2012 - Rack Level Modeling of Air Flow Through Perforated Tile in a Data Center

8/13/2019 2012 - Rack Level Modeling of Air Flow Through Perforated Tile in a Data Center

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1 Copyright 2012 by ASME

Proceedings of the ASME 2012 International Mechanical Engineering Congress & ExpositionIMECE2012

November 9-15, 2012, Houston, Texas, USA

IMECE2012-85203

RACK LEVEL MODELING OF AIR FLOW THROUGH PERFORATED TILE IN A DATA

CENTER

Vaibhav K. ArghodeG.W. Woodruff School of Mechanical Engineering

Georgia Institute of TechnologyAtlanta, Georgia, USA

Pramod KumarDepartment of Mechanical Engineering

Indian Institute of ScienceBangalore, Karnataka, India

Yogendra JoshiG.W. Woodruff School of Mechanical Engineering

Georgia Institute of TechnologyAtlanta, Georgia, USA

Thomas S. WeissTriad Floors Inc.

Denver, Colorado, USA

Gary MeyerTriad Floors Inc.

Denver, Colorado, USA

ABSTRACTEffective air flow distribution through perforated

tiles is required to efficiently cool servers in a raised

floor data center. We present detailed computational

fluid dynamics (CFD) modeling of air flow through a

perforated tile and its entrance to the adjacent server

rack. The realistic geometrical details of the perforated

tile, as well as of the rack are included in the model.

Generally models for air flow through perforated tiles

specify a step pressure loss across the tile surface, or

porous jump model based on the tile porosity. Animprovement to this includes a momentum source

specification above the tile to simulate the acceleration

of the air flow through the pores, or body force model.In both of these models geometrical details of tile such

as pore locations and shapes are not included. More

details increase the grid size as well as the

computational time. However, the grid refinement can

be controlled to achieve balance between the accuracy

and computational time. We compared the results from

CFD using geometrical resolution with the porous

jump and body force model solution as well as with

the measured flow field using Particle Image

Velocimetry (PIV) experiments. We observe thatincluding tile geometrical details gives better results as

compared to elimination of tile geometrical details and

specifying physical models across and above the tile

surface. A modification to the body force model is also

suggested and improved results were achieved.

Key words: High density rack; Perforated tile;

Air flow distribution; Geometrical resolution; Porous

jump model;Body force model

INTRODUCTIONIn recent past, many investigations have been

reported on modeling of data center air flows [2-11].

Some of the investigations only focused on the under

floor region (plenum) modeling [3-5] and they

imposed a step pressure loss across the tile surface, or

porous jump model thereby eliminating any

geometrical details of the tile from the model. The

pressure loss factor (K=P/0.5Vin2) was calculated

based on the tile porosity (open area ratio) [1]. Thefocus of these works was to predict the air flow rate

emerging from the plenum. The suggested models

include a 0D model where a uniformly pressurized

plenum was considered [3] or 1D model where the

effects of under floor pressure variation as well as

frictional resistance in plenum was considered. These

simplified model results in manageable grid size and

reduced computational time for modeling large data

centers. Such investigations are helpful for

understanding the overall air supply pattern in the data

center with objective of supplying the air flow rate as

per the requirement of the adjacent rack. It was also

suggested that the air flow design problem is based onthe under floor flow features and supplying the

required amount of air is sufficient to effective cool

the adjacent server rack [2]. However experimental

investigation of air flow emerging from perforated tile

and entering the rack suggests that even though the

supplied air flow rate matches the rack requirement,

issues such as air bypass and room air entrainment

may be present [13-14]. Hence modeling of above


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floor system is deemed useful and has been considered

in investigation such as [8-11].

In a more comprehensive investigation, both

under floor and above floor regions have been

investigated together [6]. In this investigation the two

regions were connected by perforated tiles where a

step pressure loss is specified through the tile surface

(porous jump model). A review of the computational

investigations pertaining to data center air flows could

be found in [7].

