1

Sponsored in 

part by 

Federal Emergency 

Management Agency 

U.S. Fire Administration 

Characterizing Positive Pressure Ventilation

using Computational Fluid Dynamics

Stephen Kerber

William D. Walton

NISTIR 7065
2

Characterizing Positive Pressure Ventilation 

using Computational Fluid Dynamics

Prepared for

U.S. Department of Commerce

Building and Fire Research Laboratory

National Institute of Standards and Technology

Gaithersburg, MD 20899-8661

By

Stephen Kerber

William D. Walton

NIST XXXX

February 2003

U.S. Department of Commerce

Donald L. Evans, Secretary

Technology Administration

Phillip J. Bond, Under Secretary for Technology

National Institute of Standards and Technology

Arden L. Bement, Jr., Director

Federal Emergency Management Agency 

Joe M. Allbaugh , Director 

U.S. Fire Administration 

R. David Paulison, Administrator
iii

Table of Contents 

List of Tables .................................................................................... iv 

List of Figures .................................................................................. v 

Abstract .......................................................................................... vi 

1. INTRODUCTION ................................................................... 1 

1.1. What is Positive Pressure Ventilation? .................................... 1 

2. MAPPING PPV VELOCITY FIELD - PHASE I ............................. 2 

 2.1. Experimental Description ................................................... 2 

 2.1.1. Experimental Facility .............................................. 2 

 2.1.2. Experimental Components ........................................ 2 

 2.1.3. Experimental Procedure............................................ 4 

 2.1.4. Flow Visualization Experiment .................................... 5 

 2.2. Computer Model .............................................................. 6 

 2.2.1. Fire Dynamic Simulator ............................................ 6 

 2.2.1a Model Uncertainty ......................................... 6 

2.2.2. Smokeview .......................................................... 7 

2.2.3. FDS Input ............................................................ 7 

 2.2.3a Geometry and Vents ....................................... 7 

 2.3. Results ......................................................................... 9 

3. SINGLE ROOM EXPERIMENT – PHASE II .............................. 13 

 3.1. Experimental Description ................................................... 13 

 3.1.1. Experimental Facility .............................................. 13 

 3.1.2. Experimental Components ........................................ 13 

 3.1.3. Experimental Layout ............................................... 14 

3.1.4. Experimental Procedure ........................................... 15 

3.1.5. Flow Visualization Experiment .................................... 16 

 3.2. Computer Model .............................................................. 17 

 3.2.1. FDS Input ............................................................ 17 

 3.2.1a Geometry and Vents ....................................... 17 

 3.3. Results ......................................................................... 19 

4. UNCERTAINTY ..................................................................... 23 

5. DISCUSSION ......................................................................... 24 

6. REFERENCES ...................................................................... 28 

7. ACKNOWLEDGMENTS ......................................................... 28 
iv

List of Tables 

Table 1. Comparison of Phase I Experimental and FDS Results ........................... 9 

Table 2. Comparison of Phase II Experimental and FDS Results........................... 19

Table 3. Uncertainty in Experimental Data 23

Table 4. Summary of FDS Fan Characteristics Needed to Create an Accurate Flow.... 24

Table 5. Summary of Multiblock Characteristics Needed to Create an Accurate Flow.. 24
v

List of Figures 

Figure 1. The cone of air and how PPV works ......................................... 1

Figure 2. The flow characterization grid ............................................... 2

Figure 3. Flow visualization threads on felt background ............................. 2

Figure 4. Front and back of the positive pressure fan ................................. 3

Figure 5. Anemometer ..................................................................... 4

Figure 6. Anemometer in indexer on track ............................................. 4

Figure 7. Phase I experimental layout ................................................... 4

Figure 8. Phase I measurement points ................................................... 5

Figure 9. Smoke generator flowing ...................................................... 5

Figure 10. Layout for phase I supplemental test ....................................... 5

Figure 11. Visualization of PPV flow ................................................... 6

Figure 12. Fan and smoke generator in Phase I visualization test ................... 6

Figure 13. FDS layout visualized with smokeview .................................... 8

Figure 14. Fine grid cell visualization used for computations ....................... 8

Figure 15. FDS PPV fan visualized in smokeview .................................... 8

Figure 16. Smokeview visualization of FDS PPV flow pattern ..................... 9

Figure 17. Experimental velocities 1830mm (6 ft) from the fan .................... 10

Figure 18. FDS velocities 1830 mm (6 ft) from the fan .............................. 10

Figure 19. Experimental velocities 2440 mm (8 ft) from the fan ................... 11

Figure 20. FDS velocities 2440 mm (8 ft) from the fan .............................. 11

Figure 21. Experimental velocities 3050 mm (10 ft) from the fan .................. 12

Figure 22. FDS velocities 3050 mm (10 ft) from the fan ............................. 12

Figure 23. Floor plan of Phase II room ................................................. 13

Figure 24. Test layout for phase II ...................................................... 14

