Session: 08-05-01 Internal Flows & FIV

Paper Number: 125985

125985 - Numerical Investigation on Propeller Singing Behavior of Underwater Flexible Blades 

The phenomenon of propeller singing is a significant factor in marine propeller design. The main feature of propeller singing is the strong tonal peaks in the correlated noise spectrum. The mechanism underpinning propeller singing behavior is not well clarified to date. It was suggested that this phenomenon originates from the resonance between the vortex-shedding frequency from the blade trailing edge and the structural natural frequency of the blades, but some researchers have denied the relationship between the propeller singing phenomenon and blade vibration. In view of this, the present work calculates the flow-induced vibration of an elastic flexible blade tip submerged in water and considers correlated vortex dynamics and cavitation structure. The dominant structural mode shapes supporting the blades' vibrations are derived from analysis via the software CalculiX and implemented into the following computational fluid dynamics (CFD) calculations. The flow dynamics are calculated via our in-house code (considering the cavitation generation). The study focuses on the interaction between the pulsation frequencies of the cavitation modes in the flow field and the vibration frequencies of the structure, and also analyses the pressure fluctuations in the flow field (related to the spectrum of the sound source), for further insight into the physics underlying propeller singing behavior.

Presenting Author: Zhi Cheng The University of British Columbia

Presenting Author Biography: Academic Background:
1. 2012-2016: B.E., Southeast University;
2. 2016-2019: M.E., University of Waterloo, and Southeast University (United Graduate Education);
3. 2019-2023: Ph.D., University of Waterloo, and Duke University;
4. 2023-present: Postdoctoral Research Fellow at The University of British Columbia (UBC);

Selected Research:
1. Data-driven stability analysis and measurements of flow structure interaction
2. Physics-based machine learning for hydroacoustics
3. Framework development of a fluid-deformable structure interaction modeling

Authors:

Zhi Cheng The University of British Columbia
Rajeev Jaiman The University of British Columbia