Computational Analysis of Advanced Shape-Memory Alloy Devices Through a Robust Modeling Framework

Abstract

Shape-memory alloys (SMA) provide significant advantages in various industrial fields, but their manufacturing and commercialization are currently hindered. This is attributed mainly to the poor knowledge of material behavior and the lack of standards in its mechanical characterization. SMA products are usually developed by trial-and-error testing to address specific design requirements, thus increasing costs and time. The development of simulation tools offers a possible solution to assist engineers and designers and allows to better understand SMA transformation phenomena. Accordingly, the purpose of the present paper is to numerically analyze and predict the response of spring-like actuators and septal occluders, which are industrial components exploiting the shape-memory and pseudoelastic properties of SMAs, respectively. The methodology includes two main stages: the implementation of the three-dimensional phenomenological model known as Souza–Auricchio model and the finite element modeling of the device. A discussion about the steps of each stage, as parameter identification and model generalizations, is provided. Validation results are presented through a comparison with the results of a performed experimental campaign. The framework proves good prediction capabilities and allows to reduce the number of experimental tests in the future.