吴珊, 程玉林, 侯本伟, 李化雨, 李俊. 模型参数不确定性对排水管网功能状态评价的影响[J]. 北京工业大学学报, 2021, 47(3): 280-292. DOI: 10.11936/bjutxb2019100004
    引用本文: 吴珊, 程玉林, 侯本伟, 李化雨, 李俊. 模型参数不确定性对排水管网功能状态评价的影响[J]. 北京工业大学学报, 2021, 47(3): 280-292. DOI: 10.11936/bjutxb2019100004
    WU Shan, CHENG Yulin, HOU Benwei, LI Huayu, LI Jun. Influence of Model Parameter Uncertainty on the Evaluation of Function State of Drainage Network[J]. Journal of Beijing University of Technology, 2021, 47(3): 280-292. DOI: 10.11936/bjutxb2019100004
    Citation: WU Shan, CHENG Yulin, HOU Benwei, LI Huayu, LI Jun. Influence of Model Parameter Uncertainty on the Evaluation of Function State of Drainage Network[J]. Journal of Beijing University of Technology, 2021, 47(3): 280-292. DOI: 10.11936/bjutxb2019100004

    模型参数不确定性对排水管网功能状态评价的影响

    Influence of Model Parameter Uncertainty on the Evaluation of Function State of Drainage Network

    • 摘要: 降雨时空分布的随机性,下垫面的复杂性,以及管网在设计、施工、使用过程中的不确定性,导致排水管网水力模型参数取值存在着不确定性.为了评估参数不确定性对节点和管道功能状态评价的影响,建立了考虑降雨输入、产流、汇流、管网水动力计算各过程不确定性参数的分析模型.根据建模流程的参数要求和文献结论,选择了暴雨洪水管理模型(storm water management model,SWMM)建模过程中的14个参数作为不确定性参数;基于模型参数的增量对计算结果的影响分析,进行了参数灵敏度排序,选取了5个主要参数进行不确定性分析;基于SWMM求解器,采用Monte Carlo随机模拟方法计算了节点、管道的失效概率和相应的溢流时间、体积、充满度模拟均值、变异系数;通过对比参数取中值的确定性工况计算出的节点、管道的相应结果,分析了不确性与确定性分析结果的差异性.算例分析结果表明:在降雨输入和模型计算过程中均存在影响较大的不确定性参数,有必要考虑模型计算全过程参数的不确定性;相对于确定性工况,不确定性分析模型对高风险概率的节点和管道具有较好的识别效果;不确定性分析识别出的不可靠节点的溢流时间、体积模拟值相对确定性工况全网平均值的变化率分别达到了29.13%、10.41%,各管道充满度的变化率最高可达22.31%.

       

      Abstract: The uncertainty of hydraulic model parameters of drainage network comes from the randomness in the spatial and temporal distribution of rainfall, the complexity of underlying surface and the uncertainty in the process of design, construction and use of pipeline network. To explore the influence of parameter uncertainty on functional state evaluation of nodes and pipelines, an uncertainty analysis model was established by considering the uncertain parameters in the process of precipitation, runoff, flow, and hydrodynamic calculation of pipeline network. According to the parameters in the modeling process and the reviews from literatures, fourteen parameters in the modeling process of SWMM model were selected as the uncertainty parameters in this study. The parameter sensitivity analysis was performed by analyzing the influence to the simulation results of the hydraulic model by the increment analysis of model parameters. Five sensitive parameters were selected for the uncertainty analysis of the hydraulic model of the drainage system. Based on the SWMM simulation engine, Monte Carlo simulation method was used to calculate the failure probability of nodes and pipelines, as well as the corresponding estimators and variation coefficients of the occur time and volume of node overflow, and the fullness degree of pipes. The difference between the certainty model and the uncertainty model was analyzed by comparing the hydraulic simulation results of nodes and pipes. Case study results show that the process of rainfall input and model calculation is greatly influenced by the uncertainty of parameters. It is necessary to consider the uncertainty of parameters in the whole process of hydraulic models of the drainage system. Compared to the certainty condition, the uncertainty analysis model is capable of identifying the nodes and pipes at high risk of failure. For the nodes and pipes with high failure probability identified in the uncertainty model, the relative difference between the uncertainty results and the average value of the certainty results of the occur time and volume for node overflow comes up to 29.13% and 10.41%, respectively, and the max relative difference for the fullness degree of pipes is 22.31%.

       

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