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Stochastic, analytic and numerical aspects of coagulation processes

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  • Wagner, Wolfgang

Abstract

In this paper, we review recent results concerning stochastic models for coagulation processes and their relationship to deterministic equations. Open problems related to the gelation effect are discussed. Finally, we present some new conjectures based on numerical experiments performed with stochastic algorithms.

Suggested Citation

  • Wagner, Wolfgang, 2003. "Stochastic, analytic and numerical aspects of coagulation processes," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 62(3), pages 265-275.
    • Handle: RePEc:eee:matcom:v:62:y:2003:i:3:p:265-275
    DOI: 10.1016/S0378-4754(02)00236-7
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    1. Sabelfeld K.K. & Rogasinsky S.V. & Kolodko A.A. & Levykin A.I., 1996. "Stochastic algorithms for solving Smolouchovsky coagulation equation and applications to aerosol growth simulation," Monte Carlo Methods and Applications, De Gruyter, vol. 2(1), pages 41-88, December.
    2. Kolodko, A. & Sabelfeld, K. & Wagner, W., 1999. "A stochastic method for solving Smoluchowski's coagulation equation," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 49(1), pages 57-79.
    3. Sabelfeld, K.K., 1998. "Stochastic models for coagulation of aerosol particles in intermittent turbulent flows," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 47(2), pages 85-101.
    4. Garcia, Alejandro L. & van den Broeck, Christian & Aertsens, Marc & Serneels, Roger, 1987. "A Monte Carlo simulation of coagulation," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 143(3), pages 535-546.
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    Cited by:

    1. Wells Clive G. & Kraft Markus, 2005. "Direct Simulation and Mass Flow Stochastic Algorithms to Solve a Sintering-Coagulation Equation," Monte Carlo Methods and Applications, De Gruyter, vol. 11(2), pages 175-197, June.

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