An improvement in the tile flow model was

suggested in [10-11]. However, in these investigations

the focus was limited to the above floor surface only

where designated air flow rates were specified at the

tile inlet. It was mentioned that in the porous jump

model (which considers uniform velocity based on

total open area of tile), the momentum rise of air due

to pressure loss across the tile surface is not captured

and hence in these investigations additional body force

(momentum source) was specified above the tile

surface to simulate higher momentum of the air flowabove the tile surface (body force model). This model

showed improved results as compared to the porous

jump model [10-11]. Other strategies such as modeling

the tile with an equivalent reduced single open area to

simulate higher momentum or multiple openings were

also suggested [10]. Multiple openings with some tile

geometrical details (much larger pore length scales as

compared to the actual pore size) was also investigated

and fair agreement with measurements was obtained

[10]. In this case higher air entrainment and faster

mixing was observed as compared to the body force

model which eliminated pore geometrical details.

This suggests that further inclusion of finergeometrical details can be helpful to closely capture

the flow pattern above the floor and at rack entry.

Hence, in the present work we report the effect of

including more resolved tile geometrical details on the

solution accuracy at the expense of increased

computational effort. Note that a balance between the

solution accuracy and computational effort needs to be

considered while investigating data center air flows.

We also present a modification to the body force

model which could be useful to simulate the flow field

with much reduced computational efforts and it also

shows promise for further improvements to develop

simplified models which will reduce thecomputational time while still maintaining acceptable

accuracy.

COMPUTATIONAL SETUPFigure 1 shows the server simulators, rack and the

perforated tile used in the experimental investigation

[13-14]. The 42U (1U = 4.45 cm) rack houses four

server simulators each having height of 10U (see

Figure 1(a)). There is a gap of about 2.54 cm (1 inch)

between the bottom of the rack and the solid tile

surface below the rack (see Figure 1(b)). Server

simulators have a front plastic grill with porosity of

about 37% [12]. Each server simulator has four fans

mounted on a plate. The fan-plate is located at a

distance of 25.4 cm (10 inch) from the front of server

simulator. The fans are centered and spaced 5.08 cm (2

inch) apart from fan outer edge. Each fan has an outer

diameter of 16.83 cm (6.625 inch) and 8.26 cm (3.25

inch) hub diameter. Each server simulator has fan

speed dial settings to set desired flow rates through the

rack. Further details of the server simulator could be

found in [12].

The tile used for the investigation has dampers on

the bottom and a perforated plate on the tile top

surface. The dampers have multiple rectangular

openings (see Figure 1(d)) and the tile top has

openings of different shapes with length scales of

about 1.27 cm (0.5 inch) (see Figure 1(c)). The

distance between the dampers and the tile top is about

3.81 cm (1.5 inch).Figure 2 shows the computational domain and

modeled geometrical tile details. The computational

domain considers only one tile and one rack as shown

in the Figure 2(a). All the geometrical features are

modeled as orthogonal shapes. Circular fans with hub

are modeled as square openings with square hub. The

rack geometry after the fan plate is not included in the

model and the fans are considered as exhaust fans with

target mass flow boundary condition. In this case the

pressure at the fan surface is adjusted so as to reach a

pre-assigned mass flow rate through the fan surface.

The swirl generated by the fans is not included in the

model.Figure 3 shows the dimensional details of the

computational domain. The grill at the rack inlet is

modeled as thin rectangular openings of about 1.27 cm

(0.5 inch) height. The impermeable strips adjacent to

the openings have height of 2.54 cm (1 inch) hence

giving an overall porosity of 33% (see Figure 3(d)).

All four server simulators are separated by

impermeable walls as shown in Figure 3(a). The gap

of 2.54 cm (1 inch) between the bottom of the rack and

solid tile below it is also considered in the model and

pressure inlet boundary condition is specified at the

inlet of the gap (see Figure 3(a)).

