Autonomous Underwater Vehicle Hull Geometry Optimization Using a Multi-objective Algorithm Approach

Abstarct In this paper, a new approach to optimize an Autonomous Underwater Vehicle (AUV) hull geometry is presented. Using this methode, the nose and tail of an underwater vehicle are designed, such that their length constraints due to the arrangement of different components in the AUV body are properly addressed. In the current study, an optimal design for the body profile of a torpedo-shaped AUV is conducted, and a multi-objective optimization scheme based on the optimization algorithm NSGA-II (Non-dominated Sorting Genetic Algorithm-II, as an evolutionary algorithm) is employed. In addition, predefined geometrical constraints are considered so that equipment with the specific dimensions can be placed inside the AUV space without any effect on the AUV volume and the wetted surface. By optimizing the parameters of the newly presented profile, in addition to maximizing the volume and minimizing the wetted surface area, more diversed shapes can be achieved than with the ‘Myring’ profile. A CFD analysis of the final optimal design indicates that with the help of the proposed profile, the hydrodynamic parameters for the AUV hull are improved effectively.

[1]  T. Shih,et al.  A new k-ϵ eddy viscosity model for high reynolds number turbulent flows , 1995 .

[2]  Reza Tavakkoli-Moghaddam,et al.  Solving a New Multi-objective Unrelated Parallel Machines Scheduling Problem by Hybrid Teaching-learning Based Optimization , 2017 .

[3]  R. Sharma,et al.  A CAGD+CFD integrated optimization model for design of AUVs , 2014, OCEANS 2014 - TAIPEI.

[4]  Matthew Martz,et al.  Preliminary Design of an Autonomous Underwater Vehicle Using a Multiple-Objective Genetic Optimizer , 2008 .

[5]  A. R. Packwood,et al.  Afterbody shaping and transition prediction for a laminar flow underwater vehicle , 1994 .

[6]  B. Launder,et al.  The numerical computation of turbulent flows , 1990 .

[7]  Antonin Ponsich,et al.  Constraint handling strategies in Genetic Algorithms application to optimal batch plant design , 2008 .

[8]  Bidyadhar Subudhi,et al.  The state of art of Autonomous Underwater Vehicles in current and future decades , 2014, 2014 First International Conference on Automation, Control, Energy and Systems (ACES).

[9]  Abolfazl Khalkhali,et al.  MULTI-OBJECTIVE OPTIMIZATION OF A PROJECTILE TIP FOR NORMAL PENETRATION , 2013 .

[10]  D. F. Myring.  A theoretical study of body drag in subcritical axisymmetric flow. , 1976 .

[11]  Tapabrata Ray,et al.  Design and construction of an autonomous underwater vehicle , 2014, Neurocomputing.

[12]  Sung K. Koh,et al.  Optimal design of AUV endcaps , 2011, OCEANS'11 MTS/IEEE KONA.

[13]  Alberto Alvarez,et al.  Hull hydrodynamic optimization of autonomous underwater vehicles operating at snorkeling depth , 2009 .

[14]  Kalyanmoy Deb,et al.  A fast and elitist multiobjective genetic algorithm: NSGA-II , 2002, IEEE Trans. Evol. Comput..

[15]  Karl Sammut,et al.  Shape optimization of an autonomous underwater vehicle with a ducted propeller using computational fluid dynamics analysis , 2012 .