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Research Papers: Electronic Cooling

Reduced Order Thermal Modeling of Data Centers via Distributed Sensor Data

[+] Author and Article Information
Emad Samadiani

Yogendra Joshi

Woodruff School of Mechanical Engineering,  Georgia Institute of Technology, Atlanta, GA 30340yogendra.joshi@me.gatech.edu

Hendrik Hamann

 IBM T. J. Watson Research Center, Yorktown, NY 10598hendrikh@us.ibm.com

Madhusudan K. Iyengar

 IBM, Poughkeepsie, NY 12601mki@us.ibm.com

Steven Kamalsy

 IBM, Southbury, CT 06488stevekam@us.ibm.com

James Lacey

 IBM T. J. Watson Research Center, Yorktown, NY 10598jalacey@us.ibm.com

J. Heat Transfer 134(4), 041401 (Feb 13, 2012) (8 pages) doi:10.1115/1.4004011 History: Received March 24, 2010; Revised April 07, 2011; Published February 13, 2012; Online February 13, 2012

In this paper, an effective and computationally efficient proper orthogonal decomposition (POD) based reduced order modeling approach is presented, which utilizes selected sets of observed thermal sensor data inside the data centers to help predict the data center temperature field as a function of the air flow rates of computer room air conditioning (CRAC) units. The approach is demonstrated through application to an operational data center of 102.2 m2 (1100 square feet) with a hot and cold aisle arrangement of racks cooled by one CRAC unit. While the thermal data throughout the facility can be collected in about 30 min using a 3D temperature mapping tool, the POD method is able to generate temperature field throughout the data center in less than 2 s on a high end desktop personal computer (PC). Comparing the obtained POD temperature fields with the experimentally measured data for two different values of CRAC flow rates shows that the method can predict the temperature field with the average error of 0.68 °C or 3.2%. The maximum local error is around 8 °C, but the total number of points where the local error is larger than 1 °C, is only ∼6% of the total domain points.

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Copyright © 2012 by American Society of Mechanical Engineers
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Figures

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Figure 1

Typical air cooling system in data centers

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Figure 2

Layout of the data center facility

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Figure 3

Mobile Measurement Technology (MMT): 3D temperature mapping tool

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Figure 4

Temperature contours at the height of 1.07 m (3.5 ft) for two observations

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Figure 5

Rack inlet temperature at height of 1.98 m versus nominal CRAC flow rate percentage and CRAC power consumption

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Figure 6

Air temperatures of the reference field at inlets of (a) Rack A and (b) Rack C

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Figure 7

Energy percentage captured by each POD mode versus the mode number

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Figure 8

(a) Normalized POD mode#1 and (b) #6 at racks A inlet sensors

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Figure 9

(a) Measured temperatures, (b) POD generated temperatures, and (c) temperature errors for 84% of CRAC operation at inlet sensors of Racks A

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Figure 10

(a) Measured temperatures, (b) POD generated temperatures, and (c) temperature errors for 84% of CRAC operation at inlet sensors of Racks C

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Figure 11

(a) Measured temperatures, (b) POD generated temperatures, and (c) temperature errors for 68% of CRAC operation at inlet sensors of Racks A

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Figure 12

(a) Measured temperatures, (b) POD generated temperatures, and (c) temperature errors for 68% of CRAC operation at inlet sensors of Racks C

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