Development of an n-heptane/toluene/PAH Mechanism and its Application for Soot Prediction
Hu Wang1, 2, Qi Jiao2, Mingfa Yao1, Rolf D. Reitz2
1. Engine Research Center, University of Wisconsin-Madison, Madison, Wisconsin, 53705, U.S.A
2. State Key Laboratory of Engines, Tianjin University, Tianjin, 300072, P. R. China
Abstract
A chemical reaction mechanism has been developed for modeling the combustion process and poly-aromatic hydrocarbon
(PAH) formation of diesel and n-heptane/toluene fuels. The mechanism consists of 71 species and 360 reactions. This
mechanism was extensively validated with available experimental data. A practical multi-step soot model was integrated
with the PAH kinetics model to predict soot emissions of diesel and n-heptane/toluene DI engine data. Constant volume
combustion vessel simulations were also conducted. The results show that the present mechanism provides promising
agreement in term of PAH prediction for various fuels in premixed flames. HCCI combustion and DI spray combustion
simulation results confirm that the present mechanism gives reliable predictions of combustion and soot emissions for both
diesel and n-heptane/toluene fuels under various conditions. The study also highlights the importance of aromatics on the
PAH formation and soot emissions.
1. Introduction
Diesel and gasoline fuels are complex mixtures of paraffins, aromatics, cycloalkanes and olefins [1]. A significant amount
of aromatic compounds is present in both gasoline (~35%) and diesel fuels (~30%). Toluene is a major aromatic component
in practical fuels and also a desired component for diesel and gasoline surrogates. It is one of the simplest derivatives of
benzene, and its chemistry is a foundation for large aromatic formation. Therefore, many kinetic modeling studies of
toluene and TRF fuels have been conducted. Davidson et al. [2], Shen et al. [3] and Herzler et al. [4] presented
measurements of ignition delay of toluene/air and toluene/n-heptane/air mixtures at engine relevant conditions and different
equivalence ratios. Bounaceur et al. [5] and Andrae et al. [6] proposed detailed toluene and TRF kinetic mechanisms. Based
on the toluene mechanisms developed by Bounaceur et al. [5] and Andrae et al. [6], Ra et al. [7] developed a reduced
toluene mechanism and incorporated it into a multi-chemistry mechanism.
It is clear that detailed and accurate PAH growth mechanisms are necessary if accurate simulation of soot inception is to be
realized. Xi et al. [8] proposed a reduced chemical mechanism for the chemical kinetics of n-heptane oxidation in modeling
PAH formation in diesel combustion. Vishwanathan et al. [9] combined this reduced PAH mechanism with the PRF
mechanism developed by Ra et al. [10], and coupled it with a multi-step soot model to predict the soot emissions of diesel
fuel. Recently Slavinskaya et al. [11] developed a detailed PAH mechanism for methane, ethane and ethylene flames. The
proposed PAH mechanism is highly successful at predicting concentrations of aromatics containing two to four rings.
The presence of aromatics promotes the formation of PAH and soot particles as benzene (A1) is one of the major species in
both the toluene oxidation and PAH growth processes. Therefore, an accurate PAH formation model is required for better
soot prediction, especially for fuels composed of aromatic compounds. Choi et al.[12] found that PAH initially increased
and then decreased with the toluene ratio, exhibiting a synergistic effect. The soot formation increased monotonically with
the toluene ratio; however the effect of toluene on soot formation was minimal for relatively small toluene ratios.
The objective of the present study was to develop a reduced n-heptane/toluene/PAH mechanism which can be applied to
multidimensional CFD simulations for combustion and soot predictions of diesel, n-heptane and n-heptane/toluene fuels.
2. Mechanism formulation
The current investigation is based on the n-heptane-n-butanol-PAH mechanism of Wang et al. [13], wherein a reduced
mechanism was developed to predict the combustion and soot emissions of both non-oxygenated and oxygenated fuels. The
base n-heptane-PAH mechanisms were used in this study. However, updates were made to improve the PAH predictions in
ethylene and n-heptane premixed flames and the ignition delays and benzene predictions of the reduced toluene mechanism
developed by Ra et al. [7]. In addition, an n-heptane/toluene/PAH mechanism was formulated based on these mechanisms.
