A Fast Implementation of the Linear Bond-Based Peridynamic Beam Model

IF 1.5 4区 工程技术 Q2 MATHEMATICS, APPLIED Advances in Applied Mathematics and Mechanics Pub Date : 2023-08-01 DOI:10.4208/aamm.oa-2023-0059
H. Tian, Xianchu Yang, Chenguang Liu
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Abstract

. While the theory of peridynamics (PD) holds significant potential in engineering, its application is often limited by the significant computational costs by the nonlocality of PD. This research is based on a three-dimensional(3D) complex Tim-oshenko beam structure with six degrees of freedom. We propose a fast meshfree method based on the linear bond-based PD model of the stiffness matrix structure by ingeniously using the matrix decomposition strategy to maintain the Teoplitz structure of the stiffness matrix. This method significantly reduces the amount of calculation and storage without losing accuracy, reduces the amount of calculation from O ( N 2 ) to O ( N log N ) , and decreases the storage capacity from O ( N 2 ) to O ( N ) . We validate the effectiveness of our approach through numerical examples, particularly in multi-beam structures. We demonstrate that our method realizes algorithm acceleration in numerical simulations of multi-beam structures subjected to static concentrated loads.
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基于线性键的周动力梁模型的快速实现
. 虽然周动力学理论在工程上具有巨大的潜力,但其应用往往受到其非局域性所带来的巨大计算成本的限制。这项研究是基于一个三维(3D)复杂的六自由度的Tim-oshenko梁结构。提出了一种基于线性键合的刚度矩阵PD模型的快速无网格方法,巧妙地利用矩阵分解策略来保持刚度矩阵的Teoplitz结构。该方法在不损失精度的前提下显著减少了计算量和存储量,将计算量从0 (n2)减少到O (N log N),将存储容量从0 (n2)减少到O (N)。通过数值算例验证了该方法的有效性,特别是在多梁结构中。在静态集中荷载作用下的多梁结构数值模拟中,证明了该方法实现了算法加速。
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来源期刊
Advances in Applied Mathematics and Mechanics
Advances in Applied Mathematics and Mechanics MATHEMATICS, APPLIED-MECHANICS
CiteScore
2.60
自引率
7.10%
发文量
65
审稿时长
6 months
期刊介绍: Advances in Applied Mathematics and Mechanics (AAMM) provides a fast communication platform among researchers using mathematics as a tool for solving problems in mechanics and engineering, with particular emphasis in the integration of theory and applications. To cover as wide audiences as possible, abstract or axiomatic mathematics is not encouraged. Innovative numerical analysis, numerical methods, and interdisciplinary applications are particularly welcome.
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