Appendix C
Current Fire-Modeling Capabilities

As described in Chapter 3, computer models of ignition and flame spread are used to improve the understanding of fire scenarios, to evaluate small-scale material test results and provide an estimation of full-scale performance, and to aid in the development of fire performance goals. Fire-hazard assessment models are used to characterize the hazards associated with a fire event. These models use the results of the two general types of fire models—zone models and field models—along with submodels to account for the effects of detection and extinguishing systems and toxicity. This appendix describes current modeling capabilities.

ZONE MODELS

Zone models are often applied to buildings composed of several adjoining compartments, where each compartment is subdivided into control volumes or zones. All quantities of interest are uniform within each zone; conservation of mass, energy, and momentum is applied to each zone using algebraic representations or ordinary differential equations. The advantages of zone models are the low memory requirements, speed, ability to represent large structures, a priori assumptions, structured output, and ease of use. The need for a priori assumptions and the inaccuracies that may result can also be viewed as a disadvantage.

There are a number of zone models in use in the United States. One that is in wide use is the CFAST model developed by the National Institute of Standards and Technology (Jones, 1985; Jones and Peacock, 1988; Jones and Forney, 1990). This model is also used in fire reconstruction, particularly in litigation procedures. Other well-known zone models are BRI2 (Tanaka, 1977, 1978, 1980) developed in Japan and used extensively in risk analysis at Factory Mutual Research Corporation.

To gain an understanding of the state of the art of zone modeling, the capabilities of the CFAST model are:

  • multiple compartments (currently 15);

  • multiple fires (currently 16)—can be specified with "other" objects;

  • vitiated or free-burn chemistry in the lower layer, the upper layer, or in the vent flow;

  • correct chemistry—consistent production and transport of species;

  • generalized species (10) transport;

  • four-wall and two-layer radiation to be extended for the pyrolysis model;

  • four-wall conductive heat transfer through multilayered walls, ceilings, and floors in each compartment;

  • convective and radiative heat transfer applied to both inside and outside boundaries;

  • wind effects—American Society of Heating, Refrigeration and Air-Conditioning Engineers formula for wind with the National Oceanographic and Atmospheric Administration integral for lapse rate of the standard atmosphere;

  • fire plume and entrainment in vent flow (doors and windows only)—fire plume is split into entrainment in the lower and upper layer;

  • three-dimensional specification of the location of the fire and nonuniform heat loss through boundaries;

  • generalized horizontal vent flow (doors, windows, etc.)—up to three neutral planes; mixing between the upper and lower layers; vertical flow (through holes in ceilings and floors);

  • separate internal and external ambient (elevation, temperature, and pressure specification);

  • hydrochloric acid deposition;

  • mechanical ventilation—complex building structure: 5 fans, 44 ducts, 3-way joints; vertical ducts interact with both layers; and

  • heat transfer (conductive) through barriers.

The method by which these types of models achieve the speed and low memory requirements that make them attractive is through the use of a priori assumptions. These assumptions are input parameters to the model and are derived from empirical data. One of the concerns that needs immediate attention is to increase the confidence level and reliability of model predictions. These goals can be achieved in two ways. First, close interaction is needed between the modeler and experimentalist to identify the empirical data required by the model and to then create materials property databases that contain the needed information. Second, since small-scale experimental data are being used to "scale up" and predict actual fire behavior in models, it is imperative that modeling