Several reactions were adjusted or added in this n-heptane mechanism to improve its prediction of C2H2 concentrations and
ignition delays under low oxygen concentrations, viz.
C2H4+OH=CH2O+CH3
(R1)
C3H4+O2=CH2CO+HCO+H
(R2)
CH2CO+OH=CH3O+CO
(R3)
CH3O (+M) =CH2O+H (+M)
(R4)
The pre-exponential factor of the forward rate of R1 was reduced by a factor of 15 to improve both the C2H2 and PAH
predictions. The original higher reaction rate constant of this reaction converts most of the C2H4 to CH2O, and this
dramatically reduces the building block pool for PAH formation, and thus greatly affects the formation of PAH molecules.
1
The rate constants of R2-R4 were taken from Ra et al. [7]. These three reactions can greatly improve the performance of the
mechanism under low oxygen concentration conditions without penalty on the ignition delay prediction under high oxygen
concentration conditions.
The reduced toluene mechanism developed by Ra et al. [7] was taken as the base toluene mechanism. Initial toluene
premixed flames simulation results showed that the original toluene mechanism in this multi-chemistry mechanism overpredicts benzene (A1). Through rate of production and sensitive analysis, the following three reactions were found to be
important to the production of benzene (A1), and were adjusted to improve the prediction of A1:
OC6H4CH3 = A1+H+CO
(R4)
A1+OH = C6H5OH+H
(R5)
C7H8+H = A1+CH3
(R6)
The pre-exponential factor of the forward rates of R4 and R6 were reduced by 10 times while R5 was increased by 10 times
to reduce the production of A1 when toluene was applied. However, it is also necessary to adjust the following two
reactions to match the ignition delays:
C7H8+OH=C7H7+H2O
(R7)
C7H8+O=OC6H4CH3+H
(R8)
These two reactions are the most ignition-delay-sensitive reactions in this reduced toluene mechanism. Based on the present
reduced toluene and n-heptane/PAH mechanisms, an n-heptane/toluene/PAH mechanism was formulated by adding the
toluene mechanism into the base n-heptane/PAH mechanism. The final n-heptane/toluene/PAH mechanism consists of 71
species and 360 reactions. The cross reactions between the n-heptane and toluene mechanisms were also considered and
taken from [14].
3. Validation of mechanism
3.1 Ignition delay timings
Ignition delay timings predicted by the present reaction mechanism were compared and validated using experimental data
available from the literature. Figure 1 shows comparisons of predictions of ignition delay times between the present
reaction mechanism and shock tube data at different equivalence ratios for n-heptane, toluene and toluene/n-heptane fuels.
(a)
(b)
(c)
(d)
(e)
(f)
Figure 1 Comparison of predicted constant volume ignition delay times of n-heptane/air, toluene/air and toluene/n-heptane/air between
the present mechanism and shock tube test data. (a) n-heptane/air, phi=1.0; (b) n-heptane/air, phi=0.5; (c) toluene/air, phi=1.0; (d)
toluene/air, phi=0.5; (e) toluene/n-heptane/air, phi=1.0; (d) toluene/n-heptane/air, phi=0.5.
It is seen that good agreement of ignition delay between the experimental data and the present reaction mechanism can be
achieved over wide temperature ranges and at different equivalence ratios for n-heptane fuel. The predicted toluene ignition
delays are generally in good agreement with the experimental data at the two different equivalence ratios. However, it can
be seen that even under the same conditions, the experimental data sets are different from each other. A possible reason for
this difference between these two sets of experimental data is the pre-ignition energy release caused by soot deposits in the
shock tube, as discussed by Shen et al. [3]. The comparisons of predicted ignition delays of toluene/n-heptane/air mixtures
at constant volume between the present mechanism and experimental measurements were also presented in Figure 1-(e) and
2
(f). It is seen that although the ignition delays of pure n-heptane and toluene are well predicted by the current mechanism,
when mixture of n-heptane and toluene is applied, the predictions are only roughly acceptable. However, it can be seen that
the present mechanism captures the ignition delay trends for changes in temperature and pressures.