Figure 25. Test layout looking at room inlet and outlet .............................. 14

Figure 26. Inlet and outlet from a different perspective .............................. 15

Figure 27. Phase II measurement points in the doorway (inlet) ..................... 15

Figure 28. Phase II measurement points in the window (outlet) ..................... 16

Figure 29. Visualization of Phase II supplemental experiment as soon 

 as room is pressurized ................................................................ 16

Figure 30. Visualization of Phase II once constant flow is achieved ............... 17

Figure 31. FDS layout for Phase II ...................................................... 18

Figure 32. Grid cell visualization, multiblocking ..................................... 18

Figure 33. FDS layout looking at room inlet and outlet .............................. 19

Figure 34. FDS layout with fan operating .............................................. 20

Figure 35. Orientation of velocity graphs .......................................................... 20

Figure 36. Experimental velocity measurements in the doorway (inlet) ............ 21

Figure 37. FDS velocities in the doorway (inlet) ...................................... 21

Figure 38. Experimental measurements in the window (outlet) ..................... 22

Figure 39. FDS velocities in the window (outlet) ..................................... 22

Figure 40. Smokeview visualization of FDS PPV flow pattern ..................... 23

Figure 41. Experimental visualization of the PPV flow pattern ..................... 23

Figure 42. FDS visualization of Phase II supplemental experiment as soon as the 

 room is pressurized .................................................................... 26

Figure 43. Visualization of Phase II supplemental experiment as soon as the 

 room is pressurized ......................................................................... 26

Figure 44. FDS visualization of Phase II once constant flow is achieved .......... 27

Figure 45. Visualization of Phase II once constant flow is achieved ................ 27
vi

Characterizing Positive Pressure Ventilation using Computational Fluid Dynamics 

Stephen Kerber 

William D. Walton 

Abstract 

Data from two different sets of full-scale experiments are compared with simulations 

completed with the computational fluid dynamic model, the Fire Dynamic Simulator 

(FDS). The full-scale experiments characterize a Positive Pressure Ventilation (PPV) fan 

in an open atmosphere and in a simple room geometry. The measurements of both 

experiments compare favorably with the Fire Dynamic Simulator results. With the 

correct geometry, vent placement, and boundary location FDS predicted velocities that 

were within 10 percent for the open atmosphere and 20 percent for the simple room 

geometry. FDS’s visualization of the positive pressure ventilation fan’s flow pattern, and 

the flow out of the window also correlated well with those measured experimentally. 

Disclaimer 

Certain trade names and company products are mentioned in the text or identified in an 

illustration in order to specify adequately the experimental procedure and equipment 

used. In no case does such identification imply recommendation or endorsement by the 

National Institute of Standards and Technology, nor does it imply that the products are 

necessarily the best available for the purpose. 
1

1 INTRODUCTION 

This research effort used a series of full-scale experiments to examine how positive 

pressure ventilation (PPV) may impact structural ventilation. These same experiments 

were simulated using the NIST Fire Dynamics Simulator (FDS) to provide more insight 

into the impact of ventilation on fire behavior. Comparing the computer simulations 

with the full-scale test results allows the computer simulation to be validated and if 

necessary, identifies areas that need improvement. Ultimately, using computer models to 

simulate the effects of PPV could be used to improve fire fighter safety by enabling 

improved understanding of structural ventilation techniques. 

PPV fans are engineered to maximize airflow while allowing the fan to remain light and 

durable for fire service use. Simply, a blade or impeller pulls air through a shroud 

creating the airflow. This blade or impeller is driven by an electric or gasoline motor all 

of which are mounted in a frame. The velocity field that is created is complex due to the 

speed at which the blade or impeller rotates to achieve a conical flow. These experiments 

examine FDS’s ability to accurately characterize this complex flow. 

This work will lead to a better understanding of the effective use of ventilation and the 

development of guidelines for the most effective use of positive pressure ventilation, 

including when it should and should not be used. These are both concerns that the fire 

service has documented in reference [1]. 

1.1 What is Positive Pressure Ventilation? 

Positive pressure ventilation is a technique used by the fire service to remove smoke, heat 

and other combustion products from a structure. This allows the fire service to perform 

other tasks in a more tenable atmosphere. Typically a positive pressure ventilation fan is 

placed about 1.82 m to 3.0 m (6.00 ft to 10.00 ft) from the doorway of the structure. It is 

positioned so that the “cone of air” produced by the fan extends beyond the boundaries of 

the opening. With the doorway within the fan discharge, air pressure inside the structure 

increases. An exhaust opening in the structure, such as an opening in the roof or an open 

window, allows the air to escape due to the difference between the inside and outside air 

pressure. The smoke, heat and other combustion products are pushed out of the structure 

and replaced with fresh air [2]. 

