交通运输系统工程与信息 ›› 2014, Vol. 14 ›› Issue (5): 181-187.

• 系统工程理论与方法 • 上一篇    下一篇

危险品运输网络节点失效渗流鲁棒性建模仿真

胡鹏,帅斌*,赵佳虹   

  1. 西南交通大学交通运输与物流学院,成都610031
  • 收稿日期:2014-04-30 修回日期:2014-07-23 出版日期:2014-10-25 发布日期:2014-12-17
  • 作者简介:胡鹏(1989-),男,贵州遵义人,博士生.
  • 基金资助:

    国家自然科学基金资助(71173177);四川省科技厅苗子工程资助项目(2014-013)

Model and Simulation for the Node Failure Percolation Robustness of Hazardous Goods Transportation Network

HU Peng,SHUAI Bin,ZHAO Jia-hong   

  1. College of Transportation & Logistics,Southwest Jiaotong University,Chengdu 610031,China
  • Received:2014-04-30 Revised:2014-07-23 Online:2014-10-25 Published:2014-12-17

摘要:

为了科学地进行危险品运输网络设计和节点选取,减缓突发状况造成的危害, 对突发情况下危险品运输网络节点失效渗流鲁棒性进行了仿真研究.结合液体透过缝隙 自然渗流和复杂网络渗流理论,建立仿真模型.根据设定的仿真场景和流程图,使用 MATLAB进行仿真实验,定量分析网络连通率、渗流节点数、渗流失效率和节点承载力; 定性分析不同节点度节点突发状况和不同节点承载系数对危险品运输网络节点失效渗 流鲁棒性的影响.结果显示,增加节点度过大或过小的节点数量会降低危险品运输网络的 鲁棒性,增加节点承载力则可加强鲁棒性和容错性.

关键词: 公路运输, 鲁棒性, 仿真模型, 危险品运输网络, 渗流, 突发状况

Abstract:

In order to scientifically design hazmat transport network, select the nodes, and slow down the damage under emergency, we model and simulation for the node failure percolation robustness of hazardous materials transportation network with emergency cases. Therefore, we combine the natural phenomenon about liquid through slit by percolating and percolation theory on complex network to establish the simulation model. And then, according to scenarios and the simulation flow chart, simulation experiment is done by using MATLAB software. The aim of it is for the quantitative analyzing the rate of network connectivity, the number of nodes which are effected by percolated, the rate of percolation failure and the bearing capacity of nodes, and the qualitative analyzing the effect of the node failure percolation robustness of hazardous goods transportation network of different node degree under emergency situation and node bearing capacity factor. Finally, simulation results show that adding the number of nodes which have too large degree will reduce the robustness of hazardous goods transportation network, and increasing the bearing capacity of nodes can strengthen the robustness and fault tolerance.

Key words: highway transportation, robustness, simulation model, hazardous goods transportation network, percolation, emergency

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