Stochastic weighted particle methods for population balance equations

DOI10.1016/j.jcp.2011.06.011zbMath1252.65021OpenAlexW2039006687MaRDI QIDQ655067

Wolfgang Wagner, Robert I. A. Patterson, Markus Kraft

Publication date: 28 December 2011

Published in: Journal of Computational Physics (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.jcp.2011.06.011

zbMATH Keywords

algorithmsMonte Carlonumerical experimentsMarkov chaincoagulationstochastic particle algorithmpopulation balance equationssoot

Mathematics Subject Classification ID

Monte Carlo methods (65C05) Stochastic ordinary differential equations (aspects of stochastic analysis) (60H10) Numerical analysis or methods applied to Markov chains (65C40) Ordinary differential equations and systems with randomness (34F05) Computational methods for stochastic equations (aspects of stochastic analysis) (60H35) Numerical solutions to stochastic differential and integral equations (65C30) Stochastic particle methods (65C35)

Related Items (15)

Accurate and efficient approximations for generalized population balances incorporating coagulation and fragmentation ⋮ A population balance-Monte Carlo method for particle coagulation in spatially inhomogeneous systems ⋮ Stochastic weighted particle methods for population balance equations with coagulation, fragmentation and spatial inhomogeneity ⋮ Application of stochastic weighted algorithms to a multidimensional silica particle model ⋮ Stochastic solution of population balance equations for reactor networks ⋮ Extension of moment projection method to the fragmentation process ⋮ A random cloud model for the Wigner equation ⋮ Event-driven sorting algorithm-based Monte Carlo method with neighbour merging method for solving aerosol dynamics ⋮ Conditional moment methods for polydisperse cavitating flows ⋮ A hybrid particle-number and particle model for efficient solution of population balance equations ⋮ Error analysis in stochastic solutions of population balance equations ⋮ Accelerating population balance-Monte Carlo simulation for coagulation dynamics from the Markov jump model, stochastic algorithm and GPU parallel computing ⋮ Accelerated simulation of stochastic particle removal processes in particle-resolved aerosol models ⋮ Two-component aerosol dynamic simulation using differentially weighted operator splitting Monte Carlo method ⋮ Convergence of Stochastic Particle Systems Undergoing Advection and Coagulation

Uses Software

• R
• LSODE
• MASS (R)

Cites Work

• Unnamed Item
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