Reference

NAT'L INST. OF STAND & TECH NBS

PUBLICATIONS

AlllDb 034112

NBSIR 85-3219

The Application of Models to the

Assessment of Fire Hazard From

Consumer Products

Richard W. Bukowski

U.S. DEPARTMENT OF COMMERCE

National Bureau of Standards

National Engineering Laboratory

Gaithersburg, MD 20899

August 1985

QC ored by:

100 Consumer Product Safety Commission

ij^, lisngton, DC 20207

85-3219

1985

JJATI0NA1 BUREAU V QF STANDA?..: 3 \ LIBRARY

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NBSIR 85-3219

, , ,

, THE APPLICATION OF MODELS TO THE

ASSESSMENT OF FIRE HAZARD FROM

CONSUMER PRODUCTS

O' ’ ‘

Richard W. Bukowski

U S. DEPARTMENT OF COMMERCE

National Bureau of Standards

National Engineering Laboratory

Gaithersburg, MD 20899

August 1985

Sponsored by:

U.S. Consumer Product Safety Commission

Washington, DC 20207

U.S. DEPARTMENT OF COMMERCE, Malcolm Baldrige, Secretary

NATIONAL BUREAU OF STANDARDS. Ernest Ambler. Director

TABLE OF CONTENTS

Page

ABSTRACT ' 1

1. INTRODUCTION 1

2. APPLICATION OF MODELS 2

2.1 FIRE MODELS 3

2.2 HAZARD MODELS 4

2.3 RISK MODELS 4

3. MODELING TECHNIQUES 5

4. DISCUSSION OF AVAILABLE FIRE MODELS 7

4.1 SINGLE COMPARTMENT MODELS 7

4.2 MULTIPLE COMPARTMENT MODELS 8

5. REQUIREMENTS FOR ASSESSING HAZARD 10

5.1 COMBUSTION 11

5.1.1 FLAMING COMBUSTION 11

5.1.2 SMOLDERING COMBUSTION 12

5.2 TRANSPORT 13

5.3 EFFECT ON OCCUPANTS (TENABILITY LIMITS) 13

5.4 FIRE PROTECTION SYSTEMS/HVAC 15

5.4.1 MODELING FIRE PROTECTION SYSTEM 16

5.4.2 HVAC SYSTEMS 16

5.5 VALIDATION 17

5.6 MANAGING THE OUTPUT 18

6. DATA SOURCES 19

7. RECOMMENDATIONS 21

8. REFERENCES 22

TABLE 1. SINGLE COMPARTMENT MODELS 25

TABLE 2. MULTIPLE COMPARTMENT MODELS 26

FIGURE 1. INTERRELATIONSHIPS OF MAJOR COMPONENTS OF A

FIRE HAZARD MODEL 2 7

iii

THE APPLICATION OF MODELS TO THE ASSESSMENT

OF FIRE HAZARD FROM CONSUMER PRODUCTS

Richard W. Bukowski

Center for Fire Research

National Bureau of Standards

Abstract

The differences among models of fire, fire hazard, and fire risk are

described. The use of field, zone, and network models for fire hazard assessment is discussed. A number of available single and multiple compartment

models are described. Key considerations with respect to the use of the

current models by the Consumer Product Safety Commission for hazard assessment

from upholstered furniture and mattress fires is presented. Modifications

necessary to improve the capability of these models for hazard assessment are

identified. Model validation, output presentation, and data sources are

discussed. Recommendations on specific models for the sponsor to consider for

further study and use are provided.

Key words: computer models; fire models; hazard assessment; mattresses;

toxicity; upholstered furniture

1. INTRODUCTION

Over the past decade, the field of fire modeling has progressed to the

point that quantitative predictions of fires in buildings can be made to an

accuracy which is useful for engineering purposes. Over the past two years,

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the Center for Fire Research (CFR), National Bureau of Standards (NBS), has

been working on the application of fire modeling techniques to the prediction

of the hazard to occupants from building fires. The framework of the CFR

Program [1]* and the application of these techniques to specific, product

related hazard analyses for upholstered furniture [2], and plenum cables [3]

have recently been published.

Since the mission of the Consumer Product Safety Commission (CPSC) is to

protect the public from hazards associated with products, the potential usefulness of these techniques for the evaluation of fire, and particularly

combustion toxicity hazards associated with accidental fires involving combustible consumer products is apparent. Thus, CPSC contracted with CFR to review

the current state of fire and hazard modeling and to recommend specific models

which might be currently useful by CPSC for this purpose and to identify

modifications to these models which would improve their usefulness.

