Identifying the Location and Amount of Two Simultaneous Leaks in Water Supply Networks by a Two-step Algorithm

Document Type : Research Article

Authors

1 M. Sc. Student, Faculty of Civil, Water,Environmental Engineering, Shahid Beheshti University

2 Assistant Professor, Faculty of Civil, Water, and Environmental Engineering, Shahid Beheshti University

Abstract

Leakage in the water distribution systems is a crucial issue because of some problems such as water loss, water pollution, and land subsidence. The current leakage detection methods are usually costly and time-consuming; therefore, some new methods have been developed based on the water networks simulation. In this paper, a new method for identifying the location and amount of leakage in water distribution systems based on a two-step algorithm is introduced. The first (Stepped Algorithm) and second (Firefly Algorithm) steps to determine the leak location and amount of leakage are respectively used which is applicable for up to two simultaneous leaks. The proposed method is based on the comparison of the network hydraulic simulation results and some field network data (pressure or flow or their combination). “Also, this method has no sensitivity on the location of leaks and can identify low amounts of leakage ( below 0.3% of the network inflow”) The obtained results for six examples in a looped-water network are presented. The results show that the proposed algorithm can locate both one leak and two simultaneous leaks and their leakage values with less than 8% error. The proposed developed method can be utilized by operators of water supply networks for finding unreported leakage..

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References

[1]  R. Puust, Z. Kapelan, D.A. Savic, T. Koppel, A review of methods for leakage management in pipe networks, Urban Water Journal, 7)1( )2010( 25-45.
[2]  N. Samir, R. Kansoh, W. Elbarki, A. Fleifle, Pressure control for minimizing leakage in water distribution systems, Alexandria Engineering Journal, 56)4( )2017( 601-612.
[3]  Vice Presidency for Strategic Planning and Supervision, The Guide to Recognizing and Investigating the Effective Factors in Unaccounted-For Water the Unaccounted and Approaches to its Reduction, 2012 ( in persian ).
[4]  M. Attari, M. Faghfour Maghrebi, New Method for Leakage Detection by Using Artificial Neural Networks, Journal of Water and Wastewater; Ab va Fazilab ( in persian ), 29(1) (2018) 14-26 ( in persian ).
[5]  M. Faghafur Maghrebi, M. Attari, The new leak detection method in the water supply network using the minimum pressure metering in the presence of two simultaneous leaks, in:  Seventh National Congress on Civil Engineering, Zahedan,Sistan and Baluchestan University 2013 ( in persian ).
[6]  A. Candelieri, D. Conti, F. Archetti, A Graph based Analysis of Leak Localization in Urban Water Networks, Procedia Engineering, 70 (2014) 228-237.
[7]  M. Faghafur Maghrebi, M. Aghaebrahimi, H. Taherian, M. Attari, Determining the amount and location of leakage in water supply networks using a neural network improved by the bat optimization algorithm, Journal of Civil Engineering and Urbanism, 4(3) (2014) 322-327.
[8]  J. Sousa, L. Ribeiro, J. Muranho, A.S. Marques, Locating Leaks in Water Distribution Networks with Simulated Annealing and Graph Theory, Procedia Engineering,119(2015)63-71.
[9]  M. Faghafur Maghrebi, Y. Hasanzadeh, S. Yazdani, Calibration of Water Supply Systems Based on Ant Colony Optimization, Water & Wastewater, Journal of Water and Wastewater; Ab va Fazilab (  in persian ), 24(1) (2013) 101-111 ( in persian).
[10]  M. Rahmanshahi, M. Fathi-Moghadam, A. Haghighi, Leak Detection in Viscoelastic Pipeline Using Inverse Transient Analysis, Journal of Water and Wastewater; Ab va Fazilab ( in persian ), 29(5) (2018) 85-97 ( in persian ).
[11]   M. Attari, M. Zaki Pour, M. Faghafur Maghrebi, Determination of the position and amount of leakage in water supply networks by using the combination of pressure metering and flow metering by neural networks, in:  Second National Conference ways of the front of Water Crisis in Iran and the Middle East Shiraz, Scientific Conferences Center Neghar Conference, 2015 ( in persian ).
[12]  A. Boostani, S.R. Khodashenas, Studying a leakage detection method in pressurized water networks based on the pressure–leakage relation (Presentation of Optimization Code for Locating Leakage), Journal of Water and Sustainable Development, 2(1) (2015) 5966 ( in persian ).
[13]  S. Sophocleous, D. A. Savić, Z. Kapelan, O. Giustolisi, A two-stage calibration for detection of leakage hotspots in a real water distribution network, in:  XVIII International Conference on Water Distribution Systems Analysis, WDSA2016, Elsevier, 2017, pp. 168-176.
[14]   E. Hajibandeh, S. Nazif, Pressure Zoning Approach for Leak Detection in Water Distribution Systems Based on a Multi Objective Ant Colony Optimization, Water Resources Management, 32(7) (2018) 2287-2300.
[15]  R. Moasheri, M. Jalili Ghazizadeh, Locating of Probabilistic Leakage Areas in Water Distribution Networks by a Calibration Method Using the Imperialist Competitive Algorithm, Water Resources Management, 34(1) (2020) 35-49.
[16]   M. Shekofteh, M. Jalili Ghazizadeh, J. Yazdi, A methodology for leak detection in water distribution networks using graph theory and artificial neural network, Urban Water Journal, 17(6)(2020) 525-533.
[17]  Z. Poulakis, D. Valougeorgis, C. Papadimitriou, Leakage detection in water pipe networks using a Bayesian probabilistic framework, Probabilistic Engineering Mechanics, 18(4) (2003) 315-327.
[18]   Matlab 2017b )9.3.0.713579( 64-bit )win 64(, in, September 17, 2017.
[19] Y. Xin-She, Engineering Optimization : an introduction with metaheuristic applications, John Wiley & Sons, Inc, 2010.
Amirkabir Journal of Civil Engineering
Volume 52, Issue 5
August 2020
Pages 1175-1186

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