大型结构平行自适应有限元分析

Dipankar K. Ghosh, Prodyot K. Basu
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引用次数: 4

摘要

提出了一种适用于大型结构自适应有限元建模的可扩展并行反馈算法。该算法可在MIMD并行处理器上实现,并采用有限元法的p扩展。在多处理器系统中,利用自动域分配器将问题域划分为若干合适的子域,并将每个子域分配给一个处理器。目前使用的是Connection Machine公司的CM-5系统。以往对有限元分析并行化的研究大多局限于直接或迭代方程求解的并行算法,由于并行任务粒度小,无法产生令人满意的性能。此外,这些努力是基于有限元方法的h扩展,因此不能利用p扩展的一些固有优势。由于目前的算法采用了区域分解技术,并且基于有限元法的p版,因此有望产生良好的性能,特别是对于大型结构。该反馈算法基于一种迭代格式,该格式来源于固体力学问题的应用领域分解技术。对二维问题进行了测试,显示出良好的收敛特性。目前的工作也针对推广方案,并包括自适应模型改进。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Parallel adaptive finite element analysis of large scale structures

A scalable parallel feedback algorithm for adaptive finite element modeling of large scale structures is presented. This algorithm is implementable on MIMD parallel processors, and uses the p-extension of the finite element method. The problem domain is partitioned into a number of suitable subdomains by using an automatic domain decomposer, and each subdomain is thereupon assigned to a processor in the multiprocessor system. Connection Machine's CM-5 system is being used for the present implementation. Most of the previous efforts to parallelize finite element analysis were confined to parallel algorithms for direct or iterative equation solvers, and did not produce satisfactory performance because of the small granularity of parallel tasks. Also, these efforts were based on the h-extension of the finite element method, and hence could not exploit some of the inherent advantages available in the p-extension. As the current algorithm utilizes the domain decomposition technique and is based on the p-version of the finite element method, it is expected to produce good performance, particularly for large scale structures. The feedback algorithm is based on an iterative scheme derived from the domain decomposition technique for applications to problems of solid mechanics. It has been tested for two-dimensional problems showing good convergence characteristics. Current efforts are also directed towards generalizing the scheme, and include adaptive model refinement.

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