城市供水管网节点混合模型研究
详细信息    本馆镜像全文|  推荐本文 |  |   获取CNKI官网全文
摘要
节点混合模型对给水管网水质模拟结果有着重要的影响,针对现在普遍采用的节点完全混合假定的缺陷,本文选取管网中典型的多进多出节点类型进行系统的研究:
     1.基于管网节点水力、水质的基础方程,定义了节点混合程度描述指标,和D*,改进了现有衡量节点混合程度指标的不足。典型工况的验证结果表明,新定义的指标相对较合理,能够较好地反映各工况下节点混合程度的大小。
     2.采用正交试验方法和FLUENT模拟软件分析各因素对节点混合程度的影响,取得较好的效果:正交试验设计从大量的试验点中挑选适量的具有代表性的试验点,大大提高了试验的效率;FLUENT模拟软件具有良好的收敛速度和求解精度,适合对节点混合的定性模拟。研究得到结果:入流雷诺数比(Res/Rew)、出口雷诺数比(ReE/ReN)和管径比(Ds/Dw)3个因素对节点混合影响的显著性较高。
     3.通过采用高位水箱和水位控制阀改进节点入口加压方式,进行了节点混合实验研究。实验入口压力测试数据表明:各工况的压力波动较小,且波动大小比较稳定;实验数据的质量百分数误差分析结果表明:本实验对各过程参数控制较好,实验数据误差较小;实验数据对比分析表明:本实验模拟结果与其他学者得到的模拟结果十分吻合,规律性一致。
     4.基于改进PSO算法进行节点混合模型建立研究。通过在粒子飞行过程中加入搜索因子的方法对基本PSO算法进行改进,测试函数性能检测结果表明,改进PSO算法具有较高的搜索精度和全局搜索能力;基于最小二乘法原理,以实验数据和模型模拟数据之间的误差的平方和最小为目标函数,并采用以上改进PSO算法对节点混合模型进行回归拟合,取得了较好效果;通过对水质模拟过程中流体单元体混合反应和节点新单元体生成的两项变化改进,将节点混合模型应用于EPANET软件中,提高本方法的实用性。
     5.以监测到供水系统中突发性污染为目标,本文提出了一种城市供水系统监测点优化布置的方法。在定义最短水流时间矩阵和污染覆盖矩阵的基础上,本法针对复杂管网求解最短水流时间矩阵困难的问题,利用动态规划求解最短水流时间矩阵,并由此得到给定监测等级下的污染覆盖矩阵。以监测覆盖范围最大为目标函数,并引入重复覆盖度的概念,运用遗传算法优化布置监测点。结果表明:用动态规划求解复杂管网的最短水流时间矩阵易于编程实现,并有较高的时间效率;遗传算法能够快速地搜索到最优监测点的布置方案,达到在给定监测等级下最大限度地监测整个管网突发性污染的目的。
     6.在仿真管网水力模型的基础上,应用EPANET改进程序对其进行水质模拟,通过与EPANET软件模拟结果对比分析表明:节点混合模型对管段水质分布和监测点水质变化有一定的影响。
Soluet mixing model of joints in water distribution networks has important impact on the result of water quality simulation. For the defect of the "perfect" mixing assumption which is widely used, this paper presented a systematically study on a typical node type:
     1. This paper defined the mixing index d*and D*for the joints based on the basic hydraulic and quality equation, which improves the index used now. Results by typical scenario had shown that:the new index is more reasonable and can reflect better on the degree of mixing by each condition.
     2. Used orthogonal experiment method and FLUENT simulation software to analyze the impact of the factors on the joint mixing and achieved good results:the design of orthogonal experiment greatly improved the efficiency of the test by selecting some representative ones from a large amount of tests; FLUENT simulation software has good convergence speed and solution accuracy, and is suitable for the qualitative simulation for the joints mixing. The results show that the ratio of Reynolds numbers of inlets and outlets (Res/W and RcE/N) and the ratio of pipe diameter of inlets (DS/W) have more impacts on the mixing at the joints.
