DOT/FAA/AR-03/34 

Office of Aviation Research 

Washington, D.C. 20591

Comparison of Actual and 

Simulated Smoke for the 

Certification of Smoke Detectors 

in Aircraft Cargo Compartments 

November 2003 

Final Report 

This document is available to the U.S. public 

through the National Technical Information 

Service (NTIS), Springfield, Virginia 22161. 

U.S. Department of Transportation 

Federal Aviation Administration
NOTICE 

This document is disseminated under the sponsorship of the U.S. 

Department of Transportation in the interest of information exchange. The 

United States Government assumes no liability for the contents or use 

thereof. The United States Government does not endorse products or 

manufacturers. Trade or manufacturer's names appear herein solely 

because they are considered essential to the objective of this report. This 

document does not constitute FAA certification policy. Consult your local 

FAA aircraft certification office as to its use. 

This report is available at the Federal Aviation Administration William J. 

Hughes Technical Center's Full-Text Technical Reports page: 

actlibrary.tc.faa.gov in Adobe Acrobat portable document format (PDF). 
 Technical Report Documentation Page 1. Report No.

DOT/FAA/AR-03/34

2. Government Accession No. 3. Recipient's Catalog No.

 4. Title and Subtitle

COMPARISON OF ACTUAL AND SIMULATED SMOKE FOR THE 

5. Report Date 

November 2003

CERTIFICATION OF SMOKE DETECTORS IN AIRCRAFT CARGO 

COMPARTMENTS 

6. Performing Organization Code

7. Author(s)

Jill Suo-Anttila, Walt Gill, and Louis Gritzo 

8. Performing Organization Report No. 

9. Performing Organization Name and Address

Fire Science and Technology

Sandia National Laboratories

10. Work Unit No. (TRAIS) 

 

Fire Science and Technology

Albuquerque, NM 87185-0836

11. Contract or Grant No.

 12. Sponsoring Agency Name and Address

U.S. Department of Transportation 

Federal Aviation Administration

13. Type of Report and Period Covered

 Final Report

Office of Aviation Research

Washington, DC 20591

14. Sponsoring Agency Code

 ANM-110 15. Supplementary Notes 

The FAA William J. Hughes Technical Center Technical Monitor was David Blake. 16. Abstract 

Federal regulations require that aircraft cargo compartment smoke detection systems be certified by testing their operation in

flight. For safety reasons, simulated smoke sources are permitted in these certification tests. To provide insight into smoke

detector certification in cargo compartments, this research investigates the morphology, transport, and optical properties of actual 

and simulated smoke sources. 

Experimental data show the morphology of the particulate in smoke from flaming fires is considerably different than simulated 

smoke. The particulate for all three different flaming fires was solid with similar morphological properties. Simulated smoke

was composed of relatively large liquid droplets, and considerably different size droplets can be produced from a single simulated

smoke machine. Transport behavior modeling showed that both actual and simulated smoke particulate are sufficiently small to

follow the overall gas flow. However, actual smoke transport will be buoyancy-driven due to the increased temperature, while

the simulated smoke temperature is typically low and the release may be momentum-driven. The morphology of the actual and 

simulated smoke were then used to calculate their optical properties. In contrast to the actual smoke, which is dominate by

absorption, all the extinction for the simulated smoke is due to scattering. This difference could have an impact on detection

criteria and, hence, time for photoelectric smoke detectors, since they alarm based on the scattering properties of the smoke. 

17. Key Words 

Smoke detection, Optical properties, Extinction, Scattering,

Soot morphology, Simulated smoke, Smoke transport

18. Distribution Statement 

This document is available to the public through the National

Technical Information Service (NTIS) Springfield, Virginia 

22161. 19. Security Classif. (of this report)

 Unclassified

20. Security Classif. (of this page)

 Unclassified

21. No. of Pages 

 40 

22. Price

Form DOT F1700.7 (8-72) Reproduction of completed page authorized 
ACKNOWLEDGEMENTS 

Sandia is a multiprogram laboratory operated by Sandia Corporation, a Lockheed Martin 

Company, for the United States Department of Energy under contract DE-AC04-94AL85000.

This work was performed in collaboration with the Federal Aviation Administration William J. 

Hughes Technical Center, Atlantic City International Airport, NJ, and NASA Glenn Research 

Center. The authors would like to acknowledge Dave Blake, Bob Filipczak, Louise Speitel, and

other FAA Technical Center personnel for their assistance during the experiments when soot 

samples were obtained. The assistance of Mun Choi in the random analysis technique of 

measuring morphological properties is acknowledged. Reviews by David Glaze and Tom Lalk

were also greatly appreciated. 

iii/iv
TABLE OF CONTENTS 

Page 

EXECUTIVE SUMMARY ix 

1. INTRODUCTION 1 

2. EXPERIMENTAL APPROACH 1 

2.1 Test Series 2 

2.2 Fuel Sources 2 

2.3 Experimental Facilities 4 

2.4 Experimental Observations 5 

2.5 Thermophoretic Sampling 6 

2.5.1 Diagnostic Design 7 

2.5.2 Transmission Electron Micrographs 8 

2.6 Analysis of Morphology 8 

2.6.1 Technique for Measuring Morphological Properties 8 

2.6.2 Calculation of Fractal Properties 9 

3. MORPHOLOGICAL PROPERTIES 10 

3.1 Actual Smoke Morphology 10 

3.2 Uncertainty Analysis of Measurement Technique 14 

3.3 Simulated Smoke Morphology 15 

4. TRANSPORT PROPERTIES 18 

5. OPTICAL PROPERTIES 20 

5.1 Actual Smoke 21 

5.2 Simulated Smoke 24 

5.3 Application to Detection 26 

6. SUMMARY OF RESULTS AND CONCLUSION 27 

6.1 Morphology 27 

6.2 Transport 28 

6.3 Optical Properties 29 

6.4 Conclusion 30 

7. REFERENCES 30 

v
LIST OF FIGURES

Figure Page 

1 Fuel Sources—Resin Cake, Jet A, and a Suitcase 2 

2 Cone Calorimeter Facility 4 

3 Intermediate-Scale Calorimeter Facility 5 

4 Full-Scale B-707 Cargo Compartment Facility 5 

5 Soot Collected on Filters—Smoldering and Flaming Resin 6 

6 Transmission Electron Microscopy Image of Soot Aggregates 6 

7 Grid Holder 7 

8 Schematic Displaying Measured Soot Properties 9 

9 Soot Aggregates (Resin, Jet A, and Suitcase) 10 

10 Soot Morphology—Flaming Resin Cake 11 

11 Soot Morphology—Suitcase 12 

12 Soot Morphology—Jet A 13 

13 Transmission Electron Microscopy Negative and Measurements of 

Polystyrene Spheres 15 

14 Schematic of a Smoke Generator 16 

15 Simulated Smoke Particle Size Distributions 17 

16 Transport of Theatrical Smoke Droplets 19 

17 Mass-Specific Extinction 23 

18 Mass-Specific Scattering 23 

19 Mass-Specific Absorption 23 

20 Mass-Specific Coefficient for Simulated Smoke (0.3 micron) 25 

21 Mass-Specific Coefficient for Simulated Smoke (0.66 micron) 25 

22 Schematics of Smoke Detectors 26 

23 Comparison of Scattering Properties 27 

vi
LIST OF TABLES 

Table Page 

1 Smoke Characterization Experiments 3 

2 Soot Morphology Results 13 

3 Properties of Simulated Smoke Generators 16 

vii
LIST OF ACRONYMS AND SYMBOLS 

N Number of primaries 

Aa Agglomerate area (m2) 

Ap Primary particle area (m2

) 

dp Diameter of primary (m)

L Aggregate length (m) 

W Aggregate width (m) 

kf Fractal prefactor 

Df Fractal dimension 

Rg Radius of gyration (m) 

σext Mass specific extinction (m2/g) 

σabs Mass specific absorption (m2/g) 

σsca Mass specific scattering (m2/g) 

kext Light extinction coefficient (1/m) 

ρ Density (kg/m3) 

λ Wavelength (m) 

Ms Mass concentration (kg /m3

) 

Ke Dimensionless extinction coeffient 

fv Volume fraction (m3

/m3) 

xp Size parameter 

m Complex index of refraction (m=n-ik) 

F(m) Function of the complex index of refraction 

E(m) Function of the complex index of refraction 

CCD Charge-coupled device 

FAA Federal Aviation Administration 

RDG-PFA Rayleigh-Debye-Gans theory for polydisperse fractal aggregates 

TEM Transmission Electron Microscopy 

viii
EXECUTIVE SUMMARY

Federal regulations require that smoke detection systems be certified by testing their operation in 

flight. For safety reasons, simulated smoke is often used for the required flight tests. It is, 

therefore, important to understand the similarities and differences of actual and simulated smoke. 

