A marine propeller design method based on two-fidelity data levels. (June 2022)

• Record Type: Journal Article
• Authors: Gaggero, Stefano; Vernengo, Giuliano; Villa, Diego
• Is Part Of: Applied ocean research. Volume 123(2022)
• Publication Date: 2022-06
• Subjects: Propeller design -- Gaussian process -- Optimization -- Multi-fidelity -- E779A; Ocean engineering -- Periodicals; 620.416205
• DOI: 10.1016/j.apor.2022.103156
• Languages: English
• ISSNs: 0141-1187

Abstract

Abstract: A Simulation Based Design Optimization method for marine propellers design 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 hydrodynamic shape optimization of the E779A propeller using, as fidelity levels, two different physical models for the propeller performances prediction, namely an inviscid, potential based Boundary Element Method (low-fidelity) and a viscous, finite volume RANS 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 response surfaces is highlighted as a requisite for robust and reliable predictions using these approximated methods. Highlights: SBDO represent a feasible design alternative for many complex engineering systems. Feeding SBDO with high-fidelity calculations is not always possible due to computational resource. Surrogate models can replace direct analyses, speeding up the convergence of the design. Multifidelity models have improved predictive capabilities at an even lower computational cost. An application to marine propellers design is proposed, highlighting advantages and limitations.