***APPENDIX A-H IS TREATED LIKE *** 

A SEPARATE DOCUMENT AND MAYBE 

VIEWED AND/OR DOWNLOADED THAT WAY 

Evaluation of Fire Models

for Nuclear Power Plant

Applications: Cable Tray Fires

International Panel Report

Compiled by Monideep K. Dey

NISTIR 6872

 

NISTIR 6872

***APPENDIX A-H IS TREATED LIKE ***

A SEPARATE DOCUMENT AND MAYBE 

VIEWED AND/OR DOWNLOADED THAT WAY 

Evaluation of Fire Models

 for Nuclear Power Plant

 Applications: Cable Tray Fires

Compiled by Monideep K. Dey, Guest Researcher

Fire Research Division

Building and Fire Research Laboratory

June 2002

U.S. DEPARTMENT OF COMMERCE

Donald L. Evans, Secretary

TECHNOLOGY ADMINISTRATION

Phillip J. Bond, Under Secretary of Commerce for Technology

NATIONAL INSTITUTE OF STANDARDS AND TECHNOLOGY

Arden L. Bement, Jr., Director
iii

Abstract

This technical reference document was developed in the International Collaborative

Project to Evaluate Fire Models for Nuclear Power Plant Applications. This volume

reports on the results of the first task in the international collaborative project. The

objective of the first task was to evaluate the capability of fire models to analyze cable

tray fires of redundant safety systems in nuclear power plants. The evaluation of the

capability of fire models to analyze these scenarios was conducted through an

international benchmark exercise. Consideration of appropriate input parameters and

assumptions, interpretation of the results, and determination of the adequacy of the

physical sub-models established useful technical information regarding the capabilities

and limitations of the fire models. The participants in the benchmark exercise

determined that results indicate that the models provide a comprehensive treatment of

most physical phenomena of interest in the scenarios analyzed. The predicted trends

from the models were found to be similar and reasonable for their intended use. These

fire models can provide useful results for nuclear power plant fire safety analysis for the

types of scenarios analyzed.

v

Table of Contents

Abstract . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . iii

List of Figures . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . vii

List of Tables . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ix

Executive Summary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . xi

Foreword . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . xv

Acronyms and Initialisms . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . xvii

1 Introduction ........................................................ 1

2 Definition of the Benchmark Exercise . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3

2.1 Background ................................................. 3

2.2 Procedure .................................................. 4

2.3 Fire Codes Used in the Exercise ................................. 4

2.4 Room Size and Conditions ..................................... 5

2.5 Objectives of Exercise . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5

2.6 Properties and Ambient Conditions ............................... 6

2.6.1 Properties ........................................... 6

2.6.2 Ambient Conditions and Other Constants ................... 7

2.7 Heat Release Rates and Target Model ............................ 8

2.7.1 Part I . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8

2.7.2 Part II . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 9

2.8 Cases for Exercise . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 10

2.8.1 Part I . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 10

2.8.2 Part II . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 11

3 Input Parameters and Assumptions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 13

3.1 Summary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 13

3.2 Main Issues . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 13

3.3 Other Issues . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 15

4 Results of Analyses . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 19

4.1 Summary of Results . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 19

4.1.1 Part I . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 19

4.1.2 Part II . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 19

4.2 Verification of Sub-models . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 20

4.2.1 Part I . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 20

4.2.2 Part II . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 26
vi

4.3 Validation of Models . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 30

4.3.1 Validation Studies and Uncertainty Estimate . . . . . . . . . . . . . . . . 30

4.3.2 Benefit of Extending Validation Database . . . . . . . . . . . . . . . . . . 31

5 General Conclusions and Recommendations . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 33

5.1 Capabilities and Limitations . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 33

5.2 User Interface . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 35

5.3 Benefits of Hand Calculations . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 36

5.4 Need for Model Improvements . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 36

5.5 Need for Advanced Models . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 37

5.6 Need for Additional Test Programs . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 37

5.7 Generic Applicability of Conclusions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 38

6 References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 61

Appendix A: Benchmark Analysis with FLAMME_S, Eric BOUTON, and Bruno

TOURNIAIRE, IPSN, France . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . A-1

