• Journal of the Society of Naval Architects of Korea
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• v.51 no.3
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• pp.259-264
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• 2014

Tip vortex cavitation (TVC) is important for naval ships and research vessels that require raising the cavitation inception speed to maximum possible values. The concepts for alleviating the tip vortex are summarized by Platzer and Souders (1979), who carried out a thorough literature survey. Active control of TVC involves the injection of a polymer or water from the blade tip. The main effect of such mass injection (both water and polymer solutions) into the vortex core is an increase in the core radius, consequently delaying TVC inception. However, the location of the injection port needs to be selected with great care in order to ensure that the mass injection is effective in delaying TVC inception. In the present study, we propose a semi-active control scheme that is achieved by attaching a thread at the propeller tip. The main idea of a semi-active control is that because of its flexibility, the attached thread can be sucked into the low-pressure region closer to the vortex core center. An experimental study using a scale model was carried out in the cavitation tunnel at the Seoul National University. It was found that a flexible thread can effectively suppress the occurrence of TVC under the design condition for a model propeller.

• The Journal of the Acoustical Society of Korea
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• v.40 no.4
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• pp.261-269
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• 2021

Without any validation of the incompressible assumption, most of previous studies on cavitation flow and its noise have utilized numerical methods based on the incompressible Reynolds Average Navier-Stokes (RANS) equations because of advantage of its efficiency. In this study, to investigate the effects of the flow compressibility on the Tip Vortex Cavitation (TVC) flow and noise, both the incompressible and compressible simulations are performed to simulate the TVC flow, and the Ffowcs Williams and Hawkings (FW-H) integral equation is utilized to predict the TVC noise. The DARPA Suboff submarine body with an underwater propeller of a skew angle of 17 degree is targeted to account for the effects of upstream disturbance. The computation domain is set to be same as the test-section of the large cavitation tunnel in Korea Research Institute of Ships and Ocean Engineering to compare the prediction results with the measured ones. To predict the TVC accurately, the Delayed Detached Eddy Simulation (DDES) technique is used in combination with the adaptive grid techniques. The acoustic spectrum obtained using the compressible flow solver shows closer agreement with the measured one.

• Journal of the Society of Naval Architects of Korea
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• v.58 no.2
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• pp.105-111
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• 2021

The main source of underwater radiated noise of ships is cavitation generated by propeller blades. After the Cavitation Inception Speed (CIS), noise level at all frequencies increases severely. In determining the CIS, it is based on the results observed with the naked eye during the model test, however accuracy and consistency of CIS values are becoming practical issues. This study was carried out with the aim of developing a technology that can automatically recognize cavitation images using deep learning technique based on a Convolutional Neural Network (CNN). Model tests on a three-dimensional hydrofoil were conducted at a cavitation tunnel, and tip vortex cavitation was strictly observed using a high-speed camera to obtain analysis data. The results show that this technique can be used to quantitatively evaluate not only the CIS, but also the amount and rate of cavitation from recorded images.

• Journal of the Korean Society of Visualization
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• v.20 no.3
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• pp.128-135
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• 2022

Cavitation occurs inevitably in marine propellers rotating at high speed in the water, which is a major cause of underwater radiated noise. Cavitation-induced noise from propellers rotating at a specific frequency not only reduces the sonar detection capability, but also exposes the ship's location, and it causes very fatal consequences for the survivability of the navy vessels. Therefore cavity inception speed (CIS) is one of the important factors determining the special performance of the ship. In this study, we present a method using computer vision that can detect and quantitatively estimate tip vortex cavitation on a propeller rotating at high speed. Based on the model test results performed in a large cavitation tunnel, the effectiveness of this method was verified.