Propeller tip vortex cavitation mitigation using roughness
Paper in proceeding, 2019

This paper presents an investigation of roughness application on marine propellers in order to alter their tip vortex properties, and consequently mitigate tip vortex cavitation. SST kOmega model along with a curvature correction is employed to simulate the flow on an appropriate grid resolution for tip vortex propagation, at least 32 cells per vortex diameter. The roughness is modelled by using a rough wall function to increase the turbulent properties in roughed areas. In one case, roughness geometry is included as a part of the blade geometry, and the flow around them are resolved. To minimize the negative effects of the roughness on the propeller performance, the roughness area is optimized by simultaneous consideration of the tip vortex mitigation and performance degradation. For the considered operating condition, it is found that having roughness on the tip region of suction side can reduce the cavitation inception by 18 % while keeping the performance degradation in a reasonable range, less than 2%.

Tip Vortex

CFD

Cavitation

Mitigation

Inception

Author

Abolfazl Asnaghi

Chalmers, Mechanics and Maritime Sciences (M2), Marine Technology

Urban Svennberg

Chalmers, Mechanics and Maritime Sciences (M2), Marine Technology

Kongsberg Hydrodynamic Research Centre

Robert Gustafsson

Chalmers, Mechanics and Maritime Sciences (M2), Marine Technology

Kongsberg Hydrodynamic Research Centre

Rickard Bensow

Chalmers, Mechanics and Maritime Sciences (M2), Marine Technology

8th International Conference on Computational Methods in Marine Engineering, MARINE 2019

383-392
9788494919435 (ISBN)

VIII International Conference on Computational Methods in Marine Engineering, MARINE 2019
Gothenburg, Sweden,

RoughProp - reduced radiated noise to the oceans through surface roughness

VINNOVA (2018-04085), 2018-11-19 -- 2020-05-31.

Subject Categories

Applied Mechanics

Fluid Mechanics and Acoustics

Infrastructure

C3SE (Chalmers Centre for Computational Science and Engineering)

ISBN

9788494919435

More information

Latest update

4/21/2023