2. APPLICATION OF MODELS

A model is any set of equations which mathematically represents some

physical process. Thus, a model describes what is likely to occur as the

process being modeled proceeds. The widespread availability of powerful

computers has resulted in the development of models for many complex

phenomena. For example, climate modeling forms the basis for most weather

predictions done today. These climate models are made up of mathematical

expressions for such forces as solar heating and the earth's rotation which

cause the development and movement of weather patterns across the earth. In a

lumbers in brackets refer to the references at the end of this report.

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similar fashion, fire models contain equations which describe the processes of

combustion, heat transfer, and fluid flow produced by a fire within a specific

geometry.

2.1 Fire Models

Fire models predict the environmental conditions within one or more

physically bounded spaces as a result of fire contained therein. They predict

how much heat, smoke, and gases are produced by the fire and how each of these

quantities is distributed through the building over time. Some important

points about fire models as they currently exist must be understood in order

to appreciate their capabilities and application.

Most current fire models have been developed for specific purposes such

as to describe a single phenomenon (filling of a compartment) or a specific

application (aircraft interior fires) rather than for general use. Fires

involve many highly complex phenomena and no single fire model describes all

of these phenomena to the same level of detail. Within a given model,

specific phenomena may be described empirically, semi-empirically , by partial

or complete physics, or may not be included. The level of detail included for

any specific process depends both on the level of technical understanding of

the process available at the time the model was written and on the specific

purpose for that model. Thus, a user must understand the individual model's

range of validity and how that applies to the purpose for which the model is

being used.

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2.2 Hazard Models

A hazard model is one which predicts the consequences of an exposure to a

specified set of conditions over time. Thus, a hazard model uses the information on the conditions produced by the fire over time from the fire model and

evaluates the impact of these conditions on that which was exposed. In most

cases, the hazard of interest is that to occupants of the building. But

hazard models could also be used to evaluate property damage as a result of

the fire.

Hazard is scenario dependent. That is, hazard must be evaluated for a

single, specified set of conditions involving a specific fire in a specific

building with a specific set of occupants and their associated physical

capabilities.

2.3 Risk Models

Risk models predict the cummulative threat posed by all possible

hazardous events (scenarios) weighted by their probability of occurrence.

Thus an event which is very hazardous but relatively unlikely to occur would

be similar in risk to an event which is less hazardous but more likely to

occur.

From the above, it can be seen that fire models form the phenomenological

base for hazard models, and hazard models for risk models. For engineering

purposes for the evaluation of potential impact or benefits of product design

changes, material selection, or other hazard migation strategies, hazard

-4 -
models would be the most appropriate. However, eventually, some consideration

of risk will have to be made. This is because changes which reduce the hazard

for one scenario may potentially result in increased hazard from some other

scenario. Depending on the probability of occurrence, the overall benefit

could be either positive or negative. An example of this might be that a

flame retardant which would reduce the hazard from flaming ignitions might

also promote the propensity of a material to smolder and increase the hazard

from smoldering ignitions. Depending on the relative probabilities of

smoldering and flaming ignitions for the product, the overall risk associated

with that product might be increased or decreased accordingly.

3. MODELING TECHNIQUES

There are three general categories of fire modeling techniques; field

models, zone models and network models.

Field models divide a space into a 1, 2, or 3-dimensional network of

relatively fine elements and, using the governing partial differential equations of the phenomena of interest, calculate the conditions in each element

as a function of time. These models provide very high resolution and detail

but are computationally intensive; a simple combustion problem in a single

compartment requiring a significant time on the largest super computer. Thus,

they represent an excellent research tool but generally are not as yet too

practical for problem solving.

Zone models divide each compartment into a small number of volumes,

including at a minimum an upper layer, a lower layer and a fire plume

-5 -
region. These models work well in the compartments nearest the fire where

stratified conditions exist because of the significant driving force of

buoyancy. The turbulence normally associated with fires causes mixing within

the layers which lead to conditions that are reasonably replicated by the

uniform layer approximation of the zone models. These models are more

computationally simple than field models and, given a numerical routine to

solve the equations, can run multiple compartment simulations in real time on

a mid-sized computer.

Network models assume that compartments are uniform in space. These

models can be used to solve problems involving very large numbers of nodes

(compartments) efficiently. At some distance from a fire, products are well

mixed and are driven by the now-dominant forces of HVAC, stack effect, and

wind. Network models are therefore well suited to the realm at some distance

from the fire source.

