The work presented in this paper describes a simplified thermodynamic model that can be used for exploring optimization possibilities in air-cooled data centers. The model has been used to identify optimal, energy-efficient designs, operating scenarios, and operating parameters such as flow rates and air supply temperatures. The results of this analysis highlight the important features that need to be considered when optimizing the operation of air-cooled data centers, especially the trade-off between low air supply temperature and increased air flow rate. The model was shown to be especially valuable in defining the optimal operating strategies for enclosed aisle configurations with fixed and variable server flows, and to elucidate the deleterious effect of temperature nonuniformity at the inlet of the racks on the data center cooling infrastructure power consumption. The analysis shows a potential for as much as an 58% savings in cooling infrastructure energy consumption by utilizing an optimized enclosed aisle configuration with bypass recirculation, instead of a traditional enclosed aisle, where all the data center exhaust is forced to flow through the computer room air conditioners. The analysis of open-aisle data centers shows that as the temperature at the inlet of the racks becomes more nonuniform, optimal operation tends toward lower recirculation and higher power consumption; again, stressing the importance of providing as uniform a temperature to the racks as possible. It is also revealed that servers with a modest temperature rise (10°C) have a wider latitude for cooling infrastructure optimization than those with a high temperature rise (20°C), which tend to consume less cooling power when the aisles are enclosed.

1.
Salim
,
M.
, and
Tozer
,
R.
, 2010, “
Data Centers’ Energy Auditing and Benchmarking-Progress Update
,”
ASHRAE Trans.
0001-2505,
116
(
1
), pp.
109
117
.
2.
United States Environmental Protection Agency
, 2007, “
Report to Congress on Data Center Energy Efficiency
,” Public Law 109-431.
3.
Schmidt
,
R.
, and
Iyengar
,
M.
, 2006, “
Best Practices for Data Center Thermal and Energy Management—Review of Literature
,”
ASHRAE Trans.
0001-2505,
113
(
1
), pp.
206
218
.
4.
ASHRAE
, 2008,
Best Practices for Datacom Facility Energy Efficiency
,
American Society of Heating, Refrigerating and Air-Conditioning Engineers, Inc.
,
Atlanta, GA
.
5.
Lui
,
Y.
, 2010, “
Waterside and Airside Economizers Design Considerations for Data Center Facilities
,”
ASHRAE Trans.
0001-2505,
116
(
1
), pp.
98
108
.
6.
Schmidt
,
R.
, 2004, “
Thermal Profile of a High-Density Data Center—Methodology to Thermally Characterize a Data Center
,”
ASHRAE Trans.
0001-2505,
110
(
2
), pp.
635
642
.
7.
Schmidt
,
R.
,
Cruz
,
E.
, and
Iyengar
,
M.
, 2005, “
Challenges of Data Center Thermal Management
,”
IBM J. Res. Dev.
0018-8646,
49
, pp.
709
723
.
8.
ASHRAE
, 2008,
High Density Data Centers: Case Studies and Best Practices
,
American Society of Heating, Refrigerating and Air-Conditioning Engineers, Inc.
,
Atlanta, GA
.
9.
Shrivastava
,
S.
,
Iyengar
,
M.
,
Sammakia
,
B.
,
Schmidt
,
R.
, and
Vangilder
,
J.
, 2006, “
Experimental-Numerical Comparison for a High Density Data Center: Hot Spot Heat Fluxes in Excess of 500 W/ft2
,”
Proceedings of the IEEE ITHERM 2006
, San Diego, CA.
10.
Patel
,
C.
,
Bash
,
C.
,
Belady
,
L.
,
Stahl
,
L.
, and
Sullivan
,
D.
, 2001, “
Computational Fluid Dynamics Modeling of High Compute Density Data Centers to Assure System Inlet Specifications
,”
Proceedings of the ASME InterPACK 2001
, Kauai, HI.
11.
Patel
,
C.
,
Sharma
,
C.
,
Bash
,
C.
, and
Beitelmal
,
A.