Appendix B: Benchmark Analysis with CFAST and FDS, Monideep DEY, NRC/NIST,

USA . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . B-1

Appendix C: Benchmark Analysis with MAGIC, Bernard GAUTIER, Helene

ERNANDORENA, and Maurice KAERCHER, EdF, France . . . . . . . . . . . . . . C-1

Appendix D: Benchmark Analysis with CFX, Matthias HEITSCH, GRS, Germany . . D-1

Appendix E: Benchmark Analysis with MAGIC, Daniel JOYEUX, and Olivier LECOQJAMMES, CTICM, France . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . E-1

Appendix F: Benchmark Analysis with COCOSYS, Walter KLEIN-HESSLING, GRS,

Germany . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . F-1

Appendix G: Benchmark Analysis with JASMINE and CFAST,

Stewart MILES, BRE, UK . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . G-1

Appendix H: Benchmark Analysis with CFAST, Juergen WILL, GRS, Germany . . . H-1
vii

List of Figures

Figure 1 Representative PWR Room . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 45

Figure 2 Trash Bag Fire (Part I) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 46

Figure 3 Plume Flow (Part I, Base Case) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 46

Figure 4 HGL Development (Part I, Base Case) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 47

Figure 5 Oxygen Concentration (Part I, Base Case) . . . . . . . . . . . . . . . . . . . . . . . . . . 47

Figure 6 Pressure Development (Part I, Base Case) . . . . . . . . . . . . . . . . . . . . . . . . . 48

Figure 7 Flow from Crack (Part I, Base Case) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 48

Figure 8 HGL Temperature (Part I, Base Case) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 49

Figure 9 Target Surface Temperature (Part I, Base Case) . . . . . . . . . . . . . . . . . . . . . 49

Figure 10 Total Heat Loss from Boundaries - COCOSYS

(from Klein-Hessling (Appendix F)) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 50

Figure 11 Effect of Distance between Fire and Target - FLAMME_S (from

Bouton:Appendix A) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 50

Figure 12 Effect of Distance on Radiative Flux - MAGIC

(from Gautier:Appendix C) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 51

Figure 13 Target Exposure in Plume Region in CFD Analysis - CFX

(from Heitsch (Appendix D)) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 51

Figure 14 HGL Development (Part I) - CFAST

(from Dey (Appendix B)) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 52

Figure 15 Door Flows (Part I, Case 4) - CFAST

(from Dey (Appendix B)) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 52

Figure 16 HGL Temperature (Part I) - CFAST

(From Dey (Appendix B)) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 53

Figure 17 Mechanical Ventilation Flows (Part I, Case 5) - CFAST

(from Dey (Appendix B)) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 53

Figure 18 Door Flows (Part I, Case 4) - FDS

(from Dey (Appendix B)) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 54

Figure 19 Effect of Mechanical Ventilation - JASMINE

(from Miles (Appendix G)) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 54

Figure 20 Effects of Mechanical Ventilation

(Part I, Case 5) - FDS (from Dey (Appendix B)) . . . . . . . . . . . . . . . . . . . . . . . . 55

Figure 21 Effects of Mechanical Ventilation - CFX

(from Heitsch (Appendix D)) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 55

Figure 22 Heat Release Rate (Part II, Base Case) . . . . . . . . . . . . . . . . . . . . . . . . . . . 56

Figure 23 HGL Development (Part II, Base Case) . . . . . . . . . . . . . . . . . . . . . . . . . . . 56

Figure 24 Oxygen Concentration (Part II, Base Case) . . . . . . . . . . . . . . . . . . . . . . . . 57

Figure 25 HGL Temperature (Part II, Base Case) . . . . . . . . . . . . . . . . . . . . . . . . . . . 57

Figure 26 Target Surface Temperature (Part II, Base Case) . . . . . . . . . . . . . . . . . . . 58

