Multi-Parameter Optimization Analysis of Hydrodynamic Performance for Rim-Driven Thruster

Yuanzhe Nie, Wu Ouyang (), Zhuo Zhang, Gaoqiang Li and Ruicong Zheng
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Yuanzhe Nie: School of Naval Architecture, Ocean and Energy Power Engineering, Wuhan University of Technology, Wuhan 430063, China
Wu Ouyang: School of Transportation and Logistics Engineering, Wuhan University of Technology, Wuhan 430063, China
Zhuo Zhang: School of Transportation and Logistics Engineering, Wuhan University of Technology, Wuhan 430063, China
Gaoqiang Li: School of Naval Architecture, Ocean and Energy Power Engineering, Wuhan University of Technology, Wuhan 430063, China
Ruicong Zheng: School of Transportation and Logistics Engineering, Wuhan University of Technology, Wuhan 430063, China

Energies, 2023, vol. 16, issue 2, 1-20

Abstract: The efficiency of rim-driven thrusters (RDT) has always been the focus of attention in the context of energy conservation and environmental protection. A multi-parameter collaborative optimization framework is proposed to improve the efficiency of RDT based on the response surface method (RSM). The common structural parameters of RDT, including pitch ratio, disk ratio and rake angle, are selected as design variables to carry out the Box–Behnken experimental design combined with the simulation data obtained through CFD calculations. The response surface second-order model is employed to evaluate the extent to which different parameters can affect the target variable and obtain the optimal hydraulic efficiency. The results show that the established model has high precision, good reproducibility and strong anti-interference ability. The influence of the pitch ratio, rake angle and disk ratio on open water efficiency decreases in sequence. Compared with the prototype RDT, the maximum efficiency of the optimized RDT is increased by 13.8%, and the surface pressure distribution and flow field characteristics are also significantly modified.

Keywords: rim-driven thrusters (RDT); response surface method (RSM); hydrodynamic performance; computational fluid dynamics (CFD); multi-parameter optimization (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2023
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