Block-partitioned Rayleigh-Ritz method for efficient eigenpair reanalysis of large-scale finite element models

IF 4.8 2区 工程技术 Q1 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS Journal of Computational Design and Engineering Pub Date : 2023-04-10 DOI:10.1093/jcde/qwad030
Yeon-Ho Jeong, Seung-Hwan Boo, S. Yim
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Abstract

In this manuscript, we propose a new effective method for eigenpair reanalysis of large-scale finite element (FE) models. Our method utilizes the matrix block-partitioning algorithm in the Rayleigh-Ritz approach and expresses the Ritz basis matrix using thousands of block matrices of very small size. To avoid significant computational costs from the projection procedure, we derive a new formulation that uses tiny block computations instead of global matrix computations. Additionally, we present an algorithm that recognizes which blocks are changed in the modified FE model to achieve computational cost savings when computing new eigenpairs. Through selective updating for the recognized blocks, we can effectively construct the new Ritz basis matrix and the new reduced mass and stiffness matrices corresponding to the modified FE model. To demonstrate the performance of our proposed method, we solve several practical engineering problems and compare the results with those of the combined approximation (CA) method, the most well-known eigenpair reanalysis method, and ARPACK, an eigenvalue solver embedded in many numerical programs.
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大规模有限元模型特征对有效再分析的分块Rayleigh-Ritz方法
在本文中,我们提出了一种新的有效的大尺度有限元模型特征对再分析方法。我们的方法利用瑞利-里兹方法中的矩阵块划分算法,并使用数千个非常小的块矩阵来表示里兹基矩阵。为了避免投影过程的大量计算成本,我们推导了一个使用小块计算代替全局矩阵计算的新公式。此外,我们提出了一种算法,该算法可以识别修改后的有限元模型中哪些块被改变,从而在计算新特征对时节省计算成本。通过对识别块的选择性更新,可以有效地构建新的Ritz基矩阵和与修正后的有限元模型相对应的新的质量和刚度简化矩阵。为了证明我们提出的方法的性能,我们解决了几个实际的工程问题,并将结果与最著名的特征对再分析方法组合近似(CA)方法和许多数值程序中嵌入的特征值求解器ARPACK的结果进行了比较。
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来源期刊
Journal of Computational Design and Engineering
Journal of Computational Design and Engineering Computer Science-Human-Computer Interaction
CiteScore
7.70
自引率
20.40%
发文量
125
期刊介绍: Journal of Computational Design and Engineering is an international journal that aims to provide academia and industry with a venue for rapid publication of research papers reporting innovative computational methods and applications to achieve a major breakthrough, practical improvements, and bold new research directions within a wide range of design and engineering: • Theory and its progress in computational advancement for design and engineering • Development of computational framework to support large scale design and engineering • Interaction issues among human, designed artifacts, and systems • Knowledge-intensive technologies for intelligent and sustainable systems • Emerging technology and convergence of technology fields presented with convincing design examples • Educational issues for academia, practitioners, and future generation • Proposal on new research directions as well as survey and retrospectives on mature field.
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