Posts Tagged ‘Fire Investigator’

by: Noah Ryder and Jason Sutula

This topic was presented at the International Symposium on Fire Investigation Science and Technology (ISFI 2014, September 22-24), which took place at the University of Maryland in College Park, MD.


Over the last several years, a continued push to design and build “green or sustainable” buildings has accelerated throughout the United States.  According to the U.S. Environmental Protection Agency, the term “green building” is defined as “…the practice of creating structures and using processes that are environmentally responsible and resource-efficient throughout a building’s life-cycle from siting to design, construction, operation, maintenance, renovation and deconstruction.” The goal of green building construction is to reduce the overall impact of building and development on human health and the environment.

While the concept of green building construction and green materials is important from a global perspective to ensure minimal impact of growth and development on the environment, little thought has been given to the impact of green building construction and green materials on fire initiation or fire growth within green buildings or with green materials.  The risk of using these materials in building construction has been highlighted by a number of recent fires in which firefighters were killed or injured, property losses have been excessive, and unexpected fire damage has been observed.

In the event that a fire incident occurs within green building construction, the type and installation locations of the green materials can result in enhanced heat release rates and pathways of fire spread not typically observed with standard construction materials.  The composition, construction, and placement of green materials in newly constructed structures runs the risk of creating fire damage that may be misinterpreted by investigators after a fire incident.

Thus, a need exists to develop a methodology that can be used to evaluate and compare the potential fire growth risk associated with green materials.  This paper proposes the use of the cone calorimeter as a standard test method that would allow for relevant material properties and material performance data to be obtained on green materials.  Example data is presented and linked to the potential consequences of fire growth on green materials as well as the probability of a fire occurring or spreading.  A simple formulation is then proposed that can be used to compare the relative performance of green materials and the risk associated with them.  Finally, the example data is extrapolated within a limited example of a post-fire scene reconstruction to assess resulting damage patterns in the context of green materials.


The modern green building movement has roots from the rapid increase in oil prices that occurred in the 1970’s in the U.S.[i]  A byproduct of the gas crisis was increased funding in research to improve energy efficiency in all aspects of building development.  This included research into construction methods, more efficient energy consuming devices, and green materials.1 While the concept of green building and green materials is important from a global perspective to ensure minimal impact of growth and development on the environment, little research has been conducted on the impact of green construction and green materials on the potential risk associated with fire initiation or growth within green construction or with green materials.  In the event that a fire does occur, green materials may release significantly increased quantities of carbon dioxide above standard material.  Thus, the sustainability of the structure is called into question.

The goals of this paper are to summarize some of the current fire data available for green materials, present various test methods available for assessing the flammability hazard of green materials, and offer a potential methodology for an effective comparison of the relative risk associated with the materials.

Risk Associated with Green Materials

The risk associated with green materials has been highlighted by a number of recent fires in which firefighters were killed or injured.  These fires most often occurred in newer construction where engineered I-joists were used and the floors collapsed in short order.  This has caused a number of fire departments and municipalities to call for an increase in understanding of how green materials perform under fire conditions in order to determine whether it is safe for fire fighters to enter a structure involved in fire.

Risk is an inherent part of life and takes on a special role when examined from the perspective of fire.  Risk must be identified, assessed, and mitigated to the greatest extent possible within a reasonable cost.  This is true whether a process is being assessed within a chemical plant or if a green material is being evaluated for sale in the commercial market.  To quantify it, risk is typically presented as[ii]

Risk = (Consequence of Incident) x (Frequency at which Incident Occurs)

The process of assessing the risk begins with identifying hazards associated with the process or the product.2  For example, if a green material candidate is being evaluated for sale in the commercial market, the testing can be done to determine if the material is combustible.  Additionally, if a particular material is a combustible hazard, standardized and custom testing can be used to determine environmental conditions that could drive the green material to ignition.

Once various hazards are identified with a particular candidate green material, the risk equation can be used to evaluate the magnitude of the risk.  This is the second step of the risk analysis process and is referred to as Risk Assessment.2  Available statistics related to the incidence rate of fire in the U.S. show that fire is a rare event.  Unfortunately, the consequences associated with a fire event can be astronomical when accounting for loss of life, injuries, and potential property losses.

Once the first two steps have been adequately addressed, Risk Management can be implemented in an effort mitigate the analyzed risk.2  When taken in the context of a candidate green material for commercial sale, risk management can include the determination of a test or suite of tests that the material can undergo to determine its relative hazard in comparison with other non-green materials in the marketplace.

Very little research has been done specifically on the risk associated with green materials or even on their performance from a fire perspective; however, FM Global has produced a report that addresses the potential risk to green materials due to fire and the impact on total carbon emissions.  Unfortunately, this does not directly address issues related to safety of the occupants and first responders.

Cone Calorimeter

One of the more prevalent bench-scale test apparatus that exists for determining the ignition and flammability parameters of a particular material is the Cone Calorimeter.  A test program using the Cone Calorimeter is typically conducted using a series of samples of the investigated material (i.e., square shape with four inch sides) that are exposed to different heat fluxes in the range 1-50 kW/m2.  Figure 1 shows an overall picture of the Cone Calorimeter in a laboratory setting.

Figure 1

Figure 1 Overall View of the Cone Calorimeter Apparatus

The theory behind the testing is based on an ignition model for a liquid as adapted to a solid combustible fuel.  Ignition in solid bodies can be physically modeled as a function of ignition temperature, as described by Quintiere.[iii]  The theoretical approach rigorously applies to liquids, but can be easily extended to decomposing solids, assuming that decomposition chemical reactions do not cause any significant variation of the surface temperature.  This approximation is considered to be reasonable for most materials.3  The underlying concept is that the surface temperature is sufficient to generate enough vapors to reach the lower flammable limit (e.g., the flash point).  Achieving the lower flammable limit allows a piloted ignition of the pre-mixed flame, which leads to a sustained diffusion flame.  As an additional assumption, the surface temperature is equal to the auto-ignition temperature of the vapor mixture at the surface.  This concept may also be applied to thermally thick materials.[iv]

When conducting each test, the time to ignition is recorded for every heat flux as the time interval between initial exposure of the sample and its ignition; however, the igniter is activated almost immediately after the insertion of the sample.  The critical heat flux is then determined through 1-2 kW/m2 steps, starting from 10 kW/m2.  The threshold is given by the heat flux to which the sample is exposed and has not undergone ignition after a 30-minute exposure.  A typical curve reporting the time to ignition as a function of imposed heat flux is shown in Figure 2.

figure 2

 Figure 2 – Time to Ignition as a Function of Heat Flux for ABS Thermoplastic

 Figure 2 shows a common thermoplastic ABS (Acrylonitrile Butadiene Styrene) chosen as a representative example.  Very low times to ignition (i.e., less than one minute) have been measured for heat fluxes in the range 30-50 kW/m2.  The critical heat flux was evaluated as 9.5 kW/m2 because no ignition was observed at 9 kW/m2, while a time to ignition of 670 s was measured at 10 kW/m2.

