Air Filter Effects on Data Center Supply Fan Power
Richard Eiland
1, John Fernandes
1, Betsegaw Gebrehiwot
1,
Marianna Vallejo1, Dereje Agonafer
1, Veerendra Mulay
2
1University of Texas at Arlington
P.O. Box 19023
Arlington, TX, United States, 76013
Phone: (817) 272-7378
Fax: (817) 272-5010 2Facebook Inc.
Menlo Park, CA, United States, 94304
Email: [email protected]
ABSTRACT
Driven by need to reduce energy use, many new data
centers are built with air-side economizers. This method of
bringing in outside air as the primary cooling resource greatly
reduces overall facility power by eliminating need for the
compressors and pumps required by chilled water and
refrigerant based cooling systems. However, system fans are
still necessary to supply and move large amounts of air
through the facility. The operating power of fans is dependent
on the static pressure which must be overcome to move air.
The static pressure of a data center is generally fixed for a
given configuration, with the exception of air filters which
become clogged over time. In this work, airflow versus
pressure drop curves of filters removed after eight and a half
months of service in a large data center operating an air-side
economizer are experimentally characterized. Comparisons of
this data against clean filters provides insight into the change
in pressure drop of both low-efficiency pleated pre-filters and
high-efficiency cartridge final filters as they become dirty.
Incorporating these system resistance curves into the power
curve of the data center supply fans indicates only minimal
increase in energy use resulting from dust and particle
collection of the filters.
KEY WORDS: air filter, data center, air-side economizer,
energy efficiency, fan power, system resistance
INTRODUCTION
Economizers and Filtration
As data centers move towards more energy efficient
practices in all aspects of their design, one of the major trends
of late is the use of free air cooling to alleviate the enormous
amounts of heat generated by the IT equipment. A previous
study showned models which predict up to a seven fold
reduction in the power required to cool IT equipment in data
centers employing air-side economizers versus traditional
computer room air conditioning (CRAC) based systems [1].
Although a valuable energy efficient strategy for the data
center, air-side economizers require additional consideration
for the quality of outside air brought into the computing space.
Hence filtration becomes a key component of the overall
cooling system in place.
Air filters serve the primary needs of removing
airborne particulate contaminants from outdoor air prior to
introducing the cooling resource into the data hall.
Additionally, they serve to increase reliability of mechanical
equipment such as fans and spray cooling systems. However,
the process of removing dust and particulates presents
impedance to airflow that must be accounted for as it may
significantly increase the power required to operate supply
fans. Darcy’s Law, the first law of filtration, states that
pressure drop across a filter is proportional to the flow rate of
the fluid moving through it [2]. This fundamental statement is
based on the system resistance curve (Q-∆P curve)
characteristic of every filter. A filter performance curve is
valuable in assessing power requirements necessary to utilize
free air cooling in a data center. As a filter collects particulate
matter over time an increase in both particle capture efficiency
and air flow resistance may produce variations in
performance. Filter pressure drop increases nonlinearly during
service, making characterization important in determining
ideal time of service for filters.
Industry standard filter performance testing is
achieved following ANSI/ASHRAE Standard 52.2-2007,
Method of Testing General Ventilation Air-Cleaning Device
for Removal Efficiency by Particle Size [3]. The purpose of
this test is to determine a filter’s particle capture efficiency,
dust holding capacity, and resistance to airflow. The results of
this test generate a minimum efficiency reporting value
(MERV) between 1 and 20 to classify particle size removal
efficiency of a filter. Since particle capture efficiency of filters
is not in the scope of this work, a simplified test setup is used.
Results for pressure drop have been validated as an acceptable
alternative to the ASHRAE 52.2 test with third party data.
ASHRAE Technical Committee 9.9 recommends that
data centers be kept clean to meet ISO Class 8 requirements
[4]. The specific filtration recommendations for meeting this
cleanliness are: 1) continuously filter room air with MERV8
filters and 2) outdoor air entering the data center be filtered
with MERV 11 or 13 filters.
A study conducted by Lawrence Berkeley National
Laboratory monitored particle concentration levels at eight
northern California data centers. [5] Average particle
concentrations inside the data centers were typically an order
of magnitude below published ASHRAE standards. Data
centers operating on air-side economizers did show increased
average particle concentrations over data centers without
economizers. It was shown that improving filtration from
978-1-4244-9532-0/12/$31.00 ©2012 IEEE 377 13th IEEE ITHERM Conference
MERV 9 to MERV 11 rated filters could reduce economizer
data center particulate levels to those of non-economizer data
centers; however, the cost associated with increased filtration
was not discussed.
