Machine learning-based CFD simulations: a review, models, open threats, and future tactics-Reference-Cited by-同舟云学术

Machine learning-based CFD simulations: a review, models, open threats, and future tactics

Published:2022-09-25 Issue:24 Volume:34 Page:21677-21700
ISSN:0941-0643
Container-title:Neural Computing and Applications
language:en
Short-container-title:Neural Comput & Applic

Author:

Panchigar Dhruvil,Kar Kunal,Shukla Shashank,Mathew Rhea Mary,Chadha Utkarsh^ORCID,Selvaraj Senthil Kumaran^ORCID

Publisher

Springer Science and Business Media LLC

Subject

Artificial Intelligence,Software

Link

https://link.springer.com/content/pdf/10.1007/s00521-022-07838-6.pdf

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2. Padagannavar P, Bheemanna M (2016) Automotive computational fluid dynamics simulation of a car using Ansys. Int J Mech Eng Technol (IJMET) 7:91–104

3. John J, Pane EA, Suyitno BM, Rahayu GHNN, Rhakasywi D, Suwandi A (2020) Computational fluid dynamics simulation of the turbulence models in the tested section on wind tunnel. Ain Shams Eng J 11:1201–1209. https://doi.org/10.1016/j.asej.2020.02.012

4. Zhang H, Xu Y, Cai H (2010) Using CFD software to calculate hydrodynamic coefficients. J Mar Sci Appl 9(2):149–155. https://doi.org/10.1007/s11804-010-9009-9

5. Shah MS, Joshi JB, Kalsi AS, Prasad CSR, Shukla DS (2012) Analysis of flow through an orifice meter: CFD simulation. Chem Eng Sci 71:300–309. https://doi.org/10.1016/j.ces.2011.11.022

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