Loading…
Two different approaches for monitoring planning in sewer networks: topological vs. deterministic optimization
Monitoring of sewer networks (SNs) is an important task whose planning can be related to various purposes, for example contaminant detection and epidemiological studies. This paper proposes two different approaches for the identification of a monitoring system in SNs. The first one proposes the iden...
Saved in:
Published in: | Journal of hydroinformatics 2023-11, Vol.25 (6), p.2323-2337 |
---|---|
Main Authors: | , , , , |
Format: | Article |
Language: | English |
Subjects: | |
Citations: | Items that this one cites |
Online Access: | Get full text |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Summary: | Monitoring of sewer networks (SNs) is an important task whose planning can be related to various purposes, for example contaminant detection and epidemiological studies. This paper proposes two different approaches for the identification of a monitoring system in SNs. The first one proposes the identification of the best monitoring points starting from the knowledge of the hydraulic behavior of the system with respect to specific sensor threshold values through an optimization procedure that maximizes the reliability in detecting a contaminant. A new mathematical model is developed and a global optimization solver is employed to perform the optimization procedure. The second approach is based on the complex network theory (CNT) tools, adopting the in-relevance-based harmonic centrality, and does not require any hydraulic simulation. The metric is evaluated for each node of the network and provides a range of nodes, classified with respect to their importance, useful to identify suitable locations for sensors. With reference to both a benchmark and a real SN, the comparison between the results achieved by both strategies indicates that the two approaches provide comparable solutions in terms of sensor location. |
---|---|
ISSN: | 1464-7141 1465-1734 |
DOI: | 10.2166/hydro.2023.296 |