多学科设计优化在桁架式Spar平台概念设计中的应用研究
|
摘要
为适应我国国民经济发展和人民生活快速增长的需求,国家已计划在油气资源丰富的南海深水海域进行海洋油气勘探开发。然而,我国现有海洋生产平台的作业深度通常在500米以内,远远不能满足对于南海等深水海域油气开发的迫切需求。当今世界范围内用于深水油气开发的平台类型主要包括浮式生产储油系统、半潜式平台、张力腿平台以及Spar平台。针对Spar平台功能性强、稳定性好、性价比高和安全性好等优势,我国已在Spar平台方面投入了多年的研究,具有良好的技术储备。因此,Spar平台无疑将成为我国今后南海等深水海域油气勘探开发装备中的重点选择之一。
目前,国内船舶设计单位在包括Spar平台在内的新型海洋平台的设计研究方面,特别是最重要的概念设计方面,与国外先进企业相比存在着差距,加之Spar平台设计技术具有垄断性,我国研发Spar平台将面临很多困难。为了加快我国深海平台尤其是Spar平台的研发步伐,尽快突破Spar平台的设计技术瓶颈,我们应当在Spar平台概念设计的方法与理念上有所创新。
本文首先依据现有的海洋平台设计方法,探索性地进行桁架式Spar平台的概念设计和结构设计研究。现有的海洋平台设计理念是建立在改良母型平台基础上的串行设计方法,存在过多依赖设计专家经验和母型平台、设计成本高、概念设计结果无法充分反映平台整体性能等不足。由于Spar平台系统是具有高复杂度的工程系统,其设计过程需要涉及到的多个学科,包括水动力学,结构力学、工程应用和可靠性等,这些学科之间既相互联系、相互作用,也存在着相互冲突,使得桁架式Spar平台的概念设计呈现典型的“多学科”特点。现有的海洋平台设计模式很难真正从系统的角度出发,充分考虑设计变量及各性能间的相互影响,得到的设计结果往往只是满足设计要求的方案,并非真正的系统最优设计方案。
此外,船舶与海洋平台的设计发展必将走向数字化和虚拟化,如果在设计的初始阶段,就可以通过高度的系统集成,整体的把握各个方面的性能,无疑会给决策者带来巨大的帮助。而现有的海洋平台设计方法很难实现这一目标。要加快深海资源的开发,必须创新地提出新的设计理念和设计方法。
在上述背景下,本文作为上海市科委重大基础研究课题“深海单柱式平台关键动力特性的理论与实验研究”的一部分,引入在航空航天领域获得巨大成功的、用于解决复杂系统设计与优化问题的多学科设计优化方法(Multidisciplinary Design Optimization,简称MDO),探索其在Spar平台概念设计中的应用可行性。论文主要的研究过程分为四个阶段:
第一阶段:课题相关研究领域的综述
针对现有海洋平台设计方法存在的问题,阐述了多学科设计优化在海洋平台概念设计中应用的意义。综述了多学科设计优化的发展概况和主要技术,重点介绍了多学科设计优化技术的核心技术——多学科优化算法,并对几种主要的多级优化算法,从来源和目的、近似模型、分解技术、收敛性和工程性等五个方面进行了比较。在此基础上,根据船舶与海洋平台的设计特点,指出基于近似模型的协同优化算法和BLISS 2000算法是比较适合进行船舶和海洋平台多学科设计优化的多学科优化算法。
第二阶段:现有桁架式Spar平台的概念设计和结构设计方法
首先根据现有的海洋平台设计方法,探索性地开展了Spar平台概念设计研究。Spar平台的概念设计涉及到两方面的问题:一是设计方法、流程以及结构物的形式;二是水动力性能。与船舶以及其它海洋平台设计相类似,Spar平台的概念设计思想依然是一个不断调整完善的过程。本文归纳了桁架式Spar平台概念设计的基本流程,并结合具体设计要求,给出了桁架式Spar平台的设计实例,完成了包括甲板布置、重量控制、主尺度的确定、稳性校核和初步的水动力分析。
在概念设计基础上,进行了桁架式Spar平台的结构设计,主要工作包括:
⑴归纳了桁架式Spar平台各部分结构的设计思想,根据平台结构布置特点和载荷分配情况,完成了平台结构的设计;
⑵根据设计波方法,选定了两个典型波浪工况,采用三维势流理论,得到桁架式Spar平台的波浪诱导载荷,完成该桁架式Spar平台的总体结构强度分析。
⑶分别对在硬舱底部采用双层底结构和单层底结构两种结构形式对于底部甲板的影响进行了计算,结果表明双层底结构可以大幅降低硬舱底部甲板应力。由概念设计和结构设计得到的桁架式Spar平台将作为基准平台,与多学科设计优化结果进行比较。
第三阶段:多学科设计优化在桁架式Spar平台概念设计中的应用
成功应用多学科设计优化技术的关键是建立一个合理的多学科设计优化模型。为此,首先归纳了桁架式Spar平台的主要设计参数,包括平台主尺度参数、平台作业能力参数、经济性和可靠性参数。由于本文是针对Spar平台的概念设计进行优化,因而选择主尺度参数作为优化的设计变量。然后,根据均匀设计方法,对各设计变量划分水平和建立试验方案。
在建立桁架式Spar平台多学科设计优化框架时,如果在优化框架内的学科过多,常常会导致优化难以收敛;而如果所涉及的学科过少,又无法充分反应平台的特性,也就失去了多学科设计优化的意义。因此,本文提出了一种“折衷”的多学科建模方法,将影响Spar平台性能的学科划分为三个模块,即优化模块、约束模块和检验模块,对于分属不同模块的学科采用不同的方法处理。
其中,优化模块中的学科是业主和设计人员最关注的,其设计结果体现一个设计方案的质量,在多学科优化设计中,通常作为优化目标处理。约束模块中的学科是实现平台功能的前提条件,以约束条件的形式出现在优化模型中,参与到优化循环过程。一般,仅选择一个学科中关键性的参数作为比较不同设计方案的指标;检验模块中的学科不参与优化循环过程,是对优化设计方案的全面、准确的校核。文中,壳体结构重量作为优化模块的优化目标;平台垂荡运动和纵摇运动的短期预报值作为水动力学科的约束目标,平台在风暴状态下的完整稳性衡准数作为稳性学科的约束目标,平台在静水力和波频载荷作用下的硬舱底部甲板与桁架结合处的主应力作为结构学科的约束目标。为建立桁架式Spar平台的多学科设计优化模型,根据试验设计的安排,对各试验方案分别进行了水动力分析、稳性分析和结构强度分析。最后,介绍了作为检验模块的平台/锚泊系统耦合时域动力分析的方法和检验准则。
在此基础上,根据第一阶段中对于几种多学科设计优化算法比较的结果,选择基于近似模型的协同优化方法作为多学科设计优化算法,建立了桁架式Spar平台概念设计的协同优化数学模型,并进行了多学科优化分析。
第四阶段:桁架式Spar平台多学科优化模型的改进和优化
尽管近似模型可以大幅提高计算效率,然而其精度存在问题。因此,为提高多学科设计结果的可应用性,分别采用了两种改进方法:
(1)响应面更新策略——提出了响应面更新技术及实施程序,完成了基于响应面更新的桁架式Spar平台概念设计的协同优化过程。对各设计变量更新的历程和结果进行了初步的讨论。通过与基准平台的对比表明:优化设计方案的结构重量大幅降低,垂荡、稳性、强度等性能参数也有所提高,只有纵摇性能略微下降。证明了协同优化方法在桁架式Spar平台概念设计中应用的可行性以及多学科设计优化技术的优越性。通过百年一遇海况的时域耦合分析,验证了优化结果的合理性。
(2)可变复杂度方法——由于近似模型与真实模型间存在着差距,而响应面更新策略只是提高了响应面模型的精度,并没有体现真实模型的结果。因此,使用可变复杂度方法对第三阶段协同优化的结果进行修正。
针对可变复杂度方法需要大量初始计算以保证计算精度的缺点,结合上述两种改进方法的各自特点,提出了基于响应面更新的可变复杂度方法。研究表明:基于响应面更新的可变复杂度方法可以在较少初始样本计算的情况下,获得精度高的结果,这大大节省了初始计算的时间。
综上,论文在以下四个方面,做出了创新性的研究成果:
(1)提出了一套完整的桁架式Spar平台的概念设计方法和流程。开展了甲板布置、主尺度设计、稳性和水动力性能初步分析等概念设计工作。在此基础上,进行了桁架式Spar平台的结构设计,并应用设计波法对平台主要结构进行了强度校核。
(2)将多学科设计优化技术应用到桁架式Spar平台的概念设计中,通过对由现有设计方法和多学科设计优化方法得到的方案的对比,证明了多学科设计优化技术在桁架式Spar平台设计领域的适用性和优越性。
(3)提出将Spar平台设计中所涉及的学科进行分模块处理的多学科建模方法,即分为优化模块、约束模块和检验模块,针对分属不同模块的学科采用不同方法处理。不仅简化了多学科设计优化的计算流程,降低了优化收敛的难度,而且也可以保证模型的合理性和工程适用性。
(4)针对多学科设计优化中采用近似模型所存在的精度问题,分别采用了响应面更新策略和可变复杂度方法,来改进近似模型的精度和提高优化结果的可靠性。在此基础上,提出了基于响应面更新的可变复杂度方法,通过响应面的逐步更新提高精度,通过可变复杂度方法,减小近似模型与高精度模型间的差距。
本文四个阶段的研究成果和主要创新点,是对现行Spar平台概念设计方法的革新。将多学科设计优化方法更好地应用于Spar平台设计,进而促进海洋平台设计的数字化和虚拟化发展,对推动包括Spar平台在内的新型平台的自主研制与应用均具有一定的意义。
To meet the demand of national economic development and people’s fast-growing living condition, China has planned projects of exploiting oil and gas reserves in the South China Sea. However, the manufacturing capability of offshore production platforms in China is still below 500 meters water depth, far from the exploration requirement in South China Sea. Nowadays, the mainstream platforms used in deep water around the world include Floating Production Storage and Offloading System, Semi-submersible, Tension Leg Platform and Spar platform. Among them, Spar platforms have advantages in aspects of functionality, stability, cost-efficiency and safety. Besides, China has dedicated many years’study on Spar platform and has rich technical reserves. In such circumstances, Spar platform will become one of the major equipment for the gas and oil exploration for our country in the deep water, including South China Sea.
Presently, Chinese design capability is lagged behind the foreign design enterprises on the design of advanced ocean engineering units, especially in the conceptual design stage. In addition, the technical monopoly brings difficulties for us to develop Spar platforms. To speed up the pace of research on Spar platforms, and to break through the technical bottleneck, we should make innovation in both concept and method for the conceptual design of Spar platform.
Firstly, this thesis carries out a Truss Spar conceptual design and structural design task based on the current design method of offshore platforms. The current design method prevailing in China is the series process, based on the purpose to improve the parent unit. This design process has the shortcomings of relying too much on the parent unit and high design cost. Even worse, the results of conceptual design can hardly present the overall performances. The design of Spar platforms is a complex engineering problem involving many disciplines, such as hydrodynamics, structures, reliability, etc. These disciplines are both mutual interaction and contradictions, so the overall conceptual design of Spar platform is a typical Multidisciplinary Design Optimization (MDO) problem. However, the current design method can not consider the mutual influence among these disciplines sufficiently, so it often leads to a suboptimal design instead of optimal design.
