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An experimental and numerical investigation of novel solution for energy management enhancement in data centers using underfloor plenum porous obstructions

Author

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  • Tradat, Mohammad I.
  • Manaserh, Yaman “Mohammad Ali”
  • Sammakia, Bahgat G.
  • Hoang, Cong Hiep
  • Alissa, Husam A.

Abstract

This investigation focuses on improving the airflow distribution in data centers. In many data centers vortices form in the plenum during operations. These vortices cause spatial and temporal non-uniformities and may give rise to hot regions in the data center which in turn impacts performance and reliability of the IT equipment. The current study identifies a novel approach using porous partitions in the plenum and demonstrates a significant generalized approach that is easily adoptable in existing and future data centers. For improving the overall data center energy efficiency and the cooling system effectiveness by eliminating a critical source of inefficiency. The results of quantitative and qualitative analyses of the underfloor plenum pressure field, perforated tiles airflow rate, and air temperature at the rack intake side with and without partitions are presented. Different data center configurations are studied using physics-based experimentally validated Computational Fluid Dynamics (CFD) model. The CFD model results showed that the partitions eliminated the presence of vortices in the underfloor plenum and thus enabled a more uniform pressure distribution and tile airflow delivery. Regarding rack inlet temperature, the results showed that the partitions significantly improved the air temperature at the rack inlet. Finally, a geometrical parametric study is performed. An ideal design is and demonstrated to improve the Supply Heat Index (SHI) by about 10%, while the amount of IT equipment that exceeded the ASHRAE recommended supply air temperature (SAT) was reduced by about 40%, and the floor leakage was cut in half.

Suggested Citation

  • Tradat, Mohammad I. & Manaserh, Yaman “Mohammad Ali” & Sammakia, Bahgat G. & Hoang, Cong Hiep & Alissa, Husam A., 2021. "An experimental and numerical investigation of novel solution for energy management enhancement in data centers using underfloor plenum porous obstructions," Applied Energy, Elsevier, vol. 289(C).
    • Handle: RePEc:eee:appene:v:289:y:2021:i:c:s0306261921001938
    DOI: 10.1016/j.apenergy.2021.116663
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    Citations

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    Cited by:

    1. Manaserh, Yaman M. & Tradat, Mohammad I. & Bani-Hani, Dana & Alfallah, Aseel & Sammakia, Bahgat G. & Nemati, Kourosh & Seymour, Mark J., 2022. "Machine learning assisted development of IT equipment compact models for data centers energy planning," Applied Energy, Elsevier, vol. 305(C).
    2. Xiaolei Fan & Tao Yu & Peng Liu & Xiangdong Li, 2022. "Uniformity of Supply Air in the Plenum for Under-Floor Air Distribution Ventilation in a Circular Conference Room: A CFD Study," Energies, MDPI, vol. 15(17), pages 1-18, August.
    3. Lee, Yee-Ting & Wen, Chih-Yung & Shih, Yang-Cheng & Li, Zhengtong & Yang, An-Shik, 2022. "Numerical and experimental investigations on thermal management for data center with cold aisle containment configuration," Applied Energy, Elsevier, vol. 307(C).
    4. He, Wei & Ding, Su & Zhang, Jifang & Pei, Chenchen & Zhang, Zhiheng & Wang, Yulin & Li, Hailong, 2021. "Performance optimization of server water cooling system based on minimum energy consumption analysis," Applied Energy, Elsevier, vol. 303(C).
    5. Hu, Zhi-Hua & Zheng, Yu-Xin & Wang, You-Gan, 2022. "Packing computing servers into the vessel of an underwater data center considering cooling efficiency," Applied Energy, Elsevier, vol. 314(C).
    6. Abubaker, Ahmad M. & Darwish Ahmad, Adnan & Salaimeh, Ahmad A. & Akafuah, Nelson K. & Saito, Kozo, 2022. "A novel solar combined cycle integration: An exergy-based optimization using artificial neural network," Renewable Energy, Elsevier, vol. 181(C), pages 914-932.
    7. Hou, Falin & Shen, Chenhui & Cheng, Qing, 2022. "Research on a new optimization method for airflow organization in breeding air conditioning with perforated ceiling ventilation," Energy, Elsevier, vol. 254(PB).
    8. Cho, Jinkyun & Lim, Seung-beom, 2023. "Balanced comparative assessment of thermal performance and energy efficiency for three cooling solutions in data centers," Energy, Elsevier, vol. 285(C).

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