In raised floor data centers, tiles with high open area ratio or complex understructure are used to fulfill the demand of today's high-density computing. Using more open tiles reduces the pressure drop across the raised floor with the potential advantages of increased airflow and lower noise. However, it introduces the disadvantage of increased nonuniformity of airflow distribution. In addition, there are various tile designs available on the market with different opening shapes or understructures. Furthermore, a physical separation of cold and hot aisles (containment) has been introduced to minimize the mixing of cold and hot air. In this study, three types of floor tiles with different open area, opening geometry, and understructure are considered. Experimentally validated detail models of tiles were implemented in computational fluid dynamics (CFD) simulations to address the impact of tile design on the cooling of information technology (IT) equipment in both open and enclosed aisle configurations. Also, impacts of under-cabinet leakage on the IT equipment inlet temperature in the provisioned and under-provisioned scenarios are studied. In addition, a predictive equation for the critical under-provisioning point that can lead to a no-flow condition in IT equipment with weaker airflow systems is presented. Finally, the impact of tile design on thermal performance in a partially enclosed aisle with entrance doors is studied and discussed.

References

References
1.
Kang
,
S.
,
Schmidt
,
R.
,
Kelkar
,
K. M.
,
Radmehr
,
A.
, and
Patankar
,
S. V.
,
2000
, “
A Methodology for the Design of Perforated Tiles in Raised Floor Data Centers Using Computational Flow Analysis
,” The Seventh Intersociety Conference on Thermal and Thermomechanical Phenomena in Electronic Systems (
ITHERM
), Las Vegas, NV, May 23–26, pp.
215
224
.
2.
Schmidt
,
R. R.
,
Karki
,
K. C.
,
Kelkar
,
K. M.
,
Radmehr
,
A.
, and
Patankar
,
S. V.
,
2001
, “
Measurements and Predictions of the Flow Distribution Through Perforated Tiles in Raised-Floor Data Centers
,” The Pacific Rim/ASME International Electronic Packaging Technical Conference and Exhibition, Kauai, HI, July 8–13, Paper No. IPACK2001-15728.
3.
VanGilder
,
J. W.
, and
Schmidt
,
R. R.
,
2005
, “
Airflow Uniformity Through Perforated Tiles in a Raised-Floor Data Center
,”
ASME
Paper No. IPACK2005-73375.
4.
Ling
,
Y.-Z.
,
Zhang
,
X.-S.
,
Zhang
,
K.
, and
Jin
,
X.
,
2017
, “
On the Characteristics of Airflow Through the Perforated Tiles for Raised-Floor Data Centers
,”
J. Build. Eng.
,
10
, pp.
60
68
.
5.
Arghode
,
V. K.
,
Kang
,
T.
,
Joshi
,
Y.
,
Phelps
,
W.
, and
Michaels
,
M.
,
2017
, “
Measurement of Air Flow Rate Through Perforated Floor Tiles in a Raised Floor Data Center
,”
ASME J. Electron. Packag.
,
139
(1), p.
011007
.
6.
Karki
,
K. C.
, and
Patankar
,
S. V.
,
2006
, “
Airflow Distribution Through Perforated Tiles in Raised-Floor Data Centers
,”
Build. Environ.
,
41
(6), pp.
734
744
.
7.
Patankar
,
S. V.
,
2010
, “
Airflow and Cooling in a Data Center
,”
ASME J. Heat Transfer
,
132
(7), p.
073001
.
8.
Alkharabsheh
,
S.
,
Fernandes
,
J.
,
Gebrehiwot
,
B.
,
Agonafer
,
D.
,
Ghose
,
K.
,
Ortega
,
A.
,
Joshi
,
Y.
, and
Sammakia
,
B.
,
2015
, “
A Brief Overview of Recent Developments in Thermal Management in Data Centers
,”
ASME J. Electron. Packag.
,
137
(4), p.
040801
.
9.
Abdelmaksoud
,
W. A.
,
Khalifa
,
H. E.
,
Dang
,
T. Q.
,
Elhadidi
,
B.
,
Schmidt
,
R. 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
.
10.
Arghode
,
V. K.
,
Kumar
,
P.
,
Joshi
,
Y.
,
Weiss
,
T.
, and
Meyer
,
G.
,
2013
, “
Rack Level Modeling of Air Flow Through Perforated Tile in a Data Center
,”
ASME J. Electron. Packag.
,
135
(3), p.
030902
.
11.
Arghode
,
V. K.
,
Woodruff
,
G. W.
, and
Joshi
,
Y.
,
2016
, “
Modified Body Force Model for Air Flow Through Perforated Floor Tiles in Data Centers
,”
ASME J. Electron. Packag.
,
138
(3), p.
031002
.
12.
Joshi
,
Y.