From this, it is clear that the most effective approach for treating the

problem at hand is to marry these three techniques into a hybrid model which

can provide the detail necessary for useful hazard predictions while maintaining practicality for problem solving. In fact, this is probably the only

approach with enough computational efficiency to be used for predictions in

large structures due to the large numbers of compartments therein. Thus, the

direction of the work at CFR in hazard model development is to use the zone

model for the near-fire compartments where buoyancy and stratification are the

key phenomena. This model would include field model-type elements in special

zones, as required (e.g. , the zone which represents the ceiling material,

where transient heat conduction requires a field equation analysis). Once

-6 -
beyond the distance where stratification is significant the network technique

will be used to map the distribution of products in the rest of the structure.

4. DISCUSSION OF AVAILABLE FIRE MODELS

In addition to the categories of field, zone, and network models which

relate to the number of spaces into which each compartment is divided for

solution, fire models can also be categorized as single compartment models or

multiple compartment models relating to the number of rooms in the structure

to be analyzed.

4. 1 Single Compartment Models

By far, most currently existing fire models are single compartment

models. Some of the more common single compartment models are shown in Table

1. Ihese models range from very simple such as ASET (Available Safe Egress

Time) [4] which is intended to estimate the upper layer temperature and

filling time for a fire in a single compartment, and C0MPF2 (Computation of

Post Flashover Model 2) [5] which calculates only post-f lashover temperatures

and flows, to Harvard V [6] and OSU (Ohio State University) [7] which contain

relatively complex phenomena and predict numerous aspects of a time dependent

room fire. The Cal Tech (California Institute of Technology) model [8] is a

filling model similar to ASET, and DACFIR (Dayton Aircraft Cabin Fire htodel)

[9] is designed to model a fire involving the seating of a commercial aircraft

over only the first 5 to 10 minutes after ignition.

-7 -
I

While each of these models has appropriate applications, only the Harvard

V and OSU provide sufficient detail for a rigorous hazard analysis. The OSU

code was developed by Smith at Ohio State University expressly for the purpose

of extending measurements taken in the OSU calorimeter (ASTM E906) to

compartment fire predictions. Thus, the utility of this model is generally

limited to cases where data from the OSU calorimeter is available on the

material in question. The Harvard code, however, is more general purpose and

will be more generally applicable. Currently, there are several versions of

the Harvard V Code available. These versions, identified as 5.1, 5.2, 5.3,

etc. represent modifications for the inclusion of extensions by specific

researchers. For example, 5.2 and 5.3 both contain vent mixing and

contamination of the lower layer not included in 5. 1. CFR is currently

working on the assemblage of a "standard” version of Harvard V containing all

applicable extensions. When completed and fully documented this will be the

model of choice for single room calculations, particularly when it is desired

to include combustion phenomena.

4.2 Multiple Compartment Models

Models which calculate the transport of energy and mass through multiple

compartments of a structure are a relatively recent development. The three

currently available are listed in Table 2. The Building Research Institute

(BRI or Tanaka) [10] and Harvard VI [11] models were published in 1983 and the

initial version of FAST (Fire and Smoke Transport) [12] was released one year

later.

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The BRI model can be used to predict the distribution of fire products in

an arbitrary number of compartments on multiple floors. It contains a relatively simple combustion algorithm for steady-state combustion. Ttoo major

drawbacks of this model involve the lack of vent mixing and a cumbersome

solution algorithm for solving the compartment to compartment transport.

The lack of vent mixing means that all energy and mass released by the

fire is retained in the upper layers of each compartment. Thus, temperatures,

smoke, and gas levels in the upper layer are over-estimated and the rate of

filling of each compartment is slower than would be experienced in real life.

The solution algorithm for transport is cumbersome because the user must

specify the order in which fire products will enter each compartment. For

compartments in a straight line this is obvious; but for complex geometries

this often leads to failures of the model in reaching a solution

(convergence).

Harvard VI is multi-compartment extension of Harvard 5.1. As with the

BRI code, Harvard VI does not currently contain vent mixing. In addition, the

current version of Harvard VI can only handle three compartments. The model

was initiated near the end of the Center for Fire Research Program at Harvard,

and was not completed prior to the retirement of Dr. Emmons. Dr. Morita from

Science University of Tokyo worked on Harvard VI during a one year guest

worker assignment at CFR. During his stay, he got the program running, but

there are still some subroutines which do not work. At present there is no

official released version of Harvard VI (although there is a report on the

model).

-9 -
FAST is the most widely distributed and used multi -compartment model.

FAST does contain vent mixing and has a reliable, robust equation solver which

does not require any unusual user setup. The first released version (version

16) can calculate any number of compartments on a single floor. Version 17,

scheduled for release in the fall of 1985 includes vertical shafts and thus

can handle multiple floors.

