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: richard.eiland@mavs.uta.edu

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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[3] ASHRAE, “ANSI/ASHRAE Standard 52.2-2007, Method

of Testing General Ventilation Air-Cleaning Device for

Removal Efficiency by Particle Size,” Atlanta: American

Society of Heating, Refrigeration and Air-Conditioning

Engineers, Inc., 2007.

[4] ASHRAE, “Particulate and gaseous contamination for data

centers. TC 9.9 white paper,” American Society of Heating,

Refrigeration and Air-Conditioning Engineers, Atlanta, GA;

2011.

[5] Shehabi, A. et al., “Particle Concentrations in Data

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[6] Park, J., “Data Center V1.0,” Open Compute Project.

http://opencompute.org, 2011.

[7] Instruction Manual for AMCA 210-99 Airflow Test

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[8] Fisk, W.J. et al., “Performance and Costs of Particle Air

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