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07/21/2023
A pressure-free long-time stable reduced-order model for two-dimensional Rayleigh-Bénard convection
The present work presents a stable POD-Galerkin based reduced-order mode...
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07/20/2023
Energy-consistent discretization of viscous dissipation with application to natural convection flow
A new energy-consistent discretization of the viscous dissipation functi...
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01/31/2023
Energy-Conserving Neural Network for Turbulence Closure Modeling
In turbulence modeling, and more particularly in the Large-Eddy Simulati...
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12/22/2022
No pressure? Energy-consistent ROMs for the incompressible Navier-Stokes equations with time-dependent boundary conditions
This work presents a novel reduced-order model (ROM) for the incompressi...
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10/26/2022
Comparison of neural closure models for discretised PDEs
Neural closure models have recently been proposed as a method for effici...
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08/19/2022
Learning filtered discretization operators: non-intrusive versus intrusive approaches
Simulating multi-scale phenomena such as turbulent fluid flows is typica...
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08/19/2022
Momentum-conserving ROMs for the incompressible Navier-Stokes equations
Projection-based model order reduction of an ordinary differential equat...
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11/24/2021
Markov Chain Generative Adversarial Neural Networks for Solving Bayesian Inverse Problems in Physics Applications
In the context of solving inverse problems for physics applications with...
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04/27/2020
Multi-level neural networks for PDEs with uncertain parameters
A novel multi-level method for partial differential equations with uncer...
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07/09/2019