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A machine learning approach to predict near-optimal meshes for turbulent compressible flow simulations

Sergi Sanchez-Gamero, Oubay Hassan Orcid Logo, Rubén Sevilla Orcid Logo

International Journal of Computational Fluid Dynamics

Swansea University Authors: Oubay Hassan Orcid Logo, Rubén Sevilla Orcid Logo

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DOI (Published version): 10.1080/10618562.2024.2306941

Published in: International Journal of Computational Fluid Dynamics
Published: Taylor and Francis
URI: https://cronfa.swan.ac.uk/Record/cronfa65507
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first_indexed 2024-01-24T16:11:10Z
last_indexed 2024-01-24T16:11:10Z
id cronfa65507
recordtype SURis
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spelling v2 65507 2024-01-24 A machine learning approach to predict near-optimal meshes for turbulent compressible flow simulations 07479d73eba3773d8904cbfbacc57c5b 0000-0001-7472-3218 Oubay Hassan Oubay Hassan true false b542c87f1b891262844e95a682f045b6 0000-0002-0061-6214 Rubén Sevilla Rubén Sevilla true false 2024-01-24 ACEM Journal Article International Journal of Computational Fluid Dynamics Taylor and Francis 0 0 0 0001-01-01 10.1080/10618562.2024.2306941 Preprint submitted to IJCFD COLLEGE NANME Aerospace, Civil, Electrical, and Mechanical Engineering COLLEGE CODE ACEM Swansea University SU Library paid the OA fee (TA Institutional Deal) 2024-11-06T12:30:08.2916906 2024-01-24T16:09:01.4872012 Faculty of Science and Engineering School of Aerospace, Civil, Electrical, General and Mechanical Engineering - Civil Engineering Sergi Sanchez-Gamero 1 Oubay Hassan 0000-0001-7472-3218 2 Rubén Sevilla 0000-0002-0061-6214 3
title A machine learning approach to predict near-optimal meshes for turbulent compressible flow simulations
spellingShingle A machine learning approach to predict near-optimal meshes for turbulent compressible flow simulations
Oubay Hassan
Rubén Sevilla
title_short A machine learning approach to predict near-optimal meshes for turbulent compressible flow simulations
title_full A machine learning approach to predict near-optimal meshes for turbulent compressible flow simulations
title_fullStr A machine learning approach to predict near-optimal meshes for turbulent compressible flow simulations
title_full_unstemmed A machine learning approach to predict near-optimal meshes for turbulent compressible flow simulations
title_sort A machine learning approach to predict near-optimal meshes for turbulent compressible flow simulations
author_id_str_mv 07479d73eba3773d8904cbfbacc57c5b
b542c87f1b891262844e95a682f045b6
author_id_fullname_str_mv 07479d73eba3773d8904cbfbacc57c5b_***_Oubay Hassan
b542c87f1b891262844e95a682f045b6_***_Rubén Sevilla
author Oubay Hassan
Rubén Sevilla
author2 Sergi Sanchez-Gamero
Oubay Hassan
Rubén Sevilla
format Journal article
container_title International Journal of Computational Fluid Dynamics
institution Swansea University
doi_str_mv 10.1080/10618562.2024.2306941
publisher Taylor and Francis
college_str Faculty of Science and Engineering
hierarchytype
hierarchy_top_id facultyofscienceandengineering
hierarchy_top_title Faculty of Science and Engineering
hierarchy_parent_id facultyofscienceandengineering
hierarchy_parent_title Faculty of Science and Engineering
department_str School of Aerospace, Civil, Electrical, General and Mechanical Engineering - Civil Engineering{{{_:::_}}}Faculty of Science and Engineering{{{_:::_}}}School of Aerospace, Civil, Electrical, General and Mechanical Engineering - Civil Engineering
document_store_str 0
active_str 0
published_date 0001-01-01T12:30:08Z
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score 11.037581

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