Plenum is included in the model by specifyingmass flow rate boundary condition below the tile

surface with symmetry boundary condition on the

plenum walls (see Figure 2(a), 3(a), 3(b)). For the

present investigation the plenum is fairly deep (~ 0.9

m or 3 ft) and hence the effect of directional flow

under the tile surface is expected to be less in the

present case [2]. Moreover, two down flow CRAC

units were used which were located on either sides of

the cold aisle (along the length). This would further


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suppress the directional flow characteristics in the

plenum, see [13-14] for data center layout. Hence,

mass flow condition is specified below the tile surface

and not on the sides of the modeled plenum. The aisle

top is specified as pressure outlet and the aisle

center is specified as pressure inlet. The aisle

center is the aisle surface facing the rack inlet. The

sides of the aisle are specified as pressure inlet with

some resistance to the air flow (pressure loss

coefficient, K = 10). This condition was used due to

the anticipated resistance to the flow entering the

computational domain because of the presence of

adjacent tiles. Refer [13-14] for further details on tile

layout for the experimental investigation. The value of

K was appropriately adjusted to simulate the flow field

features obtained by experiments. However, further

investigation is required to arrive at an appropriate

value for K based on the physical set-up and operating

conditions.

The modeled tile geometry is shown in Figure

2(b-f). The tile top surface is modeled as 900 squarepores of 1.27 cm (0.5 inch) side. Note that the tile top

surface has pore shapes which have curved edges,

however in our investigation we observe that the

curved pores could be modeled as orthogonal shapes

with same hydraulic diameter [15]. The spacing

between two square pores on the tile top is about 0.64

cm (0.25 inch). The porosity of the modeled tile top

surface is about 39%. The damper openings are

modeled as 36 rectangular openings, each with size of

3.18 cm (1.25 inch) 13.34 cm (5.25 inch). The

distance between two damper openings is 0.64 cm

(0.25 inch) along the longitudinal direction and 3.18

cm (1.25 inch) in the transverse direction. The porosityof damper openings is 41%. The tile top and the

dampers are spaced 3.81 cm (1.5 inch) apart (see

Figure 3(a)).

The computational domain is meshed with full

rectilinear grid. The region near the perforated tile is

appropriately refined such that each square pore on the

tile top has 8 8 cells. In this case grid refinement was

performed using hanging-node approach. Simulations

suggest that having 8 8 cells in each pore gives

reasonably close result with a grid independent

solution [15]. Note that appropriate balance between

grid refinement and solution accuracy is sought here.

For the case using geometrical details the grid size isabout 4.2 million cells. Without grid refinement, for

the cases using simplified models such as porous jump

or body force models the grid size is about 1 million

cells.

The isothermal flow field was solved using a

steady state, finite volume based method and SIMPLE

algorithm was used for pressure velocity coupling

[16]. Symmetry with only one-half the geometry was

used to reduce the computational time. k- realizable

turbulence model was used with inlet turbulence

intensity of 5%. For convective term discretization,

second order upwind scheme was used. Convergence

was assumed when the normalized residuals for all the

variables were less than 1E-04 and the selected

velocity monitors have stabilized within variation of

1%. Commercial CFD software FLUENT was used for

the simulations.

The results are compared with the experiments

[13-14], and with the simplified models specifying

porous jump boundary condition as well as body force

source above the tile surface.

Porous jump model:

Porous jump model specifies step pressure loss

across the tile surface [2-9]. Generally, the magnitude

of pressure loss factor is calculated based on the

porosity of the tile. The pressure loss specification has

a form similar to that given below in Equation (1-2)

[1].

= (1) = +1 (2)

= , = , = = It may be noted that use of this model results in no

alteration in the velocity field across the tile surface.

However, there is acceleration of air though the pores

resulting in increased momentum flux, attempted to be

captured by the body force model. It may be noted that

the tile has two surfaces in series in the path of airflow. The bottom surface has tile dampers and top

surface has the perforations as shown in Figure 2(b-f).