Figure 1. The cone of air and how PPV works [3]. 
2

2 MAPPING PPV VELOCITY FIELD - PHASE I 

2.1 Experimental Description 

The initial series of experiments served to determine the flow created by PPV fans. In 

order to implement a PPV fan in FDS it was necessary to characterize the fan in terms of 

FDS input parameters. This basic environment was an open atmosphere with the fan 

located on a stand that had negligible effects on the flow, essentially placing the fan in 

open space. This placement minimized the impact from obstructions such as walls and 

doorways on the flow. 

2.1.1 Experimental Facility 

These experiments were conducted at NIST’s Building and Fire Research Laboratory 

Large Fire Facility. The experiment was located in an area inside the facility so that the 

airflow created by the PPV fan was not affected by external factors such as wind or 

weather. The facility has the interior dimensions, 36.6 m (120.0 ft) long, 18.3 m (60.0 ft) 

wide and 7.6 m (25.0 ft) high. 

2.1.2 Experimental Components 

Grid 

A grid frame, 2.44 m x 2.44 m (8.00 ft x 8.00 ft), was constructed with 51 mm x 102mm 

(2.00 in x 4.00 in) wood members a square configuration. The corners were reinforced 

with plywood triangles. Cotton strings approximately 1.6 mm (0.0625 in) in diameter 

were placed on the grid both vertically and horizontally marking points on the grid. The 

center was highlighted by using orange string, while white strings were placed every 102 

mm (4.00 in) for the first 305 mm (12.00 in) then every 152 mm (6.00 in) towards the 

edge of the frame in both directions. The frame was notched to keep the strings in place 

(Figure 2). Once the strings were all in place, 203 mm (8.00 in) long threads were added 

to each point on the grid. These threads made it possible to view the direction of airflow 

(Figure 3). Finally, black felt was added to the frame, parallel to the threads in order to 

give a contrasting background to the threads to aid in flow visualization. The felt did not 

appear to have a significant impact on the measured flow. 

 

 Figure 2. The grid. Figure 3. Threads on felt 

 background.
3

Fan 

The fan used was an 18-inch, variable speed, electric positive pressure ventilator. The 

fan has a depth of 476 mm (18.8 in), width of 622 mm (24.5 in) and height of 622 mm 

(24.5 in). It has a maximum speed of 2200 RPM, a rating of 746 watts (1 hp) and a rating 

of 6.64 m3/s (14,060 ft3/min). The fan was mounted on a stand to set the fan at the proper 

height of 1.28 m (50.5 in), measured from the center of the fan to the ground (Figure 4). 

The grid was positioned so that the center of the fan impeller was on the centerline of the 

grid. 

Anemometer 

The digital anemometer used was a 25.4 mm (1.00 in) diameter vane-type probe (Figure 

5). It is microprocessor-based with a range of 0.3 m/s (59 ft/s) to 35.0 m/s (6890 ft/m) 

with an accuracy of 0.5% of the readings [4]. In order to position the anemometer at 

various locations, an anemometer indexer was fabricated. The indexer allowed the 

anemometer to be placed at any point on the grid by moving it horizontally and vertically. 

The indexer also permitted the anemometer to rotate in both the x and y-axis. This 

rotation allowed the measurement of velocities that were not parallel to the ground and 

perpendicular to the fan. The indexer moved horizontally across the grid on wheels that 

were grooved to ride an angle iron track. This track was positioned on the ground 

parallel with the grid (Figure 6). 

Figure 4. Front and back of the positive 

pressure fan and stand.
4

 

 Figure 5. Anemometer. Figure 6. Anemometer in 

 indexer on track. 

2.1.3 Experimental Procedure 

The grid and track were placed perpendicular to the flow. The fan was positioned so that 

the flow was centered on the grid 1.28 m (50.5 in) above the floor. The anemometer 

indexer was moved along the track and its height adjusted to correspond with 

measurement positions on the grid. (Figure 7) The vane of the anemometer was 

maintained perpendicular to the flow. The fan was started and run for two minutes at the 

maximum speed of 2200 rpm. The anemometer output was recorded every two seconds 

for four minutes using 16 second averaging. This process was repeated for the selected 

points on the grid shown in figure 8. 

Figure 7. Phase I experimental layout. 
5

 

 

2.1.4 Flow Visualization Experiment 

In order to visualize and qualify the flow from the fan a supplemental test was performed. 

A smoke generator was placed 304.8 mm (1 ft) to the rear of the fan (Figure 12). The fan 

was turned on 2200 rpm and allowed to warm up. The smoke generator was then turned 

on to maximum output and pictures were taken against a black background with heights 

labeled in 304.8 mm (1 ft) intervals and widths labeled in 609.6 mm (2 ft) intervals. See 

figures 9-12. 

Figure 9. Smoke generator flowing Figure 10. Layout for phase I 

flow visualization experiment. 

 Figure 8. Phase I measurement points. 
6

 

 Figure 11. Visualization of PPV flow. Figure 12. Fan and smoke generator in 

 phase I visualization experiment. 

