A Fluid Flow Data Set for Machine Learning
Open access
Date
2021-02Type
- Dataset
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Data
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Abstract
We provide a large fluid flow data set ready to be applied to deep learning problems. Parameterized by the Reynolds number, the data set contains a wide spectrum of laminar and turbulent fluid flow regimes. The full data set was simulated on a high-performance compute cluster and contains 8000 time Show more
Permanent link
https://doi.org/10.3929/ethz-b-000515488Contributors
Contact person: Günther, Tobias
Data collector: Jakob, Jakob
Producer: Jakob, Jakob
Project leader: Günther, Tobias
Project member: Jakob, Jakob
Project member: Gross, Markus
Project member: Günther, Tobias
Publisher
ETH ZurichSoftware
Simulated with Gerris flow solver, which was created by Stéphane Popinet.Subject
Machine Learning; Flow Visualization; Fluid DynamicsOrganisational unit
03420 - Gross, Markus / Gross, Markus
Funding
180114 - Guided Large-Scale Exploration of Meteorological Data (SNF)
Related publications and datasets
Is supplement to: http://hdl.handle.net/20.500.11850/465737
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ETH Bibliography
yes
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