In-silico tools for the optimization of smart devices: A case-study of a NiTi-based torque limiter

Abstract

Traditional device optimization often relies on iterative trial-and-error, a time-consuming and costly approach. Numerical models offer a promising solution to accelerate this process. This work presents a workflow for optimizing existing smart devices using numerical models, with a focus on an innovative torque limiter based on NiTi tapes. A numerical model, calibrated with experimental tensile data, identified critical stress concentration zones in the NiTi tapes during functioning, limiting the cyclic fatigue life of the device. By leveraging the finite element analysis, the geometry was optimized to mitigate these stress concentrations. Additive manufacturing enabled the rapid production of the optimized design. Finally, an experimental validation confirmed the effectiveness of the in silico-driven optimization approach, demonstrating a substantial improvement in the cyclic fatigue resistance of the NiTi tapes.