A rainwater control optimization design approach for airports based on a self-organizing feature map neural network model
To address the problems of high overflow rate of pipe network inspection well and low drainage efficiency, a rainwater control optimization design approach based on a self-organizing feature map neural network model (SOFM) was proposed in this paper. These problems are caused by low precision parame...
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| creator | Qiu, Dongwei Xu, Hao Luo, Dean Ye, Qing Li, Shaofu Wang, Tong Ding, Keliang |
| description | To address the problems of high overflow rate of pipe network inspection well and low drainage efficiency, a rainwater control optimization design approach based on a self-organizing feature map neural network model (SOFM) was proposed in this paper. These problems are caused by low precision parameter design in various rainwater control measures such as the diameter of the rainwater pipe network and the green roof area ratio. This system is to be combined with the newly built rainwater pipe control optimization design project of China International Airport in Daxing District of Beijing, China. Through the optimization adjustment of the pipe network parameters such as the diameter of the rainwater pipe network, the slope of the pipeline, and the green infrastructure (GI) parameters such as the sinking green area and the green roof area, reasonable control of airport rainfall and the construction of sustainable drainage systems can be achieved. This research indicates that compared with the result of the drainage design under the initial value of the parameter, the green roof model and the conceptual model of the mesoscale sustainable drainage system, in the case of a hundred-year torrential rainstorm, the overflow rate of pipe network inspection wells has reduced by 36% to 67.5%, the efficiency of drainage has increased by 26.3% to 61.7%, which achieves the requirements for reasonable control of airport rainwater and building a sponge airport and a sustainable drainage system. |
| doi_str_mv | 10.1371/journal.pone.0227901 |
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These problems are caused by low precision parameter design in various rainwater control measures such as the diameter of the rainwater pipe network and the green roof area ratio. This system is to be combined with the newly built rainwater pipe control optimization design project of China International Airport in Daxing District of Beijing, China. Through the optimization adjustment of the pipe network parameters such as the diameter of the rainwater pipe network, the slope of the pipeline, and the green infrastructure (GI) parameters such as the sinking green area and the green roof area, reasonable control of airport rainfall and the construction of sustainable drainage systems can be achieved. This research indicates that compared with the result of the drainage design under the initial value of the parameter, the green roof model and the conceptual model of the mesoscale sustainable drainage system, in the case of a hundred-year torrential rainstorm, the overflow rate of pipe network inspection wells has reduced by 36% to 67.5%, the efficiency of drainage has increased by 26.3% to 61.7%, which achieves the requirements for reasonable control of airport rainwater and building a sponge airport and a sustainable drainage system.</description><identifier>ISSN: 1932-6203</identifier><identifier>EISSN: 1932-6203</identifier><identifier>DOI: 10.1371/journal.pone.0227901</identifier><identifier>PMID: 31961903</identifier><language>eng</language><publisher>United States: Public Library of Science</publisher><subject>Airport construction ; Airports ; Analysis ; Artificial neural networks ; Beijing ; Biology and Life Sciences ; Civil engineering ; Computer and Information Sciences ; Construction ; Design optimization ; Design parameters ; Diameters ; Drainage control ; Drainage design ; Drainage systems ; Earth Sciences ; Efficiency ; Engineering and Technology ; Feature maps ; Floods ; Genetic algorithms ; Green buildings ; Green infrastructure ; Green roofs ; Informatics ; Infrastructure (Economics) ; Inspection ; Mathematical models ; Models, Theoretical ; Neural networks ; Neural Networks, Computer ; Nuclear energy ; Nuclear power plants ; Optimization ; Overflow ; Pipes ; Rain ; Rain water ; Rainfall ; Rainstorms ; Rainwater ; Research and Analysis Methods ; Runoff ; Stormwater ; Sustainability ; Sustainable design ; Water Movements</subject><ispartof>PloS one, 2020-01, Vol.15 (1), p.e0227901-e0227901</ispartof><rights>COPYRIGHT 2020 Public Library of Science</rights><rights>2020 Qiu et al. 