The pressure drop across theses surfaces, as obtained

by correlation (equation 1-2), is added to arrive at the

final pressure drop. Note that in actual case the flow is

not uniform after passing through the dampers and this

may affect the overall pressure drop from the tile. For

the present case the equivalent K across the two tile

surfaces is 16.5. The equivalent porosity of the two

layers is calculated as 31%. The value of K across the

rack inlet (front grill of server simulators) is 14.3

corresponding to the grill porosity of 33%.

Body force model:

In this model a momentum source is specified

above the tile surface to simulate the acceleration of

air passing through the pores in the tile (see equation

(3-5)) [10-11]. The magnitude of the momentum

source was calculated based on the difference of

momentum through the tile pores as compared to the

momentum of air flow in case of uniform velocity as

in the case in porous jump model (see Equation (3)).


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The momentum of air flow through the pores was

calculated assuming top-hat velocity profile through

the pores (see Equation (4)).

= (3) =

(4)

= (5), "" = =

Modified Body force model:

The body force model suggested previously

considers a top hat velocity profile at the tile pores

while calculating the excess momentum of air above

the tile surface. However, even higher momentum of

the jets is expected as in reality there will be a velocity

profile present at the tile pores instead of a top-hat

profile. Hence, we suggest a modification to the bodyforce model. In the modified body force model the

momentum rise across the tile surface is calculated

based on the pressure loss as obtained from the

correlations (see Equation (6)).

= = = + 1 (6), Once the momentum averaged velocity (Vpore)

through the tile surface is calculated the momentum

source term can be calculated as suggested by the

body force model (see Equation (5)). Note that the

modified body force model will have higher

magnitude of momentum source as compared to the

body force model.

RESULTS AND DISCUSSIONTable 1 summarizes the cases studied. The air

flow rate across the rack corresponds to a high power

density rack with 15 kW of heat dissipation and bulk

air temperature rise of 10 C across the rack. The tile

flow rate is varied from 0% upto 100% of the rack air

flow rate and the values are listed in Table 1. Further

details of the experimental conditions could be found

in [13-14].

Table 1. Different cases investigated.

Case

#

Rack flow

rate (m3/s,

CFM)

Tile flow

rate (m3/s,

CFM)

Tile flow /

Rack flow

1 1.224, 2594 0, 0 0%

2 1.224, 2594 0.234, 496 20%

3 1.224, 2594 0.754, 1598 60%

4 1.224, 2594 1.224, 2594 100%

Figure 4 shows the pressure loss obtained across

the tile surface from CFD simulations. In this case the

tile geometrical details are included in the model as

shown in Figure 2(b-f). The correlation used forcomparison is given in Equation (2) corresponding to

equivalent tile porosity of 31%. Figure 4 suggests a

good comparison between the correlation and CFD

simulations. However, note that we assume addition of

pressure loss across the two tile surfaces based on the

correlations and in actual case this may not represent

the actual pressure loss. Value of K across the tile for

cases 2, 3 and 4 are also very close to each other

suggesting that the pressure loss factor does not vary

significantly with respect to flow rates investigated

here. Note that case 1 is not included, as there is no

flow through the tile in this case.

Figure 5-8 shows the comparison between

experimental (PIV) and computational (CFD) results

for cases 1-4 (see Table 1). Pathline plots are used for

visualization of the flow field. In the CFD simulations,

massless particles released from the lines at

boundaries (tile, aisle center and aisle top, see

Figure 5-8) and are tracked and plotted. The plots

correspond to the symmetry plane positioned along the

height of the rack. Note that in the CFD model

considering geometrical resolution, the modeled

geometry of the grill at the rack inlet is included. In

the porous jump model pressure loss is specified

across the grill surface.

Figure 5 shows the results for case 1 (see Table 1).