Once a test is used to determine a measure of flammability, the thermal inertia of a material can be determined.  The last step before the ultimate evaluation of the thermal inertia is to determine the b parameter, which pertains to the relation between normalized heat flux and the square root of time to ignition.  This function is presented in Figure 3 for the considered case.

figure 3

 Figure 3 – Normalized Heat Flux as a Function of Square Root of Time to Ignition

As shown in Figure 3, the data points collapse onto a line, which leads to a straightforward evaluation of b as its slope.  The heat flux as a function of time to ignition presented in Figure 3 only serves as a way to linearize the dependence of ignition on the imposed heat flux, while the physical trend is actually shown in Figure 2.

Using the above formulation, the k(rho)c thermophysical property is calculated to be equal to 0.16 kW2 m-4 °C-2 s. Using a similar analysis and test data, thermophysical properties can be determine for any green or non-green material.


Based on the definition of green materials, there are a large number of materials that are currently being used, or considered for use, in green building projects.  Some of these materials include bamboo, straw, Linoleum, sheep wool, panels made from paper flakes, seagrass, cork, coconut, lignin, and wood fiber plates.  The available test data on these materials is limited, but some data does exist in the scientific literature.

One of the byproducts of commercial paper production is lignin.  This byproduct has been deemed by industry as a natural, renewable, and biodegradable material,[vi] which fits the definition of a green material.  Due to its ability to char when exposed to heat or flame, it is mixed with other components to create hybrid materials.[vi]  In one particular study,[vi] lignin was blended with styrene–acrylonitrile–butadiene copolymer (ABS) to produce a hybrid material.  Cone calorimetry testing was performed on the resulting hybrid and was compared with standard ABS.  The results of the testing indicated that the addition of the lignin reduced the peak heat release rate of the sample and slowed the combustion process.  While these results were promising, the data indicated that the peak heat release remained at an extremely high value, 526 kW/m2, when subjected to an external heat flux of 35 kW/m2.  This provides a good example of a green material in development that attempts to reduce the flammability hazard of a building material currently in use, but must be carefully evaluated to determine the actual benefit from a fire risk perspective.

Another potential green material that has been tested in the literature is Linoleum.  Linoleum is most commonly used as a flooring material.  In a study designed to investigate the flammability response of various flooring materials,[vii] Linoleum was compared with particle board, rubber, PVC, and polypropylene using the cone calorimeter.  The results indicated that the Linoleum floor covering behaved moderately from a flammability perspective when compared to the particle board (i.e., peak heat release rate of 247 kW/m2) and rubber (i.e., peak heat release rate of 754 kW/m2).  Linoleum produced a peak heat release rate of 400 kW/m2.[vii]  These values were obtained with an external heat flux of 50 kW/m2.  From a relative analysis, Linoleum appears to be a better actor from a flammability perspective than rubber when comparing this data and a worse actor than particle board.  The data from this type of study could be used to better assess the fire spread and growth rate of Linoleum when analyzed during a post-fire investigation.

In cone calorimeter testing conducted at the University of Maryland, a number of green materials were tested and a summary of the results is presented below.  In some cases, the green materials performed well in the cone calorimeter (e.g., high critical flux for ignition values and low peak and total heat release rate values), while others performed very poorly.  This clearly shows that it is important to test individual products in order to better understand their fire growth and spread performance.

Bamboo Flooring

Bamboo flooring produced a critical flux for ignition of 13 kW/m2, a higher value than that associated with many typical wood flooring products.[viii]  Bamboo is being used in an increasing number of products because of how rapidly it can be grown, and, thus, it is deemed to be a sustainable material.  The material appears to be comparable to or to have a slightly better fire performance than other comparable products such as oak flooring.  Figure 4 depicts the data for the critical heat flux of Bamboo Flooring.

figure 4

 Figure 4 – Heat Flux versus Ignition Time for Bamboo Flooring

Foam Spray Insulation

Several different varieties of spray-in foam insulation were tested and each yielded the same basic results.  The fire retardant foam did not appear to be significantly different in behavior to the non-fire retardant varieties.  All three foams that were tested performed identically.  Figure 5 shows the data for the critical heat flux for the various spray-in foams.

figure 5

 Figure 5 – Heat Flux versus Ignition Time for Spray-in Foam Insulation

As shown in Figure 5, the foam insulation achieved ignition at very low heat incident heat fluxes (< 10 kW/m2) and did this in less than two minutes of exposure.  In comparison, cellulose insulation will tend to smolder and not actively flame and fiberglass insulation is typically noncombustible, though the paper facing may ignite.

Data gaps that current exist must be filled with a sound testing protocol that can determine the relative potential for fire growth and spread of new and current green building materials.  The above-presented results were generated using the cone calorimeter.  This test apparatus is just one of several test apparatuses or methodologies that could be considered for developing a complete understanding of the fire performance of green building materials.  Other test methodologies could include both bench-scale and full-scale testing.


The main issue associated with full-scale testing is the cost of the test.  It is much more expensive to conduct testing on large scales for many reasons.  A larger amount of sample material is needed, an increase in testing personnel may be required, and the support facilities may be significantly larger.  These and many other factors can increase the cost substantially over small, bench-scale testing.

Additionally, a larger test does not guarantee better results.  A classic example of this is through analysis using ASTM E84 – Standard Test Method for Surface Burning Characteristics of Building Materials, which is also more commonly referred to as the Steiner Tunnel Test.  This particular test was developed prior to the common use of thermoplastics as building materials.  Samples are placed on the “ceiling” of the test apparatus and ignited from one side to observe the time of flame spread.  Between various woods and rigid combustibles, the test may provide a fair assessment of their relative flammability.  Unfortunately, the test becomes completely inappropriate for materials that deform and may melt or fall down during the test.  Depending on the material, the use of the ASTM E 84 test can be of very little value in comparing fire flammability test performance of a particular material with actual performance of the material in the field.

The known deficiencies with using the Steiner Tunnel Test have been well-documented.  Thus, other large-scale tests have been put forth as possible alternatives.  One in particular is the ISO 9705 Room Corner Test.  Fire conditions that develop in this particular test are much more in-line with the characteristics of real fires.

