Mathematical models to assessment the energy performance of textured cladding for facades

Autores
Alchapar, Noelia Liliana; Correa Cantaloube, Erica Norma
Año de publicación
2022
Idioma
inglés
Tipo de recurso
artículo
Estado
versión publicada
Descripción
The temperature increase of a city in relation to its peripheral areas leads to the formation of an Urban Heat Island. Working on the opto-thermal properties of the building envelope is a viable mitigation strategy to reduce the temperatures of a city. Having quantitative data on energy performance allows the development of precise evaluations and the selection of the most efficient data in relation to energy consumption. The degree of efficiency of a material is calculated with an indicator called Solar Reflectance Index (SRI). Since opto-thermal properties change over time, the standard recommends obtaining the SRI level of both new and three-year-aged material (SRI3). In the present work, 80 facade claddings were evaluated to: (a) determine which qualitative variables significantly influence the SRI3 of the claddings; (b) obtain an equation that calculates the SRI3 without the need to monitor the large number of variables used for its calculation. For this, the following statistical methods were used: Multifactorial ANOVA and linear regression model. In this correlational analysis, color, composition and texture were selected as independent variables. The research showed that color is the variable that significantly influences SRI3 in all the evaluated claddings. By means of the equation obtained with the regression model, the SRI3 index was predicted reaching 95% IC. These results significantly save time and simplify the process of obtaining data since it is not necessary to monitor numerous input variables to calculate the indicator.
Fil: Alchapar, Noelia Liliana. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Regional de Investigaciones Cientifícas y Tecnológicas; Argentina
Fil: Correa Cantaloube, Erica Norma. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Regional de Investigaciones Cientifícas y Tecnológicas; Argentina
Materia
BUILDING MATERIALS
CORRELATIONAL MODEL
SOLAR REFLECTANCE INDEX
Nivel de accesibilidad
acceso abierto
Condiciones de uso
https://creativecommons.org/licenses/by-nc-sa/2.5/ar/
Repositorio
CONICET Digital (CONICET)
Institución
Consejo Nacional de Investigaciones Científicas y Técnicas
OAI Identificador
oai:ri.conicet.gov.ar:11336/196578
Acceder
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network_name_str CONICET Digital (CONICET)
spelling Mathematical models to assessment the energy performance of textured cladding for facadesAlchapar, Noelia LilianaCorrea Cantaloube, Erica NormaBUILDING MATERIALSCORRELATIONAL MODELSOLAR REFLECTANCE INDEXhttps://purl.org/becyt/ford/2.5https://purl.org/becyt/ford/2The temperature increase of a city in relation to its peripheral areas leads to the formation of an Urban Heat Island. Working on the opto-thermal properties of the building envelope is a viable mitigation strategy to reduce the temperatures of a city. Having quantitative data on energy performance allows the development of precise evaluations and the selection of the most efficient data in relation to energy consumption. The degree of efficiency of a material is calculated with an indicator called Solar Reflectance Index (SRI). Since opto-thermal properties change over time, the standard recommends obtaining the SRI level of both new and three-year-aged material (SRI3). In the present work, 80 facade claddings were evaluated to: (a) determine which qualitative variables significantly influence the SRI3 of the claddings; (b) obtain an equation that calculates the SRI3 without the need to monitor the large number of variables used for its calculation. For this, the following statistical methods were used: Multifactorial ANOVA and linear regression model. In this correlational analysis, color, composition and texture were selected as independent variables. The research showed that color is the variable that significantly influences SRI3 in all the evaluated claddings. By means of the equation obtained with the regression model, the SRI3 index was predicted reaching 95% IC. These results significantly save time and simplify the process of obtaining data since it is not necessary to monitor numerous input variables to calculate the indicator.Fil: Alchapar, Noelia Liliana. