An analysis of pipe breakage in urban water distribution networks

1985 ◽  
Vol 12 (2) ◽  
pp. 286-293 ◽  
Author(s):  
A. J. Kettler ◽  
I. C. Goulter
Keyword(s):  
Cast Iron ◽  
Water Distribution ◽  
Distribution Networks ◽  
Failure Rates ◽  
Pipe Failure ◽  
Modes Of Failure ◽  
Asbestos Cement ◽  
Pipe Systems ◽  
Pipe Breakage ◽  
Joint Regression Analysis

The rates of pipe breakage with increasing pipe diameter and times are investigated. Failure rates for cast-iron pipe are found to decrease with increasing diameter. Changes in pipe failure rates for the various modes of failures are examined in detail. Asbestos-cement and cast-iron pipe overall failure rates are found to increase with time, but for different reasons. Analysis of the modes of failure shows that joint failure is predominant for cast-iron pipe systems with bolted and universal joints whereas the predominant mode of failure for asbestos-cement pipe systems is circumferential cracking. Key words: asbestos cement, cast iron, cracking, diameter, failure rate, joint, regression analysis.

scholarly journals Comparison of Statistical and Machine Learning Models for Pipe Failure Modeling in Water Distribution Networks

Water ◽  
2020 ◽  
Vol 12 (4) ◽  
pp. 1153 ◽  
Author(s):  
Mónica Marcela Giraldo-González ◽  
Juan Pablo Rodríguez
Keyword(s):  
Machine Learning ◽  
Developing Countries ◽  
Statistical Models ◽  
Water Distribution ◽  
Distribution Networks ◽  
Support Vector ◽  
Failure Rates ◽  
Learning Models ◽  
Pipe Failure ◽  
Machine Learning Models

The application of statistical and Machine Learning models plays a critical role in planning and decision support processes for efficient and reliable Water Distribution Network (WDN) management. Failure models can provide valuable information for prioritizing system rehabilitation even in data scarcity scenarios, such as developing countries. Few studies have analyzed the performance of more than two models, and examples of case studies in developing countries are insufficient. This study compares various statistical and Machine Learning models to provide useful information to practitioners for the selection of a suitable pipe failure model according to information availability and network characteristics. Three statistical models (i.e., Linear, Poisson, and Evolutionary Polynomial Regressions) were used for failure prediction in groups of pipes. Machine Learning approaches, particularly Gradient-Boosted Tree (GBT), Bayes, Support Vector Machines and Artificial Neuronal Networks (ANNs), were compared in predicting individual pipe failure rates. The proposed approach was applied to a WDN in Bogotá (Colombia). The statistical models showed an acceptable performance (R2 between 0.695 and 0.927), but the Poisson Regression was the most suitable for predicting failures in pipes with lower failure rates. Regarding Machine Learning models, Bayes and ANNs exhibited low performance in the prediction of pipe failure condition. The GBT approach had the best performing classifier.

scholarly journals Factors contributing to the failure of asbestos cement water mains

2007 ◽  
Vol 34 (5) ◽  
pp. 608-621 ◽  
Author(s):  
Y Hu ◽  
D W Hubble
Keyword(s):  
Water Distribution ◽  
Structural Integrity ◽  
Clay Soil ◽  
Distribution Networks ◽  
Soil Conditions ◽  
Clear Understanding ◽  
Pipe Failure ◽  
Asbestos Cement ◽  
Water Mains ◽  
The City

Asbestos cement (AC) water mains were installed extensively in North America, Europe, and Australia from the late 1920s to the early 1980s and still form a significant component of water distribution networks of many cities. These water mains are ageing and some water systems have experienced a high breakage rate in AC mains in recent years. It is essential that a clear understanding be developed of the factors contributing to their failure to ensure that municipalities and water authorities can manage their AC water-main assets. In this paper, the historical failure data of AC water mains from the City of Regina were collected and correlated with their corresponding environmental setting, including soil type, water quality, climate, and construction and maintenance practices. The predominant factors that influence the AC pipe breaks were identified. It was observed that pipe age, diameter, climate, clay soil, and construction and maintenance methods all influence the failure of AC water mains in the city, with climate and clay soil conditions being the two critical factors. Some chemical attack from the conveyed water and soil pore water may have occurred and detrimentally affected the structural integrity of the AC water mains. Key words: asbestos cement pipes, water mains, pipe failure, clay soil, climate.

scholarly journals Management of Water Distribution Systems in PDA Condition with Isolation Valves

Proceedings ◽  
2018 ◽  
Vol 2 (11) ◽  
pp. 672 ◽  
Author(s):  
Attilio Fiorini Morosini ◽  
Olga Caruso ◽  
Paolo Veltri
Keyword(s):  
Distribution Systems ◽  
Water Distribution ◽  
Distribution Networks ◽  
Optimal Number ◽  
System Control ◽  
Pipe Failure ◽  
Reliable System ◽  
Network Nodes ◽  
Pipe Burst

