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交替LU分裂算法及其在CFD中的应用
引用本文:相倩,吴颂平,徐悦.交替LU分裂算法及其在CFD中的应用[J].北京航空航天大学学报,2012,38(7):953-956.
作者姓名:相倩  吴颂平  徐悦
作者单位:北京航空航天大学航空科学与工程学院,北京,100191;中国航空研究院航空数值模拟技术研究应用中心,北京,100012
基金项目:国家自然科学基金资助项目
摘    要:在CFD(Computational Fluid Dynamics)时间相关算法中,为了保证计算的稳定性,时间步长的取值通常会很小,这将导致计算过程收敛缓慢.针对这一问题,提出了一种新的迭代算法—交替LU分裂(ALUS,Alternating Lower-Upper Splitting)算法,可以有效加速收敛,提高计算效率.ALUS算法将系数矩阵分裂成上、下三角矩阵,因此仅需要利用追赶法求解两个三角矩阵,计算量较小,容易实现.给出了ALUS算法收敛的定理,并且通过线性问题以及CFD圆柱绕流的数值模拟对ALUS算法进行了检验.理论分析和数值实验的结果均表明:ALUS算法计算量小,大大节省了计算时间,而且该算法是鲁棒的.因此ALUS算法是高效的、稳定的算法,适用于CFD数值模拟.

关 键 词:数值模拟  大规模线性系统  正定矩阵  鲁棒性
收稿时间:2011-06-26

Alternating lower-upper splitting iterative method and its application in CFD
Xiang Qian Wu SongpingSchool of Aeronautic Science and Engineering,Beijing University of Aeronautics and Astronautics,Beijing,China Xu Yue.Alternating lower-upper splitting iterative method and its application in CFD[J].Journal of Beijing University of Aeronautics and Astronautics,2012,38(7):953-956.
Authors:Xiang Qian Wu SongpingSchool of Aeronautic Science and Engineering  Beijing University of Aeronautics and Astronautics  Beijing  China Xu Yue
Institution:1. School of Aeronautic Science and Engineering, Beijing University of Aeronautics and Astronautics, Beijing 100191, China;2. Numerical Simulation Center, Chinese Aeronautical Establishment, Beijing 100012, China
Abstract:Small time step is used to ensure convergence in the time-dependent method in computational fluid dynamics(CFD).An improved iteration method termed as the alternating lower-upper splitting(ALUS) iterative method was proposed to address the problem,in which the coefficient matrix was split into a lower and an upper triangular matrix.In each inner step,only two triangular matrices were solved by Thom asalgorithm,therefore the ALUS method is simple.Theorems were listed to ensure the ALUS method convergence.A linear equation problem and flow around the cylinder were used to illustrate the characteristic of the ALUS method.Theoretical analysis and numerical results both demonstrate the new method performs well for positive definite matrices.Withless amount of computational work,the CPU time can be greatlydiminished.Thus the new ALUS method is efficient and robust and it is applicable in CFD numerical simulation.
Keywords:numerical simulation  large scale linear systems  positive definite matrix  robustness
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