三维黎曼问题的流场数据

IF 1 Q3 MULTIDISCIPLINARY SCIENCES
Nils Hoppe , Nico Fleischmann , Benedikt Biller , Stefan Adami , Nikolaus A. Adams
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引用次数: 0

摘要

可压缩流求解器的常见验证和核查测试案例只有一维或二维。然而,这种流动本质上是三维的。所提供的数据包含使用开源可压缩流求解器 ALPACA 计算的真正三维黎曼问题的模拟结果。问题的设计使每个八分之一的恒定初始状态只通过一个基本波连接两个相邻状态。因此,初始条件的选择可产生三维效应。此外,还设计了一些案例来触发可压缩流动求解器的常见缺陷,如假压力振荡、非物理对称性破坏或冲击扰动的发生。这些案例是使用带有 HLLC 和 Roe Riemann 求解器以及五阶 WENO 重建的有限体积方案进行模拟的。模拟在一个计算集群的 300 多个内核上进行。除了原始二进制流场数据外,还提供了输入文件、后处理脚本和可视化效果。所提供的文件便于使用不同的求解器设置和模拟相应的情况,并可对所获得的结果进行定量比较。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Flow field data of three-dimensional Riemann problems

Common validation and verification test cases for compressible flow solvers are only one- or two-dimensional. Such flows, however, are inherently three-dimensional. The provided data contains simulation results of genuine three-dimensional Riemann problems computed with the open-source compressible flow solver ALPACA. The problems are designed so that each octant's constant initial state connects two neighboring states by only one elementary wave each. Thereby, initial conditions are chosen to induce three-dimensional effects. Furthermore, the cases are designed to trigger common shortcomings of compressible flow solvers, such as spurious pressure oscillations, unphysical symmetry breaking, or the onset of shock disturbances. The cases were simulated using a finite-volume scheme with HLLC and Roe Riemann solvers and fifth-order WENO reconstruction. The simulations were conducted on over 300 cores of a compute cluster. Besides the raw binary flow field data, input files are provided next to post-processing scripts and the visualizations obtained by them. The provided files ease setting up and simulating the respective cases with different solvers and allow quantitative comparisons of the obtained results.

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来源期刊
Data in Brief
Data in Brief MULTIDISCIPLINARY SCIENCES-
CiteScore
3.10
自引率
0.00%
发文量
996
审稿时长
70 days
期刊介绍: Data in Brief provides a way for researchers to easily share and reuse each other''s datasets by publishing data articles that: -Thoroughly describe your data, facilitating reproducibility. -Make your data, which is often buried in supplementary material, easier to find. -Increase traffic towards associated research articles and data, leading to more citations. -Open up doors for new collaborations. Because you never know what data will be useful to someone else, Data in Brief welcomes submissions that describe data from all research areas.
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