Besides, the trend for ships and offshore platforms design is moving toward digitalization and virtualization, which will be beneficial for designers to acquire comprehensive information about the system to design in the early stage. Such trend demands the design method be able to highly integrate all the relevant disciplines. Obviously, it can hardly be realized by current method. To speed up the development of deep sea resources exploration, some breakthrough and innovation for the concept and method of design is in urgent need.
In such a situation, as a part of the project supported by the Science and Technology Commission of Shanghai Municipality, this thesis introduces Multidisciplinary Design Optimization, emerged from aeronautics and astronautics fields for complex engineering integrated optimization problems, and explores feasibility and applicability of MDO method to the conceptual design of Truss Spars. The thesis mainly consists of four parts.
Part I: Review about the related research area
The significance of applying MDO techniques in the Truss Spar conceptual design is stated. The definition, development and main research contents of MDO are reviewed. Four mainstream MDO algorithms are elaborated and compared in categories including origin and purpose, approximation models, decomposition, convergence and engineering applicability. Two algorithms– collaborative optimization based on approximation models and BLISS 2000 are regarded as suitable methods to apply MDO techniques in the design of ships and offshore platforms.
Part II: Study on the current conceptual design method and structural design method of Truss Spar
The current Truss Spar conceptual design method is explored. Two aspects are involved during the conceptual design: one deals with the design method and process, and the other concerns the hydrodynamic behavior. The conceptual design process of Spar platform can be described as an interactive flow. A Truss Spar conceptual design process including general arrangement, weight control and selection of main particulars is conducted. The stability and hydrodynamic performances for the Truss Spar are accessed. Based on the results of conceptual design, the structural design is conducted including:
(1) The design method for each part of Spar platforms is concluded and the structural scantling process is accomplished based on the main particulars, general arrangement and load distribution;
(2) The global strength analysis based on design wave methodology is accomplished. Two critical load criteria are selected and wave-induced load is obtained based on 3-D potential theory.
(3) The impact on bottom deck strength for two structural configurations– double bottom and single bottom is studied. The result shows the double bottom can reduces the stress of bottom deck of hard tank in great extent.
The Spar designed by current conceptual design method and structural design method is treated as baseline Spar for further comparison with the result of MDO.
Part III: Application of MDO on the Truss Spar conceptual design
The design parameters in the design of Spar platform, including main particulars, operation parameters, economics and reliability, are elaborated. Because the thesis focuses on the conceptual design, the main particulars are selected as design variables. Then the varying level of design variables are arranged by the theory of Design of Experiment (DOE) and corresponding design plans are determined by uniform design table.
One of the most significant factors for a successful application of MDO is to obtain a reasonable MDO model. A comprehensive MDO model, which includes every discipline related to Truss Spar, will make the optimization process difficult to converge; On the contrary, if only a few disciplines are included, the result of MDO can hardly represent the whole system and be impractical for engineering. To solve this contradiction, an innovative multidisciplinary modeling method is proposed. The disciplines related to Spar platform are divided into three modules: optimization module, constraint module and inspection module. Each module is treated as a different role during the optimization.
The optimization module is the main focus for platform owners and designers, and treated as optimization object function. The disciplines of constraint module are the characteristics of Spar platforms. These characteristics are precondition for the realization of platform functions, and treated as constraints in the optimization process. Only a few critical objectives for each discipline are selected and integrated in the optimization model. The inspection module is not involved in the optimization process and is used to provide a comprehensive assessment of the optimized design for checking.
In the thesis, the hull weight is treated as optimization object. The short term predictions of heave motion and pitch motion are selected as constraint objects for hydrodynamics discipline; the intact stability coefficient is selected as the constraint object for stability discipline; the von Mises stress of the connection zone of hard tank bottom deck with truss is selected as the constraint object for structure discipline. A hull/mooring coupled analysis in time domain is utilized as the method of inspection module. To set up the MDO model for Truss Spar, numerous hydrodynamic analyses, stability analyses and structural strength analyses are conducted for all design plans defined by DOE.
The Collaborative Optimization (CO) based on response surface method is selected as the MDO algorithm and the CO model for Truss Spar conceptual design is established for the first time. Then the CO optimization process is executed and an optimal design is achieved.
Part IV: The improvements of the Collaborative Optimization model
Although the approximation models can greatly improve the computational efficiency, the accuracy of the models may be not eligible. To enhance the accuracy of the approximation models and consequent optimization quality, two methods are used:
(1) Adaptive response surface method (ARSM)– The concept and procedure of ARSM is proposed. The collaborative optimization based on ARSM for Truss Spar conceptual design is accomplished and an optimal design solution, which satisfied all the constraints, is obtained. A discussion on the adaptive history for each design variables is made. The optimized results are compared with the baseline Spar. The comparison shows that the optimized solution by MDO achieves a lighter platform, and that the performances of heave response motion, stability coefficient and strength of the bottom deck are much improved. The only performance degradation for the optimized solution is the pitch motion, while the change is not significant. Finally, the time domain analysis based on 100-year storm of Gulf of Mexico is conducted and the results prove that the optimized design solution by MDO is feasible.
(2) Variable-complexity method (VCM)– Although ARSM can effectively improve the accuracy of approximation models, it fails to diminish the difference between approximation models and physical models. VCM is adapted to correct results of CO in part II by using the results of high-fidelity analysis tool.
However, VCM generally requires large number of calculations for initial sampling points to ensure precision. To overcome such a deficiency, an improved VCM method based on ARSM is proposed. The application results show that the improved VCM strategy can attain high accuracy with a small number of initial sampling.
In summary, four innovative accomplishments have been made in the thesis.
(1) A complete conceptual design process for Truss Spar is proposed and structural design is conducted. Design wave methodology is used to check the structural strength of the platform.
(2) MDO techniques are applied in Truss Spar conceptual design. The optimized design results by MDO show superiority in performances contrasting to the ones by the current design method. The feasibility of applying MDO techniques in the Spar platform is verified.
(3) An innovative multidisciplinary modeling method is proposed. The related disciplines for Spar platform are divided into three modules: optimization module, constraint module and inspection module. Each module is treated as different role during the optimization. Such modeling method decreases the convergence difficulty of optimization and relieves the computational burden. The rationality of the MDO model is also guaranteed.
(4) Adaptive response surface method and variable-complexity method are adopted to improve the accuracy of approximation models. An improved VCM method based on ARSM is proposed. The method shows advantages in both improving the accuracy of approximation models and diminishing the difference between approximation models and physical models.
The accomplishment of this thesis is an innovation to the current conceptual design method. A successful application of MDO in Truss Spar conceptual design will promote the development of digitalization and virtualization for offshore platforms, make a contribution to the independent research and application of offshore platforms, Spar platform included, in deep sea areas in China.
目前,国内船舶设计单位在包括Spar平台在内的新型海洋平台的设计研究方面,特别是最重要的概念设计方面,与国外先进企业相比存在着差距,加之Spar平台设计技术具有垄断性,我国研发Spar平台将面临很多困难。为了加快我国深海平台尤其是Spar平台的研发步伐,尽快突破Spar平台的设计技术瓶颈,我们应当在Spar平台概念设计的方法与理念上有所创新。
本文首先依据现有的海洋平台设计方法,探索性地进行桁架式Spar平台的概念设计和结构设计研究。现有的海洋平台设计理念是建立在改良母型平台基础上的串行设计方法,存在过多依赖设计专家经验和母型平台、设计成本高、概念设计结果无法充分反映平台整体性能等不足。由于Spar平台系统是具有高复杂度的工程系统,其设计过程需要涉及到的多个学科,包括水动力学,结构力学、工程应用和可靠性等,这些学科之间既相互联系、相互作用,也存在着相互冲突,使得桁架式Spar平台的概念设计呈现典型的“多学科”特点。现有的海洋平台设计模式很难真正从系统的角度出发,充分考虑设计变量及各性能间的相互影响,得到的设计结果往往只是满足设计要求的方案,并非真正的系统最优设计方案。
此外,船舶与海洋平台的设计发展必将走向数字化和虚拟化,如果在设计的初始阶段,就可以通过高度的系统集成,整体的把握各个方面的性能,无疑会给决策者带来巨大的帮助。而现有的海洋平台设计方法很难实现这一目标。要加快深海资源的开发,必须创新地提出新的设计理念和设计方法。
在上述背景下,本文作为上海市科委重大基础研究课题“深海单柱式平台关键动力特性的理论与实验研究”的一部分,引入在航空航天领域获得巨大成功的、用于解决复杂系统设计与优化问题的多学科设计优化方法(Multidisciplinary Design Optimization,简称MDO),探索其在Spar平台概念设计中的应用可行性。论文主要的研究过程分为四个阶段:
第一阶段:课题相关研究领域的综述
针对现有海洋平台设计方法存在的问题,阐述了多学科设计优化在海洋平台概念设计中应用的意义。综述了多学科设计优化的发展概况和主要技术,重点介绍了多学科设计优化技术的核心技术——多学科优化算法,并对几种主要的多级优化算法,从来源和目的、近似模型、分解技术、收敛性和工程性等五个方面进行了比较。在此基础上,根据船舶与海洋平台的设计特点,指出基于近似模型的协同优化算法和BLISS 2000算法是比较适合进行船舶和海洋平台多学科设计优化的多学科优化算法。
第二阶段:现有桁架式Spar平台的概念设计和结构设计方法
首先根据现有的海洋平台设计方法,探索性地开展了Spar平台概念设计研究。Spar平台的概念设计涉及到两方面的问题:一是设计方法、流程以及结构物的形式;二是水动力性能。与船舶以及其它海洋平台设计相类似,Spar平台的概念设计思想依然是一个不断调整完善的过程。本文归纳了桁架式Spar平台概念设计的基本流程,并结合具体设计要求,给出了桁架式Spar平台的设计实例,完成了包括甲板布置、重量控制、主尺度的确定、稳性校核和初步的水动力分析。
