核电厂运行关键控制过程仿真优化与方法研究
|
摘要
我国核电产业正处在快速发展阶段，按照国家的发展规划，到2020年中国的核电装机容量将由原来的4000万千瓦提高到7000万千瓦。安全高效的利用核能是保障核电高速发展的前提，核电厂控制管理的关键技术是建立在控制科学和技术的发展基础上的，控制科学的每一次发展都是对实际应用中出现的各种问题的深刻地思考和对困难的克服，智能控制是人工智能与自动控制研究的重要领域，智能控制在核电厂控制中的应用是近年来研究的热点，其中群智能的研究和应用受到了广泛的关注，群智能作为人工智能的一个分支，由于其具有应用方法可行性强、容易实现等优点，已在多个领域的研究中取得了良好的效果；在核电厂控制实体方面：随着直接数字控制技术DDC（Direct Digital Control）的发展，目前国内外普遍使用的核电厂计算机控制系统大部分采用了建立在DDC基础之上的DCS（Distributed Control System）分散式控制系统，其良好的性能保证了核电厂的正常运行；在反应堆堆型方面，国内外商用核电机组中压水反应堆占据了主要份额。本文以压水堆核电厂为对象，对反应堆功率控制、蒸汽发生器压差和给水流量控制进行了深入研究，在建立控制仿真模型基础上,从实时控制的角度将传统控制理论和智能控制理论相结合进行控制优化，从事物发展变化不确定性的角度出发，利用随机网络和随机过程的理论对核电厂的启堆运行过程、突发事故应急过程进行定量分析和算法优化，并利用现有的计算机软硬件条件，对核电厂控制运行信息管理系统平台提出了详细设计方案和技术细节分析，主要的研究工作和成果包括:
（1）对核电厂反应堆功率控制的冷却剂平均温度控制方案进行了控制仿真模型的构建，对传统控制棒的棒速程序进行了模糊控制的设计和推导，在模糊棒速控制仿真结果的基础上，进行反应堆功率控制的主控制回路的瞬态过程分析和控制棒动作仿真研究，得到了模糊化棒速控制程序的效果和结论。
（2）以蒸汽发生器压差和给水流量控制回路实例为研究对象，采用数字PID算法和粒子群优化相结合的思路，在粒子群优化结果作为初选目标的基础上，建立控制参数的优化采样范围。利用控制理论的稳态和瞬态相结合的分析方法，分析控制参数变化对结果的影响和变化趋势，从而最终获得控制参数优化结果，降低了寻优的盲目性。
（3）从随机过程分析的角度将核电厂运行中的多个关联环节作为带有随机性质的过程进行分析。以反应堆启堆过程中冷却泵启动过程作为分析实例，定量计算冷却泵的启动成功概率、时间消耗以及与生产过程相关的条件概率。并从计算过程中提取适合于核电厂类似随机过程的分析方法。在对日本福岛核事故处理过程分析的基础上，针对核电厂的突发事件处理和核事故应急过程，以降低核事故和突发核事件的影响为目标，提出了当应急资源一定的前提下的优化计算方法。
（4）我国核电厂目前普遍采用的是国外商用DCS控制系统，针对不同的应用环境对系统的需求是不同的，进口系统的功能扩展是受制于国外知识产权保护的，自主开发和设计是我国核电产业各系统的发展趋势，本文针对核电厂控制和运行信息管理，提出将实时控制信息、统计数据信息以及优化控制参数信息，通过网络化的平台进行数据整合，提出了详细的设计方案和技术细节，为核电厂相关子系统的自主软件开发提供了具体的思路。
China's nuclear power industry is in a stage of rapid development, in accordancewith the national development plan to2020, China's installed nuclear power capacitywill be increased from40million kilowatts to70million kilowatts. Safe and efficientuse of nuclear energy provide protection for the rapid development of nuclear power.Nuclear power plant control and management of key technologies is built on the basisand development of control science and technology.Every development of controlscience is the solution of various problems in the practical application and deepthinking. Intelligent control is an important area of research in artificial intelligenceand automatic control, intelligent control applications in the nuclear power plantcontrol is a hot research in recent years. In addition the swarm intelligence researchand applications have also been widespread concern, swarm intelligence as artificialintelligence branch because of its advantages of application method is feasible andeasy to implement in many fields of research have achieved good results. In terms ofcontrolled entities: With the development of direct digital control technology(DDC:Direct Digital Control), nowadays at home and abroad widespread use ofnuclear power plant computer control system is mostly built on the basis of DCS(Distributed Control System), its good performance ensure the normal operation ofnuclear power plants. In the reactor type, the pressurized water reactor nuclear powerplants accounted for a major share of the domestic and international commercialnuclear power generating units. Pressurized water reactor nuclear power plant, andin-depth study on the reactor power control, differential pressure and feedwater flowcontrol of the steam generator is reflected in this paper. On the basis of a simulationmodel, the traditional control theory and the theory of intelligent control are usedfrom the perspective of real-time control of the control optimization. From the uncertainty of the development and changes of things, random networks and randomprocess theory are used in the start-up phase of reactor and in the accidentcontingency process analysis and quantitative algorithm optimization. Based on theexisting computer hardware and software technology，the control and operationinformation management system platform of nuclear power plant were designed andestablished in detail. The main research work and achievements include:
(1) Construction of simulation model of the average temperature of the coolantcontrol in nuclear power plant reactor power control system and the comparison ofresult between traditional control rod speed program design and the fuzzy control rodspeed program.Transient reactor power control of the main control loop and thecontrol rod movement analysis and simulation were analysised in this paper. Rodspeed control of the fuzzy effect and conclusions are achieved.
(2) Digital PID algorithm and particle swarm optimization combining ideas isused to get the preliminary goal and to establish the sampling range of the controlparameters in the instance of control loop of steam generator differential pressure andwater flow. The combination of steady state control and transient control analysismethod is used to analyze the affect of control parameters change and trend results,control parameter optimization is obtained and the blindness of looking foroptimization is reduced.
(3) Uncertainty in the process of the control operation of nuclear power plantswere analyzed from the perspective of the random process. Cooling pump startupprocess in the start-up phase of reactor is used as a reactor startup process analysisexample, Cooling pump startup success probability, time consuming, and theconditional probability associated with the production process were calculated. Similarstochastic process analysis method suitable for nuclear power plant extract wereextracted from the calculation process. Optimization method was put forward in caseof certain preconditions emergency resources treated as unexpected events and nuclearemergency process for nuclear power plants to reduce the impact of nuclear accidentsand sudden nuclear events based on the analysis of emergency treatment process ofFukushima nuclear accident in Japan.