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Regional de Investigaciones Cientifícas y Tecnológicas; ArgentinaFil: Correa Cantaloube, Erica Norma. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Regional de Investigaciones Cientifícas y Tecnológicas; ArgentinaTamkang University2022-07info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionhttp://purl.org/coar/resource_type/c_6501info:ar-repo/semantics/articuloapplication/pdfapplication/pdfhttp://hdl.handle.net/11336/196578Alchapar, Noelia Liliana; Correa Cantaloube, Erica Norma; Mathematical models to assessment the energy performance of textured cladding for facades; Tamkang University; Journal of Applied Science and Engineering; 25; 1; 7-2022; 151-1582708-99672708-9975CONICET DigitalCONICETenginfo:eu-repo/semantics/altIdentifier/doi/10.6180/jase.202202_25(1).0015info:eu-repo/semantics/altIdentifier/url/http://jase.tku.edu.tw/articles/jase-202202-25-1-0015info:eu-repo/semantics/openAccesshttps://creativecommons.org/licenses/by-nc-sa/2.5/ar/reponame:CONICET Digital (CONICET)instname:Consejo Nacional de Investigaciones Científicas y Técnicas2025-09-17T10:44:25Zoai:ri.conicet.gov.ar:11336/196578instacron:CONICETInstitucionalhttp://ri.conicet.gov.ar/Organismo científico-tecnológicoNo correspondehttp://ri.conicet.gov.ar/oai/requestdasensio@conicet.gov.ar; lcarlino@conicet.gov.arArgentinaNo correspondeNo correspondeNo correspondeopendoar:34982025-09-17 10:44:25.877CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicasfalse
dc.title.none.fl_str_mv Mathematical models to assessment the energy performance of textured cladding for facades
title Mathematical models to assessment the energy performance of textured cladding for facades
spellingShingle Mathematical models to assessment the energy performance of textured cladding for facades
Alchapar, Noelia Liliana
BUILDING MATERIALS
CORRELATIONAL MODEL
SOLAR REFLECTANCE INDEX
title_short Mathematical models to assessment the energy performance of textured cladding for facades
title_full Mathematical models to assessment the energy performance of textured cladding for facades
title_fullStr Mathematical models to assessment the energy performance of textured cladding for facades
title_full_unstemmed Mathematical models to assessment the energy performance of textured cladding for facades
title_sort Mathematical models to assessment the energy performance of textured cladding for facades
dc.creator.none.fl_str_mv Alchapar, Noelia Liliana
Correa Cantaloube, Erica Norma
author Alchapar, Noelia Liliana
author_facet Alchapar, Noelia Liliana
Correa Cantaloube, Erica Norma
author_role author
author2 Correa Cantaloube, Erica Norma
author2_role author
dc.subject.none.fl_str_mv BUILDING MATERIALS
CORRELATIONAL MODEL
SOLAR REFLECTANCE INDEX
topic BUILDING MATERIALS
CORRELATIONAL MODEL
SOLAR REFLECTANCE INDEX
purl_subject.fl_str_mv https://purl.org/becyt/ford/2.5
https://purl.org/becyt/ford/2
dc.description.none.fl_txt_mv The temperature increase of a city in relation to its peripheral areas leads to the formation of an Urban Heat Island. Working on the opto-thermal properties of the building envelope is a viable mitigation strategy to reduce the temperatures of a city. Having quantitative data on energy performance allows the development of precise evaluations and the selection of the most efficient data in relation to energy consumption. The degree of efficiency of a material is calculated with an indicator called Solar Reflectance Index (SRI). Since opto-thermal properties change over time, the standard recommends obtaining the SRI level of both new and three-year-aged material (SRI3). In the present work, 80 facade claddings were evaluated to: (a) determine which qualitative variables significantly influence the SRI3 of the claddings; (b) obtain an equation that calculates the SRI3 without the need to monitor the large number of variables used for its calculation. For this, the following statistical methods were used: Multifactorial ANOVA and linear regression model. In this correlational analysis, color, composition and texture were selected as independent variables. The research showed that color is the variable that significantly influences SRI3 in all the evaluated claddings. By means of the equation obtained with the regression model, the SRI3 index was predicted reaching 95% IC. These results significantly save time and simplify the process of obtaining data since it is not necessary to monitor numerous input variables to calculate the indicator.
