Abstract
Water Distribution Networks (WDNs) can be regarded as complex networks and modeled as graphs. In this paper, Complex Network Theory is applied to characterize the behavior of WDNs from a topological point of view, reviewing some basic metrics, exploring their fundamental properties and the relationship between them. The crucial aim is to understand and describe the topology of WDNs and their structural organization to provide a novel tool of analysis which could help to find new solutions to several arduous problems of WDNs. The aim is to understand the role of the topological structure in the WDNs functioning. The methodology is applied to 21 existing networks and 13 literature networks. The comparison highlights some topological peculiarities and the possibility to define a set of best design parameters for ex-novo WDNs that could also be used to build hypothetical benchmark networks retaining the typical structure of real WDNs. Two well-known types of network ((a) square grid; and (b) random graph) are used for comparison, aiming at defining a possible mathematical model for WDNs. Finally, the interplay between topology and some performance requirements of WDNs is discussed.
Highlights
Biological and chemical systems, brain neural networks, social interacting species, the Internet and the World Wide Web, and the multiple and interconnected infrastructures that provide several services to consumers in the cities are network shaped [1,2]
Since the number of loops can be regarded as a robustness metric, clearly the link density can be used as a surrogate metric for the robustness of Water Distribution Networks (WDNs)
The topological analysis of several real and synthetic water distribution networks shows that such networks tend to be sparse, being characterized by small values of the average degree K and of the link density q ∼ n−1
Summary
Biological and chemical systems, brain neural networks, social interacting species, the Internet and the World Wide Web, and the multiple and interconnected infrastructures that provide several services to consumers in the cities are network shaped [1,2] It seems that the efficiency of the systems largely depends on their ability to create (if they are natural) or to have (in the case of man-made structures) multiple links between the units. It makes it difficult to understand the principles of their functioning and behavior In this regard, a suitable approach to capture the local and the global properties of network systems is to model them as graphs, where the nodes represent the units, and the links stand for the interactions between them. Two important papers [4,5] established
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