Multiple studies have been conducted examining a potential link between small bench-scale testing such as the cone calorimeter and large-scale tests such as the Room Corner Test.  Two studies in particular by Hansen and Hovde[ix] and Quintiere and Lian[x] provided strong analytical data and concluded that the cone calorimeter test was sufficient to predict the results of the larger-scale Room Corner Test.  Based on the known deficiencies of some large-scale tests and literature studies that suggest the small-scale results of the cone calorimeter can predict the useful results of the ISO 9705 Room Corner Test, the cone calorimeter can be considered to be a simple, small-scale test that can be adequately used to assess the flammability properties and relative fire risk of all combustible materials, including green building materials.


As technology changes and new building materials are introduced, it is important to be able to appropriately identify the fire risk that is associated with them.  This requires that a standard approach to risk be adopted so that the risk can be appropriately addressed.  While large-scale testing is often thought of as the best way to characterize a materials behavior in a “true” fire scenario, it may be more useful and practical to utilize a smaller-scale test method, such as the Cone Calorimeter to obtain ignition properties and heat release data.  The data derived from these small standardized tests materials can be indexed against each other and can be used to quantitatively predict large-scale performance.

The risk that green materials pose to structures and to personnel is no different than standard materials with regards to the variables of interest, namely ignition characteristics and heat release.  The main difference is that of performance.  The key variables that can be explored to quantify the risk that a material poses are:

  • Time to ignition (as a function of heat flux)
  • Thermal inertia (as derived from the cone calorimeter or other device)
  • Peak heat release rate
  • Total heat release rate
  • Products of combustion (yield and species)

Risk to Occupants

The risk to occupants posed by green materials is most clearly brought to light by documents detailing the ease of ignition, heat release rate, and toxic products of combustion.  As occupants need to be made aware as early as possible regarding a fire, any reduction in available egress time will be critical.  When looking at the difference in a green foam insulation product vs. cellulose or fiber insulation product, the differences can be examined simply using a standard t2 fire growth.  The foam insulation, even when treated with a fire retardant as shown above, will ignite readily, will tend to expand toward the fire, and, in general, can be treated as a fast or ultrafast fire, whereas the more traditional insulation materials may be non-combustible or slow fire growth.

The other major area of risk to occupants is the toxic products of combustion.  As additional plastics are used in products and building materials, the toxicity of the smoke is increasing.  Thus, in addition to the potential increase in the ease of ignition and the increased heat release rates, toxic smoke can more readily affect occupants as they attempt to egress.

Lastly, the mere presence of these products has been shown to potentially alter a firefighter’s decision making process regarding when and if they should enter a home or structure.[xi]  The concern is that if the materials are in use it may be an unacceptable risk for the firefighters to enter, and, in turn, this affects the ability of the occupant to be rescued.

Risk to First Responders

It has been well-documented[xi],[xii] in the news and in other locations that new lightweight building materials and insulation products produce an elevated level of risk to first responders.  Insulation products have created fires that have developed more rapidly, and structural flooring components have a reduced ability to withstand a fire.  This has led to an increased number of fire deaths and injuries from first responders and a national push by several groups[xiii] to further examine the use of green materials and to ensure that their response to fire is well understood.

Michigan saw two fires involving manufactured OSB I-joists that resulted in firefighter deaths within a short period of time.  These deaths occurred largely due to the failure of the flooring, which resulted in the firefighters falling through the floor a short time after the fire initiation and into an actively burning basement.11  Similar incidents have occurred in Wisconsin, Tennessee and elsewhere around the country.  In Pennsylvania, these and other incidents have caused a change in the law that essentially requires dimensional lumber to be used in new construction or requires that gypsum board be installed as a fire barrier below the OSB joists.

In full-scale testing comparing standard dimensional lumber with an engineered floor assembly, the engineered floor assembly collapsed within 15 minutes while the dimensional lumber was still structurally sound for a considerable period afterward.[xiv]

Risk to a Structure

The risk to a structure largely rests with the ease of ignition and the fire growth.  Part of making a building green and energy efficient is ensuring that there is a tight seal to minimize energy losses.  In the process, it also creates an ideal condition for containing the heat during a fire.

There have been a number of high profile fires in which the building materials played a key role, most recently the 2009 Monte Carlo fire in Las Vegas, the Borgata Water Club fire in Atlantic City in 2007, and the Mandarin Oriental Hotel fire in Beijing in 2009.  These are of particular note because each of these fires involved the use of foam materials on the exterior of the building, primarily for energy efficiency reasons.  Structural Insulated Panels (SIPs) are being used with increasing frequency and their use is increasing the fire load and combustibility of structures when compared to other materials.  In addition, lightweight concrete construction and other forms of construction are susceptible to early structural collapse during a fire.

There have also been an increasing number of fires associated with the spontaneous ignition of spray foam insulation during the installation process.  Since the curing process is exothermic and if the chemical mixture or application is incorrect, a fire can occur during or after the installation.[xv]  In this case, the product not only is a contributor to the fuel load, but can act as the ignition source and is often located in an area that is not covered by automatic fire suppression.


There have been several studies that have attempted to characterize the risk by using scaled data to correlate to large-scale results.[ix],[x],[xvi]  These have each offered a perspective on how this can be done.  The method outlined in Quintiere and Lian[x] shows promise as an effective way to characterize the risks associated with materials.

The method uses data derived from the cone calorimeter to predict time to flashover in the ISO 9705 compartment and has shown good success with a range of 54 different materials.  The methodology relies on four parameters:

  • Heat Release parameter, obtained from the heat release rate measurement
  • Thermal Response parameter, obtained from the slope of the time to ignition1/2 results
  • Critical Heat Flux, minimum heat flux at which ignition occurs
  • Available Energy parameter, the total energy released by the material during the test

These properties can be used to generate a curve to predict the measured time to flashover.  The empirical correlation that results from this analysis is:

equation 7

The results show that this equation can predict the phenomena of flashover fairly well.  Thus, the propensity for a material to cause flashover can be used as a quantitative means for evaluating the risk the material poses from a fire behavior standpoint.  If a material has the ability to produce flashover conditions in a shorter time period than other materials, then it can be viewed as increasing the risk.


The push to include green materials in building construction has already resulted in an impact in fire investigation.  Knowledge of the fire risk and fire growth properties of green building materials will continue to take on importance in the field.  Due to the lightweight nature of the fuels, rapid fire spread will destroy physical evidence and can mimic the rapidity of burn that is commonly seen with liquid accelerants.

