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Development of modular air containment system: Thermal performance optimization of row-based cooling for high-density data centers

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  • Cho, Jinkyun
  • Kim, Youngmo

Abstract

Modular air containment (MAC) prototype was developed for optimal row-based cooling system for high-density data centers. The main purpose of this study is to evaluate the thermal performance and compare the cooling provisioning of different configurations of row-based cooling system to find the optimum placement of in-row CRAC units. Techno-optimal estimations were performed considering different in-row CRAC placements and aisle layouts. A matrix combination was analyzed based on total 2592 cases that can be implemented. By the whole optimization process of in-row cooler placement, we can achieve the best solution with the statically balanced cooling provisioning with a margin of error of 0.2%. The cooled air from in-row CRAC units was supplied with almost no heat loss in the air distribution paths to each server. Numerical simulations confirmed that the cold-hot-cold (C–H–C) aisle layout can improve the minimum 9% of heat balance for the provisioned CRACs compared to the hot-cold-hot (H–C–H) aisle layout. Temperature distributions, air streamlines and net cooling usages showed that the C–H–C aisle layout has better thermal performance and cooling provisioning especially for the row-based cooling. The C–H–C aisle layout is more proper than the H–C–H aisle layout for achieving the desired cooling efficiency.

Suggested Citation

  • Cho, Jinkyun & Kim, Youngmo, 2021. "Development of modular air containment system: Thermal performance optimization of row-based cooling for high-density data centers," Energy, Elsevier, vol. 231(C).
    • Handle: RePEc:eee:energy:v:231:y:2021:i:c:s0360544221010860
    DOI: 10.1016/j.energy.2021.120838
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    References listed on IDEAS

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    1. Tatchell-Evans, Morgan & Kapur, Nik & Summers, Jonathan & Thompson, Harvey & Oldham, Dan, 2017. "An experimental and theoretical investigation of the extent of bypass air within data centres employing aisle containment, and its impact on power consumption," Applied Energy, Elsevier, vol. 186(P3), pages 457-469.
    2. Jinkyun Cho & Beungyong Park & Yongdae Jeong, 2019. "Thermal Performance Evaluation of a Data Center Cooling System under Fault Conditions," Energies, MDPI, vol. 12(15), pages 1-16, August.
    3. Cho, Jinkyun & Kim, Yundeok, 2016. "Improving energy efficiency of dedicated cooling system and its contribution towards meeting an energy-optimized data center," Applied Energy, Elsevier, vol. 165(C), pages 967-982.
    4. Han, Zongwei & Xue, Da & Wei, Haotian & Ji, Qiang & Sun, Xiaoqing & Li, Xiuming, 2021. "Study on operation strategy of evaporative cooling composite air conditioning system in data center," Renewable Energy, Elsevier, vol. 177(C), pages 1147-1160.
    5. Jinkyun Cho & Jesang Woo & Beungyong Park & Taesub Lim, 2020. "A Comparative CFD Study of Two Air Distribution Systems with Hot Aisle Containment in High-Density Data Centers," Energies, MDPI, vol. 13(22), pages 1-19, November.
    6. Emelie Wibron & Anna-Lena Ljung & T. Staffan Lundström, 2018. "Computational Fluid Dynamics Modeling and Validating Experiments of Airflow in a Data Center," Energies, MDPI, vol. 11(3), pages 1-15, March.
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    Cited by:

    1. Sijun Xu & Hua Zhang & Zilong Wang, 2023. "Thermal Management and Energy Consumption in Air, Liquid, and Free Cooling Systems for Data Centers: A Review," Energies, MDPI, vol. 16(3), pages 1-25, January.
    2. Cho, Jinkyun & Park, Beungyong & Jang, Seungmin, 2022. "Development of an independent modular air containment system for high-density data centers: Experimental investigation of row-based cooling performance and PUE," Energy, Elsevier, vol. 258(C).
    3. Zhang, Hainan & Tian, Yaling & Tian, Changqing & Zhai, Zhiqiang, 2023. "Effect of key structure and working condition parameters on a compact flat-evaporator loop heat pipe for chip cooling of data centers," Energy, Elsevier, vol. 284(C).
    4. Han, Ouzhu & Ding, Tao & Mu, Chenggang & Jia, Wenhao & Ma, Zhoujun, 2023. "Waste heat reutilization and integrated demand response for decentralized optimization of data centers," Energy, Elsevier, vol. 264(C).

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