     3. This paper accomplished the experimental study of solute mixing at cross joints by using high water head tank and valve based on improving the mode of pressure boost. Entrance pressure data shows that the pressure of the system was stable during each experiment scenario; The percentage mass fraction error of the experimental data shows that each parameter of the experiment was controlled well and the error of the experimental data was insignificant; Comparative analysis of experimental data indicates that:the curves obtained by this experiment and other scholars match well.
     4. A mixing model of joints based on improved PSO algorithm has been proposed. A search factor is added into the movement of the particle to develop basic PSO algorithm and results manifest that the developed algorithm has stronger global optimizing ability and better search accuracy; The objective function has been built based on the method of the least square, which is used to minimum the sum of the errors between experimental data and simulated data. Then, the mixing models have been fitted by improved PSO algorithm; the water quality simulation of EPANET software is utilized for improving the practicality by using the mixing models in the process of the mixing reaction of the fluid element and the generation of new element.
     5. In order to detect a random external input of water pollution, this paper built a model that can optimize the layout of the monitoring stations for the city water supply system. The model is based on defining of the concept of shortest flow-time matrix and pollution coverage matrix. To resolve the computational complexity in shortest flow-time matrix for complicated water distribution systems, the method of using dynamic programming to obtain the pollution coverage matrix under a given monitor level. Genetic algorithm is adopted to optimally allocate the monitoring stations. The method maximizes the monitoring coverage considering the duplication of coverage. The results show that the shortest flow-time matrix of complicated networks can be efficiently obtained by using dynamic programming, which can be coded easily; genetic algorithm can find the optimal layout of monitoring stations rapidly, which can monitor the accidental contaminations of the whole network by the greatest degree in a given monitor level.
     6. The developed EPANET program has been used in a realistic network, the result contrasted to basic EPANET software indicates that:the mixing models have a certain impact on the concentration distribution in the pipes and the concentration change trend at monitoring stations.
引文
[1]高从堦,陈国华.海水淡化技术与工程手册[M].北京:化学工业出版社.2004.
    [2]杨鲁豫,王琳,王宝贞.我国水资源污染治理的技术策略[J].给水排水,2001,27(1):94-101.
    [3]任金法.我国城乡饮水现状及重大饮用水污染状况分析[J1.环境与公共卫生,2009,23(6):80-81.
    [4]鄂学礼,凌波.饮水污染对健康的影响[J].中国卫生工程学,2006,5(1):3-5.
    [5]鄂学礼.突发饮用水污染事件应答[C].环境与健康——第四届长三角科技论坛.2007.
    [6]郭常义.我国城市饮水现状及对策[C].环境与健康——第三届长三角科技论坛.2007.
    [7]仇保兴.中国城镇水务“十二五”发展战略与主要任务(摘要)[J].给水排水,2011,37(1):1-3.
    [8]张俊艳,韩文秀.城市水安全问题及其对策探讨[J].北京科技大学学报,2005,21(2):78-81.
    [9]杜宝俭,朱鸿斌.中国生活饮用水卫生现状分析[J].职业卫生与病伤,2007,22(2):125-127.
    [10]李振东.认真贯彻建设部城市供水系统重大事故应急预案切实加强城市供水安全保障工作[N].李振东在中国水协2006年秘书长工作会议上的讲话,2006
    [11]水专项简介:http://nwpcp.mep.gov.cn/zxgk/200910/t20091030_180580.htm.
    [12]严煦世,范瑾初.给水工程[M].北京:中国建筑工业出版社.2003.
    [13]袁一星,赵宏宾,赵明.给水管网生长环研究[J].哈尔滨建筑大学学报,1998,31(1):72-76.
    [14]吴文燕,赵宏宾,解守志.监测配水管网水质[J].中国给水排水,1996,22(6):25-27.
    [15]Rossman L.;Boulos, P.;Altman,T. The Discrete Volume-Element Method for Network Water Quality Models [J]. Journal of Water Resources Planning and Management 1993,119(5):505-517.