One example of this was the August 13, 2006 fire in Green Bay, Wisconsin.[xvii]  The fire began in the basement of a single family residential home.  Fire department personnel made entry into the structure and within minutes, the first floor collapsed into the basement, injuring one fire fighter and resulting in the death of another.  Post-fire analysis identified the construction of the floor slab to be lightweight pre-fabricated wooden I-beams.  The resulting damage would have been difficult to account for if fire department personnel had not been on the scene early enough, and the fire had been allowed to continue to burn without intervention.  Due to the rapidly burning nature of the lightweight pre-fabricated joists, entire portions of a residential structure could be lost during a fire.  This large extent of damage can make origin determination difficult and could result in the misinterpretation of the damage patterns.  Consideration must be given to the materials involved at a fire scene to ensure proper interpretation of the fire growth and spread.


Green materials are being introduced into the marketplace at a rapid pace, often with minimal fire testing.  When tests are required, they are often poor predictors of how the materials will respond under real fire conditions or at a larger-scale.  As buildings become more elaborate and move toward increasing sustainability through the use of green materials, the materials utilized may present an increased fire risk.  There needs to be a methodology that can be used to evaluate and compare the potential risk associated with a particular green material.  The cone calorimeter is a simple standard test that allows for relevant material properties and material performance data to be obtained.  This data pertains to both the potential consequences of a fire as well as the probability of one occurring or spreading through the ignition delay curve.  Quintiere and Lian[x] and others have provided several good attempts at using the cone data to predict full-scale fire behavior.  The simple formulation can be used to compare the relative performance of materials and, indirectly, the risk associated with them.  This could be used as a means of regulating what the minimum performance characteristics of a material need to be in order to be acceptable.  In addition, it provides flexibility as the measure is not based on a single material property but on a range of material parameters.  Finally, understanding and quantifying the risk associated with green materials will allow for better understanding of the resulting damage patterns at a fire scene when green materials have been involved.

[i] “Green Building,” [Online]. [Accessed: 22-Dec.-2011].

[ii] N. Hyatt, Guidelines for process hazards analysis, hazards identification & risk analysis. CRC Press,  p. 474., (2003).

[iii] J. Quintiere, “A theoretical basis for flammability properties,” Fire and Materials, (2006).

[iv] J. Troitzsch, International plastics flammability handbook, p. 500, (1983).

[v] ASTM 1321 Standard Test Method for Determining Material Ignition and Flame Spread Properties.

[vi] P. Song, Z. Cao, S. Fu, Z. Fang, Q. Wu, and J. Ye, “Thermal degradation and flame retardancy properties of ABS/lignin: Effects of lignin content and reactive compatibilization,” Thermochimica Acta, vol. 518, no. 1, pp. 59–65, (2011).

[vii] P. Johansson and J. Axelsson, “The influence of floor materials in room fires,” Brandforsk Project 300-061.

[viii] M. Spearpoint, “Predicting the piloted ignition of wood in the cone calorimeter using an integral model — effect of species, grain orientation and heat flux,” Fire Safety Journal, (2001).

[ix] A. S. Hansen and P. J. Hovde, “Prediction of time to flashover in the ISO 9705 room corner test based on cone calorimeter test results,” Fire and Materials, vol. 26, no. 2, pp. 77–86, (2002).

[x] J. Quintiere and D. Lian, “Inherent flammability parameters—Room corner test application,” Fire and Materials, vol. 33, pp. 377–393, (2009).

[xi] “Lightweight Building Materials Cause Greater Fire Risk – Milwaukee News Story – WISN Milwaukee.”

[xii] “ LIVE: Massachusetts Fires Tied to Spray Foam Incite Debate by Tristan Roberts on 07/14/2011,” [Online]. Available: [Accessed: 23-Dec.-2011].

[xiii] J. Tidwell and J. Murphy, “Bridging the Gap: Fire Safety and Green Buildings,” [Online]. Available: [Accessed: 23-Dec.-2011].

[xiv] “Common Building Material Poses Deadly Threat To Firefighters – Milwaukee News Story – WISN Milwaukee,” [Online]. Available: [Accessed: 23-Dec.-2011].

[xv] “ LIVE: Fire Risks Not Limited to Spray-Foam Insulation by Tristan Roberts on 11/01/2011,” [Online]. Available: [Accessed: 23-Dec.-2011].

[xvi] R. Petrella, “The Assessment of Full-Scale Fire Hazards from Cone Calorimeter Data,” Journal of Fire Sciences, (1994).

[xvii] [Accessed: 01-August-2014].


by: Jason A. Sutula


The movie Backdraft opened in 1991 while I was still in high school. I will admit that there was something about that movie that peaked my interest in fire and fire investigation. I cannot give the movie full credit for why I eventually chose the fields of Fire Protection Engineering and Fire Investigation, but it definitely deserves some credit as an influence in my life. I have vivid memories of watching the fire move throughout the movie as if it was alive and with a very devious personality. Only a few short years later, during my education in the Department of Fire Protection Engineering, did I discover that many of those wonderful scenes were far from the reality of fire behavior and were just the product of some amazingly creative camera work.

Backdraft does do a great job of reiterating just how dangerous a fire can be, both to occupants of a structure involved in a fire as well as the fire department personnel who risk life and limb to perform rescue and extinguishment operations. Unfortunately, the movie does not do a great job of portraying or explaining just what a “backdraft” is.

The term backdraft is defined in NFPA 921: Guide for Fire & Explosion Investigations, 2011 Edition as, “A deflagration resulting from the sudden introduction of air into a confined space containing oxygen-deficient products of incomplete combustion.” We can examine this definition by starting with the basic components of a fire. We need something to burn (a fuel), a supply of oxygen (air), and enough heat energy to allow for the combustion process to begin and then continue. If you are missing one of these basic components, you will have no fire.

A backdraft, then, is nothing more than a specialized type of fire. To produce conditions that will allow for a backdraft to develop, you need a confined space (in a residential fire, typically this will be a room) to hold all of the components of the fire. If a fire starts in our hypothetical room and cannot get enough oxygen (imagine a fire burning in a room with the windows and doors completely closed), unburned fuel will escape the fire and fill the room. Once a door or window is then opened to this room, colder fresh air containing oxygen will flow into the room through the bottom of the opening while the hotter combustion products from the fire will flow out the top of the opening. Where these two flows meet, a flammable mixture of fuel and oxygen will develop in the room. The mixed zone will grow and spread into the room and eventually reach the area where the small fire was originally located. At that place in the room, all three conditions for fire are present, and the result is an extremely rapid ignition and spread of flame from the point of origin out toward the opening of the room.