The objective of this work is to experimentally
characterize performance of the air filters used in a data center
operating with air-side economizer. Clean filters and those
removed after eight and a half months of normal operational
service are compared to understand the changes in
performance. The impact of increased resistance of filters on
the supply fan power of the system is investigated to serve as a
first step in determining an optimal replacement schedule for
filters and the overall energy impact.
Description of Data Center under Study The data center supplying the used air filters for this
study is located in central Oregon in a high desert climate. The
cool, dry environment allows for year-round utilization of
outdoor air and a direct evaporative cooling system
eliminating need for chillers and compressors. No historical
data is present for the specific location; however the closest
city reports a 50 year extreme maximum dry bulb and wet
bulb temperatures of 105.6°F (40.9°C) and 70.3°F (21.3°C)
respectively. Extreme minimum data is given as -30.8°F (-
34.9°C) dry bulb temperature at 50% relative humidity and
0.55 grains of moisture [6].
The data center’s mechanical system utilizes a built-
up penthouse design as shown in Figure 1 and presents many
construction, operational, and serviceability advantages in the
delivery of data center cooling air. Outside air enters the
penthouse through vertical louvers into the intake corridor and
if necessary, is mixed with data hall return air. Air then passes
through the filter bank composed of the low efficiency pre-
filters and high efficiency cartridge final filters arranged in
series. The evaporative cooling/humidification room contains
the misting system and mist eliminator where air is treated
before moving into the supply fan room. The supply fans
move air down the supply openings to the cold aisles of the
data halls where it passes through the servers. The exhaust is
then either returned back to the intake corridor or dispelled out
the building [6].
The filter bank spans the entire width of the
Fig. 2: Data center intake corridor with outdoor air and data
center exhaust mixing and filter bank
penthouse corridor with a height of five filters and depth of
two filter types aligned in series as shown in Figure 2.
Synthetic fiber pleated pre-filters are responsible for collecting
large debris such as dirt and insects that enter the penthouse
air stream. The pre-filters have dimensions 24in x 24in x 2in
(0.61m x 0.61m x 0.05m) and are rated MERV 8. Immediately
downstream of the pre-filters are 24in x 24in x 12in (0.61m x
0.61m x 0.30m) extended surface cartridge final filters. The
manufacturer specifies an operating face velocity of 0-750fpm
(0-3.81m/s). These filters are rated MERV 13 and specifically
designed for highly efficient capture of particles down to 0.3
micron sizes. Due to significantly higher cost of cartridge
filters, it is important to characterize their performance and
life cycle.
The penthouse fan wall consists of fourteen arrays of
direct drive plenum fans seen in Figure 3. Consolidating larger
supply fans into a distributed grid of smaller fans promotes
even airflow distribution. Variable frequency drives (VFD) are
employed to minimize operating costs with the fluctuation of
load and fan pressure requirements.
Fig. 1: Path of airflow through mechanical components of data center penthouse design
Fig. 3: Supply fan room with mist eliminator on left and fan
arrays on right
EXPERIMENTAL SETUP
Experimental Setup
In order to evaluate the performance of air filters an
air flow chamber with maximum capacity of 3000cfm
(1.42m3/s) was employed. The air flow bench consists of a
36in (0.91m) inside diameter chamber with a 60Hz blower
connected to one end. The opposite end is open for attachment
of a device under test. A nozzle plate at the center of the
chamber has three 6in (0.15m) diameter nozzles that may be
opened and closed to obtain the desired air flow rate. Pressure
taps on each side of the nozzle plate are used to record
differential pressure across the nozzles and, along with nozzle
effective diameter and loss coefficient, calculate air flow rate
[7]. Additional pressure taps immediately upstream of the
filter under test and open to the ambient record static pressure
drop across the filter. Pressure readings are recorded with
transducers and data logged in data acquisition software on a
workstation. The test setup is shown in Figure 4.
Fig.4: Blower motor and experimental air flow test chamber
used for characterizing filter resistance curves
Fig.5: Dirty final cartridge filter under test on end of the air
flow chamber
By supplying a known air flow volume through the
filter media and recording the pressure drop, the performance
curve for each filter is generated. Positive pressure, built up
inside the air flow chamber was expelled across the filter and
the difference recorded as static pressure at the given flow
rate. Ten measurements of pressure at each flow rate were
taken and three separate data sets for each filter were obtained
to verify repeatability and consistency of the test. A typical
test configuration is shown in Figure 5 with a high efficiency
cartridge final filter attached.