(4) Nuclear power plants in china are currently widely used foreign commercialDCS control system. System requirements for different application environments aredifferent, the function of the system expansion is subject to the protection of foreignintellectual property. Self-development and design is the development trend ofChinese nuclear power industry. In this paper in connection with the nuclear power plant control and operation of information management, real-time control information,statistical data as well as optimal control parameter information were integrated in thenetwork platform for data integration. Detailed design and technical details were putforward. Specific ideas was provided to the independent software development for thenuclear power plant subsystems.
（1）对核电厂反应堆功率控制的冷却剂平均温度控制方案进行了控制仿真模型的构建，对传统控制棒的棒速程序进行了模糊控制的设计和推导，在模糊棒速控制仿真结果的基础上，进行反应堆功率控制的主控制回路的瞬态过程分析和控制棒动作仿真研究，得到了模糊化棒速控制程序的效果和结论。
（2）以蒸汽发生器压差和给水流量控制回路实例为研究对象，采用数字PID算法和粒子群优化相结合的思路，在粒子群优化结果作为初选目标的基础上，建立控制参数的优化采样范围。利用控制理论的稳态和瞬态相结合的分析方法，分析控制参数变化对结果的影响和变化趋势，从而最终获得控制参数优化结果，降低了寻优的盲目性。
（3）从随机过程分析的角度将核电厂运行中的多个关联环节作为带有随机性质的过程进行分析。以反应堆启堆过程中冷却泵启动过程作为分析实例，定量计算冷却泵的启动成功概率、时间消耗以及与生产过程相关的条件概率。并从计算过程中提取适合于核电厂类似随机过程的分析方法。在对日本福岛核事故处理过程分析的基础上，针对核电厂的突发事件处理和核事故应急过程，以降低核事故和突发核事件的影响为目标，提出了当应急资源一定的前提下的优化计算方法。
（4）我国核电厂目前普遍采用的是国外商用DCS控制系统，针对不同的应用环境对系统的需求是不同的，进口系统的功能扩展是受制于国外知识产权保护的，自主开发和设计是我国核电产业各系统的发展趋势，本文针对核电厂控制和运行信息管理，提出将实时控制信息、统计数据信息以及优化控制参数信息，通过网络化的平台进行数据整合，提出了详细的设计方案和技术细节，为核电厂相关子系统的自主软件开发提供了具体的思路。
China's nuclear power industry is in a stage of rapid development, in accordancewith the national development plan to2020, China's installed nuclear power capacitywill be increased from40million kilowatts to70million kilowatts. Safe and efficientuse of nuclear energy provide protection for the rapid development of nuclear power.Nuclear power plant control and management of key technologies is built on the basisand development of control science and technology.Every development of controlscience is the solution of various problems in the practical application and deepthinking. Intelligent control is an important area of research in artificial intelligenceand automatic control, intelligent control applications in the nuclear power plantcontrol is a hot research in recent years. In addition the swarm intelligence researchand applications have also been widespread concern, swarm intelligence as artificialintelligence branch because of its advantages of application method is feasible andeasy to implement in many fields of research have achieved good results. In terms ofcontrolled entities: With the development of direct digital control technology(DDC:Direct Digital Control), nowadays at home and abroad widespread use ofnuclear power plant computer control system is mostly built on the basis of DCS(Distributed Control System), its good performance ensure the normal operation ofnuclear power plants. In the reactor type, the pressurized water reactor nuclear powerplants accounted for a major share of the domestic and international commercialnuclear power generating units. Pressurized water reactor nuclear power plant, andin-depth study on the reactor power control, differential pressure and feedwater flowcontrol of the steam generator is reflected in this paper. On the basis of a simulationmodel, the traditional control theory and the theory of intelligent control are usedfrom the perspective of real-time control of the control optimization. From the uncertainty of the development and changes of things, random networks and randomprocess theory are used in the start-up phase of reactor and in the accidentcontingency process analysis and quantitative algorithm optimization. Based on theexisting computer hardware and software technology，the control and operationinformation management system platform of nuclear power plant were designed andestablished in detail. The main research work and achievements include:
(1) Construction of simulation model of the average temperature of the coolantcontrol in nuclear power plant reactor power control system and the comparison ofresult between traditional control rod speed program design and the fuzzy control rodspeed program.Transient reactor power control of the main control loop and thecontrol rod movement analysis and simulation were analysised in this paper. Rodspeed control of the fuzzy effect and conclusions are achieved.
(2) Digital PID algorithm and particle swarm optimization combining ideas isused to get the preliminary goal and to establish the sampling range of the controlparameters in the instance of control loop of steam generator differential pressure andwater flow. The combination of steady state control and transient control analysismethod is used to analyze the affect of control parameters change and trend results,control parameter optimization is obtained and the blindness of looking foroptimization is reduced.
(3) Uncertainty in the process of the control operation of nuclear power plantswere analyzed from the perspective of the random process. Cooling pump startupprocess in the start-up phase of reactor is used as a reactor startup process analysisexample, Cooling pump startup success probability, time consuming, and theconditional probability associated with the production process were calculated. Similarstochastic process analysis method suitable for nuclear power plant extract wereextracted from the calculation process. Optimization method was put forward in caseof certain preconditions emergency resources treated as unexpected events and nuclearemergency process for nuclear power plants to reduce the impact of nuclear accidentsand sudden nuclear events based on the analysis of emergency treatment process ofFukushima nuclear accident in Japan.
(4) Nuclear power plants in china are currently widely used foreign commercialDCS control system. System requirements for different application environments aredifferent, the function of the system expansion is subject to the protection of foreignintellectual property. Self-development and design is the development trend ofChinese nuclear power industry. In this paper in connection with the nuclear power plant control and operation of information management, real-time control information,statistical data as well as optimal control parameter information were integrated in thenetwork platform for data integration. Detailed design and technical details were putforward. Specific ideas was provided to the independent software development for thenuclear power plant subsystems.
引文
[1].张建民核反应堆控制[M].原子能出版社，2009.
[2].王建辉顾树生.自动控制原理[M].北京:清华大学出版社,2007.
[3].叶奇蓁.从“福岛第一核电站事故”看我国核能利用的核安全[J].物理,2011(7):428～433.
[4].石雷,从切尔诺贝利到福岛核事故看核应急行动[J].职业卫生与应急救援,2012,30(2):63~65.
[5].吴宜灿,福岛核电站事故的影响与思考[J].中国科学院院刊,2011,26(3):271~276
[6].王新新,新时期我国核电产业可持续发展对策分析研究[J].中国科技论坛,2011(7):38~44
[7].蔡自兴,智能控制原理与应用[M].北京:清华大学出版社,2007.
[8].蔡自兴,徐光佑,人工智能及应用[M].（第三版）.北京：清华大学出版社,2004.