, and
Kumar
,
P.
,
2012
,
Energy Efficient Thermal Management of Data Centers
,
Springer
,
New York
.
13.
U.S. Briefing
,
2013
, “
International Energy Outlook 2013
,” U.S. Energy Information Administration, Washington, DC.
14.
Bharath
,
M.
,
Shrivastava
,
S. K.
,
Ibrahim
,
M.
,
Alkharabsheh
,
S. A.
, and
Sammakia
,
B. G.
,
2013
, “
Impact of Cold Aisle Containment on Thermal Performance of Data Center
,”
ASME
Paper No. IPACK2013-73201.
15.
Makwana
,
Y. U.
,
Calder
,
A. R.
, and
Shrivastava
,
S. K.
,
2014
, “
Benefits of Properly Sealing a Cold Aisle Containment System
,” IEEE Intersociety Conference on Thermal and Thermomechanical Phenomena in Electronic Systems (
ITherm
), Orlando, FL, May 27–30, pp.
793
797
.
16.
Alissa
,
H. A.
,
Nemati
,
K.
,
Sammakia
,
B. G.
,
Seymour
,
M. J.
,
Tipton
,
R.
,
Mendo
,
D.
,
Demetriou
,
D. W.
, and
Schneebeli
,
K.
,
2016
, “
Chip to Chiller Experimental Cooling Failure Analysis of Data Centers: The Interaction Between IT and Facility
,”
IEEE Trans. Compon., Packag. Manuf. Technol.
,
6
(9), pp.
1361
1378
.
17.
Shrivastava
,
S. K.
, and
Ibrahim
,
M.
,
2013
, “
Benefit of Cold Aisle Containment During Cooling Failure
,”
ASME
Paper No. IPACK2013-73219.
18.
Khalili
,
S.
,
Alissa
,
H. A.
,
Tradat
,
M. I.
,
Nemati
,
K.
,
Sammakia
,
B.
, and
Seymour
,
M.
,
2017
, “
Experimental Methods to Characterize the Impact of Cross Flow Orientation on Jets of Air After a Perforated Tile
,” 33rd Thermal Measurement, Modeling and Management Symposium (
SEMI-THERM
), San Jose, CA, Mar. 13–17, pp.
163
171
.
19.
Alissa
,
H. A.
,
Nemati
,
K.
,
Sammakia
,
B.
,
Seymour
,
M.
,
Schneebeli
,
K.
, and
Schmidt
,
R.
,
2015
, “
Experimental and Numerical Characterization of a Raised Floor Data Center Using Rapid Operational Flow Curves Model
,”
ASME
Paper No. IPACK2015-48234.
20.
Alissa
,
H. A.
,
Nemati
,
K.
,
Sammakia
,
B. G.
,
Schneebeli
,
K.
,
Schmidt
,
R.
, and
Seymour
,
M. J.
,
2016
, “
Chip to Facility Ramifications of Containment Solution on IT Airflow and Uptime
,”
IEEE Trans. Compon., Packag. Manuf. Technol.
,
6
(1), pp.
67
78
.
21.
ASHRAE, 2012, “Thermal Guidelines for Data Processing Environments,” 3rd ed, American Society of Heating, Refrigerating and Air-Conditioning Engineers, Atlanta, GA.
22.
Arghode
,
V. K.
, and
Joshi
,
Y.
,
2013
, “
Modeling Strategies for Air Flow Through Perforated Tiles in a Data Center
,”
IEEE Trans. Compon., Packag. Manuf. Technol.
,
3
(5), pp.
800
810
.
23.
Sankar
,
S.
,
Shaw
,
M.
, and
Vaid
,
K.
,
2011
, “
Impact of Temperature on Hard Disk Drive Reliability in Large Datacenters
,” IEEE/IFIP 41st International Conference on Dependable Systems & Networks (
DSN
), Hong Kong, China, June 27–30, pp.
530
537
.
24.
Alissa
,
H. A.
,
Nemati
,
K.
,
Puvvadi
,
U. L.
,
Sammakia
,
B. G.
,
Schneebeli
,
K.
,
Seymour
,
M.
, and
Gregory
,
T.
,
2016
, “
Analysis of Airflow Imbalances in an Open Compute High Density Storage Data Center
,”
Appl. Therm. Eng.
,
108
, pp.
937
950
.
25.
Tradat
,
M.
,
Khalili
,
S.
,
Sammakia
,
B.
,
Ibrahim
,
M.
,
Peddle
,
T.
,
Calder
,
A.
,
Dawson
,
B.
,
Seymour
,
M.
,
Nemati
,
K.
, and
Alissa
,
H.
,
2017
, “
Comparison and Evaluation of Different Monitoring Methods in a Data Center Environment
,”
ASME
Paper No. IPACK2017-74105.
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