Fast IIF–WENO Method on Non-uniform Meshes for Nonlinear Space-Fractional Convection–Diffusion–Reaction Equations

被引:0
作者
Huan-Yan Jian
Ting-Zhu Huang
Alexander Ostermann
Xian-Ming Gu
Yong-Liang Zhao
机构
[1] Southwest Minzu University,School of Computer Science and Engineering
[2] University of Electronic Science and Technology of China,School of Mathematical Sciences
[3] University of Innsbruck,Department of Mathematics
[4] Southwestern University of Finance and Economics,Institute of Mathematics, School of Economic Mathematics
来源
Journal of Scientific Computing | 2021年 / 89卷
关键词
Convection–diffusion–reaction equations; Riesz fractional derivative; Implicit integration factor methods; Weighted essentially non-oscillatory methods; Adaptive restarting Krylov subspace method;
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摘要
In this article, our goal is to establish fast and efficient numerical methods for nonlinear space-fractional convection–diffusion–reaction (CDR) equations in the 1, 2, and 3 dimensions. For the spatial discretization of the CDR equations, the weighted essentially non-oscillatory (WENO) scheme is used to approximate the convection term, and the fractional centered difference formula is applied to deal with the diffusion term. As a result, a nonlinear system of ordinary differential equations (ODEs) is derived. Since implicit integration factor (IIF) methods are a class of time-stepping schemes with good robustness and stability, the second order IIF–WENO scheme on non-uniform meshes in Jiang and Zhang (J Comput Phys 253:368–388, 2013) is applied to solve the nonlinear ODEs system. In order to obtain an efficient implementation of the IIF–WENO scheme, we propose an adaptive restarting Krylov subspace method to compute the action of matrix exponentials arising in IIF–WENO. Numerical examples are presented to confirm the validity of the IIF–WENO scheme, and to verify that the proposed fast solution algorithm is extremely attractive in terms of computational complexity and memory storage.
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[1]  
Jiang T(2013)Krylov implicit integration factor WENO methods for semilinear and fully nonlinear advection-diffusion-reaction equations J. Comput. Phys. 253 368-388
[2]  
Zhang Y-T(2005)Polymerase chain reaction in natural convection systems: a convection-diffusion-reaction model Europhys. Lett. 71 1008-1014
[3]  
Yariv E(2020)Personalized image-based tumor growth prediction in a convection-diffusion-reaction model Acta Neurol. Belg. 120 49-57
[4]  
Ben-Dov G(2000)An implicit scheme for solving the convection-diffusion-reaction equation in two dimensions J. Comput. Phys. 164 123-142
[5]  
Dorfman KD(1999)An advection-diffusion-reaction model for the estimation of fish movement parameters from tagging data, with application to skipjack tuna (Katsuwonus pelamis) Can. J. Fish. Aquat. Sci. 56 925-938
[6]  
Meghdadi N(2018)A difference scheme for a degenerating convection-diffusion-reaction system modelling continuous sedimentation, ESAIM: Math Model. Numer. Anal. 52 365-392
[7]  
Soltani M(2018)A novel meshless method for fully nonlinear advection-diffusion-reaction problems to model transfer in anisotropic media Appl. Math. Comput. 339 459-476
[8]  
Niroomand-Oscuii H(2008)Finite element methods for time-dependent convection-diffusion-reaction equations with small diffusion Comput. Methods Appl. Mech. Engrg. 198 475-494
[9]  
Yamani N(2015)Finite difference approximations of multidimensional unsteady convection-diffusion-reaction equations J. Comput. Phys. 285 331-349
[10]  
Sheu TW(2017)Fast iterative method with a second-order implicit difference scheme for time-space fractional convection-diffusion equation J. Sci. Comput. 72 957-985