[9].周德俭,吴斌.智能控制[M].重庆:重庆大学出版社
[10].Zixing Cai.Intelligence science: disciplinary frame and general features[C]. Proceedings of2003IEEE International Conference on Robotics, Intelligent Systems and SignalProcessing,2003:393-398.
[11].Fu, K.Learning control systems and intelligent control systems: An intersection of artificalintelligence and automatic control[J]. IEEE Transactions on AutomaticControl,1971,16(1)70-72.
[12].史忠植.智能科学[M].北京：清华大学出版社,2006.
[13].Haomin Ma; Dan Lin; Mei Tao. An intelligent voltage control system—Training, learningand controlling[C]. International Conference on Intelligent System Application to PowerSystems (ISAP),2011:25-28.
[14].De Arriaga F,El Alami M, Arriaga, A. Agents Control for Intelligent E-Learning Systems[C]International Conference on Computational Intelligence for Modelling, Control andAutomation,2005(2):877-883.
[15].Kai-Yuan Cai,Lei Zhang. Fuzzy Reasoning as a Control Problem[J].IEEE Transactions onFuzzy Systems,2008,16(3):600-614.
[16].Chih-Min Lin,Chun-Fei Hsu.Decoupled fuzzy sliding-mode control of a nonlinear aeroelasticstructure[C].FUZZ-IEEE'02.Proceedings of the2002IEEE International Conference onFuzzy Systems,2002:662-667.
[17].Li T H.S,Shih-Jie Chang.Fuzzy target tracking control of autonomous mobile robots by usinginfrared sensors[J]. IEEE Transactions on Fuzzy Systems,2004,12(4):491-501.
[18].Shaocheng Tong,Yue Li. Observer-Based Adaptive Fuzzy Backstepping Control for a Classof Stochastic Nonlinear Strict-Feedback Systems[J]. IEEE Transactions on Systems, Man,and Cybernetics, Part B: Cybernetics,2011,41(6):1693-1704.
[19].Acampora G,Loia, V. Fuzzy control interoperability and scalability for adaptive domoticframework[J]. IEEE Transactions on Industrial Informatics,2005,1(2):97-111.
[20].张巍巍,王京,王慧,赵云涛.混沌系统的变论域模糊控制算法研究[J].物理学报,2011,60(1):010511.1-7.
[21].Christian Blum,Daniel Merkle.Swarm Intelligence[M].Berlin:Verlag Berlin Heidelberg,2008.
[22].Li Yuanzuo; Yang Xiaoduan. The optimal model of integrated with the experts' opinionsbased on partical swarm optimization[C].2011International Conference on ElectricInformation and Control Engineering,2011:3713-3716.
[23].Quan-Zhu Yao,Jie Cai,Jiu-Long Zhang. Simultaneous Feature Selection and LS-SVMParameters Optimization Algorithm Based on PSO[C].WRI World Congress on ComputerScience and Information Engineering,2009,5:723-727
[24].王锦标.计算机控制系统[M].北京:清华大学出版社,2008.
[25].王常力，罗安.分布式控制系统（DCS）设计与应用实例[M].北京：电子工业出版社,2010.
[26].王锦标.TDC3000集散控制系统的配置与应用[J].自动化化仪表,1996，11(48):31-35.
[27].杨庆柏.现场总线仪表[M].北京：国防工业出版社,2005.
[28].夏继强,邢春香.现场总线工业控制网络技术[M].北京：北京航空航天大学出版社，2005.
[29].Byvaikov, M.E Zharko, Mengazetdinov N.E. Experience from design and application of thetop-level system of the process control system of nuclear power-plant[J]. Automation andRemote Control,2006,67(5):735-747.
[30].Dhong, Hoon Lee. Regulatory approach on human factors engineering of main control roommodernization: A case of Kori-1nuclear power plant in Korea[C]. IEEE HFPP Conference onHuman Factor and Power Plants,2007:66-69.
[31].Kwon, Soonman, Cheon Jong-Min. A design and implementation of a fault-tolerant rodcontrol system for nuclear power plants[C]. IEEE International Symposium on IndustrialElectronics,2006,3:1933-1936.
[32].Khan Nafisah. Distributed Control System implementation in nuclear power plantsworldwide: A Literature survey[C].29th Annual Conference of the Canadian NuclearSociety,2008,1:236-247.
[33].Suh Yong Suk, Park Je Yun. An overview of instrumentation and control systems of a Koreastandard nuclear power plant: A signal interface standpoint[J]. Nuclear Engineering andDesign,2008,238(12):3508-3521.
[34].Kang Hyun Gook,Jang Seung-Cheol. A quantitative study on risk issues in safety featurecontrol system design in digitalized nuclear power plant[J]. Journal of Nuclear Science andTechnology,2008,45(8):850-858.
[35].Di Maio Francesco, Secchi Piercesare. Fuzzy C-means clustering of signal functionalprincipal components for post-processing dynamic scenarios of a nuclear power plant digitalinstrumentation and control system[J]. IEEE Transactions on Reliability,2011,60(2):415-425.
[36].Hu Ping, Zhao Fuyu. Coordination control and simulation for small nuclear power plant [J].Progress in Nuclear Energy,2012,58:21-26.
[37].Eliasi H, Menhaj M.B. Robust nonlinear model predictive control for a PWR nuclear powerplant[J]. Progress in Nuclear Energy,2012,54:177-185.
[38].Jin Xin, Ray Asok,Edwards. Integrated robust and resilient control of nuclear power plantsfor operational safety and high performance[J]. IEEE Transactions on NuclearScience,2010,57(2)(PART2):807-817.
[39].Lin Chiuhsiang Joe, Yenn Tzu-Chung, Yang Chih-We. Automation design in advancedcontrol rooms of the modernized nuclear power plants[J]. Safety Science,2010,48(1):63-71.
[40].Chaudhry Shabbir Majeed, Amin Yasar,Chaudhry Alina Majeed, Jama Habibu. Real timeembedded controller design for safety control of PWR nuclear power reactor[J]. WSEASTransactions on Circuits and Systems,2007,6(4):452-457.
[41].Yih Swu, Fan Chin-Feng. Analyzing the decision making process of certifying digital controlsystems of nuclear power plants[J]. Nuclear Engineering and Design,2012,242:379-388.
[42].Jin Xin, Edwards Robert M. Integrated robust and resilient control for nuclear powerplants[C].6th American Nuclear Society International Topical Meeting on Nuclear PlantInstrumentation, Control, and Human-Machine Interface Technologies,2009,3:1359-1369.
[43].Cheng Shou-Yu, Shen Bo-Chang,Peng Min-Jun. Research on coordinated control in nuclearpower plant[C]. Proceedings of the2009International Conference on Machine Learning andCybernetics,2009,6:3622-3627.
[44].Etchepareborda A, Flury, C.A. Multivariable robust control of an integrated nuclear powerreactor[J]. Brazilian Journal of Chemical Engineering,2002,19(4):441-447.
