Generative modeling integrated to energy efficiency: A study of institutional buildings form optimization

Decisions making in architectural design early stages have a significant impact on energy efficiency and internal performance of buildings. A design process that utilizes energy efficiency parameters in early stages can accelerate the creation process and adding value to the design, as well as contr...

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Päätekijät:	Barros, Natália Nakamura, Carlo, Joyce Correna
Aineistotyyppi:	Online
Kieli:	por
Julkaistu:	Unisinos 2017
Linkit:	https://revistas.unisinos.br/index.php/arquitetura/article/view/arq.2017.132.04
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id	oai:ojs.www.unisinos.br:article-7764
record_format	ojs
institution	Universidad de Vale do Rio dos Sinos (UNISINOS)
collection	OJS
language	por
format	Online
author	Barros, Natália Nakamura Carlo, Joyce Correna
spellingShingle	Barros, Natália Nakamura Carlo, Joyce Correna Generative modeling integrated to energy efficiency: A study of institutional buildings form optimization
author_facet	Barros, Natália Nakamura Carlo, Joyce Correna
author_sort	Barros, Natália Nakamura
title	Generative modeling integrated to energy efficiency: A study of institutional buildings form optimization
title_short	Generative modeling integrated to energy efficiency: A study of institutional buildings form optimization
title_full	Generative modeling integrated to energy efficiency: A study of institutional buildings form optimization
title_fullStr	Generative modeling integrated to energy efficiency: A study of institutional buildings form optimization
title_full_unstemmed	Generative modeling integrated to energy efficiency: A study of institutional buildings form optimization
title_sort	generative modeling integrated to energy efficiency: a study of institutional buildings form optimization
description	Decisions making in architectural design early stages have a significant impact on energy efficiency and internal performance of buildings. A design process that utilizes energy efficiency parameters in early stages can accelerate the creation process and adding value to the design, as well as contributing to user well-being and environment improving. The purpose is verify the potential integration generative modeling to energy efficiency, through the form optimization integrated to Inmetro PBE Edifica prescriptive method of envelope energetic performance. Therefore, an equation of RTQ-C Consumption Indicator for bioclimatic zone 3 applied to study of institutional buildings. Initial parallelepiped form was programming in Rhino / Grasshopper software. The variables was defined according to RTQ-C prescriptive method equation, such as building length, width and height, openings height, glasses solar factor and vertical shading angle. The genetic algorithm used to generate the best form to meet energy efficiency parameters. Other volumetric possibilities were studied, being these: horizontal multiplication, vertical multiplication with rotation and vertical multiplication of unique form. The forms obtained the efficiency level A from RTQ-C traditional method application, which proves a viability of proposed method. In this way, it is possible to perceive the potentialities of generative modeling integrated to energy efficiency, which can revolutionize the architect design.Keywords: generative modeling, RTQ-C, energy efficiency.
publisher	Unisinos
publishDate	2017
url	https://revistas.unisinos.br/index.php/arquitetura/article/view/arq.2017.132.04
work_keys_str_mv	AT barrosnatalianakamura generativemodelingintegratedtoenergyefficiencyastudyofinstitutionalbuildingsformoptimization AT carlojoycecorrena generativemodelingintegratedtoenergyefficiencyastudyofinstitutionalbuildingsformoptimization AT barrosnatalianakamura modelagemgenerativaintegradaaeficienciaenergeticaestudodaotimizacaodaformadeedificacoesinstitucionais AT carlojoycecorrena modelagemgenerativaintegradaaeficienciaenergeticaestudodaotimizacaodaformadeedificacoesinstitucionais
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spelling	oai:ojs.www.unisinos.br:article-77642021-08-30T19:09:21Z Generative modeling integrated to energy efficiency: A study of institutional buildings form optimization Modelagem generativa integrada à eficiência energética: estudo da otimização da forma de edificações institucionais Barros, Natália Nakamura Carlo, Joyce Correna Decisions making in architectural design early stages have a significant impact on energy efficiency and internal performance of buildings. A design process that utilizes energy efficiency parameters in early stages can accelerate the creation process and adding value to the design, as well as contributing to user well-being and environment improving. The purpose is verify the potential integration generative modeling to energy efficiency, through the form optimization integrated to Inmetro PBE Edifica prescriptive method of envelope energetic performance. Therefore, an equation of RTQ-C Consumption Indicator for bioclimatic zone 3 applied to study of institutional buildings. Initial parallelepiped form was programming in Rhino / Grasshopper software. The variables was defined according to RTQ-C prescriptive method equation, such as building length, width and height, openings height, glasses solar factor and vertical shading angle. The genetic algorithm used to generate the best form to meet energy efficiency parameters. Other volumetric possibilities were studied, being these: horizontal multiplication, vertical multiplication with rotation and vertical multiplication of unique form. The forms obtained the efficiency level A from RTQ-C traditional method application, which proves a viability of proposed method. In this way, it is possible to perceive the potentialities of generative modeling integrated to energy efficiency, which can revolutionize the architect design.Keywords: generative modeling, RTQ-C, energy efficiency. Sabe-se que decisões tomadas nos estágios iniciais de projeto arquitetônico têm impacto significativo na eficiência energética e desempenho interno dos edifícios. Um processo de projeto que utilize como parâmetros os conceitos de eficiência energética desde as etapas iniciais, pode acelerar o processo de criação agregando valor ao projeto, além de contribuir de maneira eficiente para o bem-estar do usuário e melhoria do meio ambiente. O objetivo deste artigo é verificar o potencial permitido pela integração da etiquetagem à modelagem generativa, através da otimização da forma integrada ao método prescritivo de desempenho energético da envoltória do Programa Brasileiro de Etiquetagem de edifícios do Inmetro, o PBE Edifica. Para isso, utilizou-se a equação do Indicador de Consumo do RTQ-C para a zona bioclimática 3 no item envoltória, aplicada ao estudo de edificações institucionais. Inicialmente, foi realizada a programação de uma forma inicial paralelepipédica utilizando os programas Rhino/Grasshopper. As variáveis do modelo foram definidas de acordo com a equação do método prescritivo do RTQ-C, sendo estas: comprimento, largura e altura da edificação, altura das aberturas, fator solar dos vidros e ângulo vertical de sombreamento das proteções solares horizontais. A evolução automatizada foi utilizada para gerar a melhor forma que se adeque aos parâmetros de eficiência energética. Outras possibilidades volumétricas foram também estudadas, sendo estas: multiplicação horizontal, multiplicação vertical com rotação e multiplicação vertical de forma única. A partir da aplicação do método tradicional proposto pelo RTQ-C, verificou-se que as volumetrias obtiveram nível de eficiência A, o que comprova a viabilidade do método proposto. Deste modo, pode-se perceber as potencialidades da modelagem generativa aliada à eficiência energética, que pode revolucionar o modo de projetar do arquiteto preocupado com as questões ambientais.Palavras-chave: modelagem generativa, RTQ-C, eficiência energética. Unisinos 2017-11-27 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion application/pdf https://revistas.unisinos.br/index.php/arquitetura/article/view/arq.2017.132.04 10.4013/arq.2017.132.04 Arquitetura Revista; v. 13 n. 2 (2017): Jul-Dez; 100-111 1808-5741 por https://revistas.unisinos.br/index.php/arquitetura/article/view/arq.2017.132.04/6471

Generative modeling integrated to energy efficiency: A study of institutional buildings form optimization

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