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The dynamic mode decomposition (DMD) is a data-driven approach that extracts the dominant features from spatiotemporal data. In this work, we introduce sparse-mode DMD, a new variant of the optimized DMD framework that specifically…

Machine Learning · Statistics 2025-07-29 Sara M. Ichinaga , Steven L. Brunton , Aleksandr Y. Aravkin , J. Nathan Kutz

We propose a domain-decomposition pore-network method (DD-PNM) for modeling single-phase Stokes flow in porous media. The method combines the accuracy of finite-element discretizations on body-fitted meshes within pore subdomains with a…

Numerical Analysis · Mathematics 2026-01-06 Shuyu Sun , Zhangchengrui Wang , Lei Zhang , Jijing Zhao

The increasing complexity and scale of photonic and electromagnetic devices demand efficient and accurate numerical solvers. In this work, we develop a parallel overlapping domain decomposition method (DDM) based on the finite-difference…

Optics · Physics 2025-09-26 Zhanwen Wang , Chengnian Huang , Wangtao Lu , Yuntian Chen , Wei E. I. Sha

In the present work, a new methodology is proposed for building surrogate parametric models of engineering systems based on modular assembly of pre-solved modules. Each module is a generic parametric solution considering parametric…

Computational Engineering, Finance, and Science · Computer Science 2024-03-15 Angelo Pasquale , Mohammad-Javad Kazemzadeh-Parsi , Daniele Di Lorenzo , Victor Champaney , Amine Ammar , Francisco Chinesta

We develop non-overlapping domain decomposition methods for the Biot system of poroelasticity in a mixed form. The solid deformation is modeled with a mixed three-field formulation with weak stress symmetry. The fluid flow is modeled with a…

Numerical Analysis · Mathematics 2021-08-04 Manu Jayadharan , Eldar Khattatov , Ivan Yotov

Dynamic mode decomposition (DMD) provides a principled approach to extract physically interpretable spatial modes from time-resolved flow field data, along with a linear model for how the amplitudes of these modes evolve in time. Recently,…

Fluid Dynamics · Physics 2020-07-29 Aditya G. Nair , Benjamin Strom , Bingni W. Brunton , Steven L. Brunton

Numerical algorithms for solving problems of mathematical physics on modern parallel computers employ various domain decomposition techniques. Domain decomposition schemes are developed here to solve numerically initial/boundary value…

Numerical Analysis · Computer Science 2011-02-04 Petr N. Vabishchevich

This paper is concerned with the numerical solution of compressible fluid flow in a fractured porous medium. The fracture represents a fast pathway (i.e., with high permeability) and is modeled as a hypersurface embedded in the porous…

Numerical Analysis · Mathematics 2022-02-15 Phuoc-Toan Huynh , Yanzhao Cao , Thi-Thao-Phuong Hoang

Solving the linear elasticity and Stokes equations by an optimal domain decomposition method derived algebraically involves the use of non standard interface conditions. The one-level domain decomposition preconditioners are based on the…

Numerical Analysis · Mathematics 2018-04-23 Gabriel R. Barrenechea , Michał Bosy , Victorita Dolean

The Stokes equations play an important role in the incompressible flow simulation. In this paper, a novel divergence-free parametric mixed finite element method is proposed for solving three-dimensional Stokes equations on domains with…

Numerical Analysis · Mathematics 2025-12-19 Lingxiao Li , Haiyan Su , He Zhang , Weiying Zheng

In this paper, a parallel domain decomposition method is proposed for solving the fully-mixed Stokes-dual-permeability fluid flow model with Beavers-Joseph (BJ) interface conditions. Three Robin-type boundary conditions and a modified weak…

Numerical Analysis · Mathematics 2022-06-14 Zheng Li , Feng Shi , Yizhong Sun , Haibiao Zheng

The aim of this paper is to propose a systematic way to obtain convergent finite element schemes for the Darcy-Stokes flow problem by combining well-known mixed finite elements that are separately convergent for Darcy and Stokes problems.…

Numerical Analysis · Mathematics 2012-03-22 Antonio Márquez , Salim Meddahi , Francisco-Javier Sayas

We introduce a new overlapping Domain Decomposition Method (DDM) to solve the fully nonlinear Monge-Amp\`ere equation. While DDMs have been extensively studied for linear problems, their application to fully nonlinear partial differential…

Numerical Analysis · Mathematics 2023-06-05 Yassine Boubendir , Jake Brusca , Brittany Froese Hamfeldt , Tadanaga Takahashi

In this work, we propose a new stochastic domain decomposition method for solving steady-state partial differential equations (PDEs) with random inputs. Based on the efficiency of the Variable-separation (VS) method in simulating stochastic…

Numerical Analysis · Mathematics 2025-02-06 Liang Chen , Yaru Chen , Qiuqi Li , Zhiwen Zhang

The aim of this work is to present a model reduction technique in the framework of optimal control problems for partial differential equations. We combine two approaches used for reducing the computational cost of the mathematical numerical…

Numerical Analysis · Mathematics 2023-11-09 Ivan Prusak , Monica Nonino , Davide Torlo , Francesco Ballarin , Gianluigi Rozza

We introduce an extended discontinuous Galerkin discretization of hyperbolic-parabolic problems on multidimensional semi-infinite domains. Building on previous work on the one-dimensional case, we split the strip-shaped computational domain…

Numerical Analysis · Mathematics 2023-09-01 Federico Vismara , Tommaso Benacchio

We present a component-based model order reduction procedure to efficiently and accurately solve parameterized incompressible flows governed by the Navier-Stokes equations. Our approach leverages a non-overlapping optimization-based domain…

Numerical Analysis · Mathematics 2023-11-01 Tommaso Taddei , Xuejun Xu , Lei Zhang

Three algorithms are developed for uncertainty quantification in modeling coupled Stokes and Darcy flows. The porous media may consist of multiple regions with different properties. The permeability is modeled as a non-stationary stochastic…

Numerical Analysis · Mathematics 2019-03-05 Ilona Ambartsumyan , Eldar Khattatov , ChangQing Wang , Ivan Yotov

Domain decomposition methods (DDMs) provide a unifying framework for the scalable numerical solution of partial differential equations. Originating from Schwarz's alternating method, they have evolved into a rich family of algorithms that…

Numerical Analysis · Mathematics 2026-05-26 Victorita Dolean , Pierre Jolivet , Frédéric Nataf , Pierre-Henri Tournier

Numerical solutions of partial differential equations (PDEs) require expensive simulations, limiting their application in design optimization, model-based control, and large-scale inverse problems. Surrogate modeling techniques seek to…

Computational Physics · Physics 2022-05-18 James Duvall , Karthik Duraisamy , Shaowu Pan