• International Journal of Naval Architecture and Ocean Engineering
• /
• v.7 no.6
• /
• pp.995-1006
• /
• 2015

Underwater glider, as a new kind of autonomous underwater vehicles, has many merits such as long-range, extended-duration and low costs. The shape of underwater glider is an important factor in determining the hydrodynamic efficiency. In this paper, a high lift to drag ratio configuration, the Blended-Wing-Body (BWB), is used to design a small civilian under water glider. In the parametric geometric model of the BWB underwater glider, the planform is defined with Bezier curve and linear line, and the section is defined with symmetrical airfoil NACA 0012. Computational investigations are carried out to study the hydrodynamic performance of the glider using the commercial Computational Fluid Dynamics (CFD) code Fluent. The Kriging-based genetic algorithm, called Efficient Global Optimization (EGO), is applied to hydrodynamic design optimization. The result demonstrates that the BWB underwater glider has excellent hydrodynamic performance, and the lift to drag ratio of initial design is increased by 7% in the EGO process.

• International Journal of Naval Architecture and Ocean Engineering
• /
• v.9 no.6
• /
• pp.693-704
• /
• 2017

Blended-Wing-Body Underwater Glider (BWBUG), which has excellent hydrodynamic performance, is a new kind of underwater glider in recent years. In the shape optimization of BWBUG, the lift to drag ratio is often used as the optimization target. However this results in lose of internal space. In this paper, the energy reserve is defined as the direct proportional function of the internal space of BWBUG. A motion model, which relates gliding range to steady gliding motion parameters as well as energy consumption, is established by analyzing the steady-state gliding motion. The maximum gliding range is used as the optimization target instead of the lift to drag ratio to optimizing the shape of BWBUG. The result of optimization shows that the maximum gliding range of initial design is increased by 32.1% though an Efficient Global Optimization (EGO) process.

• International Journal of Naval Architecture and Ocean Engineering
• /
• v.12 no.1
• /
• pp.455-467
• /
• 2020

Shape design optimization for Blended-wing-body Underwater Gliders (BWBUGs) is usually computationally expensive. In our previous work, a simplified shape optimization (SSO) strategy is proposed to alleviate the computational burden, which optimizes some of the Sectional Airfoils (SAs) instead of optimizing the 3-D shape of the BWBUG directly. Test results show that SSO can obtain a good result at a much smaller computational cost when three SAs are adopted. In this paper, the performance of SSO is investigated with a different number of SAs selected from the BWBUG, and the results are compared with that of the Direct Shape Optimization (DSO) strategy. Results indicate that SSO tends to perform better with more SAs or even outperforms the DSO strategy in some cases, and the amount of saved computational cost also increases when more SAs are adopted, which provides some reference significance and enlarges the applicability range of SSO.

• International Journal of Naval Architecture and Ocean Engineering
• /
• v.10 no.4
• /
• pp.439-449
• /
• 2018

In this paper, multi-objective optimization of a multi-bubble pressure cabin in the underwater glider with Blended-Wing-Body (BWB) is carried out using Kriging and the Non-dominated Sorting Genetic Algorithm (NSGA-II). Two objective functions are considered: buoyancy-weight ratio and internal volume. Multi-bubble pressure cabin has a strong compressive capacity, and makes full use of the fuselage space. Parametric modeling of the multi-bubble pressure cabin structure is automatic generated using UG secondary development. Finite Element Analysis (FEA) is employed to study the structural performance using the commercial software ANSYS. The weight of the primary structure is determined from the volume of the Finite Element Structure (FES). The stress limit is taken into account as the constraint condition. Finally, Technique for Ordering Preferences by Similarity to Ideal Solution (TOPSIS) method is used to find some trade-off optimum design points from all non-dominated optimum design points represented by the Pareto fronts. The best solution is compared with the initial design results to prove the efficiency and applicability of this optimization method.