Fractal-Heuristic Method of Water Quality Sensor Locations in Water Supply Network
Artykuł w czasopiśmie
MNiSW
100
Lista 2021
| Status: | |
| Autorzy: | Kowalska Beata, Kowalski Dariusz, Hołota Ewa |
| Dyscypliny: | |
| Aby zobaczyć szczegóły należy się zalogować. | |
| Rok wydania: | 2020 |
| Wersja dokumentu: | Elektroniczna |
| Język: | angielski |
| Numer czasopisma: | 3 |
| Wolumen/Tom: | 12 |
| Numer artykułu: | 832 |
| Strony: | 1 - 15 |
| Web of Science® Times Cited: | 5 |
| Scopus® Cytowania: | 7 |
| Bazy: | Web of Science | Scopus |
| Efekt badań statutowych | NIE |
| Finansowanie: | This research was funded by the Statutory Activity of Lublin University of Technology. |
| Materiał konferencyjny: | NIE |
| Publikacja OA: | TAK |
| Licencja: | |
| Sposób udostępnienia: | Otwarte czasopismo |
| Wersja tekstu: | Ostateczna wersja opublikowana |
| Czas opublikowania: | W momencie opublikowania |
| Data opublikowania w OA: | 16 marca 2020 |
| Abstrakty: | angielski |
| The article presents a new methodology for the selection of the water quality monitoring sensor locations using the water quality model created by means of the EPANET 2.0 software (United States Environmental Protection Agency (USEPA), Durham, NC, USA). The model represents the propagation of free chlorine in a water supply network, in conjunction with the heuristic method, applying the elements of fractal geometry. In the first stage, a subarea is determined, while in the second, a specific node for the location of the measuring point is indicated. The process of determining the location is based on a ranking method, in which the usefulness of individual subareas and measuring nodes is determined by means of a formula taking into account the amount of water intake, the required level of water supply and the effects of a lack of water supply, as well as the calculated concentration of free chlorine. The application of the method requires the construction and calibration of a numerical model of free chlorine decay in the network, as well as the knowledge on the location of the objects of particular importance for the network users. The proposed method will be applied in an existing water supply network of approximately 50,000 recipients. |
