MS003A Physics-Informed Machine Learning for Surrogate Models in Continuum Mechanics I
Main Organizer:
Ms.
Veronika Travnikova
(
RWTH Aachen University
, Germany
)
Chaired by:
Dr. Matthias Möller (Delft University of Technology , Netherlands) , Ms. Veronika Travnikova (RWTH Aachen University , Germany)
Dr. Matthias Möller (Delft University of Technology , Netherlands) , Ms. Veronika Travnikova (RWTH Aachen University , Germany)
Scheduled presentations:
-
Keynote
Accelerating Numerical Simulations in CFD by Model Reduction with Scientific and Physics-Informed Machine Learning
-
Student
Towards 3D Surrogate Model of Flow in Stirred Tank Reactors Using Physics-Informed Neural Networks
-
Surrogate Modeling of Fluid Flow at Different Reynolds Numbers Using Physics-informed Deep Operator Network
-
Student
4D Flow MRI Velocity Enhancement and Unwrapping Using Divergence-Free Neural Networks
