User:Kilmer-san/Sandbox5

Methods
There are many different methods of defuzziciation available, including the following :


 * RCOM (random choice of maximum)
 * FOM (first of maximum)
 * LOM (last of maximum)
 * MOM (middle of maximum)
 * COG (center of gravity)
 * MeOM (mean of maxima)
 * BADD (basic defuzzification distributions)
 * GLSD (generalized level set defuzzification)
 * ICOG (indexed center of gravity)
 * SLIDE (semi-linear defuzzification)
 * FM (fuzzy mean)
 * WFM (weighted fuzzy mean)
 * QM (quality method)
 * EQM (extended quality method)
 * COA (center of area)
 * ECOA (extended center of area)
 * CDD (constraint decision defuzzification)
 * FCD (fuzzy clustering defuzzification)

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FIRE MODEL SANDBOX 2

NFPA 92B Standard for Smoke Management Systems in Malls, Atria, and Large Spaces 2005 Edition/Annex A Explanatory Material (1 of 2)
A.%.1.2: Caution should be exercised in using the equations to solve the variables other than the ones presented to the left of the equal sign, unless it is clear how sensitive the result is to minor changes in any of the variables involved. If these restrictions present a limit that obstructs the users' needs, consideration should be given to combining the use of equations with either scale or compartment fire models. Users of the equations should appreciate the sensitivity of changes in the variables being solved.

NFPA 5000® Building Construction and Safety Code® 2006 Edition / Annex A Explanatory Material (2 of 15)
Chapter 5 Performance-Based Option A.5.8.11 Documentation for modeling should conform to ASTM E 1472, Standard Guide for Documenting Computer Software for Fire Models, although most, if not all, models were originally developed before this standard was promulgated.

NFPA 101® Life Safety Code® 2006 Edition
ASTM E 1355, Standard Guide for Evaluating the Predictive Capability of Deterministic Fire Models, 2004. ASTM E 1472, Standard Guide for Documenting Computer Software for Fire Models, 2003.
 * Annex B Informational References

3.3.86* Fire Model. A structured approach to predicting one or more effects of a fire.
 * Definitions

NFPA 551 Guide for the Evaluation of Fire Risk Assessments 2007 Edition / Chapter 5 Selection and Evaluation: FRA Methods
Table 5.1.2.1: Category: Semiquantitative consequence method. Definition: Treats consequences quantitatively and likelihood qualitatively. Type of Output: Deterministic fire model outputs with qualitative representation of likelihood. Examples: Enclosure fire models for selected challenging fire scenarios

NFPA 805 Performance-Based Standard for Fire Protection for Light Water Reactor Electric Generating Plants 2006 Edition
3.3.14 Fire Model. Mathematical prediction of fire growth, environmental conditions, and potential effects on structures, systems, or components based on the conservation equations or empirical data.
 * Definitions:

C.3 Fire Scenarios.
 * Annex C Application of Fire Modeling in Nuclear Power Plant Fire Hazard Assessments (2 of 2)

C.3.1 General. A fire scenario is a description of all or a portion of a postulated fire event. This description can be either qualitative, quantitative, or a combination of the two. It can start before combustion occurs by dealing with the ignition and fuel sources, and it can carry through incubation, spread, detection, suppression, damage, and even cleanup and restoration activities. The description contained in a fire scenario can be used in a variety of ways to postulate the potential effects of the fire and to plan effective mitigation.

It is important to understand that the term fire scenario as used in this standard has a very specific meaning. It refers only to the quantitative input to and output from fire modeling calculations. Depending on the particular fire model utilized, input will include the following:

(1)     Physical values related to the enclosure geometry and boundary characteristics

(2)     Nature and location of ignition sources

(3)     Fuel arrays (initial combustible and intermediate combustibles)

(4)     Heat release and fire growth rates

(5)     Ventilation conditions

(6)     Target locations and damage characteristics

(7)     Detection and suppression device location and operating characteristics

(8)     Other data required for the model calculations

The output of interest will typically relate to target damage and the response of fire detection and suppression systems.