[45].Bacher P, Beltranda G. Computer-aided design system used for the design of the chooz Bnuclear power plant control system[J]. Nuclear Technology,1990,89(3):275-280.
[46].Kwon Soonman, Cheon Jong-Min, Lee Jongmoo. A design and implementation of afault-tolerant rod control system for nuclear power plants[J]. IEEE International Symposiumon Industrial Electronics,2006,3:1933-1936.
[47].Hashemian H.M. The state of the art in nuclear power plant instrumentation and control[J].International Journal of Nuclear Energy Science and Technology,2009,4(4):330-354.
[48].Mikhailov M.N, Rozhdestvenskii M.I, Ukharov S.G. Automation of nuclear power systems[J].Atomic Energy,2007,103(1):553-559.
[49].Hashemian H.M. Applying online monitoring for nuclear power plant instrumentation andcontrol[J]. IEEE Transactions on Nuclear Science,2010,57(5):2872-2878.
[50].Choi In-Kyu, Kim, Jong-An. Development of a digital turbine control system in a nuclearpower plant[J]. International Journal of Control, Automation and Systems,2009,7(1):67-73.
[51].Urbach M,Koch D. Requirements of emergency control managements on data andinformation for assessment of the radiological situation in case of a severe accident in anuclear power plant[J]. Kerntechnik,2007,72(4):230-235.
[52].Carvalho Paulo V.R,dos Santos Isaac L. Micro incident analysis framework to assess safetyand resilience in the operation of safe critical systems: A case study in a nuclear powerplant[J]. Journal of Loss Prevention in the Process Industries,2008,21(3):277-286.
[53].Hwang, Sheue-Ling, Yau, Yi-Jan Lin,Yu-Ting.Predicting work performance in nuclear powerplants[J]. Safety Science,2008,46(7):1115-1124.
[54].Vasilevskii V.P, Mikhailov M.N. Development and adoption of measures for increasing thesafety of power-generating units of nuclear power plants with RBMK reactors in1986-2005[J]. Atomic Energy,2006,100(4):295-301.
[55].Xia Guoqing, Su Jie. Multivariable integrated model predictive control of nuclear powerplant[J]. International Journal of Control and Automation,2008,1(1):1-8.
[56].蔡章生.核动力反应堆中子动力学[M].北京：国防工业出版社,2005.
[57].谢仲生,张少泓.核反应堆物理理论与计算方法[M].西安：西安交通大学出版社，2000.
[58].郑福裕,邵向业,丁云峰.压水堆核电厂运行[M].北京：原子能出版社,1998.
[59].赵浮宇,曹艳.反应堆最优功率控制系统的设计[J].核科学与工程,1999,19(1):39-43.
[60].张英.秦山核电二期工程计算机仿真技术在控制系统中的应用[J].核动力工程,2003,24(2):244-248.数字化反应堆控制系统研究[J].核动力工程,2002,
[61].施希,吴萍,赵洁,刘涤尘.压水堆核电厂负荷跟踪系统设计与特性研究[J].核动力工程,2010,31(6):102-105.
[62].李云臣,张少泓,蒋兴华.平均温度控制系统R棒扰动的改进分析[J].核动力工程,2010,31(4):71-77.
[63].张瑞,彭华清.数字化反应堆控制系统研究[J].核动力工程,2002,23(S1):86-88.
[64].互动百科.复合核与反应堆多普勒效应[EB/OL]. http://www.hudong.com/wiki,2011.
[65].于平安,朱瑞安,喻真烷,沈秀中.核反应堆热工分析[M].上海：上海交通大学出版社，2002.
[66].朱继洲.核反应堆安全分析[M].西安：西安交通大学出版社，2002.
[67].沈维道,童钧耕.工程热力学[M].（第三版）北京：高等教育出版社，2007.
[68].张曙明,李华奇等.秦山核电站二期反应堆堆芯流量分配数值分析[J].核科学与工程,2010,30(4)：299-305.
[69].李红鹰,许川.秦山核电二期工程控制棒驱动机构国产化研制[J].核动力工程，2003，24(S1)：143-145.
[70].左文,阎玉辉.秦山核电二期工程棒控棒位系统设计[J].核动力工程,2003，24(S1)：146-147.
[71].喻丹萍,胡永陶.秦山核电二期工程控制棒导向组件动态特性试验研究[J].核动力工程,2003，24(S1)：158-160.
[72].李国勇智能控制及Matalb实现[M].北京：电子工业出版社，2005.
[73].龙升照,汪培庄.Fuzzy控制规则的自调整问题[J].模糊数学,1982,2(3):105-112.
[74].梁保松,曹殿立.模糊数学及其应用[M].北京：科学出版社，2007.
[75].佟绍成.非线性系统的自适应模糊控制[M].北京：科学出版社，2006,10-218.
[76].Zadeh L A.Fuzzy sets[J].Information and Control,1965,8:338-353.
[77].Zadeh L A.Outline of a new approach to the analysis of complex systems and decisionprocesses[J].IEEE Tran.Systems,Man,and Cybernetics,1973,3(1):28-44.
[78].Mamdani E H.Applications of fuzzy algorithms for simple dynamic plant[J].Proc.IEEControl and Science1974,121(12):1585-1588.
[79].Holmblad L P and Qstergaard J J.Control of a cement kiln by fuzzy logic[M].FuzzyInformation and Decision Processes.New York:North-Holland,1982,389-399.
[80].Yasunobu S and Miyamoto S.Automatic train operation system by predictive fuzzycontrol[M].Industrial Application of Fuzzy Control.North-Holland,1985,1-18.
[81].Lin C,Wang Q G and Lee T H.Stability and stabilization of a class of fuzzy descriptorsystems[J].IEEE Trans.Fuzzy Systems,2006,14(4):542-551.
[82].徐济鋆,贾斗南.沸腾换热与汽液两相流[M].北京：原子能出版社，2002.
[83].钱虹,叶建华,钱非,李超.蒸汽发生器水位全程控制系统数字化及仿真实现[J].核动力工程,2010,31(2):58-62.
[84].Lin Lun.核电厂蒸汽发生器数字化仪表与控制对象实时仿真系统[M].北京：原子能出版社，2003.
[85].杨柳,袁景淇.压水堆蒸汽发生器水位的前馈模型预测控制[J].控制工程，2008，15(3):251-253．
[86].陈智,张英,王华金,张瑞.岭澳核电站二期蒸汽发生器水位控制系统相关传递函数的辨识方法[J].核动力工程,2011,32(5):29-32.
[87].陈智,张英,张帆,余红星.岭澳核电站蒸汽发生器水位控制系统改进方案仿真研究[J].核动力工程,2010,31(4):66-70.
