A curated dataset for data-driven turbulence modelling

Ryley McConkey; Eugene Yee; Fue-Sang Lien

doi:10.1038/s41597-021-01034-2

Scientific Data (Sep 2021)

A curated dataset for data-driven turbulence modelling

Ryley McConkey,
Eugene Yee,
Fue-Sang Lien

Affiliations

Ryley McConkey: University of Waterloo, Department of Mechanical and Mechatronics Engineering, 200 University Avenue
Eugene Yee: University of Waterloo, Department of Mechanical and Mechatronics Engineering, 200 University Avenue
Fue-Sang Lien: University of Waterloo, Department of Mechanical and Mechatronics Engineering, 200 University Avenue

DOI: https://doi.org/10.1038/s41597-021-01034-2
Journal volume & issue: Vol. 8, no. 1
pp. 1 – 14

Abstract

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Measurement(s) velocity fields • pressure fields • turbulence fields • related gradients Technology Type(s) numerical simulation Factor Type(s) turbulence model • flow geometry Machine-accessible metadata file describing the reported data: https://doi.org/10.6084/m9.figshare.15124857

Published in Scientific Data

ISSN: 2052-4463 (Online)
Publisher: Nature Portfolio
Country of publisher: United Kingdom
LCC subjects: Science
Website: https://www.nature.com/sdata/

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