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Particle-based methods are a practical tool in computational fluid dynamics, and novel types of methods have been proposed. However, widely developed Lagrangian-type formulations suffer from the nonuniform distribution of particles, which…

Fluid Dynamics · Physics 2025-03-26 Takeharu Matsuda , Satoshi Ii

Partial Differential Equations (PDEs) are central to modeling complex systems across physical, biological, and engineering domains, yet traditional numerical methods often struggle with high-dimensional or complex problems. Physics-Informed…

Machine Learning · Computer Science 2026-02-11 Chenggong Zhang

Physics-Informed Neural Networks (PINNs) solve partial differential equations (PDEs) by embedding governing equations and boundary/initial conditions into the loss function. However, enforcing Dirichlet boundary conditions accurately…

Machine Learning · Computer Science 2025-01-15 Nahil Sobh , Rini Jasmine Gladstone , Hadi Meidani

We first propose a hybridizable discontinuous Galerkin (HDG) method to approximate the solution of a \emph{convection dominated} Dirichlet boundary control problem. Dirichlet boundary control problems and convection dominated problems are…

Numerical Analysis · Mathematics 2021-02-01 Gang Chen , John Richard Singler , Yangwen Zhang

In this paper, we discuss the steady and time-dependent nonlinear convection-diffusion (advection-diffusion) equations with the Dirichlet boundary condition. For the steady nonlinear equation, we use an iteration method to reformulate the…

Numerical Analysis · Mathematics 2025-07-28 Qiwei Feng , Catalin Trenchea

Fast and accurate solutions of time-dependent partial differential equations (PDEs) are of pivotal interest to many research fields, including physics, engineering, and biology. Generally, implicit/semi-implicit schemes are preferred over…

Finite element modeling of charged species transport has enabled analysis, design, and optimization of a diverse array of electrochemical and electrokinetic devices. These systems are represented by the Poisson-Nernst-Planck equations…

Computational Engineering, Finance, and Science · Computer Science 2022-05-13 Sungu Kim , Makrand A. Khanwale , Robbyn K. Anand , Baskar Ganapathysubramanian

A system of segregated boundary-domain integral equations (BDIEs) is obtained from the Dirichlet problem for the diffusion equation in non-homogeneous media defined on an exterior two-dimensional domain. We use a parametrix different from…

Analysis of PDEs · Mathematics 2020-11-23 Carlos Fresneda-Portillo , Zenebe W. Woldemicheal

In this paper, we consider the Stokes problem with Dirichlet boundary conditions and the constant kinematic viscosity $\nu$ in an axis-aligned domain $\Omega$. We decouple the velocity $\bm u$ and pressure $p$ by deriving a novel biharmonic…

Numerical Analysis · Mathematics 2025-06-17 Qiwei Feng , Bin Han , Michael Neilan

This study presents a two-level Deep Domain Decomposition Method (Deep-DDM) augmented with a coarse-level network for solving boundary value problems using physics-informed neural networks (PINNs). The addition of the coarse level network…

Machine Learning · Computer Science 2024-08-23 Victorita Dolean , Serge Gratton , Alexander Heinlein , Valentin Mercier

In the present work, we propose to extend to the Stokes problem a fictitious domain approach inspired by eXtended Finite Element Method and studied for Poisson problem in [Renard]. The method allows computations in domains whose boundaries…

Numerical Analysis · Mathematics 2015-06-15 Sébastien Court , Michel Fournié , Alexei Lozinski

The gradient discretisation method (GDM) is a generic framework for designing and analysing numerical schemes for diffusion models. In this paper, we study the GDM for the porous medium equation, including fast diffusion and slow diffusion…

Numerical Analysis · Mathematics 2020-04-02 Jerome Droniou , Kim-Ngan Le

This paper proposes two algorithms to impose seepage boundary conditions in the context of Richards' equation for groundwater flows in unsaturated media. Seepage conditions are non-linear boundary conditions, that can be formulated as a set…

Many problems in science and engineering can be represented by a set of partial differential equations (PDEs) through mathematical modeling. Mechanism-based computation following PDEs has long been an essential paradigm for studying topics…

Machine Learning · Computer Science 2022-11-21 Shudong Huang , Wentao Feng , Chenwei Tang , Jiancheng Lv

In this paper, we propose a new adaptation of the D-iteration algorithm to numerically solve the differential equations. This problem can be reinterpreted in 2D or 3D (or higher dimensions) as a limit of a diffusion process where the…

Numerical Analysis · Computer Science 2012-04-25 Dohy Hong

This paper presents and evaluates a framework for the coupling of subdomain-local projection-based reduced order models (PROMs) using the Schwarz alternating method following a domain decomposition (DD) of the spatial domain on which a…

Numerical Analysis · Mathematics 2024-10-08 Christopher R. Wentland , Francesco Rizzi , Joshua Barnett , Irina Tezaur

We develop a domain-decomposition model reduction method for linear steady-state convection-diffusion equations with random coefficients. Of particular interest to this effort are the diffusion equations with random diffusivities, and the…

Numerical Analysis · Mathematics 2018-02-13 Lin Mu , Guannan Zhang

In this paper, we we study boundary layer problems for the incompressible MHD systems in the presence of physical boundaries with the standard Dirichlet oundary conditions with small generic viscosity and diffusion coefficients. We identify…

Analysis of PDEs · Mathematics 2017-06-27 Shu Wang , Zhouping Xin

In this manuscript, we aim to establish global existence of weak solutions with higher regularity to the compressible Navier-Stokes equations under no-slip boundary conditions. Though Lions\cite{L1} and Feireisl\cite{F1} have established…

Analysis of PDEs · Mathematics 2024-11-05 Xiangdi Huang , Zhouping Xin , Wei Yan

In this work we design and analyse a Discrete de Rham (DDR) method for the incompressible Navier-Stokes equations. Our focus is, more specifically, on the SDDR variant, where a reduction in the number of unknowns is obtained using…

Numerical Analysis · Mathematics 2024-01-10 Daniele A. Di Pietro , Jerome Droniou , Jia Jia Qian