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| Content Provider | Directory of Open Access Journals (DOAJ) |
|---|---|
| Author | Zilin Ran Wenxing Ma Chunbao Liu |
| Abstract | Recent experiments have shown interactions between the cavitation and fluid vortex formation in a hydrodynamic torque converter. This study aimed to clarify the unsteady cavitation trigger mechanism and flow-induced vibration caused by turbulence–cavitation interactions. The mass transfer cavitation model and modified Reynolds-averaged Navier–Stokes k–ω model were used with a local density correction for turbulent eddy viscosity to investigate the cavitation structure in a hydrodynamic torque converter under various operating conditions. The model results were then validated against test data. The multi-block structured gridding technique was used to develop an orthogonally structured grid of a three-dimensional full-flow passage as an alternative analysis method for the cavitation flow. The results indicated that the re-entrant jet is the main cause of the shedding cavitation and breaking O-type cavitation. The re-entrant jet is driven by the reverse pressure gradient to move upstream towards the stator nose, and it lifts and splits the attached cavitation, which periodically induces shedding cavitation. When the cavitation was considered, the prediction error of the capacity constant was reduced from 13.23% to <5%. This work provides an insight into the cavitation–vortex interactions in a hydrodynamic torque converter, which can be used to improve the prediction accuracy of the hydrodynamic performance. |
| e-ISSN | 20763417 |
| DOI | 10.3390/app11062798 |
| Journal | Applied Sciences |
| Issue Number | 2798 |
| Volume Number | 11 |
| Language | English |
| Publisher | MDPI AG |
| Publisher Date | 2021-03-01 |
| Publisher Place | Switzerland |
| Access Restriction | Open |
| Subject Keyword | Technology Engineering (general). Civil Engineering (general) Biology (general) Physics Chemistry Hydrodynamic Torque Converter Turbulence–cavitation Interactions Re-entrant Jet Shedding Cavitation Characteristics Prediction |
| Content Type | Text |
| Resource Type | Article |
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