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A fast object-oriented Matlab implementation of the Reproducing Kernel Particle Method

机译:再生内核粒子方法的快速面向对象的Matlab实现

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Novel numerical methods, known as Meshless Methods or Meshfree Methods and, in a wider perspective, Partition of Unity Methods, promise to overcome most of disadvantages of the traditional finite element techniques. The absence of a mesh makes meshfree methods very attractive for those problems involving large deformations, moving boundaries and crack propagation. However, meshfree methods still have significant limitations that prevent their acceptance among researchers and engineers, namely the computational costs. This paper presents an in-depth analysis of computational techniques to speed-up the computation of the shape functions in the Reproducing Kernel Particle Method and Moving Least Squares, with particular focus on their bottlenecks, like the neighbour search, the inversion of the moment matrix and the assembly of the stiffness matrix. The paper presents numerous computational solutions aimed at a considerable reduction of the computational times: the use of kd-trees for the neighbour search, sparse indexing of the nodes-points connectivity and, most importantly, the explicit and vectorized inversion of the moment matrix without using loops and numerical routines.
机译:新颖的数值方法,称为无网格方法或无网格方法,从更广泛的角度讲,是统一方法的划分,有望克服传统有限元技术的大多数缺点。缺少网格使无网格方法对于涉及大变形,移动边界和裂纹扩展的问题非常有吸引力。但是,无网格方法仍然存在很大的局限性,妨碍了它们在研究人员和工程师中的接受,即计算成本。本文将对计算技术进行深入分析,以加快“再现核粒子法”和“移动最小二乘法”中形状函数的计算,特别着重于它们的瓶颈,例如邻居搜索,矩矩矩阵的求逆以及刚度矩阵的集合。本文提出了许多旨在大大减少计算时间的计算解决方案:使用kd树进行邻居搜索,稀疏索引节点-点的连通性以及最重要的是,在不使用矩量矩阵的情况下进行显式和矢量化求逆使用循环和数字例程。

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