基于残差的无网格特征值解的自适应改进

T. Kaufmann, C. Engstrom, C. Fumeaux
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引用次数: 16

摘要

提出并实现了二维结构自适应无网格特征值求解器的概念。基于径向基函数,用配点法计算了二阶波动方程的特征模态。这种类型的无网格方法具有基于节点的配置方法的简单性,保证了高度精确的结果。因此,当改变物理模型的离散表示时,只需要调整节点位置,从而避免了处理显式网格拓扑的数值开销。该方法的准确性是以处理条件较差的矩阵为代价的。通过应用留一交叉验证优化算法来获得稳定的结果,可以避免这种情况。提出了一种节点自适应算法,对初始粗离散化进行了有效的细化。通过两个具有解析解的数值算例验证了该方法的收敛性。对自适应算法中最相关的参数进行了数值研究,并检验了其对收敛速度的影响。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Residual-based adaptive refinement for meshless eigenvalue solvers
The concept of an adaptive meshless eigenvalue solver is presented and implemented for two-dimensional structures. Based on radial basis functions, eigenmodes are calculated in a collocation approach for the second-order wave equation. This type of meshless method promises highly accurate results with the simplicity of a node-based collocation approach. Thus, when changing the discrete representation of a physical model, only node locations have to be adapted, hence avoiding the numerical overhead of handling an explicit mesh topology. The accuracy of the method comes at a cost of dealing with poorly-conditioned matrices. This is circumvented by applying a leave-one-out-cross-validation optimization algorithm to get stable results. A node adaptivity algorithm is presented to efficiently refine an initially coarse discretization. The convergence is evaluated in two numerical examples with analytical solutions. The most relevant parameter of the adaptation algorithm is numerically investigated and its influence on the convergence rate examined.
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