    [16]Rossman L.;Boulos, P. Numerical Methods for Modeling Water Quality in Distribution Systems:A Comparison [J]. Journal of Water Resources Planning and Management 1996,122(2):137-146.
    [17]Uber J.;Shang. F.;Rossman,L., Extensions to EPANET for Fate and Transport of Multiple Interacting Chemical or Biological Components, in World Water and Environmental Resources Congress 2004:Salt Lake City,Utah,USA.
    [18]Elton A.;Brammer, L.F.;Tansley,N.S. Water Quality Modeling in Distribution Networks [J]. Journal of the American Water Works Association,1995,87(7):44-52.
    [19]Munavalli G.R.;Kumar, M. Water Quality Parameter Estimation in Steady-State Distribution System [J]. Journal of Water Resources Planning and Management 2003, 129(2):124-134.
    [20]王鸿翔.供水管网水质模型校正及水质监控研究[D].杭州: 市政工程,浙江大学,2009.
    [21]郭诗文.管网中基于余氯衰减的三卤甲烷动力学模型研究[D].杭州: 市政工程,浙江大学,2011.
    [22]赵洪宾.给水管网理论与分析[M].北京:中国建筑工业出版社.2003.
    [23]Flower A.G.;Jones, P., Simulation of Water Quality in Water Distribution Systems, in Water Quality Modeling in Distribution Systems.1991:AWWA/EPA,Cincinnati.
    [24]Ho C.K. Solute Mixing Models for Water-Distribution Pipe Networks [J]. Journal of Hydraulic Engineering,ASCE,2008.134(9):1236-1244.
    [25]Romero-Gomez P.;Choi, C.Y.;Van Bloemen Waanders,B.;Mckenna,S.A., Transport Phenomena at Intersections of Pressurized Pipe Systems, in 8th Annual Water Distribution Systems Analysis Symposium.2006:Cincinnati,Ohio,USA.
    [26]Ashgriz N.;Brocklehurst, W.;Tally,D. Mixing Mechanisms in a Pair of Impinging Jets [J]. Journal of Propulsion and Power,2001,17(3):736-742.
    [27]Van Bloemen Waanders B.;Hammond, G.;Shadid.J.;Collis,S., A Comparison of Navier Stokes and Network Models To Predict Chemical Transport In Municipal Water Distribution Systems, in World Water and Environmental Resources Congress 2005:Anchorage,Alaska,USA.
    [28]Ho C.K.;Orear, L.;Jr.;Wright,J.L.;Mckenna,S.A., Contaminant Mixing at Pipe Joints.Comparison Between Laboratory Flow Experiments and Computational Fluid Dynamics Models, in 8th Annual Water Distribution Systems Analysis Symposium. 2006:Cincinnati,Ohio,USA.
    [29]Webb S.W.;Van Bloemen Waanders, B., High Fidelity Computational Fluid Dynamics for Mixing in Water Distribution Systems, in 8th Annual Water Distribution Systems Analysis Symposium.2006:ASCE/EWRI,Cincinnati,Ohio,USA.
    [30]Webb S.W., High-Fidelity Simulation of the Influence of Local Geometry on Mixing in Crosses in Water Distribution Systems, in 9th Annual Water Distribution Systems Analysis Symposium.2007:ASCE/EWRI,Tampa,Florida,USA.
    [31]Romero-Gomez P.;Ho, C.K.;Choi,C.Y. Mixing at Cross Junctions in Water Distribution Systems-Part Ⅰ.An Numerical Study [J]. Journal of Water Resources Planning and Management,2008,134(3):285-294.
    [32]Rossman L. EPANET-Use's manual [M]. ed. U.S.E.P. Agency(USEPA). Cincinnati.Ohio.2000.
    [33]Mckenna S.A.;Orear, L.; Wright,J., Experimental Determination of Solute Mixing in Pipe Joints, in World Environmental and Water Resources Congress.2007:Tampa, Florida,USA.
