alkyl nitrates such as 2-ethylhexyl nitrate (EHN) can be used as cost-effective fuel additives to

improve the ignition quality of various fuels. They have been employed in both diesel and

gasoline engines, using conventional combustion schemes as well as alternative combustion

processes. Rapid elimination of the nitrate group early in the combustion process yields active

chemical species, including a alkyl radicals, aldehydes and nitric oxide. These decomposition

products, along with exothermicity associated with these processes, stimulate the breakdown of

the fuel so that resulting ignition timings can be quite different from unadditized fuel mixtures. Chemical kinetic models developed to represent these processes primarily focus on the pathways

of the generated alkyl radicals and typically utilize limited NOx sub-mechanisms to track the

interactions of the eliminated NO. However, this approach is inadequate to fully describe the

sensitizing effects over a range of conditions relevant to both conventional and advanced

combustion engines. This modeling study investigates the influence of detailed nitrogen

chemistry on the effectiveness of EHN where this is primarily indicated by the shift in ignition

timings. Specifically, reactions including nitrous acid (HONO), hydrogen cyanide (HCN) and

others, along with fuel-specific interactions, e.g., alkyl peroxy radicals (RO2) reactions, are taken

into account in the current model. Results are presented covering a range of conditions where it is

found that, particularly under scenarios of high doping (e.g., >3%), interactions with nitrogen

containing species can lead to noticeable changes in ignition timing. This seems to be especially significant for rich mixtures. Further investigations will provide insight into the reactions

controlling these phenomena, while experimental validation of the model will ensure its

robustness.

1. Introduction

Alkyl nitrates are a class of chemicals that have been identified as effective fuel additives which can be used in

very small quantities (e.g., ~1% liquid volume basis) to improve the ignition quality of a range of fuels.

Ignition quality is often described using cetane number (CN), or alternatively cetane index, where for a

particular fuel this can be measured using several methods employing a CFR engine (ASTM D-613), ignition

quality tester (ASTM D-6890) or fuel ignition tester (ASTM D-7170). High cetane numbers (>60) indicate

very reactive fuels, such as ones with significant amounts of linear paraffins, while low values (<30) indicate

less reactive fuels, such as those with high iso-paraffinic or aromatic content. Standards for US petroleum

diesel require a minimum CN of 40, while the European Union mandates values of at least 51. Low fuel

reactivity can lead to problems, in conventional diesel combustion with engine power output, deposits within

the combustion chamber, high emissions, rough operation (leading to noise and vibration issues), and cold

starting. Fuel reactivity has also been identified as an important parameter influencing the performance and

controllability of advanced combustion schemes, such as homogeneous charge compression ignition (HCCI) [1] and reactivity controlled compression ignition (RCCI) [2]. It has been suggested that fuel additives could

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US Combustion Meeting – Paper # 070RK-0371 Topic: Reaction Kinetics

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be used to dynamically control fuel reactivity during engine operation to cover a wide range of combustion

modes.

Alkyl nitrates, and other cetane enhancers such as peroxides, e.g., di-tert-butyl peroxide (DTBP), are highly

reactive compounds containing a weak chemical bond and thus decompose rapidly at modest temperatures.

This means that in practical combustors they break down early in the combustion process, substantially before

the fuel can. The decomposition process yields chemical species that are very active; in the case of alkyl

nitrates, alkyl radicals, aldehydes and nitric oxide are formed. These products interact with the fuel and other

constituent gases, e.g., oxygen, to accelerate the ignition process. The early reactions often have some

exothermicity associated with them and thus provide a thermal stimulant to supplement the additional chemical

pathways that are also available. Alkyl nitrates are advantageous relative to other cetane enhancers because of

their low cost and chemical stability outside of the combustion chamber. Peroxides, for instance, have been

shown to react with the fuel during storage so that rates of gum, varnish and sediment formation can increase

in borderline unstable fuels.

Alkyl nitrates and peroxides have a long history of testing in fundamental laboratory experiments, as well as

application in combustion engines, while a number of detailed theoretical and modeling studies have also been

undertaken [3-26]. Single shot spray chambers have been used [3,4], as have rapid compression machines [5-

7], shock tubes [8,9] and flow reactors [10]. Conventional and low temperature combustion (LTC) direct

injection (DI) schemes have been employed in engine studies [11,12], along with HCCI [13-16] and RCCI [17-

20] modes of operation. Chemical kinetic models have been developed to predict the decomposition behavior

of EHN and DTBP, and the sensitizing effects on some fuels of interest (e.g., n-heptane).

