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.

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 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.

scholarly journals Water Distribution Network Reliability: are Surrogate Measures Reliable?

10.29007/4whr ◽  
2018 ◽  
Author(s):  
João Muranho ◽  
Joaquim Sousa ◽  
Alfeu Sá Marques ◽  
Ricardo Gomes
Keyword(s):  
Water Distribution ◽  
Simulated Annealing Algorithm ◽  
Network Reliability ◽  
Water Distribution Network ◽  
Distribution Networks ◽  
Water Safety ◽  
Pipe Failure ◽  
Resilience Index ◽  
Surrogate Measures ◽  
Hydraulic Reliability

Water distribution networks (WDNs) must be reliable infrastructures since they provide an essential service to society. Reliability assessment is a complex task and involves various aspects: mechanical, hydraulic, water quality, water safety, among others. This paper focuses on the hydraulic reliability. Hydraulic reliability is computationally hard to measure directly, therefore researchers came up with surrogate measures, like the resilience index, the modified resilience index, the flow entropy or the diameter-sensitive flow entropy, that are simple and fast to compute. But, are these surrogate measures reliable to be used in the design of WDNs?This paper proposes a new reliability index based on the surplus flow available on each node to mitigate the effects of a pipe failure. To illustrate the applicability of this new index, a WDN example is optimally designed using a simulated annealing algorithm. Results show that the solutions based on the flow entropy or on the proposed index are more reliable than the others, and, also, the maximization of the other reliability indexes gives only a residual contribution to the global reliability (or even no contribution at all).

Upgrading water distribution networks to work under uncertain conditions

2020 ◽  
Vol 20 (3) ◽  
pp. 878-888 ◽  
Author(s):  
J. Marques ◽  
M. Cunha
Keyword(s):  
Water Distribution ◽  
Water Distribution Network ◽  
Distribution Networks ◽  
Water Distribution Networks ◽  
Pipe Failure ◽  
Network Layout ◽  
Failure Assessment ◽  
Uncertain Future ◽  
Alternative Solutions

Abstract This work presents a multicriteria approach to defining flexible solutions for reinforcing and renewing existing water distribution networks, considering uncertain future working conditions. Criteria related to financial, environmental and pipe failure assessment are proposed to evaluate alternative solutions and to identify the best-placed options to implement. The alternatives are obtained for a phased design scheme that enables midcourse corrections through changes in the network layout. The proposed framework has been demonstrated using a case study based on a water distribution network from the literature.

A study on appropriate investment of pipeline rehabilitation for water distribution network

2005 ◽  
Vol 5 (2) ◽  
pp. 31-38
Author(s):  
A. Asakura ◽  
A. Koizumi ◽  
O. Odanagi ◽  
H. Watanabe ◽  
T. Inakazu
Keyword(s):  
Monte Carlo Simulation ◽  
Monte Carlo ◽  
Water Supply ◽  
Water Distribution ◽  
Ad Hoc ◽  
Distribution Network ◽  
Water Distribution Network ◽  
Distribution Networks ◽  
Optimal Basis ◽  
Model Case

In Japan most of the water distribution networks were constructed during the 1960s to 1970s. Since these pipelines were used for a long period, pipeline rehabilitation is necessary to maintain water supply. Although investment for pipeline rehabilitation has to be planned in terms of cost-effectiveness, no standard method has been established because pipelines were replaced on emergency and ad hoc basis in the past. In this paper, a method to determine the maintenance of the water supply on an optimal basis with a fixed budget for a water distribution network is proposed. Firstly, a method to quantify the benefits of pipeline rehabilitation is examined. Secondly, two models using Integer Programming and Monte Carlo simulation to maximize the benefits of pipeline rehabilitation with limited budget were considered, and they are applied to a model case and a case study. Based on these studies, it is concluded that the Monte Carlo simulation model to calculate the appropriate investment for the pipeline rehabilitation planning is both convenient and practical.

scholarly journals Optimal placement of valves in a water distribution network with CLP(FD)

2011 ◽  
Vol 11 (4-5) ◽  
pp. 731-747 ◽  
Author(s):  
MASSIMILIANO CATTAFI ◽  
MARCO GAVANELLI ◽  
MADDALENA NONATO ◽  
STEFANO ALVISI ◽  
MARCO FRANCHINI
Keyword(s):  
Logic Programming ◽  
Distribution Systems ◽  
Water Distribution ◽  
Distribution Network ◽  
Real Life ◽  
Water Distribution Network ◽  
Distribution Networks ◽  
Constraint Logic Programming ◽  
Optimal Placement ◽  
Isolation System

