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Study on a Dynamic Numerical Model of an Underground Air Tunnel System for Cooling Applications—Experimental Validation and Multidimensional Parametrical Analysis

Author

Listed:
  • Liang Tang

    (College of Civil Engineering, National Center for International Research Collaboration in Building Safety and Environment, Hunan University, Changsha 410082, China)

  • Zhengxuan Liu

    (College of Civil Engineering, National Center for International Research Collaboration in Building Safety and Environment, Hunan University, Changsha 410082, China)

  • Yuekuan Zhou

    (Department of Building Services Engineering, Faculty of Construction and Environment, The Hong Kong Polytechnic University, Hong Kong 999077, China)

  • Di Qin

    (College of Civil Engineering, National Center for International Research Collaboration in Building Safety and Environment, Hunan University, Changsha 410082, China)

  • Guoqiang Zhang

    (College of Civil Engineering, National Center for International Research Collaboration in Building Safety and Environment, Hunan University, Changsha 410082, China)

Abstract

The underground air tunnel system shows promising potentials for reducing energy consumption of buildings and for improving indoor thermal comfort, whereas the existing dynamic models using the computational fluid dynamic (CFD) method show computational complexity and are user-unfriendly for parametrical analysis. In this study, a dynamic numerical model was developed with the on-site experimental calibration. Compared to the traditional CFD method with high computational complexity, the mathematical model on the MATLAB/SIMULINK platform is time-saving in terms of the real-time thermal performance prediction. The experimental validation results indicated that the maximum absolute relative deviation was 3.18% between the model-driven results and the data from the on-site experiments. Parametrical analysis results indicated that, with the increase of the tube length, the outlet temperature decreases with an increase of the cooling capacity whereas the increasing/decreasing magnitude slows down. In addition, the system performance is independent on the tube materials. Furthermore, the outlet air temperature and cooling capacity are dependent on the tube diameter and air velocity, i.e., a larger tube diameter and a higher air velocity are more suitable to improve the system’s cooling capacity, and a smaller tube diameter and a lower air velocity will produce a more stable and lower outlet temperature. Further studies need to be conducted for the trade-off solutions between air velocity and tube diameter for the bi-criteria performance enhancement between outlet temperature and cooling capacity. This study proposed an experimentally validated mathematical model to accurately predict the thermal performance of the underground air tunnel system with high computational efficiency, which can provide technical guidance to multi-combined solutions through geometrical designs and operating parameters for the optimal design and robust operation.

Suggested Citation

  • Liang Tang & Zhengxuan Liu & Yuekuan Zhou & Di Qin & Guoqiang Zhang, 2020. "Study on a Dynamic Numerical Model of an Underground Air Tunnel System for Cooling Applications—Experimental Validation and Multidimensional Parametrical Analysis," Energies, MDPI, vol. 13(5), pages 1-20, March.
    • Handle: RePEc:gam:jeners:v:13:y:2020:i:5:p:1236-:d:329551
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    References listed on IDEAS

    as
    1. Zhou, Yuekuan & Zheng, Siqian & Zhang, Guoqiang, 2020. "Machine-learning based study on the on-site renewable electrical performance of an optimal hybrid PCMs integrated renewable system with high-level parameters’ uncertainties," Renewable Energy, Elsevier, vol. 151(C), pages 403-418.
    2. Zhou, Yuekuan & Cao, Sunliang & Hensen, Jan L.M. & Lund, Peter D., 2019. "Energy integration and interaction between buildings and vehicles: A state-of-the-art review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 114(C), pages 1-1.
    3. Zhou, Yuekuan & Zheng, Siqian & Zhang, Guoqiang, 2020. "Machine learning-based optimal design of a phase change material integrated renewable system with on-site PV, radiative cooling and hybrid ventilations—study of modelling and application in five clima," Energy, Elsevier, vol. 192(C).
    4. Bansal, Vikas & Misra, Rohit & Agarwal, Ghanshyam Das & Mathur, Jyotirmay, 2013. "‘Derating Factor’ new concept for evaluating thermal performance of earth air tunnel heat exchanger: A transient CFD analysis," Applied Energy, Elsevier, vol. 102(C), pages 418-426.
    5. Misra, Rohit & Bansal, Vikas & Agrawal, Ghanshyam Das & Mathur, Jyotirmay & Aseri, Tarun K., 2013. "CFD analysis based parametric study of derating factor for Earth Air Tunnel Heat Exchanger," Applied Energy, Elsevier, vol. 103(C), pages 266-277.
    6. Zhang, Linfeng & Zhang, Quan & Huang, Gongsheng, 2016. "A transient quasi-3D entire time scale line source model for the fluid and ground temperature prediction of vertical ground heat exchangers (GHEs)," Applied Energy, Elsevier, vol. 170(C), pages 65-75.
    7. Xiaohong Liu & Yuekuan Zhou & Chun-Qing Li & Yaolin Lin & Wei Yang & Guoqiang Zhang, 2019. "Optimization of a New Phase Change Material Integrated Photovoltaic/Thermal Panel with The Active Cooling Technique Using Taguchi Method," Energies, MDPI, vol. 12(6), pages 1-22, March.
    8. Azzolin, Marco & Mariani, Andrea & Moro, Lorenzo & Tolotto, Andrea & Toninelli, Paolo & Del Col, Davide, 2018. "Mathematical model of a thermosyphon integrated storage solar collector," Renewable Energy, Elsevier, vol. 128(PA), pages 400-415.
    9. Liu, Zhengxuan & Yu, Zhun (Jerry) & Yang, Tingting & Roccamena, Letizia & Sun, Pengcheng & Li, Shuisheng & Zhang, Guoqiang & El Mankibi, Mohamed, 2019. "Numerical modeling and parametric study of a vertical earth-to-air heat exchanger system," Energy, Elsevier, vol. 172(C), pages 220-231.
    10. Zhou, Yuekuan & Zheng, Siqian & Zhang, Guoqiang, 2019. "Study on the energy performance enhancement of a new PCMs integrated hybrid system with the active cooling and hybrid ventilations," Energy, Elsevier, vol. 179(C), pages 111-128.
    11. Niu, Fuxin & Yu, Yuebin & Yu, Daihong & Li, Haorong, 2015. "Heat and mass transfer performance analysis and cooling capacity prediction of earth to air heat exchanger," Applied Energy, Elsevier, vol. 137(C), pages 211-221.
    12. De Rosa, Mattia & Bianco, Vincenzo & Scarpa, Federico & Tagliafico, Luca A., 2014. "Heating and cooling building energy demand evaluation; a simplified model and a modified degree days approach," Applied Energy, Elsevier, vol. 128(C), pages 217-229.
    13. Bordoloi, Namrata & Sharma, Aashish & Nautiyal, Himanshu & Goel, Varun, 2018. "An intense review on the latest advancements of Earth Air Heat Exchangers," Renewable and Sustainable Energy Reviews, Elsevier, vol. 89(C), pages 261-280.
    14. Wei, Haibin & Yang, Dong & Guo, Yuanhao & Chen, Mengqian, 2018. "Coupling of earth-to-air heat exchangers and buoyancy for energy-efficient ventilation of buildings considering dynamic thermal behavior and cooling/heating capacity," Energy, Elsevier, vol. 147(C), pages 587-602.
    15. Zhou, Yuekuan & Zheng, Siqian, 2020. "Uncertainty study on thermal and energy performances of a deterministic parameters based optimal aerogel glazing system using machine-learning method," Energy, Elsevier, vol. 193(C).
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    Cited by:

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