In this case there is no flow through the tile. From thefigure we observe that the flow field measured by PIV

and calculated using CFD are similar and entrainment

of air from aisle top as well as the aisle center is

present in both the experimental and computational

results. The top region of the rack inlet shows air

entrainment from the aisle top (see figure 5(a)). Figure

5(b-e) suggests that the resolution of grill geometry

(rack inlet) does not significantly influence the

computational solution, as compared to using the

porous jump model across the grill for the present

case. This also suggests that it may be beneficial to use

porous jump boundary condition across the rack inlet

to save computational effort for this case.Figure 6 shows the flow field for case 2 (see Table

1). In this case the flow rate through the tile is about

20% of the air flow rate through the rack. Due to

insufficient supply of air from the perforated tile, the

rack also entrains the air from aisle top as well as aisle

center as shown in Figure 6(a). The air supplied from

the tile reaches only the lower portion of the rack,

while near the top the rack entrains air from aisle top.

The middle portion of the rack mostly entrains air


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from the aisle center. These flow field features are also

captured by all the computational models (see Figure

6(b-e)). The body force model and modified body

force model show that the tile air flow reaches higher

along the rack height, as compared to the porous jump

model (see Figure 6(b) and 6(c)). Inclusion of body

force source above the tile surface increases the

momentum of bulk air in the region above the tile

surface, and hence results in higher reach of air to the

rack inlet. The momentum source region is between

the yellow line and tile surface (see Figure 6(c-d)).

The result obtained with geometrical resolution is very

similar to the result obtained by the body force and

modified body force models.

The flow field for case 3 (60% of rack air flow

through tile, see Table 1) is shown in Figure 7. From

Figure 7(a) we note that even though the air flow rate

through the tile is lower than the rack air requirement,

a portion of the supplied air escapes from the aisle top.

We can also observe delayed entry of the tile air at the

lower portion of rack inlet (see bottom right corner ofFigure 7(a)). This was attributed to the higher

momentum of air emerging from the tile [13-14]. Air

entrainment from the aisle center could also be noticed

for this case (see bottom left corner of Figure 7(a)).

The porous jump model is not able to capture these

phenomena and the air flow from the tile reaches only

up to a certain height of rack (see Figure 7(b)). Porous

jump model also suggests entrainment of air from aisle

top which is not observed experimentally. The porous

jump model is also not able to capture the air

entrainment from aisle center near the tile surface

(bottom left corner) and delayed entry of air in the

lower portion of rack inlet (bottom right corner).When momentum source is included above the

tile surface (body force model) the tile air flow reaches

higher as compared to the porous jump model (see

Figure 7(c)). However air entrainment from the aisle

top could be observed for the body force model too,

which is not present in the experimental results. Body

force model shows minor improvement in the

computed flow field. In this case, small entrainment of

air from the aisle center near tile (bottom left corner)

and slight delay of entry of air in lower portion of rack

could be observed (bottom right corner).

The modified body force model shows further

improvement in the results possibly due to highermagnitude of momentum source specification above

the tile surface (see Figure 7(d)) as compared to the

body force model. It may be noted that even with the

modified body force model, the flow field is

significantly different from the experimental results.

The flow field with the model that included the

geometrical details of the tile is shown in Figure 7(e).

From the figure we observe that the flow field features

are closer to the experimental results. A portion of air

flow is observed to escape from the aisle top. This

model also captures the delayed entry of air to the

lower portion of the rack inlet. The air entrainment

from aisle center could also be observed from Figure

7(e).

Figure 8 shows the flow field features for case 4

(see Table 1). In this case, the air flow rate through the

tile is equal to the air flow rate through the rack. Due

to higher momentum of air jet, significant portion of

the tile air is observed to bypass the rack through the

aisle top (see Figure 8(a), refer to [14] for the

discussion). The air entrainment through the aisle

center and delayed entry of tile air to the rack could be

prominently observed. The porous jump model (see

Figure 8(b)) shows the tile air reaching near the aisle

top, however, the prominent flow field features

measured experimentally, could not be captured by

this model. The body force model, as well as modified

body force model while showing improved prediction,

could not compare closely with the experimental

results (see Figure 8(c-d).Figure 8(e) shows the flow field obtained by

resolving the tile geometry, which is closer to the

experimental results. This model is able to capture

significant bypass of the tile air through the aisle top,

as well as entrainment of air though aisle center near

the tile (bottom left corner). The delayed entry of the

air near the bottom portion of the rack could be clearly

seen from bottom right corner of Figure 8(e). This

suggests that simplified geometrical resolution shows

promise for better solution accuracy and further

improvements in the body force, or development of

other simplified models is required to capture the flow

field closely.

