MS014B Accelerating scientific discovery for dynamical systems with physics-informed machine learning II
MS Corresponding Organizer:
Dr.
Romit Maulik
(
Argonne National Laboratory
, United States
)
Scheduled presentations:
-
ψ − flow: A Novel Physics-Constrained Architecture to Enforce Incompressibility and Boundary Conditions for Fast and Accurate Flow Predictions
-
Physics-Informed Neural Network with Turbulent Flow over Fluid Saturated Porous Media
-
Operator Learning via Neural Networks with Kernel-Weighted Corrective Residuals
-
Data-Driven Structural Health Monitoring of Beam Elements Using Machine Learning Techniques