, 2002, “
Thermal Considerations in Cooling Large Scale High Compute Density Data Centers
,”
Proceedings of the Inter-Society Conference of Thermal Phenomena
, pp.
767
776
.
12.
Shah
,
A.
,
Carey
,
V.
,
Bash
,
C.
, and
Patel
,
C.
, 2008, “
Exergy Analysis of Data Center Thermal Management
,”
ASME J. Heat Transfer
0022-1481,
130
, p.
021401
.
13.
Bash
,
C.
,
Patel
,
C.
, and
Sharma
,
R.
, 2006, “
Dynamic Thermal Management of Air Cooled Data Centers
,”
Proceedings of the ITHERM
, San Diego, CA.
14.
Boucher
,
T.
,
Auslander
,
D.
,
Bash
,
C.
,
Federspiel
,
C.
, and
Patel
,
C.
, 2004, “
Viability of Dynamic Cooling Control in a Data Center Environment
,” presented at the
IEEE ITHERM 2004
, Las Vegas, NV.
15.
Iyengar
,
M.
, and
Schmidt
,
R.
, 2007, “
Analytical Modeling of Thermodynamic Characterization of Data Center Cooling Systems
,”
ASME J. Electron. Packag.
1043-7398,
131
, p.
021011
.
16.
Pelley
,
S.
,
Meisner
,
D.
,
Wenisch
,
T.
, and
VanGilder
,
J.
, 2009, “
Understanding and Abstracting Total Data Center Power
,”
Proceedings of the 2009 Workshop on Energy Efficient Design (WEED)
.
17.
Hellmer
B.
, 2010, “
Consumption Analysis of Teleco and Data Center Cooling and Humidification Options
,”
ASHRAE Trans.
0001-2505,
116
(
1
), pp.
118
133
.
18.
Demetriou
,
D. W.
,
Khalifa
,
H. E.
,
Schmidt
,
R.
, and
Iyengar
,
M.
, “
Development and Validation of a Coupled Thermo-Hydraulic Model for Evaluating Data Center Energy Use
,”
HVAC&R Research
, in press.
19.
Walsh
,
E.
,
Breen
,
T.
,
Punch
,
J.
,
Shah
,
A.
, and
Bash
,
C.
, 2010, “
From Chip to Cooling Tower Data Center Modeling: Part I Influence of Server Inlet Temperature and Temperature Rise Across Cabinet
,”
Proceedings of the IEEE ITHERM
, Las Vegas, NV.
20.
Walsh
,
E.
,
Breen
,
T.
,
Punch
,
J.
,
Shah
,
A.
, and
Bash
,
C.
, 2010, “
From Chip to Cooling Tower Data Center Modeling: Part II Influence of Chip Temperature Control Philosophy
,”
Proceedings of the IEEE ITHERM
, Las Vegas, NV.
21.
Bejan
,
A.
, and
Ledezma
,
G. A.
, 1996, “
Thermodynamic Optimization of Cooling Techniques for Electronic Packages
,”
Int. J. Heat Mass Transfer
0017-9310,
39
(
6
), pp.
1213
1221
.
22.
Bejan
,
A.
, 1982,
Entropy Generation Through Heat and Fluid Flow
,
Wiley
,
New York
.
23.
Bejan
,
A.
, 1995,
Entropy Generation Minimization
,
CRC
,
Boca Raton, FL
.
24.
Wang
,
Z.
,
Bash
,
C.
,
Tolia
,
N.
,
Marwah
,
M.
,
Zhu
,
X.
, and
Ranhanathan
,
P.
, 2009, “
Optimal Fan Speed Control for Thermal Management of Servers
,”
Proceedings of the ASME InterPACK
, San Francisco, CA.
25.
Abdelmaksoud
,
W. A.
,
Khalifa
,
H. E.
,
Dang
,
T. Q.
,
Schmidt
,
R. R.
, and
Iyengar
,
M.
, 2010. “
Improved CFD Modeling of a Small Data Center Test Cell
,”
Proceedings of the IEEE ITHERM
, Las Vegas, NV.
26.
VanGilder
,
J.
,
Zhang
,
X.
