Finite Element Modeling and Rolling Behavior of NiTi-based SMAs

Thursday, May 7, 2026: 10:30 AM
Mr. Andre Montagnoli , University of North Texas, Denton, TX
Mr. Nathan Tran , University of North Texas, Denton, TX
Dr. Faith Gantz , Confluent Medical Technologies, Fremont, CA, University of North Texas, Denton, TX
Dr. Marcus L. Young , University of North Texas, Denton, TX
Shape memory alloys (SMAs) are widely used in biomedical applications, including bone implants and coronary stents, due to their shape memory and superelastic properties. Among them, NiTi-based SMAs are of particular importance but remain difficult and costly to process because of their thermal sensitivity and compositional variability. While finite element analysis (FEA) has been successfully applied to optimize processing parameters in metallic systems, no validated modeling framework has been established to simulate the rolling behavior of NiTi-based SMAs. This study investigates and compares the rolling behavior of two NiTi-based alloys with corresponding FEA predictions. Rolling strategies were employed to assess the effects of thermomechanical processing. Microstructural characterization was carried out using optical microscopy and scanning electron microscopy (SEM), with elemental composition analyzed through energy-dispersive spectroscopy (EDS). Grain structure evolution and phase distribution were correlated with the applied rolling strategies. Mechanical performance was evaluated through Vickers hardness and uniaxial tensile testing. Experimental results were compared with simulations generated using Forge software, focusing on rolling loads, strain distribution, and deformation behavior. The combined approach demonstrates how alloy composition, processing temperature, and annealing cycles affect microstructural refinement, crystallographic orientation evolution, and mechanical response. These findings provide new insights into optimizing rolling strategies and processing routes for NiTi-based SMAs, supporting the development of tailored microstructures and improved functional performance in biomedical applications.
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