在概念设计基础上,进行了桁架式Spar平台的结构设计,主要工作包括:
⑴归纳了桁架式Spar平台各部分结构的设计思想,根据平台结构布置特点和载荷分配情况,完成了平台结构的设计;
⑵根据设计波方法,选定了两个典型波浪工况,采用三维势流理论,得到桁架式Spar平台的波浪诱导载荷,完成该桁架式Spar平台的总体结构强度分析。
⑶分别对在硬舱底部采用双层底结构和单层底结构两种结构形式对于底部甲板的影响进行了计算,结果表明双层底结构可以大幅降低硬舱底部甲板应力。由概念设计和结构设计得到的桁架式Spar平台将作为基准平台,与多学科设计优化结果进行比较。
第三阶段:多学科设计优化在桁架式Spar平台概念设计中的应用
成功应用多学科设计优化技术的关键是建立一个合理的多学科设计优化模型。为此,首先归纳了桁架式Spar平台的主要设计参数,包括平台主尺度参数、平台作业能力参数、经济性和可靠性参数。由于本文是针对Spar平台的概念设计进行优化,因而选择主尺度参数作为优化的设计变量。然后,根据均匀设计方法,对各设计变量划分水平和建立试验方案。
在建立桁架式Spar平台多学科设计优化框架时,如果在优化框架内的学科过多,常常会导致优化难以收敛;而如果所涉及的学科过少,又无法充分反应平台的特性,也就失去了多学科设计优化的意义。因此,本文提出了一种“折衷”的多学科建模方法,将影响Spar平台性能的学科划分为三个模块,即优化模块、约束模块和检验模块,对于分属不同模块的学科采用不同的方法处理。
其中,优化模块中的学科是业主和设计人员最关注的,其设计结果体现一个设计方案的质量,在多学科优化设计中,通常作为优化目标处理。约束模块中的学科是实现平台功能的前提条件,以约束条件的形式出现在优化模型中,参与到优化循环过程。一般,仅选择一个学科中关键性的参数作为比较不同设计方案的指标;检验模块中的学科不参与优化循环过程,是对优化设计方案的全面、准确的校核。文中,壳体结构重量作为优化模块的优化目标;平台垂荡运动和纵摇运动的短期预报值作为水动力学科的约束目标,平台在风暴状态下的完整稳性衡准数作为稳性学科的约束目标,平台在静水力和波频载荷作用下的硬舱底部甲板与桁架结合处的主应力作为结构学科的约束目标。为建立桁架式Spar平台的多学科设计优化模型,根据试验设计的安排,对各试验方案分别进行了水动力分析、稳性分析和结构强度分析。最后,介绍了作为检验模块的平台/锚泊系统耦合时域动力分析的方法和检验准则。
在此基础上,根据第一阶段中对于几种多学科设计优化算法比较的结果,选择基于近似模型的协同优化方法作为多学科设计优化算法,建立了桁架式Spar平台概念设计的协同优化数学模型,并进行了多学科优化分析。
第四阶段:桁架式Spar平台多学科优化模型的改进和优化
尽管近似模型可以大幅提高计算效率,然而其精度存在问题。因此,为提高多学科设计结果的可应用性,分别采用了两种改进方法:
(1)响应面更新策略——提出了响应面更新技术及实施程序,完成了基于响应面更新的桁架式Spar平台概念设计的协同优化过程。对各设计变量更新的历程和结果进行了初步的讨论。通过与基准平台的对比表明:优化设计方案的结构重量大幅降低,垂荡、稳性、强度等性能参数也有所提高,只有纵摇性能略微下降。证明了协同优化方法在桁架式Spar平台概念设计中应用的可行性以及多学科设计优化技术的优越性。通过百年一遇海况的时域耦合分析,验证了优化结果的合理性。
(2)可变复杂度方法——由于近似模型与真实模型间存在着差距,而响应面更新策略只是提高了响应面模型的精度,并没有体现真实模型的结果。因此,使用可变复杂度方法对第三阶段协同优化的结果进行修正。
针对可变复杂度方法需要大量初始计算以保证计算精度的缺点,结合上述两种改进方法的各自特点,提出了基于响应面更新的可变复杂度方法。研究表明:基于响应面更新的可变复杂度方法可以在较少初始样本计算的情况下,获得精度高的结果,这大大节省了初始计算的时间。
综上,论文在以下四个方面,做出了创新性的研究成果:
(1)提出了一套完整的桁架式Spar平台的概念设计方法和流程。开展了甲板布置、主尺度设计、稳性和水动力性能初步分析等概念设计工作。在此基础上,进行了桁架式Spar平台的结构设计,并应用设计波法对平台主要结构进行了强度校核。
(2)将多学科设计优化技术应用到桁架式Spar平台的概念设计中,通过对由现有设计方法和多学科设计优化方法得到的方案的对比,证明了多学科设计优化技术在桁架式Spar平台设计领域的适用性和优越性。
(3)提出将Spar平台设计中所涉及的学科进行分模块处理的多学科建模方法,即分为优化模块、约束模块和检验模块,针对分属不同模块的学科采用不同方法处理。不仅简化了多学科设计优化的计算流程,降低了优化收敛的难度,而且也可以保证模型的合理性和工程适用性。
(4)针对多学科设计优化中采用近似模型所存在的精度问题,分别采用了响应面更新策略和可变复杂度方法,来改进近似模型的精度和提高优化结果的可靠性。在此基础上,提出了基于响应面更新的可变复杂度方法,通过响应面的逐步更新提高精度,通过可变复杂度方法,减小近似模型与高精度模型间的差距。
本文四个阶段的研究成果和主要创新点,是对现行Spar平台概念设计方法的革新。将多学科设计优化方法更好地应用于Spar平台设计,进而促进海洋平台设计的数字化和虚拟化发展,对推动包括Spar平台在内的新型平台的自主研制与应用均具有一定的意义。
To meet the demand of national economic development and people’s fast-growing living condition, China has planned projects of exploiting oil and gas reserves in the South China Sea. However, the manufacturing capability of offshore production platforms in China is still below 500 meters water depth, far from the exploration requirement in South China Sea. Nowadays, the mainstream platforms used in deep water around the world include Floating Production Storage and Offloading System, Semi-submersible, Tension Leg Platform and Spar platform. Among them, Spar platforms have advantages in aspects of functionality, stability, cost-efficiency and safety. Besides, China has dedicated many years’study on Spar platform and has rich technical reserves. In such circumstances, Spar platform will become one of the major equipment for the gas and oil exploration for our country in the deep water, including South China Sea.
Presently, Chinese design capability is lagged behind the foreign design enterprises on the design of advanced ocean engineering units, especially in the conceptual design stage. In addition, the technical monopoly brings difficulties for us to develop Spar platforms. To speed up the pace of research on Spar platforms, and to break through the technical bottleneck, we should make innovation in both concept and method for the conceptual design of Spar platform.
Firstly, this thesis carries out a Truss Spar conceptual design and structural design task based on the current design method of offshore platforms. The current design method prevailing in China is the series process, based on the purpose to improve the parent unit. This design process has the shortcomings of relying too much on the parent unit and high design cost. Even worse, the results of conceptual design can hardly present the overall performances. The design of Spar platforms is a complex engineering problem involving many disciplines, such as hydrodynamics, structures, reliability, etc. These disciplines are both mutual interaction and contradictions, so the overall conceptual design of Spar platform is a typical Multidisciplinary Design Optimization (MDO) problem. However, the current design method can not consider the mutual influence among these disciplines sufficiently, so it often leads to a suboptimal design instead of optimal design.
Besides, the trend for ships and offshore platforms design is moving toward digitalization and virtualization, which will be beneficial for designers to acquire comprehensive information about the system to design in the early stage. Such trend demands the design method be able to highly integrate all the relevant disciplines. Obviously, it can hardly be realized by current method. To speed up the development of deep sea resources exploration, some breakthrough and innovation for the concept and method of design is in urgent need.
In such a situation, as a part of the project supported by the Science and Technology Commission of Shanghai Municipality, this thesis introduces Multidisciplinary Design Optimization, emerged from aeronautics and astronautics fields for complex engineering integrated optimization problems, and explores feasibility and applicability of MDO method to the conceptual design of Truss Spars. The thesis mainly consists of four parts.
Part I: Review about the related research area
The significance of applying MDO techniques in the Truss Spar conceptual design is stated. The definition, development and main research contents of MDO are reviewed. Four mainstream MDO algorithms are elaborated and compared in categories including origin and purpose, approximation models, decomposition, convergence and engineering applicability. Two algorithms– collaborative optimization based on approximation models and BLISS 2000 are regarded as suitable methods to apply MDO techniques in the design of ships and offshore platforms.
Part II: Study on the current conceptual design method and structural design method of Truss Spar
The current Truss Spar conceptual design method is explored. Two aspects are involved during the conceptual design: one deals with the design method and process, and the other concerns the hydrodynamic behavior. The conceptual design process of Spar platform can be described as an interactive flow. A Truss Spar conceptual design process including general arrangement, weight control and selection of main particulars is conducted. The stability and hydrodynamic performances for the Truss Spar are accessed. Based on the results of conceptual design, the structural design is conducted including:
(1) The design method for each part of Spar platforms is concluded and the structural scantling process is accomplished based on the main particulars, general arrangement and load distribution;
(2) The global strength analysis based on design wave methodology is accomplished. Two critical load criteria are selected and wave-induced load is obtained based on 3-D potential theory.
(3) The impact on bottom deck strength for two structural configurations– double bottom and single bottom is studied. The result shows the double bottom can reduces the stress of bottom deck of hard tank in great extent.
The Spar designed by current conceptual design method and structural design method is treated as baseline Spar for further comparison with the result of MDO.
Part III: Application of MDO on the Truss Spar conceptual design
The design parameters in the design of Spar platform, including main particulars, operation parameters, economics and reliability, are elaborated. Because the thesis focuses on the conceptual design, the main particulars are selected as design variables. Then the varying level of design variables are arranged by the theory of Design of Experiment (DOE) and corresponding design plans are determined by uniform design table.
One of the most significant factors for a successful application of MDO is to obtain a reasonable MDO model. A comprehensive MDO model, which includes every discipline related to Truss Spar, will make the optimization process difficult to converge; On the contrary, if only a few disciplines are included, the result of MDO can hardly represent the whole system and be impractical for engineering. To solve this contradiction, an innovative multidisciplinary modeling method is proposed. The disciplines related to Spar platform are divided into three modules: optimization module, constraint module and inspection module. Each module is treated as a different role during the optimization.
The optimization module is the main focus for platform owners and designers, and treated as optimization object function. The disciplines of constraint module are the characteristics of Spar platforms. These characteristics are precondition for the realization of platform functions, and treated as constraints in the optimization process. Only a few critical objectives for each discipline are selected and integrated in the optimization model. The inspection module is not involved in the optimization process and is used to provide a comprehensive assessment of the optimized design for checking.
In the thesis, the hull weight is treated as optimization object. The short term predictions of heave motion and pitch motion are selected as constraint objects for hydrodynamics discipline; the intact stability coefficient is selected as the constraint object for stability discipline; the von Mises stress of the connection zone of hard tank bottom deck with truss is selected as the constraint object for structure discipline. A hull/mooring coupled analysis in time domain is utilized as the method of inspection module. To set up the MDO model for Truss Spar, numerous hydrodynamic analyses, stability analyses and structural strength analyses are conducted for all design plans defined by DOE.
The Collaborative Optimization (CO) based on response surface method is selected as the MDO algorithm and the CO model for Truss Spar conceptual design is established for the first time. Then the CO optimization process is executed and an optimal design is achieved.
