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Hydrodynamics research around the high-speed marine vehicles

Seminar

Image for Event - 25 Feb Seminar - Dr HUANG
  • Date

    25 Feb 2022

  • Organiser

    Department of Aeronautical and Aviation Engineering

  • Time

    12:00 - 13:00

  • Venue

     

Enquiry

General Office aae.info@polyu.edu.hk

Remarks

Please register for this online seminar by 12:00 pm, 24 Feb 2022 (Thu).

Summary

Abstract

The speed of marine vehicles is limited to 60 knots, due to the dramatic increase in resistance and the occurrence of vaporous cavitation at high speeds. Surface-piercing hydrofoil is used to generate lift, reduce the wetted area and thus reduce the drag. This study investigates the ventilated cavities around a surface-piercing hydrofoil, aiming to extend previous studies by an in-depth understanding of the vaporous cavity behaviours and the flow-regime transition at high Froude numbers. An experiment is carried out in a constrained-launching water tank with a vertically cantilevered hydrofoil piercing a still water surface. In addition to the well-known steady flow regimes (i.e. fully wetted flow, fully ventilated flow), an unsteady vaporous cavitating flow is revealed at a very high Froude number with a small yaw angle. The transition from the fully wetted flow to the fully ventilated flow is attributed to the vapour-cavitation-induced ventilation besides the tip-vortex-induced ventilation. Besides, an improved lifting-line model is developed with considering the effects of free surface and finite aspect ratio. Both analytical modelling and experimental measurements show that the vaporous cavity length follows a power relation against the cavitation parameter. Such knowledge lays a foundation for the design optimization and control strategy of high-speed hydrofoils.

 

Speaker

Dr. Renfang Huang graduated from Tsinghua University and she is currently an Associate Professor at the Institute of Mechanics, Chinese Academy of Sciences. She is engaged in the research of fundamental cavitation, ocean engineering and the machine-learning applications.

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