    [34]Austin R.;Van Bloemen Waanders. B.;Mckenna,S.;Choi,C.Y. Mixing at Cross Junctions in Water Distribution Systems-Part Ⅱ.An Experimental Study [J]. Journal of Water Resources Planning and Management,2008.134(3):295-302.
    [35]Song I.;Romero-Gomez. P.;Choi.C.Y. Experimental Verification of Incomplete Solute Mixing in a Pressurized Pipe Network with Multiple Cross Junctions [J]. Journal of Hydraulic Engineering.ASCE,2009,135(11):1005-1011.
    [36]Laird C.D.;Biegler, L.T.;Van Bloemen Waanders,B.;Bartlett,R.A. Time Dependent Contamination Source Determination for Water Networks [J]. Journal of Water Resources Planning and Management 2005,131(2):125-134.
    [37]Laird C.D.;Biegler, L.T.;Van Bloemen Waanders,B. Mixed-Integer approach for Obtaining Unique Solutions in Source Inversion of Water Networks [J]. Journal of Water Resources Planning and Management,2006,132(4):242-251.
    [38]Lansey K.E.;Delgado, D.;Banihani,Q. Discussion of Mixed-Integer Approach for Obtaining Unique Solutions in Source Inversion of Water Networks by C.D.Laird,L.T.Biegler.B.van Bloemen Waanders. [J]. Journal of Water Resources Planning and Management,2007,133(6):573-575.
    [39]Breidenthal R. Structure in turbulent mxing layers and wakes using a chemical reaction [J]. Journal of Fluid Mechanics,1981,109:1-24.
    [40]Plesniak M.W.;Cusano, D.M. Scalar Mixing in a Confined Rectangular Jet in Crossflow [J]. Journal of Fluid Mechanics 2005,524:1-45.
    [41]Wang S.J.;Mujumdar. A.S. A Numerical Study of Flow and Mixing Characteristics of Three-Dimensional Confined Turbulent Opposing Jets:Unequal Jets [J]. Chemical Engineering and Processing,2005,44:1068-1074.
    [42]蒋白懿,李亚峰等.给水排水管道设计计算与安装[M].北京:化学工业出版社.2005.
    [43]Wood D.J.. Slurry flow in pipe networks [J]. Hydraulic Engineering, ASCE,1980, 106(1):57-70.
    [44]Shah M.; Sinai, G. Steady state model for dilution in water networksteady state model for dilution in water networks [J]. Hydraulic Engineering, ASCE,1988, 114(2):192-206.
    [45]Boulos P. F.; Altman, T.;Sadhal,K.S.. Computer modeling of water quality in large multiple-source networks [J]. Applied Mathematical Modelling,1992,16(8):439-445.
    [46]徐洪福.配水管网系统水质变化规律与水质模型研究[D].哈尔滨: 哈尔滨工业大学.2003.
    [47]徐洪福,赵洪宾,尤作亮.配水系统的水质模型研究概况[J].中国给水排水,2002,18(3):33-36.
    [48]吴卿.饮用水管网微生物学水质研究及模拟[D].天津: 环境学科与工程,天津大学,2005.
    [49]Boulos P.F.;Altman, T.; Jarrige,P.A.;Collevati,F.. Discrete simulation approach for network-water-quality models [J]. Journal of Water Resources Planning and Management,1995.121(1):49-60.
    [50]Islam M.R.;Chaudhry. M.H.. Modeling of constituent transport in unsteady flows in pipe networks [J]. Hydraulic Engineering, ASCE,1998,124(11):1115-1124.
    [51]王志丹.输配水系统水质统计模型的研究[D].天津: 天津大学,2005.
    [52]李欣马建薇,袁一星.城市给水管网水质研究与进展[J].哈尔滨工业大学学报,2004,36(10):1392-1395.
    [53]赵新华,王晓丹,吴卿.给水管网中细菌总数快速预测模型的建立与应用[J].中国给水排水,2008,24(13):78-81.