As yet however, there is a lack of complete understanding regarding how different fuel additives interact with

various fuel components (e.g., paraffins, branched alkanes, aromatics, olefins, etc.) across a wide range of

engine operating conditions. In addition, there is a need to accurately predict these interactions, as well as the

impact on pollutant formation (e.g., NOx). This study attempts to address some of these needs where the

effects of nitrogen chemistry are investigated for fuel blends doped with EHN. A detailed chemical kinetic

model is compiled and simulations are conducted over a range of fuel loading and additive doping conditions.

Gasoline is considered as the fuel due to its relevance to some LTC modes [27] as well as RCCI [18].

Adiabatic, constant volume computations are conducted and trends in ignition timing are reported. Some

insight is provided at two select temperature and pressure conditions. The rest of this paper is organized as

follows. First, the chemical kinetic model is described with particular attention focused on the nitrogen sub-

mechanism. The simulation framework is then discussed followed by a presentation of the results of the

computations. The study is then summarized with a highlight of additional work currently underway.

2. Chemical Kinetic Model

The chemical kinetic model used for this study consists of a base fuel mechanism, a sub-mechanism for the

fuel additive, and a sub-mechanism for nitrogen chemistry. The fuel mechanism is Lawrence Livermore

National Laboratory’s gasoline surrogate model, which includes decomposition and interaction pathways for

four primary fuel components including n-heptane, iso-octane, toluene and pentene [28-30]. Presently,

cycloalkanes are not included in the gasoline model. The sub-mechanism for 2-ethyl-hexyl nitrate is based on

Iizuka and Surianarayanan’s compilation [26]. The sub-mechanism for nitrogen chemistry includes

components from GRIMech 3.0 [31], along with updates from recent work by Dagaut and co-workers [32-35],

Glarborg and co-workers [36-37] Faravelli and co-workers [38], Battin-Leclerc and co-workers [39], and Naik

and co-workers [40]. In particular, reactions including nitrous acid (HONO), hydrogen cyanide (HCN) and

others, along with fuel-specific interactions, e.g., RH+NO2=R+HONO are included. Additional reactions not

considered in previous models, e.g., RH+NO=R+HNO and RO2+NO=RO+NO2, are compiled for this study.

Table 1 provides a brief list of some fuel-specific reactions that are included in the nitrogen sub-mechanism.

The thermochemistry for new nitrogen-containing species, e.g., RONO2, is computed using the THERM

software which employs group additivity methods [48]. It should be noted that while many of the sub-

mechanisms of the model have been validated, the overall model has not yet been rigorously compared against

experimental data. This is important activity currently underway and will be reported in the future.

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Table 1 – Fuel-specific reactions including nitrogen included in the kinetic model

RH NO R HNO (R1) [41]

2RH NO R HONO (R2) [39]

R NO olefin HNO (R3) [42]

R NO RNO (R4) [43]

2 2R NO RNO (R6) [40]

2 2RO NO RO NO (R7) [44]

2 2RO NO RONO (R8) [45]

RO NO R O HNO (R9) est. based on [36,37]

2 2RO NO RONO (R10) est. based on [36,37]

RNO radical olefin NO radical (R11) [36]

2 2RNO radical olefin NO radical (R12) [36]

2RONO R O HONO (R13) [47]

2 2RONO OH RO HONO (R14) est. based on [36,37]

3. Simulation Framework

The simulations are conducted utilizing the gas-phase, chemical kinetics solver, HCT (Hydrodynamics,

Chemistry and Transport [49]). The framework of HCT allows one-dimensional, Lagrangian calculations, e.g.,

simulating propagating flames, however this study only utilizes a single computational zone homogeneous in

both composition and temperature. The volume of the zone remains fixed throughout the simulation, and it is

assumed to be well insulated, i.e., adiabatic.

4. Results

This study investigates the effect of nitrogen chemistry covering a range of fuel loadings and doping levels. In

particular, details are provided at an equivalence ratio () of 1.0 and a doping level of 3% volumetric, while it

is acknowledged that the trends seem to indicate that at higher doping levels the influence appears to be more

significant. Doping levels of this magnitude, while high for conventional DI applications which may use less

than 1%, are relevant to advanced combustion concepts, e.g., RCCI [18,19]. For this study, two primary

reference fuel (PRF) blends are considered, PRF70 and PRF100, where this notation indicates liquid

volumetric fractions of 70% iso-octane / 30% n-heptane, and 100% iso-octane / 0% n-heptane, respectively.

