Clustering for Real-Time Response to Water Distribution System Contamination Event Intrusions

被引:2
|
作者
Lifshitz, Ron [1 ]
Ostfeld, Avi [1 ]
机构
[1] Technion Israel Inst Technol, Fac Civil & Environm Engn, IL-32000 Haifa, Israel
关键词
Water distribution systems; Clustering; Analysis; Aggregation; Graph theory; Topology; SECURITY; DESIGN;
D O I
10.1061/(ASCE)WR.1943-5452.0001031
中图分类号
TU [建筑科学];
学科分类号
0813 ;
摘要
The 2013 Boston Marathon attack demonstrated the complexity of real-time response to such occurrences. The procedures used by the Federal Bureau of Investigation (FBI) at the Boston event to cluster and mitigate the event consequences inspired the development of a method for real-time response to contamination intrusion events in water distribution systems. Similar to the Boston attack, in the event of water contamination events, the shortage of real-time data, coupled with uncertainties in network topology, water consumption, and the event characteristics, set the ground for the need for a real-time response strategy. A methodology that divides the network into separate monitored zones or clusters, often referred to as district metered areas (DMAs), is widely used to cope with water-related problems such as leakage reduction or pressure control. In this study, a water-quality-related criterion called infection delay time (IDT) was introduced to dynamically cluster the network in case of a contamination event. The IDT parameter was combined with the available system resources to meet water quality goals. A coupled DMA-IDT method was developed for real-time response to contamination events. The setup of the DMA-IDT is described and demonstrated on water distribution systems of various complexities.
引用
收藏
页数:9
相关论文
共 50 条
  • [1] Real-time clustering for priority evaluation in a water distribution system
    Predescu, Alexandru
    Negru, Catalin
    Mocanu, Mariana
    Lupu, Ciprian
    [J]. 2018 IEEE INTERNATIONAL CONFERENCE ON AUTOMATION, QUALITY AND TESTING, ROBOTICS (AQTR), 2018,
  • [2] A framework for real-time disinfection plan assembling for a contamination event in water distribution systems
    Qiu, Mengning
    Salomons, Elad
    Ostfeld, Avi
    [J]. WATER RESEARCH, 2020, 174
  • [3] Real-Time Response to Contamination Emergencies of Urban Water Networks
    Bazargan-Lari, Mohammad Reza
    [J]. IRANIAN JOURNAL OF SCIENCE AND TECHNOLOGY-TRANSACTIONS OF CIVIL ENGINEERING, 2018, 42 (01) : 73 - 83
  • [4] Real-Time Response to Contamination Emergencies of Urban Water Networks
    Mohammad Reza Bazargan-Lari
    [J]. Iranian Journal of Science and Technology, Transactions of Civil Engineering, 2018, 42 : 73 - 83
  • [5] Real-time detection of intentional chemical contamination - In the distribution system
    Byer, D
    [J]. JOURNAL AMERICAN WATER WORKS ASSOCIATION, 2005, 97 (07): : 130 - +
  • [6] Real-time contamination zoning in water distribution networks for contamination emergencies: a case study
    Mohammad Reza Bazargan-Lari
    Sharareh Taghipour
    Mehdi Habibi
    [J]. Environmental Monitoring and Assessment, 2021, 193
  • [7] Real-time contamination zoning in water distribution networks for contamination emergencies: a case study
    Bazargan-Lari, Mohammad Reza
    Taghipour, Sharareh
    Habibi, Mehdi
    [J]. ENVIRONMENTAL MONITORING AND ASSESSMENT, 2021, 193 (06)
  • [8] A Multiple-Layer Clustering Method for Real-Time Decision Support in a Water Distribution System
    Predescu, Alexandru
    Negru, Catalin
    Mocanu, Mariana
    Lupu, Ciprian
    Candelieri, Antonio
    [J]. BUSINESS INFORMATION SYSTEMS WORKSHOPS (BIS 2018), 2019, 339 : 485 - 497
  • [9] Real-time statistical clustering for event trace reduction
    Department of Computer Science, Univ. Illinois at Urbana-Champaign, Urbana, IL 61801, United States
    不详
    不详
    不详
    不详
    不详
    不详
    不详
    [J]. Int J Supercomput Appl High Perform Comput, 2 (144-159):
  • [10] Contamination Event Detection in Drinking Water Systems Using a Real-Time Learning Approach
    Eliades, Demetrios G.
    Panayiotou, Christos
    Polycarpou, Marios M.
    [J]. PROCEEDINGS OF THE 2014 INTERNATIONAL JOINT CONFERENCE ON NEURAL NETWORKS (IJCNN), 2014, : 663 - 670