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Uncertainty Analysis of Optimal Instruction for WDN Pipes Repair and Replacement Using Fuzzy α-cut - hydraulic Simulation Approach

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Abstract

The optimization of the initial design or the development of repair and replacement strategies for pipes within the water distribution network (WDN) during its operational phase relies on the utilization of crisp values. Some input variables such as nodes demand, pipe’s roughness coefficient and reservoir water level have the uncertain nature. Alterations in input parameter values during the operational period, attributed to uncertainty, induce shifts in the behavior and performance of the WDN compared to scenarios with crisp input parameters. Recognizing and analyzing these variations are imperative for making informed decisions to address their ramifications and mitigate problems within the water distribution network. This research analyzes the uncertainty surrounding WDN node pressures, post-implementation of optimal instructions for pipe repair and replacement. The input parameters considered for this analysis include the uncertainty associated with the pipe’s roughness coefficient and the nodes demand within the network. To achieve this objective, a combined approach utilizing both a simulation model (EPANET) and the fuzzy α-cut methodology is employed. Triangular fuzzy membership functions (MF) are chosen for both the input and output variables in the analysis. The extreme value combinations of the two uncertain input variables, at each level of uncertainty, are formulated into four distinct scenarios, serving as the input fuzzy set for the simulation model. Among the research scenarios, the second scenario, characterized by the combination of the minimum pipe’s roughness coefficient and the maximum demand, is designated as the critical scenario. The findings indicate that in the critical scenario, under the highest level of uncertainty, the WDN reliability index diminishes significantly, ranging from approximately 30–40%. This decrease is primarily attributed to the inadequate supply of required pressure to most nodes within the network. At lower levels of uncertainty, the reliability index of the network surpasses 75%, indicating a relatively acceptable performance. Specifically, in the first and fourth scenarios, the network reliability index consistently exceeds 72%. Notably, in the third scenario, the network reliability index remains consistently above 90% across all uncertainty levels.

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References

  • Abeb AJ, Guinot V, Solomatine DP (2000) Fuzzy alpha-cut vs. Monte Carlo techniques in assessing uncertainty in model parameters. In: Proceedings of 4th International Conference on Hydroinformatics, Cedar Rapids, Iowa City, USA

  • Baños R, Reca J, Martínez J, Gil C, Márquez AL (2011) Resilience indexes for water distribution network design: a performance analysis under demand uncertainty. Water Resour Manage 25(10):2351–2366

    Article  Google Scholar 

  • Branisavljevic N, Ivetic M (2006) Fuzzy approach in the uncertainty analysis of the water distribution network of Becej. Civ Eng Environ Syst 23(3):221–236

    Article  Google Scholar 

  • Dini M, Tabesh M (2018) A New Reliability Index for evaluating the performance of water distribution network. J Water Wastewater 29(3):1–16. (In Persian)

    Google Scholar 

  • Donger SR, Gupta R (2017) Optimal design of water distribution network under hydraulic uncertainties. ASCE-ASME J Risk Uncertain Eng Syst 3(3):1–11

    Google Scholar 

  • Farmani R, Savic DA, Walters GA (2005b) Fuzzy rules for hydraulic reliability-based design and operation of water distribution systems. In: Proc, Impacts of Global Climate Change, World Water and Environmental Resources Congress, Anchorage, Alaska, United States, pp 1–9

  • Farmani R, Savic DA, Walters GA (2005a) Evolutionary multi-objective optimization in water distribution network design. Engi Opti 37(2):167–183

    Article  Google Scholar 

  • Geranmehr M, Asghari K, Chamani MR (2019) Uncertainty analysis of water distribution networks using type-2 fuzzy sets and parallel genetic algorithm. Urban Water J 16(3):193–204

    Article  CAS  Google Scholar 

  • Gupta R, Bhave PR (2007) Fuzzy parameters in pipe network analysis. Civ Eng Environ Syst 24(1):33–54

    Article  Google Scholar 

  • Haghighi A, Asl AZ (2014) Uncertainty analysis of water supply networks using the fuzzy set theory and NSGA-II. Eng Appl Artif Intell 32:270–282

    Article  Google Scholar 

  • Hwang H, Lansey K, Jung D (2018) Accuracy of first-order second-moment approximation for uncertainty analysis of water distribution systems. J Water Resour Plan Manag 144(2):p04017087

    Article  Google Scholar 

  • Ivetić M (1996) Control Valves — Principles of Operation. In: Maksimović Č, Calomino F, Snoxell J (eds) Water Supply Systems. NATO ASI Series, vol 15. Springer, Berlin, Heidelberg, pp 145–159. https://doi.org/10.1007/978-3-642-61187-2_10

