Proceedings of the Thirty-second (2022) International Ocean and Polar Engineering Conference
Shanghai, China, June 5–10, 2022
Copyright © 2022 by the International Society of Offshore and Polar Engineers (ISOPE)
ISBN 978-1-880653-81-4; ISSN 1098-6189

www.isope.org

Multi-Objective Optimization Design for DARPA Suboff Based on Kriging Model
Jianwei Wu, Yun Wang, Weihua Shi, Qingjie Meng and Haixiong Zhu*
Wuhan Second Ship Design and Research Institute, Wuhan, Hubei, People’s Republic of China*Corresponding author

be efficient, and they have been presented in a huge body of literature.

ABSTRACTCao et al. (2007) present a multidisciplinary optimization procedure,
and the results demonstrated multidisciplinary optimization (MDO)
approach was suitable for the design of underwater vehicle. Chen (2008)
used a multidisciplinary design optimization technology to analyze thestructural-acoustic optimization problem for the underwater vehicle,
and the improvements of structural-acoustic performance weresignificant. Tahara et al. (2011) took a fast catamaran as the initialdesign and the numerical optimization was performed based on anURANS solver, a potential flow solver and global optimization (GO)algorithms. The HSSL-B geometry was successfully optimized and an
experimental campaign was carried out for validation. Li et al. (2017)
optimized the missile vertical launcher of underwater vehicle based on
response surface method and multi-objective optimization algorithm,
and the impact resistance of the vertical launcher increased by 14.9%
while the total weight decreased by 2.1%. Dong et al. (2018) present a
numerical optimization procedure to reduce the strength of wake flow
feature and radar scattering feature for underwater vehicle. Surrogate
model was employed to reduce the computational efforts, and theresults presented in the work confirmed the validity and effectivenessof this optimization procedure.

A numerical multi-objective optimization procedure is proposed here to
improve the stealth performance for underwater vehicle. In this paper,
DARPA Suboff is adopted as the preliminary design, and the two
objective functions have been chosen as the wake flow feature andacoustic target strength. Firstly, several characteristic parameters arechosen to define the geometry of sail and hull under some design
constraints, and a series of realistic design schemes for underwater
vehicle will be generated during the optimization by changing the valueof the parameters. Secondly, Kriging models are established based on
OLHS samples and corresponding numerical predictions to use as
surrogates for optimization process. To ensure the precision ofsurrogate model, CFD method and planar elements method areimplemented to predict the wake flow feature and acoustic target
strength respectively. The amount of computation resulting from multidisciplinary optimization can be substantially reduced by theapplication of Kriging model. Thirdly, a multi-objective geneticalgorithm, NSGA- Ⅱ , is adopted to produce Pareto-optimal front.
Eventually, the optimal design schemes with obvious stealthperformance improvement are obtained and verified by high-precisionevaluation method.
KEY WORDS: DARPA Suboff, Multi-Objective Optimization Design,
wake flow feature, acoustic target strength.

INTRODUCTION
With the rapid development of detection technology, stealthperformance has become one of the most important properties in theconfiguration design of underwater vehicle. Hence, it is of greatsignificance to optimize the shape of underwater vehicle to reduce itswake flow feature as well as acoustic target strength. Multi-objective
optimization computations are conducted to provide a better design ofunderwater vehicle with excellent stealth performance. In the past, alarge number of alternative designs were proposed according to theexperience of ship designers and tested by model experiments before
the final design was obtained, obviously, this method is in low effectand uneconomical. At present, various optimization platforms based on
advanced multi-disciplinary design methods are applied and proved toIn this paper, DARPA Suboff is adopted as the initial design, and thetwo objective functions have been chosen as the wake flow feature andacoustic target strength. The geometry of hull form is modified basedon FFD method while the geometry of sail is defined and deformed byseveral feature curves of NURBS surfaces. One of the accurate
approximation models, Kriging model, is constructed based on thesamples given by OLHS method and predicted by CFD method andPlanar Elements method. With respect to optimizer, a multi-objective
genetic algorithm, NSGA- Ⅱ , is adopted to produce Pareto-optimalfront. Eventually, the optimal designs of underwater vehicle withobvious stealth performance improvements are obtained and verified.

MODIFICATION OF GEOMETRY
Appropriate and effective surface modification methods are crucial tooptimization process. In this paper, FFD approach (Sederbergm andParry, 1986) is chosen to perform the deformation for hull form
globally, and the shape of sail is determined by feature curves of1150