FAST has little combustion within it, requiring that the fire be entered

in terms of a mass loss rate, heat of combustion, and species yields. It

accepts this data in the form as produced by the furniture calorimeter [13] or

cone calorimeter [14]. Where more detailed combustion is needed as input,

such as multiple items burning, it is possible to use Harvard V to predict the

combustion phenomena and then enter the energy and species release rates

predicted by Harvard V into FAST for the remainder of the calculation.

Version 18 will include improved combustion, and the upholstered furniture

combustion model of Deitenberger [15] will be incorporated into a future

version of FAST. These changes will allow a broader range of applicability

for FAST in that it will be able to calculate the changes in burning rate and

species yields as a function of the surrounding compartments, as opposed to

its current "free burning" assumption.

5. REQUIREMENTS FOR ASSESSING HAZARD

The major components of a hazard assessment model are shown in Figure

1. Each of these components is currently being addressed in the CFR program

and exist in various stages of development.

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Details on the current status, capabilities, and limitations of the

component models shown in Figure 1 are beyond the scope of this report. The

following sections will discuss factors necessary for the current use of

models to assess occupant hazard from consumer products; particularly

upholstered furniture and mattresses.

5.1 Combustion

Within the hazard model, the combustion process represents the primary

source term. That is, it describes the release rates of energy, smoke, and

gas species. As shown in the left main block of Figure 1 and as discussed

earlier, the combustion process can be described as a specified fire using the

data produced by small- or large-scale burns of the product, or can be calculated using a combustion model. For the particular case of upholstered

furniture and mattresses, a considerable bank of data exist, largely from

CPSC-sponsored work at NBS. Since the bulk of this data was taken in conjunction with the development of the oxygen consumption calorimeters and since the

specified fire input to the model was tailored to accept the data from these

calorimeters, there should be no need to resort to the more complex procedure

of using the combustion model for hazard analysis involving these products

unless the scenario to be studied involves multiple items burning.

5.1.1 Flaming Combustion

Most of the data available in these product categories involves flaming

combustion. Significant quantities of small- and large-scale calorimeter data

are available on individual materials [16], fabric/filling combinations [17],

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mock-ups [18] and complete items [19]. Data from room experiments are also

available [20]. Most of the data, however, was taken under "free-burning"

conditions with adequate ventilation for complete combustion. Thus, the

ability to precisely model post-flashover release rates may currently be

limited. Design modifications to the cone calorimeter to allow the measurement of energy and species release rates under post-f lashover combustion

conditions have already been initiated.

5.1.2 Smoldering Combustion

Significantly less data are available on energy and species release rates

from smoldering combustion in upholstered furniture and mattresses. While a

large number of smoldering experiments have been conducted they have focused

primarily on the aspects of smolder propensity (ignition probability) and have

not involved the key analytical measurements necessary to specify the energy

and species release rates. Since in the case of smoldering, radiation (which

does not scale) is not important, the data necessary to describe the process

can be readily obtained through bench-scale experiments. Simply running a

cigarette ignited crevice mock-up test (as used by the state of California) in

the cone calorimeter without any externally applied flux would provide the

necessary data.

The most difficult aspect of modeling smoldering combustion in either

upholstered furniture or mattresses would involve predicting the transition

from smoldering to flaming. Since the trigger mechanism is not understood it

is not currently possible to predict its occurrence with confidence. Thus,

the best that one could do would be to (somewhat) arbitrarily select a

transition time based on experience.

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5.2 Transport

Version 16 of FAST, can be used to predict the distribution of energy and

species throughout multiple compartments on a single floor. Version 17, to be

released this fall, includes a vertical shaft allowing multi-floor calculations. This shaft is described as a tall room in which an upper layer forms

and fills the compartment in the same manner as other compartments are

modeled. While this is a good approximation for open shafts such as elevator

or utility shafts, considerably more detail must be included before stairwells

can be adequately modeled. Since we assume that the initial CPSC focus will

be on residential occupancies, this should not pose a major problem for the

present. Of particular importance to this issue is the fact that a two story

test facility is currently under construction in building 205 which will

simulate a townhouse, complete with stairway. With the addition of this

facility and the research planned for it, studies of f loor-to-f loor transport

in such a structure will be forthcoming along with the necessary revisions and

improvements to the model to better describe these phenomena.

5.3 Effect on Occupants (Tenability Limits)

Most researchers agree that processes of biological response are less

exact and understood than the physical sciences. Thus the methods currently

available to address exposure-response are crude. Initial efforts (e.g.

