Posts Tagged ‘Computer Fire Modeling’

by: Jason A. Sutula

In a previous post on the topic of fire in space, I discussed the 1997 fire incident aboard the Mir Space Station. The case study still resonates today and provides valuable lessons for both NASA and the private commercial space companies on what fire hazards can be expected and need to be defended against in both manned and unmanned spacecraft missions. The single most important lesson that the Mir incident taught us is that the process of a fire burning in space is not intuitive.

Gravity, the driving force for natural fluid flow on the earth, cannot exert its influence on people, objects, and even fire when they are in a spacecraft circling the globe. In free fall around the plant earth, hot gases do not rise, and cold gases do not fall. The effects of buoyancy as seen in earth-bound fires are removed, which results in drastic differences in the appearance and structure of flames.

Fortunately, research in these areas has continued over the past few decades. Several on-going research studies are currently being conducted independently as well as in conjunction with NASA and the International Space Station in efforts to more fundamentally understand the fire hazards in microgravity environments.

One study by McGrattan, Kashiwagi, Baum, and Olson (McGrattan et al., 1996) demonstrated some strange fire behavior in microgravity conditions. For the study, a thin cellulosic fuel was suspended in a combustion test rig designed for a 2.2 second drop tower. The 2.2 second drop tower provided of a short amount of simulated microgravity conditions while the fire was burning. Ignition occurred in the middle of the sample and the flame was allowed to spread both vertically “upward” and “downward” at the same time. As a further variable, the researchers forced an air flow across the fuel sample at various speeds. The results were very surprising. The researchers initially expected the flame to propagate more rapidly in the downstream direction of the flow of air (think of how a camp fire will flare up when you blow on the coals). Instead, the fire burned more readily in the upstream or “opposed” direction of the flow, and the downstream flame died out quickly.

McGrattan et al. formulated a two-dimensional, time-dependent combustion model using computational fluid dynamics to better understand the phenomenon. Their computational study demonstrated that the flame moving in the opposite direction to the flow created an “oxygen shadow” in relation to the flame moving in the same direction as the air flow. This resulted in the downstream flame extinguishing since the flame moving toward the flow had already consumed all of the available oxygen!

In the embedded YouTube video above, Dr. Sandra Olson of the NASA Glenn Research Center, presents actual footage of the flame front burning as it is dropped in the 2.2 second drop tower. The full video is geared toward a younger, more kid friendly audience, so if you want to skip ahead, the microgravity combustion video and discussion begins at 0:51.

More research and computational studies will need to be conducted by NASA and commercial space ventures to better understand all of the fire hazard risks associated with microgravity environments. Fortunately, there are pioneers in this field laying the groundwork for fire safety in the final frontier.

McGrattan, K.B., Kashiwagi, T., Baum. H.R., and Olson, S.L., “Effects of Ignition and Wind on the Transition to Flame Spread in a Microgravity Environment,” Combustion and Flame, 106: pp 377-391, 1996.


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

Computer Fire Modeling Image

Now that some of the basics of what it means to be a fire investigator, how to become one, and knowledge requirements have been discussed in this blog, I want to present a case study of one of the more well-known investigations. This blog post may be substantially longer than my previous posts, but it is a great segue into some of the most critical issues facing the field of fire investigation and providing sound analysis as a fire expert. This is the story of Paul Camiolo.


A fire occurred in a residential structure in the early morning of September 30, 1996.  At the time of the fire, three people were in the residence, two parents (age 81, male and age 57, female) and their adult son (age 31).  The two-story house was composed of typical wood frame construction, and was built in approximately 1971.  The 1st floor included a living room and dining room in the front of the house and a family room, kitchen, and den/storage room with an adjacent bathroom in the rear of the house.  The 2nd floor had four bedrooms and one bath.  The master bedroom was at the head of the stairs on the second floor.