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rainwater control optimization design approach for airports based on a self-organizing feature map neural network model</title><author>Qiu, Dongwei ; Xu, Hao ; Luo, Dean ; Ye, Qing ; Li, Shaofu ; Wang, Tong ; Ding, Keliang</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c692t-d27a134d8e8f81c9ceefa98c52acc15820335e923f6b68f5f065572d78e2ddd63</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2020</creationdate><topic>Airport construction</topic><topic>Airports</topic><topic>Analysis</topic><topic>Artificial neural networks</topic><topic>Beijing</topic><topic>Biology and Life Sciences</topic><topic>Civil engineering</topic><topic>Computer and Information Sciences</topic><topic>Construction</topic><topic>Design optimization</topic><topic>Design parameters</topic><topic>Diameters</topic><topic>Drainage control</topic><topic>Drainage design</topic><topic>Drainage systems</topic><topic>Earth 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neural network model (SOFM) was proposed in this paper. These problems are caused by low precision parameter design in various rainwater control measures such as the diameter of the rainwater pipe network and the green roof area ratio. This system is to be combined with the newly built rainwater pipe control optimization design project of China International Airport in Daxing District of Beijing, China. Through the optimization adjustment of the pipe network parameters such as the diameter of the rainwater pipe network, the slope of the pipeline, and the green infrastructure (GI) parameters such as the sinking green area and the green roof area, reasonable control of airport rainfall and the construction of sustainable drainage systems can be achieved. This research indicates that compared with the result of the drainage design under the initial value of the parameter, the green roof model and the conceptual model of the mesoscale sustainable drainage system, in the case of a hundred-year torrential rainstorm, the overflow rate of pipe network inspection wells has reduced by 36% to 67.5%, the efficiency of drainage has increased by 26.3% to 61.7%, which achieves the requirements for reasonable control of airport rainwater and building a sponge airport and a sustainable drainage system.</abstract><cop>United States</cop><pub>Public Library of Science</pub><pmid>31961903</pmid><doi>10.1371/journal.pone.0227901</doi><tpages>e0227901</tpages><orcidid>https://orcid.org/0000-0002-1665-7440</orcidid><orcidid>https://orcid.org/0000-0002-1313-7044</orcidid><orcidid>https://orcid.org/0000-0002-7431-3814</orcidid><orcidid>https://orcid.org/0000-0002-9825-2075</orcidid><orcidid>https://orcid.org/0000-0002-0633-2298</orcidid><orcidid>https://orcid.org/0000-0001-9981-3324</orcidid><oa>free_for_read</oa></addata></record> |
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| source | Public Library of Science (PLoS) Journals Open Access; MEDLINE; DOAJ Directory of Open Access Journals; EZB-FREE-00999 freely available EZB journals; PubMed Central; Free Full-Text Journals in Chemistry |
| subjects | Airport construction Airports Analysis Artificial neural networks Beijing Biology and Life Sciences Civil engineering Computer and Information Sciences Construction Design optimization Design parameters Diameters Drainage control Drainage design Drainage systems Earth Sciences Efficiency Engineering and Technology Feature maps Floods Genetic algorithms Green buildings Green infrastructure Green roofs Informatics Infrastructure (Economics) Inspection Mathematical models Models, Theoretical Neural networks Neural Networks, Computer Nuclear energy Nuclear power plants Optimization Overflow Pipes Rain Rain water Rainfall Rainstorms Rainwater Research and Analysis Methods Runoff Stormwater Sustainability Sustainable design Water Movements |
| title | A rainwater control optimization design approach for airports based on a self-organizing feature map neural network model |
| url | https://sfx.bib-bvb.de/sfx_tum?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2025-01-29T02%3A16%3A25IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-gale_plos_&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.genre=article&rft.atitle=A%20rainwater%20control%20optimization%20design%20approach%20for%20airports%20based%20on%20a%20self-organizing%20feature%20map%20neural%20network%20model&rft.jtitle=PloS%20one&rft.au=Qiu,%20Dongwei&rft.date=2020-01-21&rft.volume=15&rft.issue=1&rft.spage=e0227901&rft.epage=e0227901&rft.pages=e0227901-e0227901&rft.issn=1932-6203&rft.eissn=1932-6203&rft_id=info:doi/10.1371/journal.pone.0227901&rft_dat=%3Cgale_plos_%3EA611897783%3C/gale_plos_%3E%3Curl%3E%3C/url%3E&disable_directlink=true&sfx.directlink=off&sfx.report_link=0&rft_id=info:oai/&rft_pqid=2343022017&rft_id=info:pmid/31961903&rft_galeid=A611897783&rft_doaj_id=oai_doaj_org_article_7cc33abe3da04cb4a3c06d6098fa3e24&rfr_iscdi=true |