COMPARATIVE ANALYSIS OF WIDELY USED AIR CONTAINMENT SYSTEMS
IN COMMERCIAL DATA CENTERS FOR MAXIMUM
COOLING PERFORMANCE
by
KASTURI RANGAN RAJAGOPALAN
Presented to the Faculty of the Graduate School of
The University of Texas at Arlington in Partial Fulfillment
of the Requirements
for the Degree of
MASTERS OF SCIENCE IN MECHANICAL ENGINEERING
THE UNIVERSITY OF TEXAS AT ARLINGTON
AUGUST 2013
Copyright © by Kasturi Rangan Rajagopalan 2013
All Rights Reserved
ACKNOWLEDGEMENTS
I am really thankful to my advisor Prof. Dereje Agonafer for his continuous guidance and
support over the last two years of my research and study at the University of Texas at Arlington. It
has been an awesome learning process for me under his expertise in terms of understanding the
core concepts of engineering and in order to become a wonderful CFD engineer. His inspiration
and motivation is totally an unforgettable experience.
I would like to thank Prof. Haji Sheikh and Prof. Kent Lawrence for serving to be a part of
my committee. I would also like to take the opportunity to thank Deepak Sivanandan
CommScope Inc. and other Industry mentors for all their continuous support and feedback in the
projects I have worked.
I am obliged to Ms. Sally Thompson who has been of wonderful help in assisting me in all
official procedures. I also want to thank the entire EMNSPC team, especially Betsegaw
Gebrehiwot. Next I would like to thank Fahad Mirza, John Fernandez, Richard Eiland and
Marianna Vallejo for all their guidance provided. I would also like to acknowledge the help and
support extended by all my friends and colleagues who have made my stay at UTA a great
venture.
Finally, this acknowledgement would not be complete without mentioning my parents,
Mr. Rajagopalan and Mrs. Mala Rajagopalan who have served as my motivation and inspiration.
I am grateful to them for providing their continuous support to pursue my goals.
July 08, 2013
iii
ABSTRACT
COMPARATIVE ANALYSIS OF WIDELY USED AIR CONTAINMENT SYSTEMS
IN COMMERCIAL DATA CENTERS FOR MAXIMUM
COOLING PERFORMANCE
Kasturi Rangan Rajagopalan, M.S.
The University of Texas at Arlington, 2013
Supervising Professor: Dereje Agonafer
Many data centers implement containment systems to improve cooling system
performance. Literature review shows that Hot Aisle Containment System (HACS) have higher
supply air temperature set point than Cold Aisle Containment Systems (CACS) [1]. CACS in data
centers have claims to support higher density loads when compared to HACS systems [2]. Data
center owners suggest that containment of a group of racks can be a very effective technique to
improve cooling performance. On the other hand, others suggest that fewer area for containment
is better than no containment in data centers that favours the partially contained architectures of
HACS and CACS [3].The optimum containment architecture in terms of cooling and saving power
is becoming imperative for every data center nowadays.
In this study, a data center from published literature is modeled in a commercially
available computational fluid dynamics (CFD) tool and simulation results of this model are
validated with the published paper [4]. The data center is a hot aisle/cold aisle raised floor data
center. Cooling is provided with one computer room air conditioning (CRAC) unit to the data
center room. The raised floor data center is implemented with various containment architectures
iv
ranging from partial containment to full containment of racks. There are eight configurations that
are compared in terms of fan power and Inlet supply temperature for the servers. The objective of
this study is to compare the cooling performances for these eight cases and determine the
reasons behind them and also come up with new guidelines for the data center owners.
v
TABLE OF CONTENTS
ACKNOWLEDGEMENTS ........................................................................................... ……………..iii
ABSTRACT ..................................................................................................................................... iv
LIST OF ILLUSTRATIONS............................................................................................................. viii
LIST OF TABLES ............................................................................................................................xii
Chapter
Page
1. INTRODUCTION TO DATACENTER COOLING…………………..………..….............. .1
1.1 Modern Data Centers ...................................................................................... .1
1.2 Types of Data Centers .................................................................................... .2
1.3 Literatures in Data Center Cooling .................................................................. .2
2. PRIME CHALLENGES FACED IN THE DATACENTER ............................................... 7
2.1 Venturi Effect .................................................................................................... 7
2.2 Recirculation of Airflow ..................................................................................... 8
2.3 Bypass Airflow ................................................................................................ 10
3. LITERATURE REVIEW ON CONTAINMENT TECHNIQUES ..................................... 13
3.1 Hot Aisle Containment System ...................................................................... 13
3.2 Cold Aisle Containment System .................................................................... 14
3.3 Hot aisle / Cold aisle ..................................................................................... 14
3.4 Partial Containment System .......................................................................... 15
3.5 Merits of the Containment System ................................................................. 16
3.6 Reasons for Containment System ................................................................. 16
vi
4. SELECTION OF AIR CONTAINMENT SYSTEMS ...................................................... 17
4.1 Logical Selection of Air containment systems ............................................... 17
4.2 Conditions recommended for Ducted HACS ................................................. 18
4.3 Conditions recommended for CACS .............................................................. 19
5. CFD PROBLEM SPECIFICATION............................................................................... 20
5.1 Problem Description ...................................................................................... 20
5.2 Over Heated Server Sets .............................................................................. 20
5.3 Fan power ..................................................................................................... 21
6. DATA CENTER CFD MODELING ............................................................................... 23
6.1 Cabinet Model Description ............................................................................. 23
6.2 CRAC Model Description ............................................................................... 28
6.3 Ceiling drop duct specification ....................................................................... 29
6.4 Air Containment Systems CFD Models ......................................................... 30
7. RESULTS AND ANALYSIS ......................................................................................... 39
7.1 Case 1 – Results and Analysis ...................................................................... 39
7.2 Case 2 – Results and Analysis ...................................................................... 41
7.3 Case 3 – Results and Analysis ...................................................................... 42
7.4 Case 4 – Results and Analysis ...................................................................... 45
7.5 Case 5 – Results and Analysis ...................................................................... 45
7.6 Case 6 – Results and Analysis ...................................................................... 46
7.7 Case 7 – Results and Analysis ...................................................................... 47
7.8 Case 8 – Results and Analysis ...................................................................... 50
7.9 Summary of Analyzed Results for Eight Cases ............................................. 51
8. CONCLUSION AND FUTURE WORK ........................................................................ 53
vii
REFERENCES ............................................................................................................................... 55
BIOGRAPHICAL INFORMATION .................................................................................................. 59
viii
LIST OF ILLUSTRATIONS
Figure
Page
1. A Sun Microsystems datacenter … .............................................................................................. 1
