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A stochastic Galerkin lattice Boltzmann method for incompressible fluid flows with uncertainties
Zhong, Mingliang1,7; Xiao TB(肖天白)2,3,4; Krause, Mathias J.5,6,7; Frank, Martin1,5; Simonis, Stephan5,7
Corresponding AuthorZhong, Mingliang([email protected])
Source PublicationJOURNAL OF COMPUTATIONAL PHYSICS
2024-11-15
Volume517Pages:22
ISSN0021-9991
AbstractEfficient modeling and simulation of uncertainties in computational fluid dynamics (CFD) remains a crucial challenge. In this paper, we present the first stochastic Galerkin (SG) lattice Boltzmann method (LBM) built upon the generalized polynomial chaos (gPC). The proposed method offers an efficient and accurate approach that depicts the propagation of uncertainties in stochastic incompressible flows. Formal analysis shows that the SG LBM preserves the correct Chapman- Enskog asymptotics and recovers the corresponding macroscopic fluid equations. Numerical experiments, including the Taylor-Green vortex flow, lid-driven cavity flow, and isentropic vortex convection, are presented to validate the solution algorithm. The results demonstrate that the SG LBM achieves the expected spectral convergence and the computational cost is significantly reduced compared to the sampling-based non-intrusive approaches, e.g., the routinely used Monte Carlo method. We obtain a speedup factor of 5.72 compared to Monte Carlo sampling in a randomized two-dimensional Taylor-Green vortex flow test case. By leveraging the accuracy and flexibility of LBM and the efficiency of gPC-based SG, the proposed SG LBM provides a powerful framework for uncertainty quantification in CFD practice.
KeywordStochastic Galerkin method Generalized polynomial chaos Uncertainty quantification Lattice Boltzmann method Incompressible fluid flow Computational fluid dynamics OpenLB
DOI10.1016/j.jcp.2024.113344
Indexed BySCI ; EI
Language英语
WOS IDWOS:001299528500001
WOS KeywordNUMERICAL APPROXIMATION ; DIFFERENTIAL-EQUATIONS ; STATISTICAL SOLUTIONS ; MODELING UNCERTAINTY ; QUANTIFICATION
WOS Research AreaComputer Science ; Physics
WOS SubjectComputer Science, Interdisciplinary Applications ; Physics, Mathematical
Funding ProjectMinistry of Science, Research ; Arts Baden-Wurttemberg ; Federal Ministry of Education and Research ; Deutsche Forschungsgemeinschaft (DFG, German Research Foundation)[436212129] ; National Science Foundation of China[12302381]
Funding OrganizationMinistry of Science, Research ; Arts Baden-Wurttemberg ; Federal Ministry of Education and Research ; Deutsche Forschungsgemeinschaft (DFG, German Research Foundation) ; National Science Foundation of China
Classification一类/力学重要期刊
Ranking2
ContributorZhong, Mingliang
Citation statistics
Cited Times:2[WOS]   [WOS Record]     [Related Records in WOS]
Document Type期刊论文
Identifierhttp://dspace.imech.ac.cn/handle/311007/96440
Collection高温气体动力学国家重点实验室
Affiliation1.Karlsruhe Inst Technol, Sci Comp Ctr, D-76344 Eggenstein Leopoldshafen, Germany;
2.Chinese Acad Sci, Inst Mech, State Key Lab High Temp Gas Dynam, Beijing 100190, Peoples R China;
3.Chinese Acad Sci, Inst Mech, Ctr Interdisciplinary Res Fluids, Beijing 100190, Peoples R China;
4.Univ Chinese Acad Sci, Sch Engn Sci, Beijing 100049, Peoples R China;
5.Karlsruhe Inst Technol, Inst Appl & Numer Math, D-76131 Karlsruhe, Germany;
6.Karlsruhe Inst Technol, Inst Mech Proc Engn & Mech, D-76131 Karlsruhe, Germany;
7.Karlsruhe Inst Technol, Lattice Boltzmann Res Grp, D-76131 Karlsruhe, Germany
Recommended Citation
GB/T 7714
Zhong, Mingliang,Xiao TB,Krause, Mathias J.,et al. A stochastic Galerkin lattice Boltzmann method for incompressible fluid flows with uncertainties[J]. JOURNAL OF COMPUTATIONAL PHYSICS,2024,517:22.Rp_Au:Zhong, Mingliang
APA Zhong, Mingliang,肖天白,Krause, Mathias J.,Frank, Martin,&Simonis, Stephan.(2024).A stochastic Galerkin lattice Boltzmann method for incompressible fluid flows with uncertainties.JOURNAL OF COMPUTATIONAL PHYSICS,517,22.
MLA Zhong, Mingliang,et al."A stochastic Galerkin lattice Boltzmann method for incompressible fluid flows with uncertainties".JOURNAL OF COMPUTATIONAL PHYSICS 517(2024):22.
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