scholarly journals The importance of the minimum path criterion in the design of water distribution networks

2017 ◽  
Vol 17 (6) ◽  
pp. 1558-1567 ◽  
Author(s):  
Carlo Ciaponi ◽  
Enrico Creaco ◽  
Luigi Franchioli ◽  
Sergio Papiri

Abstract This paper explores the relationship between the minimum cost design of water distribution networks (WDNs) and the minimum water path criterion (MWPC), according to which the water entering the network through the source nodes should cover the shortest possible paths before being delivered to users. To this end, a three-step linear algorithm for WDN design based on the MWPC and set up in the 1980s was applied to many benchmark case studies. The results of the linear three-step algorithm were almost coincident with, and in some cases superior to, those produced by more complex and burdensome algorithms. This represents a solid proof of the strong implications of the MWPC for WDN design.

2017 ◽  
Vol 18 (2) ◽  
pp. 660-678 ◽  
Author(s):  
Douglas F. Surco ◽  
Thelma P. B. Vecchi ◽  
Mauro A. S. S. Ravagnani

Abstract In the present work, a model is presented for the optimization of water distribution networks (WDN). The developed model can be used to verify node pressures, head losses, and fluid flow rate and velocity in each pipe. The algorithm is based on particle swarm optimization (PSO), considering real and discrete variables and avoiding premature convergence to local optima using objective function penalization. The model yields the minimum cost of the network, the node pressures and the velocities in the pipes. The pressures and velocities are calculated using the hydraulic simulator Epanet. Some benchmark problems are used to test the applicability of the developed model, considering WDN for small-, medium-, and large-scale problems. Obtained results are consistent with those found in the literature.


Water ◽  
2020 ◽  
Vol 12 (4) ◽  
pp. 1037 ◽  
Author(s):  
Juan Saldarriaga ◽  
Diego Páez ◽  
Camilo Salcedo ◽  
Paula Cuero ◽  
Laura Lunita López ◽  
...  

In recent years, iterative computational techniques have been considered as the most effective methods to tackle the problem of Water Distribution System (WDS) minimum-cost design. Given their stochastic nature, these approaches involve a large number of hydraulic simulations in order to obtain suitable results. Herein, a WDS design methodology based entirely on hydraulic principles is presented. This methodology, named Optimal Power Use Surface (OPUS), focuses on both reaching low-cost designs and diminishing the number of hydraulic executions (iterations), by establishing efficient ways in which energy is dissipated and flow is distributed throughout the system. The algorithm was tested in four well known benchmark networks, previously reported in the literature. OPUS proved that following hydraulic principles is a fair choice to design WDS, showing plenty of potential in other water distribution mathematical modeling applications and offering an alternative for the extensive search process undertaken by metaheuristics.


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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