A NONLINEARLY PRECONDITIONED INEXACT NEWTON ALGORITHM FOR STEADY STATE LATTICE BOLTZMANN EQUATIONS

CORC > 软件研究所 > 软件所图书馆 > 期刊论文

	A NONLINEARLY PRECONDITIONED INEXACT NEWTON ALGORITHM FOR STEADY STATE LATTICE BOLTZMANN EQUATIONS
	Huang, JZ ; Yang, C ; Cai, XC
刊名	SIAM JOURNAL ON SCIENTIFIC COMPUTING
	2016
卷号	38 期号:3 页码:A1701-A1724
关键词	steady state lattice Boltzmann equations inexact Newton algorithm nonlinear preconditioning pollution removing coarse space parallel scalability
ISSN号	1064-8275
中文摘要	Most existing methods for calculating the steady state solution of the lattice Boltzmann equations are based on pseudo time stepping, which often requires a large number of time steps especially for high Reynolds number problems. To calculate the steady state solution directly without the time integration, in this paper we propose and study a nonlinearly preconditioned inexact Newton algorithm with a domain decomposition based linear solver for parallelization. More precisely, the proposed algorithmic framework involves an implicit, second-order discretization, a two-level inexact Newton method, and a nonlinear elimination preconditioner to accelerate the convergence of Newton iteration. A nonstandard, pollution removing, coarse space is introduced for the two-level method. Numerical experiments are presented to demonstrate the robustness and efficiency of the algorithm, especially for problems at a high Reynolds number. A comparison is also included to show the superiority of the proposed approach over other explicit and implicit methods in terms of the total compute time measured on a parallel computer.
英文摘要	Most existing methods for calculating the steady state solution of the lattice Boltzmann equations are based on pseudo time stepping, which often requires a large number of time steps especially for high Reynolds number problems. To calculate the steady state solution directly without the time integration, in this paper we propose and study a nonlinearly preconditioned inexact Newton algorithm with a domain decomposition based linear solver for parallelization. More precisely, the proposed algorithmic framework involves an implicit, second-order discretization, a two-level inexact Newton method, and a nonlinear elimination preconditioner to accelerate the convergence of Newton iteration. A nonstandard, pollution removing, coarse space is introduced for the two-level method. Numerical experiments are presented to demonstrate the robustness and efficiency of the algorithm, especially for problems at a high Reynolds number. A comparison is also included to show the superiority of the proposed approach over other explicit and implicit methods in terms of the total compute time measured on a parallel computer.
收录类别	SCI
语种	英语
WOS记录号	WOS:000385282800019
公开日期	2016-12-13
内容类型	期刊论文
源URL	[http://ir.iscas.ac.cn/handle/311060/17421]
专题	软件研究所_软件所图书馆_期刊论文
推荐引用方式 GB/T 7714	Huang, JZ,Yang, C,Cai, XC. A NONLINEARLY PRECONDITIONED INEXACT NEWTON ALGORITHM FOR STEADY STATE LATTICE BOLTZMANN EQUATIONS[J]. SIAM JOURNAL ON SCIENTIFIC COMPUTING,2016,38(3):A1701-A1724.
APA	Huang, JZ,Yang, C,&Cai, XC.(2016).A NONLINEARLY PRECONDITIONED INEXACT NEWTON ALGORITHM FOR STEADY STATE LATTICE BOLTZMANN EQUATIONS.SIAM JOURNAL ON SCIENTIFIC COMPUTING,38(3),A1701-A1724.
MLA	Huang, JZ,et al."A NONLINEARLY PRECONDITIONED INEXACT NEWTON ALGORITHM FOR STEADY STATE LATTICE BOLTZMANN EQUATIONS".SIAM JOURNAL ON SCIENTIFIC COMPUTING 38.3(2016):A1701-A1724.