Non-intrusive reduced order modeling of poroelasticity of heterogeneous media based on a discontinuous Galerkin approximation

28 January 2021

Papers citing "Non-intrusive reduced order modeling of poroelasticity of heterogeneous media based on a discontinuous Galerkin approximation"

8 / 8 papers shown

Title
Efficient machine-learning surrogates for large-scale geological carbon and energy storage T. Kadeethum Stephen J Verzi Hongkyu Yoon AI4CE 14 2 0 11 Oct 2023
Stochastic Data-Driven Variational Multiscale Reduced Order Models Fei Lu Changhong Mou Honghu Liu T. Iliescu 26 0 0 06 Sep 2022
Reduced order modeling for flow and transport problems with Barlow Twins self-supervised learning T. Kadeethum F. Ballarin Daniel O’Malley Youngsoo Choi N. Bouklas H. Yoon AI4CE 19 17 0 11 Feb 2022
Non-intrusive reduced order modeling of natural convection in porous media using convolutional autoencoders: comparison with linear subspace techniques T. Kadeethum F. Ballarin Y. Cho Daniel O’Malley H. Yoon N. Bouklas AI4CE 13 61 0 23 Jul 2021
Interval and fuzzy physics-informed neural networks for uncertain fields J. Fuhg Ioannis Kalogeris A. Fau N. Bouklas AI4CE 41 18 0 18 Jun 2021
A framework for data-driven solution and parameter estimation of PDEs using conditional generative adversarial networks T. Kadeethum Daniel O’Malley J. Fuhg Youngsoo Choi Jonghyun Lee Hari S. Viswanathan N. Bouklas AI4CE 25 87 0 27 May 2021
The mixed deep energy method for resolving concentration features in finite strain hyperelasticity J. Fuhg N. Bouklas PINN AI4CE 25 90 0 15 Apr 2021
An autoencoder-based reduced-order model for eigenvalue problems with application to neutron diffusion Toby R. F. Phillips C. Heaney Paul N. Smith Christopher C. Pain 31 57 0 15 Aug 2020