2 papers
math.DS2026
Learning Control-Affine Reduced-Order Models via Autoencoders
Ali Mjalled, Martin Mönnigmann
We present in this paper a framework for the identification of control-affine reduced-order models (ROMs). The proposed method utilizes autoencoders (AEs) to transform the high-dim…
physics.flu-dyn2023
Parametric 3D Convolutional Autoencoder for the Prediction of Flow Fields in a Bed Configuration of Hot Particles
Ali Mjalled, Reza Namdar, Lucas Reineking +3
The use of deep learning methods for modeling fluid flow has drawn a lot of attention in the past few years. In situations where conventional numerical approaches can be computatio…