Effects and optimization of airflow on the thermal environment in a data center
Frontiers in Built Environment (Frontiers Media SA) · Di Jiang
A 6SigmaRoom CFD study of a 153 m² room with 55 cabinets at 6 kW each compares three cooling arrangements: raised-floor perimeter units, in-row units and rear-door heat-pipe coolers, in seven cases.
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Overview
The study addresses rising data-centre energy consumption by optimising airflow organisation, comparing three cooling systems that are usually considered in isolation. The room is 16.2 m × 9.45 m × 5.125 m (about 153 m²) with 55 cabinets of 600 × 1200 × 2200 mm at 6 kW each, laid out in three rows in a hot/cold aisle pattern. In the raised-floor case, two perimeter units of up to 230 kW and 45,900 m³/h each supply 20 °C air through a 0.64 m raised floor and 0.6 × 0.6 m floor grilles at 50% open area.
The raised-floor and in-row cases were each run open, with cold-aisle containment (CAC) and with hot-aisle containment (HAC), giving seven cases. Air supply efficiency (ASE), air return efficiency, a recirculation index, RTI, SHI and RHI were tabulated. Raised floor without containment gave ASE 65.69%, RTI 77.94% and SHI 0.141; with CAC, ASE 85.57% and SHI 0.0027; with HAC, ASE 90.25%, RTI 90.94% and SHI 0.0024. Without containment, cabinet No. 19 had a mean inlet temperature of 30.1 °C and a maximum of 36.7 °C, and ten cabinets went above the 27 °C specification limit.
In the in-row case, three units of 51.1 kW sensible and 10,200 m³/h each gave ASE 71.29% and SHI 0.145 without containment, and with CAC ASE 92.16%, ARE 99.88% and SHI 0.0015. With 6 kW heat-pipe rear-door coolers, cabinet inlet temperatures averaged about 21.5 °C and varied by no more than 2 °C within a cabinet, and the room stayed at about 22 °C without aisle containment.
Limits: the hall was still being built, so the model was checked against a second CFD code rather than measurements: COMSOL against 6SigmaRoom gave a mean cabinet inlet temperature error below 10%. There is no measurement validation.
Key points
- The room is 16.2 m × 9.45 m × 5.125 m (about 153 m²) with 55 cabinets of 600 × 1200 × 2200 mm at 6 kW each in three rows in a hot/cold aisle pattern.
- Raised-floor case: two perimeter units of up to 230 kW and 45,900 m³/h each, 20 °C supply, a 0.64 m raised floor and 0.6 × 0.6 m floor grilles at 50% open area.
- Raised floor without containment: ASE 65.69%, RTI 77.94%, SHI 0.141. With CAC: ASE 85.57%, SHI 0.0027. With HAC: ASE 90.25%, RTI 90.94%, SHI 0.0024.
- Without containment, cabinet No. 19 had a mean inlet temperature of 30.1 °C and a maximum of 36.7 °C, and ten cabinets went above the 27 °C limit.
- In-row case: three units of 51.1 kW sensible and 10,200 m³/h each. Without containment ASE was 71.29% and SHI 0.145; with CAC, ASE 92.16%, ARE 99.88% and SHI 0.0015.
- With 6 kW heat-pipe rear-door coolers, cabinet inlet temperatures averaged about 21.5 °C and varied by no more than 2 °C within a cabinet; the room stayed at about 22 °C without aisle containment.
- Validation was code-to-code only: COMSOL against 6SigmaRoom gave a mean cabinet inlet temperature error below 10%, because the room was still under construction.
Using it in design
- Make aisle containment the default in raised-floor or in-row cooling: containment raised ASE from 65.69% to 85.57-90.25% and brought SHI close to zero.
- Show temperature-limit exceedance by cabinet (ten cabinets above 27 °C without containment) and check the worst cabinet (30.1 °C mean, 36.7 °C maximum) separately.
- Where aisle separation is not possible in high-density cabinets, consider heat-pipe rear-door coolers (for 6 kW cabinets, inlet about 21.5 °C) as an option.
- Label results that rest only on code-to-code validation in a hall under construction as preliminary design, not firm values.
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Who should read it
Cooling designers comparing raised-floor, in-row and rear-door cooling arrangements for new data halls.
Document contents
- 1 Introduction
- 2 Materials and methods (2.1 Physical model, 2.2 Numerical simulation: mathematical model, boundary conditions and solution settings, grid independence study and model)
- 3 Results and discussion (3.1 Option 1: precision air conditioners delivering air from the raised floor: without containment, CAC, HAC, quantitative analysis; 3.2 Option 2: horizontal air supply of inter-column air conditioners: without containment, CAC, HAC, quantitative analysis; 3.3 Option 3: backplane air conditioning and temperature field analysis)
- 4 Conclusion
Related standards
- ASHRAE TC 9.9 Thermal Guidelines for Data Processing Environments
Read the document
dc-airflow-thermal-optimization-2024.pdf
CC BY 4.0 — share with attribution
The document is provided unaltered because its licence permits redistribution.
Publication details
- Authors
- Di Jiang
- Publisher
- Frontiers in Built Environment (Frontiers Media SA)
- Year
- 2024
- Volume
- 10
- Pages
- 1362861
- Document language
- English
- Source type
- Scientific
- Access
- Open licence — downloadable
- Licence
- CC BY 4.0 — share with attribution
- Licence evidence
- www.frontiersin.org
Original licence note
PDF p.1 copyright notice: open-access article distributed under the terms of the Creative Commons Attribution License (CC BY).
Citation
Di Jiang (2024). Effects and optimization of airflow on the thermal environment in a data center. Frontiers in Built Environment (Frontiers Media SA). 10, 1362861. https://doi.org/10.3389/fbuil.2024.1362861
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