WW-Colloquium: Inaugural Lecture PD Dr. Frank Wendler, Simulation of thermomechanically coupled loading problems for shape memory alloy devices
Date: 16. June 2026Time: 16:00 – 18:00Location: H14/Zoom
PD Dr. Frank Wendler
Materials Simulation, Department of Materials Science and Engineering, FAU
Simulation of Thermomechanically Coupled Loading Problems for Shape Memory Alloy Devices
Shape memory alloys (SMAs) have been established in various fields from aerospace engineering, biomedicine and microsystem technology for highly specialized applications in actuation, creep-free clamping and connectors and vibration damping. Their exceptional properties relate to a fully reversible structural phase transition that enforces a highly nonlinear thermomechanical coupling, leading to well-known effects like one-way shape memory effect, superelasticity and elastocaloric self-heating/cooling. Despite more than three decades of research and modeling efforts, this material class is still a non-standard case in material simulation, and often only marginally captured in commercial material simulation software.
In the talk, two different modeling approaches including their application cases are presented, with a focus on polycrystalline materials and micro systems: First, a model that bases on thermally activated kinetics is developed and applied to dynamic loading cases. Here, examples for passive and active damping and vibration control of Ti-Ni(-Fe) micro thin film bridges are given. Second, for capturing large deformation and nonlinear effects for systems composed of slender SMA beams a model in analogy to J2-plasticity is designed. This is applied to a micro-origami meta-material that is capable of shape changes driven by Joule-heated SMA bending actuators. Furthermore, application of this simulation approach to design SMA-based restorations in dental prosthetics and implants is shown.
As a an outlook, we show how new classes of SMAs, new production processes and related certification of product life necessitate extensive quantitative simulations, based on models automatically adapted to experimental data.