In this work we present an integrated procedure for the efficient multi-objective shape optimization of a marine propeller under cavitating conditions. The model scale PPTC propeller [1] is chosen as baseline geometry for the optimization due to the significant amount of available experimental data. The geometry is updated through a radial basis function (RBF)-based morphing to provide a suitable and smooth parameterisation of the propeller shape. A finite-volume CFD model is employed to sample and explore the design space, providing an initial set of high-fidelity solutions. This full-order model solves the 3D incompressible two-phase Reynolds-Averaged Navier-Stokes equations in their unsteady formulation (URANS) to account for the cavitation using the Schnerr-Sauer model. Although very accurate, however, the full-order model is computationally demanding, e.g., several hundreds of cpu hours for a single simulation, thus making its direct use within the optimization cycle impractical for industrial applications where a large number of evaluations is typically required. In this context the use of reduced-order models (ROMs) has been shown to be extremely effective in the reduction of the overall computational cost, while still maintaining a sufficient level of accuracy [2]. In this work, a proper orthogonal decomposition (POD)-based ROM, trained on the set of available high-fidelity solutions, is employed as a low-fidelity model for the optimization, providing a cheap and fast prediction of the whole 3D flow field around the propeller as a function of the geometrical parameters employed to morph the propeller itself, i.e., the optimization variables, thus enabling an efficient optimization process. Finally, the outcomes of the optimization are presented and discussed, highlighting the effectiveness and the benefits of the proposed approach for the shape optimization in practical applications with industrial relevance. REFERENCES [1] H.-J. Heinke, Potsdam propeller test case (PPTC), cavitation tests with the model propeller VP1304, Technical report 3753, SVA (Potsdam Model Basin), 2011. [2] F. Salmoiraghi, A. Scardigli, H. Telib and G. Rozza, Free-form deformation, mesh morphing and reduced-order methods: enablers for efficient aerodynamic shape optimisation. International Journal of Computational Fluid Dynamics, 32(4-5):233–247, 2018.