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We investigate the use of non-overlapping domain decomposition (DD) methods for nonlinear structure problems. The classic techniques would combine a global Newton solver with a linear DD solver for the tangent systems. We propose a…

Numerical Analysis · Mathematics 2016-06-22 Camille Negrello , Pierre Gosselet , Christian Rey , Julien Pebrel

Domain decomposition provides an effective way to tackle the dilemma of physics-informed neural networks (PINN) which struggle to accurately and efficiently solve partial differential equations (PDEs) in the whole domain, but the lack of…

Machine Learning · Computer Science 2024-04-30 Ye Liu , Jie-Ying Li , Li-Sheng Zhang , Lei-Lei Guo , Zhi-Yong Zhang

In this work we study the convergence properties of the one-level parallel Schwarz method with Robin transmission conditions applied to the one-dimensional and two-dimensional Helmholtz and Maxwell's equations. One-level methods are not…

Numerical Analysis · Mathematics 2022-01-13 Niall Bootland , Victorita Dolean , Alexandros Kyriakis , Jennifer Pestana

Optimization with time-dependent partial differential equations (PDEs) as constraints {appears} in many science and engineering applications. The associated first-order necessary optimality system consists of one forward and one backward…

Numerical Analysis · Mathematics 2017-09-28 Jun Liu , Zhu Wang

Physics-Informed Neural Networks (PINNs) are a novel computational approach for solving partial differential equations (PDEs) with noisy and sparse initial and boundary data. Although, efficient quantification of epistemic and aleatoric…

Machine Learning · Computer Science 2025-05-02 Júlia Vicens Figueres , Juliette Vanderhaeghen , Federica Bragone , Kateryna Morozovska , Khemraj Shukla

We introduce adaptive-basis physics-informed neural networks (AB-PINNs), a novel approach to domain decomposition for training PINNs in which existing subdomains dynamically adapt to the intrinsic features of the unknown solution. Drawing…

Machine Learning · Computer Science 2025-10-13 Jonah Botvinick-Greenhouse , Wael H. Ali , Mouhacine Benosman , Saviz Mowlavi

The convergence rate of domain decomposition methods (DDMs) strongly depends on the transmission condition at the interfaces between subdomains. Thus, an important aspect in improving the efficiency of such solvers is careful design of…

Numerical Analysis · Mathematics 2025-05-19 Niall Bootland , Sahar Borzooei , Victorita Dolean , Pierre-Henri Tournier

The inverse Robin problem covers the determination of the Robin parameter in an elliptic partial differential equation posed on a domain $\Omega$. Given the solution of the Robin problem on a subdomain $\omega \subset \Omega$ together with…

Numerical Analysis · Mathematics 2025-09-23 Erik Burman , Marvin Knöller , Lauri Oksanen

In this paper we propose on continuous level several domain decomposition methods to solve unilateral and ideal multibody contact problems of nonlinear elasticity. We also present theorems about convergence of these methods.

Numerical Analysis · Mathematics 2012-09-07 Ihor I. Prokopyshyn , Ivan I. Dyyak , Rostyslav M. Martynyak , Ivan A. Prokopyshyn

A non-overlapping domain decomposition algorithm is proposed to solve the linear system arising from mixed finite element approximation of incompressible Stokes equations. A continuous finite element space for the pressure is used. In the…

Numerical Analysis · Mathematics 2012-04-10 Jing Li , Xuemin Tu

In this paper we revisit the Restricted Additive Schwarz method for solving discretized Helmholtz problems, using impedance boundary conditions on subdomains (sometimes called ORAS). We present this method in its variational form and show…

Numerical Analysis · Mathematics 2021-06-11 Shihua Gong , Martin J. Gander , Ivan G. Graham , Euan A. Spence

We propose an overlapping Schwarz space-time refinement framework for the material point method (OS-MPM) to improve computational efficiency in problems with strongly localized deformation, contact, and large geometric nonlinearity. The…

Computational Engineering, Finance, and Science · Computer Science 2026-05-12 Zhaofeng Luo , Minchen Li , Yupeng Jiang

A novel domain-decomposition least-squares Petrov-Galerkin (DD-LSPG) model-reduction method applicable to parameterized systems of nonlinear algebraic equations (e.g., arising from discretizing a parameterized partial-differential-equations…

Numerical Analysis · Mathematics 2021-07-07 Chi Hoang , Youngsoo Choi , Kevin Carlberg

In this paper, we propose and test a novel diagonal sweeping domain decomposition method (DDM) with source transfer for solving the high-frequency Helmholtz equation in $\mathbb{R}^n$. In the method the computational domain is partitioned…

Numerical Analysis · Mathematics 2020-09-02 Wei Leng , Lili Ju

This study presents a discrete physics-informed neural network (dPINN) framework, enhanced with enforced interface constraints (EIC), for modeling physical systems using the domain decomposition method (DDM). Built upon finite element-style…

Computational Engineering, Finance, and Science · Computer Science 2025-05-19 Jichao Yin , Mingxuan Li , Jianguang Fang , Hu Wang

We introduce a domain decomposition-based nonlinear preconditioned iteration for solving nonlinear, nonsmooth elliptic optimal control problems, with a nonlinear reaction term, $L^1$ regularization and box constraints on the control…

Optimization and Control · Mathematics 2021-04-02 Gabriele Ciaramella , Felix Kwok , Georg Müller

This paper explores the reconstruction of a space-dependent parameter in inverse diffusion problems, proposing a shape-optimization-based approach. We consider a Robin boundary condition, physically motivated in diffuse optical tomography…

Numerical Analysis · Mathematics 2026-01-27 Manabu Machida , Hirofumi Notsu , Julius Fergy Tiongson Rabago

A new domain decomposition method is introduced for the heterogeneous 2-D and 3-D Helmholtz equations. Transmission conditions based on the perfectly matched layer (PML) are derived that avoid artificial reflections and match incoming and…

Numerical Analysis · Mathematics 2013-06-24 Christiaan C. Stolk

In this paper, we first propose and analyze a novel mixed-type DG method for the coupled Stokes-Darcy problem on simplicial meshes. The proposed formulation is locally conservative. A mixed-type DG method in conjunction with the…

Numerical Analysis · Mathematics 2021-10-01 Lina Zhao

Accurately simulating wave propagation is crucial in fields such as acoustics, electromagnetism, and seismic analysis. Traditional numerical methods, like finite difference and finite element approaches, are widely used to solve governing…

Numerical Analysis · Mathematics 2026-02-05 Victorita Dolean , Daria Hrebenshchykova , Stéphane Lanteri , Victor Michel-Dansac
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