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 Author | Zhong, Mingliang([email protected]) |
Source Publication | JOURNAL OF COMPUTATIONAL PHYSICS
![]() |
2024-11-15 | |
Volume | 517Pages:22 |
ISSN | 0021-9991 |
Abstract | Efficient 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. |
Keyword | Stochastic Galerkin method Generalized polynomial chaos Uncertainty quantification Lattice Boltzmann method Incompressible fluid flow Computational fluid dynamics OpenLB |
DOI | 10.1016/j.jcp.2024.113344 |
Indexed By | SCI ; EI |
Language | 英语 |
WOS ID | WOS:001299528500001 |
WOS Keyword | NUMERICAL APPROXIMATION ; DIFFERENTIAL-EQUATIONS ; STATISTICAL SOLUTIONS ; MODELING UNCERTAINTY ; QUANTIFICATION |
WOS Research Area | Computer Science ; Physics |
WOS Subject | Computer Science, Interdisciplinary Applications ; Physics, Mathematical |
Funding Project | Ministry 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 Organization | Ministry 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 |
Ranking | 2 |
Contributor | Zhong, Mingliang |
Citation statistics | |
Document Type | 期刊论文 |
Identifier | http://dspace.imech.ac.cn/handle/311007/96440 |
Collection | 高温气体动力学国家重点实验室 |
Affiliation | 1.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. |
Files in This Item: | There are no files associated with this item. |
Items in the repository are protected by copyright, with all rights reserved, unless otherwise indicated.
Edit Comment