纳维-斯托克斯方程的幂律滑移边界条件非连续 Galerkin 方案

IF 2.1 3区地球科学 Q3 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS Computational Geosciences Pub Date : 2023-12-29 DOI:10.1007/s10596-023-10265-8

J. K. Djoko, V. S. Konlack, T. Sayah

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引用次数: 0

摘要

本研究涉及几种非连续伽勒金（DG）方法的数值分析，用于解决具有幂律滑移边界条件的纳维-斯托克斯方程。与此问题相对应的物理背景是考虑位置和方向滑移边界条件时的流动描述。这项工作的主要目标是研究几种 DG 方法的可解性和收敛性，并讨论通过定点迭代算法解决这些问题的实际方法。理论研究结果得到了可靠的计算结果的支持。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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Power law slip boundary condition for Navier-Stokes equations: Discontinuous Galerkin schemes

This study deals with the numerical analysis of several discontinuous Galerkin (DG) methods for the resolution of the Navier-Stokes equations with power law slip boundary condition. The physical context corresponding to this problem is the description of a flow when a position and the direction slip boundary condition is taken into consideration. The main goal in this work is to examine the solvability, convergence of several DG methods, and to discuss their practical resolution by means of fixed point iterative algorithm. Theoretical findings are backed up by solid computational results.

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来源期刊

Computational Geosciences 地学-地球科学综合

CiteScore

6.10

自引率

4.00%

发文量

审稿时长

6-12 weeks

期刊介绍： Computational Geosciences publishes high quality papers on mathematical modeling, simulation, numerical analysis, and other computational aspects of the geosciences. In particular the journal is focused on advanced numerical methods for the simulation of subsurface flow and transport, and associated aspects such as discretization, gridding, upscaling, optimization, data assimilation, uncertainty assessment, and high performance parallel and grid computing. Papers treating similar topics but with applications to other fields in the geosciences, such as geomechanics, geophysics, oceanography, or meteorology, will also be considered. The journal provides a platform for interaction and multidisciplinary collaboration among diverse scientific groups, from both academia and industry, which share an interest in developing mathematical models and efficient algorithms for solving them, such as mathematicians, engineers, chemists, physicists, and geoscientists.