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Found 5 papers, 4 papers with code
Liquid Splash Modeling with Neural Networks
We use neural networks to model the regression of splash formation using a classifier together with a velocity modifier.
Deep Learning Methods for Reynolds-Averaged Navier-Stokes Simulations of Airfoil Flows
With this study we investigate the accuracy of deep learning models for the inference of Reynolds-Averaged Navier-Stokes solutions.
A Combined Data-driven and Physics-driven Method for Steady Heat Conduction Prediction using Deep Convolutional Neural Networks
For the data-driven based method, the introduction of physical equation not only is able to speed up the convergence, but also produces physically more consistent solutions.
Numerical investigation of minimum drag profiles in laminar flow using deep learning surrogates
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
Neural Image Beauty Predictor Based on Bradley-Terry Model
This work focuses on image beauty assessment.
