基于SBD技术的船舶水动力构型优化设计研究
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摘要
将最优化技术引入船舶设计领域,并与先进的CFD技术成功结合,发展形成的SBD(Simulation Based Design)技术为船型优化设计和构型创新打开了崭新的局面,在国际船舶研究设计领域引起了广泛关注,并已成为当前国际船舶设计领域研究的前沿重点。本文对国内外研究成果进行了归纳评述,并对SBD技术的概念、内涵进行了深入地剖析,重点突破了船体几何建模与重构、全局最优化技术、综合集成等关键技术,结合高精度CFD数值预报方法(RANS),建立了以精细数值评估为特征的船型优化设计框架,推动了船型逆向设计模式的发展,并以快速性能最优为主要目标开展了实用船型的优化设计。
     首先,重点研究了粒子群全局优化算法,并对其初始化方法和权重系数进行了改进,为船型优化设计问题的求解提供了一种有效、快捷的科学方法。在此基础上,以系列模型试验数据库作为支撑,结合势流切片理论及经验公式,采用Lackenby变换几何重构方法,建立了可靠性高、响应快速、基于改进粒子群全局优化算法的舰船综合航行性能多目标全局优化设计模块。并针对舰船快速性、耐波性、操纵性三项性能,开展了舰船构型多目标全局优化设计,获得了三项性能在不同权重条件下的Pareto最优解集,充分验证了改进的粒子群全局优化算法的能力。
     其次,重点突破了复杂船体几何建模与重构技术,建立了Bezier Patch局部几何重构方法和FFD(Free-Form Deformation)整体几何重构方法,探讨了海量数值计算的简约策略,解决了复杂网格自动重生成问题,实现了高精度评估器在船型优化设计自动化流程中的应用,突破综合集成技术,构建了具有自主知识产权的基于精细CFD技术的船型优化设计框架,为后续开展船型优化设计提供了软件平台。
     再次,以典型的DTMB5415作为研究对象,设计航速下的总阻力作为优化目标,采用建立的优化设计框架对其球艏构型进行了优化设计。结果表明最优设计方案的总阻力收益十分显著,验证了本文建立的船型优化设计框架的有效性。针对中高速船型对阻力性能的影响与航速密切相关的特点,采用试验设计和响应面模型的简约策略,开展了DTMB5415球艏构型多个航速下的优化设计。结果表明最优设计方案在设计航速总阻力均减小6%左右,在整个航速范围内,总阻力最大收益达到6.73%,充分展示了基于SBD技术的船型优化设计的优越性。
     最后,针对具有挑战性的低速肥大型船,选择两艘性能优异的散货船船型作为研究对象,采用SBD技术以总阻力和桨盘面流场品质作为目标函数分别对其进行了优化设计。6600DWT散货船艉部构型优化设计结果表明:在满足工程约束条件的情况下,最优设计方案总阻力的收益十分显著。44600DWT散货船整体构型优化设计结果表明:最优方案在整个傅氏数范围内的减阻效果均十分明显(在5%左右),再计及尾部流场质量改善带来的推进效率的收益,可以预计,综合节能效果将会进一步扩大。两艘散货船优化设计的成功实践,证实了“以精细数值评估优化为特征的船型设计模式”用于难度极大的低速肥大型船体优化设计同样具有明显的优势,该设计模式将为船舶构型创新及绿色节能船型研发提供先进的研究手段和有力的技术支撑。
With the rapid development of computer technology and the continuous improvement ofoptimization theory, optimization techniques have been introduced into the field of ship design.Optimization algorithms and advanced CFD techniques are successfully integrated together intowhat is known as Simulation-Based Design (SBD) techniques, which opens a new situation forhull-form optimization design and configuration innovation. A worldwide attention has beenconcentrated since the SBD techniques was presented. In this paper, numerous internationalresearches are summarized and reviewed. And fundamental elements of the SBD techniques aredescribed and crucial components are analyzed profoundly. Foucus is on breaking through keytechnologies as hull geometry modification and reconstruction, global optimization algorithms,and codes integration. Combined with high-fidelity CFD codes (on RANS), an automatichull-form design optimization platform is established, and the hull-form reverse design pattern isdeveloped. Based on that, the application of the platform in the hull-form optimization design isillustrated by three practical examples in detail.
