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Iterative solution methods for large-scale finite element models in structural acoustics.

机译:结构声学中大型有限元模型的迭代求解方法。

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摘要

Finite-element discretizations of time-harmonic structural acoustics problems in exterior domains result in large, sparse systems of linear equations with complex symmetric coefficient matrices. In many situations, these matrix problems need to be solved repeatedly for different right-hand sides, with the same coefficient matrix. This work is concerned with the design and implementation of efficient Krylov-subspace iterative methods for solving these matrix problems.; The discretization of exterior problems, which involve an infinite fluid domain, is achieved by introducing a truncation boundary, and posing a Dirichlet-to-Neumann (DtN) map on it which incorporates the asymptotic behavior of the solution. The DtN map involves non-local spatial integrals whose discretization destroys the sparsity of the global coefficient matrix. We describe a novel discretization of the DtN map that allows the evaluation of matrix-vector products, used in iterative methods, without storage penalties related to its non-local nature.; The study of acoustic radiation and scattering problems involves solution of linear systems with the same coefficient matrix, but different right-hand sides. More generally, linear systems with multiple right-hand sides are also encountered in other areas of engineering analysis and design. We describe a block quasi-minimal residual (BL-QMR) algorithm for the simultaneous solution of non-Hermitian linear systems with multiple right-hand sides. The BL-QMR algorithm is a block Krylov-subspace iterative method that incorporates deflation to delete linearly and almost linearly dependent vectors in the underlying block Krylov sequences.; A J-symmetric variant of the BL-QMR method is also introduced to exploit the symmetry of coefficient matrices such as those arising in acoustics. Extensive numerical tests on acoustics problems show that, instead of solving each of the multiple linear systems individually, it is always more efficient to employ BL-QMR. The importance of deflations in finite-precision arithmetic and their effect on convergence is also clearly illustrated.; A general approach for implementation of unstructured grid computations on distributed-memory multi-processor computers is also described. Based on the proposed discretization of DtN condition, as well as a suitable preconditioner, an iterative solution approach is described that does not require the assembly of any global matrix, and its performance is illustrated on the Connection Machine CM-5 system.
机译:外部域中的时谐结构声学问题的有限元离散化导致大型,稀疏的线性方程组系统具有复杂的对称系数矩阵。在许多情况下,这些矩阵问题需要针对具有相同系数矩阵的不同右侧重复进行解决。这项工作涉及解决这些矩阵问题的有效Krylov子空间迭代方法的设计和实现。外部问题的离散化涉及无限的流体域,这是通过引入截断边界并在其上绘制一个Dirichlet-Neumann(DtN)映射实现的,该映射包含了解决方案的渐近行为。 DtN映射涉及非局部空间积分,其离散化破坏了全局系数矩阵的稀疏性。我们描述了一种新颖的DtN映射离散化方法,该方法可以对用于迭代方法的矩阵向量乘积进行评估,而无需对其非本地性质进行存储惩罚。声辐射和散射问题的研究涉及具有相同系数矩阵但右侧不同的线性系统的解。更一般而言,在工程分析和设计的其他领域也遇到具有多个右侧的线性系统。我们描述了具有多个右侧的非Hermitian线性系统的同时求解的块拟最小残差(BL-QMR)算法。 BL-QMR算法是一个块Krylov子空间迭代方法,该方法结合了紧缩以删除基础块Krylov序列中线性和几乎线性相关的向量。还引入了BL-QMR方法的J对称变体,以利用诸如在声学中产生的系数矩阵的对称性。关于声学问题的大量数值测试表明,与单独解决多个线性系统中的每一个相比,采用BL-QMR总是更有效。还清楚说明了放气在有限精度算法中的重要性及其对收敛的影响。还描述了在分布式内存多处理器计算机上实现非结构化网格计算的一般方法。基于建议的DtN条件的离散化以及合适的前置条件,描述了一种不需要任何全局矩阵组装的迭代解决方法,并且在Connection Machine CM-5系统上说明了其性能。

著录项

  • 作者

    Malhotra, Manish.;

  • 作者单位

    Stanford University.;

  • 授予单位 Stanford University.;
  • 学科 Engineering Mechanical.; Physics Acoustics.
  • 学位 Ph.D.
  • 年度 1996
  • 页码 131 p.
  • 总页数 131
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类 机械、仪表工业;声学;
  • 关键词

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