The purpose of this research was to characterize actual and simulated smoke sources to provide

insight into the morphology, transport, and optical properties and to determine how the smokes 

would behave in smoke detector certification tests. In this study, a series of experiments were

performed for the purpose of characterizing the morphology of actual smoke for fuel sources 

such as resin cakes, suitcases, and Jet A, which have been considered for use in certification 

tests. The transport properties of actual and simulated smoke were also compared using the 

results of the experiments and published simulated smoke data. Finally, with knowledge of the 

morphology and composition of actual and simulated smoke, the optical properties were 

calculated and compared. 

In the experiments, a thermophoretic-sampling technique allowed for characterization of the 

flaming smoke since it contained the solid particulate required for imaging. The experiments 

allowed a quantitative characterization of actual smoke from flaming fires, while only a

qualitative assessment of actual smoke from smoldering fires was feasible due to to the liquid 

nature of the collected sample. The smoke from flaming fires consisted of primary particles 

aggregated into wispy chains. The morphological properties of the solid particulate were

consistent with those reported in the literature. Overall, the morphology of the smoke from the 

flaming fires of all three fuels was very similar, but when compared to simulated smoke, extreme 

differences were identified. Simulated smoke does not consist of solid particulate like actual

smoke, and the individual droplets are considerably larger than the primary particles in actual

smoke. In contrast to the relatively narrow distribution of actual smoke morphology, simulated 

smoke morphology can vary a great deal even for a single machine. 

Based on the results of modeling transport behavior, it was determined that both actual and 

simulated smoke particulate are sufficiently small to follow the overall gas flow. It was observed 

that the transport may be different due to a difference in release temperatures and driving 

potential. Actual smoke transport will be buoyancy-driven due to the increased temperature, 

while the simulated smoke release temperature may be only very slightly elevated. In many 

cases, the simulated smoke could be forcefully expelled, which would make the transport 

momentum-driven instead of buoyancy-driven. 

To calculate the optical properties, an appropriate theory was used based on the size parameter 

for the particulate. Rayleigh-Debye-Gans-polydisperse fractal aggregate theory was used for the 

three actual smokes, and it was found that scattering comprised up to 30% of the total extinction.

Mie theory was used to calculate the optical properties of simulated smoke. In contrast to the 

actual smoke, all of the extinction for the simulated smoke was due to scattering. The extinction 

for the smaller droplets (0.3 micron) was approximately half of the total extinction for the actual

smokes, while the extinction for the larger droplets was approximately the same as the actual

smokes. The scattering for the smaller droplets was about the same as the actual smoke, but the 

scattering for the larger droplets was almost double the actual smoke scattering. This could have 

a great impact on detection time for photoelectric smoke detectors since they alarm based on the

ix
scattering properties of the smoke. Calculation of the optical properties allows the smokes to be

compared, and in addition, they can be used to calculate soot volume fraction from extinction 

measurements already being performed in the full-scale model validation experiments. 

x
1. INTRODUCTION.

Federal regulations require that smoke detection systems be certified by testing their operation in 

flight. Flight tests typically use theatrical smoke generators to produce the necessary simulated

smoke [1]. These simulated smoke generators are intended to be used in a manner representative 

of an actual fire scenario that could occur in a cargo compartment. Presently, a video of a 

burning suitcase is provided by the Federal Aviation Administration (FAA) William J. Hughes 

Technical Center, Atlantic City International Airport, NJ, to certifying officials so that a 

reasonable scenario can be selected and used in the certification tests. To supplement and 

improve the scenario selection, a computational fluid dynamics-based smoke transport model is

being developed. 

The purpose of this study was to provide a detailed comparison of the properties of actual and 

simulated smoke to determine if both smoke sources would interact with cargo compartment 

smoke detection systems in a similar manner. Smoke from combustion processes consists of

both types of particulate matter, solid (commonly referred to as soot) and liquid, as well as 

gaseous products of combustion reactions. The smoke properties of importance can be 

categorized into two groups: properties used to characterize the source term in the transport 

model (mass flux, heat release, gaseous species concentrations, and soot volume fraction) and 

properties which affect smoke detection (composition, transport, and morphology). Experiments

performed at the FAA Technical Center, using a cone calorimeter, an intermediate-scale 

calorimeter, and a full-scale cargo compartment test facility, allowed for the characterization of

most of these properties for actual smoke. Since simulated smoke is commonly used in the 

detector certification process, characterization of its morphology, transport, and optical

properties was also performed. 

To meet the need of smoke characterization, detailed visual examination of the smoke particulate 

representative of a cargo compartment fire was performed as part of the ongoing experiments. 

Smoke samples were extracted both from fires in a full-scale cargo compartment and from 

calorimeter fire experiments. The collected samples were analyzed to develop a set of 

particulate morphology characteristics as a function of the fire type. Knowledge of soot 

morphology is useful in calculating soot volume fraction from extinction measurements in the 

full-scale model validation experiments. The morphology was also used to characterize transport 

and optical properties. Similarly, based upon knowledge of simulated smoke morphology, a 

characterization of the transport and optical properties was performed. 

2. EXPERIMENTAL APPROACH.

Experiments were performed to characterize actual smoke at the FAA in the cone calorimeter,

the intermediate-scale calorimeter, and the full-scale cargo compartment test facility. The cone 

calorimeter and intermediate-scale calorimeter experiments were performed to define a baseline

fire and to characterize the fuel material in terms of the specific heat release rate, mass loss rate,

product composition, and smoke obscuration. Fire experiments were conducted in a full-scale 

cargo test facility to gather data for formulating and validating the computational smoke

transport model. Smoke particulate samples were collected during the execution of these tests. 

The sampling consisted of inserting a wand that supports a particle collection grid into the smoke 

flow for a predetermined period (on the order of seconds). The flame zone, or smoke region, 

1
was easily accessible for the full-scale tests, and the grid holder was positioned by hand. For the 

calorimeter, the grid holder was inserted into the smoke exhaust pipe via a small hinged door 

provided by the FAA. At least three samples were taken at each condition to ensure that a

sample suitable for image analysis was obtained. 

2.1 TEST SERIES.

Experiments were conducted to determine the variation of smoke particulate features with the

fire time/types (representing smoldering or flaming fires) and heat release rates (materials 

producing low or high maximum heat release rates). The test series, shown in table 1, includes 

detailed information about the test setup and progress. The designation, in the column labeled 

FAA, indicates where the experiment was performed. The type of fire, flaming or smoldering, is 

listed in the fire source column. The subsequent columns describe the fuel, the ignition source, 

and the experimental observations. 

2.2 FUEL SOURCES.

Three fuel sources, shown in figure 1, were studied in the test series: resin cakes, Jet A, and 

suitcases. The suitcases represent the most realistic fuel source, but smoke transport analysis is

not as feasible since they do not burn repeatably. All suitcases were packed identically with 

cotton rags and were ignited by passing an electric current throught a nichrome wire within the 

suitcase. The suitcases initially smoldered and then transitioned to flaming as the experiment 

progressed. 

FIGURE 1. FUEL SOURCES—RESIN CAKE, JET A, AND A SUITCASE 

The resin cakes were designed and manufactured by the FAA Technical Center and were 

formulated to provide a repeatable fire source to be used in smoke transport experiments. 

Pressed pellets (PVC, PE, PS, Nylon, PBT, and PU) of known quantity comprise the resin cakes.

A nichrome wire with a controlled length and spatial distribution is embedded within the resin 

cakes, which is capable of providing smoldering fires. Flaming fires are produced by running an 

electric current through the nichrome and by igniting a small amount of heptane placed on the 

resin cake. 

