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Modelling of 2D steady flow fields with artificial neural networks and integration of physical knowledge

机译:利用人工神经网络对二维稳态流场进行建模并整合物理知识

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摘要

The application of artificial neural networks (ANN) for the prediction of twodimensional steady pour fields is described. It could be shown that a properly trained ANN is able to predict whether wakes in a bodies outflow form or not, depending on the Reynolds number. As the no-slip condition on the bodies surface was not learned correctly, two possibilities to integrate a priori knowledge were investigated and proved to be suitable. [References: 4]
机译:描述了人工神经网络(ANN)在二维稳定倾注场预测中的应用。可以证明,受过适当训练的人工神经网络能够根据雷诺数来预测是否以身体流出的形式进行苏醒。由于没有正确学习身体表面的防滑条件,因此研究了整合先验知识的两种可能性,并证明了它们是合适的。 [参考:4]

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