Part IV: The improvements of the Collaborative Optimization model
Although the approximation models can greatly improve the computational efficiency, the accuracy of the models may be not eligible. To enhance the accuracy of the approximation models and consequent optimization quality, two methods are used:
(1) Adaptive response surface method (ARSM)– The concept and procedure of ARSM is proposed. The collaborative optimization based on ARSM for Truss Spar conceptual design is accomplished and an optimal design solution, which satisfied all the constraints, is obtained. A discussion on the adaptive history for each design variables is made. The optimized results are compared with the baseline Spar. The comparison shows that the optimized solution by MDO achieves a lighter platform, and that the performances of heave response motion, stability coefficient and strength of the bottom deck are much improved. The only performance degradation for the optimized solution is the pitch motion, while the change is not significant. Finally, the time domain analysis based on 100-year storm of Gulf of Mexico is conducted and the results prove that the optimized design solution by MDO is feasible.
(2) Variable-complexity method (VCM)– Although ARSM can effectively improve the accuracy of approximation models, it fails to diminish the difference between approximation models and physical models. VCM is adapted to correct results of CO in part II by using the results of high-fidelity analysis tool.
However, VCM generally requires large number of calculations for initial sampling points to ensure precision. To overcome such a deficiency, an improved VCM method based on ARSM is proposed. The application results show that the improved VCM strategy can attain high accuracy with a small number of initial sampling.
In summary, four innovative accomplishments have been made in the thesis.
(1) A complete conceptual design process for Truss Spar is proposed and structural design is conducted. Design wave methodology is used to check the structural strength of the platform.
(2) MDO techniques are applied in Truss Spar conceptual design. The optimized design results by MDO show superiority in performances contrasting to the ones by the current design method. The feasibility of applying MDO techniques in the Spar platform is verified.
(3) An innovative multidisciplinary modeling method is proposed. The related disciplines for Spar platform are divided into three modules: optimization module, constraint module and inspection module. Each module is treated as different role during the optimization. Such modeling method decreases the convergence difficulty of optimization and relieves the computational burden. The rationality of the MDO model is also guaranteed.
(4) Adaptive response surface method and variable-complexity method are adopted to improve the accuracy of approximation models. An improved VCM method based on ARSM is proposed. The method shows advantages in both improving the accuracy of approximation models and diminishing the difference between approximation models and physical models.
The accomplishment of this thesis is an innovation to the current conceptual design method. A successful application of MDO in Truss Spar conceptual design will promote the development of digitalization and virtualization for offshore platforms, make a contribution to the independent research and application of offshore platforms, Spar platform included, in deep sea areas in China.
引文
Abbott E.A. and Scott M.L. (2002) The case for multidisciplinary design approach for smart fiber composite structures, Composite Structures, 58(3):349-362.
ABS (2006) Rules for building and classing mobile offshore drilling units, American Bureau of shipping.
AIAA Multidisciplinary Design Optimization Technical Committee (1991) Current state of the art on multidisciplinary design optimization (MDO), An AIAA White Paper, ISBN 1-56347-021-7.
Amarchinta H.K., Khambaswadkar R. and Grandhi R.V. et al. (2006) Multidiciplinary optimization of a lightweight torpedo for reduced acoustic signature, 11th AIAA/ISSMO Multidisciplinary Analysis and Optimization Conference, Portsmouth, USA, AIAA 2006-6913.
Alexandrov N.M. and Lewis R.M. (2002a) Analytical and Computational Aspects of Collaborative Optimization for Multidisciplinary Design, AIAA Journal, 40(2):301-309.
Alexandrov N.M. and Lewis R.M. (2002b) An overview of first-order model management for engineering optimization, Optimization and Engineering, 2:413-430.
Allison J., Kokkolaras M., Zawislak M. and Papalambros P.Y. (2005) On the Use of Analytical Target Cascading and Collaborative Optimization for Complex System Design, 6th World Congress on Structural and Multidisciplinary Optimization, Rio de Janeiro, Brazil.
Allison J., Walsh D. and Kokkolaras M. et al. (2006) Analytical Target Cascading in Aircraft Design, 44th AIAA Aerospace Sciences Meeting, RENO, NV, USA, Vol.21, pp.16112-16120.
Altus T.D. (2002) A Response Surface Methodology for Bi-Level Integrated System Synthesis (BLISS), AIAA Paper, NASA CR-2002-211652.
API RP 2A (2004) Recommended Practice for Planning, Designing, and Constructing Fixed Offshore Platforms- Load and Resistance Factor Design, American PetroleumInstitute.
Astrup O.C., Nestegard A., and Sodahl N. (2001) Coupled analysis strategies for deepwater Spar platforms, Proc. of 11st International Offshore and Polar Engineering Conference, Stavanger, Norway.
Azarm S. and Li W. (1988) A two-level decomposition method for design optimization, Engineering Optimization, 13:211-224.
Backer C.A., Grossman B., Haftka R.T., et al. (1998) HSCT configuration design space exploration using aerodynamic response surface approximations, The 7th AIAA/USAF/NASA/ISSMO Symposium on Multidisciplinary Analysis and Optimization, St. Louis, Missouri, AIAA-98-4803.
Balling R.J. and Sobieszczanski-Sobieski J. (1996) Optimization of coupled systems: A critical overview of approaches, AIAA Journal, 34(1):6-7.
Balling R.J. and Wilkison C.A. (1997) Execution of multidisciplinary design optimization approaches on common test problems, A IAA Journal, 35(1): 178～186.
Batill S.M., Stelmack M.A., Yu X.Q. (1999) Multidisciplinary design optimization of an electric-powered unmanned air vehicle, Aircraft Design, 2:1-18.
Belegundu A.D., Halberg E., Yukish M.A. Simpson, T.W. (2000) Attribute-based Multidisciplinary Optimization of Undersea Vehicles, 8th AIAA/USAF/NASA/ISSMO Symposium on Multidisciplinary Analysis and Optimization, Long Beach, USA, AIAA-2000-4865.
Bloebaum C.L. (1992) An Intelligent Decomposition Approach for Coupled Engineering Systems, 4th AIAA/ NASA/USAF/OAI Symposium on Multidisciplinary Analysis and Optimization, Cleveland, Ohio, AIAA-92-4821.
Box G.E.P. and Wilson K.B. (1951) On the Experimental Attainment of Optimum Conditions, Journal of the Royal Statistical Society, Series B (Methodological), 13(1): 1-45.
Braun R., Powell R., Lepsch R., et al. (1995) Comparison of Two Multidisciplinary Optimization Strategies for Launch Vehicle Design, Journal of Spacecraft and Rockets, 32(2):404-410.
Braun R. D., Moore A. A. and Kroo I. M. (1997) Collaborative approach to launch vehicle design, Journal of Spacecraft and Rockets, 34 (4):478-486.
Brown N.F. (2005) Evaluation of Multidisciplinary Optimization (MDO) Techniques Applied to a Reusable Launch Vehicle, The 43rd AIAA Aerospace Sciences Meeting and Exhibit, Reno, Nevada.
Burgee S.L., Watson L.T., and Giunta A.A., et al. (1994) Parallel multipoint variable-complexity approximations for multidisciplinary optimization, Proc. IEEE Scalable High-Performance Computing Conference, Los Alamitos, USA, pp.734-740.
Cao A.X., Zhao M., Liu W. and Cui W.C. (2007) Application of Multidisciplinary Design Optimization in the Conceptual Design of a Submarine, Journal of Ship Mechanics, 11(3):373-382.
Chakrabarti S.K. (2005) Handbook of offshore engineering, Elsevier Science.
Choi S., Alonso J.J. and Kroo H.M. (2009) Two-level multifidelity design optimzation studies for supersonic jets, Journal of Aircraft, 46(3):776-790.
Choi S., Alonso J.J., Kroo I.M. and Wintzer M. (2004) Multi-fidelity design optimization of low-boom supersonic business jets, 10th AIAA/ISSMO Multidisciplinary Analysis and Optimization Conference, Albany, N.Y., USA, AIAA 2004-4371.
Choudhary R. Malkawi A. and Papalambros P.Y. (2005) Analytic target cascading in simulation-based building design, 20th International Symposium on Automation and Robotics in Construction: The Future Site, 14(4):551-568.
Chung H.S. and Alonso J.J. (2001) Using gradients to construct response surface models for high-dimensional design optimization problems, AIAA 40th Aerospace Science Meeting and Exhibit, RENO, NV, USA, AIAA-2001-0922.
Chung H.S. and Alonso J.J. (2002a) Using gradients to construct Cokriging approximation models for high-dimensional design optimization problems, AIAA 39th Aerospace Science Meeting and Exhibit, RENO, NV, USA, AIAA-2002-0317.
Chung H.S. and Alonso J.J. (2002b) Design of a low-boom supersonic business jet using Cokriging approximation models, 9th AIAA/ISSMO Symposium on Multidisciplinary Analysis and Optimization, Atlanta, USA, AIAA-2002-5598.
Deng X., Zhang W.M., Tong L.S. (2009) Collaborative optimization of wheel hub reducer based on reliability theory, 2009 International Conference on Measuring Technology and Mechatronics Auomation, ICMTMA, Zhangjiajie, China, Vol.2, pp.771-774.
de Weck O.L., Jones M.B. (2006) Isoperformance: Analysis and design of complexsystems with desired outcomes, System Engineering, 9(1):45-61.
de Weck O.L., Agte J., Sobieszczanski-Sobieski J., et al. (2007) State-of-the-Art and future trends in multidisciplinary design optimization, 48th AIAA/ASME/ASCE/AHS/ASC Structures, Structural Dynamics, and Material Conference, Hawaii, USA, AIAA2007-1905.
DNV (2001) Offshore standard- stability and watertight integrity, Det Norske Veritas.
DNV (2005a) SESAM user manual- DeepC Theory, Det Norske Veritas.
DNV (2005b) SESAM user manual- HydroD, Det Norske Veritas.
DNVS-WADAM (2005) SESAM user manual- Wave analysis by diffraction and Morison theory, Det Norske Veritas.
Downie M.J., Graham J.M.R., and Hall C. et al. (2000) An experimental investigation of motion control devices for truss spars, Marine Structure, 13(2):75-90.
Dudley J., Huang X., and MacMillin P.E. et al. (1995) Multidisciplinary Optimization of the High-Speed Civil Transport, AIAA 33rd Aerospace Science Meeting and Exhibit, RENO, NV, USA, AIAA Paper-95-0124.
Eason E., Nystrom G., Burlingham A. and Nelson E. (1994) Robustness Testing of Non-hierarchic Multidisciplinary System Optimization, 5th AIAA / NASA /USAF /ISSMO Symposium on Multidisciplinary Analysis and Optimization, Panama City Beach, Florida.
Finn L.D., Maher J.V., Gupta H. (2003).The Cell Spar and Vortex Induced Vibrations, Offshore Technology Conference, Houston, Texas, OTC 15244.
Gern F.H. Naqhshineh-Pour A.H., and Sulaeman E. et al. (2001) Structural wing sizing of multidisciplinary design optimization of a strut-braced wing, Journal of Aircraft, 38(1):154-163.
Giesing J.P. and Barthelemy J.M. (1998) A summary of industry MDO applications and needs, 7th AIAA/USAF/NASA/ISSMO Symposium on Multidisciplinary Analysis and Optimization, An AIAA White Paper.
Giunta A.A., Balabanov V., and Kaufman, M. et al. (1995) Variable-complexity Response Surface Design of an HSCT Configuration, Proceedings of the ICASE/NASA Langley Workshop on Multidisciplinary Design Optimization, Hampton, USA, pp.348-367.
