Giulio Ortali
A Data-Driven Reduced Order Optimization Approach for Cruise Ship Design.
Rel. Claudio Canuto, Gianluigi Rozza. Politecnico di Torino, Master of science program in Mathematical Engineering, 2019
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Abstract
This Master Thesis describes the implementation of a data-driven shape optimization pipeline in a naval architecture application. We investigate the use of Reduced Order Methods (ROMs) in order to improve the efficiency and applicability of the techniques, also in an industrial setting. The above-mentioned pipeline is applied to a realistic cruise ship in order to reduce the total drag applied. We begin by defining the design space, generated by deforming an initial unoptimized shape in a parametric way using Free Form Deformation (FFD). The evaluation of the performance of each new hull is determined by simulating the flux via finite volume discretization of a biphase (water and air) fluid.
In order to improve the efficiency of the simulation over a new shape, we use ROMs, in particular Proper Orthogonal Decomposition with Interpolation (PODI)
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