     First, the global particle swarm optimization algorithm (PSO) is studied, and itsinitialization method and the inertia weight factor are improved, which provides effective andefficient scientific methods for solving the hull-form optimization design problem. Based on that,supported by series model test database and combined with potential theory and empiricalformula, a multi-objective global optimization system with high reliability and fast response forship hydrodynamic performance is established at the initial design stage. In the procedure, thehull geometry is modified automatically by Lackenby method. Three objective functions,admiralty coefficient, percentage of time and non-dimensional turning diameter, are chosen ascriteria for evaluating the ship performance on powering, seakeeping and maneuveringrespectively. Specially, some valuable empirical formulae derived from extensive model testsdata of parent ships, strip theory and empirical formula are used to calculate the objectivefunctions.
     Furthermore, two geometry modeling methods to modify the hull surface are developedduring optimization cycles, which are Bezier Patch method and Free-Form Deformation methodto represent a complex geometry and to satisfy different design requirements. The high-fidelityCFD solvers based on RANS, complex grid automatical regeneration method and approximationstrategy are integrated into the hull-form design optimization software platform with independentintellectual property.
     Next, an example of the optimization platform application for a surface combatant hulloptimization is illustrated. In the procedure, the improved PSO algorithm is adopted forexploring the design space. The objective function, namely, the total resistance, is assessed byRANS solvers. The results verify the feasibility of the platform by showing that the decrease ofthe total resistance for the optimal design is very significant. Subsequently, the multi-objectiveoptimization design for the bulb of DTMB5415is carried out; the resistance of three different speeds are selected as the three objective functions. In order to reduce the computational cost, theapproximation strategy based on experimental design and response surface model is adopted.The results show that the reduction of the total resistance is about6%for the optimized hullformat the design speed (Fn=0.28),while the numerical noise are clearly smaller than this value. Itmay be of interest to look at off-design conditions too: in the entire speed range, a maximumreduction of about6.73%is obtained at Fn=0.21. The given combatant design optimizationexample demonstrates the practicability and superiority of the proposed SBD technique for themid-high speed ship.
     Finally, selecting the total resistance and the quality of propeller disk wake field asobjective functions, two bulk carriers are optimized by optimization platform. The6600DWTbulk carrier’s optimization results present an obvious reduction of resistance for the optimalsolution. This is a promising result for the bulk carrier design, which will be very difficult to getby traditional design approaches guided only by the experience of the designers. The44600DWTbulk carrier’s optimization results show that the decrease of the total resistance is significant inthe entire speed range, with a reduction of about5%, taking into account gains of propulsionefficiency produced by the improvement of wake field, and the comprehensive energy-savingeffect will be further expanded. This is very large improvement in the resistance performance oftwo bulk carriers, considering the small modifications allowed and the good initial performancesof the original hull. And it indicates that the SBD techniques are very attractive for low carbonshipping design.
引文
[1] Campana E F, Peri D, Tahara Y, Kandasamy M, Stern F. Numerical Optimization Methods for ShipHydrodynamic Design, SNAME Annual Meeting.2009[C].
    [2] B.Y. Li, S. Chen, Computation of carbon footprint for shipping, China Ship Survey10(2010)48-51.
    [3]沈泓萃. ITTC及船舶水动力学研究方向与重点分析[C].中国杭州:中国造船工程学会,2008.373-399.
    [4]赵峰,李胜忠,杨磊,刘卉.基于CFD的船型优化设计研究进展综述[J].船舶力学,2010,14(7):812–821.
    [5] Maisonneuve J J, Harries S, Marzi J, Raven H C, Viviani U, Piippo H. Toward optimal design of shiphull shapes. In:8th international marine design conference, IMDC03, Athens,2003[C].
    [6] Http://www.virtual_basin.org.[EB/OL]
    [7]李胜忠,李斌,赵峰,李力枫. VIRTUE计划研究进展综述[J].船舶力学,2009,13(4):662–675.
