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This work proposes an efficient space-time two-grid compact difference (ST-TGCD) scheme for solving the two-dimensional (2D) viscous Burgers' equation subject to initial and periodic boundary conditions. The proposed approach combines a…

Numerical Analysis · Mathematics 2025-10-20 Xiangyi Peng , Lisen Ding , Wenlin Qiu

With the aim of efficiently simulating three-dimensional multiphase turbulent flows with a phase-field method, we propose a new discretization scheme for the biharmonic term (the 4th-order derivative term) of the Cahn-Hilliard equation.…

Fluid Dynamics · Physics 2022-05-24 Hao-Ran Liu , Chong Shen Ng , Kai Leong Chong , Detlef Lohse , Roberto Verzicco

We consider geometric multigrid methods for the solution of linear systems arising from isogeometric discretizations of elliptic partial differential equations. For classical finite elements, such methods are well known to be fast solvers…

Numerical Analysis · Mathematics 2017-05-16 Clemens Hofreither , Stefan Takacs , Walter Zulehner

We present an explicit solver of the three-dimensional screened and unscreened Poisson's equation which combines accuracy, computational efficiency and versatility. The solver, based on a mixed plane-wave / interpolating scaling function…

Materials Science · Physics 2013-03-27 Alessandro Cerioni , Luigi Genovese , Alessandro Mirone , Vicente Armando Sole

Finite difference methods (FDMs) are widely used for solving partial differential equations (PDEs) due to their relatively simple implementation. However, they face significant challenges when applied to non-rectangular domains and in…

Numerical Analysis · Mathematics 2025-07-08 Bin Han , Jiwoon Sim

The conjugate gradient (CG) method is an efficient iterative method for solving large-scale strongly convex quadratic programming (QP). In this paper we propose some generalized CG (GCG) methods for solving the $\ell_1$-regularized…

Optimization and Control · Mathematics 2016-02-15 Zhaosong Lu , Xiaojun Chen

We propose a high-order FDTD scheme based on the correction function method (CFM) to treat interfaces with complex geometry without increasing the complexity of the numerical approach for constant coefficients. Correction functions are…

Numerical Analysis · Mathematics 2020-02-18 Yann-Meing Law , Alexandre Noll Marques , Jean-Christophe Nave

For over a century, extrapolation methods have provided a powerful tool to improve the convergence order of a numerical method. However, these tools are not well-suited to modern computer codes, where multiple continua are discretised and…

The article proposes a Caputo fractional conjugate gradient (CFCG) method for unconstrained optimization problems which is applicable to smooth as well as non-smooth problmes. The proposed method uses a non-adaptive version of the Caputo…

Optimization and Control · Mathematics 2025-12-22 Barsha Shawa , Md Abu Talhamainuddin Ansary

In this work, an efficient blackbox-type multigrid method is proposed for solving multipoint flux approximations of the Darcy problem on logically rectangular grids. The approach is based on a cell-centered multigrid algorithm, which…

Numerical Analysis · Mathematics 2024-02-13 Andrés Arrarás , Francisco J. Gaspar , Laura Portero , Carmen Rodrigo

In this article, we have developed a higher order compact numerical method for variable coefficient parabolic problems with mixed derivatives. The finite difference scheme, presented here for two-dimensional domains, is based on fourth…

Numerical Analysis · Mathematics 2013-12-19 Shuvam Sen

Due to its optimal complexity, the multigrid (MG) method is one of the most popular approaches for solving large-scale linear systems arising from the discretization of partial differential equations. However, the parallel implementation of…

Numerical Analysis · Mathematics 2025-02-27 Hardik Kothari , Maria Giuseppina Chiara Nestola , Marco Favino , Rolf Krause

In this paper, we introduce a novel category of central compact schemes inspired by existing cell-node and cell-centered compact finite difference schemes, that offer a superior spectral resolution for solving the dispersive wave equation.…

Numerical Analysis · Mathematics 2024-05-03 Lavanya V Salian , Samala Rathan , Debojyoti Ghosh

An improved finite difference method with compact correction term is proposed to solve the Poisson equations. The compact correction term is developed by a coupled high-order compact and low-order classical finite difference formulations.…

Numerical Analysis · Mathematics 2016-08-31 Kun Zhang , Liangbi Wang , Yuwen Zhang

Coarse grid projection (CGP) is a multiresolution technique for accelerating numerical calculations associated with a set of nonlinear evolutionary equations along with the stiff Poisson equations. In this article we use CGP for the first…

Computational Physics · Physics 2020-03-03 Ali Kashefi

In recent publications, the author and his coworkers have proposed a multigrid method for solving linear systems arizing from the discretization of partial differential equations in isogeometric analysis and have proven that the convergence…

Numerical Analysis · Mathematics 2021-03-05 Stefan Takacs

For uncertainty propagation of highly complex and/or nonlinear problems, one must resort to sample-based non-intrusive approaches [1]. In such cases, minimizing the number of function evaluations required to evaluate the response surface is…

Numerical Analysis · Mathematics 2017-12-04 Anindya Bhaduri , Lori Graham-Brady

We propose some multigrid methods for solving the algebraic systems resulting from finite element approximations of space fractional partial differential equations (SFPDEs). It is shown that our multigrid methods are optimal, which means…

Numerical Analysis · Mathematics 2018-07-27 Yingjun Jiang , Xuejun Xu

A finite element method for solving nonlinear differential equations on a grid, with potential applicability to computational fluid dynamics (CFD), is developed and tested. The current method facilitates the computation of solutions of a…

Computational Physics · Physics 2014-09-04 Jesper Tveit

Tensor decomposition has been widely used in machine learning and high-volume data analysis. However, large-scale tensor factorization often consumes huge memory and computing cost. Meanwhile, modernized computing hardware such as tensor…

Optimization and Control · Mathematics 2022-09-12 Zi Yang , Junnan Shan , Zheng Zhang