.png){kind=icon}
返回
A weighted nodal-radial point interpolation meshless method for 2D solid problems
.png){kind=icon}
PRE
AI
DOI：10.1016/j.enganabound.2013.11.007.png)
.png){kind=icon}
原文求助.png){kind=icon}
分享.png){kind=icon}
收藏
摘要
En 中文
In this paper, a novel weighted nodal-radial point interpolation meshless (WN-RPIM) method is proposed for 20 solid problems. In the new approach, the moment matrices are performed only at the nodes to get nodal coefficients. At each computational point (node or integration point), the shape functions are obtained by weighting the nodal coefficients whose nodes are located in its support domain. The shape functions obtained by the new scheme preserve the Kronecicer delta function property under certain conditions. This conclusion can be extended for the weighted nodal-interpolating moving least squares approximation studied in Most and Bucher [New concepts for moving least squares: An interpolating non-singular weighting function and weighted nodal least squares. Eng Anal Bound Elem 2008;32:461-470]. Besides, the new method is much less time consuming than the RPIM method, since the number of nodes is generally much smaller than that of the integration points. Some numerical examples are illustrated to show the effectiveness of the proposed method. Some parameters that influence the performance of the proposed method are also investigated. Crown Copyright (C) 2013 Published by Elsevier Ltd. All rights reserved.
Keyword:
Meshless method
Radial basis function
Point interpolation
Weighted nodal coefficient
Kronecker delta property
AI总结
对已上传原文的论文进行重点信息的提取，主要内容包括：简要概述、研究摘要、背景介绍、关键亮点、图文解析、展望与总结。
期刊
IF:
4.1
论文数:
5.9K
被引数:
9.4K
机构
引用论文
Residual Structure in Islet Amyloid Polypeptide Mediates Its Interactions with Soluble Insulin.png)
Biochemistry
BiochemistryIF0
PREAI
分享收藏
分享收藏分享收藏Analyzing 2D fracture problems with the improved element-free Galerkin method用改进的无网格伽辽金法分析二维断裂问题
PREAI
分享收藏On the optimal shape parameters of radial basis functions used for 2-D meshless methods关于用于二维无网格方法的径向基函数的最佳形状参数
PREAI
分享收藏
查看更多内容