69 citations · 115 across the 4 of their papers we have counts for
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physics.flu-dyn2022★ 69 cited
Learned Turbulence Modelling with Differentiable Fluid Solvers: Physics-based Loss-functions and Optimisation Horizons
Björn List, Li-Wei Chen, Nils Thuerey
In this paper, we train turbulence models based on convolutional neural networks. These learned turbulence models improve under-resolved low resolution solutions to the incompressi…
physics.flu-dyn2021★ 4 cited
Towards high-accuracy deep learning inference of compressible turbulent flows over aerofoils
Li-Wei Chen, Nils Thuerey
The present study investigates the accurate inference of Reynolds-averaged Navier-Stokes solutions for the compressible flow over aerofoils in two dimensions with a deep neural net…
physics.flu-dyn2020★ 42 cited
Numerical investigation of minimum drag profiles in laminar flow using deep learning surrogates
Li-Wei Chen, Berkay Alp Cakal, Xiangyu Hu +1
Efficiently predicting the flowfield and load in aerodynamic shape optimisation remains a highly challenging and relevant task. Deep learning methods have been of particular intere…