The speed at which the burning flame travels is much more rapid than the speed at which an individual can react to or move away from the fully engulfing flames. Fire service personnel tasked with rescue operations are particularly vulnerable to backdrafts as they open doors within structures to look for possible victims. A tragic example of this phenomenon was reported in a case study report put out by the Building and Fire Research Laboratory (BFRL) at the National Institute of Standards and Technology (NIST) where the lives of two District of Columbia firefighters were claimed by fire in a townhouse at 3146 Cherry Road NE, Washington D.C. The report clearly shows the dangers associated with under-ventilated fires and also demonstrates that these types of fires can be modeled with computational fluid dynamics to better understand the hazard. For more information, the NIST report can be found by following this link:

by: Jason A. Sutula

house fire

I was recently at a conference speaking with several individuals who were not fire investigators and did not work within the field of Fire Science or Fire Protection Engineering. The conversation eventually turned to the type of work that I do for a living, which led to several stories that I enjoy telling related to past fire investigations. Judging by each individual’s reaction at the end of the conversation, I could not help but wonder if I had instilled a new-found fear related to the speed at which a residential fire will spread throughout a modern family or living room.

In particular, the group I was with was surprised when I casually broke out my favorite metaphor that the polyurethane foam stuffed couches, love-seats, and easy chairs found in their respective living rooms were nothing more than large blocks of solidified gasoline. That statement certainly got their attention and opened their eyes to some understanding of why fire injuries and deaths continue to occur, and why the amount of time available to safely escape from a residential fire has decreased substantially over the last 30 years.

As I continued my conversation, I realized that I have developed a bad habit of using many “terms of the art” that other fire investigators would immediately understand, but people not associated with the field might have a hard time picking up on the meaning. I decided at that point that my next series of blog articles would cover some of these fire investigation terms in hopes of bringing further understanding. This article will kick off the fire investigation definition series and will begin with the phenomenon of “Flashover”.

One of the main fire phenomenon responsible for shortening the amount of time available to safely escape from a residential fire is the phenomenon of Flashover. In short, Flashover is a transition from a local fire in a compartment (e.g., your living room) into a fully developed fire that encompasses the entire room and all of its contents. NFPA 921: Guide for Fire & Explosion Investigations, 2011 Edition defines Flashover as, “A transition phase in the development of a compartment fire in which surfaces exposed to thermal radiation reach ignition temperature more or less simultaneously and fire spreads rapidly throughout the space, resulting in full room involvement or total involvement of the compartment or enclosed space.” This definition can be broken into three basic parts: a compartment, a fire, and time.

For a fire to transition to Flashover, a fire must first be initiated in a compartment. Compartments are readily found in all structures and can include full rooms, cabinets, bureaus, closets, wall cavities, etc. A compartment provides a means by which to trap the energy released by the fire. The trapped energy will allow for the overall temperature of the gases in the compartment to increase and for the heat transfer through radiation to increase as well.

The fire itself is an important component. As a fire grows and spreads over the surface of a fuel package in the room (e.g., your living room couch), the rate of energy released by the fire increases exponentially. With the growth of the fire accelerating, the trapped hot gases in the compartment rise to a critical temperature. Additionally, the hot gases radiate energy toward the unburned fuel packages (e.g., other furniture, carpet, drapes, etc.), which raises the surface temperatures of those fuel packages closer and closer to a temperature where they will begin to burn. The critical gas temperature from the fire research literature that most scientists refer to for the onset of Flashover is approximately 1,112 °F (600 °C). Once the critical temperature and radiant energy levels are reached, all of the remaining fuel packages ignite throughout the entire compartment over a very short amount of time. The entire compartment is filled with fire and hot gases, which will expand rapidly through any opening from the compartment to adjacent rooms or to the outside of the building.

There are other variables that come into play with whether or not a particular fire in a compartment will achieve Flashover, such as the amount of oxygen available in the room (i.e., ventilation, window and door openings) and whether or not the fire growth is interrupted by fire fighting efforts or a sprinkler system activation. With enough of the final component, time, the transition will occur, and the after effects can be extremely dangerous to occupants trapped in the residence as well as fire service personnel. A future blog post will explore the dangers associated with Post-Flashover conditions.

by: Jason A. Sutula


Complex objectives arise within every fire origin and cause investigation. These objectives include the standard goals of determining the origin and cause of the fire and can also include less common objectives such as determining the cause of the loss, the cause of the fire spread, and the cause of injury or death. Investigators who follow the Scientific Method while performing fire origin and cause investigations are increasingly relying on research and technological advancements to conduct their analyses and support their opinions and conclusions. One of the most prevalent means of testing hypotheses and supporting analyses is through computer fire modeling.

Computer Fire Modeling

The majority of all computer fire codes used within the fire investigation community can be divided into two categories – zone codes and computational fluid dynamics (CFD) codes. While these two categories are different in their unique abilities and applicability, each type of code can be used to analyze a variety of critical issues within a fire origin and cause investigation.

The zone code category encompasses the many compartment fire codes that represent a modeled system as two different zones. These two zones are composed of an upper gas layer and a lower gas layer. The fire within the system is represented as an energy source that allows for energy and mass transport from the lower layer to the upper layer. Zone codes yield relevant data that is averaged for both the upper layer and the lower layer. Observing detailed fluid flow effects within the system is not possible with this type of code, but bulk fluid transport from compartment to compartment within a model can be predicted.

One of the most commonly used multi-zone fire codes is FAST1, which builds on the routines in the fire code CFAST. Within the code, mass and energy transfer between the zones is accounted for by a plume, mixing at vents (e.g., through connections between compartments), radiation between layers, and heat transfer at the boundary surfaces. The prime equations in FAST are based on the application of mass and energy conservation principles to homogeneous upper and lower gas regions in multi-compartment systems. FAST has been extensively validated in the scientific community1,2,3.

The CFD code category encompasses a much more limited number of currently available codes that can be used to model many different aspects of fire phenomena. CFD codes can divide a system of interest into millions of control volumes or cells. Thus, while zone codes are limited to modeling rectangular structures, CFD codes can easily be manipulated to model much more complicated geometries including curved and round surfaces. CFD models yield data on a much greater scale than zone models. Data can be resolved to each cell used to comprise the system, and local fluid flow effects can be observed.

One of the most commonly used codes for the study of fire scenarios in fire investigation is the Fire Dynamics Simulator (FDS)4. The FDS fire code was developed at the National Institute of Standards and Technology (NIST) by Dr. Kevin McGrattan and co-workers. The code was written utilizing a large eddy simulation technique to describe fire induced flows. This technique splits fluid flow into large-scale turbulence and small-scale turbulence. The large-scale turbulence is directly computed using the basic equations of fluid motion, while the small-scale turbulence is approximated using a sub-grid model. These techniques are well suited for modeling many aspects of the consequences of fire, including fire growth and smoke movement, since these phenomena are driven by large-scale structures in the flow.

