三维稳定磁流体管道流动的变分多尺度无单元伽辽金方法

IF 3.7 3区 计算机科学 Q2 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS
Xiaohua Zhang , Yujie Fan
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引用次数: 0

摘要

磁流体动力学(MHD)在各个领域都有广泛的应用,因此研究三维(3D)磁流体动力学问题至关重要。对于MHD流动,当哈特曼(Ha)数较大时,会导致对流占主导地位,对流项克服扩散。在这种情况下,标准伽辽金方法无法抑制溶液中的非物理振荡,因为它们缺乏强对流的固有稳定机制。介绍了求解三维稳态MHD方程的变分多尺度无单元伽辽金法(VMEFG)。VMEFG方法继承了无单元伽辽金(EFG)方法的优点,避免了复杂的网格划分过程,这对复杂的三维问题尤其具有挑战性。此外,与EFG方法相比,该方法在处理对流占优问题时表现出更强的稳定性,并能自动生成稳定参数,优于其他稳定技术。为了验证VMEFG方法的数值稳定性和准确性,在立方、环立方、球面和环球形等不同区域进行了数值实验,并与EFG解和已有文献结果进行了比较。结果表明,VMEFG方法可以有效地避免数值振荡并保持高Ha数下三维MHD问题的稳定性,为这类问题提供了可靠、高效的解决方案。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
The variational multiscale element free Galerkin method for three-dimensional steady magnetohydrodynamics duct flows
Magnetohydrodynamics (MHD) has extensive applications in diverse fields, making the study of three-dimensional (3D) MHD problems crucial. For MHD flows, when the Hartmann (Ha) number is large, leading to a convection-dominated regime where convection terms overcome diffusion. In such scenarios, standard Galerkin methods fail to suppress non-physical oscillations in solutions, as they lack inherent stabilization mechanisms for strong convection. This paper introduces the variational multiscale element free Galerkin (VMEFG) method to solve 3D steady MHD equations. The VMEFG method inherits the advantage of the element free Galerkin (EFG) method in avoiding the complex meshing process, which is particularly challenging for complex 3D problems. Moreover, compared with the EFG method, it shows enhanced stability in dealing with convection-dominant problems and can automatically generate stabilized parameters, outperforming other stabilization techniques. To verify the numerical stability and accuracy of the VMEFG method, several numerical experiments on various domains including cubic, annular cubic, spherical, and annular spherical domains were conducted and compared with EFG solutions and existing literature results. The results indicate that the VMEFG method can effectively avoid numerical oscillations and maintain stability for 3D MHD problems at high Ha number, providing a reliable and efficient solution for such problems.
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来源期刊
Journal of Computational Science
Journal of Computational Science COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS-COMPUTER SCIENCE, THEORY & METHODS
CiteScore
5.50
自引率
3.00%
发文量
227
审稿时长
41 days
期刊介绍: Computational Science is a rapidly growing multi- and interdisciplinary field that uses advanced computing and data analysis to understand and solve complex problems. It has reached a level of predictive capability that now firmly complements the traditional pillars of experimentation and theory. The recent advances in experimental techniques such as detectors, on-line sensor networks and high-resolution imaging techniques, have opened up new windows into physical and biological processes at many levels of detail. The resulting data explosion allows for detailed data driven modeling and simulation. This new discipline in science combines computational thinking, modern computational methods, devices and collateral technologies to address problems far beyond the scope of traditional numerical methods. Computational science typically unifies three distinct elements: • Modeling, Algorithms and Simulations (e.g. numerical and non-numerical, discrete and continuous); • Software developed to solve science (e.g., biological, physical, and social), engineering, medicine, and humanities problems; • Computer and information science that develops and optimizes the advanced system hardware, software, networking, and data management components (e.g. problem solving environments).
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