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Numerical and experimental investigation of the indoor air quality and thermal comfort performance of a low energy cooling windcatcher with heat pipes and extended surfaces

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  • Calautit, John Kaiser
  • Tien, Paige Wenbin
  • Wei, Shuangyu
  • Calautit, Katrina
  • Hughes, Ben

Abstract

This work builds on previous experience in windcatcher design, maximising the ventilation rate of the windcatcher, whilst integrating low energy cooling technologies. The present study aims to investigate the thermal comfort and indoor air quality in buildings ventilated with a passive cooling windcatcher integrated with heat pipes and extended surface using numerical modelling, wind tunnel and far-field testing in the UAE during a summer month. Results of the scaled wind tunnel tests showed that the addition of the heat pipes and extended surfaces reduced the airflow through the windcatcher but did not impede the flow even at low outdoor wind speeds, this was further confirmed by the smoke visualisation tests. Analysis of pollutant concentration in the building model showed that the proposed windcatcher configuration was capable of delivering fresh air at a sufficient rate to lower CO2 concentration levels below the recommended guidelines for air quality. The thermal comfort analysis was conducted and it was observed that for the present design, equal distribution of thermal comfort was not achieved due to combination of high air movement, colder temperature and high humidity below the windcatcher which resulted in higher thermal discomfort in this area. Further work is required to develop a suitable control strategy in the form of volume control dampers which would enable the supply flowrate to be monitored and altered as required and optimized the distribution in the occupied space. Field tests data was used to validate the numerical modelling, showing good agreement between both methods.

Suggested Citation

  • Calautit, John Kaiser & Tien, Paige Wenbin & Wei, Shuangyu & Calautit, Katrina & Hughes, Ben, 2020. "Numerical and experimental investigation of the indoor air quality and thermal comfort performance of a low energy cooling windcatcher with heat pipes and extended surfaces," Renewable Energy, Elsevier, vol. 145(C), pages 744-756.
  • Handle: RePEc:eee:renene:v:145:y:2020:i:c:p:744-756
    DOI: 10.1016/j.renene.2019.06.040
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    Citations

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    Cited by:

    1. Zhang, Wanshi & Wu, Yunlei & Li, Xiuwei & Cheng, Feng & Zhang, Xiaosong, 2021. "Performance investigation of the wood-based heat localization regenerator in liquid desiccant cooling system," Renewable Energy, Elsevier, vol. 179(C), pages 133-149.
    2. Mahon, Harry & Friedrich, Daniel & Hughes, Ben, 2022. "Wind tunnel test and numerical study of a multi-sided wind tower with horizontal heat pipes," Energy, Elsevier, vol. 260(C).
    3. Kun Lan & Yang Chen, 2022. "Air Quality and Thermal Environment of Primary School Classrooms with Sustainable Structures in Northern Shaanxi, China: A Numerical Study," Sustainability, MDPI, vol. 14(19), pages 1-19, September.
    4. Marouen Ghoulem & Khaled El Moueddeb & Ezzedine Nehdi & Fangliang Zhong & John Calautit, 2020. "Design of a Passive Downdraught Evaporative Cooling Windcatcher (PDEC-WC) System for Greenhouses in Hot Climates," Energies, MDPI, vol. 13(11), pages 1-23, June.
    5. Ardalan Aflaki & Masoud Esfandiari & Saleh Mohammadi, 2021. "A Review of Numerical Simulation as a Precedence Method for Prediction and Evaluation of Building Ventilation Performance," Sustainability, MDPI, vol. 13(22), pages 1-18, November.
    6. Xingbo Yao & Bart J. Dewancker & Yuang Guo & Shuo Han & Juan Xu, 2020. "Study on Passive Ventilation and Cooling Strategies for Cold Lanes and Courtyard Houses—A Case Study of Rural Traditional Village in Shaanxi, China," Sustainability, MDPI, vol. 12(20), pages 1-36, October.
    7. Calautit, John Kaiser & O’Connor, Dominic & Tien, Paige Wenbin & Wei, Shuangyu & Pantua, Conrad Allan Jay & Hughes, Ben, 2020. "Development of a natural ventilation windcatcher with passive heat recovery wheel for mild-cold climates: CFD and experimental analysis," Renewable Energy, Elsevier, vol. 160(C), pages 465-482.
    8. Tien, Paige Wenbin & Wei, Shuangyu & Liu, Tianshu & Calautit, John & Darkwa, Jo & Wood, Christopher, 2021. "A deep learning approach towards the detection and recognition of opening of windows for effective management of building ventilation heat losses and reducing space heating demand," Renewable Energy, Elsevier, vol. 177(C), pages 603-625.
    9. Ashraf Balabel & Mamdooh Alwetaishi & Wageeh A. El-Askary & Hamza Fawzy, 2021. "Numerical Study on Natural Ventilation Characteristics of a Partial-Cylinder Opening for One-Sided-Windcatcher of Variable Air-Feeding Orientations in Taif, Saudi Arabia," Sustainability, MDPI, vol. 13(20), pages 1-20, October.

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