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Numerical experiments of preconditioned Krylov subspace methods solving the dense non-symmetric systems arising from BEM

机译:求解BEM引起的稠密非对称系统的预处理Krylov子空间方法的数值实验

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Discretization of boundary integral equations leads, in general, to fully populated non-symmetric linear systems of equations. An inherent drawback of boundary element method (BEM) is that, the non-symmetric dense linear systems must be solved. For large-scale problems, the direct methods require expensive computational cost and therefore the iterative methods are perhaps more preferable. This paper studies the comparative performances of preconditioned Krylov subspace solvers as bi-conjugate gradient (Bi-CG), generalized minimal residual (GMRES), conjugate gradient squared (CGS), quasi-minimal residual (QMR) and bi-conjugate gradient stabilized (Bi-CGStab) for the solution of dense non-symmetric systems. Several general preconditioners are also considered and assessed. The results of numerical experiments suggest that the preconditioned Krylov subspace methods are effective approaches solving the large-scale dense non-symmetric linear systems arising from BEM.
机译:边界积分方程的离散化通常导致方程的完全填充的非对称线性系统。边界元方法(BEM)的固有缺点是必须解决非对称稠密线性系统。对于大规模问题,直接方法需要昂贵的计算成本,因此迭代方法可能更可取。本文研究了预处理Krylov子空间解算器在双共轭梯度(Bi-CG),广义最小残差(GMRES),共轭梯度平方(CGS),准最小残差(QMR)和双共轭梯度稳定( Bi-CGStab)求解密集的非对称系统。还考虑并评估了几种通用的预处理器。数值实验结果表明,预处理的Krylov子空间方法是解决BEM引起的大规模稠密非对称线性系统的有效方法。

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