  • Jafari SM (2020) Multi-objective optimization of water distribution systems under demand and roughness uncertainties and pipe breakages, Ph.D Dissertation, Gorgan university of Agriculture science and natural resources

  • Jafari SM, Zahiri AR, Bozorg-Haddad O, Tabari MMR (2020) New Approach for Prediction of Water Distribution Network Pipes failure based on an Intelligent Hybrid Model (Case Study: Gorgan Water Distribution Network). J Water soil Conserv 27(5):149–166. (in persion)

    Google Scholar 

  • Jafari SM, Zahiri AR, Hadad OB, Tabari MMR (2021) A hybrid of six soft models based on ANFIS for pipe failure rate forecasting and uncertainty analysis: a case study of Gorgan city water distribution network. Soft Comput 25(11):7459–7478

    Article  Google Scholar 

  • Kapelan Z, Savic DA, Walters GA (2005) Decision-support tools for sustainable urban development. Proc Inst Civ Eng: Eng Sustain 158(3):135–142

    Google Scholar 

  • Liu H, Savić DA, Kapelan Z, Creaco E, Yuan Y (2017) Reliability surrogate measures for water distribution system design: comparative analysis. J Water Resour Plan Manag 143(2):04016072

    Article  Google Scholar 

  • Moosavian N, Lence BJ (2018) Approximation of fuzzy membership functions in water distribution network analysis. J Hydraul Eng 144(7):04018039

    Article  Google Scholar 

  • Sabzkouhi AM, Haghighi A (2016) Uncertainty analysis of pipe-network hydraulics using a many-objective particle swarm optimization. J Hydraul Eng 142(9):1–12

    Article  Google Scholar 

  • Scholten L, Scheidegger A, Reichert P, Mauer M, Lienert J (2014) Strategic rehabilitation planning of piped water networks using multi-criteria decision analysis. Water Res 49:124–143

    Article  CAS  Google Scholar 

  • Seifollahi-Aghmiuni S, Haddad OB, Omid MH, Mariño MA (2013) Effects of pipe roughness uncertainty on water distribution network performance during its operational period. Water Resour Manage 27(5):1581–1599

    Article  Google Scholar 

  • Shafiqul Islam M, Sadiq R, Rodriguez MJ, Najjaran H, Hoorfar M (2014) Reliability assessment for water supply systems under uncertainties. J Water Resour Plan Manag 140(4):468–479

    Article  Google Scholar 

  • Sharp WW, Walski TM (1988) Predicting internal roughness in water mains. J Am Water Works Ass 80(11):34–40

    Article  Google Scholar 

  • Shibu A, Reddy MJ (2011) Uncertainty analysis of water distribution networks by fuzzy-cross entropy approach. World Acad Sci Eng Technol 59:724–731

    Google Scholar 

  • Shibu A, Reddy MJ (2012) Least cost design of water distribution network under demand uncertainty by fuzzy -cross entropy method. J Environ Res Dev 6(3A):853–862

    Google Scholar 

  • Taebi A, Chamani MR (2005) Urban water distribution networks. In: Isfahan University of Technology Publication center, 10rd edn, Isfahan, 600 page (In Persian)

  • Tolson BA, Maier HR, Simpson AR, Lence BJ (2004) Genetic algorithms for reliability-based optimization of water distribution systems. J Water Resour Plan Manag 130(1):63–72

    Article  Google Scholar 

  • Wang Q, Guidolin M, Savic D, Kapelan Z (2015) Two-objective design of benchmark problems of a water distribution system via MOEAs: towards the best-known approximation of the true pareto front. J Water Resour Plan Manag 141(3):04014060

    Article  Google Scholar 

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S. M. Jafari: Conceptualization, Data acquisition, Writing- Original draft preparation, Editing of manuscript; A. R. Zahiri: Conceptualization, Visualization, Supervision; O. Bozorg Haddad: Conceptualization, Supervision, Visualization; Mahmoud Mohammad Rezapour Tabari: Conceptualization, Supervision, Methodology, Visualization, Editing of manuscript.

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Correspondence to M. Mohammad Rezapour Tabari.

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Jafari, S.M., Zahiri, A.R., Haddad, O.B. et al. Uncertainty Analysis of Optimal Instruction for WDN Pipes Repair and Replacement Using Fuzzy α-cut - hydraulic Simulation Approach. Water Resour Manage (2024). https://doi.org/10.1007/s11269-024-03851-7

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