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Machine-learning based determination of material model parameters for the out-of-plane shear behavior of fiber-reinforced plastic

Research output: Contribution to conferences › Presentation slides › Contributed

Contributors

Johannes Gerritzen - , Institute of Lightweight Engineering and Polymer Technology (Author)
Andreas Hornig - , Institute of Lightweight Engineering and Polymer Technology (Author)
Peter Winkler - , Department of Distributed and Data Intensive Computing (VDR) (Author)
Maik Gude - , Chair of Lightweight System Engineering and Multi-Material Design (Author)

Details

Original language	English
Publication status	Published - 20 Sept 2023
Peer-reviewed	No

Colloquium

Title	EUROMECH Colloquium 632
Subtitle	Data-driven modelling of porous, composite and polycrystalline microstructures for predicting their mechanical and transport properties
Abbreviated title	EUROMECH Colloquium 632
Duration	20 - 22 September 2023
Website	https://632.euromech.org/
Location	Universität Ulm
City	Ulm
Country	Germany

External IDs

ORCID	/0000-0003-2653-7546/work/187991470
ORCID	/0000-0003-1370-064X/work/187994762
ORCID	/0000-0002-0169-8602/work/187997205

Keywords