A data‐driven approach for the structural analysis of hybrid metal‐plastic composites

The manufacturing of hybrid composites has an important impact on the final structural properties. Manufacturing induced defects influence mechanical performance and thus need to be considered for design. In this contribution, we present a data-driven approach analysis metal-plastic composites. Based numerical analyses, surrogate model based Proper Orthogonal Decomposition Machine Learning is derived that can implemented in early design optimizations.