Giunta A.A. and Watson L. (1998) A comparison of approximation modeling techniques:polynomial versus interpolating model, 7th AIAA/USAF/NASA/ISSMO Symposium on Multidisciplinary Analysis and Optimization, St. Louis, USA, AIAA-98-4758.
Gundlach IV J.F. Tetrault P.A., and Gern F.H. et al. (2000) Conceptual design studies of a strut-braced wing transonic transport, Journal of Aircraft, 37(6):976-983.
Halkyard J. and Tahar A. (2004) Full scale data comparion for the Horn Mountain Spar, 23rd International Conference on Offshore Mechanics and Arctic Engineering, Vancouver, Canada, OMAE2004-51629.
Haslum H.A. and Faltinsen O.M. (1999) Alternative shape of Spar platforms for use in hostile areas, Offshore Technology Conference, Houston, TX, OTC-10953.
Hendriks M. and Lange F. (2005) Spar Installation in deep water- a developing capability, Offshore Technology Conference, Houston, USA, OTC-17516.
Huang C.H. and Bloebraum C.L. (2004) Multi-Objective Pareto Concurrent Subspace Optimization for Multidisciplinary Design, 42nd AIAA Aerospace Science Meeting and Exhibit, RENO, NV, USA, AIAA Paper-2004-278.
Huque Z. and Jahingir N. (2002) Application of Collaborative Optimization on a RBCC Inlet/Ejector System, 38th AIAA/ASME/SAE/ASEE Joint Propulsion Conference and Exhibit, Indianapolis, USA, AIAA 2002-3604.
Hutchison M.G., Unger E.R., and Mason W.H., et al. (1994) Variable-Complexity Aerodynamic Optimization of an HSCT Wing Using Structural Wing-Weight Equation, J. Aircraft, Vol.31(1):110-116.
Hu Z.Q., Cui W.C., and Yang J.M. (2008) Multidisciplinary design optimization- A new way to bring softer bows, 28th International Conference on Ocean, Offshore and Arctic Engineering, Estoril, Portugal.
Incecik A. (2000) Offshore design: an overview of basic concepts, Lecture Notes, Department of Marine Technology, Newcastle University, UK.
Kim H.M. (2001) Target cascading in optimal system design[D], University of Michigan, Ann Arbor, Michigan, USA.
Kim H.M., Michelena N.F., Papalambros P.Y. et al. (2003a) Target cascading in optimal system design, Journal of Mechanical design (Transactions of the ASME), 125(3):474-480.
Kim H.M., Rideout D.T., Papalambros P.Y. et al. (2003b) Analytical target cascading inautomotive vehicle design, Journal of Mechanical design (Transactions of the ASME), 125(3):481-489.
Kim H., Ragon S., Soremekun G., et al. (2004) Flexible approximation approach for bi-level integrated system synthesis, AIAA-2004-4545
Kirsch U. (1997) Two-level optimization of prestressed structures. Engineering Structures, 19(4):309-317.
Knill D. L., Giunta A.A., and Baker C.A. et al. (1998) Multidisciplinary HSCT design using response surface approximations of supersonic Euler aerodynamics, Proc. 36th Aerospace Sciences Meeting and Exhibit, Reno, NV, USA.
Kodiyalam S. and Sobieszczanski-Sobieski J. (2000a) Bi-level integrated system synthesis with response surfaces, AIAA Journal, 38(8): 1485-1497.
Kodiyalam S. and Yuan C. (2000b) Evaluation of Methods for Multidisciplinary Design Optimization (MDO), Part II. AIAA Paper, NASA/CR-2000-210313.
Krasteva D.T., Baker C. and Watson L.T. et al. (1999) Distributed control parallelism for multidisciplinary design of a high speed civil transport, Proc. 7th on the Frontiers of Massively Parallel Computation, Los Alamitos, CA.
Kroo I.M., Altus S., Braun R.D., Gage P, et al. (1994) Multidisciplinary Optimization Methods for Aircraft Preliminary Design, 5th AIAA/USAF/NASA/ISSMO Symposium on Multidisciplinary Analysis and Optimization, Panama City Beach, Florida, pp.697-707.
Lin J.G. (2004) Analysis and Enhancement of Collaborative Optimization for Multidisciplinary Design, AIAA Journal, 42 (2): 348-360.
Lokanathan A.N., Brockman J.B., Renaud J.E. (1995) A Multidisciplinary Optimization Approach to Integrated Circuit Design. Proceedings of Concurrent Engineering: A Global Perspective, CE95 Conference, McLean, Virginia.
Luo Y.H., Lu R. and Wang J. et al. (2001) Time-domain fatigue analysis for critical connections of truss spar, Proceedings of the 11st International Offshore and Polar Engineering Conference, Stavanger, Norway, pp.362-368.
Luo Y.H., Zhang B., and Tallavajhula S. (2007) Integrated structural analysis methodology for Truss spars, Proceedings of 26th International Conference on Offshore Mechanics and Arctic Engineering, San Diego, USA, OMAE 2007-29419.
McAllister C.D. and Simpson T.W. (2003)Multidisciplinary robust design optimization of an internal combustion engine, Journal of Mechanical Design Transaction of the ASME, 125(1): 124-130.
MacMillin P.E., Golovidov O. and Mason W.H. et al. (1998) An MDO investigation of the impact of pratical constraints on an HSCT configuration, Proc. 35th Aerospace Sciences Meeting and Exhibit, Reno, NV, USA.
Maher J.V., Weaver T.O., Thomas H., et al. (2005). Red Hawk hull design and topsides interfaces, Proceedings of the Offshore Technology Conference, Houston, USA, Paper No.OTC1742.
Manning V. M. (1999) High speed civil transport design via collaborative optimization [D], Stanford University, 1999.
Messac A. (1996) Physical programming: Effective optimization for computational design, AIAA Journal, 34(1):149-158.
McKay M.D., Conover W.J. and Beckman R.J. (1979) A comparison of three methods for selecting values of input variables in the analysis of output from a computer code, Technometrics, 21:239-245.
Meyerhoff W.K. (1970) Added mass of thin rectangular plates calculated by potential theory, J Ship Res, 14:100-111.
Miller D.W., de Weck O.L. and Mosier G.E. (2002) Framework for multidisciplinary integrated modelling and analysis of space telescope, 1st International Workshop on Integrated Modelling of Telescopes, Lund, Sweden.
Neu W.L., Mason W.H. and Ni S. et al. (2000) A Multidisciplinary design optimization scheme for containerships, 8th AIAA/USAF/NASA/ISSMO Symposium on Multidisciplinary Analysis and Optimization, Long Beach, USA.
Parasha S. and Bloebraum C.L. (2006) Multi-Objective Genetic Algorithm Concurrent Subspace Optimization (MOGACSSO) for Multidisciplinary Design, 8th AIAA/ASME/ASCE/AHS/ASC Structures, Structural Dynamics, and Material Conference, Rhode Island, USA, AIAA-2006-2047.
Park C.H., Lee W.I., Han W.S. and Vautrin A. (2008) Improved genetic algorithm for multidisciplinary optimization, Computers and Structures, 86:1894-1903.
Penney P.W., Riiser R.M. (1984) Preliminary design of Semi-submersible, North EastCoast Institute of Engineers & Shipbuilders, pp.49-69.
Prislin I., Blevins R.D. and Halkyard J. (1998) Viscous Damping and Added Mass of Solid Square Plates, 17th International Conference on Offshore Mechanics and Arctic Engineering, Lisbon, Portugal.
Sarpkaya T. (1976) In-line and transverse forces on cylinders in oscillating flow at high Reynold’s number, Proc. 8th Offshore Technology Conference, Houston, USA, OTC-2533.
Schittkowski K. (1985/86). NLPQL: A FORTRAN subroutine solving constrained nonlinear programming problems, Annals of Operations Research, Vol. 5:485-500.
Simpson T.W., Peplinski J., Koch P.N. and Allen J.K. (2001a) Metamodels for computer-based engineering design: survey and recommendations, Engineering with computers, 17(2):129-150.
Simpson T.W., Lin D.K.J. and Chen W. (2001b) Sampling strategies for computer experiments: design and analysis, International Journal of Reliability and Applications, 2(3):209-240.
Sobieski I.P., Manning V.M., Kroo I.M. (1998) Response surface estimation and refinement in Collaborative Optimization, 7th AIAA/USAF/NASA/ISSMO Symposium on Multidisciplinary Analysis and Optimization, St. Louis, USA, AIAA-98-4753.
Sobieski I.P., Kroo I.M. (2000) Collaborative Optimization using Response Surface Estimation, AIAA Journal, 38 (10):1931-1939.
Sobiesczanski-Sobieski J. (1982) A linear decomposition method for optimization problem – blueprint for development, NASA Technical Memorandum 83248, 1982.
Sobiesczanski-Sobieski J. (1988) Optimization by Decomposition: A Step from Hierarchic to Non-Hierarchic Systems, 2nd NASA/Air Force Symposium on Recent Advances in Multidisciplinary Analysis and Optimization, Hampton, VA, NASA-TM-101494, NASA-CP-3031, Part 1.
Sobiesczanski-Sobieski J. (1990) The Sensitivity of Complex, Internally Coupled Systems, AIAA Journal, 28(1):153-160.
Sobieszczanski-Sobieski J. and Haftka R. (1997) Multidisciplinary aerospace design optimization: survey of recent developments, Structural Optimization, 14(1):1-23.
Sobieszczanski-Sobieski J., Agte J., Sandusky R. Jr. (1998) Bi-level integrated system
synthesis (BLISS), 7th AIAA/USAF/NASA/ ISSMO Symposium on Multidisciplinary Analysis and Optimization, St. Louis, Missouri, AIAA-1998-4916.
Sobieszczanski-Sobieski J., Emiley M. and Agte J., et al. (2000) Advancement of Bi-Level Integrated System Synthesis (BLISS), 38th Aerospace Sciences Meeting and Exhibit, Reno, NV, AIAA-2000-421.
Sobieszczanski-Sobieski J., Altus T., Phillips M., et al. (2003) Bi-level Integrated System Synthesis for Concurrent and Distributed Processing, AIAA Journal, 41(10): 1996-2002.
Stelmack M.A., Batill S.M., Beck B.C., et al. (1998) Application of the Concurrent Subspace Design Framework to Aircraft Brake Component Design Optimization, AIAA paper, pp.98-2033.
Tedford N.P. and Martins J.R.R.A. (2006) On the common structure of MDO problems: A comparison of architectures, 11th AIAA/ ISSMO Symposium on Multidisciplinary Analysis and Optimization Conference, Poutsmouth, Virginia, AIAA-2006-7080.
Thiagarajan K.P., Datta I., and Ran A.Z. et al. (2002) Influence of heave plate geometry on the heave response of Classic spars, Proceedings of 21st International Conference on Offshore Mechanics and Arctic Engineering, Oslo, Norway, OMAE 2002-28350.
Troesch A.W., Perlin M. and He H. (2000) Hydrodynamics of thin plates, Joint Industry Report.
