Machine Learning and Artificial Intelligence in Fluid Mechanics
Fluid mechanics research has evolved during the past few years towards the direction of exploiting massive amounts of data generated from knowledge gathered insofar, either from experimental measurements or simulations. The application of novel machine learning (ML) techniques is currently the lates...
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| Materialtyp: | Online |
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| Språk: | engelska |
| Utgiven: |
MDPI - Multidisciplinary Digital Publishing Institute
2026
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| Ämnen: | |
| Länkar: | ONIX_20260416T142754_9783725864584_21 |
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| _version_ | 1869529553639047168 |
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| collection | Directory of Open Access Books |
| description | Fluid mechanics research has evolved during the past few years towards the direction of exploiting massive amounts of data generated from knowledge gathered insofar, either from experimental measurements or simulations. The application of novel machine learning (ML) techniques is currently the latest trend in the field and has almost reached standardization. Computational boosting, advanced turbulence modeling, bridging among scales, hybrid simulation schemes, and flow feature extraction are concepts that scientists and engineers must deal with. This Reprint joins together data science methods and advanced artificial intelligence (AI) and ML techniques, in order to apply them to popular fluid mechanics problems, in an alternative though effective and accurate manner, strictly bound to the physical problem. Detailed reviews on the AI/CFD intersection and the future of ML in fluid dynamics can be found in this Reprint, along with novel research papers on topics related to scientific ML, physics-informed neural networks, intelligent fluid dynamics, industrial applications of AI, and explainable and trustworthy AI. |
| format | Online |
| id | doab-20.500.12854ir-175266 |
| institution | Directory of Open Access Books |
| language | eng |
| publishDate | 2026 |
| publishDateRange | 2026 |
| publishDateSort | 2026 |
| publisher | MDPI - Multidisciplinary Digital Publishing Institute |
| publisherStr | MDPI - Multidisciplinary Digital Publishing Institute |
| record_format | ojs |
| spelling | doab-20.500.12854ir-1752662026-04-16T19:58:00Z Machine Learning and Artificial Intelligence in Fluid Mechanics Sofos, Filippos Physics-Informed Neural Networks Turbulent flows Microfluidics Fluid property prediction thema EDItEUR::G Reference, Information and Interdisciplinary subjects::GP Research and information: general Fluid mechanics research has evolved during the past few years towards the direction of exploiting massive amounts of data generated from knowledge gathered insofar, either from experimental measurements or simulations. The application of novel machine learning (ML) techniques is currently the latest trend in the field and has almost reached standardization. Computational boosting, advanced turbulence modeling, bridging among scales, hybrid simulation schemes, and flow feature extraction are concepts that scientists and engineers must deal with. This Reprint joins together data science methods and advanced artificial intelligence (AI) and ML techniques, in order to apply them to popular fluid mechanics problems, in an alternative though effective and accurate manner, strictly bound to the physical problem. Detailed reviews on the AI/CFD intersection and the future of ML in fluid dynamics can be found in this Reprint, along with novel research papers on topics related to scientific ML, physics-informed neural networks, intelligent fluid dynamics, industrial applications of AI, and explainable and trustworthy AI. 2026-04-16T19:57:53Z 2026-04-16T19:57:53Z 2026 book ONIX_20260416T142754_9783725864584_21 9783725864584 9783725864591 https://directory.doabooks.org/handle/20.500.12854/175266 eng application/octet-stream Attribution 4.0 International https://mdpi.com/books/ https://mdpi.com/books/pdfview/book/12178 MDPI - Multidisciplinary Digital Publishing Institute 10.3390/books978-3-7258-6459-1 10.3390/books978-3-7258-6459-1 46cabcaa-dd94-4bfe-87b4-55023c1b36d0 9783725864584 9783725864591 346 CH open access |
| spellingShingle | Physics-Informed Neural Networks Turbulent flows Microfluidics Fluid property prediction thema EDItEUR::G Reference, Information and Interdisciplinary subjects::GP Research and information: general Machine Learning and Artificial Intelligence in Fluid Mechanics |
| title | Machine Learning and Artificial Intelligence in Fluid Mechanics |
| title_full | Machine Learning and Artificial Intelligence in Fluid Mechanics |
| title_fullStr | Machine Learning and Artificial Intelligence in Fluid Mechanics |
| title_full_unstemmed | Machine Learning and Artificial Intelligence in Fluid Mechanics |
| title_short | Machine Learning and Artificial Intelligence in Fluid Mechanics |
| title_sort | machine learning and artificial intelligence in fluid mechanics |
| topic | Physics-Informed Neural Networks Turbulent flows Microfluidics Fluid property prediction thema EDItEUR::G Reference, Information and Interdisciplinary subjects::GP Research and information: general |
| topic_facet | Physics-Informed Neural Networks Turbulent flows Microfluidics Fluid property prediction thema EDItEUR::G Reference, Information and Interdisciplinary subjects::GP Research and information: general |
| url | ONIX_20260416T142754_9783725864584_21 |