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Fire- and Smoke-Resistant Interior Materials for Commercial Transport Aircraft Appendix C Current Fire-Modeling Capabilities As described in Chapter 3, computer models of ignition and flame spread are used to improve the understanding of fire scenarios, to evaluate small-scale material test results and provide an estimation of full-scale performance, and to aid in the development of fire performance goals. Fire-hazard assessment models are used to characterize the hazards associated with a fire event. These models use the results of the two general types of fire models—zone models and field models—along with submodels to account for the effects of detection and extinguishing systems and toxicity. This appendix describes current modeling capabilities. ZONE MODELS Zone models are often applied to buildings composed of several adjoining compartments, where each compartment is subdivided into control volumes or zones. All quantities of interest are uniform within each zone; conservation of mass, energy, and momentum is applied to each zone using algebraic representations or ordinary differential equations. The advantages of zone models are the low memory requirements, speed, ability to represent large structures, a priori assumptions, structured output, and ease of use. The need for a priori assumptions and the inaccuracies that may result can also be viewed as a disadvantage. There are a number of zone models in use in the United States. One that is in wide use is the CFAST model developed by the National Institute of Standards and Technology (Jones, 1985; Jones and Peacock, 1988; Jones and Forney, 1990). This model is also used in fire reconstruction, particularly in litigation procedures. Other well-known zone models are BRI2 (Tanaka, 1977, 1978, 1980) developed in Japan and used extensively in risk analysis at Factory Mutual Research Corporation. To gain an understanding of the state of the art of zone modeling, the capabilities of the CFAST model are: multiple compartments (currently 15); multiple fires (currently 16)—can be specified with "other" objects; vitiated or free-burn chemistry in the lower layer, the upper layer, or in the vent flow; correct chemistry—consistent production and transport of species; generalized species (10) transport; four-wall and two-layer radiation to be extended for the pyrolysis model; four-wall conductive heat transfer through multilayered walls, ceilings, and floors in each compartment; convective and radiative heat transfer applied to both inside and outside boundaries; wind effects—American Society of Heating, Refrigeration and Air-Conditioning Engineers formula for wind with the National Oceanographic and Atmospheric Administration integral for lapse rate of the standard atmosphere; fire plume and entrainment in vent flow (doors and windows only)—fire plume is split into entrainment in the lower and upper layer; three-dimensional specification of the location of the fire and nonuniform heat loss through boundaries; generalized horizontal vent flow (doors, windows, etc.)—up to three neutral planes; mixing between the upper and lower layers; vertical flow (through holes in ceilings and floors); separate internal and external ambient (elevation, temperature, and pressure specification); hydrochloric acid deposition; mechanical ventilation—complex building structure: 5 fans, 44 ducts, 3-way joints; vertical ducts interact with both layers; and heat transfer (conductive) through barriers. The method by which these types of models achieve the speed and low memory requirements that make them attractive is through the use of a priori assumptions. These assumptions are input parameters to the model and are derived from empirical data. One of the concerns that needs immediate attention is to increase the confidence level and reliability of model predictions. These goals can be achieved in two ways. First, close interaction is needed between the modeler and experimentalist to identify the empirical data required by the model and to then create materials property databases that contain the needed information. Second, since small-scale experimental data are being used to "scale up" and predict actual fire behavior in models, it is imperative that modeling

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Fire- and Smoke-Resistant Interior Materials for Commercial Transport Aircraft predictions be verified in large-scale experiments. For example, CFAST model predictions have been validated with experimental data from the Navy's fire research platform ex-U.S.S. Shadwell (Williams and Carhart, 1992). FIELD MODELS There are a number of field models available (Yang et al., 1984; Kou et al., 1986). A two-dimensional finite-difference field model of aircraft fires was developed to predict the movement of hot gases and smoke, as well as temperature and smoke concentration levels in the seating area of an aircraft cabin (Yang et al., 1984; Kou et al., 1986). Additional work included the development of a two-dimensional model of transient cooling by natural convection (Nicolette et al., 1985). This model utilized a fully transient semi-implicit upwind-differencing scheme with a global pressure correction. Baum and Rehm (1978, 1982a, b, 1984) have developed several field models for prediction of fires using time-dependent inviscid Boussinesq equations to simulate three-dimensional buoyant convection and smoke aerosol coagulation. There have been several field modeling projects to develop a computer model as a low-cost alternative to predict the spread of fire and smoke in enclosed spaces on naval vessels (Nies, 1986; Raycraft, 1987; Hauck, 1988). The similarity of the enclosed spaces of naval vessels to an aircraft interior makes these types of models valuable in evaluating the effectiveness of suppression systems and new designs in the prevention and control of fires in aircraft. Field modeling requires a large, fast computer with significantly more memory than is required in zone modeling. The accuracy of the solution depends on reducing the size of the control volumes, thus increasing the number of individual cells and the computing expense. Fire-Hazard Assessment Models Fire-hazard assessment models include both zone and field models for compartment fires, with submodels for fire endurance, activation of thermal detectors or sprinkler systems, generation of toxic gases, evacuation, and survival models. One of the early room fire models, HARVARD V, was developed in the early 1980s (Emmons, 1981; Mitler and Emmons, 1981). With this model, the user specifies room characteristics, technical information on objects contained in the room, and where the fire starts. The program calculates the fire growth, fire plume, the accumulated hot layer at the ceiling, and the outflow of hot gases and inflow of air after the smoke layer reaches the soffit. The program also calculates the radiation from the flame and hot layer to all of the objects. As each object reaches ignition temperature, the program ignites a new fire and new plume and models the additional hot gas going to the upper layer. As the flames and hot layer grow, radiation to the burning objects controls the rate of fire growth over their surface. When all the objects ignite, flashover has occurred. As the hot layer descends and envelops a burning object, the program calculates the reduction of airflow and the fire slows down. The program keeps track of the total mass and indicates when the fire of each object goes out. It also calculates the time at which a smoke detector in the room will sound its alarm. Two fire-hazard assessment models currently in use are HAZARD 1 (Bukowski et al., 1991) and FPEtool (Nelson, 1990). According to the authors, HAZARD 1 will calculate: the production of energy and mass (smoke and gases) by one or more burning objects in one room, based on small-or large-scale measurements; the buoyancy-driven ventilation, as well as forced flow, of this energy and mass through a series of user-specified rooms and connections (doors, windows, cracks, holes in ceiling or floor); the resulting temperatures, smoke optical densities, and gas concentrations after accounting for heat transfer to surfaces and dilution by mixing with clean air; the evacuation of a user-specified set of occupants accounting for delays in notification, decision making, behavioral interactions, and inherent capabilities; and the impact of the exposure of these occupants to the predicted room environments as they move through the building; and the time, location, and cause of each incapacitation or fatality. This model requires detailed knowledge of the fire scenario, including the geometry of the room(s), the location of the items that are burning, the combustion properties of those items, and also information on the exposed occupants (i.e., their initial location and characteristics such as age, and whether they have any disabilities or small children to assist). Therefore, the users of this model need to be familiar with fire physics and understand the limitations of the model. FPEtool is also a hazard assessment computer model (Nelson, 1990), but is less mathematically rigorous than HAZARD 1 and therefore takes less time to run. It will estimate ignition of exposed objects, smoke flows, gas concentrations and toxicity, pressures on a door from the fire and wind, actuation of detectors and sprinklers, and egress time of occupants. Table C-1 describes some limits inherent to HAZARD 1, FPEtool, and HARVARD V and which probably bracket the majority of limitations inherent within two-zone models. However, there is an incomplete understanding of the physical phenomenon involved in fires. Each limitation results in a computer code that may deviate from the correct representation of the fire physics that could introduce errors into

