MS132B Machine Learning and AI in Constitutive Modeling of Complex Materials II
Main Organizer:
Dr.
Francisco Sahli Costabal
(
Pontificia Universidad Católica de Chile
, Chile
)
Chaired by:
Prof. Mathias Peirlinck (Delft University of Technology , Netherlands) , Dr. Siddhant Kumar (Delft University of Technology , Netherlands)
Prof. Mathias Peirlinck (Delft University of Technology , Netherlands) , Dr. Siddhant Kumar (Delft University of Technology , Netherlands)
Scheduled presentations:
-
A framework for training DNN-based surrogate constitutive equations for thin-walled rods: incorporating local effects into global rod behavior
-
A Gaussian Process Framework with Expectation Propagation for Physics-Constrained Creep Constitutive Modeling
-
Traceable Unsupervised Constitutive Model Discovery from Sparse and Noisy Data
-
Data-Driven Modeling of Hyperelastic Material Families
-
Efficient 2-D and 3-D Elastography of Hyperelastic Functionally Graded Materials using Inverse Finite Element Method
-
Uncertainty Quantification in Model Discovery by Distilling Interpretable Material Constitutive Models from Gaussian Process Posteriors
