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Nonlinear embeddings for conserving Hamiltonians and other quantities with Neural Galerkin schemes
This work focuses on the conservation of quantities such as Hamiltonians, mass, and
momentum when solution fields of partial differential equations are approximated with …
momentum when solution fields of partial differential equations are approximated with …
Deep learning based reduced order modeling of Darcy flow systems with local mass conservation
We propose a new reduced order modeling strategy for tackling parametrized Partial
Differential Equations (PDEs) with linear constraints, in particular Darcy flow systems in …
Differential Equations (PDEs) with linear constraints, in particular Darcy flow systems in …
[HTML][HTML] Neural network solvers for parametrized elasticity problems that conserve linear and angular momentum
We consider a mixed formulation of parametrized elasticity problems in terms of stress,
displacement, and rotation. The latter two variables act as Lagrange multipliers to enforce …
displacement, and rotation. The latter two variables act as Lagrange multipliers to enforce …
A Mass-Conservative Reduced-Order Algorithm in Solving Optimal Control of Convection-Diffusion Equation
J Song, Q Wu, Y Shi - Journal of Scientific Computing, 2024 - Springer
This paper introduces a novel approach, the mass-conservative reduced-order characteristic
finite element (MCROCFE) method, designed for optimal control problem governed by …
finite element (MCROCFE) method, designed for optimal control problem governed by …
[HTML][HTML] Projection-based reduced order modeling of an iterative scheme for linear thermo-poroelasticity
This paper explores an iterative approach to solve linear thermo-poroelasticity problems,
with its application as a high-fidelity discretization utilizing finite elements during the training …
with its application as a high-fidelity discretization utilizing finite elements during the training …
Projection-based reduced order modeling of an iterative coupling scheme for thermo-poroelasticity
This paper explores an iterative coupling approach to solve thermo-poroelasticity problems,
with its application as a high-fidelity discretization utilizing finite elements during the training …
with its application as a high-fidelity discretization utilizing finite elements during the training …
A locally mass-conservative enriched Petrov-Galerkin method without penalty for the Darcy flow in porous media
H Chen, P Dong, S Sun, Z Wang - arxiv preprint arxiv:2402.08909, 2024 - arxiv.org
In this work we present an enriched Petrov-Galerkin (EPG) method for the simulation of the
Darcy flow in porous media. The new method enriches the approximation trial space of the …
Darcy flow in porous media. The new method enriches the approximation trial space of the …
Solvers for mixed finite element problems using Poincar\'e operators based on spanning trees
WM Boon - arxiv preprint arxiv:2410.08830, 2024 - arxiv.org
We propose an explicit construction of Poincar\'e operators for the lowest order finite
element spaces, by employing spanning trees in the grid. In turn, a stable decomposition of …
element spaces, by employing spanning trees in the grid. In turn, a stable decomposition of …
[PDF][PDF] Results in Applied Mathematics
F Ballarin, S Lee, SY Yi - publicatt.unicatt.it
This paper explores an iterative approach to solve linear thermo-poroelasticity problems,
with its application as a high-fidelity discretization utilizing finite elements during the training …
with its application as a high-fidelity discretization utilizing finite elements during the training …