Reverse passive strategy exploration for building massing design-An optimization-aided approach

Likai Wang, Ting Luo, Tong Shao, Guohua Ji
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Abstract

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 Rhino-Grasshopper. 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.
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建筑体量设计的逆向被动策略探索一种优化辅助方法
在建筑体量设计中,使用被动设计策略是在提供舒适室内环境的同时降低能耗的关键方法。然而,建筑师在建筑体量设计和建筑形态发现过程开始时系统地探索被动设计策略往往是不切实际的,这可能会导致策略的低效或无效利用。为了解决这个问题,本研究提出了一种反向被动设计策略探索方法,该方法利用计算优化和参数建模的能力,帮助建筑师确定建筑体量设计的可行被动设计策略。该方法是使用名为EvoMass的建筑体量设计生成和优化工具以及Rhino Grasshopper中的各种建筑性能模拟工具实现的。优化可以产生特定场地的设计参考,这些参考反映了与被动设计策略(如中庭和自遮阳)相关的丰富性能含义。因此,建筑师可以从优化结果中筛选出与不同性能因素相对应的有前景的被动设计策略。介绍了两个与采光、天空照射和太阳能热利用相关的案例研究来证明该方法,并讨论了相关的实用性和局限性。
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CiteScore
3.20
自引率
17.60%
发文量
44
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