,

as

currently provided in FAST) involve the definition of critical concentrationtime products using the NBS toxicity protocol. The model calculates the mass

concentration of combustion products in each layer (for each compartment) as a

function of time by distributing the fuel mass lost among the compartments and

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dividing by the layer volume. This distribution is a function of the mass

flow rates through the interconnected volume, driven by the buoyancy of the

fire gases. The ratio of the time integral of this mass concentration to the

critical concentration-time product is defined as the fractional lethal dose

(FLD).

While this provides a starting point, it is insufficient in the long term

since it does not describe such important factors as the cause of the observed

effect, variations in uptake rate as a function of activity, or the effect of

a varying concentration of individual species components which may change with

time or distance from the combustion site due to reaction or loss to surfaces.

Additionally, animal experiments conducted to date have not clearly demonstrated how sublethal effects such as incapacitation and exposure to irritants

can be reliably included in the predicted exposure-response. These are

clearly important factors for which some algorithms must be developed.

To try to address these issues, CFR has engaged in studies of the

exposure-response of animals to a number of the primary toxic species,

individually and in combination [21]. Species studied include carbon

monoxide, carbon dioxide, hydrogen cyanide, reduced oxygen, and hydrogen

chloride (being studied at SwRi with respect to both lethality and incapacitation on a grant). Simultaneously, Japanese researchers have been studying

these and a few additional gases with incapacitation as an end point [22,23].

At this time, considerable data has been generated and its analysis has

resulted in the development of some mathematical expressions based on

empirical correlations to these data. While such empirical correlations will

again be valuable as an interim step, it is recognized that the final method

-14 -
must include kinetic uptake models which include the effect of activity on

respiration rate, uptake, elimination, and metabolic changes in absorbed

toxicants which impact on the eventual results of the exposure.

Another portion of the exposure-response element is that of the

evacuation process and the behavioral aspects of occupants during this

process. In this area at CFR, Alvord has published an evacuation model for

large buildings [24]. This model can be used to predict the period of time

any occupant spends in any compartment and thus provides input necessary along

with the concentration-time history provided by the transport model to obtain

exposure-dose.

Working in conjunction with or to be included within the escape and

rescue model is a decision/behavioral model under development by Levin. This

will model certain aspects of typical human behavior in fire situations such

as the response to initial, ambiguous cues concerning the fire and the

tendency of males to investigate before taking escape actions. The model also

includes such factors as the need to rescue infants and to assist the elderly

or handicapped individuals.

5.4 Fire Protection Systems/HVAC

The ability to model the operation of fire protection systems such as

detectors and sprinklers or smoke control systems is an important factor in

hazard analysis since it impacts on the notification aspect (and thus the

point at which evacuation begins), and on the potential to control both the

fire and the generation and spread of its products. In addition, HVAC systems

- 15 -
can be a factor in mixing within a compartment and as a distribution path

within large buildings. Thus, these systems need to be included in the

overall hazard modeling.

5.4.1 Modeling Fire Protection Systems

Currently, it is possible to predict accurately the operation of heatactivated devices (heat detectors and sprinklers) as a function of predicted

conditions in the room of origin [25]. Estimates of the operating times of

smoke detectors as a function of soot mass concentration or number concentration can be made with less accuracy for optical and ionization types,

respectively [26].

Modeling the extinguishment process by sprinklers is not as advanced and

may not be practically achieved for a few more years. Work on this is ongoing

at NBS, Mission Research, Inc., and Factory Mutual Research Corporation in the

U. S.

5.4.2 HVAC Systems

Currently, the transport models do not include forced convection either

as a source of mixing or as a distribution path. For residential occupancies

(small structures) this should not be a major drawback. For a larger

structure, both factors need to be addressed and work on them is ongoing. We

expect, within one year, to include a convection heater within a room to

address the inter-layer mixing phenomena produced by it. Longer term research

is needed before inclusion of HVAC systems as a transport path can be

accomplished.

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5.5 Validation

In order to be useful in a practical sense, models must be validated.

That is, we must be able to establish the statistical accuracy of the

predicted quantities. Ibis requires much more than simply making direct

comparisons with selected experimental results. Thus, CFR, in conduction with

the Center for Applied Mathematics (CAM) of the National Bureau of Standards

has established a project to develop techniques to be used for this purpose.

A summary report on validation was recently published by Davies [27], and a

report on comparisons of FAST to a series of gas burner experiments in two and

three room configurations will be published in the fall of 1985.

