7 papers · 1 filter
Physics-Informed Neural Networks for Biot's Model via Fixed-Stress Splitting and Energy Natural Gradient Descent
Kexin Sun, Qiang Liu, Minfu Feng +1
Physics-Informed Neural Networks (PINNs) have recently gained considerable attention as a mesh-free framework for solving partial differential equations. Nevertheless, their perfor…
A Unified Model for Thermo- and Multiple-Network Poroelasticity with a Global-in-Time Iterative Decoupling Scheme
Huipeng Gu, Mingchao Cai, Jingzhi Li +1
This paper introduces a unified model for thermo-poroelasticity and multiple-network poroelasticity, reformulated into a total-pressure-based system. We first establish the well-po…
POD-based reduced order modeling of global-in-time iterative decoupled algorithms for Biot's consolidation model
Huipeng Gu, Francesco Ballarin, Mingchao Cai +1
This paper focuses on the efficient numerical algorithms of a three-field Biot's consolidation model. The approach begins with the introduction of innovative monolithic and global-…
Some semi-decoupled algorithms with optimal convergence for a four-field linear thermo-poroelastic model
Ziliang Li, Mingchao Cai, Jingzhi Li +1
We propose three semi-decoupled algorithms for efficiently solving a four-field thermoporoelastic model. The first two algorithms adopt a sequential strategy: at the initial time s…
An Optimally Convergent parallel splitting Algorithm for the Multiple-Network Poroelasticity Model
Jijing Zhao, Huangxin Chen, Mingchao Cai +1
This paper presents a novel parallel splitting algorithm for solving quasi-static multiple-network poroelasticity (MPET) equations. By introducing a total pressure variable, the MP…
Parameter-Robust Preconditioners for A Four-Field Thermo-Poroelasticity Model
Mingchao Cai, Miroslav Kuchta, Jingzhi Li +2
We study a thermo-poroelasticity model which describes the interaction between the deformation of an elastic porous material and fluid flow under non-isothermal conditions. The mod…