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Simulation of Thermal Distribution and Airflow for Efficient Energy Consumption in a Small Data Centers

Author

Listed:
  • Jing Ni

    (Department of Information management and Information System, Beijing Institute of Petrochemical Technology, Beijing 102617, China)

  • Bowen Jin

    (College of Liberal Arts, University of Minnesota Twin Cities, Minneapolis, MN 55455, USA)

  • Bo Zhang

    (Department of Chemical Engineering, Beijing Institute of Petrochemical Technology, Beijing 102617, China)

  • Xiaowei Wang

    (Department of Information management and Information System, Beijing Institute of Petrochemical Technology, Beijing 102617, China)

Abstract

Data centers have become ubiquitous in the last few years in an attempt to keep pace with the processing and storage needs of the Internet and cloud computing. The steady growth in the heat densities of IT servers leads to a rise in the energy needed to cool them, and constitutes approximately 40% of the power consumed by data centers. However, many data centers feature redundant air conditioning systems that contribute to inefficient air distribution, which significantly increases energy consumption. This remains an insufficiently explored problem. In this paper, a typical, small data center with tiles for an air supply system with a raised floor is used. We use a fluent (Computational Fluid Dynamics, CFD) to simulate thermal distribution and airflow, and investigate the optimal conditions of air distribution to save energy. The effects of the airflow outlet angle along the tile, the cooling temperature and the rate of airflow on the beta index as well as the energy utilization index are discussed, and the optimal conditions are obtained. The reasonable airflow distribution achieved using 3D CFD calculations and the parameter settings provided in this paper can help reduce the energy consumption of data centers by improving the efficiency of the air conditioning.

Suggested Citation

  • Jing Ni & Bowen Jin & Bo Zhang & Xiaowei Wang, 2017. "Simulation of Thermal Distribution and Airflow for Efficient Energy Consumption in a Small Data Centers," Sustainability, MDPI, vol. 9(4), pages 1-16, April.
    • Handle: RePEc:gam:jsusta:v:9:y:2017:i:4:p:664-:d:96442
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    References listed on IDEAS

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    Cited by:

    1. Marcel Antal & Tudor Cioara & Ionut Anghel & Radoslaw Gorzenski & Radoslaw Januszewski & Ariel Oleksiak & Wojciech Piatek & Claudia Pop & Ioan Salomie & Wojciech Szeliga, 2019. "Reuse of Data Center Waste Heat in Nearby Neighborhoods: A Neural Networks-Based Prediction Model," Energies, MDPI, vol. 12(5), pages 1-18, March.
    2. Naoki Futawatari & Yosuke Udagawa & Taro Mori & Hirofumi Hayama, 2020. "Improving Prediction Accuracy Concerning the Thermal Environment of a Data Center by Using Design of Experiments," Energies, MDPI, vol. 13(18), pages 1-21, September.
    3. Chu, Wen-Xiao & Wang, Chi-Chuan, 2019. "A review on airflow management in data centers," Applied Energy, Elsevier, vol. 240(C), pages 84-119.

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