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Experimentally Validated Computational Fluid Dynamics Model for Data Center With Active Tiles

[+] Author and Article Information
Jayati Athavale

George W. Woodruff School of
Mechanical Engineering,
Georgia Institute of Technology,
Atlanta, GA 30332
e-mail: jayati@gatech.edu

Yogendra Joshi, Minami Yoda

George W. Woodruff School of
Mechanical Engineering,
Georgia Institute of Technology,
Atlanta, GA 30332

1Corresponding author.

Contributed by the Electronic and Photonic Packaging Division of ASME for publication in the JOURNAL OF ELECTRONIC PACKAGING. Manuscript received September 18, 2017; final manuscript received November 29, 2017; published online March 2, 2018. Assoc. Editor: Ercan Dede.

J. Electron. Packag 140(1), 010902 (Mar 02, 2018) (10 pages) Paper No: EP-17-1087; doi: 10.1115/1.4039025 History: Received September 18, 2017; Revised November 29, 2017

This paper presents an experimentally validated room-level computational fluid dynamics (CFD) model for raised-floor data center configurations employing active tiles. Active tiles are perforated floor tiles with integrated fans, which increase the local volume flow rate by redistributing the cold air supplied by the computer room air conditioning (CRAC) unit to the under-floor plenum. The numerical model of the data center room consists of one cold aisle with 12 racks arranged on both sides and three CRAC units sited around the periphery of the room. The commercial CFD software package futurefacilities6sigmadcx is used to develop the model for three configurations: (a) an aisle populated with ten (i.e., all) passive tiles; (b) a single active tile and nine passive tiles in the cold aisle; and (c) an aisle populated with all active tiles. The predictions from the CFD model are found to be in good agreement with the experimental data, with an average discrepancy between the measured and computed values for total flow rate and rack inlet temperature less than 4% and 1.7 °C, respectively. The validated models were then used to simulate steady-state and transient scenarios following cooling failure. This physics-based and experimentally validated room-level model can be used for temperature and flow distributions prediction and identifying optimal number and locations of active tiles for hot spot mitigation in data centers.