Wang J., Zhang B. and Berg S. (2002) Truss spar time domain inplace structural strength analysis, Offshore Technology Conference, Houston, TX, OTC-14299.
Wang Y. and Fang K.T. (1981) A note on uniform distribution and experimental design, Kexue Tongbao, 26: 485-489.
Wrenn G.A. and Dovi A.R. (1988) Multilevel decomposition approach to the preliminary sizing of a transport aircraft wing, AIAA Journal of Aircraft. 25(7):32-38.
Wujek B.A., Renaud J.E., Batill S.M., Brockman J.B. (1996a) Concurrent Subspace Optimization Using Design Variable Sharing in a Distributed Computing Environment, Concurrent Engineering, 4(4): 361-377.
Wujek B.A., Renaud J.E., Johnson E.W., et al. (1996b) Design Flow Management and Multidisciplinary Design Optimization in Application to Aircraft Concept Sizing, The 34th AIAA Aerospace Sciences Meeting and Exhibit, Reno, Nevada, AIAA-96-0713.
Yu X.Q., Stelmack M.A., Batill S.M. (1998) An application of the concurrent subspacedesign (CSD) to the preliminary design of a low-Reynolds number UAV, AIAA paper, 98-4917.
白小涛(2005)飞机多学科设计协同优化及近似技术研究.硕士学位论文,西北工业大学.
操安喜(2008)载人潜水器多学科设计优化方法及其应用研究.博士学位论文,上海交通大学.
陈炉云(2008)基于多学科设计优化的潜艇结构-声辐射优化研究.博士学位论文,上海交通大学.
陈琪峰(2003)飞行器分布式协同进化多学科设计优化方法研究.博士学位论文,国防科技大学.
董艳秋(2005)深海采油平台波浪载荷及响应.天津:天津大学出版社.
范辉,李为吉(2008)一种高效的基于可靠性的多学科设计优化方法.中国航空学报(英文版),21(4):335-340.
方开泰(1978)均匀设计——数论方法在试验设计中的应用.概率统计通讯,1:56-97.
方开泰(1980)均匀设计.应用数学学报,3: 363-372.
方开泰(1994)均匀设计与均匀设计表,北京:科学出版社.
方开泰,马长兴(2001)正交与均匀试验设计,北京:科学出版社.
冯向军(2008)多学科设计优化方法及其在导航星座设计中的应用.博士学位论文, 国防科学技术大学.
高鹏(2007) Spar平台结构设计研究.硕士学位论文,上海交通大学.
苟鹏(2009)深海空间站结构系统地多学科设计优化探索.博士学位论文,上海交通大学.
顾敏童(2001)船舶设计原理.上海:上海交通大学出版社.
郝黎晶(2008)单柱式深水平台结构设计准则及主体强度初探.硕士学位论文,上海交通大学.
胡峪(2001)多学科设计优化及其应用研究.博士学位论文,西北工业大学.
胡志强(2008)多学科设计优化技术在深水半潜式钻井平台概念设计中的应用研究.博士学位论文,上海交通大学.
纪亨腾,黄国梁,范菊(2003)垂荡阻尼板的强迫振荡实验.上海交通大学学报, 37(7):977-980.
雷宗友(1988)中国海环境手册.上海:上海交通大学出版社.
李芬,邹早建(2003)浮式海洋结构物研究现状及发展趋势.武汉理工大学学报(交通科学与工程版), 27(5): 682-686.
李响(2003)多学科设计优化方法及其在飞行器设计中的应用.博士学位论文,西北工业大学.
李玉成(1998)海洋工程技术的新发展.中国海洋平台, 13 (1): 9-12.
凌六一(2006)基于ATC的供应链优化设计.博士学位论文,中国科学技术大学.
刘军,易宏(2009) CGX巡洋舰多学科设计优化模型的再分析.船舶力学,13(6): 895-904.
刘克龙,姚卫星,余雄庆(2007)几种新型多学科设计优化算法及比较.计算机集成制造系统, 13(2):209-216.
刘蔚(2007)多学科设计优化方法在7000米载人潜水器总体设计中的应用.博士学位论文,上海交通大学.
潘彬彬,崔维成,何凌(2009)船舶多学科设计优化中的船型变换模块.船舶力学,13(6): 886-894.
石红珊(2007a)深水单立柱采油平台方案设计及稳性研究.硕士学位论文,上海交通大学.
石红珊,柳存根(2007b) Spar平台及其总体设计中的考虑.中国海洋平台,22(1):1-4.
徐琦(2002) Truss Spar平台简介.中国造船,43(增刊).
薛飞,余雄庆,姚卫星(2005)轻型飞机机翼气动/结构协同优化研究.计算力学学报,22(4): 488-491.
薛鸿祥(2008)新型深海多柱桁架式平台及立管结构疲劳性能研究.博士学位论文,上海交通大学.
孙奕捷,申功璋(2009)飞机多学科设计优化中的并行多目标子空间优化框架.航空学报,30(8): 1421-1428.
姚熊亮,李克杰,张阿漫(2006)水下爆炸时舰船正交异性板的简化方法研究.中国舰船研究, 1(3): 30-37.
余雄庆(1999)多学科设计优化算法及其在飞机设计中的应用研究.博士学位论文,南京航空航天大学.
余雄庆,薛飞,穆雪飞等(2003)用遗传算法提高协同优化方法的可靠性,中国机械工程, 14(21): 1808-1881.
邢小楠,徐元铭,李烁,杨笑菡(2004)神经网络响应面逼近在飞机总体优化设计中的应用.机械设计与研究, 20(1): 69-71.
张帆,杨建民,李润培(2005) Spar平台的发展趋势及其关键技术.中国海洋平台, 20(2):6-11.
张帆(2008a).深海立柱式平台概念设计及水动力性能研究.博士学位论文,上海交通大学.
张帆,杨建民,李润培,柳存根(2008b).多柱桁架式立柱平台概念设计.上海造船, 1:18-20.
张海彬,沈志平,李小平(2007)深水半潜式钻井平台波浪载荷预报与结构强度评估.船舶, 2: 33-38.
张科施,李为吉,李响(2005)飞机概念设计的多学科综合优化技术.西北工业大学学报, 23(1):102-106.
张智,董艳秋,芮光六(2004),一种新型的深海采油平台Spar.中国海洋平台, 19(6):29-35
张智(2005)Spar平台系泊计算及波浪载荷研究.博士学位论文,天津大学.
赵敏(2009)两级集成系统协同优化方法及其在深海空间站总体概念设计中的应用.博士学位论文,上海交通大学.
智翠梅(2007)均匀设计及优化.化工中间体,3: 7-10.
周浩,陈万春,殷兴良(2008)高超声速飞行器多段弹道协作优化.北京航空航天大学学报,34(9): 1092-1095.
ABS (2006) Rules for building and classing mobile offshore drilling units, American Bureau of shipping.
AIAA Multidisciplinary Design Optimization Technical Committee (1991) Current state of the art on multidisciplinary design optimization (MDO), An AIAA White Paper, ISBN 1-56347-021-7.
Amarchinta H.K., Khambaswadkar R. and Grandhi R.V. et al. (2006) Multidiciplinary optimization of a lightweight torpedo for reduced acoustic signature, 11th AIAA/ISSMO Multidisciplinary Analysis and Optimization Conference, Portsmouth, USA, AIAA 2006-6913.
Alexandrov N.M. and Lewis R.M. (2002a) Analytical and Computational Aspects of Collaborative Optimization for Multidisciplinary Design, AIAA Journal, 40(2):301-309.
Alexandrov N.M. and Lewis R.M. (2002b) An overview of first-order model management for engineering optimization, Optimization and Engineering, 2:413-430.
Allison J., Kokkolaras M., Zawislak M. and Papalambros P.Y. (2005) On the Use of Analytical Target Cascading and Collaborative Optimization for Complex System Design, 6th World Congress on Structural and Multidisciplinary Optimization, Rio de Janeiro, Brazil.
Allison J., Walsh D. and Kokkolaras M. et al. (2006) Analytical Target Cascading in Aircraft Design, 44th AIAA Aerospace Sciences Meeting, RENO, NV, USA, Vol.21, pp.16112-16120.
Altus T.D. (2002) A Response Surface Methodology for Bi-Level Integrated System Synthesis (BLISS), AIAA Paper, NASA CR-2002-211652.
API RP 2A (2004) Recommended Practice for Planning, Designing, and Constructing Fixed Offshore Platforms- Load and Resistance Factor Design, American PetroleumInstitute.
Astrup O.C., Nestegard A., and Sodahl N. (2001) Coupled analysis strategies for deepwater Spar platforms, Proc. of 11st International Offshore and Polar Engineering Conference, Stavanger, Norway.
Azarm S. and Li W. (1988) A two-level decomposition method for design optimization, Engineering Optimization, 13:211-224.
Backer C.A., Grossman B., Haftka R.T., et al. (1998) HSCT configuration design space exploration using aerodynamic response surface approximations, The 7th AIAA/USAF/NASA/ISSMO Symposium on Multidisciplinary Analysis and Optimization, St. Louis, Missouri, AIAA-98-4803.
Balling R.J. and Sobieszczanski-Sobieski J. (1996) Optimization of coupled systems: A critical overview of approaches, AIAA Journal, 34(1):6-7.
Balling R.J. and Wilkison C.A. (1997) Execution of multidisciplinary design optimization approaches on common test problems, A IAA Journal, 35(1): 178～186.
Batill S.M., Stelmack M.A., Yu X.Q. (1999) Multidisciplinary design optimization of an electric-powered unmanned air vehicle, Aircraft Design, 2:1-18.
Belegundu A.D., Halberg E., Yukish M.A. Simpson, T.W. (2000) Attribute-based Multidisciplinary Optimization of Undersea Vehicles, 8th AIAA/USAF/NASA/ISSMO Symposium on Multidisciplinary Analysis and Optimization, Long Beach, USA, AIAA-2000-4865.
Bloebaum C.L. (1992) An Intelligent Decomposition Approach for Coupled Engineering Systems, 4th AIAA/ NASA/USAF/OAI Symposium on Multidisciplinary Analysis and Optimization, Cleveland, Ohio, AIAA-92-4821.
Box G.E.P. and Wilson K.B. (1951) On the Experimental Attainment of Optimum Conditions, Journal of the Royal Statistical Society, Series B (Methodological), 13(1): 1-45.
Braun R., Powell R., Lepsch R., et al. (1995) Comparison of Two Multidisciplinary Optimization Strategies for Launch Vehicle Design, Journal of Spacecraft and Rockets, 32(2):404-410.
Braun R. D., Moore A. A. and Kroo I. M. (1997) Collaborative approach to launch vehicle design, Journal of Spacecraft and Rockets, 34 (4):478-486.
Brown N.F. (2005) Evaluation of Multidisciplinary Optimization (MDO) Techniques Applied to a Reusable Launch Vehicle, The 43rd AIAA Aerospace Sciences Meeting and Exhibit, Reno, Nevada.
Burgee S.L., Watson L.T., and Giunta A.A., et al. (1994) Parallel multipoint variable-complexity approximations for multidisciplinary optimization, Proc. IEEE Scalable High-Performance Computing Conference, Los Alamitos, USA, pp.734-740.
