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OCR for page 11
2
FIRE MODELING
BACKGROUND
Over the past
decade numerous
computer-solved
theoretical programs
have evolved for
modeling a fire in an
enclosure (Figure 2-1~.
The growth in activity
has proceeded from
the original treatment
of a single chamber
with a single event
(Miller, 1985a), to the
more recent
undertaking of a
multicompartment
arrangement (including
corridor linkage) for a
single-story structure
(Jones, 1 985), to FIGURE: 2-1. Schematic of the fire processes in a room. Sourec: Quintiere, 1988.
efforts at treating a
multicompartment, multistory structure. Very little of this effort is aimed at mass transit
vehicles and none at such specific problems as fire in mass transit vehicles in a lengthy
TRANSFER ~
\~7 tA
~ MIXING I
RADIATION ~ _
TURBULENT'
MIXING
~ ~ ~ . - ~ - ~ ,~ ~ , AO '~
~ aim ,~oO\)G~< :
>?) ~ ;' ~ — —-'
...... .r~
... ·, _
.~;7'
P. ~ — _
—~ AIR
_
FUEL
'A LOW SPEED
BUOYANT FLOWS
11
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12
tunnel. Virtually all of the modeling is aimed at compartments whose length, width, and
height are comparable, so that an essentially two-dimensional point of view suffices.
However, the great length of a typical transit vehicle car (relative to its width and/or
height) introduces important ~three-dimensional" aspects to the thickening of a ceiling
contiguous layer comprised of hot vitiated air, unburned combustible vapors, and sooty
smoke. Because of the absence of immediate applicability to the mass transit vehicles of
interest' and because many recent reviews have been undertaken elsewhere (Quintiere, 1984;
Bukowski, 1985; Mitler, 1985b), attention here is concentrated on a nonexhaustive critique
of these models.
The mathematical fire models are of a number of types requiring different levels of
computer capability for the solutions of equations. The deterministic types include field
models that divide space into small elements and require greater computational resources to
solve the pertinent partial differential equations for the flow of hot buoyant gases derived
from the burning of fuels. Zone models, which require less computer resources, divide the
space into conceptual zones or control volumes (e.g., upper layer, lower layer, plume or
several plumes). The presumption is adopted that within a given zone the temperature, gas
composition, smoke concentration, etc., are relatively uniform spatially, but vary with time
(Bu~nick and Walton, 1986; Quintiere, 1988~.
The
· —
generic scenario
(Lyons, 1985) is
an unwanted
ignition within
an enclosure that
leads to a
fire-sustained,
turbulent,
entraining
buoyant plume
(Figure 2-2~.
This plume
transports masse
momentum, ant!
energy from a
lower layer of
coo! ambient air
to an upper
well-mixed
(homogeneous)
layer of hot,
gaseous, sooty
fluid. The hot
upper layer and
plume convey FIGURE 2-2. Conceptualisation of a two layer cone model. Source: Lyons, 1986.
heat by radiative
transfer to maintain pyrolysis of the already-burning objects and to warm other objects that
may be raised to their (prespecified) ignition temperatures. Actually only flat objects (as
ZONE-TYPE COMPUTER MODELS
-'.':'.,,:.~.'`~2.~.~' I.'' '"'a
~ ; .· ~ ;: ..'. UiiER HEATED LAYER , ~ - , ,. I , . ` . · ,.; , , ., ~~'
~'2:'2~'';~
~.e', .'.' .:,:
LOWER
COOLER
LAYER
G;:2 ' r
I'.
..r
it-]
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13
to
opposed to vertically distributed objects) are treated satisfactorily. There is also heat
transfer by convection and radiation to the ceiling and to the upper walls exposed to the hot
upper layer. Despite these losses from the upper layer, it is conceivable that the hot
homogeneous contents of the upper layer could ignite, owing to coexistence of oxygen and
some unburned fuel vapor. But this consideration is not usually regarded in existing models;
rather, a key output is the prediction of the time to ignition of easily ignitable objects on
the floor such that multiple plumes arise in the compartment. In the presence of multiple
plumes, the height of the interface between the upper and lower layers (another key output
of the model) decreases more rapidly in time, and there is enhanced low-level entrainment
into the buoyant columns. In flashover, the height of the interface decreases very rapidly to
near the floor. Any occupants would be immersed in hot, oxygen-depleted, smoky gases.