AbstractThis paper presents a new application of logic programming to a real-life problem in hydraulic engineering. The work is developed as a collaboration of computer scientists and hydraulic engineers, and applies Constraint Logic Programming to solve a hard combinatorial problem. This application deals with one aspect of the design of a water distribution network, i.e., the valve isolation system design. We take the formulation of the problem by Giustolisi and Savić (2008 Optimal design of isolation valve system for water distribution networks. InProceedings of the 10th Annual Water Distribution Systems Analysis Conference WDSA2008, J. Van Zyl, A. Ilemobade, and H. Jacobs, Eds.) and show how, thanks to constraint propagation, we can get better solutions than the best solution known in the literature for the Apulian distribution network. We believe that the area of the so-calledhydroinformaticscan benefit from the techniques developed in Constraint Logic Programming and possibly from other areas of logic programming, such as Answer Set Programming.

scholarly journals Technical note: Problem specific variators in a genetic algorithm for the optimization of drinking water networks

2018 ◽  
Author(s):  
Karel van Laarhoven ◽  
Ina Vertommen ◽  
Peter van Thienen
Keyword(s):  
Drinking Water ◽  
Real World ◽  
Water Distribution ◽  
Water Distribution Network ◽  
Distribution Networks ◽  
Technical Note ◽  
Practical Implementation ◽  
Utility Level ◽  
Water Utility ◽  
Drinking Water Distribution

Abstract. Genetic algorithms can be a powerful tool for the automated design of optimal drinking water distribution networks. Fast convergence of such algorithms is a crucial factor for successful practical implementation at the drinking water utility level. In this technical note, we therefore investigate the performance of a suite of genetic variators that was tailored to the optimisation of a least-cost network design. Different combinations of the variators are tested in terms of convergence rate and the robustness of the results during optimisation of the real world drinking water distribution network of Sittard, the Netherlands. The variator configurations that reproducibly reach the furthest convergence after 105 function evaluations are reported. In the future these may aid in dealing with the computational challenges of optimizing real world networks.

scholarly journals Proposal of optimal operation strategy applied to water distribution network with statistical approach

2020 ◽  
Vol 15 (2) ◽  
pp. 1
Author(s):  
Alex Takeo Yasumura Lima Silva ◽  
Fernando Das Graças Braga da Silva ◽  
André Carlos da Silva ◽  
José Antonio Tosta dos Reis ◽  
Claudio Lindemberg de Freitas ◽  
...  
Keyword(s):  
Genetic Algorithms ◽  
Water Distribution ◽  
Distribution Network ◽  
Water Distribution Network ◽  
Distribution Networks ◽  
Optimal Operation ◽  
Optimization Techniques ◽  
Experimental Techniques ◽  
Computational Optimization ◽  
Depth Analysis

 Inefficiency of sanitation companies’ operation procedures threatens the population’s future supplies. Thus, it is essential to increase water and energy efficiency in order to meet future demand. Optimization techniques are important tools for the analysis of complex problems, as in distribution networks for supply. Currently, genetic algorithms are recognized by their application in literature. In this regard, an optimization model of water distribution network is proposed, using genetic algorithms. The difference in this research is a methodology based on in-depth analysis of results, using statistics and the design of experimental tools and software. The proposed technique was applied to a theoretical network developed for the study. Preliminary simulations were accomplished using EPANET, representing the main causes of water and energy inefficiency in Brazilian sanitation companies. Some parameters were changed in applying this model, such as reservoir level, pipe diameter, pumping pressures, and valve-closing percentage. These values were established by the design of experimental techniques. As output, we obtained the equation of response surface, optimized, which resulted in values of established hydraulic parameters. From these data, the obtained parameters in computational optimization algorithms were applied, resulting in losses of 26.61%, improvement of 16.19 p.p. with regard to the network without optimization, establishing an operational strategy involving three pumps and a pressure-reducing valve.  We conclude that the association of optimization and the planning of experimental techniques constitutes an encouraging method to deal with the complexity of water-distribution network optimization.

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.

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