2. Airflow management in a datacenter............................................................................................ 4
3. Fluid flow shown in Venturi tube .................................................................................................. 7
4. Pressure differential in the Venturi tube ...................................................................................... 8
5. Recirculation of Airflow ................................................................................................................. 9
6. Bypass Airflow ........................................................................................................................... 11
7. Leakage through cable outlets ................................................................................................... 11
8. Under floor airflow path blocked by cables ................................................................................ 11
9. Hot aisle containment system .................................................................................................... 13
10. Cold aisle containment system ................................................................................................ 14
11. Partial Containment Air flow management ............................................................................... 15
12. Partially contained (End of Aisle) ............................................................................................ 16
13. Selection of Air Containment Systems for the comparison study ............................................ 16
14. Pros and Corns of Air Containment Systems for the comparison study .................................. 18
15. Ducted Hot Aisle Containment System .................................................................................... 18
16. Cold Aisle Containment System (CACS) ................................................................................. 19
17. Cabinet front and rear .............................................................................................................. 20
18. Equation for calculation of Fan power ...................................................................................... 20
19. The side view of the CRAC unit CFD model ............................................................................ 21
20. Equation for flow rate through the racks .................................................................................. 22
21. Cabinet simple model ............................................................................................................... 23
ix
22. System resistance curve for the experimental server .............................................................. 25
23. System resistance curve for the advanced resistance model .................................................. 26
24. Fan curve for the advanced resistance model … .................................................................... 27
25. Equation for the advanced resistance model ........................................................................... 27
26. Reduced equations for the advanced resistance model ......................................................... 28
27. CRAC unit CFD model ............................................................................................................. 28
28. Ceiling drop duct in raised floor datacenter CFD model .......................................................... 29
29. Isometric view of the data center room layout. ........................................................................ 30
30. Case 1 Hot aisle / cold aisle datacenter ................................................................................... 31
31. Case 2 Data center contained with both the cold aisle ............................................................ 32
32. Case 3 Data center contained with first cold aisle alone ......................................................... 33
33. Case 4 Datacenter contained with second cold aisle alone..................................................... 34
34. Case 5 Data center contained with all the three hot aisles ...................................................... 35
35. Case 6 Data center contained with first and second hot aisle alone ....................................... 36
36. Case 7 Data center contained with first and third hot aisle alone ............................................ 37
37. Case 8 Data center contained with second and third hot aisle alone ...................................... 38
38. Server sets which are considered as over heated ................................................................... 39
39. The maximum temperature observed in server sets is 35°C ................................................... 40
40. The pressure surface plot for the cabinet showing maximum temperature. ............................ 40
41. The velocity surface plot for the cabinet showing maximum temperature ............................... 41
42. Temperature surface plot X axis through midsection cabinets A3- D3 ................................... 42
43. Cabinets which are considered to be over heated in case 3 .................................................. 43
44. Temperature surface plot X axis through A3- D3 .................................................................... 43
45. Temperature surface plot for the cabinet showing maximum temperature.............................. 44
46. The pressure surface plot for the cabinet showing maximum temperature ............................. 44
x
47. The velocity surface plot for the cabinet showing maximum temperature ............................... 44
48. Cabinets which are considered to be over heated in Case 4 .................................................. 45
49. Temperature surface plot X axis through cabinets A3 - D3 ..................................................... 45
50. Temperature surface plot X axis through cabinets A1-D1 ...................................................... 46
51. Temperature surface plot X axis through cabinets rows A3-D3 ............................................. 46
52. Temperature surface plot X axis through midsection cabinets A1-D1…. ................................ 46
53. The server sets in the cabinet which show higher temperature in case 7 ............................... 47
54. The temperature surface plot for the cabinet with maximum temperature .............................. 48
55. The pressure surface plot for the cabinet exhibiting maximum temperature ........................... 48
56. The velocity surface plot for the server set in cabinets showing 26ºC ..................................... 49
57. Temperature surface plot through X axis midsection cabinets through A3-D3 ....................... 50
58. Temperature surface plot through X axis midsection cabinets through A1-D1 ....................... 51
xi
LIST OF TABLES
Table
Page
1. Cabinet Model Specifications – Simple model ........................................................................... 24
2. Cabinet Model Specifications - Advanced Resistance model .................................................... 24
3. Pressure drop at various fan speeds across the servers ........................................................... 26
4. CRAC Model Specification ......................................................................................................... 29
5. Analyzed cooling performance for Case 1 ................................................................................. 41
6. Analyzed cooling performance for Case 2 ................................................................................. 42
7. Analyzed cooling performance for Case 3 ................................................................................. 44
8. Analyzed cooling performance for Case 4 ................................................................................. 45
9. Analyzed cooling performance for Case 5 ................................................................................. 46
10. Analyzed cooling performance for Case 6 ............................................................................... 47
11. Analyzed cooling performance for Case 7 ............................................................................... 50
12. Analyzed cooling performance for Case 8 ............................................................................... 51
13. Summary of analyzed results for all the eight cases............................................................... .52
xii
CHAPTER 1
INTRODUCTION TO DATACENTER COOLING
1.1 Modern Data center
Data centers have high concentrations of computers and digital equipment dedicated to
housing websites and provides an essential service for new digital economy. These datacenters
centralize and consolidate information technology (IT) sources, enabling the organizations to
conduct business round the clock and around the world [5]. Data centers are mission
criticafacilities and the nerve center for various successful business operations [6].
