Advances toward Numerical Prediction of Noise Emitted by Yacht and Passenger Ship Propellers

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Verlag/Körperschaft:
Hamburg University of Technology
Erscheinungsjahr:
2020
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Text
Beschreibung:
  • The radiated underwater noise due to shipping activities raises considerably the natural underwater background noise level. With an estimated increase of about 3dB per decade, this development is extremely fast in comparison with evolutionary timescales for some of the affected sea fauna to adapt. Low frequency radiated noise covering the 63 Hz to 125 Hz 1/3 octave bands is dominated by propeller cavitation. At the same time, the highest levels of on-board noise are reportedly noted in the same lower-frequency bands, and they are thus also attributed to propeller cavitation. The present paper addresses the following main problems whose solution is critical for the adequate prediction of propeller acoustic performance using numerical approaches: 1) resolution of anisotropic fields of turbulence in the vicinity of propeller-induced vorticity; 2) prediction of dynamic behaviour of cavitation on propeller blades and in propeller-induced vortices; 3) solution of acoustic propagation in the ambient flow domain. Presenting the state-of-the-art in the field, the paper is further focused on the ongoing research and advances regarding the solution of the aforementioned problems in the R&D project ProNoVi. In particular, the aspects related to the use of scale resolving CFD simulations and implementation of acoustic analogy techniques with both the viscous flow and potential flow hydrodynamic solutions are discussed. The examples of validation studies are presented. The project ProNoVi (http://www.pronovi.eu/) is supported and funded by the MarTERA ERA-NET program, represented by BMWi-project (03SX461C) “ProNoVi” for the German partners (TUHH, Fr. Lürssen Werft GmbH & Co. KG, SCHOTTEL GmbH), the Research Council of Norway "Project 284501" for the Norwegian Partners (SINTEF Ocean, Helseth AS) and MIUR-project “ProNoVi” for the Italian partners (CNR-INM).
Quellsystem:
TUHH Open Research

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