From the 1 of 5 linked papers with an AI index.
5 papers
Comparison of a Parametric Physics-Informed Neural Network and a Tensorial Reduced-Order Model for the Shallow-Water Dam-Break Problem
Anton Myshak, Md Rezwan Bin Mizan, Ilya Timofeyev
The paper develops and compares two parametric data-driven reduced models—a physics-informed neural network and a tensorial reduced-order model—for the one-dimensional shallow-wate…
Parametric Reduced Order Models for the Generalized Kuramoto--Sivashinsky Equations
Md Rezwan Bin Mizan, Maxim Olshanskii, Ilya Timofeyev
The paper studies parametric Reduced Order Models (ROMs) for the Kuramoto--Sivashinsky (KS) and generalized Kuramoto--Sivashinsky (gKS) equations. We consider several POD and POD-D…
Reduced-Order Modeling of Parameterized Visco-Plastic Shallow Flows
Md Rezwan Bin Mizan, Ilya Timofeyev, Maxim Olshanskii
We propose a non-intrusive reduced-order modeling framework for parametrized visco-plastic free-surface flows governed by a shallow-water formulation of Herschel--Bulkley fluids. T…
Tensorial Reduced-Order Models for Parametric Coupled Reaction-Diffusion Systems: Application to Brain Tumor Growth Modeling
Asikul Islam, Md Rezwan Bin Mizan, Maxim Olshanskii +1
We construct efficient surrogate models for parametric forward operators arising in brain tumor growth simulations, governed by coupled semilinear parabolic reaction-diffusion syst…
A parametric tensor ROM for the shallow water dam break problem
Md Rezwan Bin Mizan, Maxim Olshanskii, Ilya Timofeyev
We develop a variant of a tensor reduced-order model (tROM) for the parameterized shallow-water dam-break problem. This hyperbolic system presents multiple challenges for model red…