MS007A Machine Learning Methods for Multiscale and Multiphysics Material Modeling I
MS Corresponding Organizer: Prof. Fadi Aldakheel (Leibniz Universität Hannover)
Chaired by:
Prof. Fadi Aldakheel (Leibniz Universität Hannover , Germany) , Prof. Miguel Bessa (Brown University , United States)
Prof. Fadi Aldakheel (Leibniz Universität Hannover , Germany) , Prof. Miguel Bessa (Brown University , United States)
Scheduled presentations:
-
Keynote
Machine Learning for the Inverse Design of Architected Materials
L. Zheng, J. Bastek, K. Karapipersi, S. Kumar, D. Kochmann* -
Parameterized hyperelastic material modeling and multiscale topology optimization with physics-augmented neural networks
O. Weeger*, D. Klein, F. Roth, F. Püsch, K. Maute -
Deep learning-aided inverse design of porous metamaterials
T. Nguyen*, Y. Heider, F. Aldakheel -
Experiment-informed Finite-strain Inverse Design of Spinodal Metamaterials
P. Thakolkaran, M. Espinal, S. Dhulipala, S. Kumar*, C. Portela -
Unifying the design space and optimizing linear and nonlinear truss metamaterials by generative modeling
L. Zheng*, K. Karapiperis, S. Kumar, D. Kochmann