2
TABLE 1. SMOKE CHARACTERIZATION EXPERIMENTS 

Test FAA Fire Source Fuel Ignition Source Notes 

1 B707 Smoldering 3/8′′ Resin Cake 360 W embedded 1/8′′ Short soot sample at 45 sec 

2 B707 Smoldering 3/8′′ Resin Cake 360 W embedded 1/8′′ Medium soot sample at 60 sec 

3 B707 Smoldering 3/8′′ Resin Cake 360 W embedded 1/8′′ Long soot sample at 45 sec, extra long 

sample at 60 sec 

4 B707 Flaming 3/8′′ Resin

Cake/Heptane 

(2 ml) 

360 W embedded 1/8′′ 10000V 

Continuous Spark 3/32′′ Gap 

within 1/8′′ of surface 

Short soot sample at 45 sec 

5 B707 Flaming 3/8′′ Resin

Cake/Heptane 

(2 ml) 

360 W embedded 1/8′′ 10000V 

Continuous Spark 3/32′′ Gap 

within 1/8′′ of surface 

Medium soot sample at 60 sec 

6 B707 Flaming 3/8′′ Resin

Cake/Heptane 

(2 ml) 

360 W embedded 1/8′′ 10000V 

Continuous Spark 3/32′′ Gap 

within 1/8′′ of surface 

Long soot sample at 45 sec, extra short 

sample at 60 sec 

7 Cone

Calorimeter 

Smoldering 3/8′′ Resin Cake 360 W embedded 1/8′′ 60-sec baseline power applied at 60 sec, 

smoldered until 240 sec, short soot 

sample 45 sec after power applied

8 Cone

Calorimeter 

Smoldering 3/8′′ Resin Cake 360 W embedded 1/8′′ 60-sec baseline power applied at 60 sec, 

smoldered until 240 sec, medium soot 

sample 60 sec after power applied

9 Cone

Calorimeter 

Smoldering 3/8′′ Resin Cake 360 W embedded 1/8′′ 60-sec baseline power applied at 60 sec, 

smoldered until 173 sec transitioned to 

flaming. Power to wire shutoff for 5 sec 

and then restored until 240 sec, long soot 

sample 45 sec, extra long sample at 60 

sec after power applied 

10 Cone

Calorimeter 

Flaming 3/8′′ Resin

Cake/Heptane 

(2 ml) 

360 W embedded 1/8′′ 10000V 

Continuous Spark 3/32′′ Gap 

within 1/8′′ of surface 

60-sec baseline power applied at 60 sec, 

started flaming until 240 sec, short soot 

sample 45 sec after power applied

11 Cone

Calorimeter 

Flaming 3/8′′ Resin

Cake/Heptane 

(2 ml) 

360 W embedded 1/8′′ 10000V 

Continuous Spark 3/32′′ Gap 

within 1/8′′ of surface 

60-sec baseline power applied at 60 sec, 

started flaming until 240 sec, medium soot 

sample 60 sec after power applied

12 Cone

Calorimeter 

Flaming 3/8′′ Resin

Cake/Heptane 

(2 ml) 

360 W embedded 1/8′′ 10000V 

Continuous Spark 3/32′′ Gap 

within 1/8′′ of surface 

60-sec baseline power applied at 60 sec, 

started flaming until 240 sec, short soot 

sample 45 sec, extra short 60 sec after

power applied 

13 B707 Smoldering Suitcase 5 paper towels wrapped with 

8 ft nichrome - 1 ohm/ft 65V 

Short sample during smoldering at 30 

seconds after power applied. Torch 

applied at 110 seconds 

14 Intermediate

- scale 

Calorimeter 

Smoldering Suitcase 5 paper towels wrapped with 

8 ft nichrome - 1 ohm/ft 65V 

60-sec baseline power applied at 60 sec, 

started smolder until 210 sec, short soot 

sample 105 sec after power applied 

15 B707 Flaming Suitcase Continuation of test 13 with 

Butane ignitor 

Short sample during flaming at 220 

seconds after power applied. Torch 

applied at 110 seconds 

16 Intermediate

- scale 

Calorimeter 

Flaming Suitcase Continuation of test 14 selfignited 60-sec baseline power applied at 60 sec, 

started smolder until 210 sec, self- ignited 

and burned until end of test. Short 

sample at 30 sec after ignition. 

17 Cone

Calorimeter 

Flaming Jet A (15 ml)/ 

Heptane (4 ml)

3.5′′ Dia 

Butane Ignitor 60-sec baseline torch applied at 60 sec, 

started flaming until 240 sec, short soot 

sample 20 sec after ignition, short sample 

110 sec after ignition 

18 B707 Flaming Jet A (15 ml)/ 

Heptane (4 ml)

5.0′′ Dia 

10000V Continuous Spark 

3/32′′ Gap within 1/4′′ of surface

3 minutes total burn time, short sample at 

45 sec after ignition, medium sample at 

60 secs after ignition 

Liquid Jet A fuel was also used in the experiments. These small flaming pan fires were initially 

used as the repeatable fire source before the resin cakes were developed. The resin cakes were 

deemed more suitable since they were comprised of fuels commonly found in luggage and could 

3
sustain either flaming or smoldering fires. Soot characterization was performed on the jet fuel 

for comparison with flaming resin cakes and previous large-scale JP-8 jet fuel experiments [2]. 

Using these three sources allowed comparison of the actual fuel source (i.e., suitcase) to 

repeatable fuel sources (resin cakes and Jet A) designed to simulate the actual source

characteristics. 

2.3 EXPERIMENTAL FACILITIES.

Two calorimeters were used to provide detailed information during the fires (i.e., heat release, 

species, etc.). The cone calorimeter was used to perform smoldering and flaming tests using 

resin cakes and Jet A as fuels. The cone calorimeter facility, shown in figure 2, is a standard 

American Society for Testing and Materials device. Typically, a sample is placed on a fixture 

and heated from above with a radiant heat lamp. For the resin cake, the radiant heat lamp was

replaced with power input by the nichrome wire imbedded in the sample. During the test, the 

decomposition products are captured and analyzed, while the sample is continuously weighed to 

determine a mass loss. The intermediate-scale calorimeter, shown in figure 3, was used for the

smoldering/flaming suitcase experiment. In this setup, an enclosed cabinet is used to contain and 

capture the products of decomposition. The products are then routed to the cone calorimeter 

sampling section for analysis. Soot samples were obtained from the calorimeter fires via a small 

hinged door in the sample section. The full-scale experiments were performed in an actual B707 cargo compartment using all three fuel sources (see figure 4). 

FIGURE 2. CONE CALORIMETER FACILITY 

4
FIGURE 3. INTERMEDIATE-SCALE CALORIMETER FACILITY 

FIGURE 4. FULL-SCALE B-707 CARGO COMPARTMENT FACILITY 

2.4 EXPERIMENTAL OBSERVATIONS.

The data collected in these experiments include fuel mass loss rate, species production rate, heat

release rate, and smoke obscuration [3]. The focus of this study is on the smoke properties, in 

particular, the morphology that affect detection. 

5
A notable difference in the smoldering and flaming fires was the appearance of the smoke. 

Smoldering fires produced white smoke, while flaming fire smoke appeared darker. The 

difference in color of the smoke was also evident upon visual inspection of the filter installed in 

the cone sampling section. The smoldering fire soot was yellow in color, while the flaming fire 

soot was black, as shown in figure 5. 

FIGURE 5. SOOT COLLECTED ON FILTERS—SMOLDERING AND FLAMING RESIN 

2.5 THERMOPHORETIC SAMPLING.

The particulate matter (i.e., soot) present in smoke from burning materials or fuels can be

characterized by transmission electron microscopy (TEM) imaging of samples obtained from the 

fires. To obtain a sample, a TEM grid is briefly inserted into the fire to collect soot particles. 

The particles in the flow are drawn to the grid due to thermophoresis (the attraction produced by 

the temperature gradient between the flow gas and the grid) and impingement of the flow on the

grid. The grid is then taken to the transmission electron microscope where the soot particles are 

imaged. Figure 6 shows a JP-8 fuel fire TEM image, which displays aggregated soot primary 

particles. The diagnostic design and sample collection are described in the sections that follow. 

FIGURE 6. TRANSMISSION ELECTRON MICROSCOPY IMAGE OF

SOOT AGGREGATES 

6
2.5.1 Diagnostic Design.

A grid holder was designed specifically for the experiments in the FAA calorimeters and the fullscale B-707 cargo compartment. The design is based on previous experience in large jet fuel 

pool fires [2]. This new grid holder is much smaller than the one used in large fire experiments 

to minimize the impact on the flow field. A schematic and photograph of the grid holder are 

shown in figure 7. 