Interestingly, the ease of validating a model against test data is in

many ways inversely proportional to the complexity of the modeling technique

used. That is, comparisons are most direct for field models since they

produce values of physical quantities at a specific point in space which

corresponds directly to the location where the quantity was actually measured

in an experiment. Zone models, on the other hand, produce what corresponds to

a bulk average value within a layer. The average must be derived from experimental data by averaging some number of measured values within a layer which

is continuously changing in volume. Since the measurements are taken at fixed

points, one must determine according to an operational definition of layer

interface location (which itself must be applied to the data) when they are

within one layer or the other. Differences between measured and predicted

values might be attributed to the poor quality or accuracy of the data, the

paucity or low frequency of the data, the somewhat arbitrary definition of

layer interface location, the poor performance of one or several of the

- 17 -
predictive algorithms which make up the overall model, or a combination of

these. This is not to say that model validation cannot be accomplished, but

only that it represents a complex problem.

5. 6 Managing the Output

The output produced by models is in much the same form as data from

large-scale fire experiments. That is, they give temperatures, flows, smoke

densities, gas concentrations, radiant flux, etc. at fixed time intervals over

the course of the simulation. The difference lies in the fact that fire

experiments are expensive and time consuming to run, so their number is

generally limited to a few, carefully selected scenarios.

Model runs, on the other hand, are easy to set up and inexpensive to

produce, so the limitation with models is the ability to analyze and understand the large amount of data which is so readily available. Thus, it is

critical that the models be provided with the capability of presenting their

data in a way which is more easily understood, consistent with the purpose for

which the model is being used.

Many applications will involve quantitative comparisons among numbers of

model runs where parameters of interest have been varied. Here, general

graphic techniques where X-Y plots of predicted variables can be presented

from one or more runs on a single graph would be useful.

Such a capability is provided for FAST with a program called Fastplot

(described in the appendix of ref. 12). For a more qualitative understanding

- 18-
of what would happen throughout an entire facility (especially a complex one)

for a given set of conditions, this kind of presentation may not be appropriate. The large number of plots would lead to a confusing and unclear

picture of the sequence of events.

To address this latter problem, we are developing a computer graphic

technique which presents the information provided by the model in a two- or

three-dimensional pictorial format along with graphical or tabular presentation of key quantities. This pictorial representation includes color coded

hazard information which is also keyed to the data to show the relative

contribution of a given parameter to the hazard condition present. In this

way, key information is presented to the user in an easily understood manner

similar to watching an experiment. Critical events can be noted during the

graphical presentation and analyzed later by using the data graphics routines.

With the evacuation sub-model, the graphics output can include occupants’

progress displayed along with the environmental conditions to show either

successful evacuation or the time, location, and condition which ultimately

prevents escape. Mitigation strategies are then apparent to delay the onset

of the limiting condition sufficiently to allow successful evacuation.

6. DATA SOURCES

The compilation of available data necessary to run the models and the

overall hazard analysis is a critical part of the program. Gross at CFR has

prepared a "pilot" data base report [28] which includes data on common

construction materials and references to data on fuels. With this report as

an example, CFR intends to solicit the cooperation of industry in the

- 19-
I production and contribution of data on their products in the proper format for

use in modeling. With specific regard to upholstered furniture and mattresses

as stated earlier, the bulk of the data has been produced recently in oxygen

consumption calorimeters. Other test methods do not present data in a form

compatible with the models. Therefore, a considerable amount of historical

data is not directly usable. Since large amounts of data are necessary to

handle the general problems, it is not feasible that CFR or any other single

organization can produce this amount of data. This is the reason why the

cooperation of industry will be necessary in order to compile the amount of

data in the proper form. Our experience to date in discussing this with

industry is that they are willing to cooperate and expend the resources necessary to accomplish the goal. Certainly, CPSC can be a key factor in fostering

this industry cooperation.

Once compiled, CFR intends to catalog the data in two forms. The first

will be a hard-copy catalog containing all of the information in a generic

form. Second, a computer data base will be generated which will facilitate

access to the data by modelers. Eventually, it is hoped that an "expert

system" can be developed which will not only access all available data but

will help in the selection of the most appropriate data for the problem at

hand. CFR is currently developing capabilities in the expert system technology and is obtaining the necessary hardware and software to develop such a

system.

-20 -
7. RECOMMENDATIONS

Based on the current state of technology, it is felt that the

capabilities exist to conduct product-related hazard analysis using predictive

fire models. This is particularly true for the focus of CPSC on upholstered

furniture and mattresses where a significant data base exists in the form

necessary for use of these models. Currently, the most appropriate model to

use for this is FAST, with Harvard V where the specified fire needs to be

replaced with the combustion model. In addition to the state-of-the-art

technical capabilities of these two models the fact that they are both the

subject of ongoing improvement and support is a critical factor in their

recommendation. Also, the further development of FAST, in particular, will be

for use in hazard (and risk) assessment modeling as opposed to general fire

modeling application such as Harvard VI or the BRI model.

