{"title":"A Two-fidelity level approach for Marine Propeller Design","authors":"S. Gaggero, G. Vernengo, D. Villa","doi":"10.2218/marine2021.6801","DOIUrl":null,"url":null,"abstract":"A Simulation Based Design Optimization method for marine propellers using a two-fidelity levels metamodel for global design space exploration and optimization is presented. Response surfaces are built using the co-Kriging approximation, i.e. a multi-output Gaussian process that combines large low-fidelity dataset with few, costly, high-fidelity data. The method is applied for the CFD-based shape optimization of the E779A propeller using, as fidelity levels, two different physical models for the propeller performances prediction, namely a Boundary Element Method (low-fidelity) and a RANSE solver (high-fidelity). Results demonstrate the feasibility of multi-objective, constrained, design procedures, like those involving marine propellers, using these multi-fidelity response surfaces. At the same time, the need of good correlations between low- and high- fidelity data feeding the surrogate models is highlighted as a requisite for robust and reliable predictions using these approximated methods.","PeriodicalId":367395,"journal":{"name":"The 9th Conference on Computational Methods in Marine Engineering (Marine 2021)","volume":"54 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2022-01-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","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/marine2021.6801","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 1
Abstract
A Simulation Based Design Optimization method for marine propellers using a two-fidelity levels metamodel for global design space exploration and optimization is presented. Response surfaces are built using the co-Kriging approximation, i.e. a multi-output Gaussian process that combines large low-fidelity dataset with few, costly, high-fidelity data. The method is applied for the CFD-based shape optimization of the E779A propeller using, as fidelity levels, two different physical models for the propeller performances prediction, namely a Boundary Element Method (low-fidelity) and a RANSE solver (high-fidelity). Results demonstrate the feasibility of multi-objective, constrained, design procedures, like those involving marine propellers, using these multi-fidelity response surfaces. At the same time, the need of good correlations between low- and high- fidelity data feeding the surrogate models is highlighted as a requisite for robust and reliable predictions using these approximated methods.