A Hybrid Search Technique for Inverse Transient Analysis in Water Distribution Systems

  • Zoran S. Kapelan
  • Dragan A. Savic
  • Godfrey A. Walters
Conference paper


Leak detection and calibration of water distribution system (WDS) hydraulic models for pipe internal roughnesses and other parameters is, undoubtedly, an important issue. In this paper, an inverse transient model capable of detecting leaks in pipe networks is presented. First, a brief review of existing leak detection approaches is given. The review is followed by the presentation of a inverse transient model which is formulated as an optimisation problem, with the objective function in the form of weighted least squares and a set of relevant constraints. After identifying advantages and disadvantages of both, Genetic Algorithms (GA) and the Levenberg-Marquardt (LM) search method, a hybrid genetic algorithm was developed to solve the inverse transient problem. Finally, a summary is made and relevant conclusions are drawn.


Genetic Algorithm Water Distribution System Hybrid Genetic Algorithm Water Distribution Network Leak Detection 


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  1. Chen, L.C. (1995), “Pipe Network Transient Analysis — The Forward and Inverse Problems”, PhD Thesis, Faculty of the Graduate School, Cornell University, p. 163.Google Scholar
  2. Cooley, R.L., and Naff, R.L. (1990), “Regression Modelling of Ground-Water Flow”, Techniques of Water Resources Investigations, USGS, vol. Book 3, Chapter B4, p. 232.Google Scholar
  3. Goldberg, D.E. (1989), “Genetic Algorithms in Search, Optimisation and Machine Learning”, Addison-Wesley Publishing Co. Google Scholar
  4. Holland, J.H. (1975), “Adaption in Natural and Artificial Systems”, MIT Press.Google Scholar
  5. Kapelan, Z.S., Savic, D.A., and Walters, G.A. (2001), “A Hybrid Inverse Transient Model for Leakage Detection and Roughness Calibration in Pipe Networks: Theoretical Development and Applications”, Report No. 2001/01, Centre for Water Systems, University of Exeter.Google Scholar
  6. Karney, B.W., and Mclnnis, D. (1992), “Efficient Calculation of Transient Flow in Simple Pipe Networks”, Journal of Hydraulic Engineering, ASCE, 118(7), 1014–1030.CrossRefGoogle Scholar
  7. Liggett, J.A., and Chen, L.C. (1994), “Inverse Transient Analysis in Pipe Networks”, Journal of Hydraulic Engineering, ASCE, 120(8), 934–955.CrossRefGoogle Scholar
  8. Mclnnis, D.A. (1992), “Comprehensive Hydraulic Analysis of Complex Pipe Systems”, PhD Thesis, Department of Civil Engineering, University of Toronto.Google Scholar
  9. Morley, M.S., Atkinson, R.M., Savic, D.A., and Walters, G.A. (2001), “GAnet: Genetic Algorithm platform for pipe network optimisation”, Advances in Engineering Software, 32(6), 467–475.MATHCrossRefGoogle Scholar
  10. Moscato, P. (1989), “On Evolution, Search, Optimisation, Genetic Algorithms and Martial Arts”, Report No. 826, California Institute of Technology.Google Scholar
  11. Murphy, L.J., and Simpson, A.R. (1992), “Genetic Algorithms in Pipe Network Optimisation”, Report No. R93, Department of Civil and Environmental Engineering, University of Adelaide.Google Scholar
  12. Nash, G.A., and Karney, B.W. (1999), “Efficient Inverse Transient Analysis in Series Pipe Systems”, Journal of Hydraulic Engineering, ASCE, 125(7), 761–764.CrossRefGoogle Scholar
  13. Norman, M.G., and Moscato, P. (1989), “A Competitive and Cooperative Approach to Complex Combinatorial Search”, Report No. 790, California Institute of Technology.Google Scholar
  14. Pudar, R.S., and Liggett, J.A. (1992), “Leaks in Pipe Networks”, Journal of Hydraulic Engineering, ASCE, 118(7), 1031–1046.CrossRefGoogle Scholar
  15. Savic, D., and Walters, G. (1997), “Genetic Algorithms for the Least-Cost Design of Water Distribution Networks”, Journal of Water Resources Planning and Management, ASCE, 123(2), 67–77.CrossRefGoogle Scholar
  16. Savic, D.A., and Walters, G.A. (1995), “Genetic Algorithm Techniques for Calibrating Network Models”, Report No. 95/12, Centre for Systems and Control Engineering, University of Exeter, p. 41.Google Scholar
  17. Simpson, A.R., and Vitkovsky, J.P. (1997), “A Review of Pipe Calibration and Leak Detection Methodologies for Water Distribution Networks”, Proc. 17th Federal Convention, Australian Water and Wastewater Association, Australia, vol. 1, 680–687.Google Scholar
  18. Vicini, A., and Quagliarella, D. (1998), “Airfoil and Wing Design Through Hybrid Optimization Strategies”, Proc. 16th Applied Aerodynamics Conference, Albuquerque, New Mexico.Google Scholar
  19. Vitkovsky, J.P., and Simpson, A.R. (1997), “Calibration and Leak Detection in Pipe Networks Using Inverse Transient Analysis and Genetic Algorithms”, Report No. R 157, Department of Civil and Environmental Engineering, University of Adelaide, p. 97.Google Scholar
  20. Vitkovsky, J.P., Simpson, A.R., and Lambert, M.F. (2000), “Leak Detection and Calibration Using Transients and Genetic Algorithms”, Journal of Water Resources Planning and Management, ASCE, 126(4), 262–265.CrossRefGoogle Scholar
  21. Wylie, E.B., and Streeter, V.L. (1978), “Fluid Transients”, McGraw-Hill International Book Company, p. 384.Google Scholar

Copyright information

© Springer-Verlag London 2002

Authors and Affiliations

  • Zoran S. Kapelan
    • 1
  • Dragan A. Savic
    • 1
  • Godfrey A. Walters
    • 1
  1. 1.Department of Engineering School of Engineering and Computer ScienceUniversity of ExeterExeterUK

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