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Nov, 2023
用于解决高马赫数流体流动问题的高效数据学习
Data-efficient operator learning for solving high Mach number fluid flow problems
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Noah Ford, Victor J. Leon, Honest Merman, Jeffrey Gilbert, Alexander New
TL;DR
使用SciML预测不规则几何体上的高Mach气体流动的解决方案问题，并通过学习行为模式基础从数据中进行预测的Neural Basis Functions模型，在低数据情况下表现更加有效，同时识别了该类型问题中持续存在的挑战。
Abstract
We consider the problem of using
sciml
to predict solutions of
high mach fluid flows
over
irregular geometries
. In this setting, data is l
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