PREDICTION MODELS FOR THE FLASH POINT OF

PURE COMPONENTS

Edna M. Valenzuela, Richart Vázquez-Román,

Suhani Patel, and M. Sam Mannan

2010 MARY KAY O’CONNOR PROCESS

SAFETY INTERNATIONAL SYMPOSIUM

College Station, Texas

October 26-28, 2010

•Introduction

•Literature

review

•Experimental

determination

•Theoretical

developments

•The New

Development

•Conclusions

S-2

• Definition: The flash point of a liquid is the lowest

temperature at which it gives off enough vapor to form an

ignitable mixture with air 1.

• The vapor will burn but only briefly; inadequate vapor is

produced to maintain combustion 1.

• The lower flammability limit corresponds to the liquid-

vapor equilibrium 2.

1 Crowl, D. A. and J. F. Louvar (2002). Chemical process safety, fundamentals with applications,

Jersey, Prentice Hall International Series in the Physical and Chemical Engineering Sciences2 Prugh, R. W. (2008). "The relationship between flash point and LFL with application to hybrid

mixtures." Process Safety Progress 27(2): 156-163.

• The flash point is used as a

criterion to indicate the hazard

of flammable materials

(safety). High values are

preferred.

•Introduction

•Literature

review

•Experimental

determination

•Theoretical

developments

•The New

Development

•Conclusions

S-3

1 Crowl, D. A. and J. F. Louvar (2002). Chemical process safety, fundamentals with applications,

Jersey, Prentice Hall International Series in the Physical and Chemical Engineering Sciences

Relationships between various flammability properties 1

•Introduction

•Literature

review

•Experimental

determination

•Theoretical

developments

•The New

Development

•Conclusions

S-4

Objective:

Justification

Used to prevent fire and explosion of liquids

Used in control of chemical substances

Estimate the flash point temperature for pure components

•Introduction

•Literature

review

•Experimental

determination

•Theoretical

developments

•The New

Development

•Conclusions

S-5

• Noorollahy, M., A. Z. Moghadam and A. A. Ghasrodashti (2010). "Calculation of

mixture equilibrium binary interaction parameters using closed cup flash point

measurements." Chemical Engineering Research and Design 88(1): 81-86.

• Mathieu, D. (2010). "Inductive modeling of physico-chemical properties: Flash

point of alkanes." Journal of Hazardous Materials 179(1-3): 1161-1164.

• Liaw, H.-J., V. Gerbaud, C.-C. Chen and C.-M. Shu (2010). "Effect of stirring on

the safety of flammable liquid mixtures." Journal of Hazardous Materials 177(1-

3): 1093-1101.

• Kim, S. Y. and B. Lee (2010). "A prediction model for the flash point of binary

liquid mixtures." Journal of Loss Prevention in the Process Industries 23(1): 166-

169.

• Khajeh, A. and H. Modarress (2010). "QSPR prediction of flash point of esters by

means of GFA and ANFIS." Journal of Hazardous Materials 179(1-3): 715-720.

• Xing, Y., D. Shao, W. Fang, Y. Guo and R. Lin (2009). "Vapor pressures and

flash points for binary mixtures of tricyclo [5.2.1.02.6] decane and dimethyl

carbonate." Fluid Phase Equilibria 284(1): 14-18.

• Patel, S. J., D. Ng and M. S. Mannan (2009). "QSPR Flash Point Prediction of

Solvents Using Topological Indices for Application in Computer Aided Molecular

Design." Industrial & Engineering Chemistry Research 48(15): 7378-7387.

• Gharagheizi, F. (2009). "A QSPR model for estimation of lower flammability limit

temperature of pure compounds based on molecular structure." Journal of

Hazardous Materials 169(1-3): 217-220.

•Introduction

•Literature

review

•Experimental

determination

•Theoretical

developments

•The New

Development

•Conclusions

S-6

Experimental Methods

Pure Components

Mixtures

Theoretical Methods

Pure Components (correlations)

Mixtures (Mixing rules)

Applications

•Introduction

•Literature

review

•Experimental

determination

•Theoretical

developments

•The New

Development

•Conclusions

S-7

Fact: “The flash point and flammability limits are not

fundamental properties but are defined by the specific

experimental apparatus and procedure used.“ 1

Experimental Determination2:

• The Open Cup method

• The Closed Cup method (few degrees lower than the

open-cup)

1 Crowl, D. A. and J. F. Louvar (2002). Chemical process safety, fundamentals with applications,

Jersey, Prentice Hall International Series in the Physical and Chemical Engineering Sciences2 Lance, R. C., A. J. Barnard and J. E. Hooyman (1979). "Measurement of flash points: Apparatus,

methodology, applications." Journal of Hazardous Materials 3(1): 107-119.

•Introduction

•Literature

review

•Experimental

determination

•Theoretical

developments

•The New

Development

•Conclusions

S-8

Parameters affecting the flash point temperature 1: Tester

configuration, sample size, ignition source, temperature control,

ambient pressure, sample homogeneity, operator bias.