There are two general categories of fire scenario used in this standard:

(1)     Maximum expected fire scenarios (MEFS)

(2)     Limiting fire scenarios (LFS)

Scenarios in each category must be modeled for each fire area/zone being analyzed. It is usually necessary to model more than one scenario for each category because the interaction between various input parameters is not always intuitively obvious and usually cannot be determined without actually performing fire modeling calculations. The ventilation variable is a good example. Most nuclear power plants (NPPs) rely on manual operator actions of stopping and starting the safety-related ventilation system. Changing the one variable will generate a minimum of four separate cases, namely:

(1)     Supply and exhaust on

(2)     Supply and exhaust off

(3)     Supply on exhaust off

(4)     Supply off exhaust on

The total number of different scenarios required will depend on the combinations and permutations of the variables that need to be included to adequately analyze the specific conditions present. The engineer must keep in mind that due to uncertainties/approximations in the models, coupled with the variations inherent in the fire phenomenon itself, a series of bounding cases are needed in order to draw reasonable engineering conclusions.

C.3.2 Maximum Expected Fire Scenarios. The maximum expected fire scenarios (MEFS) are used to determine by fire modeling whether performance criteria are met in the fire area being analyzed. The input data for the fire modeling of the MEFS should be based on the following:

(1)     Existing in-situ combustibles in the fire area

(2)     Types and amounts of transient combustibles that industry experience and specific plant conditions indicate can reasonably be anticipated in the fire area

(3)     Heat release and fire growth rates for the actual in-situ and assumed transient combustibles that are realistic and conservative based on available test data and applicable fire experience

(4)     Ventilation within normal operating parameters with doors in the open or closed position

(5)     Active and passive fire protection features operating as designed

C.3.3 Limiting Fire Scenarios. The limiting fire scenarios (LFS) are ones that result in unfavorable consequences with respect to the performance criteria being considered. In essence, the output for the LFS calculations is obtained by manipulating the fire model input parameters until consequences are obtained that violate the damage limits established. Thus, the LFS can be based on a maximum possible, though very unlikely, value for one input variable, or an unlikely combination of input variables. The goal of determining an LFS is to be able to analyze the margin between these scenarios and those used to establish the maximum expected fire scenario (MEFS). The values used for LFS input should remain within the range of possibility, but can exceed that determined or judged to be likely or even probable. The actual evaluation of the margin between the MEFS and the LFS can be largely qualitative, but it provides a means of identifying weaknesses in the analysis where a small change in a model input could indicate an unacceptable change in the consequences.

For example, a trash fire of 150 Btu/sec can be the most expected, but when evaluating change involving a barrier only a trash fire of 300 Btu/sec located under the raceway will result in failure of the barrier to provide the level of protection it is intended.

C.3.4 Potential Fire Scenarios. Table C.3.4 provides a list of example fire scenarios for various areas in a nuclear power plant listing the ignition source and fuel for typical fire areas. Other factors associated with fire scenario definition (i.e., ventilation, heat release rate, configuration of fuel and plant equipment, fuel loading, and space configuration) are typically plant specific and should be confirmed in the plant.

Table C.3.4 Potential Fire Scenarios Fuel Ignition Source Type Area Lube oil1 Contact with hot piping surface Containment Fuel oil Contact with hot piping surface EDG room or building Turbine lube oil2 Contact with hot piping surface Turbine generator building Electrical cable insulation3 Internal cable fault Cable spreading room, cable tunnel, or cable penetration area Electrical wiring, cables, and circuit boards4 Electrical fault inside a cabinet or behind vertical control boards Control room Charcoal in filter5 Spontaneous combustion due to being wetted then heated Main safeguards filter area Electrical cable insulation Electrical circuit fault in switchgear cabinets Rooms with electrical switchgear General combustibles Smoking, hot work, or portable heater malfunction Warehouse (at beginning of refueling outage) Transformer oil Internal electrical fault causing rupture of transformer casing and release of oil that becomes ignited Yard transformers Hydrogen, cable insulation, and plastic battery cases Electrical arc Battery rooms Core expansion material Hot work Seismic rattle space between two buildings Office supplies, furnishing, and internal wiring Smoking or electrical circuit fault Computer room next to control room Pump motor windings Overheating Various areas Hydrogen Electrical arc Turbine building or outdoor hydrogen storage tanks General Class A combustibles Smoking, hot work, or portable heater malfunction Temporary office trailer Transient material associated with construction or maintenance Hot work Various areas Lube oil Contact with hot pipes Steam-driven pumps Lube oil Hot work Storage tank room or area within turbine building Fuel oil Contact with hot metal surface Diesel fire pump house Notes: (1) Reactor coolant pump lube oil system piping or fitting failure causes release of oil. (2) A machine imbalance results in movement of the machine in relation to lube oil system piping, causing pipe failure and release of oil at more than one point along the machine. Oil sprays down from the upper elevation as a three-dimensional fire. Oil accumulates on the floor spreading as a two-dimensional pool fire. (3) High-energy internal cable fault in a fully loaded vertical cable tray ignites cable insulation within that tray and propagates to involve adjacent trays. (4) Fire produces a large quantity of smoke and potentially toxic combustion products, causing untenable conditions and damage to sensitive computer and electronic components. (5) The filter is in service providing radioactive ventilation filtration, with its charcoal at the end of its service life (contaminated), leading to the products of combustion having radioactive contamination. A systematic methodology should be followed for developing potential fire scenarios. The potential fire scenarios can vary widely between areas in the NPP. The suggested key elements used to develop the scenario are ignition source, fuel loading and configuration, ventilation parameters, targets and failure mechanisms, and suppression activities.