2.2 Computer Model 

2.2.1 Fire Dynamic Simulator 

NIST has developed a computational fluid dynamics (CFD) fire model using large eddy 

simulation (LES) techniques [5]. This model, called the NIST Fire Dynamics Simulator 

(FDS), Version 3.0, has been used to simulate the flame spread, temperatures and gas 

flows resulting from a compartment fire [6]. A CFD model requires that the room, 

building or atmosphere of interest be divided into three-dimensional rectangular control 

volumes or computational cells. The CFD model computes the density, velocity, 

temperature, pressure, and species concentration of the gas in each cell. Based on the 

laws of conservation of mass, momentum, species and energy the model tracks the 

generation and movement of gases. FDS utilizes material properties of the furnishings, 

walls, floors, and ceilings to compute fire growth and spread. A more complete 

description of the FDS model is provided in reference [5]. 

2.2.1a Model Uncertainty 

FDS can provide valuable insight into how a fire may develop or how the combustion 

gases will move throughout the structure. However the model is only a simulation. The 

model output is dependent on a variety of input and default values such as computational 

cell size, material properties, geometry, and vents. 

The ability of the FDS model to accurately predict the temperature and velocity of fire 

gases has been previously evaluated by conducting experiments, both lab-scale and fullscale, and measuring quantities of interest. For relatively simple fire driven flows, such 

as buoyant plumes and flows through doorways, FDS predictions are within the 

experimental uncertainty of the values measured in the experiments [7]. For example, if 

a gas flow velocity is measured at 0.5 m/s with an experimental uncertainty of ± 0.05 

m/s, the FDS model gas flow velocity predictions were also within the range between 

0.45 m/s and 0.55 m/s. 

In large-scale fire tests reported in [6], FDS temperature predictions were found to be 

within 15% of the measured temperatures and the FDS heat release rates were predicted 
7

to within 20% of the measured values. Therefore the results are presented as ranges to 

address these uncertainties. 

These experiments attempt to prove that using the correct set of inputs; FDS is able to 

model the flows of positive pressure ventilation fans within a desirable uncertainty. 

2.2.2 Smokeview 

Smokeview is a scientific visualization program that was developed to display the results 

of a FDS computation. Smokeview can produce animations or snapshots of FDS results 

[8]. This project used Smokeview to generate a series of planar slices. A slice file allows 

a user to record various gas phase quantities such as velocity at more than a single point. 

Each slice can portray a specific set of data, such as gas temperature or gas velocity for 

each location on that slice plane. Smokeview allows the user to animate a series of slices 

to help visualize how the data develops or changes throughout the computer model 

simulation. A series of temperature slices can be replayed to see how the temperature 

profiles develop along a specific plane in a structure. Figure 16 shows a vertical slice file 

along the center of the domain. 

2.2.3 FDS Input 

Inputs required by FDS in order to model PPV fans include, domain size, computational 

cell size, simulation duration, vent velocity, vent geometry, fan geometry, slice location 

and velocity measurement points. Many inputs were used for preliminary FDS runs, 

which are explained in the following sections. 

2.2.3a Geometry and Vents 

Many considerations need to be taken into account when modeling a PPV fan using FDS. 

The most important is the computational cell size. The cells need to be on the order of 

16.4 cm3

 (1.00 in3). Once the cells are prescribed greater than 21.3 cm3 (1.10 in3) the 

flow from the fan becomes linear and inaccurate. The cell size in the computation in 

figures 13-15 is 16.4 cm3

 (1 in3). The next consideration is the domain size. There needs 

to be at least 1 m (3.3 ft) to the rear of the fan in order for it to function accurately. If the 

fan is prescribed at or within 1 m (3.3 ft) of the boundary, whether it is “open” or not, the 

fan flow will not be predicted properly. The obstructions and vents that make up the fan 

itself need to be prescribed correctly. FDS only allows for rectangular obstructions and 

vents to be created, so this leads to an issue due to the cylindrical nature of the fan 

shroud. In order to get a proper flow pattern the shroud must be prescribed as a series of 

obstructions oriented in a circle such as figure 15. The degree of roundness depends on 

the accuracy that is desired. The shroud in figure 15 yielded good results but the shroud 

can be created more cylindrical if desired. It is not recommended to further square off 

the shroud using fewer obstructions. 

