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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| Main Authors: | , |
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| 格式: | Online |
| 語言: | por |
| 出版: |
Unisinos
2017
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| 在線閱讀: | https://revistas.unisinos.br/index.php/arquitetura/article/view/arq.2017.132.04 |
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| 總結: | 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. |
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