Figure 1 A Sun Micro systems datacenter [7]
Data center is a facility used for housing the equipment responsible for storing and
processing information. They typically consist of the servers used for transferring, storing and
1
managing data or information [8]. The computers used in datacenters are known as servers.
Multiple servers are stored in these racks. These racks are placed in a raised floor or slab floor.
The heat produced by the servers is removed by passing cold air through the cabinets. This
cold air is extracted by the server fans and the hot air is returned through the rear of the
servers. The uninterrupted power supply is placed away from the servers. There is a mixing of
hot and cold air, bypass of hot air directly to the CRAC unit, as well as the recirculation of hot air
in the data center. The air flow pattern inside the datacenter plays a vital role for the efficient
performance of the data centers.
1.2 Types of Data Centers
Most of the data centers fall into two major categories.
a Private Data center (PDC)
Private data centers are owned and operated by the private corporations with main
focus on supporting data processing and web oriented services for their own organizations.
Private data centers provide connectivity, application services and support to thousands of
company employees working with in the building, campus [9].
b Internet Data center (IDC)
Internet data centers are owned and operated by the traditional telecoms and they
provide competitive service providers. These services include wide area communications,
internet access, also web and application hosting [9].
1.3 Literatures in Data Center cooling
Kwok Wu compared Kool IT from Afco Systems, In Row cooling with Hot aisle
containment from APC, Cold aisle containment by Knur and Overhead cooling by Liebert [10].
These systems were compared for effectiveness, efficiency, control, and robustness. The data
center has 100 Cabinets ,45 % open area ratio for tiles, 2 ft. raised floor, 12 ft. ceiling from the
bottom of the raised floor plenum.
2
The goal of cold aisle containment is to maximize the utilization of air coming from the
perforated floor [10].The energy consumed in the datacenter is mainly due to UPS
(Uninterrupted Power supply), power distribution units, IT equipment; cooling equipment,
lighting and power back up.
A study by Boucher et.al [11] provides guidance for effective heat transfer and cooling
performance in data centers by automated control using sensors. The control technique
consists of a sensor which controls the supply temperature of the CRAC unit and also measures
heat dissipation. The requirements that are used essentially in this technique are distributed
sensor network, the ability to vary localized cooling and having insight of how each variable
affect the conditions of the data center.
Kukri et.al [8] focused on the techniques used for air flow distributions. He used a
mathematical model to test their effectiveness. The air flow distribution techniques depends on
the plenum height, area of the perforated tiles, position of the CRAC units and the presence of
the under floor blockages.
Baedeker et.al [13] studied the effect of altering the location of CRAC units in the raised
floor datacenter. It was found that that the performance of the data center is influenced by the
CRAC unit location. It was also found that it also depends on air flow entering the cabinets.
Beaty et.al [14] has studied the cooling performance resulting from changing the
location of CRAC units with respect to the racks. The final prediction of this study was that the
racks which have clear path for hot air to the CRACs show lower inlet temperatures. The study
suggested that CRACs can be placed facing the hot aisles rather than facing the cold aisles.
Nakao et.al [15] modeled datacenters with four variations of datacenter cooling
configuration in their computational study. The cooling models of the datacenters consisted of a
supply through the under floor with exhaust through the ceiling, a supply through the under floor
3
with the horizontal exhaust, a supply over head with exhaust through the under floor and a
overhead supply with exhaust through the ceiling.
Figure 2 Airflow management in a data center
Shrivastava et.al [16] studied different datacenter configurations. A CFD model were
constructed to analyze the effectiveness of the configurations. The analysis study characterized
the datacenter performance based on the average region Rack Inlet Temperature (RIT
) and mean region RIT. The results proved that, for a particular datacenter, under floor supply
and ceiling return configuration were very efficient. The analysis study considered factors such
4
as, supply air flow fraction, the ceiling height and the location of the return vent. It was also
found that the supply air flow fraction is highly influences rack inlet temperature in the
configurations of the data center studied.
Schmidt and Iyengar [16] discussed the suitability of air flow configurations for high
density datacenters. The under floor and overhead configurations were used for this study.
A CFD model was constructed for both the configurations to compare the air supply
fraction and rack location along the height of the rack. High temperature gradients in the rack
inlet temperatures were seen in these configurations [16]. It was also found that the rack inlet
temperatures were more pronounced in under floor configuration compared with the overhead
supply configuration.
Roger et.al [17] studied the effect of the rack inlet temperature resulting from the chilled
air that exits from the outlet of the perforated tiles. The tiles were situated in both the hot and
cold aisles of the raised floor datacenter.
A computational model [17] of the room was built with electronic equipment installed on
the raised floor with a particular focus on effect of rack inlet temperature of IT equipment load,
placing the air conditioning units and chiller flow rates.
The results suggested that, increasing the air flow rate at the tiles decreases the inlet
air flow temperature for the servers. It was also found that it was important to use chilled air at
the CRAC units placed in the cold aisle in order for the air to enter the front of the racks [17].
Bhopte et.al [18] studied that the height of the under floor, ceiling height, and the cold
aisle width affects the rack inlet air temperatures. Ceiling height, under floor height were
maintained constant in this study.
The lay out consisted of a raised floor platform with room return from the cabinets.
Based on the findings, [18] a multivariable optimization methodology was proposed to decrease
the server inlet temperature for the CFD model of the raised floor datacenter. The study utilized
5
the under floor height and ceiling height as the two design variables for this optimization
technique.
6
CHAPTER 2
PRIME CHALLENGES FACED IN THE DATA CENTER
The prime airflow management issues that the data center industry faces these days
are the Venturi effect, recirculation of air flow and air by pass. The efficiency of the CRAC unit to
cool the datacenter is affected by the above mentioned challenges. This affects the cooling
power which is directly associated with the cooling cost spent in the datacenters.
