Journal article 193 views
A machine learning approach to predict near-optimal meshes for turbulent compressible flow simulations
International Journal of Computational Fluid Dynamics
Swansea University Authors:
Oubay Hassan , Rubén Sevilla
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DOI (Published version): 10.1080/10618562.2024.2306941
Abstract
A machine learning approach to predict near-optimal meshes for turbulent compressible flow simulations
Published in: | International Journal of Computational Fluid Dynamics |
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Published: |
Taylor and Francis
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URI: | https://cronfa.swan.ac.uk/Record/cronfa65507 |
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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) 2024-07-31T13:56:58.9638276 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 |
|
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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 |
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published_date |
0001-01-01T13:56:57Z |
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1806099407217623040 |
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11.024221 |