  There is a Computational fluid dynamics (CFD) method of incorporating the DNN
inference to reduce the computational cost. The reduction is realized by
replacing some calculations by DNN inference. The cost reduction depends on the
implementation method of the DNN and the accuracy of the DNN inference. Thus,
we propose two techniques suitable to infer flow field on the CFD grid. The
first technique is to infer the flow field of the steady state from the airfoil
shape. We use the position on the coordinates of the grid point and the
distance from the surface of the airfoil as input information for the DNN. The
second method uses the customized mean square error as a loss function. The
size of the associated area for each grid point was multiplied by the square
error. This method compensates for the effect caused by the size of the
associated area of nonuniform allocation of grid points. The evaluation results
show that the CFD incorporated first technique achieves 1.7x speedup against
the CFD without DNN, while maintaining equivalent result quality. By
implementing the second technique, the CFD realized further 2.3x speed up
against the CFD with first technique only.