CONCLUSIONSExperimentally measured flow field in data center

cold aisles were compared with various computational

modeling approaches. The simplified flow models

through floor tiles, such as porous jump and body

force models suggests fair comparison with the

experimental results at lower tile air flow rates.

However, at higher air flow rates, required for high

power density racks, these simplified models do not

capture the flow field features accurately. A modified

body force model is suggested, which calculates the

momentum rise based on the prescribed pressure lossacross the tile surface. While this model shows

improvement in the results, it still does not compare

well with the experimental results at higher tile air

flow rates. Including the geometrical details of the tile

provides better comparison with the experimental

results. This model is able to capture the prominent

flow features, such as bypass of tile air though the

aisle top, as well as entrainment of air from aisle

center and delayed entry of air to the rack inlet. The


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present investigation suggests that a fairly coarse grid

could be used, with more geometrical details to

achieve better solution accuracy as compared to

specifying simplified models across the tile surface.

Improvements in the simplified models show scope for

future exploration to achieve a better balance between

the desired solution accuracy and reduced

computational time.

ACKNOWLEDGMENTSThis research is supported by Triad Floors, Inc. and

the Consortium for Energy Efficient Thermal

Management (CEETHERM). The support is gratefully

acknowledged.

REFERENCES[1] Freid, E., Idelchik, I. E., Flow Resistance, A

Design Guide for Engineers, Hemisphere, New York,

1989.

[2] Patankar, S. V., Airflow and Cooling in a Data

Center, Journal of Heat Transfer, 2010, Vol. 132, pp.073001-1-17.

[3] Kang, S., Schmidt, R., Kelkar, K. M.,

Radmehr, A., Patankar, S. V., A Methodology for the

Design of Perforated Tiles in Raised Floor data

Centers using Computational Flow Analysis, IEEE

Transactions on Components and Packaging

Technologies, 2001, Vol. 24, pp. 177-183.

[4] Karki, K. C., Patankar, S. V., Airflow

Distribution Through Perforated Tiles in Raised-Floor

Data Centers, Building and Environment, 2006, Vol.

41, pp. 734-744.

[5] Schmidt, R. R., Karki, K. C., Kelkar, K. M.,

Radmehr, A., Patankar, S. V., Measurements andPredictions of the Flow Distribution through

Perforated Tiles in Raised-Floor Data Centers,

International Electronic Packaging Technical

Conference and Exhibition, July 8-13, 2001, Kauai,

Hawaii, USA.

[6] Rambo, J., Joshi, Y., Convective Transport

Process in Data Centers, Numerical Heat Transfer

Part A, 2006, Vol. 49, pp. 923-945.

[7] Rambo, J., Joshi, Y., Modeling of Data Center

Airflow and Heat Transfer: State of the Art and Future

Trends, Distributed Parallel Databases, 2007, Vol. 21,

pp. 193-225.

[8] Cruz, E., Joshi, Y., Iyengar, M., Schmidt, R.,Comparison of Numerical Modeling to Experimental

Data in a Small Data center Test Cell, International

Electronic Packaging Technical Conference and

Exhibition, July 19-23, 2009, San Francisco,

California, USA.

[9] Iyengar, M., Schmidt, R. R., Hamann, H.,

VanGilder, J., Comparision between Numerical and

Experimental Temperature Distributions in a Small

Data Center Test Cell, International Electronic

Packaging Technical Conference and Exhibition, July

8-12, 2007, Vancouver, British Columbia, Canada.

