Wednesday, March 15th, 2023. Time: 15h
Hybrid! O.C. Zienkiewicz Room, C1 Building, UPC Campus Nord, Barcelona |
Link for online session
ABSTRACT
During the design process of a new vehicle, structural engineers face the challenge of defining the material and geometrical properties of all the car components and ensuring by means of computer simulations that all targets are fulfilled. Given that there are millions of possible configurations, exploring the entire design space by means of standard full-order simulations is not affordable, even if powerful computer resources are employed.
A reduced order technique based on the Proper Generalized Decomposition (PGD) method has been developed to significantly simplify the numerical complexity of this parametric problem and allow to explore the entire design space. With only one computation, the method computes a parametric solution that contains the results for every possible combination of predefined design variables. The result is then post-processed by an interactive GUI app, where designers can explore in real-time how changes in the design variables affect the car behavior and take decisions accordingly.
SPEAKER CV
Fabiola Cavaliere received her degree in Civil Engineering from Polytechnic of Bari (Italy) in 2016. Until 2018, she was a researcher at RWTH-Aachen University (Germany), where she focused on numerical methods and multi-scale model order reduction techniques.
From 2018 to 2022, Fabiola was a researcher PhD Candidate at CIMNE, funded by the Marie Curie Programme. Her PhD involved academic institutions (UPC/CIMNE and the Swansea University) and SEAT S.A. as an industrial partner. During her research activity, she developed a novel methodology based on a reduced order approach to optimize the development process of a car structure. After her PhD, she joined the automotive company, where she is now responsible of the “AI structural simulation” activities at the SEAT R&D Center in Barcelona.
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