Author(s): Antonietta Simone; Gabriele Freni; Mariacrocetta Sambito

Linked Author(s): Mariacrocetta Sambito, Gabriele Freni

Keywords: Sewer networks monitoring; Dominant nodes; Backtracking algorithm; Complex network theory; Harmonic centrality

Abstract: The need to define computationally advantageous sampling designs that allow the localization of contamination sources, the monitoring of contaminants and the definition of intervention priorities for sewer networks is increasingly pressing. To manage such a situation, it is essential to understand and model the dilution and dispersion phenomena of such substances within the system by considering their connective structure. In this regard, the present work proposes a two-step strategy aimed at identifying the nodes within sewer networks which deserves more attention, in particular for monitoring purposes. The first step evaluates the impact that the release of contaminants in each node has on the entire network using the deep-first search method algorithm. The analysis allows us to identify the nodes that dominate the diffusion process of the contaminant, i.e., those nodes which, once contaminated, can propagate the substance significantly due to their topological characteristics. The information is catalogued in a network contamination map to be used in the subsequent topological analysis step, where the dominance of each node is set as their own intrinsic relevance. The relevance-based in-Harmonic centrality is used as metric to define a ranking of importance of the network nodes, thus identifying the points/paths that deserve greater attention in the processes of contamination, and which could result most suitable for hosting monitoring sensors. To validate the performance of the strategy, it is applied to a small benchmark sewer system.

DOI: https://doi.org/10.64697/HIC2024_P369

Year: 2024