Grid 

Grid

Screw (optional) 

Screw 

(optional) 

Not to Scale 

3/16′′ 8′′

5/16′′

1⁄2′′ 1′′

FIGURE 7. GRID HOLDER 

The grids are held in a small slot in an aluminum bar. An optional set-screw is shown holding 

the grids in place. The grid holder was inserted into the flow and oriented such that the soot 

impinges directly on the grids. The flame zone, or smoke region, was easily accessible in the 

full-scale tests and the grid holder was positioned into the soot region. For the calorimeter

experiments, the grid holder was inserted into the smoke exhaust pipe via a small hinged door. 

7
Several different exposure times were used for each test case to ensure that a suitable sample was

obtained. 

2.5.2 Transmission Electron Micrographs.

Samples obtained from the test series, shown in table 1, were imaged with a TEM. Several 

samples were obtained for each test type, and the sample with the best soot coverage was chosen

for analysis. Overall, the soot samples obtained from the flaming fuel fires produced good soot 

coverage for exposure times of approximately 1 second. 

It was not possible to image the soot from any of the smoldering fires. The grids appeared 

almost clean except for a possible coating on the grid. A residue was slightly visible on the grid, 

but it was not possible to analyze its composition. Although the smoldering samples were not 

suitable for analysis, five samples from flaming fires were imaged. The imaged samples 

included: 

• Flaming resin in the B-707 cargo compartment (test 4)

• Flaming resin in the cone calorimeter (test 10) 

• Flaming suitcase in the B-707 cargo compartment (test 15) 

• Flaming suitcase in the intermediate-scale calorimeter (test 16) 

• Flaming pan of Jet A in the B-707 (test 18) 

2.6 ANALYSIS OF MORPHOLOGY.

All soot samples obtained were imaged using a TEM. Approximately 20 micrographs, similar to 

figure 6, were obtained for each sample. The imaged areas for the micrographs were randomly 

selected from the entire grid area. A complete analysis, as described in the sections that follow, 

was performed using the images to gain a statistically significant characterization of the soot 

morphology of the sample. 

2.6.1 Technique for Measuring Morphological Properties.

To convert the micrograph into an image suitable for analysis, it was placed on a light table and 

imaged via a high-resolution, charge-coupled device (CCD) camera. The image captured by the

CCD camera was digitized prior to analysis. The CCD camera is also capable of magnifying the 

image for detailed measurements. The contrast between the soot particles and the background 

was digitally enhanced to allow some measurements to be automated. Soot properties of interest 

included the dimension and area of primary particles and aggregates, since they influence the 

optical properties needed for sensing the smoke. The soot primary particle size (Dp) was

obtained by manually measuring the diameter of soot particles within the aggregates. Other

measurements included the projected area of the primary particles (Ap) and the projected area of

the aggregate (Aa), as shown in figure 8. 

8
Dp

N = 18 

Area sum = Aa

Ap

FIGURE 8. SCHEMATIC DISPLAYING MEASURED SOOT PROPERTIES 

2.6.2 Calculation of Fractal Properties. 

Since soot can be considered a fractal aggregate, the extinction coefficient (σext) is based on the 

number of primaries in an aggregate (N), the fractal dimension (Df), and the fractal prefactor (kf). 

These quantities, typically used to characterize soot morphology, can be extracted from the 

measured quantities in the following manner. 

The number of primary particles comprising an aggregate is calculated using an empirical

correlation [4] 

1.09

















=

p

a

A

A

N (1) 

where Aa and Ap are the projected areas of the agglomerate and primary particle, respectively,

and N is the total number of particles comprising the aggregate. Soot aggregate structure is too

sparse for it to be described as a compact sphere, and thus, the mass fractal analysis provides a 

useful relationship to determine the radius of gyration (Rg) based on primary particle size and the 

number of primary particles comprising the aggregate: 

∑=

= −

N

i

g i c r r

N

R

1

2 ( ) 1

 (2) 

where ri is the centroid of the primary particle, and rc is the centroid of the agglomerate. Since it 

is difficult to identify each individual particle that constitutes an aggregate, the Rg calculation 

formulation was revised by considering each pixel to be the individual element of interest. This 

approximation is valid since the average contribution to the total Rg from the subelements 

(pixels) that constitute the primary particle is equal to the contribution from a primary particle to

9
the total Rg. The equation for the radius of gyration remains the same, but N (determined by 

performing a histogram distribution of all pixels with graylevel greater than the threshold) now 

corresponds to the total number of pixel elements comprising the agglomerate (typically on the 

order of 20-30 thousand pixels). 

Finally, the fractal prefactor (kf) and the fractal dimension (Df) can be determined based on either 

of the following equations [3 and 4]. A ln-ln plot reveals Df and kf. 

Df

p

g

f d

R

N k















 = (3) 

( )

D f

p

f d

LW N k 



















= 2

1

(4)

3. MORPHOLOGICAL PROPERTIES.

3.1 ACTUAL SMOKE MORPHOLOGY. 

Thermophoretic sampling successfully allowed the characterization of soot morphology for all 

three fuels—resin cake, Jet A, and suitcase (see figure 9). Samples for the resin and suitcase 

fuels were obtained in both calorimeters and the full-scale B-707 cargo compartment. The Jet A 

sample was captured in the B-707 cargo compartment. 

FIGURE 9. SOOT AGGREGATES (RESIN, JET A, AND SUITCASE) 

The samples were characterized using the technique described in section 2. The results are 

displayed in figures 10 through 12 and are summarized in table 2. Samples were also obtained 

from fires within the cone calorimeter, but only the results from the full-scale B-707 test facility 

are displayed in the table. The results from the calorimeter did not differ from the B-707 results

by more than 7%, and in most cases, the difference was only 3%. 

10
10

20

30

40

50

60

70

40 60 80 100 120 140

Count

Dp (nm)

Average DP=86.39nm

Rg=297 nm

0

2

2.5

3

3.5

4

4.5

5

5.5

0.5 1 1.5 2 2.5 3 3.5

LN(N)

LN((LW)

0.5

/dP)

Df=1.71

N=(Aa/AP)

1.08

 

2

2.5

3

3.5

4

4.5

5

5.5

0 0.5 1 1.5 2 2.5

LN(N)

Kf=7.340

N=(Aa/AP)

1.08

LN(Rg/dP)

FIGURE 10. SOOT MORPHOLOGY—FLAMING RESIN CAKE 

11
10

20

30

40

50

60

40 60 80 100 120 140 160

Count

Dp (nm)

Average D P=81.04nm

Rg=253 nm

0

 

1.5

2

2.5

3

3.5

4

4.5

5

5.5

0.5 1 1.5 2 2.5 3 3.5

Df=1.58

LN(N)

N=(Aa/AP)

1.08

LN((LW)

0.5

/dP) 

1.5

2

2.5

3

3.5

4

4.5

5

5.5

-0.5 0 0.5 1 1.5 2 2.5

Kf

=7.146

N=(Aa/AP)

1.08

LN(N)

LN(Rg/dP)

FIGURE 11. SOOT MORPHOLOGY—SUITCASE 

12
0

10

20

30

40

50

60

70

20 40 60 80 100 120

Count

Dp (nm)

Average DP

=75.9 nm

Rg=349 nm

 

2.5

3

3.5

4

4.5

5

5.5

6

1 1.5 2 2.5 3 3.5

Df=1.56

LN(N)

N=(Aa/AP)

1.08

LN((LW)

0.5

/dP) 

2.5

3

3.5

4

4.5

5

5.5

6

0 0.5 1 1.5 2 2.5 3

LN(N)

N=(A a/AP)

1.08

LN(R g/dP)

Kf=7.588

FIGURE 12. SOOT MORPHOLOGY—JET A 

TABLE 2. SOOT MORPHOLOGY RESULTS 

Dp kf Df Rg

Resin B-707 86.4 nm 7.34 1.71 297 nm

Suitcase B-707 81.0 nm 7.15 1.58 253 nm

Jet A B-707 75.9 nm 7.59 1.56 349 nm

13
The first parameter used to describe the morphology is the diameter of the primary particles (Dp). 

In all fuel samples there was a range of primary particles collected, typically between 40 and 

140 nm. The average primary particle size from all fuels was approximately 80 nm. These 

primary particles aggregated into wispy chains up to several microns in length, as shown in

figure 9. 