    [54]刘磊磊,高德凯,廖静.基于时间序列法的管网水质趋势分析模型[J].安徽农业科学,2007,35(4):1079-1080.
    [55]肖金树.指数平滑法在水质预测中的应用[J]福建环境.1996.13(4):34-35.
    [56]章春星.厦门杏林区供水余氯优化控制的研究[D].上海: 环境科学和工程学院.同济大学,2003.
    [57]吴卿,赵新华.BP神经网络用于饮用水管网细菌总数预测[J].天津大学学报,2007,40(1):1382-1386.
    [58]李霞,李国金,赵新华,王亮.供水管网的多水质组分预测建模研究[J]中国给水排水,2008,24(11):57-59.
    [59]沈承,俞亭超,张土乔.基于系统分析理论给水管网水质模型的建立[J].给水排水,2011,37(7):158-160.
    [60]廖永平,严擎宇.正交试验法在机械工业中的应用[M].北京:中国农业机械出版社.1984.
    [61]《正交试验法》编写组.正交试验法[M].北京:国防工业出版社.1976.
    [62]徐仲安,王天保,李常英,暴丽艳,马青梅,苗玉宁.正交试验设计法简介 [J].科技情报开发与经济,2002,12(5):148-150.
    [63]王岩,隋思涟,ed.数理统计与MATLAB工程数据分析.2006,清华大学出版社:北京.
    [64]朱立奎,雷永平,史耀武FLUENT在焊接模拟中的应用[J].电焊机,2007,37(8):13-19.
    [65]李磊,胡非,程雪玲,韩浩玉Fluent在城市街区大气环境中的一个应用[J].中国科学院研究生院学报,2004,24(4):476-480.
    [66]韩占忠,王敬,兰小平.FLUENT流体工程仿真计算实例与应用[M].北京:北京理工大学出版社.2004.
    [67]赵妍.应用FLUENT对管路细部流场的数值模拟[D].大连: 水利工程学院,大连理工大学,2004.
    [68]王瑞金,张凯,王刚.Fluent技术基础与应用实例[M].北京:清华大学出版社.2007.
    [69]喻志洁.涡激力作用下过河管道的动力响应分析[D].杭州: 市政工程,浙江大学,2010.
    [70]王宜怀,王林.基于人工神经网络的非线性回归[J].计算机工程与应用,2004,12:79-82.
    [71]霍倩,李书全,王文元,赵胜利,赵春生.遗传算法应用于多元非线性回归模型求参的研究[J].河北农业大学学报,2002,25(2):107-110.
    [72]裴鑫德.多元统计分析及其应用[M].北京:北京农业出版社.1991.
    [73]李晓磊,邵之江,钱积新.一种基于动物自治体的寻优模式:鱼群算法[J].系统工程理论与实践,2002,22(11):32-38.
    [74]Colorni A. Distributed optimization by ant colonies [C].Proceedings of European Conference on Artifical Life.1991.134-142.
    [75]Holland J.H. Genetic Algorithms and Optimal Allocation of Trials [J]. SIAM J Canput,1973,2(2):890-1004.
    [76]Hopfield J.J.;Tank, D.W. Neural computation of decision in optimization problems [J]. Bio Cybern,1985(52):92-97.
    [77]Vapnik V.N. The Nature of Statistical Learning Theory [M]. New York: Springer-Verlag.1995.
    [78]Vapnik V.N. Statistical Learning Theory [M]. New York:Wiley.1998:493-520.
    [79]沈承,俞亭超,张土乔,改进PSO算法对靠性约束下的水管网优化设计.in Proceedings of the 8th World Congress on Intelligent Control and Automation. 2010:Jinan,China. p.3331-3335.
    [80]Shi Y.; Eberhart, R.C., A modified particle swarm optimizer, in IEEE World Congress on Computational Intelligence.1998. p.69-73.
