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Prediction of water distribution system pipes and isolation valves failure using Bayesian models with the consideration of soil corrosion and climate change Demissie, Gizachew Ababu
Abstract
Aging water distribution system pipes and valves are at stake due to progressive deterioration. Deterioration of the pipes and valves might be as a result of static, operational and dynamic (time-dependent) factors. The impact of these factors are manifested in the form of declined water quality, diminished hydraulic capacity, increased leakage rate and frequent pipe breaks. Reported literature shows that there are a limited number of comprehensive models which integrate characteristics of these factors. As a result, municipalities have been facing a challenge in predicting pipe failure and practicing proactive decision making. The primary objective of this research was to develop a comprehensive Bayesian (Bayesian Belief Network (BBN), Dynamic Bayesian Network (DBN) and Bayesian Model Averaging (BMA)) models to predict/forecast pipe and valve failures by considering driving factors with particular attention to soil corrosion and climate change. Firstly, a comprehensive BBN-based Soil Corrosivity Index (SCI) model was developed to account for interdependencies among different soil parameters. The developed BBN-SCI model combines in situ, experimental, and expert opinion data sources. This model is, then, extended to BBN-based Remaining Service Life (RSL) model which predicts pit depth and quanti es the probability and time to failure for cast iron pipes. The next part of this research evaluates the failure of valves using BBN-based failure mode and effect analysis. The DBN model considers static, operational and time-dependent factors to predict annual and monthly pipe failure rates. Finally, the BMA model integrates climate projection data for future pipe failure forecasting. Overall, this research integrated physical, environmental, and operational factors speculated in contributing to failures of pipes and valves. The data analysis and methodology proposed in this study will help water utility managers and operators to make informed decision making for e cient design and construction of a new water supply systems or planning renewal and rehabilitation programs for old water supply systems. By implementing this methodology, water utilities can incorporate the most impacting pipe and valve failure factors, speci cally soil corrosion and climate change, in operational, tactic, and strategic level decision making.
Item Metadata
Title |
Prediction of water distribution system pipes and isolation valves failure using Bayesian models with the consideration of soil corrosion and climate change
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Creator | |
Publisher |
University of British Columbia
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Date Issued |
2017
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Description |
Aging water distribution system pipes and valves are at stake due to progressive deterioration. Deterioration of the pipes and valves might be as a result of static, operational and dynamic (time-dependent) factors. The impact of these factors are manifested in the form of declined water quality, diminished hydraulic capacity, increased leakage rate and frequent pipe breaks. Reported literature shows that there are a limited number of comprehensive models which integrate characteristics of these factors. As a result, municipalities have been facing a challenge in predicting pipe failure and practicing proactive decision making.
The primary objective of this research was to develop a comprehensive Bayesian (Bayesian Belief Network (BBN), Dynamic Bayesian Network (DBN) and Bayesian Model Averaging (BMA)) models to predict/forecast pipe and valve failures by considering driving factors with particular attention to soil corrosion and climate change. Firstly, a comprehensive BBN-based Soil Corrosivity Index (SCI) model was developed to account for interdependencies among different soil parameters. The developed BBN-SCI model combines in situ, experimental, and expert opinion data sources. This model is, then, extended to BBN-based Remaining Service Life (RSL) model which predicts pit depth and quanti es the probability and time to failure for cast iron pipes. The next part of this research evaluates the failure of valves using BBN-based failure mode and effect analysis. The DBN model considers static, operational and time-dependent factors to predict annual and monthly pipe failure rates. Finally, the BMA model integrates climate projection data for future pipe failure forecasting. Overall, this research integrated physical, environmental, and operational factors speculated in contributing to failures of pipes and valves.
The data analysis and methodology proposed in this study will help water utility managers and operators to make informed decision making for e cient design and construction of a new water supply systems or planning renewal and rehabilitation programs for old water supply systems. By implementing this methodology, water utilities can incorporate the most impacting pipe and valve failure factors, speci cally soil corrosion and climate change, in operational, tactic, and strategic level decision making.
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Genre | |
Type | |
Language |
eng
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Date Available |
2017-10-27
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Provider |
Vancouver : University of British Columbia Library
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Rights |
Attribution-NonCommercial-NoDerivatives 4.0 International
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DOI |
10.14288/1.0357367
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URI | |
Degree | |
Program | |
Affiliation | |
Degree Grantor |
University of British Columbia
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Graduation Date |
2017-11
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Campus | |
Scholarly Level |
Graduate
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Rights URI | |
Aggregated Source Repository |
DSpace
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Rights
Attribution-NonCommercial-NoDerivatives 4.0 International