Session: 03-04-01: Emerging Materials Technology

Paper Number: 121467

121467 - Large-Scale Simulations of the Spring Tires and Actuation Devices Made of Shape Memory Alloys 

The current work focuses on implementation of the user-defined shape memory alloy (SMA) model in the finite element analysis program ABAQUS for large-scale simulations of Spring Tires and actuation devices made of SMAs developed at the NASA Glenn Research Center.  The SMA User-Material routine (UMAT) used herein was initially developed as a generalized viscoplasticity routine with potential structure (GVIPS) to target the modeling of both ordinary and high-temperature SMAs. Recently, the UMAT has been modified by the authors to account for concurrent temperature dependency. Prior to implementing the UMAT for modeling the tire construct or the actuation devices, it is characterized using material-level experimental data. To aid with material characterization, cyclic tests were conducted on material-level specimens (e.g., dogbone samples for actuation devices and wire samples for the tire) to produce material-level stress-strain responses at different temperatures. These characterized material properties remain unchanged throughout all designs made from any given SMA material class. Various design variables were varied to study their influence on the global response of the tires and actuators. Despite geometric and configuration differences, a properly characterized material model can accurately predict the performance of the complicated structure even when multiple design variables are altered simultaneously. A detailed investigation of the three-dimensional stress states was also carried out to enhance understanding of the local changes as the structure goes through global deformation. It was concluded that a robust numerical model with a good predictive capability, together with a thoughtfully crafted sensitivity study, can result in reduced design iterations and informed decisions required to reach a desired tire performance. This will, in turn, lead to significantly reduced manufacturing time, required labor, and testing expense. 

Presenting Author: Paria Naghipour NASA Glenn Research Center

Presenting Author Biography: I have been working in the field of computational modeling for the past 15 years. I received my PhD from University of Stuttgart (Germany) in a collaborative effort with German Aerospace Research Center in 2011. Since 2012 I have been working on various projects ranging from modeling of composites to shape memory alloys and electrified propulsion systems.