C.3.4.1 Ignition Sources. An ignition source of sufficient magnitude and duration will be necessary to initiate the event. The ignition source can be introduced as a human action such as dropping slag from overhead welding/burning, or equipment failure such as overheating electrical faults in switchgear, transformers, or unwanted mechanical friction in motors/pumps. Cable initiated failures can also be considered due to fuse/breaker failure and circuit overloading. Bags of transient materials can experience spontaneous combustion from improper disposal of oil soaked rags. The ignition source should be realistic for the area under evaluation.

C.3.4.2 Fuel Loading and Configuration. The fuel loading should be consistent with the in-situ combustibles in the area. The model input data can be accurately represented by field walkdowns. Special care should be given to the combustibles' installed configurations. For example, vertical runs of cable trays will exhibit different burning characteristics than horizontal runs. Caution should be exercised when selecting heat release rates (HRRs) and burning durations.

C.3.4.3 Ventilation Parameters. The mechanical ventilation systems found in NPPs can influence the potential fire scenarios. Depending on the physical locations of supply discharges and exhaust inlets, ventilation can affect combustion and flame spread of materials. The injection of additional air can also influence the HRR intensity and burning duration.

C.3.4.4 Targets and Failure Mechanisms. The fire model can be used to estimate a number of thermal transients from the fire inside the area under evaluation. Examples include but are not limited to the approximated temperature on essential cables located in the area, the actuation temperature at fire detection and suppression devices, and the thermal exposure to fire barriers and structural members.

C.3.4.5 Suppression System Actuation and Manual Suppression Activities. The fire model can be time stepped to correspond with automatic and or manual suppression activities. In evaluating the maximum expected and limiting fire scenarios, the engineer might choose to arbitrarily fail the automatic suppression system and examine the impact on the other elements of defense-in-depth, such as fire barrier ratings.

C.3.4.6 Number of Case Runs. There is no defined maximum number of model runs that are to be performed for an area. The number of cases analyzed will depend on the physical parameters of the area, the number of different variables, and the object of study in the analysis. The engineer can provide a series of bounding case runs (possibly from multiple models) to define the fire scenario for an area.

C.3.5 Fire Event Tree and Other Analytical Tools. In the context of this standard, a fire scenario should not be confused with a fire event tree, which can be used to illustrate the various pathways along which a particular fire could develop. NFPA 550 contains a detailed discussion of the development and utilization of the fire event tree.

A fire event tree can be a useful analytical tool without being as elaborate or complete as that outlined in NFPA 550. It can provide a graphic summary of the potential sequence and variations of a fire event from initiation to conclusion. It can also be a framework for the utilization of probability data associated with such factors as frequency, reliability, and availability.

For a given fire area, there can be several different potential fires that can be analyzed using a fire event tree. For example, Figure C.3.5(a) depicts a fire area containing a Train A oil-filled pump, associated motor, and electrical cabinet, a Train B cable tray, automatic sprinklers in one portion, and automatic carbon dioxide in another.

FIGURE C.3.5(a) Fire Area.

There are several potential fire events that could be considered for this fire area. [See Figure C.3.5(b).] Initiating events could include the following:

(1)     Cable insulation fire

(2)     Electrical cabinet components fire

(3)     Pump lube oil leak fire

(4)     Electric motor insulation fire

(5)     Electric motor bearing grease fire

(6)     Transients (various types, quantities, and locations)

An event tree can be developed for each of these fires. Figure C.3.5(b) illustrates such a tree for a fire involving a leak of the pump lube oil.

FIGURE C.3.5(b) Fire Event Tree.

