Decapodes:用于表示、组成和计算空间化偏微分方程的图解工具

IF 3.1 3区 计算机科学 Q2 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS Journal of Computational Science Pub Date : 2024-06-03 DOI:10.1016/j.jocs.2024.102345
Luke Morris , Andrew Baas , Jesus Arias , Maia Gatlin , Evan Patterson , James P. Fairbanks
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引用次数: 0

摘要

我们介绍的 Decapodes 是一种用于表示、组合和求解偏微分方程的图解工具。Decapodes 提供了方程系统中变量间关系的直观图解表示法、使用接线图操作数组合偏微分方程系统的方法,以及使用超图和字符串图推导求解器的算法。利用分类数据迁移、图形遍历和离散外部微积分技术,弦图又被编译成可执行程序。通过与 SU2 的基准比较,生成的求解器产生的数值解与最先进的开源工具一致。这些数值实验证明了这种多物理场仿真方法的可行性,并确定了需要进一步开发的领域。
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Decapodes: A diagrammatic tool for representing, composing, and computing spatialized partial differential equations

We present Decapodes, a diagrammatic tool for representing, composing, and solving partial differential equations. Decapodes provides an intuitive diagrammatic representation of the relationships between variables in a system of equations, a method for composing systems of partial differential equations using an operad of wiring diagrams, and an algorithm for deriving solvers using hypergraphs and string diagrams. The string diagrams are in turn compiled into executable programs using the techniques of categorical data migration, graph traversal, and the discrete exterior calculus. The generated solvers produce numerical solutions consistent with state-of-the-art open source tools as demonstrated by benchmark comparisons with SU2. These numerical experiments demonstrate the feasibility of this approach to multiphysics simulation and identify areas requiring further development.

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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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