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Diagnosis of Pipe Systems by means of a Stochastic Successive Linear Estimator

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Abstract

Environmental concerns and legislation of the water industry have recently drawn the attention of many researchers to the management, calibration and power cost reduction of water pipeline systems. Effective water system management rests upon the knowledge of the current state of a water pipeline system. For example, leakages, unknown status of in-line valves, and partial blockages are often a source of management costs. These anomalies must be detected and corrected as early as possible. In this paper a diagnosis tool is presented able to detect leaks, partially closed in-line valves and partial blockages by means of transient head measurements. The algorithm introduced is a Stochastic successive Linear Estimator [SLE] (Yeh et al. Water Resour Res 32: 2757–2766, 1996a) which provides statistically best unbiased estimate of these anomalies and quantifies the uncertainty associated with these estimates via assimilation of available information. Therefore, the information from common diagnosis techniques e.g., inspection methods, and head measurements available at different locations of the system, obtained by different transient tests are fused to provide the most accurate and reliable diagnosis.

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References

  • Alkasseh JMA, MohdNordin A, Ismail A, HamidiAbdul A, Abu Bakar Mohamad H (2013) Applying minimum night flow to estimate water loss using statistical modeling: a case study in Kinta Valley, Malaysia. Water Resour Manag 27(5):1439–1455

    Article  Google Scholar 

  • Brunone B (1999) Transient test-based technique for leak detection in outfall pipes. J Water Resour Plan Manag ASCE 125(5):302–306

    Article  Google Scholar 

  • Brunone B, Ferrante M (2001) Detecting leaks in pressurised pipes by means of transients. J Hydraul Res 39(5):539–547

    Article  Google Scholar 

  • Brunone B, Ferrante M, Meniconi S (2008a) Portable pressure wave-maker for leak detection and pipe system characterization. J Am Water Works Assoc 100(4):108–116

    Google Scholar 

  • Brunone B, Ferrante M, Meniconi S (2008b) “Discussion of ‘’Detection of Partial Blockage in Single Pipelines“ by Mohapatra PK, Chaudhry MH, Kassem AA, Moloo J.” Journal of Hydrauilic Engineering, ASCE 134 (6) (January): 872–874

  • Cabrera E, Pardo MA, Cobacho R, Cabrera E Jr (2010) Energy audit of water networks. J Water Resour Plan Manag ASCE 136(6):669–677

    Article  Google Scholar 

  • Cabrera E, Pardo MA, Cabrera E Jr, Arregui FJ (2013) Tap water costs and service sustainability, a close relationship. Water Resour Manag 27(1):239–253

    Article  Google Scholar 

  • Christodoulou S, Deligianni A (2009) A neurofuzzy decision framework for the management of water distribution networks. Water Resour Manag 24(1):139–156

    Article  Google Scholar 

  • Colombo AF, Karney BW (2002) Energy and costs of leaky pipes: toward comprehensive picture. J Water Resour Plan Manag ASCE 128(6):441–450

    Article  Google Scholar 

  • Dettinger MD, Wilson JL (1981) First order analysis of uncertainty in numerical models of groundwater flow part 1. Mathematical development. Water Resour Res 17:149–161

    Article  Google Scholar 

  • Fang J, Tacher L (2003) An efficient and accurate algorithm for generating spatially-correlated random fields. Commun Numer Methods Eng 19(10):801–808

    Article  Google Scholar 

  • Ferrante M (2012) Experimental investigation of the effects of pipe material on the leak head-discharge relationship. J Hydraul Eng ASCE 138(8):736–743

    Article  Google Scholar 

  • Ferrante M, Brunone B (2003) Pipe system diagnosis and leak detection by unsteady-state tests. 2. Wavelet analysis. Adv Water Res 26(1):107–116

    Article  Google Scholar 

  • Ferrante M, Brunone B, Meniconi S (2007) Wavelets for the analysis of transient pressure signals for leak detection. J Hydraul Eng ASCE 133(11):1274–1282

    Article  Google Scholar 

  • Ferrante M, Brunone B, Meniconi S (2009) Leak detection in branched pipe systems coupling wavelet analysis and a Lagrangian model. J Water Supply Res Technol AQUA 58(2):95–106