There are other analytical tools available that are useful in certain situations. These include failure analysis, failure modes and effects analysis (FEMA), HAZOP analysis, various checklists, and similar methodologies. These tools can be included as part of a performance-based assessment of fire protection, depending on the particular situation involved.

C.4 Uncertainties in Fire Modeling.

Uncertainty results from the specification of the problem being addressed (fire size, location, exposures, etc.). Limitations associated with the fire models used for problem analysis can produce additional uncertainties. Specifically, limitations in the number of physical processes considered and the depth of consideration can produce uncertainties concerning the accuracy of fire modeling results. Other uncertainties can be introduced due to limitations related to the input data required to conduct a fire simulation. Other sources of uncertainty include specification of human tenability limits, damage thresholds, and critical end point identifiers (e.g., flashover).

A sensitivity analysis can be conducted to evaluate the impact of uncertainties associated with various aspects of a fire model. A sensitivity analysis should identify the dominant variables in the model, define acceptable ranges of input variables, and demonstrate the sensitivity of the output. This analysis can point out areas where extra caution is needed in selecting inputs and drawing conclusions. A complete sensitivity analysis for a complex fire model is a sizable task. Again, engineering judgment is required to select an appropriate set of case studies to use for the sensitivity analysis. The American Society for Testing and Materials also has a guide for evaluating the predictive capabilities of fire models. The recommendations in this guide should be reviewed and applied as appropriate when utilizing fire modeling.

C.4.1 Source of Heat-Release and Fire Growth Rates. A significant source of uncertainty in fire models is associated with the heat-release and fire growth rates. The modeling of the combustion process and heat release is extremely complex. Experimental data are widely used and provided as input to fire models, and large uncertainties are associated with this input because of the inability to accurately correlate experimental data to the fire source of concern. The HRR is the driving force for the plume mass flow rate, the ceiling jet temperature, and, finally, the hot gas layer temperature that is driven by the energy balance. The HRR is dependent on the heat of combustion of the fuel, mass loss rate of the fuel, and the fuel surface area. The mass loss rate is dependent upon the fuel type, fuel geometry, and ventilation.

C.4.2 Effects of Ventilation. In certain applications, the effects of mechanical ventilation are important. Most fire models have difficulty in accurately predicting the effects of mechanical ventilation on fire development and the corresponding effects on the fire compartment(s) and contents; therefore, uncertainty is introduced and is addressed by conservative assumptions. Nuclear power plants in the U.S. are typically multiroom, windowless structures of various sizes and are provided, exclusively, with forced-ventilation systems that provide supply air and exhaust at different locations and elevations within the compartment(s). Mechanical ventilation can vary with weather and operating conditions.

C.4.3 Structural Cooling Effects. Considerable cooling effects can come from the masses of cable trays, ventilation ducts, and piping in the upper part of compartments in nuclear power plants. Most zone models do not have the ability to calculate the heat transfer by convection from the gas in the hot gas layer to these structures as a function of time.

C.4.4 Threshold for Thermal Damage to Equipment. Failures of equipment exposed to the harsh environment of a fire and the subsequent suppression activities are typically modeled by a threshold value of an appropriate parameter. This threshold value is referred to as the “equipment damage criterion.” As an example, a threshold surface temperature is usually considered as a damage criterion for cables.

Establishing damage criteria is a complex process and is a source of uncertainty. Equipment exposed to the thermal environment of a fire can fail either temporarily or permanently. As an example, an electronic circuit can temporarily fail (not respond or respond incorrectly) when exposed to high temperature; however, it can recover performance when the temperature drops. The failure criteria for equipment are also dependent on equipment function. As an example, small insulation leakage current can cause failure of an instrument cable, whereas the same amount of leakage in low-voltage power cable could be inconsequential.

C.4.5 Effects of Smoke on Equipment. Smoke from a fire that starts in one zone can propagate to other zones and potentially damage additional equipment. Currently, fire PSAs do not treat the question of smoke propagation to other areas and their effect on component operability in a comprehensive manner. The extent to which the issue is addressed depends on the analyst, and if it is addressed, it is typically addressed qualitatively.