    [8] Final Report and Recommendations to the26th ITTC.26th International Towing Tank Conference. Riode Janeiro, Brazil,28August-3September,2011[C].
    [9] Hino T, Kodama Y, Hirata N. Hydrodynami c shape optimization of ship hull forms using CFD.Proceedings,3rd Osaka Colloquium on Advanced CFD Applications to Ship Flow and Hull FormDesign,1998[C], Osaka Prefecture Univ. and Osaka Univ., Japan.
    [10] Tahara Y, Himeno Y. An application of computational fluid dynamics to tanker hull form optimizationproblem. Proceedings,3rd Osaka Colloquium on Advanced CFD Applications to Ship Flow and HullForm Design,1998[C], Osaka Prefecture University and Osaka University, Japan.
    [11] Hino T. Shape optimization of practical ship hull forms using Navier-Stokes analysis. Proceedings,7thInternational Conference on Numerical Ship Hydrodynamics,1999[C], Names, France.
    [12] Janson C, Larsson L. A method for the optimization of ship hulls from a resistance point of view.Proceedings,21st Symposium on Naval Hydrodynamics,1996[C], Trondheim, Norway.
    [13] Day A H, Doctors L J. The survival of the fittest-evolutionary tools for hydrodynamic design of shiphull form [J]. Trans. Royal Inst. Naval Architects,2000,182-197.
    [14] Harries S. Parametric Design and Hydrodynamic Optimization of Ship Hull Forms [D]. Germany:Institut für Schiffs-und Meerestechnik, Technische University Berlin,1998.
    [15] Huan J, Huang T T. Sensitivity Analysis Methods for Shape Optimization in Nonlinear Free SurfaceFlow. Osaka Prefecture Univ. and Osaka Univ. Japan: Proceedings3rd Osaka Colloquium on AdvancedCFD Applications to Ship Flow and Hull Form Design,1998[C].
    [16] Yang C, Noblesse F, Lohner R. Practical hydrodynamic optimization of a trimaran. SNAMETransactions,2001[C].
    [17] Ragab S A. An adjoint formulation for shape optimization in free-surface potential flow [J]. Journal ofShip Research,2001,45(4),269-278.
    [18] Saha G, Suzuk K and Kai H. Hydrodynamic optimization of ship hull forms in shallow water [J].Journal of Marine Science and Technology,2004,9:51-62.
    [19] Saha G, Suzuki K, Kai H. Hydrodynamic optimization of a catamaran hull with large bow and sternbulbs installed on to center plane of the catamaran [J]. Journal of Marine Science and Technology,2005,10:32-40.
    [20] Harries S. and Abt C.Formal hydrodynamic optimization of a fast mono-hull on the basis of parametrichull design. In5th International Conference on Fast Sea Transportation,1999[C], Seattle. WA.
    [21] Chen P. Huang C. An inverse hull design approach in minimizing the ship wave [J]. Ocean Engineering,2004,31:1683-1712.
    [22] Tahara Y, Patterson E, Stern F, Himeno Y. Flow-and wave-field optimization of surface combatantsusing CFD-based optimization methods. Val de Reuil, France: Proceedings,23rd ONR Symposium onNaval Hydrodynamics, September,2000[C].
    [23] Valorani M, Peri D, Campana E F. Efficient strategies to design optimal ship hulls. AIAA8thMultidisciplinary Analysis and Optimization Conf.,2000[C], AIAA2000-4731.
    [24] Peri D, Rossetti M, Campana E F. Design optimization of ship hulls via CFD techniques [J]. Journa ofShip Research,2001,45(2):140–149.
    [25] Valorani M, Peri D, Campana E F. Sensitivity Analysis Techniques for Design Optimization Ship Hulls[J]. Optimization and Engineering,2002.4(4):337-364.
    [26] Campana E F. Peri D, Bulgarelli U P. Optimal Shape Design of a Surface Combatant with ReducedWave Pattern. Symposium on “Reduction of Military Vehicle Acquisition Time and Cost throughAdvanced Modelling and Virtual Simulation”, Paris, France,2002.