[10] Abdelmaksoud, W. A., Khalifa, H. E., Dang,

T. Q., Elhadidi, B., Schmidt, R. R., Iyengar, M.,

Experimental and Computational Study of Perforated

Floor Tile in Data Centers, Intersociety Conference on

Thermal Phenomena, Jun 2-5, 2010, Las Vegas, USA.

[11] Abdelmaksoud, W. A., Khalifa, H. E., Dang,

T. Q., Schmidt, R. R., Iyengar, M., Improved CFD

Modeling of a Small Data Center Test Cell,

Intersociety Conference on Thermal Phenomena, Jun

2-5, 2010, Las Vegas, USA.

[12] Nelson, G., Development of an

Experimentally-Validated Compact Model of a Server

Rack. MS Thesis - 2007, Georgia Institute of

Technology, GA, USA.

[13] Kumar, P., Joshi, Y., Experimental

Investigations on the Effect of Perforated Tile Air Jet

Velocity on Server Air Distribution in a High Density

Data Center, Intersociety Conference on Thermal

Phenomena), Jun 2-5, 2010, Las Vegas, USA.[14] Kumar, P., Sundaralingam, V., Joshi, Y.,

Dynamics of Cold Aisle Air Distribution in a Raised

Floor Data Center, Thermal Issues in Emerging

Technologies, Dec 19-22, 2010, Cairo, Egypt.

[15] Arghode, V. K., Joshi, Y., Modeling

Strategies for Air flow Through Perforated Tile in a

Data Center, IEEE Transactions on Components,

Packaging and Manufacturing Technology, In

Preparation 2012

[16] Patankar, S. V., Numerical Heat Transfer and

Fluid Flow, Hemisphere, New York, 1980.


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(c) Tile top

(a) Server simulators (b) Rack (d) Dampers

Figure 1. (a-b) Rack and (c-d) tile details under investigation.


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(b) Tile top (c) Mesh for each square

pore in tile top

(d) Dampers (e) Mesh for eachopening in dampers

(a) Computational domain (f) Perforated tile with dampers

Figure 2. (a) Computational domain and (b-f) the modeled tile.


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Figure 3. Details of the computational domain and set-up.

Figure 4. Pressure drop across the tile obtained by CFD with tile geometrical resolution.

. . . .

(.

)

(a) Side view (b) Front view (c) Fans (rack exit) (d) Grill (rack inlet)

.

()

.

.


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Velocity

(m/s)

(a) PIV (b) Porous jump (c) Body force (d) Modified

body force

(e) Geometrical

resolution

Figure 5. Comparison of PIV and CFD results for case 1 (rack flow = 1.224 m3/s, 2594 CFM, tile flow = 0 m3/s,0 CFM, 0% of rack flow).

Velocity

(m/s)

(a) PIV (b) Porous jump (c) Body force (d) Modified body

force

(e) Geometrical

resolution

Figure 6. Comparison of PIV and CFD results for case 2 (rack flow = 1.224 m3/s, 2594 CFM, tile flow = 0.234

m3/s, 496 CFM, 60% of rack flow).


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Velocity

(m/s)

(a) PIV (b) Porous jump

model

(c) Body force

model

(d) Modified body

force

(d) Geometrical

resolution

Figure 7. Comparison of PIV and CFD results for case 3 (rack flow = 1.224 m3/s, 2594 CFM, tile flow = 0.754m

3/s, 1598 CFM, 60% of rack flow).

Velocity

(m/s)

(a) PIV (b) Porous jump (c) Body force (d) Modified body

force

(e) Geometrical

resolution

Figure 8. Comparison of PIV and CFD results for case 4 (rack flow = 1.224 m3/s, 2594 CFM, tile flow = 1.224

m3/s, 2594 CFM, 100% of rack flow).

2012 - Rack Level Modeling of Air Flow Through Perforated Tile in a Data Center

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