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Intelligent Parametric Optimization of Building Atrium Design: A Case Study for a Sustainable and Comfortable Environment

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  • Yunzhu Ji

    (School of Architecture, Southeast University, Nanjing 210096, China
    Center for the Built Environment, University of California, Berkeley, CA 94720, USA)

  • Minghao Xu

    (College of Environmental Design, University of California, Berkeley, CA 94720, USA)

  • Tong Zhang

    (School of Architecture, Southeast University, Nanjing 210096, China)

  • Yingdong He

    (Center for the Built Environment, University of California, Berkeley, CA 94720, USA
    College of Civil Engineering, Hunan University, Changsha 410082, China)

Abstract

Building atrium design is crucial to maintaining a sustainable built environment and providing thermal comfort to occupants. This study proposes a parametric framework to optimize the atrium’s geometry for environmental performance and thermal comfort improvement. It integrates the parametric design, performance simulation, and multi-objective optimization in the Rhino and Grasshopper platform to realize automatic optimization. The atrium’s well index, shape ratio, volume ratio, position index, and inner interface window-to-wall ratio were set as optimized factors. For the optimization objectives, useful daylight illuminance (UDI), energy use intensity (EUI), and the discomfort time percentage (DTP) were chosen as metrics for the measurement of daylighting, energy use efficiency, and thermal comfort, respectively. Moreover, a geometry mapping method is developed; it can turn atrium shape into rectangular profiles. Thus, the framework can apply to general buildings. To validate the effectiveness of the proposed framework, an atrium optimization case study is conducted for a villa in Poland. According to the optimization results, the performance of the compared three objectives are improved by 43.20%, 15.52%, and 3.89%, respectively. The running time for the optimization is about 36 s per solution, which greatly reduce the human and time cost compared to the traditional working method.

Suggested Citation

  • Yunzhu Ji & Minghao Xu & Tong Zhang & Yingdong He, 2023. "Intelligent Parametric Optimization of Building Atrium Design: A Case Study for a Sustainable and Comfortable Environment," Sustainability, MDPI, vol. 15(5), pages 1-25, February.
    • Handle: RePEc:gam:jsusta:v:15:y:2023:i:5:p:4362-:d:1084138
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    References listed on IDEAS

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    4. Ciardiello, Adriana & Rosso, Federica & Dell'Olmo, Jacopo & Ciancio, Virgilio & Ferrero, Marco & Salata, Ferdinando, 2020. "Multi-objective approach to the optimization of shape and envelope in building energy design," Applied Energy, Elsevier, vol. 280(C).
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    Cited by:

    1. Rui Han & Shiqi Yang, 2023. "A Study on Industrial Heritage Renewal Strategy Based on Hybrid Bayesian Network," Sustainability, MDPI, vol. 15(13), pages 1-32, July.

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