The radius of gyration was obtained directly from the image (as in section 2) and gives an 

indication of the size of the agglomerate (average distance from the centoid to the edge of the 

agglomerate). The radius of gyrations calculated ranged from 253-349 nm. Also calculated

directly from the images was the number of primary particles (N) per agglomerate. 

Since soot is a fractal aggregate, the measured quantities (Dp, Rg, and N) can be used to compute 

the fractal dimension (Df) and the fractal prefactor (kf) based on the fractal power law for 

aggregates (shown in equation 3). The fractal prefactors calculated for the different fuels were 

very similar, ranging from 7.15 to 7.59. The fractal dimensions were also very similar (1.56-

1.71). The fractal dimension gives an indication of the compactness of the aggregate. For 

reference, a straight line has a fractal dimension of 1, a two-dimensional plane has a fractal 

dimension of 2, and a sphere has a fractal dimension of 3. The average fractal dimension of 

approximately 1.6 is consistent with the TEM images and is commonly described as a wispy 

chain. 

Overall, the morphology of the soots studied is consistent with a variety of soots documented in 

the literature [4, 5, and 6]. The soot consists of spherical primary particles aggregated into a 

wispy chain of fractal dimension less than 2. The average primary particle size is approximately 

80 nm for all samples. Although the fractal dimension and fractal prefactor measured are similar 

to literature values, the measured average size of the primaries is larger than is typically stated in

the literature [4, 5, and 6]. A thorough investigation of the measurement technique was

performed, including quantitative characterization of the accuracy and uncertainty of the process.

In general, the soots studied here are very similar in their morphological characteristics, and 

substitution of one source for another (i.e., resin cake instead of a suitcase) should not cause a 

significant difference in the morphology of the soot used in a particular experiment. 

3.2 UNCERTAINTY ANALYSIS OF MEASUREMENT TECHNIQUE.

An estimate of the uncertainty in the measurement technique was performed by creating TEM 

micrographs of polystyrene spheres. Three different sized polystyrene spheres were mixed and 

deposited on a grid. The grid was then imaged to produce a negative in exactly the same way the 

soot grids were imaged and analyzed. The individuals performing the analysis of the grid were 

not informed of the size of the spheres deposited on the grid. 

When analyzing soot images, the random analysis technique takes only a sampling of the total 

number of primary particles to represent the overall average. For the polystyrene sphere 

analysis, an estimate of the error in this sampling was sought by increasing the sample number

until all spheres were imaged. In addition, the measurement of all spheres in the captured image 

provided an estimate of the accuracy of the automatic measurement technique. If the 

measurements were accurately performed, a multimodal distribution would be seen. The peaks 

would correspond to the size of the spheres stated by the manufacturer. 

14
The diameter of the polystyrene spheres were 79, 93, and 173 nm. A sample image is shown in 

figure 13. The figure was scanned directly from the negative. In the analysis of the TEM

micrographs, 12 regions were identified and then the spheres were measured in the regions. To 

obtain a particle size distribution for the overall population, all the spheres (668 total) within the 

selected regions were measured. Then a representative sample was obtained by only measuring 

random spheres (121 total) within the regions. This allowed assessment of the random technique 

as well as the accuracy of the measurement technique. It was concluded that the random 

technique allowed for characterization of the sphere diameters within an average of 8%. The 

histograms obtained are also shown in figure 13. A very similar distribution is shown in both the 

total population and the random sampling, and the peaks are in line with the sphere sizes, 

showing that the calibration and measurements are being correctly performed. Overall, 

confidence in the technique was obtained. 

0

50

100

150

200

250

300

13.728.042.356.570.885.199.3

113.6127.9142.1156.4170.7184.9

Frequency

 

0

5

10

15

20

25

30

35

40

13.748.060.573.085.497.9

110.4122.9135.3147.8160.3172.7

More

Frequency

Total Population Random Sampling 

FIGURE 13. TRANSMISSION ELECTRON MICROSCOPY NEGATIVE AND 

MEASUREMENTS OF POLYSTYRENE SPHERES 

3.3 SIMULATED SMOKE MORPHOLOGY.

Simulated smoke is produced by heating a liquid above its vaporization temperature. The 

vaporized liquid is then expelled from the heating chamber into the environment where it 

condenses, forming a fog-like smoke. Simulated smoke could not be characterized via 

thermophoretic sampling, like the three fuels described in section 2.2, due to the liquid nature of 

15
the simulated smoke. As mentioned previously, imaging via TEM requires solid, opaque

particles or objects. 

Since simulated smoke could not be characterized using thermophoretic sampling, the properties 

of the simulated smoke were obtained from the manufacturer. Some of the data obtained from 

various manufacturers of simulated smoke machines are shown in table 3. 

TABLE 3. PROPERTIES OF SIMULATED SMOKE GENERATORS

Supplier Composition Driving Potential Temperature 

Mass Flux 

(cfm) 

Diameter 

(microns) 

1 glycol/oil Vapor press (CO2) 3400 max 0.2-0.3

2 glycol Vapor press (pump) 380°-480°F 20,000 max ?

3 glycol Vapor press (pump) 80°-100°F 2,500-35,000 fixed ?

4 secret Vapor press (pump) 212°-470°F variable 0.25-60 (4avg)

5 glycol & glycerols 3-4 m plume 60°C nozzle ? 0.5

6 Proprietary fluid 5000 max 0.5-0.7 

Upon request, more detailed data was obtained from a manufacturer (#1) who stated that their 

smoke generators are used in certification of aircraft smoke detectors, although the validity of 

this claim has not been investigated. A schematic of a smoke generator is shown in figure 14. 

Oil Fill Cap

Oil forced up through 

filter and metering disk 

Filter

Heat Exchanger

To Gas Cylinder

Solenoid 

Valve 

FIGURE 14. SCHEMATIC OF A SMOKE GENERATOR

16
The manufacturer states that running for 10 minutes at the maximum output, the smoke generator 

will consume 0.62 kg of oil fluid and 0.5 kg of CO2 for driving potential. The fog produced by 

the simulated smoke generator consists of oil droplets that have recondensed upon exiting the

heat exchanger. Measurement of the droplets was performed based on the scattered intensity of

laser light to allow for a quantitative comparison between different machine settings and actual 

smoke from a combustion process. The particle size distribution was obtained for various 

machine settings (see figure 15). The different settings were referred to as

• 100 psi, standard setting (with nozzle at 314°C) 

• 100 psi thin, dry setting 

• 100 psi ultrathin setting 

• Very wet setting 

0

5

10

15

20

25

30

35

40

45

0 0.2 0.4 0.6 0.8 1

Size (microns)

% counts in channel

Standard

thin dry

ultra thin

very wet

FIGURE 15. SIMULATED SMOKE PARTICLE SIZE DISTRIBUTIONS 

The count and mass mean diameter for both the thin dry and the ultrathin settings was 0.15 and 

0.17 micron, respectively. The standard and very wet count mean was 0.29 micron, while the 

mass mean was approximately 0.36 micron. The factor of 2 difference in the average size could 

greatly impact detection times, therefore, the setting should be consistent when certifying aircraft 

smoke detectors. It should also be noted that the size of the simulated smoke droplets is 

considerably larger than the actual smoke primary particles. In the case of the generator tested, 

the droplets are 2-3.5 times larger than actual smoke, but another smoke generation machine 

(listed as being acceptable for smoke detection tests [1]) reports considerably larger droplets (up 

to 60 microns which is 750 times larger than the primary particle size of actual smoke). The 

spectrum of different simulated smoke will result in different transport properties and detection

times. 

17
4. TRANSPORT PROPERTIES.

Knowledge of the morphology of real and simulated smoke allows an assessment of the transport 

properties of the smoke to be made. It is typically assumed that soot particles are small enough

to follow the overall gaseous flow, allowing the soot particulates to be transported with the 

buoyant plume to upper regions of the cargo bay. These regions can potentially contain smoke

detectors; therefore, detection times are dependent on transport of smoke containing particles or 

droplets to the area. If the particulates are large enough that they do not follow the flow, a fallout of particles from the plume could impact detection times. Since theatrical smoke droplets

can be considerably larger than soot particles, a calculation was performed to determine when 

the droplets would no longer follow the flow. 

The analysis of the transport properties of simulated smoke was performed by writing a short 

computer code capable of calculating the forces on the droplet for varying droplet size, droplet

properties, and velocity. The two forces existing are the drag force and the weight defined as 































 =

3

3 2

4 drop

weight drop

D

F ρ g π (5) 

D

air drop

drag air C V D

F

2 2

2 2

0.5 





























 = ρ π (6)

FD

Fw

Ddrop, ρdrop

Vair, ρair

where CD is based upon correlations for a sphere that depends on the magnitude of the Reynolds 

number (Re). 