    Article  Google Scholar 

  • Ferrante M, Massari C, Brunone B, Meniconi S (2011) “Experimental evidence of hysteresis in the head-discharge relationship for a leak in a polyethylene pipe. J Hydraul Eng ASCE 137(7):775–780

    Article  Google Scholar 

  • Fletcher J (1988) Computational techniques for fluid dynamics Vol. 1, 409 pp, Springer-Verlag, New York. 1988

  • Gooch RM, Clarke TA, Ellis TJ (1996) “A semi-autonomous sewer surveillance and inspection vehicle.” In Intelligent Vehicles Symposium, 1996. Proceedings of the 1996 IEEE, 64–69

  • Hoeksema RJ, Kitanidis PK (1984) An application of the geostatistical approach to the inverse problem in two-dimensional groundwater modeling. Water Resour Res 20(7):1003–1020

    Article  Google Scholar 

  • Hunt A (1996) Fluid properties determine flow line blockage potential. Oil Gas J 94(29):62–66

    Google Scholar 

  • Kapelan ZS, Savic DA, Walters GA (2003) A hybrid inverse transient model for leakage detection and roughness calibration in pipe networks. J Hydraul Res 41(5):481–492

    Article  Google Scholar 

  • Kitanidis PK, Vomvoris EG (1983) A geostatistical approach to the inverse problem in groundwater modeling (steady state) and one-dimensional simulations. Water Resour Res 19(3):677–690

    Article  Google Scholar 

  • Lee PJ, Vitkovsky JP, Lambert MF, Simpson AR, Liggett JA (2008) Discrete blockage detection in pipelines using the frequency response diagram: numerical study. J Hydraul Eng 134(5):658–663

    Article  Google Scholar 

  • Liggett JA, Chen LC (1994) Inverse transient analysis in pipe networks. J Hydraul Eng ASCE 120(8):934–955

    Article  Google Scholar 

  • Marquardt DW (1963) An algorithm for least-squares estimation of nonlinear parameters. J Soc Ind Appl Math 11(2):431–441

    Article  Google Scholar 

  • Massari C, Ferrante M, Brunone B, Meniconi S (2012) Is the leak head–discharge relationship in polyethylene pipes a bijective function? J Hydraul Res IAHR 50(4):409–417

    Article  Google Scholar 

  • Massari C, Yeh TCJ, Ferrante M, Brunone B, Meniconi S (2013a) “Detection and sizing of extended partial blockages in pipelines by means of a stochastic successive linear estimator” Journal of Hydroinformatics. (In press)

  • Massari C, Yeh TCJ, Ferrante M, Brunone B, Meniconi S (2013b) “A successive stochastic linear estimator to diagnose pipe systems: first results” Journal of Water Science and Technology: Water Supply. (In press)

  • Meniconi S, Brunone B, Ferrante M, Massari C (2010) “Potential of transient tests to diagnose real supply pipe systems: What can be done with a single extemporary test.” Journal of Water Resources Planning and Management 137 (2) (June 24): 238–241

    Google Scholar 

  • Meniconi S, Brunone B, Ferrante M (2011a) In-line pipe device checking by short-period analysis of transient tests. J Hydraul Eng 137(7):713–722

    Article  Google Scholar 

  • Meniconi S, Brunone B, Ferrante M, Massari C (2011b) Small amplitude sharp pressure waves to diagnose pipe systems. Water Res Manag 25(1):79–96

    Article  Google Scholar 

  • Meniconi S, Brunone B, Ferrante M (2012) Water-hammer pressure waves interaction at cross-section changes in series in viscoelastic pipes. J Fluids Struct 33(8):44–58

    Article  Google Scholar 

  • Misiunas D, Vítkovský J, Olsson G, Simpson A, Lambert M (2005) Pipeline break detection using pressure transient monitoring. J Water Res Plan Manag 131(4):316–325

    Article  Google Scholar 

  • Mohapatra PK, Chaudhry MH, Kassem AA, Moloo J (2006) Detection of partial blockage in single pipelines. J Hydraul Eng 132(2):200

    Article  Google Scholar 

  • Romano M, Kapelan Z, Savic AD (2011) “Geostatistical Techniques for Approximate Location of Bursts in Water Distribution Systems.” In 11th International Conference on Computing and Control for the Water Industry: Challenges and Opportunities, CCWI

