|January 25, 2024, 1:00 p.m. (CET)
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Since 2009, this seminar represents a general platform for talks and exchange in the field of surrogate modelling, in particular Model Order Reduction (MOR) as well as novel data-based techniques in simulation science. Both methodological as well as application oriented presentations highlight the various aspects and the relevance of surrogate modelling in mathematics, technical mechanics, material science, control theory and other fields. We aim both at university members, as well as external persons from science and industry. The seminar is organized by four research groups and represents an activity of the SimTech Cluster of Excellence.
Date: Thursday, 25 January
Time: 1:00 pm
Venue: Pfaffenwaldring 7, V7.12
Topic: Numerical Surrogate Models for the Optimization of Automotive Crash Structures
Speaker: Ralf Sturm (DLR Stuttgart)
Abstract: A challenge in the design and optimisation of vehicle structures is the high computational costs required for crash analysis. A methodological approach to simplifying Finite Element (FE) vehicle models and crash barriers is presented in this talk. The methodology uses global deformation characteristics of structures which are obtained from the global crash model. For the simplification of the vehicle crash model structural regions which are sustaining only elastic deformations during the crash are replaced by kinematic numerical representations which describe both stiffness and load paths at the interface of the substituted structures. Verification studies of the simplified vehicle model show a very good agreement of the global and local structural response during the frontal crash. Further simplifications were applied to deformable barriers by replacing its detailed crushing behaviour by kinematic descriptions. Through the combined use of both simplified numerical representations, the computational cost of an Euro NCAP offset crash analysis can be reduced by around 92%. With the obtained time reduction structural optimisation studies of the remaining structure can be conducted efficiently for the identification of weight reduction potentials.