The net force was calculated for various droplet sizes and velocities. Two commonly used 

theatrical smoke droplet compositions (paraffin and a proprietary fluid) were analyzed. The two 

types of droplets differed in density. Paraffin density is 900 kg/m3

, while the proprietary fluid is 

1100 kg/m3

. The results from the analysis are presented in figure 16. The vertical axis shows 

the air velocity that must be present to counteract the weight of the droplet. This velocity could 

also be considered the settling velocity of the droplet. For air velocities lower than this value, 

the force due to the weight will be greater than the drag force, thus the particle will not follow

the flow. Since the proprietary fluid has a greater density, the force due to the weight is also 

greater and a larger air velocity is required for the particle to be transported with the flow. The 

average diameter for the proprietary droplet is approximately 4 microns, while the paraffin 

smoke generator, being considered for use by the FAA, is approximately 0.66 micron. In either

case, the droplet could be considered small enough to be transported with the flow since the 

force on the particle due to the weight is significantly smaller than the drag force on the particle 

18
due to the flow. Soot primary particles are typically less than 0.08 micron and, even when 

agglomerated into sparsely packed chains up to several microns in length, will follow the flow. 

Proprietary

Paraffin 

FIGURE 16. TRANSPORT OF THEATRICAL SMOKE DROPLETS 

Although it has been shown that simulated smoke droplets are small enough to follow the flow, 

the transport of simulated smoke may be quite different from actual smoke, due in part to the 

potentially different release temperatures. Initially, simulated smoke will want to rise because

the particles and gases exceed ambient temperature (i.e., buoyancy-driven flow). Shortly after 

release, the simulated smoke will cool to the ambient temperature and it will then be transported 

due to natural convection or settling. One supplier stated that the simulated smoke temperature 

is less than 60°C, just inches from the nozzle, as required for safety. The flow of real smoke is 

buoyancy-driven due to the elevated temperature of the smoke (much greater than 60°C) emitted

from the burning materials. 

For all smoke generators, the liquid used to produce simulated smoke is pumped into a heat 

exchanger where it is vaporized, but the release of the simulated smoke from the heat exchanger 

can vary, as reported by several manufacturers. Some suppliers have stated that the smoke is

released due to the vaporization pressure in the machine as well as pressure produced by the 

pump. Other machines use a propellant, such as CO2 or N2, to expel the smoke. The use of a 

pressurized gas will likely result in momentum-driven transport of the smoke instead of 

buoyancy-driven transport. In addition, the angle and method of release of the plume of 

19
simulated smoke is very important to its transport. If the simulated smoke is released vertically,

it will collect near the ceiling until the particles begin to settle. Smoke released at the floor could 

remain around the level it was released unless the smoke generator adds heat or a carrier gas, 

such as helium, to introduce buoyancy [1]. A patent exists on a smoke generator modified to 

include a helium carrier gas for the purpose of creating a buoyant plume [7]. 

The wide variety of available smoke generators will produce smoke with different morphological 

and transport properties; therefore, it will become necessary to consider which types of smoke 

generators produce a type and amount of simulated smoke that is comparable to actual smoke. 

5. OPTICAL PROPERTIES.

Based on the morphology and composition of the smoke, the optical properties can be calculated. 

The extinction properties of the smoke are responsible for reducing visibility, and they are 

ultimately responsible for triggering the smoke detector alarm. The total extinction consists of 

two components: the portion of the light being absorbed and the portion of the light being 

scattered 

σ ext = σ abs +σ scat (7)

In the following section, the mass-specific extinction (m2

/gm) will be calculated for actual and 

simulated smoke. Knowledge of the mass-specific extinction (σext) can be used to calculate soot

concentration based upon light extinction measurement, presently being performed at the FAA 

full-scale test facility. The light extinction measurements are based upon Bouguer’s Law, which 

relates the light extinction coefficient (K in 1/m) and path length (L in m) to the ratio of the

transmitted light (I/Io) [8 and 9] 

M L L f K KL

o

ext s

v e

e e e

I

I λ −σ − − = = = (8)

where fv is the volume fraction of soot, and λ is the wavelength of incident light. 

The relation of the mass-specific extinction coefficient (σext) to the light extinction coefficient 

(K in 1/m) and the dimensionless extinction coefficient (Ke) is 

λ ρ λ

σ

soot

e

s

e v

s

ext

K

M

K f

M

K = = = (9)

where Ms is the mass concentration of smoke (in kg/m3). 

The following section will characterize the extinction properties, (scattering and absorption)

based on the morphology of actual and simulated smoke. The theory used to calculate the 

extinction properties is dependent on the size parameter, x, which is based on the size of the 

particle, Dp, and the wavelength, λ. The size parameter is defined as [10] 

20
λ

πDp x = (10)

Considering a common visible laser wavelength (635 nm), the size parameter for actual soot is 

0.39 (using Dp = 80 nm) and for simulated smoke it is 1.48 (Dp = 300 nm). 

For x << 1, the particles are within the Rayleigh regime where scattering is assumed to be 

negligible. Typically, it is assumed that soot falls within the Rayleigh regime, although 

aggregation of the primaries typically causes this assumption to result in underestimation of the 

extinction by approximately 30% [4 and 11]. For x = O(1), the extinction properties of the 

particles can be described by the complex Mie theory [10]. Simulated smoke droplets are in this 

range; therefore, Mie theory will be used to characterize the optical properties. For x>>1, the 

extinction properties are calculated using geometric optics where the surface of the particle is

treated as a normal surface. 

Actual soot does not fit into any of these three catagories very well. As stated before, aggregated

soot particles are not likely within the Rayleigh regime. There have been attempts to find the

optical properties of soot using the Mie theory by concentrating the entire mass of the soot

agglomerate into an equivalent sphere, but this is not a good representation of a wispy chain [12]. 

Since soot is a fractal aggregate, the Rayleigh-Debye-Gans theory for polydisperse fractal 

aggregates (RDG-PFA) will be used to calculate the scattering and absorption properties for soot. 

Using the appropriate theory, the calculated optical properties for both actual and simulated 

smoke could provide insight into the effect of smoke type on detector certification. 

5.1 ACTUAL SMOKE.

RDG-PFA can be used to calculate the scattering and absorption properties for soot. In using 

this theory, several assumptions about the properties of the soot are invoked, i.e., the soot 

consists of fractal aggregates, which obey the power law relation between number of primaries 

and radius of gyration (see equation 3); soot consists of spherical primary particles that just touch 

each other; and the index of refraction is uniform [4]. All of these appear to be valid as shown in 

figure 9. 

Equations 11 through 13 for the mass-specific coefficients were derived from the total scattering 

and absorption cross sections [12]. The resulting equations were compared to the same

derivation performed in a later paper [13], where it was determined that a typographical error 

existed. The sign of the exponent in the scattering term in the following equations has been 

corrected (positive value). The following equations display the derived expressions for the

absorption and scattering properties of the soot as a function of their morphology. 

( )

p

abs

E m

λρ

π

σ

6 = (11)

( ) 2

2

3

16

4 3

Df

p

f

p

p f

scat x

x k F m D















 = λρ

π

σ (12)

21
σ ext = σ abs +σ scat (13)

where E(m) and F(m) are functions of the complex index of refraction of the soot. The complex 

index of refraction is defined as m = n-ik, where, n, is the ratio of the speed of electromagnetic 

radiation in a vacuum to the speed in the medium. For absorbing media (such as soot), the index 

of refraction is always complex and the k component is an indication of the absorptive property

of the medium. The complex index of refraction for soot that will be used in all subsequent 

calculations is the one most frequently used, m=1.57-i0.56 [14]. Refractive indices of soot have 

been shown to be relatively independent of fuel type; therefore, the same refractive index will be

used for all three fuel sources [15]. Note that simulated smoke is not an absorbing medium; 

therefore, its index of refraction will not contain an imaginary component (k). The functions, E

and F, of the complex index of refraction used in calculating the extinction are 

















+

− = 2

1 ( ) 2

2

m

m E m Im (14)

2

2

2

2

1 ( )

+

− = mm F m . (15)

The above equations for E(m) and F(m) can be used for x<0.1, but for shorter wavelengths or 

larger particles (up to x≈0.5) E(m) should be replaced by E’(m), defined in references 10 and 13 

as 

( ) ( ) 































+

+ +

















+

− = +

2 3

27 38

2

1

15

Im 2

4 2 2

2

2 2

'

m

m m

m

x m E m E m p . (16) 

Equations 11 through 16 were used to calculate the optical properties (extinction, scattering, and 

absorption) for all three types of actual smoke using the RDG-PFA theory, which has been 

shown to agree with measured properties within experimental uncertainty [15]. 

