16KDD Convolutional Neural Networks for Steady Flow Approximation
本文簡介 以前空氣動力學的計算方法是傳統CFD算法，但是它需要的計算開銷大。本文提出了用CNN的方法，預測2D和3D的非均勻穩定層流(non-uniform steady laminar flow)，在誤差允許範圍內比CFD快很多（在GPU上快4個數量級）。這使得可以在空氣動力學產品的設計初期快速迭代。訓練數據可以源於CFD結果和實測結果。 本文提出的模型模型步驟： 用SDF(Signed Dis
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相關文章
- 1. Understanding Convolutional Neural Networks for NLP
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