    [81]朱丽莉,杨志鹏,袁华.粒子群优化算法分析及研究进展[J].计算机工程与应用,2007,43(5):24-27.
    [82]沈燕,郭兵吉天祥.粒子群优化算法及其与遗传算法的比较[J].电子科技大学学报,2005,34(5):696-699.
    [83]纪震,廖惠连,吴青华.粒子群算法及应用(第一版)[M].北京:科学出版社.2009.
    [84]刘伟,周育人.一种改进惯性权重的算法[J].计算机工程与应用,2009,22(45):46-48.
    [85]张寅.基于速度变异的粒子群算法[J].苏州科技学院学报(自然科学版),2011,28(3):62-65.
    [86]刘瑞芳,王希云.一种混沌惯性权重的简化粒子群算法[J].计算机工程与应用,2011,47(21):58-60.
    [87]刘思远.基于水质保障的城乡一体化供水系统改建优化研究[D].杭州: 市政工程,浙江大学,2011.
    [88]暴励,曾建潮.自适应搜索空间的混沌蜂群算法[J].计算机应用研究.2010.27(4):1330-1334.
    [89]袁亚湘,孙文瑜.最优化理论与方法[M].北京:科学出版社.1997.
    [90]程毛林,张伦俊.多元非线性经济预测模型的建立方法[J].理论新探,2005.5:20-21.
    [91]Liou C.P.;Kroon, J.R. Modeling the propagation of waterborne substances in distrubution networks [J]. J.AWWA,1987,77(11):54-58.
    [92]沈承,俞亭超,张土乔.城市供水系统突发性污染监测[J].浙江大学学报工学版,2010,44(8):1604-1607.
    [93]Lee B.H.;Deininger, R.A.;Clark,R.M. Locating Monitoring Stations in Water Distribution Systems [J]. Journal of the American Water Works Association,1991. 83(7):60-66.
    [94]Lee B.H.;Deininger, R.A. Optimal Locations of Monitoring Stations in Water Distribution System [J]. Journal of Environmental Engineering,1992,118(1):4-16.
    [95]Kumar A.;Kansal, M.L.;Arora,G. IDENTIFICATION OF MONITORING STATIONS IN WATER DISTRIBUTION SYSTEM [J]. JOURNAL OF ENVIRONMENTAL ENGINEERING, 1997:746-752.
    [96]张怀宇,赵洪宾,吴文燕.市政给水管网水质监测点的优化选址[J].给水排水,1996,22(10):5-8.
    [97]张土乔,黄亚东,吴小刚.供水管网水质监测点优化选址研究[J].浙江大学学报(工学版),2007,41(1):1-5.
    [98]Al-Zahrani M.A.;Moied, K., Locating Optimum Water Quality Monitoring Stations in Water Distribution System, in World Water and Environmental Resources Congress. 2001:Reston.
    [99]Harmant P.;Nace, A;Kiene,L.;Fotoohi,F., Optimal Supervision of Drinking Water Distribution Network, in 26th Annual Water Resources Planning and Management Conference.1999:Tempe.
    [100]Choi C.Y.;Woo, H.M.;Yoon,J.H.;Young,D., Optimal Monitoring Sites Based on Water Quality and Quantity in Water Distribution Systems, in World Water Congress 2001.2001.
    [101]许仕荣,周书葵.基于节点水龄的供水管网水质监测点的优化布置[J]南华大学学报(理工版),2003.17(3):13-16.
    [102]伍悦滨,赵洪宾.用节点水龄量度给水管网的水质状况[J].给水排水,2005,28(5):36-37.
    [103]韩云峰.城市供水管网水质在线监测系统的研究[D].哈尔滨: 哈尔滨工业大学环境工程学院,2004.
    [104]Kessler A.;Ostfeld, A.;Sinai,G. Detecting accidental contaminations in municipal water networks [J]. Detecting accidental contaminations in municipal water networks, 1998,124(4):192-198.