2.1 Venturi Effect
Venturi effect is the reduction of fluid pressure when the fluid passes through the
narrow constricted section of pipe [47]. The fluid mechanic principle behind the Venturi effect is
that the velocity of the fluid must increase through the constriction to satisfy the continuity
equation whereas, its pressure must decrease to balance the conservation of energy. The gain
in kinetic energy is balanced by the drop in pressure. The pressure drop as a result of Venturi
effect may be derived from a combination of Bernoulli’s principle and equation of continuity [47].
Figure 3 Fluid flow shown in Venturi tube [49]
7
Figure 4 Pressure differential in Venturi tube [49]
The limitation of the Venturi effect occurs when a fluid reaches the state of choked flow
where, the velocity of the fluid approaches the local speed of sound. In the case of choked flow,
the mass flow rate remains constant and does not increase or decrease in the downstream
pressure environment [49]
2.2 Recirculation of air flow
Some portion of air that exits out of the outlet of the server exhaust, cycles back to the
server inlet. This phenomenon in air flow is called recirculation of air flow [19]. In the modern
datacenters, most of the hot air in aisle returns back to the CRAC unit [6]. But small portion of
air may mix into the cold aisle from the top or bottom of the racks or from the side of the racks.
The recirculation can also occur due to reversed air flow in certain IT equipments, whenever the
internal fans of the IT equipment blows the hot exhaust air from hot aisle directly to cold aisle.
Thus, the recirculated air is always a part of inlet air that flows to the racks in the raised floor
data center [19].
a Effect of recirculated air [19]
1. The datacenter cooling efficiency is affected due to entropy change owing to recirculated air.
8
2. The hot spot are formed in the servers due to recirculation of air.
Figure 5 Recirculation of Airflow [19]
3. The numbers of CRAC units operated must be increased to compensate the hike in
temperature.
b Measures to prevent recirculation of air [19]
1. Fitting of blanking plates in the cabinet in the locations where the blade servers are not fixed.
2. Gaps in the cabinet needs to be closed at the areas where the warm air can seep into the
inlet.
3. An adequate supply of cold air should be ensured for the all the servers in the data center.
4. The air distribution at the server inlet should be made sure to reach all the servers in the
cabinet.
5. The path for the return air from the cabinet should be checked for duct work if needed.
9
6. Cold air supply should be isolated from the hot air streams wherever needed.
7. Obstructions under the floor that restricts the cold air stream should be removed.
8. The proper routing for the cables through the under floor and at the back of the cabinets
should be made sure to be away from the airflow path.
2.3 By pass Air flow
The air that enters the perforated tiles returns back to the CRAC unit without cooling the
servers. This is termed as Bypass Air flow. The supply air from the CRAC unit enters the under
floor and penetrates the perforated tiles. This air directly moves to the CRAC or cooler return
without entering the server.
Figure 6 Bypass Airflow [20]
a Effects of Bypass Air flow
1. The CRAC return temperature is increased because of the bypass Air flow.
2. The cold air reduces the static pressure resulting in poorly distributed airflow through the cold
aisle.
10
3. The hot spots are present in high heatload areas which occurs due to Bypass Air Flow.
Figure 7 Leakage through cable outlets [4]
Figure 8 Under floor airflow path blocked by cables [4]
11
b Best practices to prevent bypass air in datacenter [19].
1. Air gaps in the raised floor should be sealed with the foam brushes or pillows.
2. Floor grills if present at the hot aisles should be removed if cooling is not necessary.
3. The air flow from the floor grills should be optimized not to overshoot the cabinet top.
4. The back draft dampers need to installed on the idle CRAC units as they are the source of
air by pass.
5. Duct extensions should be installed on the CRAC return air paths to have increased height
for the air intake.
12
CHAPTER 3
LITERATURE REVIEW ON CONTAINMENT TECHNIQUES
3.1 Hot Aisle Containment System
The hot aisle containment collects the server exhaust air and restricts its entry to the
rest of the datacenter. In one of the hot aisle containment types, the hot aisle is sealed with
doors, side walls or roofs [21]. The CRAC unit cools the servers and the rest of the remaining
room without allowing them to get overheated. In other arrangements, the data center room
have specialized cabinets with solid rear door and there is also an attached duct that leads to
the false ceiling. The server cabinets collect the exhaust air off the servers and transfer it into
the false ceiling. This exhaust air is finally driven back to the air conditioning unit. The setting
above mentioned may or may not contain fans which may remove exhaust air from servers
efficiently
Figure 9 Hot aisle containment system [2]
13
3.2 Cold Aisle Containment System
Cold aisle containment provides physical separation between the hot and cold air by
isolating the cold aisle. This containment technique sets apart the cold air from the room. It uses
the metal, curtain to concentrate the cold air at the server inlet. By this technique, the cold air
compulsorily passes through the server racks cooling the racks before entering the rest of the
room. The importance of the cold aisle containment is that, they are good for the existing
datacenters without hot air return but, focused cooling on the IT equipment eliminating the rest
of the room. They also support high density loads in datacenters. [22] The cold aisle
containment provides optimum cold air to enter the IT equipment by aiding for the uniform inlet
temperatures [6].
Figure 10 Cold aisle containment system [2]
3.3 Hot Aisle / Cold Aisle
The Hot aisle / Cold aisle are design lay out for server racks and other computing
equipment in the data centers. [24] In this layout, the servers are arranged to form a separate
14
hot and cold aisle. This helps to save energy by allowing air supply at lower operating
temperatures than hot aisle containment: [25]
Figure 11 Partial Containment Air flow management [26]
3.4 Partial Containment System
`
“End of Aisle” is one of the preferred partial containment technique used in the
datacenters. In this technique, the end of the cold aisle is contained with the doors on each
ends. These doors allow for the stratification of the air and help to reduce the temperatures in
the cold aisle. [27]. The partial containments system is said to have double or even triple the
power density limits in the data center rooms. The partial containment products are
advantageous in terms of reduced bypass airflow, increased usable cooling unit capacity and
maximized efficiency for HVAC equipments [28].The essential reasons to implement the partial
containment systems are, to improve CRAC efficiency, to aid in simple installation, to be
effective at cold aisle proximity. [38]
15
3.5 Merits of the Containment systems [27]
1. Cooling systems can be set at higher supply temperatures that helps in increasing
Figure 12 Partially contained (End of Aisle) [38]
the cooling capacity with lesser frequent hot spot formation.