The family room, which was situated in the back, left portion of the first floor had a brick fireplace along the south wall and plywood paneling along the other three walls.  A substantial fuel load was present in the room at the time of the fire.  The fuel load included a three-cushion couch along the east wall, a two-cushion love seat along the west wall, and a lift-type recliner chair near the north wall by the doorway to the kitchen.  In addition, there were several small tables and a television.  The family room also had wall-to-wall carpeting over the original hardwood floor.

The fire was first reported via 911 by the Paul Camiolo at 4:30 a.m.  The first person to respond to the emergency call was a police officer who arrived at the scene at approximately 4:35 a.m.  Paul met the officer on the north side of the residence.  They proceeded to the south side of the house.  The officer reported that the large bay window on the southeast corner of the house had broken out and flames were venting through it.  The officer found Paul’s mother on the back porch at the southwest corner of the house.  Paul’s mother was found conscious and alert but suffering from burns to her hands, upper body, and head, including singed hair.

The first fire department units arrived at approximately 4:40 a.m. and the fire was declared under control at 5:03 a.m.  A fire department search of the house found Paul’s father unconscious in the bathroom in the right rear of the first floor near the back door exit to the porch. He was later pronounced dead. Paul’s mother was treated at the scene for burns and smoke inhalation and then transported to the hospital.  After initial treatment in the emergency room, she was transferred to the Burn Unit of a second hospital.  She ultimately died several months after the event from complications related previous health conditions and injuries sustained during the fire.  Paul was also transported to a hospital and was treated for burns and smoke inhalation and then released.

An autopsy performed on Paul’s father revealed that he had non-lethal burns to his head and upper torso and had suffered smoke inhalation. His cause of death was listed as smoke inhalation as a result of carbon monoxide poisoning.  Paul’s father’s carboxyhemoglobin (COHb), or the percentage of total hemoglobin in the form of COHb in the blood, was reported as 45%.  Incapacitation of a victim due to carbon monoxide poisoning typically occurs with COHb greater than 30 percent, and death usually occurs above 50 percent, though research has shown that both incapacitation and death can occur at lower percentages than those listed above.

Police and fire officials conducted a cause and origin investigation.  Their investigation determined that the fire originated in the family room in the left rear of the first floor.  Examination of the scene revealed heavy burn damage to most of the furnishings in the family room.  Heat and smoke damage was observed throughout the rest of the house with some fire extension into the kitchen and hallway adjacent to the family room.

Further investigation of the burn damage in the family room showed substantial damage to the couch, the love seat, and the lift chair.  The greatest damage to the couch was at the north end (toward the kitchen) with damage decreasing toward the south end (toward the fire place).  A similar damage pattern was noted on the love seat including greater damage high up on the back of the love seat.  The lift chair showed greatest burn damage to the east (toward the couch).  The wood paneling and studs behind the couch showed damage beginning behind the north end of the couch with a “V” pattern toward the south (fireplace).  In addition, the carpet in the center of the room was heavily damaged including a substantial area where the carpet and padding had been consumed in the fire, revealing the hardwood floor underneath.  The hardwood floor showed irregular discoloration in the center of the room where the carpet had been completely burned.  Because of the irregular pattern on the hardwood floor, samples were taken of the carpet, padding, newspaper (used between the padding and the hardwood floor to stop squeaks), and floorboards by fire investigators and sent to a laboratory to test for the presence of flammable or combustible liquids.

