Parallel Monte Carlo simulation of aerosol dynamics

Handle URI:
http://hdl.handle.net/10754/334537
Title:
Parallel Monte Carlo simulation of aerosol dynamics
Authors:
Zhou, K.; He, Z.; Xiao, M.; Zhang, Z.
Abstract:
A highly efficient Monte Carlo (MC) algorithm is developed for the numerical simulation of aerosol dynamics, that is, nucleation, surface growth, and coagulation. Nucleation and surface growth are handled with deterministic means, while coagulation is simulated with a stochastic method (Marcus-Lushnikov stochastic process). Operator splitting techniques are used to synthesize the deterministic and stochastic parts in the algorithm. The algorithm is parallelized using the Message Passing Interface (MPI). The parallel computing efficiency is investigated through numerical examples. Near 60% parallel efficiency is achieved for the maximum testing case with 3.7 million MC particles running on 93 parallel computing nodes. The algorithm is verified through simulating various testing cases and comparing the simulation results with available analytical and/or other numerical solutions. Generally, it is found that only small number (hundreds or thousands) of MC particles is necessary to accurately predict the aerosol particle number density, volume fraction, and so forth, that is, low order moments of the Particle Size Distribution (PSD) function. Accurately predicting the high order moments of the PSD needs to dramatically increase the number of MC particles. 2014 Kun Zhou et al.
KAUST Department:
Clean Combustion Research Center
Citation:
Zhou K, He Z, Xiao M, Zhang Z (2014) Parallel Monte Carlo Simulation of Aerosol Dynamics. Advances in Mechanical Engineering 2014: 1-11. doi:10.1155/2014/435936.
Publisher:
SAGE Publications
Journal:
Advances in Mechanical Engineering
Issue Date:
2014
DOI:
10.1155/2014/435936
Type:
Article
ISSN:
16878132
Appears in Collections:
Articles; Clean Combustion Research Center

Full metadata record

DC FieldValue Language
dc.contributor.authorZhou, K.en
dc.contributor.authorHe, Z.en
dc.contributor.authorXiao, M.en
dc.contributor.authorZhang, Z.en
dc.date.accessioned2014-11-11T14:28:53Z-
dc.date.available2014-11-11T14:28:53Z-
dc.date.issued2014en
dc.identifier.citationZhou K, He Z, Xiao M, Zhang Z (2014) Parallel Monte Carlo Simulation of Aerosol Dynamics. Advances in Mechanical Engineering 2014: 1-11. doi:10.1155/2014/435936.en
dc.identifier.issn16878132en
dc.identifier.doi10.1155/2014/435936en
dc.identifier.urihttp://hdl.handle.net/10754/334537en
dc.description.abstractA highly efficient Monte Carlo (MC) algorithm is developed for the numerical simulation of aerosol dynamics, that is, nucleation, surface growth, and coagulation. Nucleation and surface growth are handled with deterministic means, while coagulation is simulated with a stochastic method (Marcus-Lushnikov stochastic process). Operator splitting techniques are used to synthesize the deterministic and stochastic parts in the algorithm. The algorithm is parallelized using the Message Passing Interface (MPI). The parallel computing efficiency is investigated through numerical examples. Near 60% parallel efficiency is achieved for the maximum testing case with 3.7 million MC particles running on 93 parallel computing nodes. The algorithm is verified through simulating various testing cases and comparing the simulation results with available analytical and/or other numerical solutions. Generally, it is found that only small number (hundreds or thousands) of MC particles is necessary to accurately predict the aerosol particle number density, volume fraction, and so forth, that is, low order moments of the Particle Size Distribution (PSD) function. Accurately predicting the high order moments of the PSD needs to dramatically increase the number of MC particles. 2014 Kun Zhou et al.en
dc.language.isoenen
dc.publisherSAGE Publicationsen
dc.rightsThis is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.en
dc.rightsArchived with thanks to Advances in Mechanical Engineeringen
dc.rights.urihttp://creativecommons.org/licenses/by/3.0/en
dc.titleParallel Monte Carlo simulation of aerosol dynamicsen
dc.typeArticleen
dc.contributor.departmentClean Combustion Research Centeren
dc.identifier.journalAdvances in Mechanical Engineeringen
dc.eprint.versionPublisher's Version/PDFen
dc.contributor.institutionKey Laboratory for Ferrous Metallurgy and Resources Utilization of MOE, Wuhan University of Science and Technology, Wuhan 430072, Chinaen
dc.contributor.institutionZhejiang Institute of Quality Inspection Science, Hangzhou 310000, Chinaen
dc.contributor.affiliationKing Abdullah University of Science and Technology (KAUST)en
kaust.authorZhou, Kunen
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