MS013A Physics-Based Data-Driven Modeling and Uncertainty Quantification in Computational Materials Science and Engineering I
Main Organizer:
Prof.
Johann Guilleminot
(
Duke University
, United States
)
Chaired by:
Prof. Johann Guilleminot (Duke University , United States)
Prof. Johann Guilleminot (Duke University , United States)
Scheduled presentations:
-
Physics-Constrained Data-Driven Constitutive Modeling for Microstructure-Informed Anisotropic Progressive Damage Analysis
-
Generative Physics-Aware Neural Implicit Solvers Inverse Problems in Heterogeneous Media.
-
The Bayesian Finite Element Method: a Probabilistic Model for Discretization Error
-
Data-driven Approaches for Tracking Error in Adaptive Training of Non Intrusive Reduced Order Models
-
Continuous-Scale Bridge Processes for Multiscale Generation
-
Reliability-Aware Physically-Guided Neural Networks for uncertainty assimilation, error propagation and statistically-informed decision making