    [105]Kumar A.;Kansal, M.L.;Arora,G. Detecting Accidental Contaminations in Municipal Water Networks:Discussion [J]. Journal of Water Resources Planning and Management,1999,125(5):308-310.
    [106]方海恩,吕谋,毕继胜.预警监测站优化布置方法的探讨[J].青岛理工大学 学报,2006,27(3):71-73.
    [107]Carr R.D.;Greenberg, H.J.;Hart,W.E., Addressing modeling uncertainties in sensor placement for community water systems, in Proceedings of the World Water and Environmental Resources Conference, ASCE.2004:Salt Lake City.
    [108]Watson J.P.;Greenberg. H.J.;Hart,W.H., A multiple-objective analysis of sensor Placement optimization in water networks, in Proceedings of the World Water and Environmental Resources Conference, ASCE.2004:Salt Lake City.
    [109]Berry J.W.;Fleischer, L.;William,E.;Hart,C.P.;Watson,J.P. Sensor Placement in Municipal Water Networks [J]. Journal of Water Resources Planning and Management,2005,131(3):237-243.
    [110]Uber J.;Janke, R.;Murray,R.;Meyer,P., Greedy heuristic methods for locating water quality sensors in distribution systems, in Proceedings of the World Water and Environmental Resources Conference, ASCE.2004:Salt Lake City.
    [111]Watson J.P.;Hart, W.H.;Berry,J.W., Scalable high-performance heuristics for sensor placement in water distribution networks, in Proceedings of the World Water and Environmental Resources Congress.2005:Anchorage,Alaska,USA.
    [112]Mirchandani P.S.;Francis. R.L. Discrete location theory [M]. John Wily and Sons. 1990.
    [113]Resende M.G.C.; Werneck, R.F. A hybrid heuristic for the p-median problem [J]. Journal of Heuristics,2004,10(1):59-88.
    [114]Propato M. Contamination Warning in Water Networks:General Mixed. Integer Linear Models for Sensor Location Design [J]. Journal of Water Resources Planning and Management,2005,131(2):237-243.
    [115]Berry J.W.;William, E.;Hart,C.P.;Phillips,J.G.;Uber;Watson,J.P. Sensor Placement in Municipal Water Networks with Temporal Integer Programming Models [J]. Journal of Water Resources Planning and Management,2006,132(4):218-224.
    [116]Shastri Y.;Diwekar, U. Sensor placement in water networks:a stochastic programming approach [J]. Journal of Water Resources Planning and Management, 2006,132(3):192-203.
    [117]Dantzig G.;Glynn, P. Parallel processors for planning under uncertainty [J]. Annals of Operations Research,1990,22:1-21.
    [118]Dantzig G.;Infanger, G. Computational and applied mathematics 1 [M]. Elsevier Science, B.V., North Holland, Amsterdam, The Netherlands.1992.
    [119]Infanger G. Monte Carlo (importance) sampling within a benders decomposition algorithm for stochastic linear progress [J]. Annals of Operations Research.1992. 39(69-95).
    [120]Sahin K.;Diwekar, U. Better optimization of nonlinear uncertain systems(BONUS): A new algorithm for stochastic programming using reweighting through kernel density estimation [J]. Annals of Operations Research,2004,132:47-68.
    [121]Grayman W.M.;Ostfeld, A.;Salomons,E. Locating Monitors in Water Distribution Systems:Red Team-Blue Team Exercise [J]. Journal of Water Resources Planning and Management,2006,132(4):300-304.
    [122]汪树玉刘国华.系统分析[M].杭州:浙江大学出版社.2002.
    [123]Goldberg D.E.;Koza, J.R. Genetic Algorithms in Pipeline Optimization [J]. Journal of Computing in Civil Engineering,1987,1(12):128-141.

© 2004-2018 中国地质图书馆版权所有 京ICP备05064691号 京公网安备11010802017129号

地址:北京市海淀区学院路29号 邮编:100083

电话:办公室:(+86 10)66554848;文献借阅、咨询服务、科技查新:66554700