hschilling + cfd   23

[1801.02762] Physics-Informed Machine Learning Approach for Augmenting Turbulence Models: A Comprehensive Framework
Reynolds-averaged Navier-Stokes (RANS) equations are widely used in engineering turbulent flow simulations. However, RANS predictions may have large discrepancies due to the uncertainties in modeled Reynolds stresses. Recently, Wang et al. demonstrated that machine learning can be used to improve the RANS modeled Reynolds stresses by leveraging data from high fidelity simulations (Physics informed machine learning approach for reconstructing Reynolds stress modeling discrepancies bas...
cfd  turbulence  machine-learning 
8 weeks ago by hschilling
Democratization of HPC Part 4: Deep Learning for Fluid Flow Prediction in the Cloud
This is the fourth and final article demonstrating the growing acceptance of high-performance computing (HPC) in new user communities and application
cfd  computation-fluid-dynamics  machine-learning  deep-learning 
10 weeks ago by hschilling
timofeymukha/turbulucid: A Python package for visualising 2D CFD datasets.
A Python package for visualising 2D CFD datasets. Contribute to timofeymukha/turbulucid development by creating an account on GitHub.
cfd  plotting  python 
10 weeks ago by hschilling
Supercomputing how Fish Save Energy Swimming in Schools - insideHPC
Researchers also gained detailed knowledge about this process, which may have implications for energy-efficient swimming or flying swarms of drones.
reinforcement-learning  cfd 
june 2018 by hschilling

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