    [27] Peri D, Campana E F. Multidisciplinary Design Optimization of a Naval Surface Combatant [J]. Journalof Ship Research,2003,47(1):1–12.
    [28] Peri D, Campana E F. High-Fidelity Models and Multiobjective Global Optimization Algorithms inSimulation-Based Design [J]. Journal of Ship Research,2005,49(3):159-175.
    [29] Campana E F, Peri D, Tahara Y, Stern F. Comparison and validation of CFD based local optimizationmethods for surface combatant bow. Canada: The25th Symposium on Naval Hydrodynamics,2004[C].
    [30] Tahara Y, Peri D, Campana E F, Stern F. Computational fluid dynamics-Based multiobjectiveoptimization of a surface combatant [J]. Marine Science and Technology,2008,13(2):95-116.
    [31] Campana E F, Peri D, Tahara Y, Kandasamy M, Stern F. Numerical Optimization Methods for ShipHydrodynamic Design. SNAME Annual Meeting,2009[C].
    [32] Peri D, Campana E F. Variable Fidelity and Surrogate Modeling in Simulation-Based Design. Seoul,Korea:27th Symposium on Naval Hydrodynamics.2008[C].
    [33] Peri D. Self-Learning Metamodels for Optimization [J]. Journal Ship Research.2009,56(3):94-108.
    [34] Pinto A, Peri D, Campana E F. Multiobjective Optimization of a Containership Using DeterministicParticle Swarm Optimization[J]. Journal of Ship Research,2007,51:217–228.
    [35] Campana E F, Liuzzi D, Lucidi S, Peri D, Piccialli V. New global optimization methods for ship designProblems [J]. Optimization Engineering.2009.
    [36] Zalek S. F. Multi-criterion Evolutionary Optimization of Ship Hull Forms for Propulsion andSeakeeping [D]. Michigan University.2007.
    [37] Peri D, Campana E F. Simulation Based Design of Fast Multihull Ship[C].26th Symposium on NavalHydrodynamics. Rome, Italy,2006.
    [38] Campana E F, Peri D. Shape optimization in ship hydrodynamics using computational fluid dynamics[J]. Computer Methods in Applied. Mechanics and Engineering.2006.196:634–651.
    [39] Tahara Y, Peri D, Campana E F, Stern F. Single and Multiobjective Design Optimization of a FastMultihull Ship: numerical and experimental results.27th Symposium on Naval Hydrodynamics.2008[C].
    [40] Kim H, Yang C, Chun H H. A Combined Local and Global Hull Form Modificati on Approach forHydrodynamic Optimization.28th Symposium on Naval Hydrodynamics,2010[C].
    [41] Kim H. Multi-Objective Optimization for Ship Hull Form Design [D]. George Mason University,2009.
    [42] Diez M, Fasano G, Peri D, Campana E F. Multidisciplinary Robust Optimization for Ship Design.28thSymposium on Naval Hydrodynamics,2010[C].
    [43] Han S, Lee Y S, Choi Y B. Hydrodynamic hull form optimization using parametric models [J]. JournalMar Sci Technol,2012.
    [44]卢晓平,陈军.穿浪双体船的船型优化[J].船舶工程.2003,25(1):18-21.
    [45]梁军,许劲松,谢杰等.基于设计空间探索的型线自动优化.中国杭州:中国造船工程学会,2008[C].50-63.
    [46]杨卓懿,庞永杰,秦再白.参数化艇型最优化设计研究[J].舰船科学技术,2009.31:8.
    [47]程成.基于iSIGHT的螺旋桨优化系统的开发及运用研究[D].无锡,中国船舶科学研究中心硕士论文,2007.
    [48]叶茂盛.最小阻力船型优化方法研究[D].大连理工大学,2007.
    [49]张宝吉.船体线型优化设计方法及最小阻力船型研究[D].大连理工大学,2009.
    [50]张宝吉,马坤,纪卓尚.基于非线性规划法的最小阻力船型优化设计[J].武汉理工大学学报,2010,34(2).
    [51]张宝吉,马坤,纪卓尚.基于遗传算法的最小阻力船型优化设计[J],船舶力学,2011, l5(4):325-331.
