A modified cell-centered nodal integral scheme for the convection-diffusion equation

IF 3.1 3区 计算机科学 Q2 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS Journal of Computational Science Pub Date : 2024-05-11 DOI:10.1016/j.jocs.2024.102320
Nadeem Ahmed, Suneet Singh
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Abstract

The nodal integral methods (NIMs) are very efficient and accurate coarse-mesh methods for solving partial differential equations. The cell-centered NIM (CCNIM) is a simplified variant of the NIMs that has recently shown its efficiency in solving fluid flow problems but has been hampered by issues such as inapplicability to one-dimensional problems, complexities in handling Neumann boundary conditions and the formulation of a system of differential-algebraic equations (DAEs) for discrete unknowns. Here, we present a modified version of the CCNIM designed to overcome the challenges associated with its previous version. Our novel development retains the essence of CCNIM while resolving these issues. The proposed scheme, grounded in the nodal framework, achieves second-order accuracy in both spatial and temporal dimensions. Unlike its precursor, the proposed method formulates algebraic equations for discrete variables per node, eliminating the cumbersome DAE system. Neumann boundary conditions are seamlessly incorporated through a straightforward flux definition, and applicability to one-dimensional problems is now feasible. We successfully apply our approach to one and two-dimensional convection-diffusion problems with known analytical solutions to validate our approach. The simplicity and robustness of the approach lay the foundation for its seamless extension to more complex fluid flow problems.

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对流扩散方程的修正单元中心节点积分方案
节点积分法(NIM)是求解偏微分方程的高效、精确的粗网格方法。以单元为中心的节点积分法(CCNIM)是节点积分法的简化变体,最近在求解流体流动问题时显示出其高效性,但由于不适用于一维问题、处理诺伊曼边界条件的复杂性以及离散未知数的微分代数方程(DAE)系统的表述等问题而受到阻碍。在此,我们提出了 CCNIM 的改进版,旨在克服其先前版本所面临的挑战。我们的创新发展保留了 CCNIM 的精髓,同时解决了这些问题。所提出的方案以节点框架为基础,在空间和时间维度上都达到了二阶精度。与前者不同的是,所提出的方法为每个节点的离散变量制定了代数方程,消除了繁琐的 DAE 系统。通过直观的通量定义,新曼边界条件被无缝纳入,并且适用于一维问题。我们成功地将我们的方法应用于已知分析解的一维和二维对流扩散问题,以验证我们的方法。该方法的简单性和稳健性为其无缝扩展到更复杂的流体流动问题奠定了基础。
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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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