The vents are prescribed to the interior dimensions of the shroud. They also must be 

located on the front of the shroud, opposite the motor and handle. This allows air to be 

pulled through the shroud creating a more realistic flow pattern. If the vents are placed to 

the rear or middle of the shroud the flow pattern will appear linear and unrealistic. The 

vents also had a prescribed velocity. Numerous velocities were examined within FDS 

and the velocity that provided the best result was 17.89 m/s (40.00 mi/h). This input is 
8

based on maximum speed of the experimental PPV fan. Altering this input allows the 

user to characterize the fan operating at different speeds. The final items are the 

obstructions in the center of the fan, simulating the center of the blade connected to the 

shaft, and the motor and handle to the rear of the shroud. These obstructions were found 

to create a more realistic flow pattern. They affect the air moving through the shroud in 

FDS similarly as they did experimentally. Pulling air past the motor affects the flow 

pattern significantly so it must be included in the model. Finally slice files and prediction 

points were prescribed. The slice files were placed at the center of the fan in both the 

horizontal and vertical directions to visualize the flow pattern. Velocity measurement 

points were placed in the model in conjunction with the measurement points used 

experimentally, in order to make a good comparison of the two (1.83 m, 2.44 m, and 3.05 

m (6 ft, 8 ft and 10 ft) from the PPV fan). 

 

Figure 13. FDS layout visualized with Figure 14. Fine grid cell visualization used for 

 smokeview. computations. 

 Figure 15. FDS PPV fan visualized in 

 smokeview. 

Fan Shroud 

Motor 

Vents 

Blade Center 

Handle 
9

2.3 Results 

Velocity measurements were taken at the locations in figure 8. These measurements 

were recorded with the fan at 1.83 m, 2.44 m, and 3.05 m (6 ft, 8 ft and 10 ft) from the 

anemometer, corresponding to typical distances of a positive pressure ventilation fan 

from a structure. The magnitudes of the velocities are shown in figures 17, 19 and 21. 

The average velocities of the three distances were 2.42 m/s, 2.72 m/s and 3.35 m/s (7.90 

ft/s, 8.90 ft/s and 11.00 ft/s) respectively. Using NIST’s Fire Dynamic Simulator, many 

runs were performed examining the possibilities of creating a PPV fan that closely 

portrays the actual fan that was used for experimentation. The final fan that was created 

and used in the FDS runs, figure 15, yielded velocity measurements that are graphed in 

figures 18, 20 and 22. The average velocities of the three distances were 2.65 m/s, 3.19 

m/s and 3.25 m/s (8.7 ft/s, 10.5 ft/s and 10.7 ft/s) respectively. This comparison gives an 

average difference of slightly less than 10 %. The quality of the flow can be compared in 

figures 39 and 40. 

Table 1. Comparison of Phase I Experimental and FDS Results. 

 Average Velocities (m/s (ft/s)) 

Distance To Anemometer 1830 mm (6 ft.) 2440 mm (8 ft.) 3050 mm (10 ft.) 

Experimental 2.42 (7.9) 2.72 (8.9) 3.35 (11.0) 

Fire Dynamic Simulator 2.65 (8.7) 3.19 (10.5) 3.25 (10.7) 

Percent Difference (%) 8.7 14.7 3.1 

Figure 16. Smokeview visualization of FDS PPV flow pattern. 
10

Figure 17. Experimental velocities 1830mm (6 ft) from the fan. 

The center of the fan is located at (0,0). 

Figure 18. FDS velocities 1830 mm (6 ft) from the fan. 
11

Figure 19. Experimental velocities 2440 mm (8 ft) from the fan. 

Figure 20. FDS velocities 2440 mm (8 ft) from the fan. 
12

Figure 21. Experimental velocities 3050 mm (10 ft) from the fan. 

Figure 22. FDS velocities 3050 mm (10 ft) from the fan. 
13

3 SINGLE ROOM EXPERIMENT – PHASE II 

3.1 Experimental Description 

A series of experiments were conducted to determine the impact that basic room 

geometries have on the flow of PPV fans. The experimental results were compared to 

FDS simulations to see if FDS predicts the airflow accurately. Just as in phase I, the 

results were both qualitative and quantitative. 

3.1.1 Experimental Facility 

These experiments were also conducted at NIST’s Building and Fire Research 

Laboratory Large Fire Facility. The experiment was located in an area within the facility 

so that the airflow created by the PPV fan was not affected by external factors to the 

experiments. The facility has the interior dimensions, 36.6 meters (120 ft) long, 18.3 

meters (60 ft) wide and 7.6 meters (25 ft) high. 

3.1.2 Experimental Components 

Fan and Anemometer 

The same fan and anemometer were used in phase I and phase II. A complete description 

can be found in section 2.1.2 of this report. 

Room 

The floor plan for the room was shown in figure 23. The room was on a 203 mm (8 in) 

high base with a plywood decking and had a ceiling that was 2,640 mm (8 ft - 8 in) high, 

measured from the top of the base. The window on the left hand side of the room was 

located 457 mm (18 in) off the floor and was 1,372 mm (54 in) tall. The door centered in 

the front wall was 2032 mm (80 in) tall. There was a 1.8 m (6 ft) overhang that extended 

over the front of the room (Figure 26). 

