Order-lifted data inversion/retrieval method of neighbor cells to implement general high-order schemes in unstructured-mesh-based finite-volume solution framework

IF 3.8 2区 物理与天体物理 Q2 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS Journal of Computational Physics Pub Date : 2025-03-01 Epub Date: 2025-01-10 DOI:10.1016/j.jcp.2025.113735
Hao Guo, Boxing Hu, Peixue Jiang, Xiaofeng Ma, Yinhai Zhu
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Abstract

This study introduces an order-lifted inversion/retrieval method for implementing high-order schemes within the framework of an unstructured-mesh-based finite-volume method. This method defines a special representation called the data order-lifted inversion of neighbor cells (DOLINC) differential, which transforms the degrees of freedom of wide templates into differentials of various orders stored in local grid cells. Furthermore, to retrieve the original far-field information without bias during the reconstruction/interpolation of face values, the corresponding accurate inversion formulas are derived based on the defined DOLINC differentials. The order-lifted inversion method can be applied to multi-dimensional polyhedral-mesh solvers by considering the influence of grid non-uniformity on high-order schemes. It seamlessly accommodates multi-process parallel computing for high-order methods without requiring special consideration for the boundary interface. This method not only enhances the numerical accuracy of second-order finite-volume methods, but also demonstrates a significant computational-speed advantage over similar methods. A series of benchmark cases, including the linear advection, Burgers, and Euler equations, are comprehensively validated to assess the practical performance of the method. The results indicate that the unstructured-mesh high-order schemes implemented based on this method achieve theoretical accuracy in practical computations and substantially reduce computational costs compared with methods that increase grid resolution.
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在基于非结构网格的有限体积解框架中,邻元的升序数据反演/检索方法实现了一般的高阶方案
本文介绍了一种在基于非结构化网格的有限体积法框架内实现高阶方案的提升阶反演/检索方法。该方法定义了一种特殊的表示形式,称为数据升序反转邻格(DOLINC)微分,它将宽模板的自由度转换为存储在局部网格单元中的各种阶数的微分。此外,为了在重建/插值过程中无偏差地获取原始远场信息,基于定义的DOLINC微分推导了相应的精确反演公式。考虑到网格不均匀性对高阶格式的影响,提升阶反演方法可以应用于多维多面体网格求解。它无缝地适应高阶方法的多进程并行计算,而不需要特别考虑边界接口。该方法不仅提高了二阶有限体积方法的数值精度,而且与同类方法相比,具有显著的计算速度优势。对线性平流、Burgers方程和Euler方程等一系列基准案例进行了全面验证,以评估该方法的实际性能。结果表明,与提高网格分辨率的方法相比,基于该方法实现的非结构化网格高阶格式在实际计算中达到了理论精度,大大降低了计算成本。
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来源期刊
Journal of Computational Physics
Journal of Computational Physics 物理-计算机:跨学科应用
CiteScore
7.60
自引率
14.60%
发文量
763
审稿时长
5.8 months
期刊介绍: Journal of Computational Physics thoroughly treats the computational aspects of physical problems, presenting techniques for the numerical solution of mathematical equations arising in all areas of physics. The journal seeks to emphasize methods that cross disciplinary boundaries. The Journal of Computational Physics also publishes short notes of 4 pages or less (including figures, tables, and references but excluding title pages). Letters to the Editor commenting on articles already published in this Journal will also be considered. Neither notes nor letters should have an abstract.
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