Cao A.X., Zhao M., Liu W. and Cui W.C. (2007) Application of Multidisciplinary Design Optimization in the Conceptual Design of a Submarine, Journal of Ship Mechanics, 11(3):373-382.
Chakrabarti S.K. (2005) Handbook of offshore engineering, Elsevier Science.
Choi S., Alonso J.J. and Kroo H.M. (2009) Two-level multifidelity design optimzation studies for supersonic jets, Journal of Aircraft, 46(3):776-790.
Choi S., Alonso J.J., Kroo I.M. and Wintzer M. (2004) Multi-fidelity design optimization of low-boom supersonic business jets, 10th AIAA/ISSMO Multidisciplinary Analysis and Optimization Conference, Albany, N.Y., USA, AIAA 2004-4371.
Choudhary R. Malkawi A. and Papalambros P.Y. (2005) Analytic target cascading in simulation-based building design, 20th International Symposium on Automation and Robotics in Construction: The Future Site, 14(4):551-568.
Chung H.S. and Alonso J.J. (2001) Using gradients to construct response surface models for high-dimensional design optimization problems, AIAA 40th Aerospace Science Meeting and Exhibit, RENO, NV, USA, AIAA-2001-0922.
Chung H.S. and Alonso J.J. (2002a) Using gradients to construct Cokriging approximation models for high-dimensional design optimization problems, AIAA 39th Aerospace Science Meeting and Exhibit, RENO, NV, USA, AIAA-2002-0317.
Chung H.S. and Alonso J.J. (2002b) Design of a low-boom supersonic business jet using Cokriging approximation models, 9th AIAA/ISSMO Symposium on Multidisciplinary Analysis and Optimization, Atlanta, USA, AIAA-2002-5598.
Deng X., Zhang W.M., Tong L.S. (2009) Collaborative optimization of wheel hub reducer based on reliability theory, 2009 International Conference on Measuring Technology and Mechatronics Auomation, ICMTMA, Zhangjiajie, China, Vol.2, pp.771-774.
de Weck O.L., Jones M.B. (2006) Isoperformance: Analysis and design of complexsystems with desired outcomes, System Engineering, 9(1):45-61.
de Weck O.L., Agte J., Sobieszczanski-Sobieski J., et al. (2007) State-of-the-Art and future trends in multidisciplinary design optimization, 48th AIAA/ASME/ASCE/AHS/ASC Structures, Structural Dynamics, and Material Conference, Hawaii, USA, AIAA2007-1905.
DNV (2001) Offshore standard- stability and watertight integrity, Det Norske Veritas.
DNV (2005a) SESAM user manual- DeepC Theory, Det Norske Veritas.
DNV (2005b) SESAM user manual- HydroD, Det Norske Veritas.
DNVS-WADAM (2005) SESAM user manual- Wave analysis by diffraction and Morison theory, Det Norske Veritas.
Downie M.J., Graham J.M.R., and Hall C. et al. (2000) An experimental investigation of motion control devices for truss spars, Marine Structure, 13(2):75-90.
Dudley J., Huang X., and MacMillin P.E. et al. (1995) Multidisciplinary Optimization of the High-Speed Civil Transport, AIAA 33rd Aerospace Science Meeting and Exhibit, RENO, NV, USA, AIAA Paper-95-0124.
Eason E., Nystrom G., Burlingham A. and Nelson E. (1994) Robustness Testing of Non-hierarchic Multidisciplinary System Optimization, 5th AIAA / NASA /USAF /ISSMO Symposium on Multidisciplinary Analysis and Optimization, Panama City Beach, Florida.
Finn L.D., Maher J.V., Gupta H. (2003).The Cell Spar and Vortex Induced Vibrations, Offshore Technology Conference, Houston, Texas, OTC 15244.
Gern F.H. Naqhshineh-Pour A.H., and Sulaeman E. et al. (2001) Structural wing sizing of multidisciplinary design optimization of a strut-braced wing, Journal of Aircraft, 38(1):154-163.
Giesing J.P. and Barthelemy J.M. (1998) A summary of industry MDO applications and needs, 7th AIAA/USAF/NASA/ISSMO Symposium on Multidisciplinary Analysis and Optimization, An AIAA White Paper.
Giunta A.A., Balabanov V., and Kaufman, M. et al. (1995) Variable-complexity Response Surface Design of an HSCT Configuration, Proceedings of the ICASE/NASA Langley Workshop on Multidisciplinary Design Optimization, Hampton, USA, pp.348-367.
Giunta A.A. and Watson L. (1998) A comparison of approximation modeling techniques:polynomial versus interpolating model, 7th AIAA/USAF/NASA/ISSMO Symposium on Multidisciplinary Analysis and Optimization, St. Louis, USA, AIAA-98-4758.
Gundlach IV J.F. Tetrault P.A., and Gern F.H. et al. (2000) Conceptual design studies of a strut-braced wing transonic transport, Journal of Aircraft, 37(6):976-983.
Halkyard J. and Tahar A. (2004) Full scale data comparion for the Horn Mountain Spar, 23rd International Conference on Offshore Mechanics and Arctic Engineering, Vancouver, Canada, OMAE2004-51629.
Haslum H.A. and Faltinsen O.M. (1999) Alternative shape of Spar platforms for use in hostile areas, Offshore Technology Conference, Houston, TX, OTC-10953.
Hendriks M. and Lange F. (2005) Spar Installation in deep water- a developing capability, Offshore Technology Conference, Houston, USA, OTC-17516.
Huang C.H. and Bloebraum C.L. (2004) Multi-Objective Pareto Concurrent Subspace Optimization for Multidisciplinary Design, 42nd AIAA Aerospace Science Meeting and Exhibit, RENO, NV, USA, AIAA Paper-2004-278.
Huque Z. and Jahingir N. (2002) Application of Collaborative Optimization on a RBCC Inlet/Ejector System, 38th AIAA/ASME/SAE/ASEE Joint Propulsion Conference and Exhibit, Indianapolis, USA, AIAA 2002-3604.
Hutchison M.G., Unger E.R., and Mason W.H., et al. (1994) Variable-Complexity Aerodynamic Optimization of an HSCT Wing Using Structural Wing-Weight Equation, J. Aircraft, Vol.31(1):110-116.
Hu Z.Q., Cui W.C., and Yang J.M. (2008) Multidisciplinary design optimization- A new way to bring softer bows, 28th International Conference on Ocean, Offshore and Arctic Engineering, Estoril, Portugal.
Incecik A. (2000) Offshore design: an overview of basic concepts, Lecture Notes, Department of Marine Technology, Newcastle University, UK.
Kim H.M. (2001) Target cascading in optimal system design[D], University of Michigan, Ann Arbor, Michigan, USA.
Kim H.M., Michelena N.F., Papalambros P.Y. et al. (2003a) Target cascading in optimal system design, Journal of Mechanical design (Transactions of the ASME), 125(3):474-480.
Kim H.M., Rideout D.T., Papalambros P.Y. et al. (2003b) Analytical target cascading inautomotive vehicle design, Journal of Mechanical design (Transactions of the ASME), 125(3):481-489.
Kim H., Ragon S., Soremekun G., et al. (2004) Flexible approximation approach for bi-level integrated system synthesis, AIAA-2004-4545
Kirsch U. (1997) Two-level optimization of prestressed structures. Engineering Structures, 19(4):309-317.
Knill D. L., Giunta A.A., and Baker C.A. et al. (1998) Multidisciplinary HSCT design using response surface approximations of supersonic Euler aerodynamics, Proc. 36th Aerospace Sciences Meeting and Exhibit, Reno, NV, USA.
Kodiyalam S. and Sobieszczanski-Sobieski J. (2000a) Bi-level integrated system synthesis with response surfaces, AIAA Journal, 38(8): 1485-1497.
Kodiyalam S. and Yuan C. (2000b) Evaluation of Methods for Multidisciplinary Design Optimization (MDO), Part II. AIAA Paper, NASA/CR-2000-210313.
Krasteva D.T., Baker C. and Watson L.T. et al. (1999) Distributed control parallelism for multidisciplinary design of a high speed civil transport, Proc. 7th on the Frontiers of Massively Parallel Computation, Los Alamitos, CA.
Kroo I.M., Altus S., Braun R.D., Gage P, et al. (1994) Multidisciplinary Optimization Methods for Aircraft Preliminary Design, 5th AIAA/USAF/NASA/ISSMO Symposium on Multidisciplinary Analysis and Optimization, Panama City Beach, Florida, pp.697-707.
Lin J.G. (2004) Analysis and Enhancement of Collaborative Optimization for Multidisciplinary Design, AIAA Journal, 42 (2): 348-360.
Lokanathan A.N., Brockman J.B., Renaud J.E. (1995) A Multidisciplinary Optimization Approach to Integrated Circuit Design. Proceedings of Concurrent Engineering: A Global Perspective, CE95 Conference, McLean, Virginia.
Luo Y.H., Lu R. and Wang J. et al. (2001) Time-domain fatigue analysis for critical connections of truss spar, Proceedings of the 11st International Offshore and Polar Engineering Conference, Stavanger, Norway, pp.362-368.
Luo Y.H., Zhang B., and Tallavajhula S. (2007) Integrated structural analysis methodology for Truss spars, Proceedings of 26th International Conference on Offshore Mechanics and Arctic Engineering, San Diego, USA, OMAE 2007-29419.
McAllister C.D. and Simpson T.W. (2003)Multidisciplinary robust design optimization of an internal combustion engine, Journal of Mechanical Design Transaction of the ASME, 125(1): 124-130.
MacMillin P.E., Golovidov O. and Mason W.H. et al. (1998) An MDO investigation of the impact of pratical constraints on an HSCT configuration, Proc. 35th Aerospace Sciences Meeting and Exhibit, Reno, NV, USA.
Maher J.V., Weaver T.O., Thomas H., et al. (2005). Red Hawk hull design and topsides interfaces, Proceedings of the Offshore Technology Conference, Houston, USA, Paper No.OTC1742.
Manning V. M. (1999) High speed civil transport design via collaborative optimization [D], Stanford University, 1999.
Messac A. (1996) Physical programming: Effective optimization for computational design, AIAA Journal, 34(1):149-158.
McKay M.D., Conover W.J. and Beckman R.J. (1979) A comparison of three methods for selecting values of input variables in the analysis of output from a computer code, Technometrics, 21:239-245.
Meyerhoff W.K. (1970) Added mass of thin rectangular plates calculated by potential theory, J Ship Res, 14:100-111.
Miller D.W., de Weck O.L. and Mosier G.E. (2002) Framework for multidisciplinary integrated modelling and analysis of space telescope, 1st International Workshop on Integrated Modelling of Telescopes, Lund, Sweden.
Neu W.L., Mason W.H. and Ni S. et al. (2000) A Multidisciplinary design optimization scheme for containerships, 8th AIAA/USAF/NASA/ISSMO Symposium on Multidisciplinary Analysis and Optimization, Long Beach, USA.