The blends have cetane numbers of approximately 27 and 15, respectively, with corresponding octane numbers

of 70 and 100, respectively. These blends are good candidates to illustrate the influence of EHN for such

gasoline-representative fuels. Future studies are planned to investigate the interactions between EHN and

other gasoline components, e.g., aromatics and olefins.

Results are presented for parametric simulations covering lean, stoichiometric and rich mixtures ( = 0.35, 1.0

and 2.0, respectively) with EHN doping levels of 0.0, 0.1, 1.0 and 3.0% volumetric, at temperatures spanning

625 to 1333 K. The oxygen concentration is fixed for this study at atmospheric levels (~21%) and the pressure is 20 bar. It is noted that though not illustrated here, similar trends are seen in the mechanism predictions for

dilute, high pressure conditions. Figure 1 summarizes the parametric results where the predicted ignition delay

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Figure 1 – Computed ignition delay times as a function of inverse temperature for the two fuel blends covering a range of fuel loadings and additive doping levels.

times are plotted as a function of inverse temperature, in typical Arrhenius fashion. The notation ‘mech0’

indicates that the simulations are conducted using the base, complete nitrogen sub-mechanism as described in

Section 2.

In Fig. 1 there are a number of trends that are visible. First, very small quantities of EHN dopant can have a

substantial impact on fuel reactivity, especially at low temperatures, where much earlier ignition delay times are observed. This is more significant at the richer fuel loadings. At high temperatures however, e.g., T>1000

K, the model predicts that there is little impact on reactivity, and thus ignition timing, for small fractions of

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Figure 2 – Computed ignition delay times as a function of inverse temperature for the two fuel blends at = 1.0 and 3% EHN

doping where four iterations of the nitrogen sub-mechanism are employed.

dopant (e.g., 0.1%). This is most likely due to the fact that the predominant ignition pathways at high

temperature are less dependent on fuel structure, so that influences on RO2 isomerization via additional heptyl

radicals, for instance are not relevant. At high dopant levels it can be seen that the model indicates a more

substantial increase in reactivity at high temperatures, where this is due to the contributions of the nitrogen

chemistry (as will be illustrated shortly). At low temperatures, it can be seen that the model predicts that as the

doping level is increased, the fuel reactivity is not necessarily increased. In some cases it actually is predicted

to decrease. This feature is more substantial for the leaner mixtures, and for the less reactive fuel blend, i.e.,

PRF100. This is also due to the contributions of the nitrogen chemistry and in particular the fuel-specific

interactions.

To investigate the trends observed in Fig. 1 additional simulations are conducted where these are limited to =

1.0 and a doping level of 3% EHN volumetric. For these calculations three variations of the nitrogen sub-

mechanism are employed. The first, labeled ‘mech1’, includes just the reactions in GRIMech 3.0 [31]. The

second, labeled ‘mech2’, includes GRIMech 3.0 reactions plus those compiled by Glarborg and co-workers

[36-37]. These contain the HONO sub-mechanism. Finally, the last iteration, ‘mech3’, includes the GRIMech

3.0 reactions, Glarborg et al.’s reactions, as well as Dagaut and co-workers reactions. These contain the HCN

sub-mechanism, as well as others.

Figure 2 illustrates the effects of these modifications where the computed ignition delay times are plotted as a

function of inverse temperature. Here it can be seen that at high temperatures the nitrogen interactions are

complex, where the four iterations yield somewhat different results. At low temperatures it is primarily the

fuel-specific, nitrogen interactions that are important. To investigate these features further two cases are

considered, Case 1, which has a temperature of 714 K, and Case 2, which has a temperature of 1111 K. These

cases are probed in more detail with the results presented in the following figures.

Figure 3 presents the computed temperatures as a function of time for Case 1 using the two different fuel

blends. Here it can be seen that ‘mech1’, ‘mech2’ and ‘mech3’ yield very similar results with much earlier

low temperature heat release and correspondingly earlier high temperature ignition. The results for ‘mech0’

however, indicate some earlier exothermicity, however the magnitude is not as great as with the other three

mechanism iterations, and for PRF100 the resulting high temperature ignition is delayed past the undoped fuel

behavior. These features are explored more in Fig. 4 where the mole fractions of HO2 and QOOH are plotted

as a function of temperature. HO2 and QOOH are two important radical species at the low temperature used in

Case 1. Note that the results for HO2 are shifted by +50PPM for clarity. Here it can be seen that while

‘mech1’, ‘mech2’ and ‘mech3’ show slight differences, overall the behavior is similar for these three

iterations. The results for ‘mech0’ however indicate that at the 3% doping level used here the flux through the

RO2 isomerization channel to QOOH is inhibited, and this appears to be a significant cause for the extended

ignition times seen in Fig. 3. An important reaction influencing this is RO2+NO=RO+NO2, however further

investigation of this is in order.

