Publications

Johannes Gerritzen, Andreas Hornig, Peter Winkler, and Maik Gude. A methodology for direct parameter identification for experimental results using machine learning — Real world application to the highly non-linear deformation behavior of FRP. Computational Materials Science, (244 (2024))Elsevier Science B.V., September 2024. [PUMA: FIS_scads Fiber modeling, area_architectures plastics, reinforced Constitutive Machine identification learning, networks, Parameter topic_engineering Neural]

Johannes Gerritzen, Andreas Hornig, Peter Winkler, and Maik Gude. Direct parameter identification for highly nonlinear strain rate dependent constitutive models using machine learning. ECCM21 - Proceedings of the 21st European Conference on Composite Materials, (3):1252--1259, European Society for Composite Materials (ESCM), Jul 2, 2024. [PUMA: Convolutional FIS_scads Fiber area_architectures neural plastics rate dependency, reinforced Direct Strain Machine learning, networks, identification, parameter topic_engineering] URL