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Research Papers

Thermally Aware, Energy-Based Load Placement in Open-Aisle, Air-Cooled Data Centers

[+] Author and Article Information
Dustin W. Demetriou

Research Assistant
Mem. ASME
Department of Mechanical and
Aerospace Engineering
e-mail: dustin.demetriou@gmail.com

H. Ezzat Khalifa

Professor
Mem. ASME
Mechanical and Aerospace Engineering
e-mail: hekhalif@syr.edu
Syracuse University,
Syracuse, NY 12344

ψT is the ratio of the perforated tile airflow to the required rack airflow. The perforated tile airflow is the cold air that is supplied through perforated tile in the cold aisle; however, this is not the cold air ingested by the IT equipment. Typically, the ingested cold air is less because of unintentional “spilling” of cold air out of the cold aisle and/or short-circuiting of cold air the CRAH units [39].

Contributed by the Electronic and Photonic Packaging Division of ASME for publication in the Journal of Electronic Packaging. Manuscript received April 26, 2012; final manuscript received July 6, 2013; published online July 24, 2013. Assoc. Editor: Saurabh Shrivastava.

J. Electron. Packag 135(3), 030906 (Jul 24, 2013) (14 pages) Paper No: EP-12-1048; doi: 10.1115/1.4024946 History: Received April 26, 2012; Revised July 06, 2013

This paper introduces a methodology for developing a reduced order model, using proper orthogonal decomposition (POD), to predict the IT rack's inlet temperature distribution within a raised floor air-cooled data center. The method used in this paper uses a limited set of computational fluid dynamics data at different useful IT levels and tile airflow fractions. The model was able to reconstruct these datasets to with 0.16 °C rms error and interpolate successfully for alternative configurations that were not included in the original dataset. The reduced order model can produce the temperature distribution in the data center in a fraction of a second on a standard personal computer. Several practical IT load placement options in open-aisle, air-cooled data centers, based on either geometrical traits of the data center, a prior physics-based knowledge of the airflow and temperature patterns or measurements that are easily obtainable during operation, are considered. The outcome of this work is the development of a robust set of guidelines that facilitate the energy efficient placement of the IT load amongst the operating servers in the data center. This work found that a robust approach was to use real-time temperature measurements at the inlet of the racks to remove the unnecessary IT load from the servers with the warmest inlet temperature. This strategy shows superior performance to the other strategies studied. The study considered the holistic optimization of the data center and cooling infrastructure for a range of data center IT utilization levels. The results showed that allowing for significant reductions in the supply air flow rate proved superior to providing a higher supply air temperature to meet the IT equipment's inlet air temperature constraint.

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References

Figures

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Fig. 1

Computational geometry

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Fig. 2

(a) Reconstruction error for 50% useful IT and (b) POD reconstruction comparison for different snapshots using 12 modes

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Fig. 6

Optimization flowchart

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Fig. 3

Mean of the rack's inlet temperature distribution from the 35 snapshots and the temperature reconstruction contours as the number of modes is increased

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Fig. 4

(a) Example error plots (rms and Max) for interpolated datasets and (b) POD interpolation comparison

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Fig. 5

Schematic of typical air-cooled data center cooling infrastructure

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Fig. 10

Summary of load placement analysis

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Fig. 7

Optimization results for 100% useful IT

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Fig. 8

Proposed load placement scenarios for 75% useful IT

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Fig. 9

Optimization results for different scenarios at 75% useful IT

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