, and
Shrivastava
,
S.
, 2007, “
Partially Decoupled Aisle Method for Estimating Rack-Cooling Performance in Near-Real Time
,”
Proceedings of the ASME InterPACK
, Vancouver, BC, Canada.
27.
Samadiani
,
E.
,
Joshi
,
Y.
,
Hamann
,
H.
,
Iyengar
,
M.
,
Kamalsy
,
S.
, and
Lacey
,
J.
, 2009, “
Reduced Order Thermal Modeling of Data Centers via Distributed Sensor Data
,”
Proceedings of the ASME InterPACK
, San Francisco, CA.
28.
Moore
,
J.
,
Chase
,
J. S.
, and
Ranganathan
,
P.
, 2006, “
Weatherman: Automated, Online and Predictive Thermal Mapping and Management for Data Centers
,”
Proceedings of the Third IEEE International Conference on Autonomic Computing
, pp.
155
164
.
29.
VanGilder
,
J. W.
, and
Shrivastava
,
S. K.
, 2007, “
Capture Index: An Airflow-Based Rack Cooling Performance Metric
,”
ASHRAE Trans.
0001-2505,
113
(
1
), pp.
126
136
.
30.
Sharma
,
R.
,
Bash
,
C.
, and
Patel
,
C.
, 2002. “
Dimensionless Parameters for Evaluation of Thermal Design and Performance of Large-Scale Data Centers
,”
Proceedings of the IEEE ITHERM
, San Diego, CA.
31.
Tozer
,
R.
,
Kurkjian
,
C.
, and
Salim
,
M.
, 2009, “
Air Management Metrics in Data Centers
,”
ASHRAE Trans.
0001-2505,
115
(
1
), pp.
63
70
.
32.
Demetriou
,
D. W.
, and
Khalifa
,
H. E.
, 2011, “
Evaluation of a Data Center Recirculation Non-Uniformity Metric Using Computational Fluid Dynamics
,” submitted to the ASME InterPACK, Portland, OR.
33.
Lawrence Berkeley National Laboratories
, 2007, “
Benchmarking: Data Centers—Charts
,” http://hightech.lbl.gov/benchmarking-dc-charts.htmlhttp://hightech.lbl.gov/benchmarking-dc-charts.html.
34.
Incropera
,
F. P.
,
DeWitt
,
D. P.
,
Bergman
,
T. L.
, and
Lavine
,
A. S.
, 2007,
Fundamentals of Heat and Mass Transfer
,
6th Ed.
,
Wiley
,
Hoboken, NJ
.
35.
Moore
,
J.
,
Chase
,
J.
,
Ranganathan
,
P.
, and
Sharma
,
R.
, 2005, “
Making Scheduling ‘Cool:’ Temperature-Aware Workload Placement in Data Centers
,”
Proceedings of the 2005 USENIX Annual Technical Conference
, pp.
61
74
.
36.
Tang
,
Q.
,
Gupta
,
S.
, and
Varsamopoulou
,
G.
, 2007, “
Thermal-Aware Task Scheduling for Data Centers Through Minimizing Heat Recirculation
,”
Proceedings of the IEEE Cluster
.
37.
Khalifa
,
H. E.
, and
Demetriou
,
D. W.
, 2010, U.S. Patent No. 61/367931.
38.
Tang
,
Q.
,
Gupta
,
S.
, and
Varsamopoulos
,
G.
, 2008, “
Energy-Efficient Thermal Aware Task Scheduling for Homogenous High-Performance Computing Data Centers: A Cyber-Physical Approach
,”
IEEE Trans. Parallel Distrib. Syst.
1045-9219,
19
(
11
), pp.
1458
1472
.
39.
ASHRAE
, 2009,
Fundamentals Handbook
,
American Society of Heating, Refrigerating and Air-Conditioning Engineers, Inc.
,
Atlanta, GA
.
40.
Marion
,
W.
, and
Urban
,
K.
, 1995,
User’s Manual for TMY2s: Typical Meteorological Year
,
National Renewable Energy Laboratory (NREL)
,
Golden, CO
.
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