A shape optimization pipeline for marine propellers by means of reduced order modeling techniques

Abstract

In this article, 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 nonintrusive reduced‐order model. This article provides a proof of concept of the pipeline proposed, where the optimized propeller improves the efficiency of the original propeller.