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An Improved Material Point Method with Aggregated and Smoothed Bernstein Functions

Authors :
Zheng Zhu
Tengfei Bao
Xi Zhu
Jian Gong
Yuhan Hu
Jingying Zhang
Source :
Mathematics, Vol 11, Iss 4, p 907 (2023)
Publication Year :
2023
Publisher :
MDPI AG, 2023.

Abstract

Nodal shape functions and their gradients are vital in transferring physical information within the material point method (MPM). Their continuity is related to numerical stability and accuracy, and their support domain size affects computational efficiency. In this paper, a scheme of aggregated and smoothed Bernstein functions is proposed to improve the MPM. In detail, the Bernstein polynomials are smoothed with a convolution reformation to eliminate the cell crossing error, and an aggregation strategy is implemented to cut down the node amount required for field probing. Hierarchical MPM variants are obtained with choices of original Bernstein polynomials and degrees of smoothing. Numerical examples show that mass, momentum, and energy conservations are all well met, and no cell crossing noise exists. In addition, solution accuracy and numerical stability are significantly improved in large deformation problems.

Details

Language :
English
ISSN :
22277390
Volume :
11
Issue :
4
Database :
Directory of Open Access Journals
Journal :
Mathematics
Publication Type :
Academic Journal
Accession number :
edsdoj.7d2e0fcaea6d47e9a3bc663b1b2249fb
Document Type :
article
Full Text :
https://doi.org/10.3390/math11040907