MONTE CARLO SIMULATION FOR SOOT DYNAMICS

Abstract

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

Dates

  • Submission Date2012-08-01
  • Revision Date2012-09-01
  • Acceptance Date2012-09-01

DOI Reference

10.2298/TSCI1205391Z

References

  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
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