Experimental validation of shape memory material model implemented in commercial finite element software under multiaxial loading

Abstract

Shape memory alloys are used in ever-increasing numbers of applications, such as implants made of porous shape memory alloys, where the material is subjected to complex loading conditions with various loading paths. Finite element simulation of such parts requires utilizing a constitutive model that is able to capture the multiaxial and path-dependent behavior of shape memory alloys. The main objective of this article is to investigate the accuracy of the constitutive model implemented in current commercial finite element software such as Ansys in predicting the shape memory alloys mechanical response under different multiaxial loading paths. To this end, several isothermal tests were conducted on thin-walled NiTi tubes with uniaxial, as well as multiaxial, path-varying loadings. The performance of the material model within Ansys was then investigated by finite element modeling of the sample tubes and performing simulations of the tests. Comparing the finite element results with experimental data, it was observed that while this model provided a close prediction of the uniaxial tensile superelastic response, it was not able to reproduce the multiaxial and path-dependent behavior of the shape memory alloy samples with sufficient accuracy. A brief discussion of the reasons behind the inaccuracy of the current model and potentially promising models for future investigation are provided.

Laser powder bed fusion of diatom frustule inspired bionic NiTi lattice structures: compressive behavior and shape memory effect

“…When the ratio is less than 0.71, the material exhibits cyclic hardening behavior [55]. According to the experimental result [36] (figure 3(c)), the yield ratio of LPBF-processed NiTi was 0.585 (<0.71), which meant that cyclic hardening behavior occurred during compression tests. Figures 9(b), (d), (f) and (h) show the recovery strain after unloading (ε unload , marked by green), the recovery strain via heating (ε heat , marked by red), and irrecoverable strain (ε irr , marked by blue).…”

“…The numerical simulation of components was conducted to analyze the stress distribution and deformation process of bionic lattice structures. According to the stress-strain curve of the NiTi sample [36] (figure 3(c)), material properties of NiTi were set as shown in table 2. Before using the data, the chemical composition and tensile properties of NiTi materials were compared to ensure that the error was within the allowable range.…”

A novel smart assistive knee brace incorporated with shape memory alloy wire actuator

“…Recently, the use of shape memory alloy (SMA) materials has been significantly increasing due to their unique properties such as adapting intelligently to external disturbances (Khodaei and Terriault, 2018; Kuo et al, 2012; Liu et al, 2020; Sohn et al, 2018; Vignoli et al, 2020). An SMA is categorized as a smart material capable of changing its crystal structure between the martensite phase and the austenite phase through thermo-mechanical loading.…”

Deformation and Degradation of Superelastic NiTi Under Multiaxial Loading

“…Among most multiaxial studies mentioned above, the transformation behavior and the material degradation were examined only at the macroscopic length scale. Khodaei et al showed that constitutive modelling failed to predict the mechanical response under multiaxial loads, because the model does not capture the anisotropic transformation behaviour related to the crystallographic orientation and the loading path [33]. Detailed experimental data is required to improve the micromechanical models.…”