Premium
A parallel finite volume scheme preserving positivity for diffusion equation on distorted meshes
Author(s) -
Sheng Zhiqiang,
Yue Jingyan,
Yuan Guangwei
Publication year - 2017
Publication title -
numerical methods for partial differential equations
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.901
H-Index - 61
eISSN - 1098-2426
pISSN - 0749-159X
DOI - 10.1002/num.22185
Subject(s) - domain decomposition methods , finite volume method , polygon mesh , mathematics , interface (matter) , scheme (mathematics) , domain (mathematical analysis) , speedup , partial differential equation , diffusion , stability (learning theory) , computer science , finite element method , parallel computing , mathematical analysis , geometry , physics , bubble , maximum bubble pressure method , machine learning , mechanics , thermodynamics
Parallel domain decomposition methods are natural and efficient for solving the implicity schemes of diffusion equations on massive parallel computer systems. A finite volume scheme preserving positivity is essential for getting accurate numerical solutions of diffusion equations and ensuring the numerical solutions with physical meaning. We call their combination as a parallel finite volume scheme preserving positivity, and construct such a scheme for diffusion equation on distorted meshes. The basic procedure of constructing the parallel finite volume scheme is based on the domain decomposition method with the prediction‐correction technique at the interface of subdomains: First, we predict the values on each inner interface of subdomains partitioned by the domain decomposition. Second, we compute the values in each subdomain using a finite volume scheme preserving positivity. Third, we correct the values on each inner interface using the finite volume scheme preserving positivity. The resulting scheme has intrinsic parallelism, and needs only local communication among neighboring processors. Numerical results are presented to show the performance of our schemes, such as accuracy, stability, positivity, and parallel speedup.© 2017 Wiley Periodicals, Inc. Numer Methods Partial Differential Eq 33: 2159–2178, 2017