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An application of neural networks to the prediction of aerodynamic coefficients of aerofoils and wings

机译:神经网络在机翼空气和翼的空气动力系数预测中的应用

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摘要

This work proposes a novel multi-output neural network for the prediction of aerodynamic coefficients of aerofoils in two dimensions and wings in three dimensions. Contrary to existing neural networks that are often designed to predict aerodynamic quantities of interest, the proposed network considers as output the pressure at a number of selected points on the aerodynamic shape. The proposed multi-output neural network is compared with other approaches found in the literature. Furthermore, a detailed comparison of the proposed neural network with the popular proper orthogonal decomposition method is presented. The numerical results, involving high dimensional problems with flow and geometric parameters, show the benefits of the proposed approach.
机译:这项工作提出了一种新的多输出神经网络,用于预测三维翼型的空气滤波器的空气动力学系数。 与经常设计用于预测空气动力学量的现有神经网络相反,所提出的网络认为在空气动力学形状上的许多选定点处输出压力。 将所提出的多输出神经网络与文献中发现的其他方法进行比较。 此外,提出了具有流行适当的正交分解方法的提出的神经网络的详细比较。 涉及具有流动和几何参数的高维问题的数值结果,显示了所提出的方法的好处。

著录项

  • 来源
    《Applied Mathematical Modelling》 |2021年第8期|456-479|共24页
  • 作者单位

    Zienkiewicz Centre for Computational Engineering Faculty of Science and Engineering Swansea University Bay Campus SA1 8EN Wales United Kingdom;

    Zienkiewicz Centre for Computational Engineering Faculty of Science and Engineering Swansea University Bay Campus SA1 8EN Wales United Kingdom;

    Zienkiewicz Centre for Computational Engineering Faculty of Science and Engineering Swansea University Bay Campus SA1 8EN Wales United Kingdom;

    Zienkiewicz Centre for Computational Engineering Faculty of Science and Engineering Swansea University Bay Campus SA1 8EN Wales United Kingdom;

  • 收录信息 美国《科学引文索引》(SCI);美国《工程索引》(EI);
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

    Neural network; Proper orthogonal decomposition; CFD; NURBS; Aerofoil; Wing;

    机译:神经网络;适当的正交分解;CFD;nurbs;翼型;翅膀;

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