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Title:

Deep Learning Methods for Reynolds-Averaged Navier-Stokes Simulations, Reduced Data Set (6.4k Samples)

Document type:
Forschungsdaten
Responsible:
Thuerey, Nils
Authors:
Thuerey, Nils; Xiangyu, Hu
Author affiliation:
TUM
Publisher:
TUM
Identifier:
doi:10.14459/2018mp1470791
End date of data production:
05.10.2018
Subject area:
DAT Datenverarbeitung, Informatik
Resource type:
Simulationen / simulations
Data type:
Datenbanken / data bases
Description:
This archive contains 6400 data sets of RANS simulations for the "Deep Flow Prediction" project, in addition to 90 test data sets. The data set is intended for training deep neural networks for fluid simulations.
Links:

Project & Source-Code

Key words:
Fluid Simulation; Deep Learning; Navier-Stokes
Technical remarks:
Data format: numpy arrays, 128x128 with 6 channels: freestream x, freestream y, airfoil mask, output pressure, output velocity x, output velocity y.
View and download
The data server also offers downloads with FTP
The data server also offers downloads with rsync (password m1470791):
rsync rsync://m1470791@dataserv.ub.tum.de/m1470791/
Language:
en
Rights:
by-sa, http://creativecommons.org/licenses/by-sa/4.0
Horizon 2020:
ERC StG 637014
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