2. Amount of economization hours is increased since the cooling system is turned off for a
longer period of time.
3. The humidification cost is increased since containment technique helps to eliminate the
mixing of hot and cold air.
4. The containment aids in better infrastructure utilization and right sizing that has decreased
the datacenter’s dependency on required fan power.
3.6 Reason for implementation of Containment Systems [48]
1. The containment systems are essential to improve CRAC’s efficiency.
2. The containment is highly effective for areas where CRAC units are close to the cold aisles.
3. They are proven for their effectiveness and simple installation of their frame work.
16
CHAPTER 4
SELECTION OF AIR CONTAINMENT SYSTEMS
4.1 Logical Selection of Air containment systems
This chapter briefly describes the logical steps for deciding which airflow management
solutions to implement starting with, assessing the datacenter facility, reviewing the possible
solutions and selecting the right containment solutions.
Figure 13 Selections of Air Containment Systems for the Comparison Study [29]
The containment methods responsible for cooling are classified according to hot air and
cold air and further classified according to their purposes especially for cooling the racks or
cooling the servers [29].
17
Figure 14 Pros and Corns for Air Containment Systems for the comparison study [29]
4.2 Conditions Recommended for Ducted HACS [30]
1. The racks and IT equipments need to be alligned in the hot / cold aisle configuration [48].
Figure 15 Ducted Hot Aisle Containment System [30]
18
2. When the drop ceiling is present for the Hot air return path [7].
3. When Individual IT equipments are placed on the data center perimeter [31].
4. When data center is frequently occupied by workers with less hotter enviroment [30].
Figure 16 Cold Aisle Containment System (CACS) [30]
4.3 Conditions Recommended for CACS [30]
1. When IT equipment and racks are aligned in a hot aisle / cold aisle pattern of air
containment [29].
2. When the data center makes use of raised floor platform and flooded return air distribution
[32] technique.
3. When there are no individual separate IT devices on the perimeter of the data center room.
4. When the racks are fully packed and unable to draw enough cool air from the raised floor.
5. When the project of air containment has a shorter period of time for the implementation.
19
CHAPTER 5
CFD PROBLEM SPECIFICATION
5.1 Problem Description
1. The containment techniques modeled are essentially Hot Aisle / Cold Aisle, full Hot Aisle
Containment System [29], full Cold Aisle Containment System, Partial hot aisle containment
system and Partial cold aisle containment system which are basically from the earlier
mentioned containment system.
2. The objective of this case study is to compare these containment techniques in separate CFD
platform and find out which technique is the best in terms of maximum cooling performance at
reduced fan power consumption. There are eight cases studied in CFD platform compared for
this cooling performance study.
5.2 Overheated Server sets [33]
This value is the number of servers in the cabinets that have server inlet temperatures
over 77°F with air conditioning units at a set point of 64.4°F.
Figure 17 Cabinet front and rear
20
It is essential to observe the amount of racks overheated by implementing containment
configurations. This gives an idea of which configuration provides the most effective
containment. The location of these racks in the cabinets in relation to the air conditioning units is
very important. [33]
5.3 Fan power [34]
The fan power or the pump power to drive the air throughout the data center depends
on mass flow rate, the liquid density and the differential height.
Figure 18 Equation for calculation of Fan power
In the above figure, P is the pumping power in Watts, ρ is the fluid density in Kg/m³, and q is
the flow rate in m³/s, h is the head difference in meter and g is the acceleration due to gravity
which is 9.8065 m /s².
a Pressure drop calculation: [35]
Figure 19 The side view of the CRAC unit CFD model [35]
A volume region using the FloVENT smart part of size (2.4*0.152*0.9) each below the
supply and above the return side of the CRAC unit to calculate the average pressure in the
21
supply side and the average pressure in the return side of the CRAC unit. The averaged
pressure drop is calculated from the values form the supply and return side of the CRAC unit.
b Heat load calculation: [48]
There are two main functions for a data center cooling system [48]. The first function is
to remove heat from datacenter and second function is to effectively distribute this cool air to the
data center equipment.
c Flow rate through racks: [18]
The heat removal rate is a function of the temperature difference across the server
intake and exhaust and also function of volumetric flow rate.
Figure 20 Equation for flow rate through the racks [36]
In the above figure, ΔT is the temperature difference across the racks, Q is the heat
removal rate and CFM is the measure of volumetric flow rate [48].
22
CHAPTER 6
DATA CENTER CFD MODELING
6.1 Cabinet Model Description
a Cabinet model description –(Simple model)
Supply side
side
Rack 1
Rack 2
Extract side
Rack 3
Figure 21 Cabinet simple model [35]
The cabinet assembly consists of an outer chassis with three racks. This allows for the
heat load at lower, middle and higher levels. Three fans are placed at the rack supply to pull the
air through the rack system. The model is also flexible to allow different flow rates through the
three levels to coincide with the different sources. The sources attached inside the cabinet
define equal heat on each thirds of the cabinet. The source also straightens the flow preventing
23
vertical flow. The front door is divided into three sections to allow analysis of the air
temperatures at lower, middle and upper door sections.
Table 1 Cabinet Model Specifications – Simple model
Cabinet Model Geometric Parameters
Cabinet dimensions
Value/info
(0.9*2*2.4) m
Number of racks per cabinet
3
Temperature difference across the cabinet
11°C
Extract and supply dimensions
(0.6*0.6) m
Cabinet heat load
2.67 KW
b Cabinet model description – (Advanced) [35]
The cabinet model considered for this study is advanced resistance model .This cabinet
is specified with the system curve and fan curve input. The server used in this cabinet is an Intel
Xeon 5500, 350 Watt processor. The experimental data of the system resistance curve of this
Face book server has been implemented in the Flo-VENT code. Each rack of the cabinet is
represented as a set of servers. Single rack accommodates nine servers. There are in total 27
servers in the cabinet model.
