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Effective optimization of irrigation networks with pressure-driven outflows at randomly selected installation nodes
This paper presents an innovative methodology for the design of pressurized irrigation networks. Compared to other methodologies proposed in the scientific literature, it features three novel aspects: (i) construction of peak demand scenarios based on the random selection of installation nodes for h...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10628099/ https://www.ncbi.nlm.nih.gov/pubmed/37932363 http://dx.doi.org/10.1038/s41598-023-45844-3 |
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author | Creaco, E. Barbero, G. Montanaro, A. Reduzzi, M. |
author_facet | Creaco, E. Barbero, G. Montanaro, A. Reduzzi, M. |
author_sort | Creaco, E. |
collection | PubMed |
description | This paper presents an innovative methodology for the design of pressurized irrigation networks. Compared to other methodologies proposed in the scientific literature, it features three novel aspects: (i) construction of peak demand scenarios based on the random selection of installation nodes for hydrant heads available in each sector of irrigated properties; (ii) realistic hydraulic modelling of outflows from hydrant heads by means of the pressure driven approach; and (iii) adoption of linear constraints to enforce the telescopic property in the distribution of diameters from the source towards the external areas of the network in the optimized design. The applications of the methodology to the real network serving an irrigated area of 750 ha in Northern Italy proved that the aspects (i) and (ii) contribute to the accurate modelling of the current network while highlighting its hydraulic deficiencies. The adoption of the linear constraints described in (iii) in the context of the bi-objective genetic optimization of network diameters resulted in the speeding up of the algorithm convergence. The results show how decision makers can choose the ultimate configuration based on budget considerations from the trade-off solutions obtained between installation costs and hydraulic performance, considering network layouts with different level of topological redundancy. |
format | Online Article Text |
id | pubmed-10628099 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-106280992023-11-08 Effective optimization of irrigation networks with pressure-driven outflows at randomly selected installation nodes Creaco, E. Barbero, G. Montanaro, A. Reduzzi, M. Sci Rep Article This paper presents an innovative methodology for the design of pressurized irrigation networks. Compared to other methodologies proposed in the scientific literature, it features three novel aspects: (i) construction of peak demand scenarios based on the random selection of installation nodes for hydrant heads available in each sector of irrigated properties; (ii) realistic hydraulic modelling of outflows from hydrant heads by means of the pressure driven approach; and (iii) adoption of linear constraints to enforce the telescopic property in the distribution of diameters from the source towards the external areas of the network in the optimized design. The applications of the methodology to the real network serving an irrigated area of 750 ha in Northern Italy proved that the aspects (i) and (ii) contribute to the accurate modelling of the current network while highlighting its hydraulic deficiencies. The adoption of the linear constraints described in (iii) in the context of the bi-objective genetic optimization of network diameters resulted in the speeding up of the algorithm convergence. The results show how decision makers can choose the ultimate configuration based on budget considerations from the trade-off solutions obtained between installation costs and hydraulic performance, considering network layouts with different level of topological redundancy. Nature Publishing Group UK 2023-11-06 /pmc/articles/PMC10628099/ /pubmed/37932363 http://dx.doi.org/10.1038/s41598-023-45844-3 Text en © The Author(s) 2023 https://creativecommons.org/licenses/by/4.0/Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . |
spellingShingle | Article Creaco, E. Barbero, G. Montanaro, A. Reduzzi, M. Effective optimization of irrigation networks with pressure-driven outflows at randomly selected installation nodes |
title | Effective optimization of irrigation networks with pressure-driven outflows at randomly selected installation nodes |
title_full | Effective optimization of irrigation networks with pressure-driven outflows at randomly selected installation nodes |
title_fullStr | Effective optimization of irrigation networks with pressure-driven outflows at randomly selected installation nodes |
title_full_unstemmed | Effective optimization of irrigation networks with pressure-driven outflows at randomly selected installation nodes |
title_short | Effective optimization of irrigation networks with pressure-driven outflows at randomly selected installation nodes |
title_sort | effective optimization of irrigation networks with pressure-driven outflows at randomly selected installation nodes |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10628099/ https://www.ncbi.nlm.nih.gov/pubmed/37932363 http://dx.doi.org/10.1038/s41598-023-45844-3 |
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