1 Lance, R. C., A. J. Barnard and J. E. Hooyman (1979). "Measurement of flash points: Apparatus,

methodology, applications." Journal of Hazardous Materials 3(1): 107-119.

Name Method Samples

Tag closed tester ASTM D56 Liquids having flash point

temperature below 200°F

(93.3 °C)

Tag open-cup

tester

Pensky-Martens

closed tester

ASTM D1310

ASTM D93

Liquids having flash point

temperature below 325 °F

Liquids having flash point

temperature below 700°F

(369°C)

Cleveland open-

cup tester

ASTM D92 Liquids having flash point

temperature between 175-

760 °F (77-445 °C)

Setaflash closed

tester

ASTM D3278 Liquids having flash point

temperature below 230 °F

(110 °C)

•Introduction

•Literature

review

•Experimental

determination

•Theoretical

developments

•The New

Development

•Conclusions

S-9

Flash Point Estimations1

Tf is flash point T

Tb is boiling T

a, b and c are parameters

1 Satyanarayana, K. y P. G. Rao (1992). "Improved Equation to Estimate Flash Points of Organic

Compounds." Journal of Hazardous Materials, 32: 81-85.

2

2

1 Tb

c

Tb

c

f

e

eTb

cb

aT

Group a b c

Hydrocarbons 225.1 537.6 2217

alcohols 230.8 390.5 1780

Amines 222.4 416.6 1900

Acids 323.2 600.1 2970

Ethers 275.9 700.0 2879

Sulphur 238.0 577.9 2297

Esters 260.8 449.2 2217

Ketones 260.5 296.0 1908

Halogens 262.1 414.0 2154

Aldehydes 264.5 293.0 1970

Phosphorus 201.7 416.1 1666

Nitrogens 185.7 432.0 1645

Petroleum fractions 237.9 334.4 1807

•Introduction

•Literature

review

•Experimental

determination

•Theoretical

developments

•The New

Development

•Conclusions

S-10

Flash Point Estimations1

Tf is flash point T

Tb is boiling T

Flash Point Estimations for alkanes2

nk is the number of bond groups

Tk refers to the associated effective T

1 Shebeko, Y. N., A. Y. Korol'chenko, A. V. Ivanov y E. N. Alekhina (1984). "Calculation of flash

point and ignition temperatures of organic compounds." Sovietic Chemical Industry, 16: 1371.2 Mathieu, D. (2010). "Inductive modeling of physico-chemical properties: Flash point of alkanes."

Journal Hazardous Materials, doi:10.1016/j.jhazmat.2010.03.081.

TbTf 64.06.57

4

1

22

k

kkf TnT

nk Grupo Tk

1 CH3– 101.9

2 –CH2– 100.3

3 =CH– 84.9

4 =C= 58.8

•Introduction

•Literature

review

•Experimental

determination

•Theoretical

developments

•The New

Development

•Conclusions

S-11

Group contribution and neural networks1

1 Yong, P., J. Juncheng y W. Zhirong (2007). "Quantitative Structure -Property Relationship

Studies for Predicting Flash Points of Alkanes Using Group Bond Contribution Method with Back-

Propagation Neutral Network." Journal of Hazardous Materials, 147: 424-430.

Yong, P., J. Juncheng and W. Zhirong (2007). "Prediction of the flash points of alkanes by group

bond contribution method using artificial neural networks." Front. Chem. Eng. China 1(4): 390-

394.

No. Group No. Group No. Group

1 CH3−CH2− 4 −CH2−CH2− 7 =CH−CH=

2 CH2−CH= 5 −CH2−CH= 8 =CH−C≡

3 CH3−C≡ 6 −CH2−C≡ 9 ≡C−C≡

9876

54321

851.29413.24660.20685.20

802.18194.17796.0232.11180.9234.175

xxxx

xxxxxFP

•Introduction

•Literature

review

•Experimental

determination

•Theoretical

developments

•The New

Development

•Conclusions

S-12

QuantitativeStructure-Property Relationship (QSPR)

Katritzky, A. R., R. Petrukhin, R. Jain and M. Karelson (2001). "QSPR Analysis of

Flash Points." Journal of Chemical Information and Computer Sciences 41(6):

1521-1530.

Katritzky, A. R., I. B. Stoyanova-Slavova, D. A. Dobchev and M. Karelson (2007).

"QSPR modeling of flash points: An update." Journal of Molecular Graphics and

Modelling 26(2): 529-536.

Yong, P., J. Juncheng y W. Zhirong (2007). "Quantitative Structure -Property

Relationship Studies for Predicting Flash Points of Alkanes Using Group Bond

Contribution Method with Back-Propagation Neutral Network." Journal of

Hazardous Materials, 147: 424-430.

Pan, Y., J. Jiang and Z. Wang (2007). "Quantitative structure-property relationship

studies for predicting flash points of alkanes using group bond contribution method

with back-propagation neural network." Journal of Hazardous Materials 147(1-2):

424-430.

Patel, S. J., D. Ng and M. S. Mannan (2009). "QSPR Flash Point Prediction of

Solvents Using Topological Indices for Application in Computer Aided Molecular

Design." Industrial & Engineering Chemistry Research 48(15): 7378-7387.