Paul’s Story

Paul was interviewed by investigators and gave the following account of the fire.  He stated that his mother had gone to bed at approximately 8:30 p.m. on the night of the fire.  His father subsequently went to bed at about 11:30 p.m.  Paul fell asleep watching television in the family room, woke up about 2:30 a.m., and went to his bedroom.  He was awakened at just before 4:30 a.m. by his father’s call for help from downstairs.  He went downstairs to the family room in response to his father’s call and discovered his father in his lift chair and his mother on the couch.  Upon entering the family room, he observed his mother attempting to pat out a small fire on the couch with her left hand.  He immediately went to the kitchen and got a pitcher of water.  When he returned to the living room, he attempted to extinguish the fire with the pitcher of water but found that it had little effect on the fire.  He advised his parents to get out and quickly retreated to the dining room to call 911.  While on the 911 call, he observed his parents traveling across the kitchen toward the den/storage room (in the direction of the rear exit) as the fire continued to grow.  Upon completion of the 911 call, he left the house through the front door.  After retrieving some sweatpants from his car (he was originally wearing only a pair of boxer shorts), he went to the rear of the house to meet up with his parents.  When he arrived at the back of the house neither of his parents were visible.  He opened the rear door and found his mother on the floor inside the door.  He dragged his mother outside onto the porch but could not enter further to find his father because of the heat and smoke.  He then went to the front of the house to await the arrival of emergency personnel.  He met a police officer and accompanied the officer around back to his mother’s location while advising the officer that his father was still in the house.  Eventually, the son was taken to the hospital and treated for his smoke inhalation and burn injuries.  The son suggested that the fire started as a result of his mother’s mishandling of smoking materials.

The Fire Investigator’s Hypothesis

Based on the burn damage to the residence and the Paul’s statement, the investigation focused on the area near the north end of the couch.  A lamp in this area was eliminated as a possible cause of the fire when an examination of the lamp and the adjacent outlet revealed no evidence of damage consistent with initiation of a fire.  The careless use of smoking materials could not be eliminated based on the burn damage, the statements of Paul, and evidence of other smoking materials throughout the 1st floor.  Other possible accidental causes of the fire were eliminated.  Initial investigation reports concluded that the fire was accidental as the result of careless smoking or improper disposal of smoking materials.

Some samples of fire debris were taken and sent to the state crime laboratory. The laboratory report showed that the samples of carpet, padding, and newsprint obtained from the room of origin were negative for common ignitable liquids, but the floorboards of the room of origin did test positive for trace amounts of weathered gasoline.  After receiving this report, the fire investigator changed his fire investigation report to conclude that the fire was intentionally set by Paul through the use of gasoline as an accelerant.  The motives given for the Paul’s actions were that he wanted to collect the assets of his parents, and that he no longer wanted to provide physical care for them.

The fire investigator developed the following account of the fire.  While Paul’s parents were upstairs in bed, he spread a gallon of gasoline on the carpet in the family room.  He ignited the room on fire, grabbed the cordless phone, ran to the front door, went outside and shut the door, and waited for his parents to wake up.  When they had been alerted to the fire, he called 911 from outside the house, held the door shut as his parents came down the stairs, and forced them to traverse the house to the rear of the building where they succumbed to smoke inhalation.

Computer Fire Modeling as a Means to Reconstruct the Fire

After examining the available data, it was determined that a computer fire model could be employed to determine which of the two competing scenarios was more likely to occur.  The lead fire investigator insisted that the fire was a result of Paul pouring gasoline in the family room, while Paul maintained that the fire was the result of an accident.

The geometry was first constructed in the fire model to form an accurate three-dimensional representation of the structure of the house.  After the geometry had been completed, the initiating fire scenarios were placed into the model.

The fire scenario in the accidental case was initiated by a small heat release curve placed on the couch in the family room simulating a small flaming match dropped on the couch.  The curve allowed a short fire exposure to ignite the surrounding couch structure and grow from that point.  The following figure depicts the resultant convective heat release rate modeled during this fire scenario.

The fire scenario in the incendiary case was initiated by an area of gasoline igniting, burning, and spreading quickly over a large surface area located on the floor in the middle of the family room.  The following figure shows the resultant convective heat release rate for the incendiary fire scenario.

Results and Discussion

The computer fire models produce various resultant quantities that can be analyzed for each scenario to determine which scenario is most consistent with all of the facts in the case. In the accidental case, the greatest interest is how the time to reach untenable conditions “fits” with the story provided by Paul.  In the incendiary story, again of greatest interest is how the time to reach untenable conditions “fits” with the story proposed by the fire investigator.  To decide which scenario is most consistent with either of the two proposed hypotheses, a quantity of data must be chosen to analyze such that a determination between the two scenarios can be made (i.e. temperature).

