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Journal of Computational Physics
Article . 2001 . Peer-reviewed
License: Elsevier TDM
Data sources: Crossref
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zbMATH Open
Article . 2001
Data sources: zbMATH Open
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Statistical Simulation of Low-Speed Rarefied Gas Flows

Statistical simulation of low-speed rarefied gas flows
Authors: Fan, Jing; Shen, Ching;

Statistical Simulation of Low-Speed Rarefied Gas Flows

Abstract

Conclusions: An information preservation technique is proposed to overcome serious statistical fluctuations inherent in direct simulation Monte Carlo (DSMC) method for low-speed rarefied gas flows. This technique is applied to benchmark problems, namely Couette, Poiseuille, and Rayleigh flows over the entire Knudsen regime. The characteristic velocities in these flows ranged from 0.01 to 1\,m/s, which were much smaller than the thermal velocity of about 340\,m/s. Meaningful results are obtained at a sample size of \(10^3-10^4\), in comparison with a sample size of \(10^8\) or more required for DSMC method at such a range of flow velocity. This results in a tremendous gain in CPU time. A comparison of velocity distributions, surface shear stresses, and mass fluxes given by the information preservation technique with exact solutions in continuum and free molecular limits, and with numerical solutions of linearized Boltzmann equation, experimental data and DSMC results in the transition regime, shows a good agreement.

Related Organizations
Keywords

statistical fluctuations, Rarefied gas flows, Boltzmann equation in fluid mechanics, Stochastic analysis applied to problems in fluid mechanics, Couette flow, Rayleigh flow, Poiseuille flow

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
197
Top 1%
Top 1%
Top 10%
bronze
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