[88].王川,于雷.自然循环蒸汽发生器倒U型管内单相流体倒流特性研究[J].核动力工程,2011,32(1):58-62.
[89].李凤宇,陆古兵,张龙飞,刘东.蒸汽发生器水位双PI控制的改进研究[J].原子能科学技术,2010,44(S1):279-282.
[90].林卫星,陈炎海.一种快速收敛的改进粒子群优化算法[J].系统仿真学报,2011,23(11):2406-2411. Coordination control and simulation for small nuclear powerplant
[91].程启明,程尹曼,汪明媚,薛阳,胡晓青.基于混沌粒子群算法优化的自抗扰控制在蒸汽发生器水位控制中的应用研究[J].华东电力,2011,39(6):957-962.
[92].王林,刘君,曾宇容,易觉.基于粒子群优化算法和模糊模拟的核电备件模糊EOQ模型[J].系统工程,2008,26(11):123-126.
[93].徐辉,李石君,.一种整合粒子群优化和K-均值的数据聚类算法[J].山西大学学报(自然科学版),2011,34(4):518-523.
[94].应明峰,鞠全勇,高峰,.基于粒子群优化的PID控制器设计与应用[J].计算机仿真,2011,28(11):283-287.
[95].刘金琨.先进PID控制Matlab仿真[M].北京：电子工业出版社，2009.
[96].Tan Ying, Z.M.Xiao. Clonal particle swarm optimization and its applications[C].IEEECongress on Evolutionary Computation,2007:2303-2309
[97].Junqi Zhang, Z.M.Xiao, Ying Tan, Xingui He.Hybrid Particle Swarm Optimizer withAdvance and Retreat Strategy and Clonal Mechanism for Global Numerical Optimization[C].IEEE World Congress on Computational Intelligence2008:2059-2066.
[98].刘坤,谭营,何新贵.基于粒子群优化的过程神经网络学习算法[J].北京大学学报(自然科学版),2011,47(2):238-244.
[99].徐静波.基于PSO算法的PID控制参数优化[J].东华大学学报(自然科学版),2007,33(1):135-138
[100].冯允成.随机网络及其应用[M].北京:北京航空航天大学出版社，1987.
[101].郑轶松,齐二石,郑晓东.基于图示评审技术GERT的高科技产品开发研究[J].系统工程,2005，23(11):112-115.
[102]. Gaurishankar,Vandana Sahan.GERT Analysis of a Two-Unit Cold Standby System byRepair[J],Microelectron.Reliab,1995,35(5):837-840.
[103]. Yang Bao-Hua，Fang Zhi-Geng.Model of GERT network based on grey information andits applications[C].IEEE International Conference on Grey Systems and IntelligentServices,2011:640-644.
[104]. Gavareshki M.H.Karimi. Newfuzzy GERT method for research projectsscheduling[C].IEEE International Engineering Management Conference on Innovation andEntrepreneurship for Sustainable Development,2004,2:820-824.
[105]. Matsumoto Tsuyoshi. Evaluation for development of superconducting technologies inpower sectors using GERT[C]. Proceedings of the IASTED Multi-Conference-Power andEnergy Systems,2003,7:109-114.
[106].方志耕.随机网络（GERT）模型[EB/OL]. http://video.chaoxing.com,2010.
[107].熊杨恒.日本福岛核泄漏事故与核能发电前景展望[EB/OL].http://video.chaoxing.com,2011.
[108].陈绍廉.核能的安全和合理利用[EB/OL]. http://video.chaoxing.com,2011.
[109]. World Nuclear Association. Fukushima Accident2011[EB/OL].http://www.world-nuclear.org,2012.
[110].李文辉,苏永杰.核电厂应急监测探讨[J].辐射防护,2011,31(4):252-256.
[111].杨保华,方志耕,刘思峰,郭本海.基于GERT网络的应急抢险过程资源优化配置模型研究[J].管理学报,2011,8(12):1883.
[112].龚迪琛,方方,黄洪全.一种混合结构的无功补偿控制系统的设计[J].电力系统保护与控制,2009,37(13):80-82.
[113].赵朋飞,李乃乾.基于XML的分布式数据库集成系统[J].计算机工程,2010,36(13):70-72.
[114].郑荣,马世龙.网格环境下基于XML的异构数据集成系统[J].计算机工程,2008,34(22):52-54.
[115].张水平,孙云星,张凤琴等.SOA架构的分布式网络监管系统的设计与实现[M].计算机工程与设计，2011,32(7):2352-2355.
[116].刘黎志,吴云韬.应用WCF分布式框架实现移动数据同步[J].计算机应用，2011，31(12):3281-3284.
[117].吴莉.基于.NET框架的N层分布式应用程序研究[J]贵州工业大学学报(自然科学版)，2008，37(4):207－210．
[118].殷跃鹏,郭长国,李小玲,王怀民.基于事件的分布式系统行为分析框架[J].微电子学与计算机，2010，27(8):70-76.
[119].霍林,黄俊文,潘英花,王力.大规模分布式资源搜索技术研究进展[J].计算机应用研究，2010，27(11):4006-4009.
[120]. FUNG K T,CHAN Y L,SIU W C.Low-Complexity and High-Quality Frame-SkippingTranscoder for Continuous Presence Multipoint Video Conferencing[J].IEEE Transactions onMultimedia,2004,6(1):31-46.
[121]. LYNDEN S，MUKHERJEE A，HUME A，et al．The design and imple-mentation ofOGSA-DQP:a service-based distributed query processor[J].Future Generation ComputerSystems，2009，25(3):224-236．
[122]. CZAJKOWSKIY K，FITZGERALDZ S，FOSTER I．Grid information services fordistributed resource sharing［C］Proc of the10th IEEE International Symposium on HighPerformance Distributed Computing．2001:181-195．
[123]. SHEN Heng-tao，SHU Yan-feng，YU Bei．Efficient semantic-based content search inP2P network[J].IEEE Trans on Knowledge and Data Engineering,2004,17(7):813-826．
[124]. LACKS D,KOCAK T.Developing reusable simulation core code for networking:the gridresource discovery example［J］．Journal of Sys-tems and Software，2009，82(1):89-100．
[125].肖侬,任浩,徐志伟等.基于资源目录技术的网格系统软件设计与实现[J].计算机研究与发展，2002，39(8):902-906．
[2].王建辉顾树生.自动控制原理[M].北京:清华大学出版社,2007.
[3].叶奇蓁.从“福岛第一核电站事故”看我国核能利用的核安全[J].物理,2011(7):428～433.
[4].石雷,从切尔诺贝利到福岛核事故看核应急行动[J].职业卫生与应急救援,2012,30(2):63~65.
