Identifying sets of key nodes for placing sensors in dynamic water distribution networks

被引:49
|
作者
Xu, Jianhua [1 ]
Fischbeck, Paul S. [1 ,2 ]
Small, Mitchell J. [1 ,3 ]
VanBriesen, Jeanne M. [3 ]
Casman, Elizabeth [1 ]
机构
[1] Carnegie Mellon Univ, Dept Engn & Publ Policy, Pittsburgh, PA 15213 USA
[2] Carnegie Mellon Univ, Dept Social & Decis Sci, Pittsburgh, PA 15213 USA
[3] Carnegie Mellon Univ, Dept Civil & Environm Engn, Pittsburgh, PA 15213 USA
关键词
D O I
10.1061/(ASCE)0733-9496(2008)134:4(378)
中图分类号
TU [建筑科学];
学科分类号
0813 ;
摘要
The design of a sensor-placement scheme capable of detecting all possible contamination events for a water distribution system before consumers are put at risk is essentially impossible given current technologies and budgets. It is, however, possible to design sensor-placement schemes that optimize related objectives (e.g., minimize expected volume of contaminated water consumed prior to detection), but this requires the availability of hydraulic and water quality models for the distribution network and significant computational power, which are the main obstacles to the identification of optimal sensor locations. This paper describes a different approach that reduces the problem's complexity by expressing a water distribution system as different graphs based on the information readily available from most, if not all, water utilities. The approach provides critical policy and decision support for utilities when hydraulic and water quality models are not available and/or when simulation-based techniques are computationally infeasible.
引用
收藏
页码:378 / 385
页数:8
相关论文
共 50 条
  • [21] Identifying key nodes and edges of complex networks based on the minimum connected dominating set
    Li J.
    Wu M.
    Wen X.
    Liu F.
    [J]. Xi Tong Gong Cheng Yu Dian Zi Ji Shu/Systems Engineering and Electronics, 2019, 41 (11): : 2541 - 2549
  • [22] Identifying Key Nodes in Complex Networks Based on Local Structural Entropy and Clustering Coefficient
    Li, Peng
    Wang, Shilin
    Chen, Guangwu
    Bao, Chengqi
    Yan, Guanghui
    [J]. MATHEMATICAL PROBLEMS IN ENGINEERING, 2022, 2022
  • [23] A Knowledge-aggregated Approach for Identifying Influential Nodes in Dynamic Social Networks
    Wang, Jing-Dong
    Liu, Tong
    Mu, Qi-Zi
    Meng, Fan-Qi
    Qu, Guang-Qiang
    [J]. Journal of Network Intelligence, 2024, 9 (01): : 192 - 209
  • [24] Identifying and Ranking Influential Nodes in Complex Networks Based on Dynamic Node Strength
    Li, Xu
    Sun, Qiming
    [J]. ALGORITHMS, 2021, 14 (03)
  • [25] Graphanalytical Model of Key Distribution in Networks with Dynamic Architecture
    Konoplev, A. S.
    Kalinin, M. O.
    [J]. NONLINEAR PHENOMENA IN COMPLEX SYSTEMS, 2019, 22 (03): : 277 - 284
  • [26] Dynamic Key Distribution System in Ad Hoc Networks
    Song Yubo
    Hu Aiqun
    [J]. 2008 4TH INTERNATIONAL CONFERENCE ON WIRELESS COMMUNICATIONS, NETWORKING AND MOBILE COMPUTING, VOLS 1-31, 2008, : 4880 - 4883
  • [27] Robust placement of sensors in dynamic water distribution systems
    Xu, Jianhua
    Johnson, Michael P.
    Fischbeck, Paul S.
    Small, Mitchell J.
    VanBriesen, Jeanne M.
    [J]. EUROPEAN JOURNAL OF OPERATIONAL RESEARCH, 2010, 202 (03) : 707 - 716
  • [28] Water Distribution Networks Optimization Considering Uncertainties in the Demand Nodes
    Cassiolato, Gustavo H. B.
    Ruiz-Femenia, Jose Ruben
    Salcedo-Diaz, Raquel
    Ravagnani, Mauro A. S. S.
    [J]. WATER RESOURCES MANAGEMENT, 2024, 38 (04) : 1479 - 1495
  • [29] Water Distribution Networks Optimization Considering Uncertainties in the Demand Nodes
    Gustavo H. B. Cassiolato
    Jose Ruben Ruiz-Femenia
    Raquel Salcedo-Diaz
    Mauro A. S. S. Ravagnani
    [J]. Water Resources Management, 2024, 38 : 1479 - 1495
  • [30] Water Losses Dynamic Modelling in Water Distribution Networks
    Puleo, Valeria
    Milici, Barbara
    [J]. INTERNATIONAL CONFERENCE OF COMPUTATIONAL METHODS IN SCIENCES AND ENGINEERING 2015 (ICCMSE 2015), 2015, 1702