Table 2 Cabinet Model Specifications - Advanced Resistance Model [35]
Cabinet Model Geometric Parameters
Value/info
Cabinet dimensions [35]
(0.9*2*2.4) m
Number of server sets per cabinet
3
Number of servers in server set
9
Number of servers per cabinet
27
Server supply and extract dimensions
(23*2.6) in
Type of resistance [35]
Advanced resistance model
Heat load per server
296 W of 350 W
Heat load per rack
2.67 KW
Maximum heat load per cabinet [18]
8 KW
24
The system resistance curve is fed as a input by creating an advance resistance model
that acts as a flow resistance. The fan curve is also specified to the server fan from the face
book server.
Static pressure Vs Flow rate
Figure 22 System resistance curve for the experimental server [37]
The server fan curve represents the increase in volumetric flow with the increase in the
pressure drop. The maximum pressure drop for this fan is 80 pascals (Pa) and maximum
volumetric flow across the server is 1150 cfm.
c) Approach to advanced resistance model [35]
In my study, the server is modeled using advanced resistance model feature from
FloVENT software. The Intel XEON 5500 R server is simulated by using its fan curve and
system resistance curve in the FloVENT software.
25
The server is represented as a 2D model. This procedure involved in creating the
advanced resistance model consists of two major steps.
a To import the system resistance curve. [35]
Table 3 Pressure drop at various fan speeds across the servers
Velocity (m/s)
Pressure Drop (Pa)
0
0
0.02
4.98
0.04
9.95
0.08
14.94
0.15
19.92
0.23
24.9
Pressure Vs. Velocity
Figure 23 System resistance curve for the advanced resistance model [35]
b To insert the fan curve.
26
The fan curve is a function of Pressure drop and volumetric flow rate as known from
Pressure Vs Volumetric Flow.
Figure 24 Fan curve for the advanced resistance model [35]
We equate the equation of the trend line to the equation which we arrived for the
advanced resistance model. The value of l is arbitarily set to 1 m and considerd.
Figure 25 Equation for the advanced resistance model
27
Figure 26 Reduced equations for the advanced resistance model
This gives the complete values to be entered in the dialogue box for the advanced
resistance model , ρ is the density of the resistance, v is the air flow velocity across the server.
ΔP is the Pressure difference across the server inlet and outlet.
The resistance model is calculated with the equation above. Here 𝑎 and 𝑏 are the
calculated by equating the υ and υ² coefficients from the above equation with the equation of
the system resistance curve. This 𝑎 and 𝑏 coefficients are entered in the resistance model to
represent the resistances for the servers. The fan curve is imported in the rack smart part along
with resistance model to represent the server compact model.
6.2 CRAC Model Specification
The CRAC unit provides use a cuboid to represent the body of the unit. A recirculation
device represents the fans and coils.
Figure 27 CRAC unit CFD model [35]
28
Table 4 CRAC Model Specification [35]
CRAC Model Geometric Parameters
Value/info
CRAC dimensions
(0.9*2*2.4) m
Number of CRAC unit
One
Flow rate
16000 Cfm
Extract and supply dimensions
(0.9*2.4) m
Supply Temperature set point
18°C
CRAC unit capacity
211 KW
Direction of Flow
Normal
6.3 Ceiling drop duct specification
The ceiling drop duct in the HACS is specified with 82% open area ratio for air from the
room to the ceiling plenum. This is the preferred open are considered in most of the
datacenters.
Figure 28 Ceiling drop duct in raised floor datacenter CFD model
29
6.4 Air Containment Systems CFD Models [29]
The air containment systems are configured in a common datacenter room lay
out with fixed underfloor depth.The figure below shows the drop duct and the
underfloor im the same lay out.
Figure 29 Isometric view of the data center room layout [35]
This Data center platform is validated first from a published paper [4]. The Ceiling drop
duct, perforated floor and CRAC unit positions in this raised floor data center. Only half of the
data center is modeled and simulated due to symmetry. The symmetry plane is shown in the
left. The raised floor perforation is shown in blue. The air ducts in the ceiling are colored in
yellow. Some of the feature might not appear in the actual model, depending on the
configuration being analyzed.
30
a Case 1 Hot aisle / cold aisle datacenter [35]
Figure 30 Case 1 Hot aisle / cold aisle datacenter [35]
The case 1 is the datacenter is simple hot aisle /cold aisle datacenter. This does not
have any blanking panels. The hot aisles are considered from 1 through 3 beginning from the
CRAC unit The cold aisle are considered 1 and 2 beginning from the CRAC unit . The server
cabinets are numbered from 1 through 3 in their respective rows. This layout represents the hot
aisle / cold aisle lay- out referred common in most of the datacenter rooms.
This case is expected to have more recirculation than the other cases since there is no
isolation between the hot aisles and the cold aisles.
31
b Case 2 Data center contained with both the cold aisle
Figure 31 Case 2 Data center contained with both the cold aisle [35]
The above figure shows the datacenter with both the aisle contained. This is the CFD
model. The blanking panel of neglible thickness is placed above the cabinet rows A and B.
There are blanking panels that also covers the end of the aisle. Similarly the blanking panels
are placed containing the second cold aisle for the cabinets rows C and D in the figure. This
leaves the datacenter with both the cold aisles contained. This lay out is expected to have
better cooling in the server sets compared to the case.
This arrangement is referred from Cold aisle containment system [29].
32
c Case 3 Data center contained with first cold aisle alone
Figure 32 Case 3 Data center contained with first cold aisle alone [1]
In this CFD model of the datacenter room lay out, the first cold aisle considered is
contained leaving the second cold aisle uncontained. This model is similar to previous
containment system excepting that the second cold aisle is left uncontained. A blanking panel is
used to contain the roof of the cabinets in the second cold aisle. The blanking panels are also
used to contain the end of the aisle.
