American Society of Civil Engineers


Use of Prior Information on Parameters in Inverse Transient Analysis for Leak Detection and Roughness Calibration


by Zoran S. Kapelan, (Research Fellow, Centre for Water Systems, Department of Engineering, School of Engineering and Computer Science, University of Exeter, North Park Road, Exeter, EX4 4QF, UK), Dragan A. Savic, (Professor, Centre for Water Systems, Department of Engineering, School of Engineering and Computer Science, University of Exeter, North Park Road, Exeter, EX4 4QF, UK), and Godfrey A. Walters, (Reader, Centre for Water Systems, Department of Engineering, School of Engineering and Computer Science, University of Exeter, North Park Road, Exeter, EX4 4QF, UK)

pp. 1-10, (doi:  http://dx.doi.org/10.1061/40569(2001)408)

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Document type: Conference Proceeding Paper
Part of: Bridging the Gap: Meeting the World’s Water and Environmental Resources Challenges
Abstract: Leak detection and calibration of hydraulic models for pipe internal roughnesses and other parameters is undoubtedly an important issue. In this paper, first, a recently developed inverse transient model, capable of detecting leaks and internal pipe roughnesses in water supply networks (WSN), is briefly presented. After that, a classic objective function of weighted least squares type is generalised by adding terms that take into account prior information (PI) on calibration parameters. The methodology presented here is of a general type, i.e. it can be applied to any inverse model. Prior estimates (PE) of both explicit and implicit type and of known and unknown reliability are analysed. It is then shown that PE, when used carefully, can improve the solution of the inverse problem by conditioning it. As a part of the suggested PE approach, a procedure for careful and effective use of PE in inverse problems is defined. After that, the methodology presented here is applied to a case study. At the end, a summary is made and relevant conclusions are drawn.


ASCE Subject Headings:
Calibration
Hydraulic models
Leakage
Water pipelines
Roughness