A multi-objective optimization design framework integrated with CFD for the design of AUVs

Abstract

This paper presents a multi-objective optimization design framework that is integrated with the Computer Aided Design (CAD) for geometric variation and Computational Fluid Dynamics (CFD) software for hydrodynamic computations for the design of Autonomous Underwater Vehicles (AUVs). The optimization model utilizes the ‘Non-dominated Sorting Genetic Algorithm (NSGA-II)’. In the present model hull geometric parameters (i.e. length of nose $\left(L_n\right)$, length of the parallel middle body $\left(L_m\right)$, length of the tail $\left(L_t\right)$, maximum diameter $\left(D_{\max }\right)$, and two shape variation coefficients of nose $\left(n_n\right)$ and tail $\left(n_t\right)$) are considered as the design parameters and minimization of viscous drag, and maximization of nominal wake fraction and total volume are considered as the objective functions for the integrated design approach. CFD software (Shipflow^∗™) is used to evaluate the viscous drag and it is integrated with the CAD definition. The optimization framework NSGA-II is implemented in MATLAB^∗∗™. Finally, we present a design example of an existing AUV Cormoran and show that the integration of NSGA-II with CFD and CAD is effective for AUV hull form design. Our reported results show that for the given bounds on the design parameters, the optimization design framework is able to produce more efficient hull forms than the existing design.