The correct management of Water Distribution Networks (WDNs) allows to obtain a reliable system. When a pipe failure occurs in a network and it is necessary to isolate a zone, it is possible that some nodes do not guarantee service for the users due to inadequate heads. In these conditions a Pressure Driven Analysis (PDA) is the correct approach to evaluate network behavior. This analysis is more appropriate than the Demand Driven Analysis (DDA) because it is known that the effective delivered flow at each node is influenced by the pressure value. In this case, it is important to identify a subset of isolation valves to limit disrupting services in the network. For a real network, additional valves must be added to existing ones. In this paper a new methodological analysis is proposed: it defines an objective function (OF) to provide a measure of the system correct functioning. The network analysis using the OF helps to choose the optimal number of additional valves to obtain an adequate system control. In emergency conditions, the OF takes into account the new network topology obtained excluding the zone where the broken pipe is located. OF values depend on the demand deficit caused by the head decrement in the network nodes for each pipe burst considered. The results obtained for a case study confirm the efficiency of the methodology.

scholarly journals Prediction of pipe failure rate in Tehran water distribution networks by applying regression models

2018 ◽  
Vol 19 (3) ◽  
pp. 695-702 ◽  
Author(s):  
Homayoun Motiee ◽  
Sonya Ghasemnejad
Keyword(s):  
Logistic Regression ◽  
Statistical Models ◽  
Poisson Regression ◽  
Regression Models ◽  
Water Distribution ◽  
Water Distribution Network ◽  
Distribution Networks ◽  
Hydraulic Pressure ◽  
Pipe Failure ◽  
Exponential Regression

Abstract Four statistical models (linear regression, exponential regression, Poisson regression and logistic regression) applied to analyze the variables in pipe vulnerabilities with the objective of finding equations to predict probable future pipe accidents. The most effective variables in pipe failures are material, age, length, diameter and hydraulic pressure. To evaluate these models, the data collected in recent years in the water distribution network of district 1 in Tehran were used, with a total length of 582,702 m of pipes, and 48,500 consumers. The results demonstrate that among the four studied models, the logistic regression model is best able to give a good performance and is capable of predicting future accidents with a higher probability.

Spatial and temporal groupings of water main pipe breakage in Winnipeg

1988 ◽  
Vol 15 (1) ◽  
pp. 91-97 ◽  
Author(s):  
I. C. Goulter ◽  
A. Kazemi
Keyword(s):  
Water Distribution ◽  
Interval Parameter ◽  
Pipe Failure ◽  
Spatial And Temporal Patterns ◽  
Exponential Decrease ◽  
Spatial Interval ◽  
Ground Conditions ◽  
Temporal And Spatial ◽  
Pipe Breakage ◽  
The City

The spatial and temporal patterns of water distribution pipe failure in the City of Winnipeg are examined. The failures are shown to be strongly clustered in space, where 22% of the total failures examined occur within 1 m of another failure and 46% occur within 20 m of another failure. A strong temporal clustering is also apparent, with 42% of all failures that occur within 1 m of another found also to occur within 1 day of the initial failure in the group. An exponential decrease in the marginal rates of failure with respect to both the temporal and spatial interval parameter is also observed. Earlier failures in a particular location appear to be an important key to assessing potential failures in that vicinity. These results suggest that a fruitful area for further examination for the reduction of failure rates is the change in the ground conditions resulting from an initial leak and its subsequent repair. Key words: failures, groupings, marginal rates, pipes, space, time, water distribution, Winnipeg.

scholarly journals Complex network and fractal theory for the assessment of water distribution network resilience to pipe failures

2017 ◽  
Vol 18 (3) ◽  
pp. 767-777 ◽  
Author(s):  
Armando Di Nardo ◽  
Michele Di Natale ◽  
Carlo Giudicianni ◽  
Roberto Greco ◽  
Giovanni Francesco Santonastaso
Keyword(s):  
Complex Network ◽  
Water Distribution ◽  
Fractal Theory ◽  
Distribution Networks ◽  
Pipe Failure ◽  
Operational Conditions ◽  
Complex Network Theory ◽  
Topological Features ◽  
Wide Range ◽  
The Impact

AbstractWater distribution networks (WDNs) must keep a proper level of service under a wide range of operational conditions, and, in particular, the analysis of their resilience to pipe failures is essential to improve their design and management. WDNs can be regarded as large sparse planar graphs showing fractal and complex network properties. In this paper, the relationship linking the geometrical and topological features of a WDN to its resilience to the failure of a pipe is investigated. Some innovative indices have been borrowed from fractal geometry and complex network theory to study WDNs. Considering all possible network configurations obtained by suppressing one link, the proposed indices are used to quantify the impact of pipe failure on the system's resilience. This approach aims to identify critical links, in terms of resilience, with the help of topological metrics only, and without recourse to hydraulic simulations, which require complex calibration processes and come with a computational burden. It is concluded that the proposed procedure, which has been successfully tested on two real WDNs located in southern Italy, can provide valuable information to water utilities about which pipes have a significant role in network performance, thus helping in their design, planning and management.

