Black-Box Solver for Numerical Simulations and Mathematical Modelling in Engineering Physics

Sergey I. Martynenko () and Aleksey Yu. Varaksin
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Sergey I. Martynenko: Joint Institute for High Temperatures of the Russian Academy of Sciences, Moscow 125412, Russia
Aleksey Yu. Varaksin: Joint Institute for High Temperatures of the Russian Academy of Sciences, Moscow 125412, Russia

Mathematics, 2023, vol. 11, issue 16, 1-21

Abstract: This article presents a two-grid approach for developing a black-box iterative solver for a large class of real-life problems in continuum mechanics (heat and mass transfer, fluid dynamics, elasticity, electromagnetism, and others). The main requirements on this (non-)linear black-box solver are: (1) robustness (the lowest number of problem-dependent components), (2) efficiency (close-to-optimal algorithmic complexity), and (3) parallelism (a parallel robust algorithm should be faster than the fastest sequential one). The basic idea is to use the auxiliary structured grid for more computational work, where (non-)linear problems are simpler to solve and to parallelize, i.e., to combine the advantages of unstructured and structured grids: simplicity of generation in complex domain geometry and opportunity to solve (non-)linear (initial-)boundary value problems by using the Robust Multigrid Technique. Topics covered include the description of the two-grid algorithm and estimation of their robustness, convergence, algorithmic complexity, and parallelism. Further development of modern software for solving real-life problems justifies relevance of the research. The proposed two-grid algorithm can be used in black-box parallel software for the reduction in the execution time in solving (initial-)boundary value problems.

Keywords: mathematical modelling; parallel; high-performance and multigrid computing; black-box software; multiphysics simulation; real-life problems (search for similar items in EconPapers)
JEL-codes: C (search for similar items in EconPapers)
Date: 2023
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