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Figure 3 – Computed temperature as a function of time for the two fuel blends at = 1.0 and 3% EHN doping where four iterations

of the nitrogen sub-mechanism are employed.

Figure 4 – Computed mole fractions of HO2 and QOOH as a function of temperature for the two fuel blends at = 1.0 and 3% EHN

doping where four iterations of the nitrogen sub-mechanism are employed.

Figure 5 next presents the computed temperatures as a function of time for Case 2 using the two different fuel

blends. As opposed to Fig. 3, ‘mech1’, ‘mech2’ and ‘mech3’ yield noticeably different results where the

mixtures are increasingly reactive as the additional reaction pathways are added to the model. All of the

mechanism iterations predict substantial ‘pre-ignition’ heat release, and this appears to be tied to the shifts in

ignition timing for the simulations undertaken here. These features are explored more in Fig. 6 where the mole

fractions of H2O, H2O2 and OH are plotted as a function of time. H2O2 and OH are two important radicals at

the intermediate temperature used in Case 2. H2O is indicative of the exothermicity of the system. Here it can

be seen that the concentrations for all four iterations are different, though ‘mech0’ and ‘mech3’ are very

similar, as should be expected. The results for ‘mech0’ and ‘mech3’ indicate the highest levels of H2O early in

the decomposition / ignition process, and this corresponds to the temperature-time results seen in Fig. 5. The

differences seen in these figures illustrate the significant influence that the nitrogen chemistry has on the

kinetic processes at these conditions, and this warrants further investigation to understand which reaction

pathways are most critical, in addition to validating the model predictions.

5. Summary and Future work

A chemical kinetic model is compiled here to investigate the sensitizing effects that alkyl nitrates such as 2-ethylheptyl-nitrate have on the ignition of fuels that are relevant to advanced combustion processes. In

particular, attention was focused on the influence of the nitrogen chemistry. Simulations are conducted across

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Figure 5 – Computed temperature as a function of time for the two fuel blends at = 1.0 and 3% EHN doping where four iterations

of the nitrogen sub-mechanism are employed.

Figure 5 – Computed mole fractions of H2O, H2O2 and OH as a function of temperature for the two fuel blends at = 1.0 and 3%

EHN doping where four iterations of the nitrogen sub-mechanism are employed.

a range of fuel loadings and doping levels and trends in ignition timing are identified. It is found that small

quantities of dopant can have a significant influence, especially at lower temperatures and higher equivalence

ratios. In conventional DI applications, the fuel and additizer will experience temperatures that are locally

cooler and richer than the bulk gas due to evaporative cooling and mixing of the fuel so this feature is very

relevant. At higher temperatures, nitrogen chemistry is predicted to be influential, but only at higher doping

levels (~3%). The model predicts that high doping levels can, in some cases, e.g., rich mixtures, delay the

ignition timing. Certainly more work can be undertaken to better understand the model results by isolating the

influential reaction pathways, e.g., through sensitivity analyses, and to improve the model predictions through

the use of experimental data covering a wide range of conditions. Future studies investigating interactions of

various fuel structures, e.g., aromatics and olefins, with alkyl nitrates and other cetane improvers will help to

improve the chemical kinetic model, and could also aid in the development of future additive formulations.

Acknowledgments

This manuscript has been created in part by UChicago Argonne, LLC, Operator of Argonne National

Laboratory ("Argonne"). Argonne, a U.S. Department of Energy Office of Science laboratory, is operated

under Contract No. DE-AC02-06CH11357. The U.S. Government retains for itself, and others acting on its behalf, a paid-up non-exclusive, irrevocable worldwide license in said article to reproduce, prepare derivative

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works, distribute copies to the public, and perform publicly and display publicly, by or on behalf of the

Government.

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The influence of nitrogen chemistry on the effectiveness ...8th US Combustion Meeting – Paper # 070RK-0371 Topic: Reaction Kinetics 2 be used to dynamically control fuel reactivity