2021
DOI: 10.1016/j.oceaneng.2021.109058
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RANS simulation of unsteady cavitation around a Clark-Y hydrofoil with the assistance of machine learning

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Cited by 15 publications
(3 citation statements)
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“…The methods would utilise the experimental or DNS data as their input for their machine learning or deep learning algorithms and use the algorithm output for the traditional field input for turbulence models and are potentially promising. [54,55] 6. Appendix: Implementation of Turbulence models Many of the models discussed in this study are not part of the official OpenFOAM [52] code repository.…”
Section: Discussionmentioning
confidence: 99%
“…The methods would utilise the experimental or DNS data as their input for their machine learning or deep learning algorithms and use the algorithm output for the traditional field input for turbulence models and are potentially promising. [54,55] 6. Appendix: Implementation of Turbulence models Many of the models discussed in this study are not part of the official OpenFOAM [52] code repository.…”
Section: Discussionmentioning
confidence: 99%
“…Cavitation is a commonly natural phenomenon caused by local pressure being lower than the saturated vapor pressure, resulting in the formation of steam pockets. These pockets aggregate and collapse with the flow of fluid, not only disrupting the stable flow state but also generating considerable noise and causing damage to nearby surfaces [1,2]. When cavitation occurs in a centrifugal pump, it leads to a decline in the pump's overall performance, accompanied by vibrations, noise, and other unfavorable effects [3,4].…”
Section: Introductionmentioning
confidence: 99%
“…Zhu et al [40] further investigated the different stages of cavitation life using the Stress-Blended Eddy Simulation (SBES) turbulent model, which yielded results that closely matched experimental data. Some new models based on the existing ones were also proposed recently [41,42].…”
Section: Introductionmentioning
confidence: 99%