Eng. Sara Di Donato, PhD, obtained her PhD in March 2025 from the Department of Industrial Engineering (DIN), University of Bologna. Her doctoral dissertation, entitled “TORSION TESTING FOR CHARACTERIZING THE PLASTIC BEHAVIOR IN METALS: Determination of Material Flow Stress for FEM-Based Design and Optimization of Metal Forming Processes”, focused on advanced experimental and modeling approaches for the reliable determination of flow stress curves to be implemented in FEM simulations of metal forming processes. During her doctoral studies, she also served as a teaching tutor for courses in Mechanical Technology at the University of Bologna.
In the academic year 2025–2026, she is Adjunct Professor for the course “Technologies for Polymeric Composites P (Module 2)” within the Degree Program in Polymeric Composites at the University of Bologna. In the academic year 2024–2025, she was Adjunct Professor for the course “Laboratory of Technologies for Polymeric Composites P (Module 2)” in the same degree program.
Since November 2024, she has been a Research Fellow at the Department of Industrial Engineering (DIN), University of Bologna, within the Horizon Europe project ZEvRA (Zero Emission electric Vehicles enabled by haRmonised circulArity). Her activity in this framework focuses on the development of digital twin models of the aluminum extrusion process, integrated with predictive models for the final microstructure of extruded products made from both primary and secondary aluminum alloys.
Her research activity is focused on the study and modeling of metal forming processes. In recent years, she has specialized in the mechanical characterization of metallic materials, particularly through hot torsion testing aimed at determining reliable flow stress curves to be implemented as input data in FEM simulation codes. She has acquired solid expertise in the development of digital twin models for metal forming processes, with specific focus on aluminum alloy extrusion and wire drawing processes, enabling reliable and simulation-driven process design and optimization. Ultimi avvisi
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