In the water distribution networks, a deliberate or accidental contamination causes loss of water quality; the implementation of a real-time sensor network is essential to promptly detect the event of contamination. To achieve the optimum positioning of the probes, to reduce the cost of the instrumentation and maintenance, and obtaining, at the same time, a reliable monitoring of the system, optimization techniques are widely applied. In the present study, a numerical optimisation approach was compared with the results of an experimental campaign. The optimization problem is formulated in accordance with literature stateof- the-art, using the genetic algorithm NSGA-II coupled with a hydraulic simulator. The results were tested and verified using a looped laboratory distribution network, equipped with a real-time monitoring water quality system, which allows to run contamination experiments in a controlled environment.
Stefania Piazza, Mariacrocetta Sambito, Roberto Feo, Gabriele Freni, Valeria Puleo (2017). Optimal positioning of water quality sensors in water distribution networks: comparison of numerical and experimental results. In Proocedings of the 15th International Computing & Control for the Water Industry Conference CCWI 2017 [10.15131/shef.data.5364499.v1].
Optimal positioning of water quality sensors in water distribution networks: comparison of numerical and experimental results
Valeria Puleo
2017-01-01
Abstract
In the water distribution networks, a deliberate or accidental contamination causes loss of water quality; the implementation of a real-time sensor network is essential to promptly detect the event of contamination. To achieve the optimum positioning of the probes, to reduce the cost of the instrumentation and maintenance, and obtaining, at the same time, a reliable monitoring of the system, optimization techniques are widely applied. In the present study, a numerical optimisation approach was compared with the results of an experimental campaign. The optimization problem is formulated in accordance with literature stateof- the-art, using the genetic algorithm NSGA-II coupled with a hydraulic simulator. The results were tested and verified using a looped laboratory distribution network, equipped with a real-time monitoring water quality system, which allows to run contamination experiments in a controlled environment.File | Dimensione | Formato | |
---|---|---|---|
24 - Piazza et al Figshare 2017.pdf
accesso aperto
Descrizione: Articolo principale
Tipologia:
Versione Editoriale
Dimensione
636.89 kB
Formato
Adobe PDF
|
636.89 kB | Adobe PDF | Visualizza/Apri |
I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.