M. Kalikatzarakis, Andrea Coraddu, M. Atlar, G. Tani, S. Gaggero, D. Villa, L. Oneto
{"title":"Computational Prediction of Propeller Cavitation Noise","authors":"M. Kalikatzarakis, Andrea Coraddu, M. Atlar, G. Tani, S. Gaggero, D. Villa, L. Oneto","doi":"10.2218/marine2021.6784","DOIUrl":null,"url":null,"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.","PeriodicalId":367395,"journal":{"name":"The 9th Conference on Computational Methods in Marine Engineering (Marine 2021)","volume":"24 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2022-01-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"The 9th Conference on Computational Methods in Marine Engineering (Marine 2021)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.2218/marine2021.6784","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
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.