Evolution of CFD as an engineering science. A personal perspective with emphasis on the finite volume method
Computational Fluid Dynamics—CFD for short—is a comparatively recent development that has made a significant impact in engineering sciences. The foundations of CFD were laid by developments in physics, numerical analysis and matrix theory over the last 200 years or so. It was, however, the electroni...
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Académie des sciences
2024-06-01
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| Series: | Comptes Rendus. Mécanique |
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| Online Access: | https://comptes-rendus.academie-sciences.fr/mecanique/articles/10.5802/crmeca.240/ |
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| author | Runchal, Akshai Kumar |
| author_facet | Runchal, Akshai Kumar |
| author_sort | Runchal, Akshai Kumar |
| collection | DOAJ |
| description | Computational Fluid Dynamics—CFD for short—is a comparatively recent development that has made a significant impact in engineering sciences. The foundations of CFD were laid by developments in physics, numerical analysis and matrix theory over the last 200 years or so. It was, however, the electronic computer in the middle of the 20th century that led to its birth and its widespread use. It has now become an invaluable tool for almost every sphere of human activity. A number of researchers contributed to the tools and technology that came to be called CFD but the prime movers were two brilliant scientists—one at Los Alamos National Laboratory and the other at Imperial College, London. The author was a part of the Imperial College group and this is a personal perspective on the evolution of CFD.Over the last few decades, CFD has made a significant impact in a wide spectrum of engineering and environmental sectors. These include both traditional disciplines such as aerospace, automotive, mechanical and thermal sciences, and newer disciplines and emerging fields of human and social relevance such as biomedical, sports, entertainment, food processing, fire safety, HVAC and energy efficiency. However, a number of challenges remain. For many important applications, we lack both the physics and the mathematical tools to adequately understand the behavior of fluids. The current generation of CFD tools are resource intensive and difficult to use that require a long period of training. Most importantly, except for a very limited set of applications, one cannot rely on the predictions with a high level of confidence.Computational Fluid Dynamics is now poised on the threshold of a revolution. Recent developments in machine learning, AI, computer hardware, big data, IOT and Virtual Reality tools will lead to design tools with CFD engines that are robust, reliable and easily accessible to a practicing engineer rather than be the domain of a CFD expert. CFD will be a tool that is ubiquitous by its absence—buried inside devices and applications into diverse areas of human activity. This would make it possible for a practicing engineer to effectively visualize a fluid system, interact with its components, conduct CFD simulation, and control its behaviour through dynamic intervention. |
| format | Article |
| id | doaj-art-7e676c013c6647b59fc5fa246b48e665 |
| institution | Kabale University |
| issn | 1873-7234 |
| language | English |
| publishDate | 2024-06-01 |
| publisher | Académie des sciences |
| record_format | Article |
| series | Comptes Rendus. Mécanique |
| spelling | doaj-art-7e676c013c6647b59fc5fa246b48e6652025-02-07T13:45:37ZengAcadémie des sciencesComptes Rendus. Mécanique1873-72342024-06-01350S123325810.5802/crmeca.24010.5802/crmeca.240Evolution of CFD as an engineering science. A personal perspective with emphasis on the finite volume methodRunchal, Akshai Kumar0https://orcid.org/0000-0002-8226-5234Analytic & Computational Research, Inc., 1931 Stradella Road, Los Ángeles, CA 90077, USAComputational Fluid Dynamics—CFD for short—is a comparatively recent development that has made a significant impact in engineering sciences. The foundations of CFD were laid by developments in physics, numerical analysis and matrix theory over the last 200 years or so. It was, however, the electronic computer in the middle of the 20th century that led to its birth and its widespread use. It has now become an invaluable tool for almost every sphere of human activity. A number of researchers contributed to the tools and technology that came to be called CFD but the prime movers were two brilliant scientists—one at Los Alamos National Laboratory and the other at Imperial College, London. The author was a part of the Imperial College group and this is a personal perspective on the evolution of CFD.Over the last few decades, CFD has made a significant impact in a wide spectrum of engineering and environmental sectors. These include both traditional disciplines such as aerospace, automotive, mechanical and thermal sciences, and newer disciplines and emerging fields of human and social relevance such as biomedical, sports, entertainment, food processing, fire safety, HVAC and energy efficiency. However, a number of challenges remain. For many important applications, we lack both the physics and the mathematical tools to adequately understand the behavior of fluids. The current generation of CFD tools are resource intensive and difficult to use that require a long period of training. Most importantly, except for a very limited set of applications, one cannot rely on the predictions with a high level of confidence.Computational Fluid Dynamics is now poised on the threshold of a revolution. Recent developments in machine learning, AI, computer hardware, big data, IOT and Virtual Reality tools will lead to design tools with CFD engines that are robust, reliable and easily accessible to a practicing engineer rather than be the domain of a CFD expert. CFD will be a tool that is ubiquitous by its absence—buried inside devices and applications into diverse areas of human activity. This would make it possible for a practicing engineer to effectively visualize a fluid system, interact with its components, conduct CFD simulation, and control its behaviour through dynamic intervention.https://comptes-rendus.academie-sciences.fr/mecanique/articles/10.5802/crmeca.240/CFDFinite volume methodsMachine learningPINNAI |
| spellingShingle | Runchal, Akshai Kumar Evolution of CFD as an engineering science. A personal perspective with emphasis on the finite volume method Comptes Rendus. Mécanique CFD Finite volume methods Machine learning PINN AI |
| title | Evolution of CFD as an engineering science. A personal perspective with emphasis on the finite volume method |
| title_full | Evolution of CFD as an engineering science. A personal perspective with emphasis on the finite volume method |
| title_fullStr | Evolution of CFD as an engineering science. A personal perspective with emphasis on the finite volume method |
| title_full_unstemmed | Evolution of CFD as an engineering science. A personal perspective with emphasis on the finite volume method |
| title_short | Evolution of CFD as an engineering science. A personal perspective with emphasis on the finite volume method |
| title_sort | evolution of cfd as an engineering science a personal perspective with emphasis on the finite volume method |
| topic | CFD Finite volume methods Machine learning PINN AI |
| url | https://comptes-rendus.academie-sciences.fr/mecanique/articles/10.5802/crmeca.240/ |
| work_keys_str_mv | AT runchalakshaikumar evolutionofcfdasanengineeringscienceapersonalperspectivewithemphasisonthefinitevolumemethod |