Research on Superelasticity of Shape Memory Alloys Based on Reproducing Kernel Particle Method-Reference-Cited by-同舟云学术

Research on Superelasticity of Shape Memory Alloys Based on Reproducing Kernel Particle Method

Published:2024-03-28 Issue:04 Volume:16 Page:
ISSN:1758-8251
Container-title:International Journal of Applied Mechanics
language:en
Short-container-title:Int. J. Appl. Mechanics

Author:

Zhang Yijie¹²^ORCID,Wei Gaofeng¹²^ORCID,Liu Tengda¹²^ORCID,Li Anqing¹²^ORCID,Ren Fei¹²^ORCID

Affiliation:

1. School of Mechanical Engineering, Qilu University of Technology (Shandong Academy of Sciences), Shandong 250353, P. R. China

2. Shandong Institute of Mechanical Design and Research, Shandong 250353, P. R. China

Abstract

Shape memory alloys (SMAs), known for their unique superelastic effect, exhibit superior mechanical properties compared to traditional materials. In this study, the reproducing kernel particle method (RKPM) is applied to investigate the superelastic effect of the SMAs. A segmented linearization RKPM model is developed to establish the stress–strain relationship for the superelastic effect, and relevant formulas of superelasticity for the SMAs are derived. Finally, the applicability and accuracy of the RKPM in analyzing the superelastic effect of the SMAs are demonstrated through numerical examples.

Funder

Natural Science Foundation of Shandong Province

National Natural Science Foundation of China

Publisher

World Scientific Pub Co Pte Ltd

Link

https://www.worldscientific.com/doi/pdf/10.1142/S1758825124500406

Reference48 articles.

1. An Experimental Investigation on Training of NiTi-Based Shape Memory Alloys

2. Finite element simulation of strain rate effects on localized unstable pseudoelastic response of shape memory alloys

3. Analytical preconditioners for Neumann elastodynamic boundary element methods

4. The complex variable reproducing kernel particle method for bending problems of thin plates on elastic foundations

5. Analysis of the factors influencing industrial land leasing in Beijing of China based on the district-level data