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Influence of floor air supply methods and geometric parameters on thermal performance of data centers

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Abstract

This paper compares four commonly used air supply methods, namely hot and cold aisle open air supply systems, hot aisle sealed air supply systems, under-rack cold aisle air supply systems and cold aisle sealed air supply systems. For each air supply method, the effects of geometric factors, including static pressure box height (0.4–0.6 m in steps of 0.1 m), perforation rate (10%-40% in steps of 10%), baffle position shape (\/-shaped and /\- shaped) and baffle angle (30°/45°/60°), on the thermal environment of the data center are numerically calculated (288 cases in total). Thereafter, the numerical calculation results of the optimal structure were verified through comparison with the results of measurement of the average rack temperature, the average hot spot temperature, the thermal performance evaluation index and the return temperature index on site. The results show that by increasing the height of the static pressure box or reducing the perforation rate within range of 10–30%, the thermal performance of the static pressure box can be improved. Taking into account the room temperature profile and the evaluation indicators (β, RTI), the best overall performance is achieved in the case of cold aisle containment. Finally, \/-shaped and /\-shaped baffles are compared in the model with cold aisle contained, and the results show that the perforation rate is 20% for both \/-shaped and /\-shaped baffles, and the optimum static pressure heights are 0.5 m and 0.6 m for \/-shaped and /\-shaped baffles, respectively. Overall, \/-shaped baffles have better temperature uniformity than /\-shaped baffles. It is found that the best performance for the CACS model is the configuration with \/-shaped baffle at the angle of 60°, the plenum height of 0.5 m and a perforation rate of 20%.

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Abbreviations

UFAD:

Underfloor air distribution

CRAC:

Computer room air conditioner

C/HAOS:

Cold/hot-aisle airflow open-ended system

HACS:

Hot aisle containment system

CURS:

Cold aisle under racks system

CACS:

Cold aisle containment system

PDU:

Power distribution units

RCI:

Rack cooling index

RHI:

Return heat index

RTI:

Return temperature index

σFUI :

Standard deviation of FUI

β :

Thermal performance evaluation index

ρ :

Density, kg·m−3

\(\overrightarrow{\alpha }\) :

Acceleration of gravity, N·kg−1

T :

Temperature, K

Δp :

Pressure drop, Pa

c p :

Specific heat capacity, J·kg−1·K−1

v e :

Effective fluid viscosity, Pa·s−1

S :

Heat source, W

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Acknowledgements

This research is supported by Postgraduate Research & Practice Innovation Program of Jiangsu Province, China (SJCX22_0599). Jiangxi Provincial Education Department Science and Technology Research Project, China (GJJ214812). Excellent Graduate Workshop in Nanjing Canatal Data-Center Environmental Tech Co., Ltd in Jiangsu Province, China (2012_043)

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Authors and Affiliations

  1. School of Energy and Mechanical Engineering, Nanjing Normal University, Nanjing, Jiangsu Province, China

    Yanzhen Feng & Zhongbin Zhang

  2. School of Architecture and Engineering, Jiangxi Vocational College of Finance and Economics, Jiangxi, 332000, China

    Peng Liu

  3. School of Civil Engineering and Architecture, Zhejiang Sci-Tech University, Hangzhou, 310018, China

    Wenting Zhang

  4. Nanjing Canatal Data-Centre Environmental Tech Co.,Ltd., Nanjing, Jiangsu Province, China

    Linda Li

  5. School of Engineering, The Australian National University, Canberra, ACT, 2601, Australia

    Xiaolin Wang

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  1. Yanzhen Feng
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Contributions

Conceptualization, methodology, and funding acquisition were contributed by ZZ*. Data curation, writing—original draft, and investigation were contributed by YF. Formal analysis and investigation were contributed by PL. Investigation and validation were contributed by WZ. Supervision was contributed by LL. Writing—review & editing, was contributed by XW.

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Correspondence to Zhongbin Zhang.

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Feng, Y., Liu, P., Zhang, Z. et al. Influence of floor air supply methods and geometric parameters on thermal performance of data centers. J Therm Anal Calorim 148, 8477–8496 (2023). https://doi.org/10.1007/s10973-023-12188-z

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