Carbon Monoxide Uptake in Fire

The most significant factor affecting the ability of occupants to escape when remote from the room of origin is carbon monoxide. Carbon monoxide is a product of combustion that is formed in very large quantities after flashover, or full-involvement, has occurred within a compartment fire5. Carbon monoxide will combine readily with hemoglobin in the blood to form carboxyhemoglobin (COHb), which in sufficient levels will cause incapacitation followed by death6. Experimentation has shown that incapacitation will typically occur between 30 and 40% COHb6, and that behavioral performance deficits can occur at as little as 20% COHb6. These deficits can affect the ability to make sound decisions when attempting to escape. Additionally, it has been noted in the scientific literature that whether a subject was at rest or doing light to heavy activity drastically increased the observed symptoms from exposure6. Subjects engaged in light activity were observed to have rapid loss of function, which would significantly delay or prevent escape6.

Well-known research has been conducted into predicting the uptake of carbon monoxide in the blood6,7. The most commonly used model is the Coburn, Forster, Kane Equation (i.e., CFK Equation). Peterson and Stewart7 presented a validation of the CFK Equation and included a working model in their 1975 paper. Their model represents a series of equations and variables that can be solved with any iterative program and takes the basic form of7:

eqns for CO

The CFK Equation used in the model analysis developed by Peterson and Stewart is robust enough to calculate the time history of the uptake and excretion of carbon monoxide in any human individual regardless of age. The most pertinent variables necessary for the prediction of carbon monoxide uptake and excretion are the weight, sex, and activity level of the individual exposed and, most importantly, a time history of the concentration of carbon monoxide to which they were exposed.


Neither the zone codes nor CFD codes have directly incorporated a sub-model for the actual prediction of carbon monoxide uptake in the blood of possible victims within a fire. Thus, a methodology must be developed to link the output data that can be produced by a zone fire model or a CFD fire model.

The first step in this methodology is data collection. Every fire scene produces its own unique set of data. This will include the geometrical configuration of the structure, building materials present, eye-witness testimony, and, most important to this particular analysis, the medical records of all victims of the fire. When examining both injured victims of a fire as well as victims who die as a result of the fire, it is very common for documentation to exist that tabulates the COHb of the victim. For victims that end up in the Emergency Room, a measurement of the various gases in the blood is routinely drawn to provide vital information to the medical staff. For the victims who die as a result of the fire, a blood sample is also drawn post-mortem to specifically look for carbon monoxide in the blood. Retaining this type of information in a fire can provide a “hard time” to an analysis of when a victim was removed from exposure to a fire or when a victim became incapacitated as a result of the fire conditions surrounding them.

The second step in the methodology is the development and testing of strong candidate fire initiation hypotheses. If knowledge of the exact initiating event is well supported or not disputed, then this step can be trivial. A fire model of the lone scenario can be generated and allowed to predict the necessary carbon monoxide concentration data. This is usually not the case in most fire investigations, so a matrix of fire scenarios that cannot be ruled out must be developed and analyzed using bounding analysis techniques.

The third step is to process the data generated by the chosen fire model. Carbon monoxide data produced by a given fire model can be used directly with the CFK Equation as presented above to build a time history of the COHb in a particular victim’s blood. The time history can then be use to analyze various factors in a fire reconstruction analysis such as the time to incapacitation of a victim, the position and location of a victim within a structure over the course of the fire, and the time available for safe egress. Figure 1 provides a flow chart of the linking methodology.

Figure 1 for CO

Figure 1 – Flow Chart of Linking Methodology

Strengths and Weaknesses of Each Fire Code

Both zone fire models and CFD fire models are capable of predicting the generation rate of carbon monoxide as a byproduct of combustion. There are differences, though, in how the two categories of codes predict these values. These differences affect the usefulness and applicability of a particular fire code in predicting the generation of carbon monoxide within a given fire scenario.

In general, fire models developed using a zone code will not be able to provide the same resolution of data within a single compartment as with a CFD code. This is balanced by the ease with which a zone code handles the leakage between compartments and the well-validated bulk flow of gases from one compartment to another. Another strength of zone fire models is their ability to more easily handle rapidly changing production rates of carbon monoxide at the transition from a localized compartment fire to a fully involved compartment fire. The transition to flashover represents the conversion of a localized fire to a fully-involved, vitiated compartment fire that is in effect a carbon monoxide pump, which will quickly produce fatal amounts of the gas in short periods of time. While it is possible to account for this with CFD fire codes such as FDS, the process is much more simplified, verified, and quicker with zone fire models.

Due to the various strengths and weakness of both zone and CFD fire models, a combination modeling analysis utilizing both can be effectively used in fire reconstruction analyses. The following case study is presented as a means to demonstrate a combination modeling effort and to demonstrate the use of the methodology outlined in this paper.


A fire occurred in a three-story brick duplex house. The front of the house faced south, and the east wall was shared with a neighboring unit. The first floor had a living room, dining room, and kitchen. The second floor had three bedrooms and one bathroom. The third floor had an attic, which had been converted into a bedroom. There was also a basement with an additional bathroom. Figure 2 depicts a cut away view of the residence. The east wall has been removed and north faces to the right in the figure.

Figure 2 for CO

Figure 2 – Case Study Residence (North Points to the Right)

The fire occurred sometime prior to 2:54 a.m. while the residents of the house were asleep. At the time of the fire, the mother (age 38) and father (age 40) and five children (ages 18, 16, 14, 12, and 1) were present in the residence. The mother and father shared the front bedroom on the second floor with the 1-year-old child. The 14-year-old child and 12-year-old child shared a middle bedroom on the second floor. The 16-year-old child had the rear bedroom on the second floor, and the 18-year-old had her bedroom on the third floor.

When firefighters arrived at the home at 2:54 a.m., the house was already heavily involved. Three of the children (ages 18, 16, 14) had been able to escape by jumping from a second story window to the rear of the structure and were transported to the hospital. The rest of the occupants did not escape from the fire and died as a result.