The cold air is contained due to the blanking panel leaving the hot air isolated from the
cold air in this arrangement.
33
d Case 4 Data center contained with second cold aisle alone
Figure 33 Case 4 Data center contained with second cold aisle alone [35]
In this FloVENT model, the arrangement is again on the raised floor datacenter
platform but second cold aisle formed far from the CRAC unit is contained by using the blanking
panel of negligible thickness at the end of the aisle. One more blanking panel of negligible
thickness is used at the top of the cabinets placed in rows C and D.
34
e Case 5 Data center contained with the all the three hot aisles [35]
Figure 34 Case 5 Data center contained with all the three hot aisles [35]
In this CFD model of the raised floor datacenter, the three hot aisles formed are
contained by the blanking panel. The drop ceiling formed with ceiling ducts are used allow the
hot air to be removed from the room.
35
f Case 6 Data center contained with first and second hot aisle alone [35]
In this CFD model of the raised floor datacenter, the first and second hot aisles formed
with respect to the CRAC unit location are contained by the blanking panel. The drop ceiling
formed with ceiling ducts are used allow the hot air to be removed from the room.
Figure 35 Case 6 Data center contained with first and second hot aisle alone [35]
In this CFD model of the raised floor datacenter, the first and second hot aisles formed
with respect to the CRAC unit location are contained by the blanking panel. The drop ceiling
formed with ceiling ducts are used allow the hot air to be removed from the room.
36
g Case 7 Data center contained with second and third hot aisle alone [35]
Figure 36 Case 7 Data center contained with first and third hot aisle alone [35]
In this the raised floor datacenter platform the second and third hot aisles formed with
respect to the CRAC unit location are contained by the blanking panel. The second hot aisle
mentioned is the aisles in between row B and C.
37
g Case 8 Data center contained with second and third hot aisle alone [35]
Figure 37 Case 8 Data center contained with second and third hot aisle alone [35]
In this the raised floor datacenter platform the second and third hot aisles formed with
respect to the CRAC unit location are contained by the blanking panel. The second hot aisle
mentioned is the aisles in between row B and C.
38
CHAPTER 7
RESULTS AND ANALYSIS
7.1 Case 1 Results and Analysis
From the previously mentioned configurations, the following results have been obtained
by the computational analysis.
Figure 38 Server Sets which are considered as over heated [35]
The above figure shows the servers sets in various cabinets which had temperatures
higher than the 25°C at the inlet. The results of temperature surface plot , pressure plot and the
velocity surface plot for the server set in the cabinet
which has maximum temperature
compared with other server sets is shown.
The surface plot for temperature is plotted for the server set which has been observed
with maximum temperature at the server inlet. The pressure plot allows to understand the
39
resistance offered by the system. The occurrence of recirculation can be observed from velocity
plot.
Figure 39 The maximum temperature observed in server sets is 35°C
Figure 40 The pressure surface plot for the cabinet showing maximum temperature
40
Figure 41 The velocity surface plot for the cabinet showing maximum temperature
Table 5 Analysed cooling performance for Case 1
S.no
Cooling performance parameters
1
Number of Overheated server sets
2
Fan Power
3
Maximum Temperature exhibited by the server set
Values
40 / 72
1.85 KW
34.5°C
7.2 Case 2 – Results and Analysis
Figure 42 Temperature surface plot X axis through midsection cabinets A3- D3
41
In the datacenter contained with both the cold aisle, the surface plot, Fan power and the
Maximum temperatures exhibited by the server set is tabulated.
Table 6 Analyzed cooling performance for Case 2
S.No
Cooling performance parameters
1
Number of Overheated Sets
2
Fan Power
3
Maximum Temperature exhibited by the server set
Values
0
5.16 KW
<25°C
7.3 Case 3 – Results and Analysis
In case 3, the location of the servers sets, the thermal surface plot , total number of
servers sets over heated and the Fan power is shown below.
Figure 43 Cabinets which are considered to be over heated in case 3 [35]
42
Figure 44 Temperature surface plot X axis through A3 – D3 in Case 3
The temperature surface plot shows the distribuution of the temperatures through
server sets though midesection A3- D3.
Figure 45 Temperature surface plot for the cabinet showing maximum temperature
The Cabinet was observed with temperatures 29°C at the inlet which is higher than the
considered temperature of 25°C.
43
Figure 46 The pressure surface plot for the cabinet showing maximum temperature
Figure 47 The velocity surface plot for the cabinet showing maximum temperature
Table 7 Analyzed cooling performance for Case 3
S.No
Cooling performance parameters
1
Number of Overheated Sets
2
Fan Power
3
Maximum Temperature exhibited by the server set
Values
20 / 72
2.01 KW
44
28°C at D3
7.4 Case 4 - Results and Analysis
In case 4, the location of the servers sets, the thermal surface plot , total number of
servers sets over heated and the Fan power is shown below.
Figure 48 Cabinets which are considered to be over heated in Case 4 [35]
Table 8 Analyzed Cooling performance Table for Case 4
S.No
Cooling performance parameters
Values
1
Number of Overheated Sets
16 / 72
2
Fan Power
2.01 KW
3
Maximum Temperature exhibited by the server set
35 ° C at B3
7.5 Case 5 - Results and Analysis
The thermal surface plot, total number of servers over heated and the fan power
consumed in this configuration is shown below.
Figure 49 Temperature surface plot X axis through cabinets A3-D3
45
Figure 50 Temperature surface plots X axis through cabinets A1-D1
Table 9 Analyzed cooling performance for Case 5
S.No
Cooling performance parameters
1
Number of Overheated Sets
2
Fan Power
3
Maximum Temperature exhibited by the server set
Values
0
5.36 KW
<25°C
It is observed that there are no server sets have temperatures higher than 25°C.