    [52]冯佰威,刘祖源,詹成胜,常海超,程细得.基于CAD/CFD的船型阻力性能优化设计.2010全国现代制造集成技术学术会议论文集,2010[C].221-228.
    [53]冯佰威,刘祖源,詹成胜,常海超.船舶CAD/CFD一体化设计过程集成技术研究[J].武汉理工大学学报.2010,34(4):649-651.
    [54]邱辽原,谢伟,姜治芳,冯佰威,刘祖源.基于参数化CAD模型的船型阻力/耐波性—体化设计[J].中国舰船研究,2011,6(1):18-29.
    [55]杨铭,毛筱菲.基于iSIGHT的船型耐波性优化研究[J].船海工程,2011,40(3):62-65.
    [56]钱建魁,毛筱菲,王孝义,恽秋琴.基于CFD和响应面方法的最小阻力船型自动优化[J].船舶力学,2012,16(1-2):36-43.
    [57]周玉龙,杨松林,奚炜,陈淑玲,张火明.基于遗传-混沌算法的船舶水动力学性能综合优化研究[J].舰船科学技术,2005,27(4):18-21.
    [58]谢宜,王长雷.基于小生境遗传算法的单体船船型参数优化[J].舰船科学技术,2011,33(3):35-38.
    [59] Wolpert, D h, Macteady, W G. No free lunch theorems for optimization [J]. IEEE Transaction onEvolutionary Computation,1997,1(1):67-82.
    [60] Sheng-zhong Li, Lei Yang, Feng Zhao, Bin Zhou, Ming-dao Cheng. A practical global optimizationmethod for ship integrated hydrodynamic performance design. APHydro,2010[C]:32-37.
    [61]郭科,陈聆,魏友华.最优化方法及其应用[M].北京:高等教育出版社,2007。
    [62] Srinivas N, Deb K. Multi-objective function optimization using nondominated sorting geneticalgorithms [J]. Evolutionary Computation,1995,2(3):221-248.
    [63] Deb K, Agrawal S,Pratap A, et al. A fast elitist nondominated sorting genetic algorithm formultl-objeotive optimization:NSGA-II. Proc of the Parallel Problem Solving from Nature VI Conf,Paris,2000[C]:849-858.
    [64] Deb K, Pratap A, Agarwal S, Meyarivan T. A fast and elitist multiobjective genetic algorithm:NSGA–II [J]. IEEE Transactions on Evolutionary Computation,2002,6(2):182-197.
    [65] Kennedy J, Eberhart R C. Particle swarm optimization. Proc. IEEE Intl. Conf. on Neural Networks,1995[C], IV,1942-1948. Piscataway, NJ: IEEE Service Center.
    [66] Kennedy J, Eberhart R C. A discrete binary version of the particle swarm algorithm. Proc.1997Conf.on Systems, Man, and Cybernetics,1997[C],4104–4109. Piscataway, NJ: IEEE Service Center.
    [67] Riccardo P. Kennedy J. An overview of particle swarm optimization [J]. Swarm Intell.2007,1:33-57.
    [68] www.swarmintelligence.org
    [69]王俊伟.粒子群优化算法的改进及应用.[D].东北大学,2006.
    [70]张文爱,刘丽芳,李孝荣.基于粒子进化的多粒子群优化算法[J].计算机工程与应用,2008,44(7):51-53.
    [71] Ali M M, Kaelo B. Improved particle swarm algorithms for global optimization [J]. AppliedMathematics and Computation.2008,196:578-593.
    [72] Langdon W B, Poli R. Evolving problems to learn about particle swarm and other optimizers. In: Proc.CEC-2005[C].2005,1:81-88.
    [73] Clerc M. Stagnation analysis in particle swarm optimization or what happens when nothing happens.Online at http://clerc.maurice.free.fr/pso/.
    [74] Ling S H, Iu H. C F, Leung H F, et al. Improved hybrid particle swarm optimized wavelet neuralnetwork for modeling the development of fluid dispensing for electronic packaging [J]. IEEE Trans. Ind.Electron.,2008,55(9):3447-3460.