After the fire, an origin and cause investigation was conducted. Analysis of the fire damage led to an initial conclusion that the fire originated in the basement and was accidentally caused by an electrical malfunction. Another potential accidental cause was electrical activity on an artificial Christmas tree in the room of origin. Subsequent inspections were performed to examine other hazardous electrical conditions and determine if smoke detectors were present. Two smoke detectors were found. One was found in the debris on the basement stairs near the kitchen entrance. The damage to the detector and its battery indicated it was disconnected at the time of the fire. The second detector was located on the ceiling of the third floor. This detector had a weak flash and sound, which did not improve when a newer battery was inserted. Indications of a smoke detector installation were also found on the walls of the second floor, and a later examination uncovered a smoke detector on the second floor within debris.

Autopsies were conducted on the victims of the fire. The father was found at the foot of the stairs on the first floor. Blood sample analysis revealed a COHb level of 28.7%. His cause of death was listed as smoke inhalation with a significant contributory cause of coronary artery atherosclerosis. The mother was found in the rear bedroom on the second floor with her 1-year old child. Her COHb level was reported as 58.1%. The 1-year-old child had sustained a COHb level of 85.4%. The final victim of the fire, the 12-year-old child, was found on the floor in her second floor bedroom. She had sustained a COHb level of 67%. The cause of death in the autopsy reports for these three victims was listed as “smoke inhalation.”

As mentioned, the first step in the proposed methodology is to collect data. The above-presented background is only a short summary of the data that was collected during the investigation phase of this fire event. Most importantly, the autopsy reports and laboratory report of the victims COHb were available and retained in this particular case.

The second step in the proposed methodology is to develop and tabulate the candidate hypotheses for fire initiation. Unfortunately in this particular case, the physical evidence and witness testimony did not allow for the cause of the fire to be narrowed to one scenario. Thus, several hypotheses were formulated and included an electrical heating unit, an artificial Christmas tree, an overheated extension cord, and an electrical start in the entertainment center. These fire scenarios were all carried through into the modeling analysis via separate models built for each unique scenario.

Fire Modeling Analysis

The third and final step in the methodology is to generate carbon monoxide concentration data from the fire modeling analysis and post-process the data using the CFK Equation as presented above to predict the blood COHb levels of the fire victims. In this case study, this analysis was critical as it addressed the lack of operational smoke detectors within the home. It was hypothesized that working smoke detectors within the residence would have afforded the victims of the fire sufficient notification to safely egress the building. Thus, a modeling comparison between the time to smoke detector activation and the time to incapacitation due to carbon monoxide was analyzed.

In order to determine the activation time of the smoke detectors, the FDS model was used. A complete three-dimensional geometry of the residence was created in FDS. The computational geometry of this FDS model contained 489,888 cells. The cells were cubes approximately four inches on a side, and each room of the residence was explicitly modeled according to diagrams in evidence, photographic evidence, and measurements gathered (i.e., refer to Figure 2 for a depiction of the modeled geometry). Many runs were conducted with the FDS model geometry representing the various initiation possibilities.

A zone modeling analysis with FAST was used to predict the time history of the concentration of carbon monoxide within the residence. FAST was chosen for this aspect of the analysis based on the previously presented strengths and weaknesses of CFD and zone fire models. Figure 3 shows an example prediction of COHb for the mother who was found with her 1-year-old child in the rear bedroom near the same window where the survivors had jumped to safety.

Figure 3 for CO

Figure 3 – Example COHb Prediction from Fire Modeling Data

The time history data of COHb uptake was then tabulated across all modeled fire scenarios and presented in tabular format to complete the analysis. Table 1 presents an example of how the most pertinent ignition scenarios in this case study were examined to determine the amount of escape time that would have been available to the residents if they had a working smoke detector on the night of the fire.

    Table 1 for CO
Table 1 – Example of Predicted Available Escape Time

The results shown in Table 1 supported the hypothesis that a working smoke detector in the residence would have provide earlier warning to the residents and allowed more time for escape. The modeling analysis predicted that four minutes of escape time would have been available to the residents as opposed to the actual results of the fire, which afforded them no time at all for self-preservation.


Neither zone modeling codes nor CFD modeling codes currently provide a means for assessing the toxicity effects on fire victims of carbon monoxide exposure. A model user is able to predict the production and transport of the toxic gas throughout the model space, but further analysis must be completed in the post-processing of the model results. This paper has presented a standardized methodology for linking the prediction of carbon monoxide uptake in victims of a fire with computer fire modeling. This methodology is robust enough to calculate the time history of the uptake and excretion of carbon monoxide in any human individual regardless of age and aid in the analysis of various factors in a fire reconstruction analysis such as the time to incapacitation of a victim, the position and location of a victim within a structure over the course of the fire, and the time available for safe egress.


1Peacock, R. D., Jones, W. W., and Bukowski, R. W. “Verification of a Model of Fire and Smoke Transport”, Fire Safety Journal, Vol. 21, No.2 89-129, 1993.

2Nelson, H. E., and Deal, S., “Comparing Compartment Fires with Compartment Fire Models”, National Institute of Standards and Technology, Gaithersburg, MD, International Association for Fire Safety Science.   Fire Safety Science.  Proceedings. 3rd International Symposium, July 8-12, 1991, Edinburgh, Scotland, Elsevier Applied Science, New York, Cox, G.: Langford, B., Editors, pp. 719-728.

3Dembsey, N. A.; Pagni, P. J.; Williamson, R.B., Compartment Fire Experiments:  Comparison with Models. Worcester Polytechnic Institute, MA; California Univ., Berkeley, CA; National Institute of Standards and Technology, Gaithersburg, MD. Fires Safety Journal, Vol. 25, No.3, 187-227, 1995.

4McGrattan, Kevin, et al., “Fire Dynamics Simulator (Version 5) User’s Guide”, NIST Special Publication 1019-5, 2010.

5Gottuk, D.T. and Lattimer, B.Y., “Effect of Combustion Conditions on Species Production,” SFPE Handbook of Fire Protection Engineering, 4th edition, 2008.

6Purser, D.A., “Assessment of Hazards to Occupants from Smoke, Toxic Gases, and Heat,” SFPE Handbook of Fire Protection Engineering, 4th edition, 2008.

7Peterson, J., and Stewart, R., “Predicting the carboxyhemoglobin levels resulting from carbon monoxide exposures,” Journal of Applied Physiology, Vol. 39, No. 4, October 1975.

by: Jason A. Sutula

As a fire investigator, it is our duty to obtain as much information related to the fire incident as possible so that an appropriate analysis of the origin of the fire, cause of the fire, and responsibility for the fire can be completed. In any given fire, the most significant factor affecting the ability of occupants to escape when remote from the room of origin is carbon monoxide. Carbon monoxide is a product of combustion that is formed in very large quantities after a room within a structure achieves full-involvement. Carbon monoxide in sufficient concentrations will cause the incapacitation of victims followed by death. Thus, obtaining autopsy reports and medical data on fire victims is critical in conducting a thorough origin and cause analysis.