RESULTS AND DISCUSSION
Experimental Filter Characterization
Five clean, unused pre-filter samples were tested to
develop a baseline initial resistance performance curve. A
single clean, unused final cartridge filter was characterized to
serve as the baseline for the performance of the high
efficiency filters.
Samples of six pre-filters were taken post-service
from various locations along the data center penthouse filter
wall. A single final cartridge filter was removed from one of
these locations as well. These filters were in service at the data
center for eight and a half months during normal operation.
They are represented by the “dirty” designation in the
following results. An increase in resistance due to dust and
particulate collection over the course of service was expected
to be seen.
Figure 6 shows the performance curve obtained from
three runs of one clean pre-filter. A second order polynomial
curve fit of each data set was taken, and the static pressure was
interpreted at air flow rates in 200cfm (0.94m3/s) increments
from 600–3000cfm (0.28–1.42m3/s). The values at each of
these points were used to generate a cumulative average for
each filter tested as shown by the solid line in Figure 6. A
similar plot for one of the dirty pre-filter samples is shown in
Figure 7.
Fig.6: Results of three trials and average for resistance curve
of a single clean pre-filter
Fig.7: Results of three trials and average for resistance curve
of a single dirty pre-filter
Compiled results of all clean pre-filters tested are
shown in Figure 8. These samples showed wide variability,
possibly due to the manufacturing process for these low
efficiency filters. The average of the static pressures at each
air flow increment was plotted to generate an average
performance curve for all pre-filters in the clean condition.
The same procedure was followed for six dirty pre-filter
samples and their results shown in Figure 9. The average
performance of all clean pre-filter samples and all dirty pre-
filter samples are compared in Figure 10. A similar
comparison is made in Figure 11 of the clean and dirty final
cartridge filters tested. Only single samples of clean and dirty
final cartridge filters were tested due to their higher cost.
However, since the cartridge filters require a stricter design to
meet MERV 13 specifications, it is assumed they will show
less variability in performance between clean samples than
seen in the pre-filters.
Fig.8: Average resistance values at tested airflow rates for all
characterized clean pre-filters
Fig.9: Average resistance values at tested airflow rates for all
characterized dirty pre-filters
Fig.10: Comparison of the average resistance curves of the
clean and dirty pre-filters sample sets
Fig.11: Comparison of the average resistance curves of the
clean and dirty final cartridge filters
Since the air filters are in a series configuration in service in
the data center penthouse, a test in which a clean pre-filter and
clean final filter attached together was performed. An
equivalent test was performed with the dirty pre and final
filters that were removed from the same location in the filter
wall. The results of these series combination tests are shown in
Figure 12.
Table 1 shows the increase in static pressure
observed between the clean and dirty conditions of the pleated
pre-filters, final cartridge filters, and series combination
arrangements tested. The values at each flow rate represent the
average static pressure of all the filters tested for each
condition. The increase in static pressure over the course of
eight and a half months in service is indicated by the
difference and the percent change also shown.
Discussion of Experimental Characterization
Attention should be granted to the wide variability in
resistance curves for the pre-filters. The primary operating
range of interest for the filters is 2000-2600cfm (0.94-
1.23m3/s). Assuming a normal distribution, static pressure of
Fig.12: Comparison of the resistance curves of the clean and
dirty series arrangement test of pre-filter and final filter
clean pre-filters is 0.30±0.06inH2O at 2000cfm and
0.46±0.09inH2O at 2600cfm. For dirty pre-filters, static
pressure is 0.38±0.03inH2O at 2000cfm and 0.59±0.05inH2O
at 2600cfm. Large standard deviations relative to the mean
elicit uncertainty in the measurements; however the authors
are confident in the assumption that dirty filters will, on
average, exhibit a higher static pressure at a given flow rate
when compared to the clean filters.
Part of the experimental uncertainty may be resolved
by including a larger sample size which may possibly discount
instances such as Clean Pre-Filter B in Figure 8 as an outlier.