C.4.6 Compartment and Fuel Geometry. Properly evaluating the unique or complex compartment and/or fuel geometry typical of a nuclear power plant can be a significant limitation of the model and a source for uncertainty in the results obtained. The interaction with and effect of adjacent compartments on the fire environment cannot be evaluated with models that are limited to a single compartment. In nuclear power plants, most combustibles (e.g., cable trays) are located well above the floor level. There is limited experimental data available for this type of fuel configuration. For most compartments of interest, the overhead areas in nuclear power plants are obstructed with cable trays, ventilation ducts, conduit banks, and piping. These obstructions are typically not evaluated for effect on the compartment environment by most zone models.

C.5 Fire Model References.

C.5.1 Technical References for Specific Fire Model Codes.

(1)     Peacock, R.D. and Jones, W.W., “Consolidated Model of Fire Growth and Smoke Transport, User's Guide (Version 5),” National Institute of Standards and Technology, Special Publication (in press).

(2)     Ho, et al., University of California at Los Angeles, “COMPRN IIIe: An Interactive Computer Code for Fire Risk Analysis,” EPRI NP-7282, Electric Power Research Institute, Palo Alto, CA, December 1992.

(3)     Walton, G., “CONTAM 93 User Manual,” NISTIR 5385, National Institute of Standards and Technology, Gaithersburg, MD, March 1994.

(4)     Jones, W., Peacock R., Forney, G., and Reneke, P., “CFAST: An Engineering Tool for Estimating Fire and Smoke Transport, Version 5-Technical Reference Guide” National Institute of Standards and Technology, SP 1030, 2004.

(5)     Department of Commerce, “FASTLite,” Special Publication 889, National Institute of Standards and Technology, Building and Fire Research Laboratory, Fire Modeling and Applications Group, Gaithersburg, MD, 1996.

(6)     Electric Power Research Institute, “Fire Modeling Guide for Nuclear Power Plant Applications,” TR-1002981, Palo Alto, CA, 2005.

(7)     Deal, S., “Technical Reference Guide for FPETOOL Version 3.2,” NISTIR 5486-1, National Institute of Standards and Technology, Gaithersburg, MD, 1995.

(8)     McGrattan, K.B., and Forney, G.P., “Fire Dynamics Simulator (Version 4), User's Guide,” NIST Special Publication 1019, National Institute of Standards and Technology, Gaithersburg, MD, July 2004.

(9)     ASCOS is one of the best-known models for smoke travel between interconnecting rooms. ASCOS is described in the ASHRAE (American Society of Heating, Refrigeration and Air Conditioning Engineers) publication “Design of Smoke Management Systems,” Atlanta, GA, 1993.

(10)     FLAMME is a computer fire model developed by the Institute of Protection and Nuclear Safety (IPSN) of the French Atomic Energy Commission (CEA). The FLAMME code was developed to quantify the thermal response to the environment and equipment and use the results of this analysis in fire PRAs. The objective of this code is to predict the damage time for various safety-related equipment. The FLAMME-S version can simulate the development of fire in one of several rooms in a parallelopedic form with vertical or horizontal openings, confined or ventilated, containing several targets and several combustible materials.

(11)     FLOW-3D is a computational fluid dynamics (CFD Field) model used at the British Harwell Laboratory.

(12)     Gay, L., and Epiard, C., “User guide of the MAGIC Software V4.1.1,” EDF HI82/04, December 2004.

(13)     Gay, L., and Epiard, C., “MAGIC Software version 4.1.1: Mathematical model,” EDF HI82/04/024/P, December 2004.

(14)     NUREG 1805, “Fire Dynamics Tools (FDT): Quantitative Fire Hazard Analysis Methods for the U.S. Nuclear Regulatory Commission Fire Protection Inspection Program.”

(15)     Forney, G.P., and McGrattan, K.B., “User's Guide for Smokeview Version 4,” NIST Special Publication 1017, National Institute of Standards and Technology, Gaithersburg, MD, July 2004.

C.5.2 Comparisons of Fire Model Codes.

(1)     Azarm Dey, M.A., Travis, R., Martinez-Guridi, G., and Levine, R., “Technical Review of Risk-Informed, Performance-Based Methods for Nuclear Power Plant Fire Protection Analyses,” Draft NUREG 1521, U.S. Nuclear Regulatory Commission, Washington, D.C., July 1998.

(2)     Deal, S., “A Review of Four Compartment Fires with Four Compartment Fire Models,” Fire Safety Developments and Testing, Proceedings of the Annual Meeting of the Fire Retardant Chemicals Association, pp. 33–51, 1990.

(3)     Duong, D.Q., “Accuracy of Computer Fire Models: Some Comparisons With Experimental Data From Australia,” Fire Safety Journal, 16:6, pp. 415–431, 1990.