[5].吴宜灿,福岛核电站事故的影响与思考[J].中国科学院院刊,2011,26(3):271~276
[6].王新新,新时期我国核电产业可持续发展对策分析研究[J].中国科技论坛,2011(7):38~44
[7].蔡自兴,智能控制原理与应用[M].北京:清华大学出版社,2007.
[8].蔡自兴,徐光佑,人工智能及应用[M].（第三版）.北京：清华大学出版社,2004.
[9].周德俭,吴斌.智能控制[M].重庆:重庆大学出版社
[10].Zixing Cai.Intelligence science: disciplinary frame and general features[C]. Proceedings of2003IEEE International Conference on Robotics, Intelligent Systems and SignalProcessing,2003:393-398.
[11].Fu, K.Learning control systems and intelligent control systems: An intersection of artificalintelligence and automatic control[J]. IEEE Transactions on AutomaticControl,1971,16(1)70-72.
[12].史忠植.智能科学[M].北京：清华大学出版社,2006.
[13].Haomin Ma; Dan Lin; Mei Tao. An intelligent voltage control system—Training, learningand controlling[C]. International Conference on Intelligent System Application to PowerSystems (ISAP),2011:25-28.
[14].De Arriaga F,El Alami M, Arriaga, A. Agents Control for Intelligent E-Learning Systems[C]International Conference on Computational Intelligence for Modelling, Control andAutomation,2005(2):877-883.
[15].Kai-Yuan Cai,Lei Zhang. Fuzzy Reasoning as a Control Problem[J].IEEE Transactions onFuzzy Systems,2008,16(3):600-614.
[16].Chih-Min Lin,Chun-Fei Hsu.Decoupled fuzzy sliding-mode control of a nonlinear aeroelasticstructure[C].FUZZ-IEEE'02.Proceedings of the2002IEEE International Conference onFuzzy Systems,2002:662-667.
[17].Li T H.S,Shih-Jie Chang.Fuzzy target tracking control of autonomous mobile robots by usinginfrared sensors[J]. IEEE Transactions on Fuzzy Systems,2004,12(4):491-501.
[18].Shaocheng Tong,Yue Li. Observer-Based Adaptive Fuzzy Backstepping Control for a Classof Stochastic Nonlinear Strict-Feedback Systems[J]. IEEE Transactions on Systems, Man,and Cybernetics, Part B: Cybernetics,2011,41(6):1693-1704.
[19].Acampora G,Loia, V. Fuzzy control interoperability and scalability for adaptive domoticframework[J]. IEEE Transactions on Industrial Informatics,2005,1(2):97-111.
[20].张巍巍,王京,王慧,赵云涛.混沌系统的变论域模糊控制算法研究[J].物理学报,2011,60(1):010511.1-7.
[21].Christian Blum,Daniel Merkle.Swarm Intelligence[M].Berlin:Verlag Berlin Heidelberg,2008.
[22].Li Yuanzuo; Yang Xiaoduan. The optimal model of integrated with the experts' opinionsbased on partical swarm optimization[C].2011International Conference on ElectricInformation and Control Engineering,2011:3713-3716.
[23].Quan-Zhu Yao,Jie Cai,Jiu-Long Zhang. Simultaneous Feature Selection and LS-SVMParameters Optimization Algorithm Based on PSO[C].WRI World Congress on ComputerScience and Information Engineering,2009,5:723-727
[24].王锦标.计算机控制系统[M].北京:清华大学出版社,2008.
[25].王常力，罗安.分布式控制系统（DCS）设计与应用实例[M].北京：电子工业出版社,2010.
[26].王锦标.TDC3000集散控制系统的配置与应用[J].自动化化仪表,1996，11(48):31-35.
[27].杨庆柏.现场总线仪表[M].北京：国防工业出版社,2005.
[28].夏继强,邢春香.现场总线工业控制网络技术[M].北京：北京航空航天大学出版社，2005.
[29].Byvaikov, M.E Zharko, Mengazetdinov N.E. Experience from design and application of thetop-level system of the process control system of nuclear power-plant[J]. Automation andRemote Control,2006,67(5):735-747.
[30].Dhong, Hoon Lee. Regulatory approach on human factors engineering of main control roommodernization: A case of Kori-1nuclear power plant in Korea[C]. IEEE HFPP Conference onHuman Factor and Power Plants,2007:66-69.
[31].Kwon, Soonman, Cheon Jong-Min. A design and implementation of a fault-tolerant rodcontrol system for nuclear power plants[C]. IEEE International Symposium on IndustrialElectronics,2006,3:1933-1936.
[32].Khan Nafisah. Distributed Control System implementation in nuclear power plantsworldwide: A Literature survey[C].29th Annual Conference of the Canadian NuclearSociety,2008,1:236-247.
[33].Suh Yong Suk, Park Je Yun. An overview of instrumentation and control systems of a Koreastandard nuclear power plant: A signal interface standpoint[J]. Nuclear Engineering andDesign,2008,238(12):3508-3521.
[34].Kang Hyun Gook,Jang Seung-Cheol. A quantitative study on risk issues in safety featurecontrol system design in digitalized nuclear power plant[J]. Journal of Nuclear Science andTechnology,2008,45(8):850-858.
[35].Di Maio Francesco, Secchi Piercesare. Fuzzy C-means clustering of signal functionalprincipal components for post-processing dynamic scenarios of a nuclear power plant digitalinstrumentation and control system[J]. IEEE Transactions on Reliability,2011,60(2):415-425.
[36].Hu Ping, Zhao Fuyu. Coordination control and simulation for small nuclear power plant [J].Progress in Nuclear Energy,2012,58:21-26.
[37].Eliasi H, Menhaj M.B. Robust nonlinear model predictive control for a PWR nuclear powerplant[J]. Progress in Nuclear Energy,2012,54:177-185.
[38].Jin Xin, Ray Asok,Edwards. Integrated robust and resilient control of nuclear power plantsfor operational safety and high performance[J]. IEEE Transactions on NuclearScience,2010,57(2)(PART2):807-817.
[39].Lin Chiuhsiang Joe, Yenn Tzu-Chung, Yang Chih-We. Automation design in advancedcontrol rooms of the modernized nuclear power plants[J]. Safety Science,2010,48(1):63-71.
[40].Chaudhry Shabbir Majeed, Amin Yasar,Chaudhry Alina Majeed, Jama Habibu. Real timeembedded controller design for safety control of PWR nuclear power reactor[J]. WSEASTransactions on Circuits and Systems,2007,6(4):452-457.
[41].Yih Swu, Fan Chin-Feng. Analyzing the decision making process of certifying digital controlsystems of nuclear power plants[J]. Nuclear Engineering and Design,2012,242:379-388.
[42].Jin Xin, Edwards Robert M. Integrated robust and resilient control for nuclear powerplants[C].6th American Nuclear Society International Topical Meeting on Nuclear PlantInstrumentation, Control, and Human-Machine Interface Technologies,2009,3:1359-1369.
