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A new Monte Carlo method termed Comb-like frame Monte Carlo is developed to simulate the soot dynamics. Detailed stochastic error analysis is provided. Comb-like frame Monte Carlo is coupled with the gas phase solver Chemkin II to simulate soot formation in a 1-D premixed burner stabilized flame. The simulated soot number density, volume fraction, and particle size distribution all agree well with the measurement available in literature. The origin of the bimodal distribution of particle size distribution is revealed with quantitative proof.

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ZHOU, Kun. MONTE CARLO SIMULATION FOR SOOT DYNAMICS. Thermal Science, [S.l.], v. 16, n. 5, p. 1391-1394, dec. 2016. ISSN 2334-7163. Available at: <>. Date accessed: 24 jan. 2018. doi:
Received 2016-12-29
Accepted 2016-12-30
Published 2016-12-30


[1] Yu, M. Z., Lin, J. Z., Chan, T. L., Numerical Simulation of Nanoparticle Synthesis in Diffusion Flame reactor, Powder Technology, 181 (2008), 1, pp. 9-20
[2] Yu, M. Z., Lin, J. Z., Chan, T. L., Effect of Precursor Loading on Non-Spherical TiO2 Nanoparticle Synthesis in a Diffusion Flame Reactor, Chemical Engineering Science, 63 (2008), 9, pp. 2317-2329
[3] Yu, M. Z., Lin, J. Z., Chan, T. L., A New Moment Method for Solving the Coagulation Equation for Particles in Brownian Motion, Aerosol Science and Technology, 42 (2008), 9, pp. 705-713
[4] Yu, M. Z., Lin, J. Z., Taylor-Expansion Moment Method for Agglomerate Coagulation due to Brownian Motion in the Entire Size Regime, Journal of Aerosol Science, 40 (2009), 6, pp. 549-562
[5] Nie, D. M., Lin, J. Z., A Fluctuating Lattice Boltzmann Model for Direct Numerical Simulation of Particle Brownian Motion, Particuology, 7 (2009), 6, pp. 501-506
[6] Nie, D. M., Lin, J. Z., A Lattice Boltzmann-direct Forcing/Sictitious Domain Model for Brownian Particles in Fluctuating Fluids, Communications in Computational in Physics, 9 (2011), 4, pp. 959-973
[7] Kee, R. J., Grcar, J. F., Smooke, M. D., PREMIX: A Fortran Program for Modeling Steady Laminar One- Dimensional Premixed Flame, Technical Report SAND85-8240, Sandia National Laboratories, Albuquerque, N. Mex., USA, 1985
[8] Appel, J., Bockhorn, H., Frenklach, M., Kinetic Modeling of Soot Formation with Detailed Chemistry and Physics: Laminar Premixed Flames of C2 Hydrocarbons, Combustion and Flame, 121 (2000), 1-2, pp. 122- 136
[9] Frenklach, M., Wang, H., Detailed Modeling of Soot Particle Nucleation and Growth, Proceedings of the Combustion Institute, 23 (1990), pp. 1559-1566
[10] Zhou, K., Bisetti, F., Operator Splitting Monte Carlo: A Highly Efficient Simulator for Aerosol Dynamics, Journal of Computational Physics, (2012), (in progress)
[11] Grcar, J. F., The Twopnt Program for Boundary Value Problems, Technical Report SAND91-8230, Sandia National Laboratories, Albuquerque, N. Mex., USA, 1992
[12] Spall, J. C., Introduction to Stochastic Search and Optimization: Estimation, Simulation, and Control, John Wiley & Sons, Inc. 2003
[13] Abid, A. D., Heinz, N., Tolmachoff, E. D., On Evolution of Particle Size Distribution Functions of Incipient Soot in Premixed Ethylene-Oxygen-Argon Flames, Combustion and Flame, 34 (2008), 4, pp. 775-788
[14] Frenklach, M., Harris, S. J., Aerosol Dynamics Modeling Using the Method of Moments, Journal of Colloid and Interface Science, 118 (1987), pp. 252-261