3.2 Premixed flames
This section presents comparisons between the simulation results obtained using the present mechanism and available
experimental data in premixed flames. Table 1 provides the details of the premixed flames simulated in this work for the
mechanism validation. The simulation was conducted with the CHEMKIN package, and temperature profiles from the
experiments were used for the calculations. Figure 2 shows comparisons of the concentration profiles between experiments
and simulations. It is seen that the reduced mechanism describes satisfactorily the concentrations of C2H2, C2H4, benzene,
and toluene and PAH molecules in various flame test conditions.
No. of
Flame
1
2
3
4
5
6
Fuel
C2H4
n-C7H16
benzene
CH4
toluene
toluene
benzene
fuel
0.213
0.0398
0.0957
CH4:0.049
toluene:0.015
0.05
0.118
Table 1 - Test conditions of premixed flames.
Composition
Mass flow
g/(cm2.s)
O2
N2/Ar
0.209
0.578/Ar
0.0084
0.2301
0.7301/N2
0.00617
0.4043
0.50/Ar
0.0021
P
Φ
Ref.
1 bar
1 bar
4.0 kPa
3.06
1.9
1.78
[15]
[16]
[17]
0.234
0.702/N2
34.2 cm/s
5.3 kPa
1.0
[18]
0.45
0.442
0.50/Ar
0.44/Ar
35.0 cm/s
35.0 cm/s
4.0 kPa
5.0 kPa
1.0
2.0
[19]
[20]
(a)
(b)
(c)
(d)
(e)
(f)
Figure 2 Prediction of benzene, C2H2, C2H4 and PAH in benzene premixed flames. (a), C2H4 flame, flame 1; (b) n-heptane flame, flame
2; (c) CH4/toluene flames, flame 4; (d) benzene flame, flame 5; (e) and (f) benzene flames, flame 3 and 6.
3.3 HCCI combustion
HCCI engine experiments were conducted and the experimental results were used for validation of the current mechanism.
Mixtures of n-heptane and toluene, with liquid volume fractions of 80%/20% and 60%/40%, respectively, named TRF20
and TRF40, were used. The engine operating conditions are listed in Table 2.
The simulations were performed using the KIVA code coupled with the CHEMKIN for the chemistry calculation. A 45
degree sector mesh with a cell number of around 10,000 was used, as shown in Figure 3-(a). The computations started from
intake valve closure (IVC) with an assumed uniform mixture distribution in the cylinder and ended at exhaust valve open
time. Figure 3-(b) and (c) show comparisons of the pressure profiles and apparent heat release rate (AHRR) between the
experimental data and predictions obtained using the current n-heptane/toluene/PAH mechanism at EGR rates of 15% and
45%. It can be seen that the ignition timings are well predicted by the present mechanism. The in-cylinder peak pressures at
lower EGR conditions for both TRF fuels are slightly over predicted while for higher EGR conditions, the agreements
between simulation and experiments are better.
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Table 2 - Engine operating conditions
Engine speed/r/min
1400
IMEP/bar
~3.5 bar
Intake air pressure/bar
1.6
Intake temperature/K
373
EGR ratio/%
15, 45
Equivalence ratio
TRF20: 0.38, 0.48; TRF40: 0.37, 0.46
Figure 3 Comparisons of predicted pressure trace and AHRR with experimental data in TRF fuels HCCI combustion at different EGR
rates. TRF20 fuel, EGR 15/45%, phi=0.38/0.48; TRF40 fuel, EGR 15/45%, phi=0.37/0.46.
3.4 DI spray combustion
DI diesel experiments were also conducted for the validation of the proposed mechanism. The engine operating conditions
are shown in Table 3. In order to predict soot emissions, the practical phenomenological soot model developed by
Vishwanathan et al. [9] was applied and coupled with the present mechanism. In this soot model, PAH is treated as the soot
precursor species, and soot inception starts with pyrene (A4). The main processes related to the soot formation and
oxidations processes and the reaction rates of these steps and further details about the soot model can be found in [9].