The above figure shows a temperature time curve for the conditions present within the family room during both the accidental fire scenario and the incendiary scenario.  When the couch is burning due to the accidental scenario, the fire grows relatively slow and the temperatures within the room increase slowly over time.  Conversely, the temperatures for the incendiary fire spike early in the fire and slowly subside.  This indicates a strong difference in the resultant fire conditions from each fire scenario.

Examining the accidental fire and the data, the question must be answered as to whether or not the temperature within the family room over a period of time is tenable enough for the Paul’s story to make sense.  Paul claimed that he observed his mother trying to pat out the fire with her left hand early on in the fire growth.  This is consistent with temperatures early in the fire caused by a small fire on the couch and is consistent with the burn injuries observed on his mother’s left hand.

Over the first 200 seconds of the accidental fire scenario, the temperature in the family room does not exceed 200 oC (392 oF).  It can be determined then, for the accidental scenario, that for the first three minutes of the fire, Paul would have had time to respond to his parent’s call for help, attempt to put the fire out with a pitcher of water, call 911, urge his parents to leave the residence, and exit the house through the front door.  The fire growth and tenability for this scenario is consistent with the story given by Paul.

The incendiary scenario created by the fire investigator indicated that Paul poured gasoline throughout the family room, lit the room on fire, and exited the building through the front door.  The temperature-time graph above clearly shows that Paul would have to have been moving very quickly to exit the residence without receiving significant burns.  The fire investigator also specified that the parents were on the 2nd floor asleep in their bed at the initiation of the fire.  In order to explain the parents being found where they were after the fire, the investigator states that the parents awakened at some point, moved downstairs, could not open the front door, headed to the back door, and were found near the rear of the structure without severe burn injuries.  For this to occur, the incendiary scenario must allow for temperatures cool enough to allow the parents to traverse the house over the course of a few minutes without being burned.  The results of the computer fire modeling as seen in the above figure indicate that conditions would have been severe enough to cause burns within the first 20 seconds after ignition.  The following figure shows the temperature versus time in the front hallway near the stairs and the front door.

The above figure also clearly demonstrates that the temperatures within the house quickly become untenable in the incendiary case. For the incendiary scenario, if the parents were indeed in their bed asleep when the fire was lit, they would have succumbed to the fire upstairs in their bedroom.


When conducting a fire investigation, reconstruction, and analysis, it is extremely important to gather as much data about the incident as possible.  In this case study, a computer fire model was used to compare two competing scenarios.  The majority of the data obtained, such as the burns on Paul’s mother’s left hand, the location of Paul’s mother and father within the residence during the fire, and the Paul’s lack of serious injury supported the Paul’s account of the fire.  Only the presence of gasoline found within the floorboards of the family room provided the fire investigator with weak evidence supporting an incendiary fire cause.  A qualitative analysis of each scenario using computer fire modeling determined that the incendiary scenario was implausible based on the resultant fire conditions within the residence.  It also led to the reexamination of the laboratory test results for gasoline.  Additional testing revealed that Lead was present within the gasoline found in the floorboard samples.  This discovery dated the gasoline to having been in the floorboards for over a decade prior to the date of the incident and eliminated the fire investigator’s proposed scenario.

This particular case study demonstrates just how powerful computer fire modeling can be when used in fire forensics. When computer fire modeling is combined with a thorough origin and cause analysis of a fire incident, it can be considered an extremely effective and powerful tool for fire investigators. This tool has the power to explore multiple fire scenarios quickly and cost effectively. Over the last decade, the use of computer fire modeling in forensic analysis has increased dramatically. With the continued rapid expansion of processing power, storage, and memory, the use of computer fire modeling will become a requirement for truly understanding what happened in a fire incident.

Without the use of computer fire modeling in this particular case, Paul Camiolo would have been falsely accused of killing his parents through arson, convicted, and punished for a crime that never happened. Few tragedies can compare to losing loved ones in an accident and then being accused of their murder. In this case, science prevailed.