Optimization of Propeller Boss Cap Fin Design Using Surrogate-Based Model and CFD Simulation
Abstract Propeller boss cap fin (PBCF) is an energy-saving device that enhances the efficiency of marine vessels by mitigating propeller hub vortex and improving propulsion performance. In this work, a design procedure of the PBCF is introduced. It involves airfoil and fin shape optimization as well as PBCF performance evaluation. The airfoil optimization is performed under given ship advance ratio and propeller rotating speed, using an engineering tool and surrogate-based optimization to achieve maximum net thrust. The optimized airfoil demonstrates improved performance compared to the baseline design. The pitch angle describing the orientation of the PBCF is then optimized through iterative adjustments. The adjustment is guided by performance data obtained from computational fluid dynamics (CFD) simulations. The thrust and torque on the fin, cap and propeller are analyzed for better understanding of the force contribution from each component. Both straight fin for constant pitch angle and twisted fin with linearly decreased pitch angle are investigated. Moreover, simulations are conducted to evaluate the performance with a convergent cap as a replacement of the straight cap. CFD simulations show that the efficiency of the propeller equipped with the optimized PBCF and a convergent cap can increase by nearly 1% compared to the propeller without PBCF. The increase in propeller efficiency with optimized straight fins is higher than that achieved with twisted fins. With this design optimization framework, propeller performance can be improved, resulting in better fuel efficiency and cost savings.
Authors
- B. Chia
- Chang Wei Kang (ORCID: https://orcid.org/0000-0002-9737-488X)
- Xiuqing Xing
- Xiaoqin Zhang (ORCID: https://orcid.org/0000-0003-0254-7598)
- Jichao Li (ORCID: https://orcid.org/0000-0003-2541-2557)
- Xinmiao Liang
Institutions
- Northwestern Polytechnical University (CN)
- Comcast (United States) (US)
- Institute of High Performance Computing (SG)
- Northwestern Polytechnic University (US)
Publication Details
- Published
- 2025-06-22
- DOI
- https://doi.org/10.1115/omae2025-157189
- Primary Topic
- Engineering Applied Research
- Type
- article
- Field-Weighted Citation Impact
- 0.00