Since the principle focus of the CFR program in developing hazard and

risk modeling techniques involves the application of these techniques to

materials and products questions, continued CPSC financial support will be

leveraged with the substantial CFR investment and the related work sponsored

by other agencies and industry. In addition to assistance in refining the

capabilities of these techniques, CPSC financial support will assure that the

specialized needs of CPSC, particularly as to the modifications made to the

models to improve performance, will be considered and addressed within this

overall program. The now-operational fire simulation laboratory will assist

in the transfer of this technology to CPSC personnel without the current need

for hardware expenditures. Following training in their use, both FAST and

FASTPLQT can be run by CPSC staff from the Tektronix 4010 terminal at Westbard

-21 -
Towers. As budgetary pressures in both agencies continue to increase, the

necessity and benefits of a continuation of cooperation in the development of

these techniques is essential. 8.

REFERENCES

1. Bukowski, R.W. and Jones, W.W. , Development of a Method for Assessing

Toxic Hazard, Fire Journal, Vol. 79, No. 2, 24-26, 28-29, 82, March 1985.

2. Bukowski, R.W. , Evaluation of Furniture Fire Hazard Using a Hazard

Assessment Computer Model, Fire and Materials, in press.

3. Bukowski, R.W., Toxic Hazard Assessment of Plenum Cables, Fire

Technology, in press.

4. Cooper, L. Y. , A Mathematical Model for Estimating Available Safe Egress

Time in Fires, Fire and Materials, Vol. 6, Nos. 3 and 4, 135-144, 1983.

5. Babrauskas, V., C0MPF2 - A Program for Calculating Post-Flashover Fire

Temperatures, NBS TN 991, National Bureau of Standards, Gaithersburg, MD,

June 1979.

6. Mitler, H.E. and Emmons, H.W. , Documentation for CFC V, The Fifth Harvard

Computer Fire Code NBS-GCR-81-344, National Bureau of Standards,

Gaithersburg, MD, October 1981.

7. Smith, E. and Satija, S. , Release Rate Model for Developing Fires,

presented at the 20th Joint ASME/AIC National Heat Transfer Conference,

August 1981.

8. Zukoski, E. E. and Kaboda, T. , TWo-Layer Modeling of Smoke Movement in

Building Fires, Fire and Materials, _4_, 17 (1980).

9. Smith, E. E. , Computer based hazard assessment using heat release rate

test data, Fire Safety Journal, Vol. 9, Nos. 1 and 2 (1985).

10. Tanaka, T. , A Model of Maltiroom Fire Spread, NBSIR 83-2718, National

Bureau of Standards, Gaithersburg, MD, August 1983.

11. Gahm, J.B., Computer Fire Code VI, NBS-GCR-83-451, National Bureau of

Standards, Gaithersburg, MD, December 1983.

12. Jones, W.W. , A Model for the Transport of Fire, Smoke, and Toxic Gases

(FAST), NBSIR 84-2934, National Bureau of Standards, Gaithersburg, MD,

September 1984.

-22 -
13. Babrauskas, V. , Lawson, J. R. , Walton, W. D. and TWilley, W.H. , Upholstered

Furniture Heat Release Rates Measured with a Furniture Calorimeter,

NBSIR 82-2604, National Bureau of Standards, Gaithersburg, MD 20899

(1982).

14. Babrauskas, V. , Development of the cone calorimeter - a bench scale heat

release rate apparatus based on oxygen consumption, Fire and Materials,

_8, 81-95 (1984).

15. Dietenburger, M. A. , Furniture Fire Model, NBS-GCR-84-480, National Bureau

of Standards, Gaithersburg, MD, November 1984.

16. Tewarson, A., Seale Effects on Fire Properties of Materials,

NBS-GCR-85-488, National Bureau of Standards, Gaithersburg, MD,

February 1985.

17. Babrauskas, V. , private communication.

18. Krasny, J. F. and Babrauskas, V., Burning Behavior of Upholstered

Furniture Mock-Ups, J. of Fire Sciences, Vol. 2, No. 3, 205-235,

May/June 1984.

19. Babrauskas, V., Upholstered Furniture Heat Release Rates: Measurements

and Estimation, J. of Fire Sciences, _1_, 9-32, Jan/Feb 1983.

