Computational prediction of underwater radiated noise of cavitating marine propellers: On the accuracy of semi-empirical models. (1st September 2022)

• Record Type: Journal Article
• Authors: Kalikatzarakis, Miltiadis; Coraddu, Andrea; Atlar, Mehmet; Gaggero, Stefano; Tani, Giorgio; Villa, Diego; Oneto, Luca
• Is Part Of: Ocean engineering. Volume 259(2022)
• Publication Date: 2022-09-01
• Subjects: Underwater radiated noise -- Semi-empirical model -- Marine propeller -- Cavitation -- Validation test -- Tip-vortex cavitation -- Sheet cavitation; Ocean engineering -- Periodicals; Ocean engineering; Periodicals; 620.4162
• DOI: 10.1016/j.oceaneng.2022.111477
• Languages: English
• ISSNs: 0029-8018

Abstract

Abstract: The potential impact of underwater radiated noise from maritime operations on marine fauna has become an important issue. The most dominant noise source on a propeller-driven vessel is propeller cavitation, producing both structure-borne and radiated noise, with a broad spectrum that covers a wide range of frequencies. To ensure acceptable noise levels for sustainable shipping, accurate prediction of the noise signature is essential, and procedures able to provide a reliable estimate of propeller cavitation noise are becoming a fundamental tool of the design process. In this work, we investigate the potential of using computationally cheap methods for the prediction of underwater radiated noise from cavitating marine propellers. 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. The results indicate that the approaches employed can be a convenient solution for noise analysis during the design process. Highlights: A tip vortex induced noise semi-empirical model has been developed, calibrated, and validated. A sheet cavitation model has been developed, calibrated, and validated. The calibration process has been formulated as an optimisation problem. The considered decision variables are the values of the calibration constants. Results on a dataset of 432 cavitation tunnel test experiments showed results of high accuracy. Optimal parameters provided for further use in academia.