9/6/22    11:00 - 13:00
Data-driven Reduced Simulation Models for Industrial Applications I  
Minisymposium organized by Norbert Hosters, Daniel Wolff and Daniel Hilger
Room: Spitsbergen
Chair: Norbert Hosters
CoChair: Daniel Wolff
TN, ROM, ML, PINNs – Four approaches for real-time temperature estimation in electric motors in comparison
Henning Sauerland, Akiyasu Miyamoto, Anthony Ohazulike, Huihui Xu and Rik W. De Doncker

Adaptation of multi-fidelity optimization schemes to nonlinear structural dynamics applications
Arne Kaps, Tobias Lehrer, Koushyar Komeilizadeh and Fabian Duddeck

Reduced Order Models for Interdisciplinary Optimization of a Compressor Blade
Lisa Pretsch, Ilya Arsenyev and Fabian Duddeck

Physical Inspired Data-Driven Models using Evolutionary Approach
Somayeh Hosseinhashemi, Christoph Thon, Marvin Röhl and Carsten Schilde

A Data-Driven Reduced Order Modeling Approach Applied in Context of Numerical Analysis and Optimization of Plastic Profile Extrusion
Daniel Hilger and Norbert Hosters

Data-driven Machine Learning (ML) and Reduced Order Modeling (ROM) Approaches in Industrial Finite Element (FEA) Applications
Vasiliki Tsianika, Mariyappa Manohara and Kambiz Kayvantash