Improved Performance Prediction of Marine Propeller: Numerical Investigation and Experimental Verification

Yue Tan, Jing Li, Yuan Li and Chunbao Liu

Mathematical Problems in Engineering, 2019, vol. 2019, 1-10

Abstract:

An approach was presented to improve the performance prediction of marine propeller through computational fluid dynamics (CFD). After a series of computations were conducted, it was found that the passage in the former study was too narrow, resulting in the unnecessary radial outer boundary effects. Hence, in this study, a fatter passage model was employed to avoid unnecessary effects, in which the diameter was the same as the length from the propeller to the downstream outlet and the diameter was larger than the previous study. The diameter and length of the passage were 5 D and 8 D , respectively. The propeller DTMB P5168 was used to evaluate the fat passage model. During simulation, the classical RANS model (standard k - ) and the Multiple Reference Frame (MRF) approach were employed after accounting for other factors. The computational performance results were compared with the experimental values, which showed that they were in good agreement. The maximum errors of K t and K q were less than 5% and 3% on different advance coefficients J except 1.51, respectively, and that of was less than 2.62%. Hence the new model obtains more accurate performance prediction compared with published literatures. The circumferentially averaged velocity components were also compared with the experimental results. The axial and tangential velocity components were also in good agreement with the experimental data. Specifically, the errors of the axial and tangential velocity components were less than 3%, when the r/R was not less than 3.4. When the J value was larger, the variation trends of radial velocity were consistent with the experimental data. In conclusion, the fat passage model proposed here was applicable to obtain the highly accurate predicted results.

Date: 2019
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Persistent link: https://EconPapers.repec.org/RePEc:hin:jnlmpe:7501524

DOI: 10.1155/2019/7501524

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