Antonietta Simone

Optimal Design of District Metering Areas for the Reduction of Leakages

AbstractThe division of water distribution networks (WDNs) into district metering areas (DMAs) is a challenging issue and can be effective for analysis, planning, and management purposes. This cont...

A proposal of optimal sampling design using a modularity strategy

In real water distribution networks (WDNs) are present thousands nodes and optimal placement of pressure and flow observations is a relevant issue for different management tasks. The planning of pressure observations in terms of spatial distribution and number is named sampling design and it was faced considering model calibration. Nowadays, the design of system monitoring is a relevant issue for water utilities e.g. in order to manage background leakages, to detect anomalies and bursts, to guarantee service quality, etc. In recent years, the optimal location of flow observations related to design of optimal district metering areas (DMAs) and leakage management purposes has been faced considering optimal network segmentation and the modularity index using a multi-objective strategy. Optimal network segmentation is the basis to identify network modules by means of optimal conceptual cuts, which are the candidate locations of closed gates or flow meters creating the DMAs. Starting from the WDN-oriented modularity index, as a metric for WDN segmentation, this paper proposes a new way to perform the sampling design, i.e. the optimal location of pressure meters, using newly developed sampling-oriented modularity index. The strategy optimizes the pressure monitoring system mainly based on network topology and weights assigned to pipes according to the specific technical tasks. A multi-objective optimization minimizes the cost of pressure meters while maximizing the sampling-oriented modularity index. The methodology is presented and discussed using the Apulian and Exnet networks. This article is protected by copyright. All rights reserved.

Network structure classification and features of water distribution systems

The network connectivity structure of water distribution systems (WDSs) represents the domain where hydraulic processes occur, driving the emerging behavior of such systems, for example with respect to robustness and vulnerability. In complex network theory (CNT), a common way of classifying the network structure and connectivity is the association of the nodal degree distribution to specific probability distribution models; and during the last decades, researchers classified many real networks using the Poisson or Pareto distributions. In spite of the fact that degree-based network classification could play a crucial role to assess WDS vulnerability, this task is not easy because the network structure of WDSs is strongly constrained by spatial characteristics of the environment where they are constructed. The consequence of these spatial constraints is that the nodal degree spans very small ranges in WDSs hindering a reliable classification by the standard approach based on the nodal degree distribution. This work investigates the classification of the network structure of twenty-two real WDSs, built in different environments, demonstrating that the Poisson distribution generally models the degree distributions very well. In order to overcome the problem of the reliable classification based on the standard nodal degree, we define the “neighborhood” degree, equal to the sum of the nodal degrees of the nearest topological neighbors (i.e., the adjacent nodes). This definition of “neighborhood” degree is consistent with the fact that the degree of a single node is not significant for analysis of WDSs. This article is protected by copyright. All rights reserved.

Modularity Index for Optimal Sensor Placement in WDNs

The division of water distribution networks (WDNs) in districts/modules for optimal placement of flow/pressure observations is a relevant issue for different management tasks. In fact, the division of hydraulic systems in districts allows simplifying technical tasks related to analysis and planning activities. Starting from the modularity index, i.e., the most used metric to measure the propensity of the network to be divided into modules, the optimal monitoring design proposes scenarios of optimal placement of flow and pressure meters. This way, each module results bounded by a subset of observations, guarantying the information about flow (i.e., mass balance) and pressure (i.e., energy balance) at the boundary cuts/nodes of each district of the network. Starting from the infrastructure segmentation-oriented modularity index as metric for WDN segmentation and the infrastructure sampling-oriented modularity index as metric for the sampling design, an integrated planning strategy for WDNs monitoring is here proposed, in order to increase service reliability and quality. The strategy is based on a multi-objective optimization that minimizes the number of devices, flow or pressure meters, and maximizes a specific tailoring modularity index, for segmentation and sampling design, respectively. The strategy allows dividing the network into integrated district and pressure monitoring areas, and flexibility is implemented by searching for nested districts.

Estimating Leakages in Water Distribution Networks Based Only on Inlet Flow Data

AbstractThe estimate of current real losses in water distribution networks (WDN) is crucial to plan investments for rehabilitation, assess the rise of leakage over time, and possibly drive procedur...