Escape of occupants after flashover would be an exceptional occurrence.
The discussion to this point has ignored the role of forced ventilation and of open
windows and/or doors, which may introduce coo} ambient air into the room. More
explicitly, once the thickness of the ceiling layer increases to the extent that the interface
(or thermocline) between the upper and lower layers lies below the top of a vent in a wall,
influx/efflux occurs owing to cross-vent pressure differential. Some exchange between
exiting and entering streams also occurs, such that some vitiated air is drawn into the cool
lower layer.
The solution is largely invariant of the position of the fire plume within the room.
It is hardly surprising that, within the broad latitude of the fire event, quite divergent
results would be collected from several different experimental apparatuses realizing the
event. Furthermore, only spatially averaged information from measurements can be used
for comparisons with the output from the computer models for purposes of experimental
validation.
FIELD-T=E MODELS
While a zonal mode! might be pressed into service to discern the time to activation of
a fire sensor or of a fire suppression system (e.g., sprinklers), there is motivation to consider
so-called field-type models that undertake description of fire spread, smoke transport,
convective-column properties, and so forth via a more spatially refined treatment. In
practice the alternative to the zonal mode! (which essentially requires that properties of the
fire be specified input) is taken to be the solution of coupled nonlinear partial differential
equations for conservation of mass, momentum, and energy on a refined mesh (Baum and
Rehm, 1984; Ku et al., 1976; Hwang et al., 1976; Yang et al., 19841. While frequent lip
service is paid to the possibility of an undertaking of a level of sophistication intermediate
to zonal and field models, limited intermediate effort seems to be under way. Special-
purpose, often field-type, models have been developed to be used (within or as a comple-
ment to a zonal approach) to calculate, for example, the thermal field in the ceiling, but
field-type models might also be used to describe the rate of efflux of combustible vapor
from a charring solid under a specified radiative flux.
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14
to
LIMITATIONS OF PRESENT COMPUTER MODELING OF FIRES
It should be emphasized that even the relatively advanced, single-compartment
models are rather crude. They require, as input, quantities that would be outputs from
more fundamental treatments. Among such quantities are flame temperature, flame
geometry, flame spreading, the ignition process, the fraction of chemically-released heat
that appears as radiation, the efficiency of burning (what fraction of pyrolyzed vapor is
burned, and, of that fraction what amount of carbon monoxide [CO] relative to carbon
dioxide is formed), etc. Other phenomena (e.g., ~hidden" fires within walls and breakage of
windows under heating of interior gases) are not included at all. As a consequence, there is
little in the way of unanticipated output from these models and more in the way of some
quantification within rather preset behavior. In particular, in the absence of detailed
chemical kinetics' any yield of toxicants would have to be specified as a predetermined,
perhaps time-varying' fraction of the mass of fuel burned. In fact, usually not even this
minimum is attempted for any toxicant except CO, and in general the level of CO is
particularly poorly predicted by the models (Miller, 1985b).
If a candidate theoretical model in the form of a computer code yields any
intuitively plausible results, the temptation exists to extend some credibility to other results
produced by the code. Often formulation of essential physical processes is compromised
because subgridscale phenomena (e.g., turbulent and radiative transfer and smoke
production) can be simulated only by adopting parameterizations in terms of gridscale
variables. Adequate parameterization may not exist for a given subgridscale phenomenon or
may not be known even if it does exist. Typically, the adopted parameterizations are
adjusted by the cocle developer or user unfit the computer results are consistent either with
the developer's intuitive expectations and/or with experimental data from a limited range of
parametric assignments. But such practices amount to mere curve-fitting unless the
parameterizations are then held invariant and the code is demonstrated to yield
experimentally verified results over a substantially broader range of parameter assignments.
Finally, quantification of even gridscale phenomena may be highly approximate (possibly
with uncertain error) because of inaccurate input of thermodynamic and/or physicochemical
Properties (e.g., of materials comprising the vehicle) and also owing to the complicated
character of a mathematical statement of the physics (e.g., three-dimensional flow may be
idealized as two-dimensional ~QW, more for reasons of convenience than for reasons of
demonstrable justification).
