1 code implementation • 29 Sep 2020 • Li-Wei Chen, Berkay Alp Cakal, Xiangyu Hu, Nils Thuerey
In the present study, U-net based deep neural network (DNN) models are trained with high-fidelity datasets to infer flow fields, and then employed as surrogate models to carry out the shape optimisation problem, i. e. to find a drag minimal profile with a fixed cross-section area subjected to a two-dimensional steady laminar flow.
Fluid Dynamics