Engine speed / r/min
IMEP / bar
Intake air pressure / bar
Intake temperature / K
EGR ratio / %
Fuel
SOI
CA10
Injection pressure / bar
Fuel mass / mg/cycle
Table 3 - Engine operating conditions
1400
~8.3 bar
1.8
313
0-50%
Diesel, TRF15, TRF30
-5.3~-9.2 deg ATDC, adjusted to keep CA10 fixed
Top dead center (TDC)
1000
50 mg@diesel, 48.5 mg@TRF15, 49.2 mg@TRF30
(a)
(b)
(c)
(d)
Figure 4 Predicted in-cylinder pressure traces and AHRR profiles, NOx and soot emissions for diesel, TRF15 and TRF30 fuels
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The predictions of in-cylinder pressure and AHRR of diesel, TRF15 and TRF30 fuels at EGR rates of 25.2% and 40.6%
using the current mechanism are shown in Figure 4-(a) and (b). It can be seen that current mechanism can well predict the
in-cylinder pressure traces, as well as AHRR with the different fuels at the different EGR conditions. Also, the proposed
mechanisms capture the difference between different fuels well. Figure 4-(c) and (d) show comparisons of NOx and soot
emissions between the experimental data and simulation results. It can be seen that NO x emissions are predicted well by the
current mechanism. As for soot prediction, the general trend is also captured quite well by the current mechanism. The
difference in soot emissions among the three fuels is well captured by the present mechanism. It can be seen that, for the
two TRF fuels, the one with higher toluene content actually produces the lowest soot emissions in all EGR conditions in
both experiments and simulations. This can be attributed to the slightly longer ignition delay of TRF30 fuel, which is
helpful to improve the fuel-air mixing process. This also indicates a higher aromatic in the fuel does not necessarily produce
higher soot.
3.5 Constant Volume Combustion Chamber Simulations
The present mechanism was also applied to simulate Sandia ECN constant volume chamber data [21]. The purpose of the
simulations was to further explore the effects of the aromatic content of the fuel on sooting propensity. A 15% ambient
oxygen concentration, 30.0 kg/m3 ambient density case was chosen for the simulations, in which n-heptane was
progressively replaced with toluene (20% steps of mass fraction). The same CFD code, related sub models and soot model
used in the above DI engine simulations were used. Two different sets of tests were conducted. In the first set, the physical
properties of the blended fuels were represented with those of n-heptane to highlight the effects of the aromatic chemical
properties on mixing and soot emissions. In the second set, both the physical properties and chemical reaction mechanisms
were applied for each fuel. Through these comparisons, the effects of both chemical and physical properties of toluene
could be evaluated.
(a)
(b)
Fig.5 Predicted distributions of soot volume fraction, equivalence ratio, A4 concentration and temperature for the two test sets. (a) The
first set; (b) the second set. From left to right: pure n-heptane, 80% n-heptane + 20% toluene, 60% n-heptane + 40% toluene and 40% nheptane + 60% toluene fuels. From up to bottom: soot volume fraction, equivalence ratio, A4 mass fraction and temperature. Soot volume
fraction is averaged between 2.5 to 5.5 ms ASI; Equivalence ratio, A4 concentration and temperature at 5.0 ms ASI.
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Figure 5-(a) shows the predicted distributions of soot volume fraction, equivalence ratio, A4 mass fraction and temperature
for the first set. It is seen that the lift-off length increases as the toluene content increases in the fuel, which is helpful to
improve the fuel-air mixing. This is helpful to reduce the soot formation through improved mixing process. However, the
predicted A4 mass fraction demonstrates a dramatic increase due to the introduction of toluene. Thus, on the one hand, the
longer ignition delay and lift-off length hinders the formations of PAH and soot and also enhances the soot oxidation. But,
on the other hand, the aromatic greatly promotes the PAH and soot formation. Therefore, the final soot reflects the
competitive outcome of these two processes.
These results clearly show the importance of the mixing process and the effects of the fuel on soot emissions. Figure 5-(b)
shows the predicted distributions for the second set, in which the real physical properties of n-heptane and toluene were
applied. It is seen that the general trend of this set is quite similar to that of the first set. The soot volume fraction increases
as the toluene content in the blended fuels increases, accompanied by a lower equivalence ratio, longer lift-off length,
higher A4 concentration and similar flame structure and temperature distributions.
