  In this paper, we propose a shape optimization pipeline for propeller blades,
applied to naval applications. The geometrical features of a blade are
exploited to parametrize it, allowing to obtain deformed blades by perturbating
their parameters. The optimization is performed using a genetic algorithm that
exploits the computational speed-up of reduced order models to maximize the
efficiency of a given propeller. A standard offline-online procedure is
exploited to construct the reduced-order model. In an expensive offline phase,
the full order model, which reproduces an open water test, is set up in the
open-source software OpenFOAM and the same full order setting is used to run
the CFD simulations for all the deformed propellers. The collected
high-fidelity snapshots and the deformed parameters are used in the online
stage to build the non-intrusive reduced-order model. This paper provides a
proof of concept of the pipeline proposed, where the optimized propeller
improves the efficiency of the original propeller.
