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Modelling Water Distribution Systems with Deficient Pressure: An Improved Iterative Methodology

Author

Listed:
  • Ping He

    (Tongji University)

  • Tao Tao

    (Tongji University)

  • Kunlun Xin

    (Tongji University)

  • Shuping Li

    (Tongji University)

  • Hexiang Yan

    (Tongji University)

Abstract

In the last three decades, many researchers have proposed different models for water distribution network (WDN) hydraulic analysis by head-driven analysis (HDA). By considering a pressure-discharge relationship (PDR), head-driven analysis (HDA) can avoid deviation caused by traditional demand-driven analysis (DDA) under abnormal conditions. Generally, there are three types of HDA models: 1) models achieved by embedding a PDR into DDA, 2) models using EPANET structures such as emitter or tank to take place of PDR, 3) models aiming at modifying nodal outflows to satisfy PDR based on EPANET. Among these models, modifying nodal outflows is flexible to simulate network with different PDRs and specify parameters related to PDR. Most of the models use iterative algorithms to solve HDA problems; however, present ways to ensure convergence of models are still inadequate. The purpose of this paper is to present a new way to meet the iterative convergence when modifying nodal outflows based on PDR and leakage. This new methodology has been incorporated into the hydraulic network solver EPANET and is formalized algorithmically as EPANET-IMNO. Then two typical networks are used to test EPANET-IMNO, and the results demonstrate that EPANET-IMNO can converge well and applied successfully both in static simulation and extended period simulation. Different pressure deficiency conditions are tested to further confirm the flexibility and the convergence of EPANET-IMNO. Furthermore, quality analysis results back that pressure reduction can be a practical way in contamination accident response.

Suggested Citation

  • Ping He & Tao Tao & Kunlun Xin & Shuping Li & Hexiang Yan, 2016. "Modelling Water Distribution Systems with Deficient Pressure: An Improved Iterative Methodology," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 30(2), pages 593-606, January.
  • Handle: RePEc:spr:waterr:v:30:y:2016:i:2:d:10.1007_s11269-015-1179-4
    DOI: 10.1007/s11269-015-1179-4
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    References listed on IDEAS

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    1. Calvin Siew & Tiku Tanyimboh, 2012. "Pressure-Dependent EPANET Extension," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 26(6), pages 1477-1498, April.
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    Cited by:

    1. Tiku T. Tanyimboh & Anna M. Czajkowska, 2021. "Entropy maximizing evolutionary design optimization of water distribution networks under multiple operating conditions," Environment Systems and Decisions, Springer, vol. 41(2), pages 267-285, June.
    2. Hui Zhang & Xin Cheng & Tinglin Huang & Haibing Cong & Jinlan Xu, 2017. "Hydraulic Analysis of Water Distribution Systems Based on Fixed Point Iteration Method," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 31(5), pages 1605-1618, March.
    3. Xiang He & Yongbo Yuan, 2019. "A Framework of Identifying Critical Water Distribution Pipelines from Recovery Resilience," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 33(11), pages 3691-3706, September.
    4. Mingyuan Zhang & Juan Zhang & Gang Li & Yuan Zhao, 2020. "A Framework for Identifying the Critical Region in Water Distribution Network for Reinforcement Strategy from Preparation Resilience," Sustainability, MDPI, vol. 12(21), pages 1-17, November.
    5. Farid Saberi-Movahed & Mohammad Najafzadeh & Adel Mehrpooya, 2020. "Receiving More Accurate Predictions for Longitudinal Dispersion Coefficients in Water Pipelines: Training Group Method of Data Handling Using Extreme Learning Machine Conceptions," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 34(2), pages 529-561, January.
    6. José Antonio Palomero-González & Vicent Almenar-Llongo & Ramón Fuentes-Pascual, 2021. "Evaluating the Efficiency of Water Distribution Network Sectors Using the DEA-Weight Russell Directional Distance Model: The Case of the City of Valencia (Spain)," Sustainability, MDPI, vol. 13(19), pages 1-21, September.

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