The potential impact of ships underwater radiated noise (URN) on marine fauna has become an important issue. The most dominant noise source on a propeller-driven vessel is propeller cavitation, and the accurate prediction of its noise signature is fundamental for the design process. In this work, we investigate the potential of using low-computational-cost methods for the prediction of URN from cavitating marine propellers that can be conveniently implemented within the design process. We compare computational and experimental results on a subset of the Meridian standard propeller series, behind different severities of axial wake, for a total of 432 experiments.

Computational Prediction of Propeller Cavitation Noise

GIORGIO TANI;STEFANO GAGGERO;DIEGO VILLA;LUCA ONETO
2021

Abstract

The potential impact of ships underwater radiated noise (URN) on marine fauna has become an important issue. The most dominant noise source on a propeller-driven vessel is propeller cavitation, and the accurate prediction of its noise signature is fundamental for the design process. In this work, we investigate the potential of using low-computational-cost methods for the prediction of URN from cavitating marine propellers that can be conveniently implemented within the design process. We compare computational and experimental results on a subset of the Meridian standard propeller series, behind different severities of axial wake, for a total of 432 experiments.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11567/1048015
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