To reiterate, most models (e.g., Emmons, 1978) of fires in enclosures seek to
estimate only certain features, such as the height of the ceiling layer or the time from
ignition to flashover. The production and dispersion of toxicants and smoke often entail
chemical details about trace levels of gas species and particulates, details that typically are
not undertaken in existing computer models. Thus, existing models of fires in enclosures
usually do not attempt to describe the presence of toxicants, other than a limited attempt to
characterize CO concentration in the ceiling layer.
The increased detail (e.g., of a field-type model) does not necessarily imply
increased accuracy, especially since the thermochemical properties of so many materials are
so poorly known or documented (Rockett, 1984~. There is no way to establish credibility
for one code simply by comparing its output with that of another (perhaps more detailed)
code. Consistency establishes nothing more than effective equivalence of two
approximation and solution procedures for the particular cases examined. Validation
requires comparison of the output of a mode! against the results of a physical experiment or
(probably with less complete information) an unplanned accidental fire.
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15
Despite what might appear to be rather severe limitations, proliferation of modeling
methodologies, using the parameters of ignition, flame spread, heat release rate, mass
burning rate and transport of combustion products, have led to increased application of fire
modeling in the assessment of fire hazards.
CONCLUSION
Fire growth models exist that, although not perfect ire all respects, are perhaps
satisfactory for the purpose of estimating the rate of temperature increase, the development
of visual obscuration, and the concentration of combustion products as a function of time
for a fire scenario. The models may thus be used to provide input for hazard assessment in
characterizing the fire safety implications of alternative designs or of changes in materials
used.
REFERENCES
Baum, H. R. and R. G. Rehm. 1984. "Calculation of Three Dimensional Buoyant Plumes in
Enclosures." Combustion Science and Technology, Vol. 40, pp. 55-77.
Bu~nick, E. K. and W. D. Walton. 1986. "Computer Fire Models, Fire Protection
Handbook, 16th Ed., Section 21, Chapter 4, pp. 21-25through 21-30, National Fire
Protection Association, Quincy, MA.
Bukowski, R. W. 1985. "The Application of Models to the Assessment of Fire Hazard from
Consumer Products, Report NBSTR 85-3219. Center for Fire Research, National
Institute of Standards and Technology, Gaithersburg, MD.
Em mans, H. W. 1978. "The Prediction of Fires in Buildings," Seventeenth SYmDosium
(International) on Combustion, Combustion Institute, Pittsburgh, PA,
pp. 1101-1111.
Hwang, C. C., R. F. Chaiken, I. M. Singer ant! N. H. Chi. 1976. Reverse Stratified Flow
in Duct Fires: A Two-dimensional Approach," Sixteenth SYmDosium {In¢ernationall
on Combustion, Combustion Institute, Pittsburgh, PA, pp. 1385-139S.
Jones, W. W. 1985. HA Multicompartment Mode! for the Spread of Fire, Smoke and Toxic
Gases, Fire Safetv Journal, Vol. 9, pp. 55-79.
Ku, A. C., M. L. Doria and I. R. Lloyd. 1976. "Numerical Modeling of Unsteady Buoyant
Flows Generated by Fire in a Corridor, Sixteenth Svmoosium (international) on
Combustion, Combustion Institute, Pittsburgh, PA' pp. 1373-1384.
Lyons, ]. W. 1985. Fire, Scientific American Library, New York, NY.
Mitler, H. E. 1985a. "The Harvard Fire Modem, Fire Safety Journal, Vol. 9, pp. 7-16.
Mitler, H. E. l985b. Comparison of Several Compartment Fire Models: An Interim
Report,. NMSIR 85-3233, Center for Fire Research, National Institute of Standards
and Technology, Gaithersburg, MD.
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16
Quintiere, J. 1984. "A Perspective on Compartment Fire Growth, Com
Technologv, Yol. 39, pp. 1 1-54.
Quintiere, J. l9SX. "Analytic Methods for Firesafety Design,
pp. 333-352.
Rockett, J. A. 1984. "Data for Room Fire Models, Com
Vol. 40, pp. 137-151.
On
Technologv, Vol. 24
ustion Science
Tech nolnov
Yang, K. T., I. R. Lloyd, A. M. Kanury, and K. Satok. 1984. "Modeling of Turbulent
Buoyant Flows in Aircraft Cabins, Combustion Science and TechnoloeY, Vol. 39,
pp. 107-118.
Representative terms from entire chapter:
transit vehicles