The RDG-PFA theory described above allowed for calculation of the extinction properties, 

including the relative contributions of scattering and absorption (shown in figures 17-19), which 

is not possible with typical cone calorimeter measurements. The scattering (thus extinction also) 

of the resin cake is slightly higher than the other two sources due to having both a larger primary 

particle size and fractal dimension. For all samples, the extinction (scattering and absorption) 

decreases as the wavelength of light increases for a constant particle size (from approximately 9 

to 3 m2

/gm). From this analysis, it is evident that up to 30% of the total extinction can be 

attributed to scattering for actual soot from these three fire sources. This further validates the 

claim that treating soot particles to be in the Rayleigh regime results in a large error in the total 

extinction and other measurements drawn from the total extinction such as volume fraction (fv). 

Overall, there is a good agreement in optical properties for the three different sources. 

22
0

2

4

6

8

10

0.5 0.6 0.7 0.8 0.9 1

Wavelength (microns)

Extinction Coefficient 

(m2/gm)

Suitcase

Resin

JetA

FIGURE 17. MASS-SPECIFIC EXTINCTION 

0

1

2

3

4

0.5 0.6 0.7 0.8 0.9 1

W avelength (m icrons)

Scattering Coefficient (m2/gm)

Suitcase

Resin

JetA

FIGURE 18. MASS-SPECIFIC SCATTERING 

0

1

2

3

4

5

6

7

0.5 0.6 0.7 0.8 0.9 1

W avelength (m icrons)

Absorption Coefficient (m2/gm)

Suitcase

Resin

JetA

FIGURE 19. MASS-SPECIFIC ABSORPTION 

23
Calculation of these properties proves useful in obtaining concentration (i.e., volume fraction or

mass concentration) from light extinction measurements already being performed at the FAA 

full-scale test facility by using the extinction coefficient value corresponding to the wavelength

of the lasers being used (see equation 17). Calculation of the soot volume fraction, using the 

specific extinction coefficient calculated in equations 11 through 13 using the RDG-PFA theory, 

should provide reliable results. The volume fraction of soot (fv) can be calculated in the 

following manner: using K from the light extinction measurement, the value of σext is calculated

using the RDG-PFA theory and the density of the soot (ρsoot in kg/m3

) [11 and 16] 

ext soot

v

K f

σ ρ = (17)

5.2 SIMULATED SMOKE.

As stated previously, calculation of the size parameter allows one to assess the validity of the

Mie theory for a particular size droplet and wavelength. Recall that for x=O(1), the extinction

properties of the particles can be described by the complex Mie theory [10]. Simulated smoke

droplets are in this range; therefore, the Mie theory will be used to characterize the optical 

properties. 

A Mie theory computer code, based on the code in appendix A of reference 10, was used to 

calculate the optical properties of the simulated smoke. Two different sized simulated smoke

droplets were considered: a 0.3-micron-diameter droplet corresponding to the average droplet

size from the smoke generator study using supplier 1 (in table 3) and 0.66-micron droplets 

corresponding to the average droplet size obtained during a study performed at the FAA for a 

different smoke generator. These droplet sizes correspond to size parameters (x) from 0.94 to 4.1 

for wavelengths less than 1 micron. The index of refraction used in the calculations was m = 1.4 

(based on values of glycerol assumed to be very close to mineral oil or paraffin). 

The optical properties for the two droplet sizes are shown in figures 20 and 21. Based on the 

plots, it is evident that all the extinction is due to scattering. The droplets do not have any 

absorptive capability, also indicated by the absence of the imaginary component of the refractive 

index. For the smaller droplets (0.3 micron), the extinction is a maximum of 5 m2

/gm for the 

smallest wavelength of 500 nm. The extinction decreases as the wavelength increases to a value 

below 1 m2

/gm for a wavelength of 1000 nm. For all wavelengths, the total extinction for the 

simulated smoke with this size droplet is approximately half of the extinction for actual smoke. 

24
0

1

2

3

4

5

6

0.5 0.6 0.7 0.8 0.9 1

Wavelength (microns)

Mass Specific Coefficient 

(m2/gm)

EXT

SCAT

ABS

FIGURE 20. MASS-SPECIFIC COEFFICIENT FOR SIMULATED SMOKE 

(0.3 micron) 

0

1

2

3

4

5

6

7

8

9

10

0.5 0.6 0.7 0.8 0.9 1

Wavelength (microns)

Mass-Specific Coefficient

(m2/gm)

EXT

SCAT

ABS

FIGURE 21. MASS-SPECIFIC COEFFICIENT FOR SIMULATED SMOKE 

(0.66 micron) 

For the larger droplets (0.66 micron), the extinction is a maximum of 9 m2

/gm for the smallest 

wavelength of 500 nm. The extinction decreases as the wavelength increases to a value below 

3 m2/gm for a wavelength of 1000 nm. For all wavelengths, the total extinction for the simulated 

smoke with this size droplet is approximately equal to the extinction for actual smoke, although 

the scattering is significantly higher than the scattering for actual smoke. 

A wide range of optical properties can exist for simulated smoke due to the range in droplet size 

produced by the generator. Even a single smoke generator can produce different sized droplets, 

depending on the machine setting. It has been shown that for the two different droplet sizes, all 

of the extinction is due to scattering for the simulated smoke, while only 30% of the extinction is

due to scattering for the actual smokes. 

25
5.3 APPLICATION TO DETECTION.

Current regulations require that cargo compartments be equipped with smoke detection systems 

that provide a visible indication of a fire. The detection systems should alarm within 1 minute of 

the start of the fire and before the fire has compromised the structural integrity of the aircraft [1].

Two different types of smoke detectors are readily available for use in a variety of applications. 

These two detectors, photoelectric and ionization, alarm when the output of a sensor changes in 

the presence of smoke. These detectors can also alarm due to nonfire sources such as dust, 

simulated smoke, and water vapor. 

Photoelectric detectors contain a light source and a sensor (see figure 22). Under normal 

conditions, the light travels unimpeded across the chamber. If smoke is present in the chamber, 

light is scattered and some light is detected by the sensor. The detection of light by the sensor 

causes the device to alarm. Ionization detectors contain a small radiation source that ionizes the 

oxygen and nitrogen atoms in the air. The ionization (removal of an electron from the atom)

creates a current due to the flow of positive and negative ions between two electrodes. When 

smoke enters the system it scavenges the ions, reduces the current, and produces an alarm. With 

knowledge of the operation of smoke detectors, the impact of the characteristics (morphology, 

transport, and optical properties) of actual and simulated smoke on detection times could be 

hypothesized. 

Ionization 

Photoelectric

-

+

Sensor 

Light 

Source 

FIGURE 22. SCHEMATICS OF SMOKE DETECTORS 

Photoelectric-type detectors are most commonly used in aircraft cargo compartments. As 

described above, these detectors alarm based on light scattered from smoke; therefore, the 

portion of the extinction due to scattering would have the most impact on smoke detection. The

scattering properties of both simulated and actual smoke were calculated in the sections 5.1 and 

5.2. All the extinction from simulated smoke is due to scattering, while only 20%-30% of the

extinction is due to scattering for actual smoke. The mass-specific scattering is shown in figure 

23 for all the smoke at visible wavelengths, since the source for most photoelectric detectors 

emits in the visible regime (some smoke detectors use an infrared light emitting diode as the light 

source). For both sizes of simulated smoke droplets, the scattering is greater than that calculated 

for any of the actual smokes. The scattering properties of the smaller simulated smoke droplets

(0.3 micron) are similar to the actual smoke, although at short wavelengths the difference is

fairly significant (up to 40%). The larger simulated smoke droplets (0.66 micron) scatter 

significantly more than any of the actual smoke. This considerable difference in scattering

properties could result in significantly different detection times. 

