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Thermal Comfort Assessment of the Perimeter Zones by Using CFD Simulation

Author

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  • Taesub Lim

    (Department of Architectural Engineering, Seoil University, Seoul 02192, Republic of Korea)

  • Daeung Danny Kim

    (Architectural Engineering Department, King Fahd University of Petroleum and Minerals (KFUPM), Dhahran 31261, Saudi Arabia)

Abstract

Most perimeter zones are thermally susceptible to the variation of outdoor conditions, especially due to a large amount of heat gain through glazing. To reduce heat gain, spandrel panels are generally installed in curtain walls of commercial buildings. For the present study, thermal performance in an office located in the perimeter zone was investigated using Computational Fluid Dynamics (CFD) simulation. By varying the spandrel panel heights, thermal comfort was assessed quantitatively. The findings suggest that when the spandrel panel height was 0 m, the highest temperature was observed in all cases. As the height of the spandrel panel was increased, the temperature decreased. For thermal comfort evaluation, Predicted Mean Vote (PMV) values at 1.5 m from the floor in all cases were larger than zero. PMV values in all cases were within the range of slightly cool to warm. When the spandrel panel height was 0 m, the highest thermal sensation (warm) among the cases was observed, which may cause thermal dissatisfaction for occupants. In addition, thermal comfort was deemed satisfactory based on the criteria of ASHRAE standard 55, when the height of the spandrel panel was higher than 0.6 m.

Suggested Citation

  • Taesub Lim & Daeung Danny Kim, 2022. "Thermal Comfort Assessment of the Perimeter Zones by Using CFD Simulation," Sustainability, MDPI, vol. 14(23), pages 1-16, November.
    • Handle: RePEc:gam:jsusta:v:14:y:2022:i:23:p:15647-:d:983074
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    References listed on IDEAS

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    1. Paulos, Jason & Berardi, Umberto, 2020. "Optimizing the thermal performance of window frames through aerogel-enhancements," Applied Energy, Elsevier, vol. 266(C).
    2. Cuce, Erdem & Riffat, Saffa B., 2015. "A state-of-the-art review on innovative glazing technologies," Renewable and Sustainable Energy Reviews, Elsevier, vol. 41(C), pages 695-714.
    3. Khamma, Thulasi Ram & Zhang, Yuming & Guerrier, Stéphane & Boubekri, Mohamed, 2020. "Generalized additive models: An efficient method for short-term energy prediction in office buildings," Energy, Elsevier, vol. 213(C).
    4. Zhang, Yi & Tennakoon, Thilhara & Chan, Yin Hoi & Chan, Ka Chung & Fu, Sau Chung & Tso, Chi Yan & Yu, Kin Man & Huang, Bao Ling & Yao, Shu Huai & Qiu, Hui He & Chao, Christopher Y.H., 2022. "Energy consumption modelling of a passive hybrid system for office buildings in different climates," Energy, Elsevier, vol. 239(PA).
    5. Ihara, Takeshi & Gao, Tao & Grynning, Steinar & Jelle, Bjørn Petter & Gustavsen, Arild, 2015. "Aerogel granulate glazing facades and their application potential from an energy saving perspective," Applied Energy, Elsevier, vol. 142(C), pages 179-191.
    6. Chan, A.L.S., 2019. "Effect of adjacent shading on the energy and environmental performance of photovoltaic glazing system in building application," Energy, Elsevier, vol. 187(C).
    7. de Almeida Rocha, Ana Paula & Reynoso-Meza, Gilberto & Oliveira, Ricardo C.L.F. & Mendes, Nathan, 2020. "A pixel counting based method for designing shading devices in buildings considering energy efficiency, daylight use and fading protection," Applied Energy, Elsevier, vol. 262(C).
    8. Huang, Yu & Niu, Jian-lei & Chung, Tse-ming, 2014. "Comprehensive analysis on thermal and daylighting performance of glazing and shading designs on office building envelope in cooling-dominant climates," Applied Energy, Elsevier, vol. 134(C), pages 215-228.
    9. Wong, S.L. & Wan, Kevin K.W. & Lam, Tony N.T., 2010. "Artificial neural networks for energy analysis of office buildings with daylighting," Applied Energy, Elsevier, vol. 87(2), pages 551-557, February.
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