Gharagheizi, F. (2009). "A QSPR model for estimation of lower flammability limit

temperature of pure compounds based on molecular structure." Journal of

Hazardous Materials 169(1-3): 217-220.

Khajeh, A. and H. Modarress (2010). "QSPR prediction of flash point of esters by

means of GFA and ANFIS." Journal of Hazardous Materials 179(1-3): 715-720.

•Introduction

•Literature

review

•Experimental

determination

•Theoretical

developments

•The New

Development

•Conclusions

S-13

New Polynomial Correlations

First Observations for Alkanes:

•Introduction

•Literature

review

•Experimental

determination

•Theoretical

developments

•The New

Development

•Conclusions

71.0b

f

T

T

S-14

New Polynomial Correlations

First Observations (Rearranged) :

•Introduction

•Literature

review

•Experimental

determination

•Theoretical

developments

•The New

Development

•Conclusions

71.0b

f

T

T

S-15

New Polynomial Correlations

First Model: Using 82 Alkanes the average error is 1.52%

•Introduction

•Literature

review

•Experimental

determination

•Theoretical

developments

•The New

Development

•Conclusions

Compound Tf

exp

(K)

Tf

predicción(

K)

Deviation

(K)

Propane 169 164.62 -4.38

Pentane 224 220.30 -3.70

Hexane 250 243.57 -6.43

Heptane 269 264.73 -4.27

Octane 286 284.14 -1.86

N-nonane 304 302.05 -1.95

N-decane 319 318.68 -0.32

2,3-

dimetiloctane

314 311.45 -2.55

2,6-

dimetiloctane

314 308.60 -5.40

S-16

New Polynomial Correlations

First Observations for 611 components:

•Introduction

•Literature

review

•Experimental

determination

•Theoretical

developments

•The New

Development

•Conclusions

75.0b

f

T

T

S-17

New Polynomial Correlations

Second Model: Using 58 Non-alkanes the average error is

1.8%

•Introduction

•Literature

review

•Experimental

determination

•Theoretical

developments

•The New

Development

•Conclusions

Hv

Hr

Tb

Tf0007476.0819.0

Compuesto Tf

exp

(K)

Tf

predicción(

K)

Desviación

(K)

Acetaldehyde 235.37 231.02 -4.35

Acetic acid 312.59 310.61 -1.98

Acetone 253.15 255.91 2.76

Acetonitrile 278.71 279.76 1.05

Acrolein 247.04 253.88 6.84

Aniline 343.15 347.09 3.94

Benzene

aldehyde 337.59 340.29 2.69

Benzene 262.04 262.10 0.06

Benzyl

Alcohol 366.48 367.86 1.37

S-18

A Combined polynomial-group contributions method

Third Model: Using 48 alkanes

•Introduction

•Literature

review

•Experimental

determination

•Theoretical

developments

•The New

Development

•Conclusions

4433221100004.08182.0 nnnnHv

Hr

Tb

Tf

ni Group αi ni Group αi

1 CH3− -0.0242924 3 =CH= 0.0071968

2 −CH2− -0.0072769 4 −C≡ 0.0156201

S-19

Compound

Tf

experimental

(K)

Tf

prediction

(K)

Deviatio

n (K)

Butane 213 204.56 -8.44

Heptane 269 270.36 1.36

Hexane 250 251.35 1.35

Octane 286 287.01 1.01

Pentane 224 229.67 5.67

Propane 169 177.16 8.16

2,3-

dimetilbutano 244 243.58 -0.42

2-

metilpentano 250 247.89 -2.11

2,4-

dimetilpentan

o 261 259.65 -1.35

2,3-

dimetilhexano 283 282.64 -0.36

A Combined polynomial-group contributions method

Third Model: Using 48 alkanes the average error is 1.63%

•Introduction

•Literature

review

•Experimental

determination

•Theoretical

developments

•The New

Development

•Conclusions

S-20

No theoretical method has been developed to estimate the flash

temperature in spite of the several correlations. The QSPR is probably the

closest approach in the theoretical approach which could overcome the

lack of information in particular for new compounds. In this work, it was

observed that experimental values seem to behave according to the

typical straight line proposed in several correlations. However, it has not

been possible to distinguish the independent variables affecting the real

flash temperature value. Chemical characteristics are combined here with

physical properties to improve the estimated flash temperatures.

Considering that the liquid molecules should be evaporated to burn, the

vaporization change of enthalpy ( ) is included in our models. In addition,

the inclusion of heat of combustion ( ) in the model incorporates a

chemical behavior of the molecules. Thus, the thumb rule is expanded to

include the dimensionless group ( ). Given the lack of experimental data,

the number of components used to produce the new correlation is rather

reduced but the results are enhanced and the required properties can

easily be predicted in a process simulator such as ASPEN

•Introduction

•Literature

review

•Experimental

determination

•Theoretical

developments

•The New

Development

•Conclusions

S-21

Thank you!

QUESTIONS?