20. Babrauskas, V., Upholstered Furniture Room Fires-Measurements , Comparison

with Furniture Calorimeter Data, and Flashover Predictions, J. of Fire

Sciences, 2_, 5-19, Jan/Feb 1984.

21. Levin, B. C. , Determination of the Toxicological Effects of Fire Gases,

Alone and in Various Combinations, for use in Toxic Hazard Assessment

Models, presented at the Third Canada-Japan-USA Trilateral Study Group

Meeting on Toxicity, Ottawa, Canada, October 1984, to be published.

22. Sakuri, T. , Incapacitation Test Using Several Pure Gases and Their

Mixtures, presented at the Third Canada-Japan-USA Trilateral Study Group

Meeting on Toxicity, Ottawa, Canada, October 1984, to be published.

23. Nishimarv, Y. and Tsuda, Y. , Study of Physiological Disorders in Rats

Caused by Poisionous Gases, presented at the Third Canada-Japan-USA

Trilateral Study Group Meeting on Toxicity, Ottawa, Canada, October 1984,

to be published.

24. Alvord, D. M. , The Fire Emergency Evacuation Simulation for Multifaraily

Buildings, NBS-GCR-84-483, National Bureau of Standards,

Gaithersburg, MD, December 1984.

25. Evans, D. D. , Thermal Activation of Extinguishing Systems, NBSIR 83-2807,

National Bureau of Standards, Gaithersburg, MD, March 1984.

26. Mulholland, G. and Jones, W.W. , private communication.

27. Davies, A. D. , Applied Model Validation, NBSIR 85-3154, National Bureau of

Standards, Gaithersburg, MD, January 1985.

-23 -
28. Gross, D. , Data Sources for Parameters Used in Predictive Modeling of

Fire Growth and Smoke Spread, NBSIR 85-3223, National Bureau of

Standards, Gaithersburg, MD 20899 (1985).

-24 -
Table 1. Single Compartment Models

Name Type

Harvard V.X^ Time dependent room fire

Cal Tech Smoke filling

DACFIR Aircraft, early time, state transition

OSU2 Time dependent room fire, OSU apparatus

ASET Smoke filling

C0MPF2 Post-f lashover temperatures

^Multiple fuel items

2Wall burning (primitive)

-25“
Table 2. Multiple Compartment Models

Harvard VI

BRI

FAST

Lower layer fixed at ambient conditions

Ttoo layer with vent mixing and lower

layer contamination

-26
INTERRELATIONSHIPS

OF

MAJOR

COMPONENTS

OF

A

FIRE

HAZARD

MODEL

-27

Figure
NBS-114A (rev. 2 -ec) U.S. DEPT. OF COMM.

BIBLIOGRAPHIC DATA

SHEET (See instructions)

1. PUBLICATION OR

REPORT NO. NBSIR-85/3219

2. Performing Organ. Report No. 3. Publ ication Date

August ly85

4. TITLE AND SUBTITLE

The Application of Models to the Assessment of Fire Hazard from Consumer Products

5. AUTHOR(S)

Richard W. Bukowski

6. PERFORMING ORGANIZATION (If joint or other than NBS. see instructions)

NATIONAL BUREAU OF STANDARDS

DEPARTMENT OF COMMERCE

Gaithersburg, Maryland 20899

7. Contract/Grant No.

8. Type of Report & Period Covered

Final

9.

SPONSORING ORGANIZATION NAME AND COMPLETE ADDRESS (Street. City. State. ZIP)

U.S. Consumer Product Safety Commission

Washington, DC 20207

10.

SUPPLEMENTARY NOTES

| | Document describes a computer program; SF-185, FIPS Software Summary, is attached.

11.

ABSTRACT (A 200-word or less factual summary of most significant information. If document includes a significant

bibliography or literature survey, mention it here) The differences among models of fire, fire hazard, and fire risk are described. The use of field, zone, and network models for fire hazard assessment is discussed. A

number of available single and multiple compartment models are described. Key

considerations with respect to the use of the current models by the Cosumer Product

Safety Commission for hazard assessment from upholstered furniture and mattress fires

is presented. Modifications necessary to improve the capability of these models for

hazard assessment are identified. Model validation, output presentation, and data sources are discussed. Recommendations on specific models for the sponsor to consider

for further study and use are provided.

12. KEY WORDS (Six to twelve entries; alphabetical order; capitalize only proper names; and separate key words by semicolons)

computer models; fire models; hazard assessment; mattresses; toxicity; upholstered

furniture

13. AVAILABILITY 14. NO. OF

PRINTED PAGES

|~~yl Uni imited

Q3] For Official Distribution. Do Not Release to NTIS 31 —

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