
MS007C Machine Learning Methods for Multiscale and Multiphysics Material Modeling III
MS Corresponding Organizer: Prof. Fadi Aldakheel ( Leibniz Universität Hannover , Germany )
Chaired by:
Prof. Miguel Bessa ( Brown University , United States ) , Prof. Oliver Weeger ( TU Darmstadt , Germany )
Prof. Miguel Bessa ( Brown University , United States ) , Prof. Oliver Weeger ( TU Darmstadt , Germany )
Scheduled presentations:
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Deep learning for accelerating computational homogenization schemes: application to flows in porous media
M. Shakoor*, V. Itier, J. Mennesson -
Symmetry-enforcing neural networks for constitutive modeling
K. Garanger, J. Rimoli* -
A physical-informed FE-NN methodology for predicting highly nonlinear thermomechanical response of thermoset and thermoplastic polymers
N. Tang*, P. Hao, F. Gilabert Villegas -
Evaluating Filled Rubber Viscoelasticity: A Comparative Analysis between NODEs and Classical Phenomenological Models
F. Califano*, J. Ciambella -
A data-driven framework to establish surrogate constitutive models of porous elastomers
M. Bozkurt*, V. Tagarielli