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A Stochastic Framework for Reliability and Sensitivity Analysis of Large Scale Water Distribution Networks

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  • Jensen, H.A.
  • Jerez, D.J.

Abstract

The hydraulic reliability and sensitivity analysis of large scale water distribution systems in presence of uncertainty is considered in this work. The assessment of the network reliability and sensitivity is performed by an efficient Markov chain Monte Carlo method, namely Subset simulation. Prescribed nodal heads of storage tanks, nodal demands and pipe roughness coefficients are modeled as uncertain parameters and described in a probabilistic manner. Failure is assumed to occur when the minimum nodal head in the network is lower than a minimum allowable value. The efficiency of the proposed method is demonstrated with the analysis of a real water distribution network consisting of a large number of nodes and pipes (of the order of thousands). The corresponding reliability problem represents a high dimensional problem. The approach gives an important insight into the performance, reliability and sensitivity of a class of complex utility networks.

Suggested Citation

  • Jensen, H.A. & Jerez, D.J., 2018. "A Stochastic Framework for Reliability and Sensitivity Analysis of Large Scale Water Distribution Networks," Reliability Engineering and System Safety, Elsevier, vol. 176(C), pages 80-92.
    • Handle: RePEc:eee:reensy:v:176:y:2018:i:c:p:80-92
    DOI: 10.1016/j.ress.2018.04.001
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    References listed on IDEAS

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    1. Torres, Jacob M. & Brumbelow, Kelly & Guikema, Seth D., 2009. "Risk classification and uncertainty propagation for virtual water distribution systems," Reliability Engineering and System Safety, Elsevier, vol. 94(8), pages 1259-1273.
    2. Au, Siu-Kui & Patelli, Edoardo, 2016. "Rare event simulation in finite-infinite dimensional space," Reliability Engineering and System Safety, Elsevier, vol. 148(C), pages 67-77.
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    Cited by:

    1. Chi, Lixun & Su, Huai & Zio, Enrico & Zhang, Jinjun & Li, Xueyi & Zhang, Li & Fan, Lin & Zhou, Jing & Bai, Hua, 2020. "Integrated Deterministic and Probabilistic Safety Analysis of Integrated Energy Systems with bi-directional conversion," Energy, Elsevier, vol. 212(C).
    2. Villez, Kris & Del Giudice, Dario & Neumann, Marc B. & Rieckermann, Jörg, 2020. "Accounting for erroneous model structures in biokinetic process models," Reliability Engineering and System Safety, Elsevier, vol. 203(C).
    3. Chen, Qian & Zuo, Lili & Wu, Changchun & Bu, Yaran & Lu, Yifei & Huang, Yanfei & Chen, Feng, 2020. "Short-term supply reliability assessment of a gas pipeline system under demand variations," Reliability Engineering and System Safety, Elsevier, vol. 202(C).
    4. Zhou, Xingyuan & van Gelder, P.H.A.J.M. & Liang, Yongtu & Zhang, Haoran, 2020. "An integrated methodology for the supply reliability analysis of multi-product pipeline systems under pumps failure," Reliability Engineering and System Safety, Elsevier, vol. 204(C).
    5. Jensen, H.A. & Jerez, D.J., 2019. "A Bayesian model updating approach for detection-related problems in water distribution networks," Reliability Engineering and System Safety, Elsevier, vol. 185(C), pages 100-112.
    6. Rifaai, Talha M. & Abokifa, Ahmed A. & Sela, Lina, 2022. "Integrated approach for pipe failure prediction and condition scoring in water infrastructure systems," Reliability Engineering and System Safety, Elsevier, vol. 220(C).
    7. Bistouni, Fathollah & Jahanshahi, Mohsen, 2019. "Reliability-aware ring protection link selection in Ethernet ring mesh networks," Reliability Engineering and System Safety, Elsevier, vol. 191(C).

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