  • Sharma A, Sandhu BS, Singh B (2010) Incoherent scattering of gamma photons for non-destructive tomographic inspection of pipeline. Appl Radiat Isot Incl Data Instrumen Methods Use Agric Ind Med 68(12):2181–2188

    Google Scholar 

  • Sykes JF, Wilson JL, Andrews RW (1985) Sensitivity analysis for steady state groundwater flow using adjoint operators. Water Resour Res 21(3):359–371

    Google Scholar 

  • Vargas-Guzmán JA, Yeh T-CJ (2002) The successive linear estimator: a revisit. Adv Water Res 25(7):773–781

    Article  Google Scholar 

  • Vítkovský J, Simpson A, Lambert M (2000) Leak detection and calibration using transients and genetic algorithms. J Water Res Plan Manag ASCE 126(4):262–265

    Article  Google Scholar 

  • Wang XJ, Martin L, Simpson A (2005) Detection and location of a partial blockage in a pipeline using damping of fluid transients. J Water Res Plan Manag ASCE 131(3):244–249

    Article  Google Scholar 

  • Wylie E, Streeter V (1993) Fluid Transients in Systems. Prenctice Hall

  • Xiang J, Yeh T-CJ, Lee C-H, Hsu K-C, Wen J-C (2009) A simultaneous successive linear estimator and a guide for hydraulic tomography analysis. Water Resour Res 45, W02432

    Article  Google Scholar 

  • Ye G, Fenner R (2010) “Kalman Filtering of Hydraulic Measurements for Burst Detection in Water Distribution Systems.” Journal of Pipeline Systems Engineering and Practice 2 (1) (31): 14–22

    Google Scholar 

  • Yeh T-CJ, Jin M (1996b) An iterative stochastic inverse method: conditional effective transmissivity and hydraulic head fields. Water Resour Res 32(1):85–92

    Article  Google Scholar 

  • Yeh T-CJ, Liu S (2000) Hydraulic tomography: development of a new aquifer test method. Water Resour Res 36(8):2095–2105

    Google Scholar 

  • Yeh T-CJ, Zhang J (1996a) A geostatistical inverse method for variably saturated flow in the vadose zone. Water Resour Res 32(9):2757–2766

    Article  Google Scholar 

  • Yeh T-CJ, Gutjahr AL, Jin M (1995) An iterative cokriging-like technique for ground-water flow modeling. Ground Water 33(1):33–41

    Article  Google Scholar 

  • Zhang J, Yeh TC, J. T-C (1997) “An iterative geostatistical inverse method for steady flow in the vadose zone.” Water Resources Research 33(1): 63–71

  • Zhu J, Yeh J. T-C (2005) “Characterization of Aquifer Heterogeneity Using Transient Hydraulic Tomography.” Water Resources Research 41(7) (January 26): W07028

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Acknowledgments

This research has been supported by Fondazione Cassa Risparmio Perugia under the Project “Hydraulic characterization of innovative pipe materials” (Project 2013.0050.021).

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Authors and Affiliations

  1. Research Institute for Geo-hydrological Protection, National Research Council, Via Madonna Alta 126, 06128, Perugia, Italy

    Christian Massari

  2. Department of Hydrology and Water Resources, The University of Arizona, John Harshbarger Bldg. 1133 E James E. Rogers Way, Tucson, AZ, 85721, USA

    Tian-Chyi Jim Yeh

  3. Dipartimento di Ingegneria Civile ed Ambientale, University of Perugia, Via Duranti, 93-06125, Perugia, Italy

    Bruno Brunone, Marco Ferrante & Silvia Meniconi

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  1. Christian Massari
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  2. Tian-Chyi Jim Yeh
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  3. Bruno Brunone
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  4. Marco Ferrante
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  5. Silvia Meniconi
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Correspondence to Christian Massari.

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Massari, C., Yeh, TC.J., Brunone, B. et al. Diagnosis of Pipe Systems by means of a Stochastic Successive Linear Estimator. Water Resour Manage 27, 4637–4654 (2013). https://doi.org/10.1007/s11269-013-0433-x

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  • DOI: https://doi.org/10.1007/s11269-013-0433-x

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