Technical Papers
Apr 30, 2018

Direct Inversion Algorithm for Pipe Resistance Coefficient Calibration of Water Distribution Systems

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Publication: Journal of Water Resources Planning and Management
Volume 144, Issue 7

Abstract

To enable a water distribution system (WDS) model to yield predictions with a reasonably good match to measurements, pipe resistance coefficients (PRCs) of the model often need to be calibrated. The majority of methods developed recently solve the PRCs’ calibration problem using evolutionary algorithms. The common feature of these methods is to perform the forward computation (i.e., solve the traditional hydraulic equation of networks) repeatedly to search optimal solutions. This paper presents a direct inversion algorithm for PRC calibration of WDSs, which has an identical framework with a global gradient algorithm (GGA) that has been proved to be the most effective method to solve networks and adopted by EPANET. Therefore, all advantages of GGA can be extended in terms of high computational efficiency and convergence, as well as being easy to understand and program. In addition, under the proposed framework, uncertainties propagated from measurement noises, nodal demand uncertainties, and model simplification errors to the estimates can be quantified individually or simultaneously in a flexible manner, enabling the identification of uncertainties source, as well as which kind of effort is preferred to reduce them. Three networks are applied to validate the proposed algorithm. Encouraging results achieved demonstrate that the proposed algorithm is valid for the calibration and uncertainty qualification of PRCs, as well as the uncertainty source identification.

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Acknowledgments

The authors would like to thank the editor and reviewers, especially Dr. Tom Walski, for their guidance and constructive proposals that improved the quality of the paper. This work supported by National Natural Science Foundation of China under Grant No. 51608242.

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Go to Journal of Water Resources Planning and Management
Journal of Water Resources Planning and Management
Volume 144Issue 7July 2018

History

Received: May 24, 2017
Accepted: Jan 17, 2018
Published online: Apr 30, 2018
Published in print: Jul 1, 2018
Discussion open until: Sep 30, 2018

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Kun Du, Ph.D. [email protected]
Lecturer, Faculty of Architectural Engineering, Kunming Univ. of Science and Technology, Kunming 650500, China; Key Laboratory of Eco-Environments in Three Gorges Reservoir Region, Chongqing Univ., Chongqing 400045, China (corresponding author). Email: [email protected]
Rong-yi Ding [email protected]
Master’s Student, Faculty of Architectural Engineering, Kunming Univ. of Science and Technology, Kunming 650500, China. Email: [email protected]
Zhi-hao Wang [email protected]
Associate Professor, Faculty of Architectural Engineering, Kunming Univ. of Science and Technology, Kunming 650500, China. Email: [email protected]
Zhi-gang Song [email protected]
Professor, Faculty of Architectural Engineering, Kunming Univ. of Science and Technology, Kunming 650500, China. Email: [email protected]
Bing-feng Xu [email protected]
Associate Professor, Faculty of Architectural Engineering, Kunming Univ. of Science and Technology, Kunming 650500, China. Email: [email protected]
Associate Professor, Faculty of Architectural Engineering, Kunming Univ. of Science and Technology, Kunming 650500, China. Email: [email protected]
Yun Bai, Ph.D. [email protected]
Lecturer, National Research Base of Intelligent Manufacturing Service, Chongqing Technology and Business Univ., Chongqing 400067, China. Email: [email protected]
Senior Research Fellow, Institute of Urban Water Management, Technische Universität Dresden, Dresden 01062, Germany. Email: [email protected]

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