Multi-criteria Calibration of Water-supply Networks under Unsteady Flow

Subject Areas : Subjects

Saeed Sarkamaryan ¹ (Ph.D. Candidate, Civil Engineering Department, Faculty of Engineering, Shahid Chamran University of Ahvaz, Ahvaz, Iran, Mobile)
Ali Haghighi ² (Associate Professor, Civil Engineering Department, Faculty of Engineering, Shahid Chamran University of Ahvaz, Ahvaz, Iran)
Arash Adib ³ (Professor, Civil Engineering Department, Faculty of Engineering, Shahid Chamran University of Ahvaz, Ahvaz, Iran)

Received: 2017-05-18 Accepted : 2019-06-09 Published : 2019-05-22

Keywords: Optimization, Calibration, Inverse transient analysis, Unsteady flow, Correction factors,

Abstract :

To evaluate a pipe network performance, both steady and unsteady flow conditions are required to be accurately analyzed in the system. For this purpose, mathematical models are developed and utilized. Calibration of parameters with dynamic effects like the steady and unsteady friction loss factors as well as pipe wave speed is crucial to the simulation models. A common approach for calibration of pipe networks under unsteady flow is the Inverse Transient Analysis (ITA) method. This study introduces a model for hydraulic analysis of unsteady flow in pressurized pipes using the numerical Method of Characteristics (MOC). To each calibration parameter a correction factor is specified. Then, a nonlinear optimization problem is developed with the aim of minimizing the discrepancy between the calculated and measured transient pressure heads at the measurement sites. The decision variables are the correction factors multiplied by the pipe wave speeds, steady friction factors and unsteady friction loss components. In this Article, the proposed model applied to an experimental system set up in the Technical University of Lisbon. By defining the genetic algorithm to minimize the objective function, after 30 generations error rate was reduced from 140 m to 92.15 meters. The results, increasing the accuracy of modeling showed as much as 33%.

References:

1) Bergant, A., Ross Simpson, A., & Vìtkovsk, J. 2001. Developments in unsteady pipe flow friction modelling. Journal of Hydraulic Research, 39(3), 249-257.
2) Brunone, B., Golia, U. M., & Greco, M. 1991. Modelling of fast transients by numerical methods. In Proc. Int. Conf. on Hydr. Transients With Water Column Separation (pp. 273-280).
3) Brunone, B., Golia, U. M., & Greco, M. 1995. Effects of two-dimensionality on pipe transients modeling. Journal of Hydraulic Engineering, 121(12), 906-912.
4) Chaudhry, M. H. 2014. Applied Hydraulic Transients (p. 503). Springer New York.
5) Covas, D., & Ramos, H. 2001. Hydraulic transients used for leakage detection in water distribution systems. In 4th International Conference on Water Pipeline Systems.
6) Covas, D., Ramos, H., Brunone, B., & Young, A. 2004. Leak detection in water trunk mains using transient pressure signals: Field tests in Scottish water. In International conference on pressure surges.
7) Daily, J. W., Hankey Jr, W. L., Olive, R. W., & Jordaan Jr, J. M. 1955. Resistance coefficients for accelerated and decelerated flows through smooth tubes and orifices. Massachusetts inst of tech Cambridge, (No. 55-SA-78).
8) Haghighi, A., & Ramos, H. M. 2012. Detection of leakage freshwater and friction factor calibration in drinking networks using central force optimization. Water resources management, 26(8), 2347-2363.
9) Huang, Y. C., Lin, C. C., & Yeh, H. D. 2015. An optimization approach to leak detection in pipe networks using simulated annealing. Water Resources Management, 29(11), 4185-4201.
10) Jung, B., & Karney, B. 2008. Systematic exploration of pipeline network calibration using transients. Journal of Hydraulic Research, 46(sup1), 129-137.
11) Kapelan, Z. S., Savic, D. A., & Walters, G. A. 2003. A hybrid inverse transient model for leakage detection and roughness calibration in pipe networks. Journal of Hydraulic Research, 41(5), 481-492.
12) Liggett, J. A., & Chen, L.-C. 1994. Inverse transient analysis in pipe networks. Journal of hydraulic engineering, 120(8), 934-955.
13) Shamloo, H., & Haghighi, A. 2010. Optimum leak detection and calibration of pipe networks by inverse transient analysis. Journal of Hydraulic Research, 48(3), 371-376.
14) Vardy, A., & Brown, J. 1996. On turbulent, unsteady, smooth-pipe friction. In BHR group conference series publication (Vol. 19, pp. 289-312).
92 مجله ی مهندسی منابع آب / سال دوازدهم / بهار 8931
15) Vítkovský, J. P., Simpson, A. R., & Lambert, M. F. 2000. Leak detection and calibration using transients and genetic algorithms. Journal of Water Resources Planning and Management, 126(4), 262-265.
16) Vítkovský, J. P., Lambert, M. F., Simpson, A. R., & Liggett, J. A. 2007. Experimental observation and analysis of inverse transients for pipeline leak detection. Journal of Water Resources Planning and Management, 133(6), 519-530.
17) Zielke, W. 1968. Frequency-dependent friction in transient pipe flow. Journal of Fluids Engineering, 90(1), 109-115.

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