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We present a non-conforming least squares method for approximating solutions of second order elliptic problems with discontinuous coefficients. The method is based on a general Saddle Point Least Squares (SPLS) method introduced in previous…

Numerical Analysis · Mathematics 2019-04-01 Constantin Bacuta , Jacob Jacavage

High-velocity fluid flow through porous media is modeled by prescribing a nonlinear relationship between the flow rate and the pressure gradient, called the Darcy--Forchheimer equation. This paper is concerned with the analysis of parallel…

Numerical Analysis · Mathematics 2026-04-03 Jongho Park , S. Majid Hassanizadeh

A domain decomposition method for the solution of general variable-coefficient elliptic partial differential equations on regular domains is introduced. The method is based on tessellating the domain into overlapping thin slabs or shells,…

Numerical Analysis · Mathematics 2025-10-31 Simon Dirckx , Anna Yesypenko , Per-Gunnar Martinsson

We propose an efficient algorithm that combines overlapping domain decomposition and proper generalized decomposition (PGD) to construct surrogate models of linear elliptic parametric problems. The technique is composed of an offline and an…

Numerical Analysis · Mathematics 2024-09-16 Marco Discacciati , Ben J. Evans , Matteo Giacomini

We study a natural alternating method of Schwarz type (domain decomposition) for certain class of couplings between local and nonlocal operators. We show that our method fits into Lion's framework and prove, as a consequence, convergence in…

Numerical Analysis · Mathematics 2022-12-13 Gabriel Acosta , Francisco M. Bersetche , Julio D. Rossi

A multiscale numerical method is proposed for the solution of semi-linear elliptic stochastic partial differential equations with localized uncertainties and non-linearities, the uncertainties being modeled by a set of random parameters. It…

Numerical Analysis · Mathematics 2019-01-23 Anthony Nouy , Florent Pled

Physics-informed neural networks (PINNs) are appealing data-driven tools for solving and inferring solutions to nonlinear partial differential equations (PDEs). Unlike traditional neural networks (NNs), which train only on solution data, a…

Numerical Analysis · Mathematics 2023-11-02 Will Snyder , Irina Tezaur , Christopher Wentland

Accelerating iterative eigenvalue algorithms is often achieved by employing a spectral shifting strategy. Unfortunately, improved shifting typically leads to a smaller eigenvalue for the resulting shifted operator, which in turn results in…

Numerical Analysis · Mathematics 2024-10-10 Lambert Theisen , Benjamin Stamm

By applying a simple symmetry reduction on a two-layer liquid model, a nonlocal counterpart of it is obtained. Then a general form of nonlocal nonlinear Schrodinger (NNLS) equation with shifted parity, charge-conjugate and delayed time…

Exactly Solvable and Integrable Systems · Physics 2019-03-05 Xi-Zhong Liu

We prove linear convergence for a new family of modified Dirichlet--Neumann methods applied to quasilinear parabolic equations, as well as the convergence of the Robin--Robin method. Such nonoverlapping domain decomposition methods are…

Numerical Analysis · Mathematics 2023-08-30 Emil Engström , Eskil Hansen

In the following paper, we present a consistent Newton-Schur solution approach for variational multiscale formulations of the time-dependent Navier-Stokes equations in three dimensions. The main contributions of this work are a systematic…

Numerical Analysis · Mathematics 2008-09-30 D. Z. Turner , K. B. Nakshatrala , K. D. Hjelmstad

In this paper we want to propose practical numerical methods to solve a class of initial-boundary problem of time-space fractional convection-diffusion equations (TSFCDEs). To start with, an implicit difference method based on two-sided…

Numerical Analysis · Mathematics 2021-07-26 Xian-Ming Gu , Ting-Zhu Huang , Cui-Cui Ji , Bruno Carpentieri , Anatoly A. Alikhanov

In this work we propose upscaling method for nonlinear Forchheimer flow in highly heterogeneous porous media. The generalized Forchheimer law is considered for incompressible and slightly-compressible single-phase flows. We use recently…

Numerical Analysis · Mathematics 2015-06-15 Eugenio Aulisa , Lidia Bloshanskaya , Yalchin Efendiev , Akif Ibragimov

A new penalty-free neural network method, PFNN-2, is presented for solving partial differential equations, which is a subsequent improvement of our previously proposed PFNN method [1]. PFNN-2 inherits all advantages of PFNN in handling the…

Numerical Analysis · Mathematics 2022-05-03 Hailong Sheng , Chao Yang

We study the applicability of the derivative nonlinear Schr\"{o}dinger (DNLS) equation, for the evolution of high frequency nonlinear waves, observed at the foreshock region of the terrestrial quasi-parallel bow shock. The use of a…

Plasma Physics · Physics 2016-12-07 B. Hnat , D. Y. Kolotkov , D. O'Connell , V. M. Nakariakov , G. Rowlands

Pricing American options is more complicated than pricing European options, because they can be exercised at any time, and one thus needs to solve a linear complementarity problem instead of simply doing time stepping for computing European…

Numerical Analysis · Mathematics 2026-05-22 Martin J. Gande , Si-Wei Liao , Liu-Di Lu

The multigroup neutron transport criticality calculations using modern supercomputers have been widely employed in a nuclear reactor analysis for studying whether or not a system is self-sustaining. However, the design and development of…

Numerical Analysis · Mathematics 2020-02-19 Fande Kong

We deal with the numerical solution of linear elliptic problems with varying diffusion coefficient by the $hp$-discontinuous Galerkin method. We develop a two-level hybrid Schwarz preconditioner for the arising linear algebraic systems. The…

Numerical Analysis · Mathematics 2025-09-19 Vit Dolejsi , Tomas Hammerbauer

Domain decomposition methods are widely used and effective in the approximation of solutions to partial differential equations. Yet the optimal construction of these methods requires tedious analysis and is often available only in…

Machine Learning · Computer Science 2022-10-19 Ali Taghibakhshi , Nicolas Nytko , Tareq Zaman , Scott MacLachlan , Luke Olson , Matthew West

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