A larger sample of dirty filters may also provide additional
insight into the effect of location across the large filter bank on
particle and contaminant collection of the filters. Additionally,
the ability to control for the variability in the initial
construction of the pre-filters may be achieved by testing the
filters in the clean condition, placing them in service, then
testing them again in the dirty condition. Dirty filters used in
this study were not characterized prior to service.
Although final cartridge filters are expected to be
held to a higher manufacturing standard, a single sample in the
clean and dirty conditions will not provide a substantial
Clean Dirty Clean Dirty Clean Dirty
600 0.05 0.07 0.02 42 0.06 0.08 0.01 16 0.11 0.14 0.03 27
800 0.07 0.09 0.02 33 0.09 0.10 0.01 15 0.16 0.20 0.04 23
1000 0.10 0.13 0.03 30 0.12 0.14 0.02 13 0.22 0.27 0.05 21
1200 0.13 0.17 0.04 30 0.16 0.18 0.02 11 0.29 0.35 0.06 19
1400 0.17 0.22 0.05 31 0.20 0.22 0.02 9 0.37 0.44 0.07 19
1600 0.20 0.27 0.06 31 0.25 0.27 0.02 8 0.46 0.54 0.08 19
1800 0.25 0.32 0.08 31 0.30 0.33 0.02 8 0.55 0.65 0.10 18
2000 0.30 0.38 0.09 30 0.36 0.39 0.03 8 0.66 0.77 0.12 18
2200 0.35 0.45 0.10 29 0.42 0.45 0.03 7 0.77 0.90 0.13 17
2400 0.40 0.52 0.11 28 0.49 0.52 0.03 6 0.89 1.03 0.14 16
2600 0.46 0.59 0.13 28 0.56 0.59 0.03 5 1.02 1.17 0.16 15
2800 0.52 0.67 0.14 27 0.63 0.66 0.02 4 1.16 1.32 0.17 14
Percent
Change
Difference
(in H2O)
Average Static
Pressure (in H2O)
Series CombinationPre-Filter Final Filter
Flow
Rate
(cfm)
Average Static
Pressure (in H2O)Difference
(in H2O)
Percent
Change
Average Static
Pressure (in H2O)Difference
(in H2O)
Percent
Change
Table 1: Average values of pre-filter, final filter and series combination static pressure drop in clean and dirty conditions
statistical population to make definitive conclusions regarding
overall increase in resistance. Discussions as to the results of
the experimental tests will thus only be general.
Comparison of the increase in resistance between
pleated pre-filters and final cartridge filters indicates the
majority of total system resistance increase occurs due to the
pre-filters. In particular, in the operating range, the increase in
static pressure of the pre-filters over eight and a half months of
service is three to four times that of the final filters.
Depending on the requirements of the data center fan power,
these results indicate that final cartridge filters may be kept in
service for a longer period than the pleated pre-filters. The
inexpensive pre-filters serve an important role in extending the
life of the final filters. This may result in significant cost
savings depending on the facility size and number of filters in
place.
The additive effect of placing the filters in series can
be seen by adding the static pressure values of the pre-filters in
a given condition to the static pressure of the final filter in the
same condition in Table 1. This is as expected since theory
states that the pressure drop across two objects in series is the
sum of each individual components static pressure. This
observation assures that the series combination results can be
used in modeling of the system resistance at the filter wall
level.
Determination of Fan-Filter Interaction Upon installation of the fan wall in the data center
fans are balanced to reduce noise and vibration. Additionally,
a total system resistance curve is obtained to determine the
operating point of the fans within the system. The operating
point can be optimized to the fan speed and VFD requirements
for best performance in a particular application.
Figure 13 shows a representative operating point
between a single fan array and initial system resistance of the
entire penthouse design. The initial resistance curve was
developed by the fan wall manufacturer at the time of
commissioning of the data center facility. This represents the
total system resistance of the penthouse when the filters were
in the clean condition. All the mechanical components in the
penthouse design except for the filter bank are assumed to
have a fixed contribution to the overall system pressure. As
seen in the experimental section, over the course of service,
the clogging of filters will lead to increased resistance for the
fans to overcome.
To determine the contribution to the penthouse
system static pressure from components such as the outdoor
air intake louvers and misting system, a resulting correction
curve must be obtained. Additionally, a simplifying
assumption that all fan arrays operate at the same frequency
was made. To establish the correction curve, the airflow
values of the initial system curve were multiplied by the total
number of fan arrays in the penthouse, giving the airflow of
the entire data center versus the static pressure of the system.
