EU Regional School - Fritzen Seminar

Dr. Felix Fritzen - Model Order Reduction and Data-assisted Surrogates in Materials Science

Abstract

In engineering applications the use of manufactured or natural composite materials is a key technology enabling leight-weight constructions and outstanding physical properties. However, the prediction of the impact of changes of the microstructural configuration on the physical properties are nontrivial to foresee. In order to better understand the microstructure-property relations, the use of model order reduction can be of great use. First, it enables parametric studies that account for deviations of the phase properties. Second, it allows for the consideration of nonlinearities at a fraction of the compute time of fully resolved models. The link between model reduction and computational homogenization in linear and nonlinear settings will be explored in this lecture. Further, the use of state of the art data-assisted techniques for the surrogation of nonlinear material models will be discussed. Here the use of reduced order models for the generation of the samples of the full order model are found to be rather useful.