[43].Cheng Shou-Yu, Shen Bo-Chang,Peng Min-Jun. Research on coordinated control in nuclearpower plant[C]. Proceedings of the2009International Conference on Machine Learning andCybernetics,2009,6:3622-3627.
[44].Etchepareborda A, Flury, C.A. Multivariable robust control of an integrated nuclear powerreactor[J]. Brazilian Journal of Chemical Engineering,2002,19(4):441-447.
[45].Bacher P, Beltranda G. Computer-aided design system used for the design of the chooz Bnuclear power plant control system[J]. Nuclear Technology,1990,89(3):275-280.
[46].Kwon Soonman, Cheon Jong-Min, Lee Jongmoo. A design and implementation of afault-tolerant rod control system for nuclear power plants[J]. IEEE International Symposiumon Industrial Electronics,2006,3:1933-1936.
[47].Hashemian H.M. The state of the art in nuclear power plant instrumentation and control[J].International Journal of Nuclear Energy Science and Technology,2009,4(4):330-354.
[48].Mikhailov M.N, Rozhdestvenskii M.I, Ukharov S.G. Automation of nuclear power systems[J].Atomic Energy,2007,103(1):553-559.
[49].Hashemian H.M. Applying online monitoring for nuclear power plant instrumentation andcontrol[J]. IEEE Transactions on Nuclear Science,2010,57(5):2872-2878.
[50].Choi In-Kyu, Kim, Jong-An. Development of a digital turbine control system in a nuclearpower plant[J]. International Journal of Control, Automation and Systems,2009,7(1):67-73.
[51].Urbach M,Koch D. Requirements of emergency control managements on data andinformation for assessment of the radiological situation in case of a severe accident in anuclear power plant[J]. Kerntechnik,2007,72(4):230-235.
[52].Carvalho Paulo V.R,dos Santos Isaac L. Micro incident analysis framework to assess safetyand resilience in the operation of safe critical systems: A case study in a nuclear powerplant[J]. Journal of Loss Prevention in the Process Industries,2008,21(3):277-286.
[53].Hwang, Sheue-Ling, Yau, Yi-Jan Lin,Yu-Ting.Predicting work performance in nuclear powerplants[J]. Safety Science,2008,46(7):1115-1124.
[54].Vasilevskii V.P, Mikhailov M.N. Development and adoption of measures for increasing thesafety of power-generating units of nuclear power plants with RBMK reactors in1986-2005[J]. Atomic Energy,2006,100(4):295-301.
[55].Xia Guoqing, Su Jie. Multivariable integrated model predictive control of nuclear powerplant[J]. International Journal of Control and Automation,2008,1(1):1-8.
[56].蔡章生.核动力反应堆中子动力学[M].北京：国防工业出版社,2005.
[57].谢仲生,张少泓.核反应堆物理理论与计算方法[M].西安：西安交通大学出版社，2000.
[58].郑福裕,邵向业,丁云峰.压水堆核电厂运行[M].北京：原子能出版社,1998.
[59].赵浮宇,曹艳.反应堆最优功率控制系统的设计[J].核科学与工程,1999,19(1):39-43.
[60].张英.秦山核电二期工程计算机仿真技术在控制系统中的应用[J].核动力工程,2003,24(2):244-248.数字化反应堆控制系统研究[J].核动力工程,2002,
[61].施希,吴萍,赵洁,刘涤尘.压水堆核电厂负荷跟踪系统设计与特性研究[J].核动力工程,2010,31(6):102-105.
[62].李云臣,张少泓,蒋兴华.平均温度控制系统R棒扰动的改进分析[J].核动力工程,2010,31(4):71-77.
[63].张瑞,彭华清.数字化反应堆控制系统研究[J].核动力工程,2002,23(S1):86-88.
[64].互动百科.复合核与反应堆多普勒效应[EB/OL]. http://www.hudong.com/wiki,2011.
[65].于平安,朱瑞安,喻真烷,沈秀中.核反应堆热工分析[M].上海：上海交通大学出版社，2002.
[66].朱继洲.核反应堆安全分析[M].西安：西安交通大学出版社，2002.
[67].沈维道,童钧耕.工程热力学[M].（第三版）北京：高等教育出版社，2007.
[68].张曙明,李华奇等.秦山核电站二期反应堆堆芯流量分配数值分析[J].核科学与工程,2010,30(4)：299-305.
[69].李红鹰,许川.秦山核电二期工程控制棒驱动机构国产化研制[J].核动力工程，2003，24(S1)：143-145.
[70].左文,阎玉辉.秦山核电二期工程棒控棒位系统设计[J].核动力工程,2003，24(S1)：146-147.
[71].喻丹萍,胡永陶.秦山核电二期工程控制棒导向组件动态特性试验研究[J].核动力工程,2003，24(S1)：158-160.
[72].李国勇智能控制及Matalb实现[M].北京：电子工业出版社，2005.
[73].龙升照,汪培庄.Fuzzy控制规则的自调整问题[J].模糊数学,1982,2(3):105-112.
[74].梁保松,曹殿立.模糊数学及其应用[M].北京：科学出版社，2007.
[75].佟绍成.非线性系统的自适应模糊控制[M].北京：科学出版社，2006,10-218.
[76].Zadeh L A.Fuzzy sets[J].Information and Control,1965,8:338-353.
[77].Zadeh L A.Outline of a new approach to the analysis of complex systems and decisionprocesses[J].IEEE Tran.Systems,Man,and Cybernetics,1973,3(1):28-44.
[78].Mamdani E H.Applications of fuzzy algorithms for simple dynamic plant[J].Proc.IEEControl and Science1974,121(12):1585-1588.
[79].Holmblad L P and Qstergaard J J.Control of a cement kiln by fuzzy logic[M].FuzzyInformation and Decision Processes.New York:North-Holland,1982,389-399.
[80].Yasunobu S and Miyamoto S.Automatic train operation system by predictive fuzzycontrol[M].Industrial Application of Fuzzy Control.North-Holland,1985,1-18.
[81].Lin C,Wang Q G and Lee T H.Stability and stabilization of a class of fuzzy descriptorsystems[J].IEEE Trans.Fuzzy Systems,2006,14(4):542-551.
[82].徐济鋆,贾斗南.沸腾换热与汽液两相流[M].北京：原子能出版社，2002.
[83].钱虹,叶建华,钱非,李超.蒸汽发生器水位全程控制系统数字化及仿真实现[J].核动力工程,2010,31(2):58-62.
[84].Lin Lun.核电厂蒸汽发生器数字化仪表与控制对象实时仿真系统[M].北京：原子能出版社，2003.