26
0

1

2

3

4

5

6

7

8

9

10

0.5 0.55 0.6 0.65 0.7

Wavelength (microns)

Mass-Specific Scattering (m2/gm)

Suitcase

Resin

JetA

Sim(0.3)

Sim(0.66)

FIGURE 23. COMPARISON OF SCATTERING PROPERTIES 

Properties of the smoke most likely to affect the alarm potential of the ionization detector are 

particle size, concentration, and transport. It is also believed that the particle charge (possibly

also dependent on the composition) could likely play a role in the sensitivity of ionization

detectors. Actual and simulated smoke are quite different with regard to morphology and 

composition; therefore, one could expect a different detector response, depending on the type of 

smoke. 

6. SUMMARY OF RESULTS AND CONCLUSION.

This research provided insight into the morphology, transport, and optical properties of actual 

and simulated smoke. The following observations were made. 

6.1 MORPHOLOGY.

• Soot from flaming fires (resin, suitcase and Jet A) was quantitatively characterized using 

thermophoretic sampling and subsequent analysis. 

• Soot from smoldering fires was not characterized via transmission electron microscopy 

since the smoke did not contain solid particulate. 

• Smoke from flaming fires was black, while smoke from smoldering fires was white 

(yellow on filter paper). 

• Soot from all flaming fire sources consisted of spherical primary particles aggregated into

wispy chains. 

27
− The average primary particle diameter was 80 nm. The overall range of sizes 

within all samples was between 40 and 140 nm. 

− The fractal dimension measurements (1.56-1.71) were consistent with visual 

observations and with values quoted in the literature. 

− The fractal prefactor measurements (7.15-7.59) were consistent with values

quoted in the literature. 

− Overall, morphology of soot from all flaming sources was similar. 

• Simulated smoke consists of droplets created when heated liquid condenses upon being 

expelled from the generator. 

• Characterization of the morphology was obtained from the machine manufacturer. 

• The droplet sizes for simulated smoke varied greatly (0.2-60 microns). Even a single 

machine could be operated under various conditions producing simulated smoke with

very different morphological properties. 

• The morphology of simulated smoke is considerably different from actual smoke because 

− actual smoke consists of solid particulate while simulated smoke is a fog 

(i.e., droplets). 

− the size of the individual primaries in actual smoke are a minimum of 3 times 

smaller than the simulated smoke droplets. 

− actual smoke primaries agglomerate into chains.

− great variation was found in simulated smokes (even from a single machine), 

while actual smoke appear to have a relatively narrow range of characteristics for 

different fires and fuels. 

6.2 TRANSPORT.

• Transport of actual and simulated smoke was analyzed with knowledge of morphology 

and density. 

• Based on the results from the force balance equations, simulated smoke droplets are small 

enough to be transported with the flow. Actual smoke particulate will also follow the 

flow. 

• The driving potential for transport could differ between actual fire sources and simulated

smoke sources. Smoke from actual fires is buoyancy-driven due to the increased 

temperature, while simulated smoke transport may be momentum-driven due to the lower 

temperatures and forced expulsion from the vaporization chamber. 

28
• A smoke generator modified with helium could provide buoyancy, therefore making the 

transport more like actual smoke. 

6.3 OPTICAL PROPERTIES.

• With knowledge of the morphology and composition, the optical properties of actual and 

simulated smoke were calculated. 

• The RDG-PFA theory was used to calculate the optical properties of actual soot since 

agglomerated soot are not within the Rayleigh regime, and the Mie theory for an 

equivalent sphere has typically been inadequate. 

• For actual smoke, the total extinction decreased as the wavelength increases (from a 

maximum of 10 m2

/gm at 500 nm to 3 m2/gm at 1000 nm). 

• The scattering accounted for 30% of the total extinction for actual smoke.

• The overall extinction of all three actual smokes was very similar and also agreed with 

the range typically stated in the literature. The scattering from the resin cake was slightly

higher due to the larger primaries and fractal dimension. 

• For simulated smoke, the total extinction decreased as the wavelength increased and the 

total extinction was greater for the bigger droplets (0.66 micron). 

• All the extinction was due to scattering for the simulated smoke. 

• The extinction for the smaller droplets (0.3 micron) was approximately half of the total 

extinction for the actual smokes from 0.5-1 micron wavelengths, while the extinction for 

the larger droplets was approximately the same as the actual smokes. 

• The scattering for the smaller droplets was slightly higher than the actual smoke, but the

scattering for the larger droplets was almost double the actual smoke scattering. This 

could have a great impact on detection time for photoelectric smoke detectors. 

• Knowledge of optical properties can be used to calculate soot volume fraction from 

extinction measurements in the full-scale model validation experiments. 

As summarized above, this research characterized the dominant features of actual and simulated 

smoke used in the certification of aircraft cargo compartment detection systems. The smoke

from actual flaming fires and aerosol generators was compared based upon morphological, 

optical, and transport properties. Several differences were noted that will likely impact the way 

detection systems interact with simulated smoke compared to actual smoke. Minimization of this

affect could be acheived through careful selection and standardization of simulated smoke

sources. 

29
6.4 CONCLUSION.

Standardization of the in-flight certification process through characterization of simulated smoke

generators (specification of machine, operating setting, etc.) is the only way to ensure all cargo

compartment detection systems are being certified under similar conditions. Calculation of the

extinction, scattering, and absorption for the characterized simulated smoke could be performed

using the Mie theory code. Comparison with the results from the actual smoke characterization

using the RDG-PFA theory could ensure that a suitable simulated smoke source is being used 

that should interact with the detector in the same way as the intended actual fire source. 

7. REFERENCES.

1. Advisory Circular, AC 25-9A, “Smoke Detection, Penetration, and Evacuation Tests and 

Related Flight Manual Emergency Procedures,” 1994. 

2. Williams, J.M. and Gritzo, L.A., “In-Situ Sampling and Transmission Electron 

Microscope Analysis of Soot in the Flame Zone of Large Pool Fires,” 27th International 

Symposium on Combustion, 1998. 

3. R.A. Filipczak, D. Blake, L. Speitel, R.E. Lyon, J.M. Suo-Anttila, and W. Gill, 

“Development and Testing of a Plastic Smoke Generation Source,” Proceedings of the 

Fire and Materials Conference, January 2001. 

4. Köylü and Faeth, Combustion Science and Technology, 108:207-229 (1995a). 

5. Krishnan, S.S., Lin, K.C., Faeth, G.M., Journal of Heat Transfer, 2001; 123: 331. 

6. Haynes, B.S., Wagner, H.G.G., Progress in Energy and Combustion Science, 1981; 7: 

229. 

7. Eklund, T.I., “Generation of a Buoyant Plume of Artificial Smoke for Airplane Tests,” 

DOT/FAA/CT-90/9, September 1990. 

8. “The SFPE Handbook of Fire Protection Engineering” (1995). 

9. Dobbins, R.A. and Megaridis, C.M., “Absorption and Scattering of Light by Polydisperse 

Aggregates” Applied Optics, Vol. 30, No. 33, 1991. 

10. Bohren, C.F. and Huffman, D.R., “Absorption and Scattering of Light by Small 

Particles,” 1983. 

11. Choi, M.Y., Mullholland, G.W., Hamins, A., and Kashiwagi, T., “Comparisons of the 

Soot Volume Fraction Using Gravimetric and Light Extinction Techniques,” Combustion 

and Flame, 102:161-169, 1995. 

12. Köylü, U.O. and Faeth, G.M., “Radiative Properties of Flame Generated Soot,” Journal 

of Heat Transfer, 115:409-417, 1993. 

30
13. Dobbins, R.A., Mullholland, G.W., and Bryner, N.P., “Comparison of a Fractal Smoke 

Optics Model With Light Extinction Measurements,” Atmospheric Environment, 28:889-

897, 1994. 

14. Smyth and Shaddix, “The Elusive History of m=1.57-0.56i for the Refractive Index of 

Soot,” Brief Communication, Combustion and Flame, 107:314-320, 1996. 

15. Wu, J.S., Krishnan, S.S., and Faeth, G.M., “Refractive Indices at Visible Wavelengths of 

Soot Emitted From Buoyant Turbulent Diffusion Flames,” Journal of Heat Transfer, 

Vol. 119, May 1997. 

16. Zhu, J., Choi, M.Y., Mullholland, G.W., and Gritzo, L.A., “ Measurement of Soot Optical 

Properties in the Near-Infrared Spectrum,” International Journal of Heat and Mass 

Transfer, 43: 3299-3303, 2000. 

31/32