    [75] Richards M, Ventura D. Choosing a starting configuration for particle swarm optimization. In: Proc.IEEE Int. Joint. Conf. Neural Network,2004[C],3:2309–2312.
    [76]薛明志,左秀会,钟伟才等.正交微粒群算法[J].系统仿真学报,2005,17(12):2908-2911.
    [77]刘衍民,赵庆祯,牛奔.基于正交设计的多目标粒子群算法[J].计算机应用研究,2011,28(1):72-74.
    [78] Clerc M. Initialisations for particle swarm optimization. Online at http://clerc.maurice.free.fr/pso/,2008.
    [79] Campana E F, Fasano G, Pinto A. Dynamic system analysis and initial particles position in particleswarm optimization. In: Proc. IEEE Swarm Intell. Symp.2006[C],202-209.
    [80] Hu X, Shi Y, Eberhart R. Recent advances in particle swarm. In: Proc. IEEE Congr. Evol. Comput,2004[C],1:90-97.
    [81] Eberhart R, Shi Y. Particle swarm optimization: Developments, applications and resources. in: Proc.IEEE Congr. Evol. Comput,2001[C],1(1):81-86.
    [82] Eberhart R, Shi Y, Kennedy J. Swarm Intelligence [M]. San Mateo, CA: Morgan Kaufmann,2001.
    [83] Shi Y, Eberhart R. A modified particle swarm optimizer. Proceedings of the IEEE Congress onEvolutionary Computation.1998[C],69-73.
    [84] Kennedy J. Small worlds and mega-minds: Effects of neighborhood topology on particle swarmperformance. In: Proc. IEEE Congr. Evol. Comput,1999[C],3:1931–1938.
    [85] Suganthan P N. Particle swarm optimizer with neighbourhood operator. In: Proceedings of the IEEECongress on Evolutionary Computation (CEC), Piscataway, NJ,1999[C],1958-1962.
    [86]闫元元,高兴宝,周喜虎,基于变异和交叉的改进粒子群算法[J].陕西科技大学学报,29(4),2011,121-124.
    [87] Sierra M R,Coello A C. Improving PSO-based multi-objective optimization using crowding,mutation and ε-dominance. Proc of the3rd International Conference on Evolutionary Multi-CriterionOptimization.2005[C]:505-519.
    [88] Santos Coelho L, Herrera B M. Fuzzy identification based on a chaotic particle swarm optimizationapproach applied to a nonlinear yo-yo motion system [J]. IEEE Trans. Ind. Electron.,2007,54(6):3234-3245.
    [89]郭乙木,王双连,蔡新.工程优化——原理、算法与实施[M].北京:机械工业出版社,2008.9.
    [90] Julio E A, Richard M E, Jonathan E F. A MOPSO algorithm based exclusively on pareto dominanceconcepts. In Third International Conference on Evolutionary Multi-Criterion Optimization, EMO2005[C],459–473, Guanajuato, M′exico,2005. LNCS3410, Springer-Verlag.
    [91] Brown A, Salcedo J. Multiple-Objective Optimization in Naval Ship Design[J]. Journal of ShipResearch.2000.
    [92] Zalek S F, Parsons M G, Beck R F. Naval Hull Form Multicriterion Hydrodynamic Optimization for theConceptual Design Phase [J]. Journal of Ship Research,2009,53(4):199-213.
    [93] Li X B. Multiobjective Optimization and Multiattribute Decision Making Study of Ship's PrincipalParameters in Conceptual Design [J]. Journal of Ship Research,2009,53(2):83-92.
    [94] Tahara Y, Tohyama S, Katsui T. CFD-Based Multi-Objective Optimization Method for Ship Design [J].International J. Numerical Methods in Fluids,2006,52:449-527.
    [95] Liu D, Tan K C, et al. A multi-objective memetic algorithm based on particle swarm optimization[J].IEEE Transactions on Systems, Man and Cybernetics,2007,37(1):42-50.
    [96] Lackenby H. On the Systematical Geometrical Variation of Ship Forms. TINA.1950.