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References

Patel, C. D. , Bash, C. E. , Sharma, R. K. , Beitelmal, A. , and Friedrich, R. J. , 2003, “ Smart Cooling of Data Centers,” ASME Paper No. IPACK-35059.
Bash, C. E. , Patel, C. D. , and Sharma, R. K. , 2006, “ Dynamic Thermal Management of Air Cooled Data Centers,” Tenth Intersociety Conference on Thermal and Thermomechanical Phenomena in Electronics Systems (ITHERM), San Diego, CA, May 30–June 2, pp. 445–452.
Shrivastava, S. , 2008, “ Cooling Analysis of Data Centers: CFD Modeling and Real-Time Calculators,” Ph.D. dissertation, Binghamton University, Binghamton, NY.
Boucher, T. , Auslander, D. M. , Bash, C. E. , Federspied, C. , and Patel, C. D. , 2006, “ Viability of Dynamic Cooling Control in a Data Center Environment,” ASME J. Electron. Packag., 282(2), pp. 137–144.
Beitelmal, M. H. , Wang, Z. , Felix, C. , Bash, C. , Hoover, C. , and McReynolds, A. , 2009, “ Local Cooling Control of Data Centers With Adaptive Vent Tiles,” ASME Paper No. InterPACK2009-89035.
Degree, 2016, “ Degree,” Degree Controls, Inc., Milford, NH, accessed Oct. 10, 2016, www.degreec.com/
Athavale, J. , Joshi, Y. , and Yoda, M. , 2016, “ Impact of Active Tiles on Data Center Flow and Temperature Distribution,” 15th IEEE Intersociety Conference on Thermal and Thermomechanical Phenomena in Electronic Systems (ITHERM), Las Vegas, NV, May 31–June 3, pp. 1162–1171.
Arghode, V. K. , Sundaralingam, V. , and Joshi, Y. , 2013, “ Airflow Management in a Contained Cold Aisle Using Active Fan Tiles for Energy Efficient Data-Center Operation,” Second International Workshop on Heat Transfer Advances for Energy Conservation and Pollution Control (IWHT), Xi'an, China, Oct. 18–21, pp. 246–256.
Schmidt, R. , Karki, K. , and Pantankar, S. , 2004, “ Raised-Floor Data Center: Perforated Tile Flow Rates for Various Tile Layouts,” The Ninth Intersociety Conference on Thermal and Thermomechanical Phenomena in Electronic Systems (ITHERM), Las Vegas, NV, June 1–4, pp. 571–578.
Rambo, J. , and Joshi, Y. , 2007, “ Modeling of Data Center Airflow and Heat Transfer: State of the Art and Future Trends,” Distrib. Parallel Databases, 21(3), pp. 193–225. [CrossRef]
King, D. , Ross, M. , Seymour, M. , and Gregory, T. , 2014, “ Comparative Analysis of Data Center Design Showing the Benefits of Server Level Simulation Models,” 30th Annual Semiconductor Thermal Measurement and Management Symposium (SEMI-THERM) San Jose, CA, Mar. 9–13, pp. 193–196.
Alissa, H. , Nemati, K. , Sammakia, B. , Ortega, A. , King, D. , Seymour, M. , and Tipton, R. , 2015, “ Steady State and Transient Comparison of Perimeter and Row-Based Cooling Employing Controlled Cooling Curves,” ASME Paper No. IPACK2015-48237.
Abdelmaksoud, W. , Dang, T. Q. , Khalifa, H. E. , Elhadidi, B. , Schmidt, R. , and Iyengar, M. , 2010, “ Experimental and Computational Study of Perforated Floor Tile in Data Centers,” 12th IEEE Intersociety Conference on Thermal and Thermomechanical Phenomena in Electronic Systems (ITHERM), Las Vegas, NV, June 2–5, pp. 1–10.
Alissa, H. A. , Nemati, K. , Sammakia, B. , Ghose, K. , Seymour, M. , and Schmidt, R. , 2015, “ Innovative Approaches of Experimentally Guided CFD Modeling for Data Centers,” 31st Thermal Measurement, Modeling & Management Symposium (SEMI-THERM), San Jose, CA, Mar. 15–19, pp. 176–184.
Zhang, X. , VanGilder, J. W. , Iyengar, M. , and Schmidt, R. R. , 2008, “ Effect of Rack Modeling Detail on the Numerical Results of a Data Center Test Cell,” 11th Intersociety Conference on Thermal and Thermomechanical Phenomena in Electronic Systems (ITHERM), Orlando, FL, May 28–31, pp. 1183–1190.
Iyengar, M. , Schmidt, R. R. , Hamann, H. , and VanGilder, J. , 2007, “ Comparison Between Numerical and Experimental Temperature Distributions in a Small Data Center Test Cell,” ASME Paper No. IPACK2007-33508.
Future Facilities, 2016, “ 6SIGMAROOM,” Future Facilities Ltd., London, accessed Jan. 24, 2018, https://www.futurefacilities.com/products/6sigmaroom/
Vertiv, 2016, “ Vertiv,” Vertiv Co., Columbus, OH, accessed Sept. 18, 2016, https://www.vertivco.com/
Arghode, V. K. , Kang, T. , Joshi, Y. , Phelps, W. , and Michaels, M. , 2015, “ Anemometric Tool for Air Flow Rate Measurement Through Perforated Tiles in a Raised Floor Data Center,” 31st Thermal Measurement, Modeling & Management Symposium (SEMI-THERM), San Jose, CA, Mar. 15–19, pp. 163–171.
TSI, 2016, “ Alnor Micromanometer AXD610,” TSI Inc., Shoreview, MN, accessed Mar. 16, 2016, http://www.tsi.com/alnor-micromanometer-axd610/

Figures

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Fig. 3

Experimental setup

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Fig. 2

Data center experimental facility

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Fig. 1

(a) Active tile and (b) numerical model representation for active tile

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Fig. 4

(a) Baseline model: isometric view and (b) baseline model: plan view

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Fig. 11

(a) Comparison of measured and predicted rack inlet temperature contour for baseline case, (b) comparison of measured and predicted rack inlet temperature contour for under-provisioned case, and (c) comparison of measured and predicted rack inlet temperature contour for exactly provisioned case

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Fig. 5

Model with single active tile

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Fig. 6

Model with aisle of active tile

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Fig. 7

Comparison of measured and predicted tile flow rate for baseline case

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Fig. 8

(a) Comparison of measured and predicted relative plenum pressure for different CRAC blower speeds and (b) comparison of measured and predicted total tile flow rate for different CRAC blower speeds

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Fig. 9

Plenum pressure contour for CRAC blower speed of 60%

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Fig. 10

Comparison of measured and predicted tile flow rate for different active tile fan speeds

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Fig. 12

Comparison of measured and predicted tile flow rate for an aisle of active tiles

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Fig. 13

(a) Comparison of measured and predicted relative plenum pressure for different active tile fan speeds and (b) comparison of measured and predicted total tile flow rate for different active tile fan speeds

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Fig. 17

Computer room air conditioning flow rate as a function of time for baseline case and an aisle of active tiles

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Fig. 21

Experimental setup—active tiles

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Fig. 22

Experimental setup—aisle with single active tile

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Fig. 18

Array of 16 anemometers for tile air flow rate measurement

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Fig. 19

Array of anemometers for rack air flow measurement

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Fig. 20

Experimental setup—aisle of passive tiles

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Fig. 14

(a) Pressure contour for baseline configuration and (b) pressure contour for configuration of aisle of active tiles

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Fig. 15

(a) Velocity contour for baseline configuration and (b) velocity contour for configuration of aisle of active tiles

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Fig. 16

Percentage leakage through raised floor as a function of CRAC blower speed and active tile fan speed

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