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Fire- and Smoke-Resistant Interior Materials for Commercial Transport Aircraft TABLE C-1 Characteristics and Limitations of Fire-Hazard Assessment Models Prediction HARVARD V HAZARD 1 FPEtool Ignition of primary fuel Specified by user Specified by user Specified by user Toxic gas release Calculated by program after rate of burning calculations Specified by user Specified by user Pyrolysis enhancement from smoke-layer radiation Calculated by program as is pyrolysis enhancement from secondary fuel fire radiation Specified by user Specified by user Fire growth Calculated by program Specified by user Specified by user Ignition of secondary fuel Calculated by program for all fuels in a compartment as user specified Planned Calculated by program Flames burning in door jets No Yes, but predicted from a limited set of experimental data No Plume entrainment Correlated to a limited set of experimental data Correlated to a limited set of experimental data, not based on fundamental fluid dynamics Correlated to a limited set of experimental data, not based on fundamental fluid dynamics Radiation transfer from smoke Calculated by program from hot smoke layer and flames to all specified items in compartment chosen by user Considers reasonable detail to floors, walls, and ceilings Considered in correlational approach for walls, reasonable detail to the floor Flashover Program calculates when all items ignite and when room reaches 600°C Oxygen starvation of fire is considered, otherwise same as preflashover treatment Calculated distinctly from preflashover burning. No plume calculations. Heat transfer from one room to another No Planned No Failure of wall or ceiling barrier No Planned No Activation of sprinkler/heat detector remote from fire No No No Unconsciousness/death based on toxic gases No Yes, prediction is based on N-gas model of four gases: CO, CO2, O2 , and HCN. Yes, prediction is based on N-gas model of four gases: CO, CO2, O2 , and HCN. Death based on atmospheric temperature No Yes, assumes instantaneous death when room temperature reaches 100°C. Yes, based on energy absorption by the body; data from literature   Source: HAZARD 1 and FPEtool—S. Deal and R. Peacock to B.C. Levin, personal communication, January, 1995.