    [97]荣焕宗,华振洪,傅玲玲.用母型船变换方法设计船舶型线.船舶[J],1991,45-52.
    [98]张军,程明道.船体设计水线面变换方法.船舶力学[J],1998,2(1):12-19.
    [99]张军,沈泓萃.一种实用的水线面变换方法.中国造船[J],1997,139(4):7-11.
    [100]杨磊,李胜忠,赵峰.基于CFD的船型优化设计内涵及关键技术分析.第二十二届全国水动力学研讨会,四川成都,2010[C].
    [101]李雷雷.船体型线自动生成及优化研究[D].华中科技大学硕士学位论文.2009.
    [102] Perry E, Balling R. A New Morphing Method for Shape Optimization [J]. AIAA-98-2896,1998.
    [103]冯佰威,刘祖源,詹成胜,常海超等.基于CFD的船型自动优化技术研究.2008年船舶水动力学学术会议,2008[C],杭州.
    [104] JAMSHID A., Geometry and Grid/Mesh Generation Issues for CFD and CSM Shape Optimization [J].Optimization and Engineering.2005,6:21–32.
    [105]张弛.基于参数法的船型生成与水动力计算[D].武汉理工大学硕士论文.2009.
    [106]张萍,冷文浩等.船型参数化建模[J].船舶力学,2009,13(1):47-54.
    [107]张萍.船型参数化设计[D].江南大学博士学位论文.2009.
    [108]张弛,毛筱菲.基于参数法的船型自动生成.武汉理工大学学报[J].2009,33(4):675-678.
    [109] Kim H J, Chun H H. Optimizing using Parametric Modification Functions and Global OptimizationMethods.27th Symposium on Naval Hydrodynamics.2008[C], Seoul, Korea.
    [110]吉贝尔.德忙热,让皮尔.甫热著,王向东译.曲线与曲面的数学[M].北京:商务印书馆,2000年.
    [111] Sederberg T W, Parry S R. Free-Form Deformation of Solid Geometric Models [J]. Proc.SIGGRAPH’86, Computer Graphics,20(4):151-159.
    [112] Jamshid A. Aerodynamic Shape Optimization Based on Free-form Deformation [J]. AIAA.2004.
    [113]陆丛红.基于NURBS表达的船舶初步设计关键技术研究[D].大连理工大学博士学位论文,2005.
    [114]陆丛红,林焰,纪卓尚.船舶设计中的三维参数化技术[M].北京:国防工业出版社,2007.
    [115]徐岗,汪国昭,陈小雕.自由变形技术及其应用[J].计算机研究与发展,2010,47(2):344-352.
    [116]王志国.曲线曲面形状修改和变形关键技术研究[D].南京航空航天大学博士学位论文,2006.
    [117]朱心雄.自由曲线曲面造型技术[M].北京:科学出版社,2000.
    [118] Coquillart S. Extended free-form deformation:A sculpting tool for3D geometric modeling [J].Computer Graphics,1990,24(4):187-196.
    [119] Kalra P,Mangil A,Thalmann N M,et al. Simulation of facial muscle action based on rationalfree-form deformation [J]. Computer Graphics Forum,1992,11(3):59-69.
    [120] Lamousin H J,Waggenspack W N. NURBS-based free-form deformation [J]. IEEE ComputerGraphics and Applications,1994,14(6):95-108.
    [121] Boulic R,Capin T,Huang Z,et al. The humanoid environment for interactive animation of multipledeformation human characters [J].Computer Graphics Forum,1995,14(3):337-348.
    [122] Ronzheimer A, Post-Parameterization of complex CAD-Based aircraft-shapes using freeformdeformation.8th International Conference on Numerical Grid Generation in Computational FieldSimulations,2002[C], Honolulu, Hawaii, USA.
    [123]孙岩松.带几何约束条件的空间变形方法[D].大连理工大学硕士论文,2001.
    [124]盛振邦,刘应中.船舶原理[M].上海交通大学出版社.2004.
    [125]刘应中.船舶兴波阻力理论[M].国防工业出版社,2003.
