CPINNs: A coupled physics-informed neural networks for the closed-loop geothermal system
W Zhang, J Li - Computers & Mathematics with Applications, 2023 - Elsevier
There has been an arising trend of adopting deep learning methods to study partial
differential equations (PDEs). This article is to propose a kind of coupled physics-informed …
differential equations (PDEs). This article is to propose a kind of coupled physics-informed …
Efficient coupled deep neural networks for the time-dependent coupled Stokes-Darcy problems
J Yue, J Li - Applied Mathematics and Computation, 2023 - Elsevier
In this paper, we propose and investigate an efficient method called CDNNs (Coupled Deep
Neural Networks) for the time-dependent coupled Stokes-Darcy problems. Specifically, we …
Neural Networks) for the time-dependent coupled Stokes-Darcy problems. Specifically, we …
Local and parallel finite element methods based on two-grid discretizations for a non-stationary coupled Stokes-Darcy model
Q Li, G Du - Computers & Mathematics with Applications, 2022 - Elsevier
In this paper, some local and parallel finite element methods based on two-grid
discretizations are proposed and investigated for a non-stationary coupled Stokes-Darcy …
discretizations are proposed and investigated for a non-stationary coupled Stokes-Darcy …
Full weak Galerkin finite element discretizations for poroelasticity problems in the primal formulation
This paper develops novel finite element solvers for linear poroelasticity problems on
quadrilateral meshes. These solvers are based on the primal formulations of linear elasticity …
quadrilateral meshes. These solvers are based on the primal formulations of linear elasticity …
A lowest-order staggered DG method for the coupled Stokes–Darcy problem
In this paper we propose a locally conservative, lowest-order staggered discontinuous
Galerkin method for the coupled Stokes–Darcy problem on general quadrilateral and …
Galerkin method for the coupled Stokes–Darcy problem on general quadrilateral and …
The physics informed neural networks for the unsteady Stokes problems
J Yue, J Li - International Journal for Numerical Methods in …, 2022 - Wiley Online Library
In this article, we develop the physics informed neural networks (PINNs) coupled with small
sample learning for solving the transient Stokes equations. Specifically, the governing …
sample learning for solving the transient Stokes equations. Specifically, the governing …
A weak Galerkin-mixed finite element method for the Stokes-Darcy problem
H Peng, Q Zhai, R Zhang, S Zhang - Science China Mathematics, 2021 - Springer
In this paper, we propose a new numerical scheme for the coupled Stokes-Darcy model with
the Beavers-Joseph-Saffman interface condition. We use the weak Galerkin method to …
the Beavers-Joseph-Saffman interface condition. We use the weak Galerkin method to …
A second-order artificial compression method for the evolutionary Stokes-Darcy system
Y Li, Y Hou, Y Rong - Numerical Algorithms, 2020 - Springer
In this paper, we present a second-order decoupled scheme based on the artificial
compression method for the time-dependent Stokes-Darcy equations. This method not only …
compression method for the time-dependent Stokes-Darcy equations. This method not only …
The coupled deep neural networks for coupling of the Stokes and Darcy–Forchheimer problems
We present an efficient deep learning method called coupled deep neural networks
(CDNNs) for coupling of the Stokes and Darcy–Forchheimer problems. Our method …
(CDNNs) for coupling of the Stokes and Darcy–Forchheimer problems. Our method …
A discontinuous Galerkin method for the Brinkman–Darcy-transport problem
In this paper, a weighted discontinuous Galerkin finite element method and an upwind
format are presented to solve the coupled Brinkman–Darcy flow and transport model. The …
format are presented to solve the coupled Brinkman–Darcy flow and transport model. The …