Fil: Alchapar, Noelia Liliana. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Regional de Investigaciones Cientifícas y Tecnológicas; Argentina
Fil: Correa Cantaloube, Erica Norma. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Regional de Investigaciones Cientifícas y Tecnológicas; Argentina
description The temperature increase of a city in relation to its peripheral areas leads to the formation of an Urban Heat Island. Working on the opto-thermal properties of the building envelope is a viable mitigation strategy to reduce the temperatures of a city. Having quantitative data on energy performance allows the development of precise evaluations and the selection of the most efficient data in relation to energy consumption. The degree of efficiency of a material is calculated with an indicator called Solar Reflectance Index (SRI). Since opto-thermal properties change over time, the standard recommends obtaining the SRI level of both new and three-year-aged material (SRI3). In the present work, 80 facade claddings were evaluated to: (a) determine which qualitative variables significantly influence the SRI3 of the claddings; (b) obtain an equation that calculates the SRI3 without the need to monitor the large number of variables used for its calculation. For this, the following statistical methods were used: Multifactorial ANOVA and linear regression model. In this correlational analysis, color, composition and texture were selected as independent variables. The research showed that color is the variable that significantly influences SRI3 in all the evaluated claddings. By means of the equation obtained with the regression model, the SRI3 index was predicted reaching 95% IC. These results significantly save time and simplify the process of obtaining data since it is not necessary to monitor numerous input variables to calculate the indicator.
publishDate 2022
dc.date.none.fl_str_mv 2022-07
dc.type.none.fl_str_mv info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
http://purl.org/coar/resource_type/c_6501
info:ar-repo/semantics/articulo
format article
status_str publishedVersion
dc.identifier.none.fl_str_mv http://hdl.handle.net/11336/196578
Alchapar, Noelia Liliana; Correa Cantaloube, Erica Norma; Mathematical models to assessment the energy performance of textured cladding for facades; Tamkang University; Journal of Applied Science and Engineering; 25; 1; 7-2022; 151-158
2708-9967
2708-9975
CONICET Digital
CONICET
url http://hdl.handle.net/11336/196578
identifier_str_mv Alchapar, Noelia Liliana; Correa Cantaloube, Erica Norma; Mathematical models to assessment the energy performance of textured cladding for facades; Tamkang University; Journal of Applied Science and Engineering; 25; 1; 7-2022; 151-158
2708-9967
2708-9975
CONICET Digital
CONICET
dc.language.none.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv info:eu-repo/semantics/altIdentifier/doi/10.6180/jase.202202_25(1).0015
info:eu-repo/semantics/altIdentifier/url/http://jase.tku.edu.tw/articles/jase-202202-25-1-0015
dc.rights.none.fl_str_mv info:eu-repo/semantics/openAccess
https://creativecommons.org/licenses/by-nc-sa/2.5/ar/
eu_rights_str_mv openAccess
rights_invalid_str_mv https://creativecommons.org/licenses/by-nc-sa/2.5/ar/
dc.format.none.fl_str_mv application/pdf
application/pdf
dc.publisher.none.fl_str_mv Tamkang University
publisher.none.fl_str_mv Tamkang University
dc.source.none.fl_str_mv reponame:CONICET Digital (CONICET)
instname:Consejo Nacional de Investigaciones Científicas y Técnicas
reponame_str CONICET Digital (CONICET)
collection CONICET Digital (CONICET)
instname_str Consejo Nacional de Investigaciones Científicas y Técnicas
repository.name.fl_str_mv CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicas
repository.mail.fl_str_mv dasensio@conicet.gov.ar; lcarlino@conicet.gov.ar
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score 13.001348

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