    [126]李胜忠,赵峰.基于Bezier Patch几何重构技术的船舶球艏构型优化设计研究.第二十三届全国水动力学研讨会,2011[C],西安.496-502.
    [127] Patankar S V, Spalding D B. A calculation processure for heat, mass and momentum transfer inthree-dimensional parabolic flows. Int J Heat Mass Transfer,1972,15:1787-1806.
    [128] Jin R, Chen W, Simpson T W. Comparative studies of metamodelling techniques under multiplemodelling criteria [J]. Struct Multidisc Optim.23:1-13.
    [129] Simpson T W, Mauery T M, Korte J J, Mistree F. Comparison of response surface and Kriging modelsfor multidisciplinary design optimization [J]. AIAA1998,1:381-391.
    [130] Anthony A, Steven F. Overview of modern design of experiments methods for computationalsimulations [J]. AIAA.2003.
    [131] Douglas C. Montgomery著,傅珏生等译.实验设计与分析[M].北京:人民邮电出版社,2009年.
    [132]潘彬彬,多学科设计优化及其在舰船设计中的应用[D].中国船舶科学研究中心硕士论文,2009.
    [133] Minami Y, Hinatsu M. Multi objective optimization of ship hull form design by response surfacemethodology. Proceedings,24th Symposium on Naval Hydrodynamics,2002[C], Fukuoka, Japan.
    [134] Myers R H, Montgomery D C. Response Surface Methodology: Process and Product Optimiza-tionUsing Designed Experiments. John Wiley&Sons, Inc., New York, NY,1995[C].
    [135] iSIGHT manual.
    [136] Koch, P N, Wujek B. Facilitating probabilistic multidisciplinary design optimization using Krigingapproximation medels. AIAA,2002[C].
    [137] Baker C A, Watson L T, Grossman B, Haftka R T, Mason W H. Parallel Global Aircraft ConfigurationDesign Space Exploration. Proceedings of the8th AIAA/NASA/ISSMO,2000[C].
    [138] Schutte J F, Reinbolt J A, Fregly B J, Haftka R T, George A D. Parallel Global Optimization with theParticle Swarm Algorithm[J]. J. Numer. Meth. Eng.,2004,61(13),2296-2315.
    [139] http://www-unix.mcs.anl.gov/mpi
    [140] Aoyama Y, Nakano J. RS/6000SP: Practical MPI Programming, International Technical SupportOrganization.1999.
    [141]李胜忠.基于CFD的船型多目标优化设计框架的构建[R].702所科技报告,2009.12
    [142] DTMB5415模型阻力、波型测量试验报告.中国船舶科学研究中心.科技报告.2009.
    [143]6600DWT散货船快速性试验研究.中国船舶科学研究中心.科技报告.2011.
    [144]44600DWT散货船快速性试验研究.中国船舶科学研究中心.科技报告.2011.
    [145]赵峰,李胜忠,杨磊,吴乘胜.虚拟试验技术在船舶水动力性能设计中的应用及发展思考.702所建所60周年所庆纪念学术论文集,无锡,2011[C],24-32.
    [146] Shengzhong Li, Feng Zhao. An innovative hullform design technique for low carbon shipping[J].Journal of Shipping and Ocean Engineering,2012,2(1):28-35.
    [147]朱德祥,沈泓萃,洪方文,吴乘胜,赵峰.船模数值水池框架及其研究基础[J].水动力学研究与进展,A辑,2008,23(1):24~32.
    [148]沈泓萃,赵峰、蔡大明,创新发展我国舰船水动力性能虚拟试验集成系统——数值水池体系的设想.中国人民解放军总装备部科技委2007年年会论文集,2007[C].
    [149]颜开、赵峰、刘登成、程红霞、王志博.船舶水动力学的若干研究进展.第二届两岸船舶、海洋工程及环境工程水动力学研讨会,台湾.基隆.2009[C].
    [150]张志荣.水面舰船综合粘性流场的实用化CFD研究[D].无锡:中国船舶科学研究中心,2004.
    [151]黄少锋,张志荣,赵峰,李百齐.带自由面肥大船粘性绕流场的数值模拟[J].船舶力学,2008,12(1):46-53.

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