7.6 Case 6 - Results and Analysis
Figure 51 Temperature surface plot X axis through cabinet rows A3-D3
Figure 52 Temperature surface plot X axis through cabinet rows A1 - D1
46
Table 10 Analyzed cooling performance for Case 6
S.No
Cooling performance parameters
1
Number of Overheated Sets
2
Fan Power
3
Maximum Temperature exhibited by the server set
Values
0
2.4 KW
<25°C
7.7 Case 7 - Results and Analysis
The location of the server set showing maximum temperature, the temperature surface
plot, pressure surface plot and velocity surface plot is shown in the next three figures.
Figure 53 The server sets in this cabinet shows temperature higher in case 7 [35]
47
There are three server sets that show temperatures higher than 25°C in the half
symmetry model. The temperature surface plot is modified to observe temperature distribution
in the server sets. The server sets placed closer to second aisle exhibit temperatures lower than
25°C at the inlet.
Figure 54 The temperature surface plot for the cabinet maximum temperature
The temperature surface plot shows the temperature distribution in the server inlet for
the case 7 when the first and the third aisle is contained and the second aisle is left
uncontained.
48
Figure 55 The pressure surface plot for the cabinet exhibiting maximum temperature
Figure 56 The velocity surface plot for the server set in cabinets showing 26°C [35]
49
The velocity surface plot aids for understanding the recirculation that occurs in the
server sets showing higher temperatures at the inlet.
Table 11 Analyzed cooling performance for Case 7
S.No
Cooling performance Parameters
1
Number of Overheated Sets
2
Fan Power
3
Maximum Temperature exhibited by the server set
Values
6 / 72
2.38 KW
26°C
Fan power is observed to 2.38 KW which is quite less compared with the data center
contained with all the three hot aisles.
7.8 Case 8 - Results and Analysis
The temperature surface plot results, total number of overheated server sets, the Fan
power consumed in case 7 is illustrated below. The below two temperature surface plots shows
higher temperature closer to CRAC unit since the first aisle is left uncontained.
Figure 57 Temperature surface plot through X axis midsection cabinets through A3-D3 [35]
It is well observed from the surface plot results that the temperature of the serves sets
in the corner cabinets show lower temperatures. When the second and third hot aisle is
contained and the fists aisle is left uncontained.
50
Figure 58 Temperature surface plots through X axis midsection cabinets through A1-D1
It is well observed from the tabulated results that there is no cabinet with servers sets
showing temperatures higher than 25ºC in this case.
Table 12 Analyzed cooling performance for Case 8
S.No
Cooling performance Parameters
Values
1
Number of Overheated Sets
0
2
Fan Power
0
3
Maximum Temperature exhibited by the server set
2.27 KW
The Fan power value is slightly lower compared to the previous cases of partially
contained datacenters
7.9 Summary of Analyzed Results for Eight Cases
The next table shows the summarized results for all the eight cases of the air
containment systems that has been compared. The predicted results of Fan power that is
consumed in a day for each of the configurations is also tabulated in addition.
51
Table 13 Summary of analysed results for all the eight cases
Number of
Air containment System
Server sets
[29] incorporated
observed
in the
CFD problem
over heated
out of 72
Case1 – Hot aisle / Cold
Aisle datacenter
Maximum
Temperature
observed in an
individual server
set in ºC (above
Fan power
Fan Power
spend for a
(calculated )
day
KW
24 hours
KW
25ºC)
40
34.5
1.85
44.4
0
<25
5.16
123.84
20
28
2.19
52.56
16
35.6
2.01
48.24
0
<25
5.56
133.44
0
<25
2.4
57.6
6
26
2.38
57.12
0
<25
2.27
54.48
Case 2 - Datacenter
contained with both the
cold aisle.
Case 3 – Data center
contained with first cold
aisle alone.
Case 4- CACS [29] –
Second cold aisle alone
contained
Case 5-HACS [29] Fully
contained
Case 6 -HACS [29]- first
and second hot aisle
alone contained
Case 7- HACS [29] – First
and third hot aisle alone
contained
Case 8 - HACS [29]
Second and third hot aisle
alone contained
52
CHAPTER 8
CONCLUSION AND FUTURE WORK
Containment is a fairly effective and relatively cheap approach to reduce the cost of
energy in legacy as well design of new data centers. The hot aisle containment collects the
server exhaust air and restricts its entry to the rest of the datacenter. Cold aisle containment
provides physical separation between the hot and cold air by isolating the cold aisle. This
containment technique sets apart the cold air from the room.
In this study, eight different containment configurations of the datacenter were created
using Flo-VENT. Based on reference from ASHRAE handbook TC 9.9 2004, maximum
temperature at which servers gets over heated is utilized as one matrix for evaluating the
performance or effectiveness of the various containment systems discussed in this study. A
second matrix in evaluating the performance of the containment in question is the fan power
consumption which is dependent on the pressure drop at the CRAC unit.
Primarily, the cold air containment fully contained with asymmetric CRAC unit location
with raised floor datacenter performs better in cooling performance than the ducted hot aisle
containment system [31] in terms of cooling performance. The reasons as observed from the
simulation result are, the pressure drop observed at the CRAC supply and return is higher in the
fully contained hot air containment system than the cold air containment system. It was also
observed that, partial aisle containment system which is currently less frequent in practice
consumes lower power to cool the server sets.
Finally, we conclude that by containing the second and third hot aisle from the
incorporated ducted hot aisle containment system technique (Hot air containment system
approach [30]), we achieve maximum cooling performance since there is lesser recirculation is
53
being observed from the interpreted CFD results. The study can also be extended to row based
aisle containment systems [30] to find out the optimized air containment technique.
54
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58
BIOGRAPHICAL INFORMATION
Kasturi Rangan Rajagopalan, an aspiring student, received his Bachelor’s in
Automobile Engineering from Anna University. India in 2005-2009. His research interest
towards Thermal Engineering made him choose Mechanical Engineering for his Masters in Fall
2010 at the University of Texas at Arlington. The same interest resulted in working with cooling
in electronic applications and gradually into cooling in Data centers. During the course of his
study he represented the university in eight conferences through his research and also
collaborated with industry professionals for his projects.
59