参考解数值方法精度的比较评价

Q4 Computer Science
A.E. Bondarev, A.E. Kuvshinnikov
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引用次数: 0

摘要

当在数学建模的帮助下组织气体动力学计算问题的大量实际解决方案时,关于所使用的数值方法的相对准确性的信息现在越来越需要。通常,计算器不仅需要问题的特定气体动力学参数(特征马赫数、雷诺数等)组合的信息,而且需要这些参数在一定范围内的变化信息。这项工作提出了数值研究致力于数值方法的精度的比较评估与参考解决方案的一些问题。用各种数值方法对特征数范围进行了这些问题的计算。将所得结果与参考解进行了比较,从而可以估计每种数值方法的误差。利用广义计算实验的构造进行了计算。广义计算实验是将数学建模问题的解决、并行技术和可视化分析技术相结合的一种计算技术。广义计算实验的结果是多维数组,其中数组的维数对应于定义参数。对所得结果的分析和可视化表示提供了关于所选问题的数值方法的相对准确性的信息。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Comparative Evaluation of the Accuracy of Numerical Methods on Reference Solutions
When organizing a mass practical solution of computational problems of gas dynamics with the help of mathematical modeling, information on the comparative accuracy of the numerical methods used is now increasingly in demand. As a rule, calculators need information not only for a particular combination of the defining gas-dynamic parameters of the problem (characteristic Mach, Reynolds numbers, etc.), but also for the variation of these parameters in certain ranges. This work presents numerical studies devoted to a comparative assessment of the accuracy of numerical methods for a number of problems with reference solutions. The calculation of these problems is carried out for ranges of characteristic numbers using various numerical methods. The results obtained are compared with the reference solution and make it possible to estimate the error for each of the numerical methods. Calculations are carried out using the construction of a generalized computational experiment. A generalized computational experiment is a computational technology that combines the solution of mathematical modeling problems, parallel technologies and visual analytics technologies. The results of the generalized computational experiment are multidimensional arrays, where the dimension of the arrays corresponds to the defining parameters. Analysis and visual representation of the obtained results provide information on the comparative accuracy of the numerical method for the selected class of problems.
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来源期刊
Scientific Visualization
Scientific Visualization Computer Science-Computer Vision and Pattern Recognition
CiteScore
1.30
自引率
0.00%
发文量
20
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