Zobrazeno 1 - 10
of 10
pro vyhledávání: '"Charles Patrick Bounds"'
Publikováno v:
Vehicles, Vol 6, Iss 3, Pp 1318-1344 (2024)
Computational fluid dynamic (CFD) models and workflows are often developed in an ad hoc manner, leading to a limited understanding of interaction effects and model behavior under various conditions. Machine learning (ML) and explainability tools can
Externí odkaz:
https://doaj.org/article/0b035cc5c2ab433bbe80c8d70618bd79
Publikováno v:
Fluids, Vol 6, Iss 11, p 404 (2021)
This paper presents a study on the flow dynamics involving vehicle interactions. In order to do so, this study first explores aerodynamic prediction capabilities of popular turbulence models used in computational fluid dynamics simulations involving
Externí odkaz:
https://doaj.org/article/4cf59ef6102847e18fc2ce179c763a99
Publikováno v:
Fluids, Vol 4, Iss 3, p 148 (2019)
In today’s road vehicle design processes, Computational Fluid Dynamics (CFD) has emerged as one of the major investigative tools for aerodynamics analyses. The age-old CFD methodology based on the Reynolds Averaged Navier−Stokes (RANS) approach i
Externí odkaz:
https://doaj.org/article/5dcba9dc38a045d59c4d7aa939e91796
Publikováno v:
SAE Technical Paper Series.
This article discusses an application of Machine Learning (ML) tools to improve the prediction accuracy of Computational Fluid Dynamics (CFD) for external aerodynamic workflows. The Reynolds Averaged Navier-Stokes (RANS) approach to CFD has proved to
Publikováno v:
Proceedings of the Institution of Mechanical Engineers, Part D: Journal of Automobile Engineering. 234:2522-2545
In spite of its shortcomings, faster turnaround time and cost-effectiveness make the Reynolds-averaged Navier–Stokes modeling approach still a popular and widely used methodology in many industrial applications, including the automotive industries
Publikováno v:
Fluids
Volume 6
Issue 11
Fluids, Vol 6, Iss 404, p 404 (2021)
Volume 6
Issue 11
Fluids, Vol 6, Iss 404, p 404 (2021)
This paper presents a study on the flow dynamics involving vehicle interactions. In order to do so, this study first explores aerodynamic prediction capabilities of popular turbulence models used in computational fluid dynamics simulations involving
Publikováno v:
SAE International Journal of Passenger Cars - Mechanical Systems. 12:211-223
Publikováno v:
SAE International Journal of Advances and Current Practices in Mobility. 1:1226-1232
Publikováno v:
SAE Technical Paper Series.
Publikováno v:
Fluids
Volume 4
Issue 3
Fluids, Vol 4, Iss 3, p 148 (2019)
Volume 4
Issue 3
Fluids, Vol 4, Iss 3, p 148 (2019)
In today&rsquo
s road vehicle design processes, Computational Fluid Dynamics (CFD) has emerged as one of the major investigative tools for aerodynamics analyses. The age-old CFD methodology based on the Reynolds Averaged Navier&ndash
Stokes
s road vehicle design processes, Computational Fluid Dynamics (CFD) has emerged as one of the major investigative tools for aerodynamics analyses. The age-old CFD methodology based on the Reynolds Averaged Navier&ndash
Stokes