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dc.contributor.author
E Silva Machado, Rayner Mauricio
dc.contributor.author
Bre, Facundo
dc.contributor.author
Melo, Ana Paula
dc.contributor.author
Lamberts, Roberto
dc.date.available
2024-09-11T10:23:10Z
dc.date.issued
2024-04
dc.identifier.citation
E Silva Machado, Rayner Mauricio; Bre, Facundo; Melo, Ana Paula; Lamberts, Roberto; Bioclimatic zoning for building performance using tailored clustering method and high-resolution climate data; Elsevier Science SA; Energy and Buildings; 311; 4-2024; 1-21
dc.identifier.issn
0378-7788
dc.identifier.uri
http://hdl.handle.net/11336/244028
dc.description.abstract
Building environments are specific and complex bioclimatic systems. Thus, well-suited climate classification methods for buildings are essentially needed to develop building design guidelines and standards. To address it, the present research introduces a novel fit-for-purpose clustering method for bioclimatic zoning based on the hygrothermal and energy performance of buildings. This bioclimatic zoning was developed to update the Brazilian standard and has been validated across various climates and building typologies (residential and commercial) in Brazil. In a preliminary analysis, three classification methods were developed using K-means and Decision Tree to classify climates according to building performance. Subsequently, a final bioclimatic zoning method was developed using a tailored version of the best method designed for real-world applications (Decision Tree) in the Brazilian context. The performance of the bioclimatic zoning achieved was compared with three existing climate classifications: Köppen-Geiger, ASHRAE 169-2020, and ABNT-NBR 15220-3 (Brazilian Standard). The results showed that the new bioclimatic zoning method outperformed the existing ones to cluster the building performance indicators. Moreover, high-resolution spatial climate databases, such as NASA-POWER, CRU, and ERA5-Land, were processed and analyzed to be employed in locations without properly measured data. Three metamodels of climate indicators were developed and compared with these databases to select the most accurate climate data sources. Finally, these databases were employed to classify all 5570 Brazilian municipalities according to the final bioclimatic zoning, which enabled the development of an accurate and high-resolution map.
dc.format
application/pdf
dc.language.iso
eng
dc.publisher
Elsevier Science SA
dc.rights
info:eu-repo/semantics/restrictedAccess
dc.rights.uri
https://creativecommons.org/licenses/by-nc-sa/2.5/ar/
dc.subject
Climatic zoning
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Clustering analysis
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Metamodel
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Building performance
dc.subject.classification
Ingeniería Civil
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Ingeniería Civil
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INGENIERÍAS Y TECNOLOGÍAS
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Investigación Climatológica
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Ciencias de la Tierra y relacionadas con el Medio Ambiente
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CIENCIAS NATURALES Y EXACTAS
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Ingeniería Mecánica
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Ingeniería Mecánica
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INGENIERÍAS Y TECNOLOGÍAS
dc.title
Bioclimatic zoning for building performance using tailored clustering method and high-resolution climate data
dc.type
info:eu-repo/semantics/article
dc.type
info:ar-repo/semantics/artículo
dc.type
info:eu-repo/semantics/publishedVersion
dc.date.updated
2024-09-10T12:56:36Z
dc.journal.volume
311
dc.journal.pagination
1-21
dc.journal.pais
Países Bajos
dc.journal.ciudad
Amsterdam
dc.description.fil
Fil: E Silva Machado, Rayner Mauricio. Universidade Federal de Santa Catarina; Brasil
dc.description.fil
Fil: Bre, Facundo. Universitat Technische Darmstadt; Alemania. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Santa Fe. Centro de Investigaciones en Métodos Computacionales. Universidad Nacional del Litoral. Centro de Investigaciones en Métodos Computacionales; Argentina
dc.description.fil
Fil: Melo, Ana Paula. Universidade Federal de Santa Catarina; Brasil
dc.description.fil
Fil: Lamberts, Roberto. Universidade Federal de Santa Catarina; Brasil
dc.journal.title
Energy and Buildings
dc.relation.alternativeid
info:eu-repo/semantics/altIdentifier/url/https://www.sciencedirect.com/science/article/pii/S0378778824002731
dc.relation.alternativeid
info:eu-repo/semantics/altIdentifier/doi/http://dx.doi.org/10.1016/j.enbuild.2024.114157
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