(4)     Friedman, R., “International Survey of Computer Models of Fire and Smoke,” Journal of Fire Protection Engineering, vol. 4, pp. 81–92, 1992.

(5)     “Assessment and Verification of Mathematical Fire Models,” ISO/CD 13387-3, International Organization for Standardization, April 1996.

(6)     Mowrer, F.W., and Stroup, D.W., “Features, Limitations, and Uncertainties in Enclosure Fire Hazard Analyses — Preliminary Review,” NISTIR 6152, National Institute of Standards and Technology, Gaithersburg, MD, March 1998.

(7)     Mowrer, F.W., and Gautier, B., “Fire Modeling Code Comparisons,” EPRI TR-108875, Electric Power Research Institute, Palo Alto, CA, September 1998.

(8)     Mingchun Luo and Yaping He, “Verification of Fire Models for Fire Safety System Design,” Journal of Fire Protection Engineering, vol. 9, no. 2, pp. 1–13, 1998.

(9)     Simcox, S., Wilkes, N., and Jones, I., “Computer Simulation of the Flows of Hot Gases From the Fire at King's Cross Underground Station,” Institution of Mechanical Engineers, King's Cross Underground Fire: Fire Dynamics and the Organization of Safety, London, pp. 19–25, 1989.

C.5.3 Other References Relating to Fire Modeling.

(1)     Society of Fire Protection Engineers, “The SFPE Engineering Guide to Performance-Based Fire Protection Analysis and Design,” National Fire Protection Association, Quincy, MA. 1999.

(2)     Wade, C.A., “A Performance-Based Fire Hazard Analysis of a Combustible Liquid Storage Room in an Industrial Facility,” Journal of Fire Protection Engineering, vol. 9, no. 2, pp. 36–45, 1998.

(3)     Mowrer, F.W., “Methods of Quantitative Fire Hazard Analysis,” EPRI TR-100443, Electric Power Research Institute, Palo Alto, CA, May 1992.

(4)     Meacham, B.J., “SFPE Focus Group on Concepts of a Performance-Based System for the United States,” Summary of Consensus Focus Group Meeting, Society of Fire Protection Engineers, April 1996.

(5)     DiNenno, P., ed., The SFPE Handbook of Fire Protection Engineering, 2nd edition, National Fire Protection Association, Quincy, MA, 1995.

(6)     “National Fire Protection Association's Future in Performance-Based Codes and Standards,” Report of the NFPA in-house task group, National Fire Protection Association, Quincy, MA, July 1995.

(7)     “Design Fire Scenarios and Design Fires,” ISO/CD 13387-2, International Organization for Standardization, 1997.

(8)     Taylor, B.N. and Kuyatt, C.E., “Guidelines for Evaluating and Expressing the Uncertainty of NIST Measurement Results,” NIST Technical Note 1297, National Institute of Standards and Technology, Gaithersburg, MD, January 1994.

(9)     “Standard Guide for Evaluating the Predictive Capability of Fire Models,” ASTM E 1355, American Society for Testing and Materials, Philadelphia, PA, 1992.

(10)     Gallucci, R., and Hockenbury, R., “Fire-Induced Loss of Nuclear Power Plant Safety Functions,” Nuclear Engineering and Design, vol. 64, pp. 135–147, 1981.

(11)     Electric Power Research Institute, “Fire PRA Implementation Guide,” EPRI TR-105928, Palo Alto, CA, December 1995.

(12)     Stroup, D.W., “Using Field Models to Simulate Enclosure Fires,” The SFPE Handbook of Fire Protection Engineering, 2nd edition, National Fire Protection Association, Quincy, MA, pp. 3-152–3-159, 1995.

(13)     Lee, B.T., “Heat Release Rate Characteristics of Some Combustible Fuel Sources in Nuclear Power Plants,” NBSIR 85-3195, NIST, Gaithersburg, MD, July 1985.

(14)     Nowlen, S.P. “Heat and Mass Release for Some Transient Fuel Source Fires: A Test Report,” NUREG/CR-4680, October 1986.

(15)     “Fire Modeling Guide for Nuclear Power Plant Applications,” Electric Power Research Institute, TR-1002981.

(16)     NUREG / CR-6850 and EPRI 1011989, “Verification and Validation of Selected Fire Models for Nuclear Power Plant Applications,” expected December 2005.