Window sill height = 457mm

Ceiling height = 2642mm

Door height = 2032mm

3657mm 914mm

5485mm

7314mm

3200mm 914mm

Figure 23. Floor plan of Phase II room. 
14

3.1.3 Experimental Layout 

The room was constructed and was not furnished with carpeting or furniture. The fan 

was positioned in the center of the doorway and allowed to run at maximum rpm. The 

cone of air coming from the fan covered the doorway when the fan was 3050 mm (10 ft) 

from the doorway so that was the location chosen for the tests. The doorway and window 

were marked with anemometer measurement locations. These locations can be seen in 

figures 27 and 28. The measurement setup is shown in figure 24 and the inlet and outlet 

of the room are shown in figure 25. 

Figure 24. Experimental layout for phase II. 

Figure 25. Experimental layout looking at room inlet and outlet. 
15

Figure 26. Inlet and outlet from a different perspective. 

3.1.4 Experimental Procedure 

The fan was turned on and allowed to run for two minutes at maximum speed, 2200 

RPM. While the fan was running, the door was rechecked to make sure there was a cone 

of airflow around the door, and the window was checked to make sure there was a 

constant flow prior to measurement. Once the fan had been running for two minutes the 

data recording was started. Four minutes of readings were taken without rotating the 

anemometer. Signals were sampled every two seconds and the signal record was the 

average of eight continuous samples. Readings were taken at specific points at the door 

and window as seen in figures 27 and 28 in order to record the air flow through the room. 152mm 508mm 2030mm

914mm

457mm

152mm 152mm 152mm 508mm 1015mm

Figure 27. Phase II measurement points in the doorway (inlet). 
16

914mm

686mm

1372mm

152mm 152mm

152mm

457mm

152mm

Figure 28. Phase II measurement points in the window (outlet). 

3.1.5 Flow Visualization Experiment 

In order to visualize and qualify the flow through the room a supplemental experiment 

was performed. A smoke generator was placed in the room and turned on to produce 

enough simulated smoke in order to fill the room. Cameras were set up and the fan was 

turned on to the maximum, 2200 rpm. Pictures were taken of the simulated smoke flow 

from the room on a black background to be compared to the FDS simulations. See 

figures 29 and 30. 

Figure 29. Visualization of Phase II supplemental 

experiment as soon as room is pressurized. 
17

Figure 30. Visualization of phase II once constant 

 flow is achieved. 

3.2 Computer Model 

3.2.1 FDS Input 

The inputs required by FDS in order to model the PPV fan for this experiment were the 

same as those in phase I. The difference was the addition of the room. The room 

required additional inputs such as the properties of the ceiling, walls and openings. 

3.2.1a Geometry and Vents 

The PPV fan used for these runs was the same fan created in phase I. (See section 2.2.3a 

for details on fan geometry and vent considerations.) Phase II involved the addition of a 

room with dimensions of that in figures 24-26. This room was prescribed in FDS as a 

series of blocks with characteristics of gypsum board. The dimensions and openings 

were the same as those in the experimental setup. All of the room boundaries, including 

the walls and ceiling were contained within the domain. None of the room envelope 

obstructions were formed by the use of a boundary. The main issue that arises with the 

use of both the fan and the room is computational cell size. As stated in phase I, the fan 

required a computational cell size of 16.4 cm3

 (1.00 in3). If the domain containing the 

fan and room were completely 16.4 cm3

 (1.00 in3) cells then there would be in excess of 

15 million cells. Past experience with FDS suggested that the amount of cells should 

remain less than one million cells in order to keep computer computational time down. 

With 15 million cells one simulation would require over a month to complete. 

In order to minimize the number of cells and still maximize the accuracy of the 

calculation FDS has a feature entitled multiblocking. Multiblocking enables the user to 

save computational time by applying relatively fine grids in areas that need it and coarse 

grids elsewhere [8]. In this case a fine grid is used for the domain surrounding the fan 

and a coarser grid is used for the room. There are many considerations that need to be 

taken into account when using multiblock, especially for these cases due to the large 

quantity of air movement. The finer grid, the fan grid, must be specified first in the input 

file. This allows FDS to give precedence to this domain and speed up calculation times. 

Second, the grids need to overlap by at least one meter. This helps speed up calculations 

because information is transferred from grid to grid via external boundaries [8]. When 
18

the grids overlap they share the same information, which helps speed up calculations. 

Third, neither of the domain boundaries can be within one meter of the face of the fan. 

This allows for airflow in and out of the fan. Placing the end of a domain too close to the 

fan face causes a linear flow, which is not accurate. Next, the fan grid should not be 

embedded within the room grid. When this is done information is not transferred 

between the grids and there will be no results for the fan. Finally, the cell size for the 

room domain should not be larger than 65.6 cm3

 (4.00 in3). 

Another issue that needs to be addressed is the positioning of the PPV fan. From the 

Smokeview animation, it appears that the fan is floating in mid air. The reason for this is 

the inability of FDS to portray angled geometry. Typically the fire service places the fan 

away from the door and adjusts the angle of the fan to achieve a cone surrounding the 

opening [2]. In order for FDS to achieve this angle there would have to be hundreds of 

pieces prescribed to create the shroud. In order to avoid this, the fan is placed in the 

center of the doorway above floor level. This placement allows for the flow from the fan 

to complete a cone around the opening just as done by the fire service, without using 

hundreds of additional inputs to the model. 

