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There is a Computational fluid dynamics (CFD) method of incorporating the DNNinference to reduce the computational cost. The reduction is realized byreplacing some calculations by DNN inference. The cost reduction depends on theimplementation 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. Thefirst technique is to infer the flow field of the steady state from the airfoilshape. We use the position on the coordinates of the grid point and thedistance from the surface of the airfoil as input information for the DNN. Thesecond method uses the customized mean square error as a loss function. Thesize of the associated area for each grid point was multiplied by the squareerror. This method compensates for the effect caused by the size of theassociated area of nonuniform allocation of grid points. The evaluation resultsshow that the CFD incorporated first technique achieves 1.7x speedup againstthe CFD without DNN, while maintaining equivalent result quality. Byimplementing the second technique, the CFD realized further 2.3x speed upagainst the CFD with first technique only.

Accuracy Improvement Technique of DNN for Accelerating CFD Simulator