ブロック構造型直交格子に対する深層学習を用いた後流積分領域推定法

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書誌事項

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  • Wake-Integral Region Estimation Using Deep Learning for Block-Structured Cartesian Mesh.
  • Part 1: On the Accuracy of Drag Estimation
  • その1：抵抗推算精度について

抄録

<p>Cartesian-Mesh CFD solvers have a problem of inaccurate drag force calculation because the grid does not conform to the object. This is attributed to the fact that near-field drag calculations are performed on the surface of the object, which is represented as a staircase. To avoid this problem, the wake integration method, which calculates the drag from the wake region, has been proposed. However, It is not easy to determine the appropriate integration region. In this research, in order to simplify the selection of the wake region in the drag calculation of the Block-Structured Cartesian Mesh using the wake integration method, deep learning was performed using 70 visualized entropy drag image data. As a result, the prediction worked well for some test data. However, we found that further validation is needed to improve a generalization capability of the network model.</p>

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