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CLC number: TU991

On-line Access: 2010-07-06

Received: 2009-10-01

Revision Accepted: 2010-04-09

Crosschecked: 2010-06-10

Cited: 8

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Journal of Zhejiang University SCIENCE A 2010 Vol.11 No.7 P.495-504

http://doi.org/10.1631/jzus.A0900628


An assessment model of water pipe condition using Bayesian inference


Author(s):  Chen-wan Wang, Zhi-guang Niu, Hui Jia, Hong-wei Zhang

Affiliation(s):  School of Environment Science and Technology, Tianjin University, Tianjin 300072, China, School of Environment and Chemical Engineering, Tianjin Polytechnic University, Tianjin 300160, China

Corresponding email(s):   wan314@yahoo.com.cn, nzg@tju.edu.cn

Key Words:  Bayesian inference, Condition assessment, Pipe factor, Water distribution system, Weight


Chen-wan Wang, Zhi-guang Niu, Hui Jia, Hong-wei Zhang. An assessment model of water pipe condition using Bayesian inference[J]. Journal of Zhejiang University Science A, 2010, 11(7): 495-504.

@article{title="An assessment model of water pipe condition using Bayesian inference",
author="Chen-wan Wang, Zhi-guang Niu, Hui Jia, Hong-wei Zhang",
journal="Journal of Zhejiang University Science A",
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pages="495-504",
year="2010",
publisher="Zhejiang University Press & Springer",
doi="10.1631/jzus.A0900628"
}

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%A Zhi-guang Niu
%A Hui Jia
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%J Journal of Zhejiang University SCIENCE A
%V 11
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%P 495-504
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%D 2010
%I Zhejiang University Press & Springer
%DOI 10.1631/jzus.A0900628

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T1 - An assessment model of water pipe condition using Bayesian inference
A1 - Chen-wan Wang
A1 - Zhi-guang Niu
A1 - Hui Jia
A1 - Hong-wei Zhang
J0 - Journal of Zhejiang University Science A
VL - 11
IS - 7
SP - 495
EP - 504
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Y1 - 2010
PB - Zhejiang University Press & Springer
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DOI - 10.1631/jzus.A0900628


Abstract: 
An accurate understanding of the condition of a pipe is important for maintaining acceptable levels of service and providing appropriate strategies for maintenance and rehabilitation in water supply systems. Many factors contribute to pipe deterioration. To consolidate information on these factors to assess the condition of water pipes, this study employed a new approach based on Bayesian configuration against pipe condition to generate factor weights. Ten pipe factors from three pipe materials (cast iron, ductile cast iron and steel) were used in this study. The factors included size, age, inner coating, outer coating, soil condition, bedding condition, trench depth, electrical recharge, the number of road lanes, material, and operational pressure. To address identification problems that arise when switching from pipe factor information to actual pipe condition, informative prior factor weight distribution based on the literature and previous knowledge of water pipe assessment was used. The influence of each factor on the results of pipe assessment was estimated. Results suggested that factors that with smaller weight values or with weights having relative stable posterior means and narrow uncertainty bounds, would have less influence on pipe conditions. The model was the most sensitive to variations of pipe age. Using numerical experiments of different factor combinations, a simplified model, excluding factors such as trench depth, electrical recharge, and the number of road lanes, is provided. The proposed bayesian inference approach provides a more reliable assessment of pipe deterioration.

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