Numerical analysis of small-strain elasto-plastic deformation using local Radial Basis Function approximation with Picard iteration

TL;DR

This paper presents a meshless RBF-FD numerical method combined with Picard iteration for analyzing small-strain elasto-plastic deformation, demonstrating accuracy and robustness in complex geometries compared to FEM.

Contribution

It introduces a novel meshless RBF-FD approach with Picard iteration for elasto-plastic problems, enabling effective analysis without traditional meshing.

Findings

Results agree with analytical and FEM solutions.

Method handles complex geometries effectively.

Comparable accuracy to FEM with meshless advantages.

Abstract

This paper deals with a numerical analysis of plastic deformation under various conditions, utilizing Radial Basis Function (RBF) approximation. The focus is on the elasto-plastic von Mises problem under plane-strain assumption. Elastic deformation is modelled using the Navier-Cauchy equation. In regions where the von Mises stress surpasses the yield stress, corrections are applied locally through a return mapping algorithm. The non-linear deformation problem in the plastic domain is solved using the Picard iteration. The solutions for the Navier-Cauchy equation are computed using the Radial Basis Function-Generated Finite Differences (RBF-FD) meshless method using only scattered nodes in a strong form. Verification of the method is performed through the analysis of an internally pressurized thick-walled cylinder subjected to varying loading conditions. These conditions induce states of elastic expansion, perfectly-plastic yielding, and plastic yielding with linear hardening. The results are benchmarked against analytical solutions and traditional Finite Element Method (FEM) solutions. The paper also showcases the robustness of this approach by solving case of thick-walled cylinder with cut-outs. The results affirm that the RBF-FD method produces results comparable to those obtained through FEM, while offering substantial benefits in managing complex geometries without the necessity for conventional meshing, along with other benefits of meshless methods.