Bioclimatic zoning for building performance using tailored clustering method and high-resolution climate data

被引:1
|
作者
Machado, Rayner Mauricio e Silva [1 ]
Bre, Facundo [2 ,3 ]
Mazzaferro, Leonardo [1 ]
Melo, Ana Paula [1 ]
Lamberts, Roberto [1 ]
机构
[1] Fed Univ Santa Catarina UFSC, Dept Civil Engn, Lab Energy Efficiency Bldg LabEEE, Florianopolis, Brazil
[2] Tech Univ Darmstadt, Inst Construct & Bldg Mat, D-64287 Darmstadt, Germany
[3] UNL, CONICET, Ctr Invest Metodos Computac CIMEC, Predio Dr Alberto Cassano, Colectora Ruta Nacl 168, RA-3000 Santa Fe, Argentina
关键词
Climatic zoning; Clustering analysis; Metamodel; Building performance; CLASSIFICATION; VALIDATION; MAP;
D O I
10.1016/j.enbuild.2024.114157
中图分类号
TU [建筑科学];
学科分类号
0813 ;
摘要
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: K & ouml;ppen-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.
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页数:21
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