Figure 31. FDS layout for phase II. 

Figure 32. Grid cell visualization, multiblocking. 

Fine grid 

for fan 

Coarse grid 

for room 
19

Figure 33. FDS layout looking at room inlet and outlet. 

3.3 Results 

Velocity measurements were taken at the locations in the door shown in figure 27, and in 

the window in figure 28. These measurements were recorded with the fan 3050 mm (10 

ft) from the front door of the room. Having the fan 3050 mm (10 ft) from the door 

provides a cone of air around the front door per International Fire Service Training 

Association recommendations [2]. The magnitudes of the velocities into the door are 

shown in figure 35. The magnitudes of the outlet velocities at the window are in figure 

37. The average inlet velocity at the door is 2.2 m/s (7.2 ft/s). The average outlet 

velocity at the window is 2.6 m/s (8.5 ft/s). NIST’s Fire Dynamic Simulator was used to 

examine the use of the PPV fan from phase I in the same configuration as in the 

experiment. FDS yielded an average inlet velocity at the door of 4.1 m/s (13.5 ft/s) and 

an average outlet velocity of 3.0 m/s (9.8 ft/s) measured at the window. These 

comparisons give a difference of 84 percent at the door and a difference of 16.5 percent 

at the window. This yields a good comparison at the window, which is the important 

correlation. The air movement at the window is the result of the pressure change in the 

room, interaction of the geometry of the room and the airflow. The door point 

predictions are dependent upon the local turbulence that FDS creates from the fan 

simulation shown in figure 34. Experimentally this turbulence is very complex and 

difficult to measure. Qualitatively, the flow can be compared in figures 41 to 44. 

Table 2. Comparison of Phase II Experimental and FDS Results. 

 Average Velocities (m/s (ft/s)) 

 Door Window 

Experimental 2.2 (7.2) 2.6 (8.5) 

Fire Dynamic Simulator 4.1 (13.5) 3.0 (9.8) 

Percent Difference 84.0 16.5 
20

Figure 34. FDS layout with fan operating. 

Figure 35. Orientation of velocity graphs. 
21

Figure 36. Experimental velocity measurements in the doorway (inlet). 

Figure 37. FDS velocities in the doorway (inlet). 
22

Figure 38. Experimental measurements in the window (outlet). 

Figure 39. FDS velocities in the window (outlet). 
23

4 Uncertainty 

There are different components of uncertainty in the length and velocity measurements 

reported here. Uncertainties are grouped into two categories according to the method 

used to estimate them. Type A uncertainties are those which are evaluated by statistical 

methods, and Type B are those which are evaluated by other means (Taylor and Kuyatt, 

1994). Type B analysis of systematic uncertainties involves estimating the upper (+ α) 

and lower (- α) limits for the quantity in question such that the probability that the value 

would be in the interval (± α) is essentially 100 percent. 

After estimating uncertainties by either Type A or B analysis, the uncertainties are 

combined in quadrature to yield the combined standard uncertainty. Multiplying the 

combined standard uncertainty by a coverage factor of two results in the expanded 

uncertainty which corresponds to a 95 percent confidence interval (2θ). 

Components of uncertainty are tabulated in Table 3. Some of these components, such as 

the velocities, are derived from instrument specifications, while other components, such 

as length measurements include past experience. Each length measurement was taken 

carefully but due to some construction issues such as the size and straightness of the 

lumber, the slots for the strings on the grid having thickness, and the symmetry of the 

rather large room the total expanded uncertainty was estimated to 6 %. The flow 

measurements were taken in the complex flow of the positive pressure ventilation fan, 

which created a total expanded uncertainty of 14 % primarily due to the repeatability and 

the randomness of the measurements. 

Table 3. Uncertainty in Experimental Data 

 Combined Standard 

 Uncertainty 

Total Expanded 

 Uncertainty 

Length Measurements 

 Grid Size 

 String Location 

 Fan Stand Height 

 Anemometer Location 

 Fan Location 

 Room Dimensions 

 Repeatability 

 Random 

± 1 % 

± 0.5 % 

± 0.5 % 

± 1 % 

± 1 % 

± 1 % 

± 2 % 

± 2 % 

 3 % 6 % 

Flow Measurements 

 Calibration 

 Repeatability 

 Random 

± 0.5 % 

± 5 % 

± 5 % 

 7 % 14 % 

Note: Random and repeatability evaluated as Type A, other components as Type B 
24

5 Discussion 

A comparison of the computational fluid dynamic model Fire Dynamic Simulator (FDS) 

was made with data from two different sets of data collected from full-scale experiments. 