This topic and many others will be discussed and presented at the upcoming International Symposium on Fire Investigation Science and Technology (ISFI 2012, October 15-17) taking place at the University of Maryland in College Park, MD. I will be presenting a paper related to the uptake of carbon monoxide by fire victims titled “Methodology for Linking Carbon Monoxide Uptake in Fire Victims with Computer Fire Modeling in Post-Fire Reconstruction Analyses.” The abstract for this paper is presented below, and, after the conference is completed, I will provide a summary of the article in a separate post.


The use of computer fire modeling in post-fire reconstruction analyses has continued to increase in both use and significance. It is now commonplace to find computer fire modeling used in both investigative and research settings for the comparison of competing fire initiation scenarios, detector and sprinkler activation, fire growth and spread, and the transport of toxic products of combustion. In particular, the use of a zone modeling code such as the Consolidated Model of Fire and Smoke Transport (CFAST) or a Computational Fluid Dynamics (CFD) code such as the Fire Dynamics Simulator (FDS) has become the norm when analyzing the most complicated and complex fire losses.

The most tragic of all fire losses are those where a fire fatality has occurred. These fire losses naturally tend to be the more complicated and complex to analyze. One of the most important factors to consider in this type of fire loss is whether or not the victim died as a result of carbon monoxide. Carbon monoxide is, arguably, the most significant factor affecting the ability of occupants to escape when remote from the room of origin. As a product of combustion, carbon monoxide is formed in very large quantities after flashover has occurred during a fire event. Carbon monoxide will combine readily with hemoglobin in the blood of a fire victim to form carboxyhemoglobin (COHb), which in sufficient levels will cause incapacitation (i.e., the loss of consciousness and the inability to move), followed by death. The most commonly used model for the prediction of carbon monoxide uptake in humans is the Coburn, Forster, Kane Equation (i.e., CFK Equation).

Currently, neither zone modeling codes nor FDS provide a means for assessing the effects on fire victims of carbon monoxide uptake. A user is able to predict the production and transport of the toxic gas throughout the model space, but further analysis must be completed in the post-processing of the model results.

This paper proposes a methodology for linking a carbon monoxide uptake analysis for victims of a fire with computer fire modeling. First, a standardized methodology for bridging the gap between data generated by computer fire modeling predictions and the use of those results for the analysis of carbon monoxide uptake in fire victims will be presented. Second, a case example of a post-fire reconstruction analysis utilizing the methodology will be explored.

by: Jason A. Sutula

“All we know is still infinitely less than all that remains unknown.” – William Harvey

Beginning each and every fire investigation is a unique experience. No two fire scenes are ever the same. As such, no fire investigator should feel comfortable jumping to conclusions as to the origin and cause of the fire immediately upon their arrival on the scene. As mentioned in my post on the Scientific Method, data is the key to determining the origin and cause of a fire. The more data that is available to an investigator, the more likely it is that an accurate determination will be made. This is why it is extremely important for a fire investigator to understand what resources are available.

In many cases, experience and training in fire investigation can only take the investigation so far. Eventually, the entire determination or outcome of a case may hinge on the ability of the investigator to explore the unfamiliar territory of a physical process that they do not understand. To overcome this, an investigator must be prepared to research the phenomenon in question.

The links posted on this blog are designed to help along these lines. One of the most helpful in researching fire phenomena is sponsored by the Building and Fire Research Laboratory (BFRL), which is a division within the National Institute of Standards and Technology (NIST). BFRL supports a website called, “Fire on the Web,” which can be found at Fire on the Web contains information on a host of topics including fire test data, fire modeling software, and links to NIST’s publication directories. The information found here can provide that extra insight for a fire investigator to more fully understand the fire phenomena associated with a particular fire scene and the resulting investigation.

by: Jason A. Sutula

I strongly recommend reading the book “The Demon-Haunted World: Science as a Candle in the Dark” by Carl Sagan to anyone serious about utilizing the Scientific Method in fire investigation. Sagan always was a gifted writer who had the ability to take very complex ideas and break them down into manageable and much more easily understood segments. “The Demon-Haunted World” is no exception to the rule. In this book, Sagan presents the Scientific Method in a fashion that is easy to grasp. Additionally, he provides several practical tools that can be carried throughout our professional (and personal) lives to think more critically and skeptically about the world around us. These tools should and can be routinely used in the realm of Fire Investigation.

From a reference more familiar to many of us in the field of Fire Investigation, NFPA 921 – Guide for Fire & Explosion Investigations provides a very clearly defined section on what the Scientific Method is and how it is used during a fire investigation. In general, NFPA 921 requires that a systematic approach is used to come to a determination of both the origin and cause of a fire. The systematic approach that is recommended is the Scientific Method.

Various forms and flow charts of the Scientific Method exist in greater and lesser detail. The basic concepts of the Scientific Method do not change though, no matter how the “blueprint” is presented. The Scientific Method always starts by recognizing that a need exists (i.e., a fire has occurred and we need to figure out where and how it started, if possible). Once we have recognized and identified our problem, the problem must be specifically defined. Thus, if we want to focus on determining the origin of the fire (which should always be determined BEFORE the cause), we must decide that this is our problem. Next, we must collect all of the available data in the case. An example list of what this data is and where it comes from could potentially encompass an entire post all by itself, but a few examples are eye-witness statements, surveillance video, fire service personnel statements, fire department reports, police reports, etc. After we have exhausted all avenues of potential data, the data must then be analyzed. Hopefully, the data is sufficient to develop a set of possible hypotheses that can account for the resulting data. Once these hypotheses (or a lone hypothesis in rare cases) are developed, they must be tested. Testing can range from very complex to very simple. Comparing the developed hypotheses against the fire department report or pieces of physical evidence found at the scene may be enough to decide that certain hypotheses are just not possible. The Scientific Method must be thought of as an iterative process, though, where each hypothesis is tested until it is verified, ruled out, or a determination is made that there is insufficient data to verify it or rule it out.

Using the Scientific Method while performing fire investigation has taken on even more importance in the last decade. This is due in part to a much more fundamental and better understanding of fire phenomenon and fire dynamics as well as several landmark rulings in the court system. In particular, Daubert v. Merrel Dow Pharmaceuticals has established that the court is the “gatekeeper” in determining whether or not an expert in the field has used proper methodology when arriving at his/her conclusion. While this new precedent specifically affects cases tried under federal rules, a fire investigator would be prudent to conduct their investigations using the Scientific Method with the belief that their methodology could be under scrutiny based on Daubert.