[85].杨柳,袁景淇.压水堆蒸汽发生器水位的前馈模型预测控制[J].控制工程，2008，15(3):251-253．
[86].陈智,张英,王华金,张瑞.岭澳核电站二期蒸汽发生器水位控制系统相关传递函数的辨识方法[J].核动力工程,2011,32(5):29-32.
[87].陈智,张英,张帆,余红星.岭澳核电站蒸汽发生器水位控制系统改进方案仿真研究[J].核动力工程,2010,31(4):66-70.
[88].王川,于雷.自然循环蒸汽发生器倒U型管内单相流体倒流特性研究[J].核动力工程,2011,32(1):58-62.
[89].李凤宇,陆古兵,张龙飞,刘东.蒸汽发生器水位双PI控制的改进研究[J].原子能科学技术,2010,44(S1):279-282.
[90].林卫星,陈炎海.一种快速收敛的改进粒子群优化算法[J].系统仿真学报,2011,23(11):2406-2411. Coordination control and simulation for small nuclear powerplant
[91].程启明,程尹曼,汪明媚,薛阳,胡晓青.基于混沌粒子群算法优化的自抗扰控制在蒸汽发生器水位控制中的应用研究[J].华东电力,2011,39(6):957-962.
[92].王林,刘君,曾宇容,易觉.基于粒子群优化算法和模糊模拟的核电备件模糊EOQ模型[J].系统工程,2008,26(11):123-126.
[93].徐辉,李石君,.一种整合粒子群优化和K-均值的数据聚类算法[J].山西大学学报(自然科学版),2011,34(4):518-523.
[94].应明峰,鞠全勇,高峰,.基于粒子群优化的PID控制器设计与应用[J].计算机仿真,2011,28(11):283-287.
[95].刘金琨.先进PID控制Matlab仿真[M].北京：电子工业出版社，2009.
[96].Tan Ying, Z.M.Xiao. Clonal particle swarm optimization and its applications[C].IEEECongress on Evolutionary Computation,2007:2303-2309
[97].Junqi Zhang, Z.M.Xiao, Ying Tan, Xingui He.Hybrid Particle Swarm Optimizer withAdvance and Retreat Strategy and Clonal Mechanism for Global Numerical Optimization[C].IEEE World Congress on Computational Intelligence2008:2059-2066.
[98].刘坤,谭营,何新贵.基于粒子群优化的过程神经网络学习算法[J].北京大学学报(自然科学版),2011,47(2):238-244.
[99].徐静波.基于PSO算法的PID控制参数优化[J].东华大学学报(自然科学版),2007,33(1):135-138
[100].冯允成.随机网络及其应用[M].北京:北京航空航天大学出版社，1987.
[101].郑轶松,齐二石,郑晓东.基于图示评审技术GERT的高科技产品开发研究[J].系统工程,2005，23(11):112-115.
[102]. Gaurishankar,Vandana Sahan.GERT Analysis of a Two-Unit Cold Standby System byRepair[J],Microelectron.Reliab,1995,35(5):837-840.
[103]. Yang Bao-Hua，Fang Zhi-Geng.Model of GERT network based on grey information andits applications[C].IEEE International Conference on Grey Systems and IntelligentServices,2011:640-644.
[104]. Gavareshki M.H.Karimi. Newfuzzy GERT method for research projectsscheduling[C].IEEE International Engineering Management Conference on Innovation andEntrepreneurship for Sustainable Development,2004,2:820-824.
[105]. Matsumoto Tsuyoshi. Evaluation for development of superconducting technologies inpower sectors using GERT[C]. Proceedings of the IASTED Multi-Conference-Power andEnergy Systems,2003,7:109-114.
[106].方志耕.随机网络（GERT）模型[EB/OL]. http://video.chaoxing.com,2010.
[107].熊杨恒.日本福岛核泄漏事故与核能发电前景展望[EB/OL].http://video.chaoxing.com,2011.
[108].陈绍廉.核能的安全和合理利用[EB/OL]. http://video.chaoxing.com,2011.
[109]. World Nuclear Association. Fukushima Accident2011[EB/OL].http://www.world-nuclear.org,2012.
[110].李文辉,苏永杰.核电厂应急监测探讨[J].辐射防护,2011,31(4):252-256.
[111].杨保华,方志耕,刘思峰,郭本海.基于GERT网络的应急抢险过程资源优化配置模型研究[J].管理学报,2011,8(12):1883.
[112].龚迪琛,方方,黄洪全.一种混合结构的无功补偿控制系统的设计[J].电力系统保护与控制,2009,37(13):80-82.
[113].赵朋飞,李乃乾.基于XML的分布式数据库集成系统[J].计算机工程,2010,36(13):70-72.
[114].郑荣,马世龙.网格环境下基于XML的异构数据集成系统[J].计算机工程,2008,34(22):52-54.
[115].张水平,孙云星,张凤琴等.SOA架构的分布式网络监管系统的设计与实现[M].计算机工程与设计，2011,32(7):2352-2355.
[116].刘黎志,吴云韬.应用WCF分布式框架实现移动数据同步[J].计算机应用，2011，31(12):3281-3284.
[117].吴莉.基于.NET框架的N层分布式应用程序研究[J]贵州工业大学学报(自然科学版)，2008，37(4):207－210．
[118].殷跃鹏,郭长国,李小玲,王怀民.基于事件的分布式系统行为分析框架[J].微电子学与计算机，2010，27(8):70-76.
[119].霍林,黄俊文,潘英花,王力.大规模分布式资源搜索技术研究进展[J].计算机应用研究，2010，27(11):4006-4009.
[120]. FUNG K T,CHAN Y L,SIU W C.Low-Complexity and High-Quality Frame-SkippingTranscoder for Continuous Presence Multipoint Video Conferencing[J].IEEE Transactions onMultimedia,2004,6(1):31-46.
[121]. LYNDEN S，MUKHERJEE A，HUME A，et al．The design and imple-mentation ofOGSA-DQP:a service-based distributed query processor[J].Future Generation ComputerSystems，2009，25(3):224-236．
[122]. CZAJKOWSKIY K，FITZGERALDZ S，FOSTER I．Grid information services fordistributed resource sharing［C］Proc of the10th IEEE International Symposium on HighPerformance Distributed Computing．2001:181-195．
[123]. SHEN Heng-tao，SHU Yan-feng，YU Bei．Efficient semantic-based content search inP2P network[J].IEEE Trans on Knowledge and Data Engineering,2004,17(7):813-826．
[124]. LACKS D,KOCAK T.Developing reusable simulation core code for networking:the gridresource discovery example［J］．Journal of Sys-tems and Software，2009，82(1):89-100．
[125].肖侬,任浩,徐志伟等.基于资源目录技术的网格系统软件设计与实现[J].计算机研究与发展，2002，39(8):902-906．