scholarly journals The Unfavourable Impact of Street Traffic on Water Distribution Pipelines

Water ◽  
2018 ◽  
Vol 10 (8) ◽  
pp. 1086 ◽  
Author(s):  
Ioan Așchilean ◽  
Mihai Iliescu ◽  
Nicolae Ciont ◽  
Ioan Giurca
Keyword(s):  
Cast Iron ◽  
Water Supply ◽  
Water Distribution ◽  
Road Traffic ◽  
Distribution Networks ◽  
Negative Influence ◽  
Supply System ◽  
Water Supply System ◽  
Pipe Material

This article analyses the relation between the failures that occurred in the water supply network and the road traffic in the city of Cluj-Napoca in Romania. The calculations in this case study were made using the Autodesk Robot Structural Analysis Professional 2011 software. In the case study, the following types of pipes were analysed: steel, gray cast iron, ductile cast iron and high density polyethylene (HDPE). While in most studies only a few sections of pipelines, several types of pipelines and certain mounting depths have been analysed, the case study presented analyses the entire water supply system of a city with a population of 324,576 inhabitants, whose water supply system has a length of 479 km. The results of the research are useful in the design phase of water distribution networks, so depending on the type of pipe material, the minimum depth of installation can be indicated, so as to avoid the failure of the pipes due to road traffic. From this perspective, similar studies could also be carried out regarding the negative influence of road traffic on sewerage networks, gas networks and heating networks.

Predicting the effect of water quality on water distribution cast iron and steel pipes using two novel indices

2017 ◽  
Vol 18 (2) ◽  
pp. 524-538
Author(s):  
Marc Philibert ◽  
Sofia Mendaza ◽  
Flavia Zraick ◽  
Benjamin Rabaud
Keyword(s):  
Cast Iron ◽  
Corrosion Rate ◽  
Water Distribution ◽  
Iron Particle ◽  
Distribution Networks ◽  
Pilot Scale ◽  
Internal Corrosion ◽  
Iron And Steel ◽  
Particle Release ◽  
Steel Pipes

Abstract The internal corrosion of cast iron and steel pipes is one of the main issues that drinking water distribution operators are facing. This study evaluated the relevance of 10 known corrosion indices according to their estimate of corrosion rate and iron particle release for 20 different water qualities. Pilot-scale contact trials were run over 45 days using cast iron and steel coupons. Corrosion rate was measured by coupon weight-loss and by an online linear polarization rate probe. Particle release was monitored by an online turbidimeter. The results showed that none of the indices properly predicted the level of risk associated with each water and that corrosion and particle release were not correlated. Two novel indices were developed to predict the corrosion and particle release risks independently of each other. The corrosion index showed a strong linear correlation with the corrosion rate of cast iron and slightly less reliable results for steel. The Particle Emission Index presented good correlation with turbidity in waters following contact with cast iron. These two indices thus showed interesting potential as tools to limit internal corrosion risks for metal pipes in water distribution networks.

scholarly journals Assessing pipe failure rate and mechanical reliability of water distribution networks using data-driven modeling

2009 ◽  
Vol 11 (1) ◽  
pp. 1-17 ◽  
Author(s):  
M. Tabesh ◽  
J. Soltani ◽  
R. Farmani ◽  
D. Savic
Keyword(s):  
Neural Network ◽  
Multivariate Regression ◽  
Regression Models ◽  
Water Distribution ◽  
Distribution Networks ◽  
Data Driven ◽  
Mechanical Reliability ◽  
Pipe Failure ◽  
Neuro Fuzzy ◽  
Data Driven Modeling

In this paper two models are presented based on Data-Driven Modeling (DDM) techniques (Artificial Neural Network and neuro-fuzzy systems) for more comprehensive and more accurate prediction of the pipe failure rate and an improved assessment of the reliability of pipes. Furthermore, a multivariate regression approach has been developed to enable comparison with the DDM-based methods. Unlike the existing simple regression models for prediction of pipe failure rates in which only few factors of diameter, age and length of pipes are considered, in this paper other parameters such as pressure and pipe depth, are also included. Furthermore, an investigation is carried out on most commonly used mechanical reliability relationships and the results of incorporation of the proposed pipe failure models in the reliability index are compared. The proposed models are applied to a real case study involving a large water distribution network in Iran and the results of model predictions are compared with measured pipe failure data. Compared with the results of neuro-fuzzy and multivariate regression models, the outcomes of the artificial neural network model are more realistic and accurate in the prediction of pipe failure rates and evaluation of mechanical reliability in water distribution networks.

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