• Journal of the Korean Society of Visualization
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• v.22 no.1
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• pp.49-60
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• 2024

The purpose of this study establishes the deep neural network (DNN) and Decoder models to predict the flow and thermal fields of three-dimensional wavy wings as a passive flow control. The wide ranges of the wavy geometric parameters of wave amplitude and wave number are considered for the various the angles of attack and the aspect ratios of a wing. The huge dataset for training and test of the deep learning models are generated using computational fluid dynamics (CFD). The DNN and Decoder models exhibit quantitatively accurate predictions for aerodynamic coefficients and Nusselt numbers, also qualitative pressure, limiting streamlines, and Nusselt number distributions on the surface. Particularly, Decoder model regenerates the important flow features of tiny vortices in the valleys, which makes a delay of the stall. Also, the spiral vortical formation is realized by the Decoder model, which enhances the lift.

• Journal of Ocean Engineering and Technology
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• v.12 no.2 s.28
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• pp.79-86
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• 1998

A three-dimensional WIG (Wing In Ground effect) moving above free surface is numerically studied by means of finite difference techniques. The air flow field around the WIG is analyzed by MAC (Marker & Cell) method, and interactions between WIG and the free surface are appeared as the variation of pressure distribution acting on the free surface. To analyze the wavemaking phenomena by those pressure distributions, the NS (Navier-Stokes) solver is employed in which nonlinearities of the free surface conditions can be included. Through the numerical simulation, Cp values and lift/drag ratio are carefully reviewed by changing the height/chord ratio. The section shape of model is NACA0012 with the span/chord ratio of 3.0. Through computational results, it is confirmed that the effect of free surface is small enough to treat it as a rigid wavy wall.