The full-scale experiments characterized a Positive Pressure Ventilation (PPV) fan in an 

open atmosphere, and with a simple room geometry. Both experimental data sets 

provide insight into the gas velocities, as well as providing the opportunity to validate the 

predictions of the Fire Dynamic Simulator. 

The measurements for the fan in an open atmosphere compared favorably with the FDS 

predictions. With the correct geometry, vent placement and boundary location FDS 

predicted velocities that were within 10 percent of the experimental results. FDS’s 

visualization of the flow pattern also correlates well with the experimental visualization. 

The measurements for the fan and a single room also compared favorably with the FDS 

predictions for the flow out the window. The flow that was created out of the window in 

FDS was within 20 percent of that measured experimentally. FDS’s visualization of the 

flow out of the window also correlates well with that measured experimentally. 

The results from these two experiments are a good indicator that FDS is able to 

accurately portray the flow created by positive pressure ventilation fans. Future 

experiments need to be conducted to examine the flow in other structures such as a multifloor structures and structures with a more complex geometry. The impact of the fan on 

other factors in the fire environment such as temperature, burning rate, and gas 

concentrations should be examined in future studies. 

Table 4. Summary of FDS Fan Characteristics Recommended for Efficient 

Effective Modeling. 

1 Computational cell size of less than or equal to 16.4 cm3

 (1.00 in3) 

2 At least 1 meter of domain to the rear of the fan 

3 Shroud must be cylindrical 

4 Vents must be located on the front face of the shroud 

5 A velocity must be prescribed for the vents (17.88 m/s for this fan) 

6 A block must be added to the center of the shroud to simulate the blade center 

(effects air movement) 

7 A motor must be added to the rear of the fan (effects air movement) 

Table 5. Recommended Multiblock Characteristics For an Accurate Flow Calculation. 

1 Specify the fan grid (finer) first in the data file 

2 Overlap the grids by at least 1 meter 

3 Neither of the domain boundaries should be within 1 meter of the fan 

4 Do not embed on grid within the other 

5 Computational cell size for the non-fan grid should not be greater than 65.6 cm3

(4.00 in3

) 
25

Figure 40. Smokeview visualization of FDS PPV flow pattern. 

Figure 41. Experimental visualization of the PPV flow pattern. 
26

Figure 42. FDS visualization of Phase II supplemental experiment as soon 

as the room is pressurized. 

Figure 43. Visualization of Phase II supplemental experiment as soon as the 

 room is pressurized. 
27

Figure 44. FDS visualization of phase II once constant flow is achieved. 

Figure 45. Visualization of phase II once constant flow is achieved. 
28

6 References 

1. Walton, William D., Bryner, Nelson, Madrzykowski, Daniel, Lawson, James R., 

Jason, Nora H., Fire Service Needs Workshop Proceeding – San Antonio, Texas, 

October 13-15, 1999. National Institute of Standards and Technology, 

Gaithersburg, MD., NISTIR 6538, July 2000. 

2. Hall, Richard, Adams, Barbara, Essentials of Fire Fighting, 4th ed., Oklahoma 

State University, Stillwater, OK., 1998. 

3. Tempest Technology Corporation, http://www.tempest-edge.com, January 2003. 

4. Omega Engineering Inc., User’s Guide for the HH-31A Handheld Anemometer, 

Stamford, CT, 1996. 

5. Mcgrattan, Kevin B., Baum, Howard R., Rehm, Ronald G., Hamins, Anthony, 

Forney, Glenn P., Fire Dynamics Simulator – Technical Reference Guide, 

National Institute of Standards and Technology, Gaithersburg, MD., NISTIR 

6467, January 2000. 

6. Mcgrattan, Kevin B., Baum, Howard R., Rehm, Ronald G., Large Eddy 

Simulations of Smoke Movement, Fire Safety Journal, vol 30 (1998), p 161-178. 

7. Mcgrattan, Kevin B., Hamins, Anthony, Stroup, David, Sprinkler, Smoke & Heat 

Vent, Draft Curtain Interaction – Large Scale Experiments and Model 

Development, National Institute of Standards and Technology, Gaithersburg, 

MD., NISTIR 6196-1, September 1998. 

8. Mcgrattan, Kevin B., Forney, Glenn P., Fire Dynamics Simulator – User’s 

Manual, National Institute of Standards and Technology, Gaithersburg, MD., 

NISTIR 6469, Rev. 1, May 2002. 

9. Super Vacuum Manufacturing Company, Inc., http://www.supervac.com, January 

2003. 

7 Acknowledgements 

Appreciation is extended to Dan Madrzykowski, Kevin Mcgrattan and Glenn Fourney of 

the Building and Fire Research Laboratory for their technical assistance. In addition, I 

would like to thank Bill Twilley and Roy McLane for their support with setting up and 

running the experiments. Finally I would like to thank Robert T. McCarthy of the United 

States Fire Administration for his support of this project. 
29