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Fire- and Smoke-Resistant Interior Materials for Commercial Transport Aircraft the calculations. A further complication arises when limitations inherited from the numerical representation of one physical phenomenon compound, potentiate, or negate limitations inherited from the numerical representation of a second physical phenomenon. None of the fire-hazard models was designed to be applicable to aircraft interior fires since they model rooms rather than the cylindrical geometry of an aircraft interior. The models assume uniform smoke filling the upper layer with no time lag to compensate for the length of the corridor-like space and point-source fires of an aircraft. Also, the behavior and evacuation of individuals modeled in HAZARD 1 is from one-and two-family residences which is a very different scenario from the behavior and evacuation of people from an airplane. As in all fire models, the definition of the fire will depend on the materials that are burning. New materials will need to be characterized to obtain the data necessary to input into these models. Thus, their use to model an interior fire on an aircraft will take them outside their domain of applicability. REFERENCES Baum, H.R., and R.G. Rehm. 1978. The equations of motion for thermally driven, buoyant flows. Journal of Research of the National Bureau of Standards 83(3):297–308. Baum, H.R., and R.G. Rehm. 1982a. Computation of fire induced flow and smoke coagulation. Pp. 921–931 in Nineteenth Symposium (International) of Combustion. Pittsburgh, Pa.: The Combustion Institute. Baum, H.R., and R.G. Rehm. 1982b. Natural Computation of Large Scale Fire-Induced Flows. Paper presented at the Eighth International Conference on Numerical Methods in Fluid Dynamics, Aachen, West Germany, June 28–July 2. Baum, H.R., and R.G. Rehm. 1984. Calculations of three dimensional buoyant plumes in enclosures. Combustion Science and Technology 40:55–77. Bukowski, R.W., R.D. Peacock, W.W. Jones, and C.L. Forney. 1991. Technical Reference Guide for HAZARD 1 Fire Assessment Method, Version 1.1, Vol. 2. National Institute of Standards and Technology Handbook 146/II. Gaithersburg, Md.: National Institute of Standards and Technology. Emmons, H.W. 1981. The Calculation of a Fire in a Large Building. ASME Paper 81-HT-2 for meeting of the American Society of Mechanical Engineers, August 2–5, 1981. Hauck, R.R. 1988. Numerical Field Model Simulation of Full-Scale Fire Tests in a Closed Spherical/Cylindrical Vessel with Internal Ventilation. Unpublished master's and mechanical engineer's thesis, Naval Postgraduate School, Monterey, California. Jones, W.W. 1985. A multicompartment model for the spread of fire, smoke and toxic gases. Fire Safety Journal 9:55. Jones, W.W., and G.P. Forney. 1990. A Programmer's Reference Manual for CFAST, The Unified Model of Fire Growth and Smoke Transport. NIST Note 1283. Gaithersburg, Md.: National Institute of Standards and Technology. Jones, W.W., and R.D. Peacock. 1988. Refinement and experimental verification of a model for fire growth and smoke transport. Pp. 897–906 in the Proceedings of the Second International Symposium on Fire Safety Science, T. Wakamatsu, Y. Hasemi, A. Sekizawa, P.G. Seeger, P.J. Pagni, and C.E. Grant, eds. New York: Hemisphere Publishing Corp. Kou, H.S., K.T. Yang, and J.R. Lloyd. 1986. Turbulent buoyant flow and pressure variations around an aircraft fuselage in a cross wind near the ground. Pp. 173–184 in Fire Safety Science, Proceedings of the First International Symposium, C.E. Grant and P.J. Pagni, eds. New York: Hemisphere Publishing Corp. Mitler, H., and H. Emmons. 1981. Documentation for CFS V, the Fifth Harvard Computer Fire Code. NBS-GCR-81-344. Gaithersburg, Md.: National Institute of Standards and Technology . Nelson, H.E. 1990. FPEtool: Fire Protection Engineering Tools for Hazard Estimation. NISTIR 4380. Gaithersburg, Md.: National Institute of Standards and Technology. Nicolette, V.F., K.T. Yang, and J.R. Lloyd. 1985. Transient cooling by natural convection in a two-dimensional square enclosure. International Journal of Heat Transfer 28(9):1721–1732. Nies, G.F. 1986. Numerical Field Model Simulation of Full Scale Tests in a Closed Vessel. Unpublished master's and mechanical engineer's thesis, Naval Postgraduate School, Monterey, California. Raycraft, J.K. 1987. Numerical Field Model Simulation of Full Scale Fire Tests in a Closed Spherical/Cylindrical Vessel. Unpublished master's and mechanical engineer's thesis, Naval Postgraduate School, Monterey, California. Tanaka, T. 1977. A Mathematical Model of a Compartment Fire. Report 70. Ibaraki-ken, Japan: Building Research Institute. Tanaka, T. 1978. A Mathematical Model of a Compartment Fire. Report 79. Ibaraki-ken, Japan: Building Research Institute. Tanaka, T. 1980. A Mathematical Model of a Compartment Fire. Report 84. Ibaraki-ken, Japan: Building Research Institute. Williams, F.W., and H.W. Carhart. 1992. The Ex-Shadwell—Full Scale Fire Research and Test Ship. NRL Memorandum Report 6074. Washington, D.C.: Naval Research Laboratory. Yang, K.T., J.R. Lloyd, A.M. Kanury, and K. Satoh. 1984. Modeling of turbulent buoyant flows in aircraft cabins. Combustion Science and Technology 39:107–118.