A high order cut-cell method for solving the shallow-shelf equations

IF 3.1 3区 计算机科学 Q2 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS Journal of Computational Science Pub Date : 2024-05-21 DOI:10.1016/j.jocs.2024.102319
Will Thacher , Hans Johansen , Daniel Martin
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Abstract

In this paper we present a novel method for solving the shallow-shelf equations in the presence of grounding lines. The shallow-self equations are a two-dimensional system of nonlinear elliptic PDEs with variable coefficients that are discontinuous across the grounding line, which we treat as a sharp interface between grounded and floating ice. The grounding line is “reconstructed” from ice thickness and basal topography data to provide necessary geometric information for our cut-cell, finite volume discretization. Our discretization enforces jump conditions across the grounding line and achieves high-order accuracy using stencils constructed with a weighted least-squares method. We demonstrate second and fourth order convergence of the velocity field, driving stress, and reconstructed geometric information.

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求解浅层方程的高阶切割单元法
在本文中,我们提出了一种解决存在接地线情况下浅自方程的新方法。浅自方程是一个二维非线性椭圆 PDEs 系统,其系数可变,在接地线上不连续,我们将接地线视为接地冰与浮冰之间的尖锐界面。接地线是根据冰层厚度和基底地形数据 "重建 "的,为我们的切割单元有限体积离散化提供了必要的几何信息。我们的离散化方法在整个接地线上强制执行跳跃条件,并利用加权最小二乘法构建的模版实现了高阶精度。我们证明了速度场、驱动应力和重建几何信息的二阶和四阶收敛性。
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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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