Non-hydraulic Factors Analysis of Pipe Burst in Water Distribution Systems

Pipe bursts in water distribution systems (WDS) must be rapidly detected to minimize the loss of system functionality and recovery time. Pipe burst is the most common failure in WDS. It results in water loss out of the system, increased head losses, and low pressure at the customers' taps. Therefore, effective and efficient detection of pipe bursts can improve system resilience. To this end, this study proposes an optimal meter placement model to identify meter locations that maximize detection effectiveness for a given number of meters and type of meter. The linear programming model is demonstrated on a modified Austin EPANET hydraulic network. Receiver operating characteristic (ROC) curves for alternative pressure and flow meters are applied to investigate the relationship between the level of available information and pipe burst detection effectiveness. The optimal sensor locations were distinctly different depending on the type of meter and the objective to be considered. The ROC curves for alternative pressure and pipe flow meters showed that pipe flow meters are vulnerable to false alarms, and that using many pipe flow meters could detect all pipe bursts. Pressure meters could detect up to 82% of the burst events.

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IoT-Based Pipe Burst Detection in Water Distribution Systems

Innovations in Computer Science and Engineering - Lecture Notes in Networks and Systems ◽

10.1007/978-981-13-7082-3_68 ◽

2019 ◽

pp. 599-604

Author(s):

Suri Shanmukh ◽

Meka Poorna Sai ◽

S. Sai Sri Charan ◽

Nithya Chidambaram

Keyword(s):

Distribution Systems ◽

Water Distribution ◽

Water Distribution Systems ◽

Burst Detection ◽

Pipe Burst

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Near–Real Time Burst Location and Sizing in Water Distribution Systems Using Artificial Neural Networks

Water ◽

10.3390/w13131841 ◽

2021 ◽

Vol 13 (13) ◽

pp. 1841

Author(s):

Miguel Capelo ◽

Bruno Brentan ◽

Laura Monteiro ◽

Dídia Covas

Keyword(s):

Real Time ◽

Distribution Systems ◽

Water Distribution ◽

Water Distribution Systems ◽

Pressure Head ◽

Distribution Networks ◽

Management Tool ◽

Artificial Data ◽

Pipe Burst ◽

Artificial Neural

The current paper proposes a novel methodology for near–real time burst location and sizing in water distribution systems (WDS) by means of Multi–Layer Perceptron (MLP), a class of artificial neural network (ANN). The proposed methodology can be systematized in four steps: (1) construction of the pipe–burst database, (2) problem formulation and ANN architecture definition, (3) ANN training, testing and sensitivity analyses, (4) application based on collected data. A large database needs to be constructed using 24 h pressure–head data collected or numerically generated at different sensor locations during the pipe burst occurrence. The ANN is trained and tested in a real–life network, in Portugal, using artificial data generated by hydraulic extended period simulations. The trained ANN has demonstrated to successfully locate 60–70% of the burst with an accuracy of 100 m and 98% of the burst with an accuracy of 500 m and to determine burst sizes with uncertainties lower than 2 L/s in 90% of tested cases and lower than 0.2 L/s in 70% of the cases. This approach can be used as a daily management tool of water distribution networks (WDN), as long as the ANN is trained with artificial data generated by an accurate and calibrated WDS hydraulic models and/or with reliable pressure–head data collected at different locations of the WDS during the pipe burst occurrence.

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Pipe Burst Localization in Water Distribution Systems Based on Artificial Neural Network

Journal of Water Resources Research ◽

10.12677/jwrr.2018.72016 ◽

2018 ◽

Vol 07 (02) ◽

pp. 144-153

Author(s):

海陈

Keyword(s):

Neural Network ◽

Artificial Neural Network ◽

Distribution Systems ◽

Water Distribution ◽

Water Distribution Systems ◽

Pipe Burst ◽

Artificial Neural

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How are Various Surrogate Indicators Consistent with Mechanical Reliability of Water Distribution Systems: From a Perspective of Many-Objective Optimization

Water ◽

10.3390/w11081669 ◽

2019 ◽

Vol 11 (8) ◽

pp. 1669 ◽

Cited By ~ 2

Author(s):

Wang ◽

Huang ◽

Wang ◽

Zhan ◽

Wang ◽

...

Keyword(s):

Optimal Design ◽

Distribution Systems ◽

Water Distribution ◽

Water Distribution Systems ◽

Poor Performance ◽

Mechanical Reliability ◽

Design Problems ◽

Pipe Burst ◽

The Best Approximation ◽

The One

Exploring the trade-off between cost and system reliability of water distribution systems (WDSs) has been focused for two decades. Due to the intensive computation associated with the reliability analysis, it is popular in the research community to replace this procedure by using surrogate indicators. However, the discussion on the correlation among different types of such indicators is generally lacking, which implies that a deeper understanding of this aspect is needed. This paper proposes a novel methodology of investigating the relationships among many commonly used surrogate indicators for measuring the mechanical reliability of WDSs. In particular, the optimal design of WDSs is formulated as a many-objective optimization problem, using cost and each surrogate indicator as an individual goal. Two benchmark design problems of different scales and complexities are considered for verifying the proposed method. The well-known multi-objective evolutionary algorithm (MOEA), namely Borg that is suitable for coping with problems involving many objectives, is used to obtain the best approximation to the Pareto-optimal fronts for both cases. Afterward, the one-pipe burst testing is conducted to quantify the correlation between mechanical reliability and surrogate indicators. Results suggest that investigating the correlation of surrogate indicators from the perspective of many-objective optimization provides a direct and efficient way of distinguishing better indicators from worse ones. Resilience-based surrogate indicators and the Redundancy indicator that only depends on nodal pressures are highly related to the mechanical reliability of WDSs. In contrast, entropy-based indicators exhibit poor performance in reflecting the mechanical reliability. These insights contribute to the selection of more appropriate surrogate indicators for the optimal design of WDSs for researchers and practitioners.

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Optimal sensor placement for pipe burst detection in water distribution systems using cost–benefit analysis

Journal of Hydroinformatics ◽

10.2166/hydro.2020.158 ◽

2020 ◽

Vol 22 (3) ◽

pp. 606-618

Author(s):

Mengke Zhao ◽

Chi Zhang ◽

Haixing Liu ◽

Guangtao Fu ◽

Yuntao Wang

Keyword(s):

Distribution Systems ◽

Water Distribution ◽

Cost Benefit Analysis ◽

Sensor Placement ◽

Water Distribution Systems ◽

Cost Benefit ◽

Optimal Number ◽

Optimal Detection ◽

Benefit Analysis ◽

Pipe Burst

Abstract Fast detection of pipe burst in water distribution systems (WDSs) could improve customer satisfaction, increase the profits of water supply and more importantly reduce the loss of water resources. Therefore, sensor placement for pipe burst detection in WDSs has been a crucial issue for researchers and practitioners. This paper presents an economic evaluation indicator named as net cost based on cost–benefit analysis to solve the optimal pressure sensor placement problem. The net cost is defined as the sum of the normalized optimal detection uncovering rate and investment cost of sensors. The optimal detection uncovering rate and the optimal set of sensor locations are determined through a single-objective optimization model that maximizes the detection coverage rate under a fixed number of sensors. The optimal number of sensors is then determined by analyzing the relationship between the net cost and the number of sensors. The proposed method is demonstrated to be effective in determining both the optimal number of sensors and their locations on a benchmark network Net3. Moreover, the sensor accuracy and pipe burst flow magnitude are shown to be key uncertainties in determining the optimal number of sensors.

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