Through the comparison of these two sets of simulations, it can be concluded that it is due to toluene’s physical property
effects on the spray development, evaporation and mixing that the improvement in equivalence ratio (mixing process) of the
second set is not as good as the first set. This results in slightly higher soot volume fractions. Besides these relatively small
differences, the overall distributions are quite similar.
4. Conclusion
A reduced chemical reaction mechanism has been developed for modeling the combustion process and PAH formation of
diesel and n-heptane/toluene fuels. The final mechanism consists of 71 species and 360 reactions. The mechanism was
extensively validated against available experimental data, and shows promising agreements with experimental results. In
addition, a multi-step soot model was integrated with the mechanism to predict the soot emissions. The mechanism predicts
the combustion processes of the different fuels quite well. The general combustion characteristics and NOx and soot
emissions of the tested fuels are well captured under different EGR conditions. The overall results show that the present
mechanism provides promising agreements in terms of PAH prediction for various fuels in premixed flames and highlights
the importance of aromatics on PAH formation and soot emissions.
Acknowledgements
The authors would like to acknowledge the financial support provided by the National Science Foundation of China through
the project of Outstanding Young Scholarship Award (51125026) and the scholarship provided by China Scholarship
Council (CSC) under its project [2010] 3006. The authors would also like to thank Dr. Youngchul Ra for providing the
MultiChem mechanism and Dr. J. L. Brakora of University of Wisconsin-Madison for supplying helpful suggestions for the
mechanism reduction. The authors are also thankful for the support from CEI, Inc. in the in-cylinder visualization made
possible by EnSight software.
References
1. Pitz, W.J. and C.J. Mueller. Progress in Energy and Combustion Science, 2011. 37(3): p. 330-350.
2. Davidson, D.F., B.M. Gauthier, and R.K. Hanson. Proceedings of the Combustion Institute, 2005. 30(1): p. 1175-1182.
3. Shen, H.-P.S., J. Vanderover, and M.A. Oehlschlaeger. Proceedings of the Combustion Institute, 2009. 32(1): p. 165-172.
4. Herzler, J., et al. Combustion and Flame, 2007. 149(1-2): p. 25-31.
5. Bounaceur, R., et al. International Journal of Chemical Kinetics, 2005. 37(1): p. 25-49.
6. Andrae, J.C.G., et al. Combustion and Flame, 2007. 149(1-2): p. 2-24.
7. Ra, Y. and R.D. Reitz. Combustion and Flame, 2011. 158(1): p. 69-90.
8. Xi, J. and B.J. Zhong. Chemical Engineering & Technology, 2006. 29(12): p. 1461-1468.
9. Vishwanathan, G. and R.D. Reitz. Combustion Science and Technology, 2010. 182(8): p. 1050-1082.
10. Ra, Y. and R.D. Reitz. Combustion and Flame, 2008. 155(4): p. 713-738.
11. Slavinskaya, N.A., et al. Combustion and Flame, 2012. 159(3): p. 979-995.
12. Choi, B.C., S.K. Choi, and S.H. Chung. Proceedings of the Combustion Institute, 2011. 33(1): p. 609-616.
13. Wang, H., et al. Combustion and Flame, 2013. 160(3): p. 504-519.
14. Andrae, J.C.G., et al. Combustion and Flame, 2007. 149(1-2): p. 2-24.
15. Castaldi, M.J., et al. Symposium (International) on Combustion, 1996. 26(1): p. 693-702.
16. Inal, F. and S.M. Senkan. Combustion and Flame, 2002. 131(1–2): p. 16-28.
17. Yang, B., et al. Proceedings of the Combustion Institute, 2007. 31(1): p. 555-563.
18. El Bakali, A., et al. Journal of Physical Chemistry A, 2007. 111(19): p. 3907-3921.
19. Li, Y., et al. Proceedings of the Combustion Institute, 2011. 33(1): p. 593-600.
20. Wang, H. and M. Frenklach. Combustion and Flame, 1997. 110(1-2): p. 173-221.
21. Engine Combustion Network. http://www.sandia.gov/ecn/. (2012, accessed 10 July 2012).
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