| id |
ijac202321304 |
| authors |
Wang, Likai; Ting Luo; Tong Shao; Guohua Ji |
| year |
2023 |
| title |
Reverse passive strategy exploration for building massing design-An optimization-aided approach |
| source |
International Journal of Architectural Computing 2023, Vol. 21 - no. 3, 445461 |
| summary |
In building massing design, using passive design strategies is a critical approach to reducing energy consumption while offering comfortable indoor environments. However, it is often impractical for architects to systematically explore passive design strategies at the outset of the building massing design and architectural form-finding processes, which may result in inefficient or ineffective utilization of the strategies. To address this issue, this study presents a reverse passive design strategy exploration approach that leverages the capability of computational optimization and parametric modeling to help architects identify feasible passive design strategies for building massing design. The approach is achieved using a building massing design generation and optimization tool, called EvoMass, and various building performance simulation tools in RhinoGrasshopper. The optimization can produce site-specific design references that reflect rich performance implications associated with passive design strategies, such as atriums and self-shading. As such, architects can screen out promising passive design strategies corresponding to different performance factors from the optimization result. Two case studies related to daylighting, sky exposure, and solar heat utility are presented to demonstrate the approach, and the relevant utility and limitations are discussed |
| keywords |
Passive design strategies, computational optimization, design exploration, building massing design, formfinding |
| series |
journal |
| references |
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| last changed |
2024/04/17 14:30 |
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