Modeling the Mixing Phenomenon in Water Distribution Networks: A State-of-the-Art Review

Author(s):  
Reza Yousefian ◽  
Sophie Duchesne
2021 ◽  
Vol 10 (12) ◽  
pp. e407101220659
Author(s):  
Emerson Pessanha de Almeida ◽  
Fernando das Graças Braga da Silva ◽  
Victor Eduardo de Mello Valerio

The research carried out in the water distribution networks is of great importance, given the social, environmental and economic impacts that have occurred due to the scarcity of water resources. Therefore, any scientific effort shown in research that studies water distribution systems is of great relevance. Techniques such as mathematical modeling, computer simulation and statistical methods are widely used in order to obtain more reliable answers, whether for the identification of the current situation of the network, as well as for the prediction of scenarios, failure events, increased demand, etc. The objective of this work is to carry out a bibliometric analysis to identify the state of the art of research that addresses the theme of water distribution networks for the control and reduction of the volume of water losses, which will serve as a guide for future works to to structure itself in the most relevant researches that study the theme. The developed methodology was able to analyze a metadata composed of 4188 documents taken from the Web of Science journals database. As a result, a geographical view of the theme was obtained, pointing out the main countries, affiliations, journals and researchers, as well as pointing out the main documents and relevance of the theme. It can be concluded after the results obtained that bibliometric analysis is an important tool for obtaining the state of the art. With it is possible to have a better understanding of the current situation in the development of research, familiarizing researchers with what is most current and relevant.


2019 ◽  
Vol 161 ◽  
pp. 517-530 ◽  
Author(s):  
E. Creaco ◽  
A. Campisano ◽  
N. Fontana ◽  
G. Marini ◽  
P.R. Page ◽  
...  

2013 ◽  
Vol 316-317 ◽  
pp. 758-761
Author(s):  
Shi Ze Zhang ◽  
Yi Xing Yuan ◽  
Pei Ming Li

Genetic algorithms (GA) are currently one of the state-of-the-art techniques for the optimization of engineering systems including water distribution networks design and rehabilitation. They are capable of finding near optimal cost solutions to these problems when certain cost and hydraulic parameters are given. Since many forms of GAs rely on random starting points, that is to say, the poor solutions, it has become an ongoing research topic how to efficiently provide good initial estimates of solution sets automatically. A novel method is proposed in this paper, known as two-step optimization, which uses a heuristic-based, Dijkstra arithmetic to optimize network topology to obtain the layout of main pipes. The first step provides a good pattern for subsequent GA runs. Two-step optimization is applied to a network.. The result shows that the proposed approach consistently outperforms the traditional design and the conventional non-heuristic-based GA approach in terms of convergence and calculation efficiency.


2020 ◽  
Vol 53 (2) ◽  
pp. 16697-16702
Author(s):  
I. Santos-Ruiz ◽  
J. Blesa ◽  
V. Puig ◽  
F.R. López-Estrada

2020 ◽  
Vol 13 (1) ◽  
pp. 31
Author(s):  
Enrico Creaco ◽  
Giacomo Galuppini ◽  
Alberto Campisano ◽  
Marco Franchini

This paper presents a two-step methodology for the stochastic generation of snapshot peak demand scenarios in water distribution networks (WDNs), each of which is based on a single combination of demand values at WDN nodes. The methodology describes the hourly demand at both nodal and WDN scales through a beta probabilistic model, which is flexible enough to suit both small and large demand aggregations in terms of mean, standard deviation, and skewness. The first step of the methodology enables generating separately the peak demand samples at WDN nodes. Then, in the second step, the nodal demand samples are consistently reordered to build snapshot demand scenarios for the WDN, while respecting the rank cross-correlations at lag 0. The applications concerned the one-year long dataset of about 1000 user demand values from the district of Soccavo, Naples (Italy). Best-fit scaling equations were constructed to express the main statistics of peak demand as a function of the average demand value on a long-time horizon, i.e., one year. The results of applications to four case studies proved the methodology effective and robust for various numbers and sizes of users.


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