A multi-linear hardening approach in state-based peridynamics for efficient plastic deformation analysis
Abstract
This paper presents a multi-linear plastic hardening constitutive model based on ordinary state-based peridynamics, which is used to solve the nonlinear hardening behavior of materials effectively. The nonlinear model is discretized into multi-stage linear segments, replacing the Newton-Raphson method for nonlinear iteration, which improves computational efficiency and reduces iteration complexity for nonlinear hardening problems. The algorithm implementation process of peridynamics multi-linear plastic hardening constitutive model is given. By simulating the tensile test of a square plate, the accuracy and efficiency of the multi-linear plastic hardening algorithm are verified. Through discrete analysis using the multi-linear hardening model, it is demonstrated that the number of segments in the multi-linear model can be appropriately increased while maintaining high computational efficiency. Based on the MATLAB platform and by comparing with the J2 plastic hardening benchmark, the proposed model demonstrates a 4-50 times relevant efficiency speedup over nonlinear methods while maintaining accuracy. • The paper innovatively proposes an ordinary state-based peridynamics multi-linear hardening plastic model. • The model avoids using the Newton-Raphson method for numerical iteration, significantly improving computational efficiency and reducing iteration complexity. • The paper demonstrates a significant improvement in computational efficiency. The specific data shows that the computational efficiency has increased by 4 to 50 times using MATLAB platform by comparing with the J2 plastic hardening benchmark. • Through discrete analysis, it has been demonstrated that the multi-linear hardening model can maintain high computational accuracy and efficiency under different discretization densities.
Fields of Study & Subjects
Numerical methods in engineering
High-Velocity Impact and Material Behavior
Rock Mechanics and Modeling
Publication details
- Journal / source
- Computational Particle Mechanics
- Volume
- 14
- Pages
- 19–36
- Publication date
- 30 January 2026
- Language
- EN