The airflow value of the total data center curve was divided by
the total number of filter locations (pre-filter/final filter series
combinations in the filter bank) to establish the system curve
on a per filter airflow basis. The difference between per filter
initial system curve and the experimentally acquired clean
Fig. 13: Initial operating point between a representative fan
curve of a single fan array and the penthouse system resistance
with clean filters at time of commissioning of the data center
Fig. 14: Correction curve obtained from the difference of the
initial system curve and clean filter series combination
experimental curve
series combination filter curve is shown in Figure 14 and
represents the correction curve. Once the correction curve is
obtained, it is added to the experimental dirty series
combination filter curve. This represents the total static
pressure of the penthouse that must be overcome by supply
fans after the filters have been in service for eight and a half
months. Using a similar strategy as above to plot the dirty
system curve on a per fan array basis, Figure 15 shows the
penthouse system curves for both the clean, initial condition
and the dirty condition. The operating points of the
representation of the fan array fan curve along with an
illustrative power curve of a fan array are also included. The
power curve dictates the amount of power required to achieve
the fan speed necessary for the operating flow rate. The two
crosses in Figure 15 indicate the airflow rate of the clean and
dirty system operating points projected onto the power curve.
A decrease in airflow due to increased
Fig.15: Operating point of representative fan array fan curve
and power curve for both clean and dirty filter conditions
resistance of the filters corresponds to additional power
required to drive the fans.
Table 2 shows a comparison of the overall cooling
system in both clean and dirty filter conditions. It is shown
that the 0.07inH2O (25Pa) increase in total system pressure
from the clogging of filters has resulted in a 1.5% decrease in
total air flow through each filter, fan array, and the penthouse.
This corresponds to a 1.7% increase in the brake horse power
required to operate the fans.
The brake horse power of a fan accounts for the
efficiency of the motor. The total input power to the fans is
given by:
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The motor efficiency is assumed to be 0.9, which is a
characteristic representation of large commercial HVAC
system fans [8]. From this, total input power to a single supply
fan array is 41.90hp (30.82kW) and 42.62hp (31.35kW)
during the clean and dirty filter conditions respectively.
Table 2: Airflow and fan power comparison between clean
and dirty conditions
The designed operating point of this system on a per
filter basis is 2105cfm (0.99m3/s) and 1.57inH20 (391Pa).
Static pressure at this airflow for the clean series combination
of filters is 0.71inH2O (177Pa). This represents 46% of the
total static pressure in the system. In the dirty condition, the
0.81inH2O (202Pa) static pressure contributed by filters at the
fan operating point airflow rate represents 49% of the total
system resistance. This indicates that nearly half of the overall
system impedance that the supply fans must overcome is due
to filters.
CONCLUSION
Air filters from a data center operating with an air-side
economizer were experimentally characterized to determine
their airflow rate versus static pressure curves. Small sample
sizes of clean, unused filters were compared to dirty filters that
were removed from service after eight and a half months
during normal operation. Both synthetic fiber pleated pre-
filters and high efficiency final cartridge filters were tested.
This data was used to evaluate the increase in system
resistance during the course of service of these filters types.
An evaluation of the impact on the data center supply fan
power required was made by comparing the experimental data
with the fan curves and power curves of the data center supply
air fans at the time of commissioning. Findings from this
limited study suggest the following:
(1) The increase in filter resistance after the service time
under study is primarily attributed to the pre-filters.
Pre-filters accounted for roughly 75% of the total
increased static pressure across the pre-filter and final
filter series combinations. Depending on operational
needs, higher cost final filters may be kept in service
for longer periods while the pre-filters are replaced
on a more frequent schedule.
(2) The air filters contributed close to half of the total
system resistance through the data center in both
clean and dirty conditions.
(3) For the data center under study, the increased
resistance due to eight and a half months of service
time for the air filters resulted in only minimal
increase in the total power required to operate the
data center supply air fans.
Future work in this area may include characterization of a
larger sample of filters and over a wider range of service time
intervals. The information and corresponding fan power
analysis of this study may serve as a first step in understanding
air filter performance and aid in optimizing air filter
replacement life cycle required for the most energy and cost
efficient operation of the data center.
ACKNOWLEDGEMENTS
The authors would like to acknowledge the assistance
of Fred Taylor of Air Measurements Systems in validation of
the test procedures. Additional gratitude is owed to teammates
Naveen Kannan and Kushal Aurangabadkar in data collection
for characterization of the air filters.
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