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Assessing the effectiveness of dynamic metrics in predicting daylight availability and visual comfort in classrooms

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  • Zomorodian, Zahra S.
  • Tahsildoost, Mohammad

Abstract

In this study, daylight performance and visual comfort have been evaluated by a longitudinal subjective survey (842 total responses) and simulation-based metrics in four classrooms in two LEED™ silver certified buildings during a year. Dynamic and static daylight and glare metrics are reviewed and critiqued based upon their ability to explain the perception of human subjective responses in classrooms. Results indicate high correlation between students' perceptions and dynamic daylight metrics; sDA300/50% and UDI300-3000/50%, in defining the daylit area. Moreover, according to results the Vertical illuminance-based metrics (sDGPexceed) is more compatible than horizontal illuminance-based metrics (ASE) at fitting the range of perceived discomfort glare. However, more and larger studies are needed to confirm utilizing the sDGPexceed index for indication of discomfort glare in early stage of building design. According to results, daylight and glare metrics' thresholds should be reconsidered based on global filed surveys, since occupants' ability to adapt to higher or lower levels of light is related to culture and climate location.

Suggested Citation

  • Zomorodian, Zahra S. & Tahsildoost, Mohammad, 2019. "Assessing the effectiveness of dynamic metrics in predicting daylight availability and visual comfort in classrooms," Renewable Energy, Elsevier, vol. 134(C), pages 669-680.
    • Handle: RePEc:eee:renene:v:134:y:2019:i:c:p:669-680
    DOI: 10.1016/j.renene.2018.11.072
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    References listed on IDEAS

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    1. Singh, M.C. & Garg, S.N., 2010. "Illuminance estimation and daylighting energy savings for Indian regions," Renewable Energy, Elsevier, vol. 35(3), pages 703-711.
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    Cited by:

    1. Jie Li & Qichao Ban & Xueming (Jimmy) Chen & Jiawei Yao, 2019. "Glazing Sizing in Large Atrium Buildings: A Perspective of Balancing Daylight Quantity and Visual Comfort," Energies, MDPI, vol. 12(4), pages 1-14, February.
    2. Jack Ngarambe & Amina Irakoze & Geun Young Yun & Gon Kim, 2020. "Comparative Performance of Machine Learning Algorithms in the Prediction of Indoor Daylight Illuminances," Sustainability, MDPI, vol. 12(11), pages 1-22, June.
    3. Amir Faraji & Maria Rashidi & Fatemeh Rezaei & Payam Rahnamayiezekavat, 2023. "A Meta-Synthesis Review of Occupant Comfort Assessment in Buildings (2002–2022)," Sustainability, MDPI, vol. 15(5), pages 1-36, February.
    4. Alexander Rani Suryandono & Agus Hariyadi & Hiroatsu Fukuda, 2021. "Economic Assessment of L-Shaped Minilouvers for Reducing Cooling Energy and Improving Daylight Condition in Offices: A Simulation Study in Jakarta," Sustainability, MDPI, vol. 13(7), pages 1-18, April.

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