Parasha S. and Bloebraum C.L. (2006) Multi-Objective Genetic Algorithm Concurrent Subspace Optimization (MOGACSSO) for Multidisciplinary Design, 8th AIAA/ASME/ASCE/AHS/ASC Structures, Structural Dynamics, and Material Conference, Rhode Island, USA, AIAA-2006-2047.
Park C.H., Lee W.I., Han W.S. and Vautrin A. (2008) Improved genetic algorithm for multidisciplinary optimization, Computers and Structures, 86:1894-1903.
Penney P.W., Riiser R.M. (1984) Preliminary design of Semi-submersible, North EastCoast Institute of Engineers & Shipbuilders, pp.49-69.
Prislin I., Blevins R.D. and Halkyard J. (1998) Viscous Damping and Added Mass of Solid Square Plates, 17th International Conference on Offshore Mechanics and Arctic Engineering, Lisbon, Portugal.
Sarpkaya T. (1976) In-line and transverse forces on cylinders in oscillating flow at high Reynold’s number, Proc. 8th Offshore Technology Conference, Houston, USA, OTC-2533.
Schittkowski K. (1985/86). NLPQL: A FORTRAN subroutine solving constrained nonlinear programming problems, Annals of Operations Research, Vol. 5:485-500.
Simpson T.W., Peplinski J., Koch P.N. and Allen J.K. (2001a) Metamodels for computer-based engineering design: survey and recommendations, Engineering with computers, 17(2):129-150.
Simpson T.W., Lin D.K.J. and Chen W. (2001b) Sampling strategies for computer experiments: design and analysis, International Journal of Reliability and Applications, 2(3):209-240.
Sobieski I.P., Manning V.M., Kroo I.M. (1998) Response surface estimation and refinement in Collaborative Optimization, 7th AIAA/USAF/NASA/ISSMO Symposium on Multidisciplinary Analysis and Optimization, St. Louis, USA, AIAA-98-4753.
Sobieski I.P., Kroo I.M. (2000) Collaborative Optimization using Response Surface Estimation, AIAA Journal, 38 (10):1931-1939.
Sobiesczanski-Sobieski J. (1982) A linear decomposition method for optimization problem – blueprint for development, NASA Technical Memorandum 83248, 1982.
Sobiesczanski-Sobieski J. (1988) Optimization by Decomposition: A Step from Hierarchic to Non-Hierarchic Systems, 2nd NASA/Air Force Symposium on Recent Advances in Multidisciplinary Analysis and Optimization, Hampton, VA, NASA-TM-101494, NASA-CP-3031, Part 1.
Sobiesczanski-Sobieski J. (1990) The Sensitivity of Complex, Internally Coupled Systems, AIAA Journal, 28(1):153-160.
Sobieszczanski-Sobieski J. and Haftka R. (1997) Multidisciplinary aerospace design optimization: survey of recent developments, Structural Optimization, 14(1):1-23.
Sobieszczanski-Sobieski J., Agte J., Sandusky R. Jr. (1998) Bi-level integrated system
synthesis (BLISS), 7th AIAA/USAF/NASA/ ISSMO Symposium on Multidisciplinary Analysis and Optimization, St. Louis, Missouri, AIAA-1998-4916.
Sobieszczanski-Sobieski J., Emiley M. and Agte J., et al. (2000) Advancement of Bi-Level Integrated System Synthesis (BLISS), 38th Aerospace Sciences Meeting and Exhibit, Reno, NV, AIAA-2000-421.
Sobieszczanski-Sobieski J., Altus T., Phillips M., et al. (2003) Bi-level Integrated System Synthesis for Concurrent and Distributed Processing, AIAA Journal, 41(10): 1996-2002.
Stelmack M.A., Batill S.M., Beck B.C., et al. (1998) Application of the Concurrent Subspace Design Framework to Aircraft Brake Component Design Optimization, AIAA paper, pp.98-2033.
Tedford N.P. and Martins J.R.R.A. (2006) On the common structure of MDO problems: A comparison of architectures, 11th AIAA/ ISSMO Symposium on Multidisciplinary Analysis and Optimization Conference, Poutsmouth, Virginia, AIAA-2006-7080.
Thiagarajan K.P., Datta I., and Ran A.Z. et al. (2002) Influence of heave plate geometry on the heave response of Classic spars, Proceedings of 21st International Conference on Offshore Mechanics and Arctic Engineering, Oslo, Norway, OMAE 2002-28350.
Troesch A.W., Perlin M. and He H. (2000) Hydrodynamics of thin plates, Joint Industry Report.
Wang J., Zhang B. and Berg S. (2002) Truss spar time domain inplace structural strength analysis, Offshore Technology Conference, Houston, TX, OTC-14299.
Wang Y. and Fang K.T. (1981) A note on uniform distribution and experimental design, Kexue Tongbao, 26: 485-489.
Wrenn G.A. and Dovi A.R. (1988) Multilevel decomposition approach to the preliminary sizing of a transport aircraft wing, AIAA Journal of Aircraft. 25(7):32-38.
Wujek B.A., Renaud J.E., Batill S.M., Brockman J.B. (1996a) Concurrent Subspace Optimization Using Design Variable Sharing in a Distributed Computing Environment, Concurrent Engineering, 4(4): 361-377.
Wujek B.A., Renaud J.E., Johnson E.W., et al. (1996b) Design Flow Management and Multidisciplinary Design Optimization in Application to Aircraft Concept Sizing, The 34th AIAA Aerospace Sciences Meeting and Exhibit, Reno, Nevada, AIAA-96-0713.
Yu X.Q., Stelmack M.A., Batill S.M. (1998) An application of the concurrent subspacedesign (CSD) to the preliminary design of a low-Reynolds number UAV, AIAA paper, 98-4917.
白小涛(2005)飞机多学科设计协同优化及近似技术研究.硕士学位论文,西北工业大学.
操安喜(2008)载人潜水器多学科设计优化方法及其应用研究.博士学位论文,上海交通大学.
陈炉云(2008)基于多学科设计优化的潜艇结构-声辐射优化研究.博士学位论文,上海交通大学.
陈琪峰(2003)飞行器分布式协同进化多学科设计优化方法研究.博士学位论文,国防科技大学.
董艳秋(2005)深海采油平台波浪载荷及响应.天津:天津大学出版社.
范辉,李为吉(2008)一种高效的基于可靠性的多学科设计优化方法.中国航空学报(英文版),21(4):335-340.
方开泰(1978)均匀设计——数论方法在试验设计中的应用.概率统计通讯,1:56-97.
方开泰(1980)均匀设计.应用数学学报,3: 363-372.
方开泰(1994)均匀设计与均匀设计表,北京:科学出版社.
方开泰,马长兴(2001)正交与均匀试验设计,北京:科学出版社.
冯向军(2008)多学科设计优化方法及其在导航星座设计中的应用.博士学位论文, 国防科学技术大学.
高鹏(2007) Spar平台结构设计研究.硕士学位论文,上海交通大学.
苟鹏(2009)深海空间站结构系统地多学科设计优化探索.博士学位论文,上海交通大学.
顾敏童(2001)船舶设计原理.上海:上海交通大学出版社.
郝黎晶(2008)单柱式深水平台结构设计准则及主体强度初探.硕士学位论文,上海交通大学.
胡峪(2001)多学科设计优化及其应用研究.博士学位论文,西北工业大学.
胡志强(2008)多学科设计优化技术在深水半潜式钻井平台概念设计中的应用研究.博士学位论文,上海交通大学.
纪亨腾,黄国梁,范菊(2003)垂荡阻尼板的强迫振荡实验.上海交通大学学报, 37(7):977-980.
雷宗友(1988)中国海环境手册.上海:上海交通大学出版社.
李芬,邹早建(2003)浮式海洋结构物研究现状及发展趋势.武汉理工大学学报(交通科学与工程版), 27(5): 682-686.
李响(2003)多学科设计优化方法及其在飞行器设计中的应用.博士学位论文,西北工业大学.
李玉成(1998)海洋工程技术的新发展.中国海洋平台, 13 (1): 9-12.
凌六一(2006)基于ATC的供应链优化设计.博士学位论文,中国科学技术大学.
刘军,易宏(2009) CGX巡洋舰多学科设计优化模型的再分析.船舶力学,13(6): 895-904.
刘克龙,姚卫星,余雄庆(2007)几种新型多学科设计优化算法及比较.计算机集成制造系统, 13(2):209-216.
刘蔚(2007)多学科设计优化方法在7000米载人潜水器总体设计中的应用.博士学位论文,上海交通大学.
潘彬彬,崔维成,何凌(2009)船舶多学科设计优化中的船型变换模块.船舶力学,13(6): 886-894.
石红珊(2007a)深水单立柱采油平台方案设计及稳性研究.硕士学位论文,上海交通大学.
石红珊,柳存根(2007b) Spar平台及其总体设计中的考虑.中国海洋平台,22(1):1-4.
徐琦(2002) Truss Spar平台简介.中国造船,43(增刊).
薛飞,余雄庆,姚卫星(2005)轻型飞机机翼气动/结构协同优化研究.计算力学学报,22(4): 488-491.
薛鸿祥(2008)新型深海多柱桁架式平台及立管结构疲劳性能研究.博士学位论文,上海交通大学.
孙奕捷,申功璋(2009)飞机多学科设计优化中的并行多目标子空间优化框架.航空学报,30(8): 1421-1428.
姚熊亮,李克杰,张阿漫(2006)水下爆炸时舰船正交异性板的简化方法研究.中国舰船研究, 1(3): 30-37.
余雄庆(1999)多学科设计优化算法及其在飞机设计中的应用研究.博士学位论文,南京航空航天大学.
余雄庆,薛飞,穆雪飞等(2003)用遗传算法提高协同优化方法的可靠性,中国机械工程, 14(21): 1808-1881.
邢小楠,徐元铭,李烁,杨笑菡(2004)神经网络响应面逼近在飞机总体优化设计中的应用.机械设计与研究, 20(1): 69-71.
张帆,杨建民,李润培(2005) Spar平台的发展趋势及其关键技术.中国海洋平台, 20(2):6-11.
张帆(2008a).深海立柱式平台概念设计及水动力性能研究.博士学位论文,上海交通大学.
张帆,杨建民,李润培,柳存根(2008b).多柱桁架式立柱平台概念设计.上海造船, 1:18-20.
张海彬,沈志平,李小平(2007)深水半潜式钻井平台波浪载荷预报与结构强度评估.船舶, 2: 33-38.
张科施,李为吉,李响(2005)飞机概念设计的多学科综合优化技术.西北工业大学学报, 23(1):102-106.
张智,董艳秋,芮光六(2004),一种新型的深海采油平台Spar.中国海洋平台, 19(6):29-35
张智(2005)Spar平台系泊计算及波浪载荷研究.博士学位论文,天津大学.
赵敏(2009)两级集成系统协同优化方法及其在深海空间站总体概念设计中的应用.博士学位论文,上海交通大学.
智翠梅(2007)均匀设计及优化.化工中间体,3: 7-10.
周浩,陈万春,殷兴良(2008)高超声速飞行器多段弹道协作优化.北京航空航天大学学报,34(9): 1092-1095.