Figure 27 Species Concentration (Part II, Base Case)

(from Bouton (Appendix A)) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 58

Figure 28 Pyrolysis Rate (Part II, Base Case)

(from Dey (Appendix B)) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 59
viii

Figure 29 Effect of Cable Structure

(from Bouton (Appendix A)) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 59

Figure 30 Temperature Development (Special Cases) . . . . . . . . . . . . . . . . . . . . . . . . 60
ix

List of Tables

Table 1 Thermophysical Data for Walls, Floor, and Ceiling ..................... 6

Table 2 Thermophysical Data for Cables . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6

Table 3 Yields for PVC . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6

Table 4 Properties of Fire Door .......................................... 7

Table 5 Ambient Conditions ............................................. 7

Table 6 Other Constants and Indices ..................................... 8

Table 7 32 Gallon Trash Bag Fire . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8

Table 8 Summary of Cases for Part I . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 10

Table 9 Summary of Cases for Part II . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 12

Table 10 Comparison of Results for Part I, Base Case . . . . . . . . . . . . . . . . . . . . . . . 39

Table 11 Comparison of Results for Part I, Case 1 . . . . . . . . . . . . . . . . . . . . . . . . . . 40

Table 12 Comparison of Results for Part I, Case 2 . . . . . . . . . . . . . . . . . . . . . . . . . . 40

Table 13 Comparison of Results for Part I, Case 3 . . . . . . . . . . . . . . . . . . . . . . . . . . 40

Table 14 Comparison of Results for Part I, Case 4 . . . . . . . . . . . . . . . . . . . . . . . . . . 41

Table 15 Comparison of Results for Part I, Case 5 . . . . . . . . . . . . . . . . . . . . . . . . . . 41

Table 16 Comparison of Results for Part II, Base Case . . . . . . . . . . . . . . . . . . . . . . . 42

Table 17 Comparison of Results for Part II, Case 1 . . . . . . . . . . . . . . . . . . . . . . . . . . 42

Table 18 Comparison of Results for Part II, Case 2 . . . . . . . . . . . . . . . . . . . . . . . . . . 42

Table 19 Comparison of Results for Part II, Case 10 . . . . . . . . . . . . . . . . . . . . . . . . . 43

Table 20 Comparison of Results for Part II, Case 11 . . . . . . . . . . . . . . . . . . . . . . . . . 43

Table 21 Comparison of Results for Part II, Case 12 . . . . . . . . . . . . . . . . . . . . . . . . . 43

Table 22 Comparison of Results for Part II, Case 13 . . . . . . . . . . . . . . . . . . . . . . . . . 44

Table 23 Comparison of Results for Part II, Special Cases . . . . . . . . . . . . . . . . . . . . 44

xi

Executive Summary

Objective

This technical reference document was developed in the International Collaborative

Project to Evaluate Fire Models for Nuclear Power Plant Applications. The objective of

the collaborative project is to share the knowledge and resources of various

organizations to evaluate and improve the state of the art of fire models for use in

nuclear power plant fire safety and fire hazard analysis. The project is divided into two

phases. The objective of the first phase is to evaluate the capabilities of current fire

models for fire safety analysis in nuclear power plants. The second phase will

implement beneficial improvements to current fire models that are identified in the first

phase, and extend the validation database of those models. Currently, twenty-two

organizations from six countries are represented in the collaborative project.

Problem

The first task of the international collaborative project was to evaluate the capability of

various fire models to analyze cable tray fires of redundant safety systems in nuclear

power plants. The evaluation of the capability of fire models to analyze these scenarios

was conducted through an international benchmark exercise. The benchmark exercise

was intended to simulate a basic scenario defined in sufficient detail to allow evaluation

of the physics modeled in the fire computer codes. An assessment of appropriate input

parameters and assumptions, interpretation of results, and determination of the

adequacy of the physical sub-models in the codes for specific scenarios will establish

useful technical information regarding the capabilities and limitations of the fire

computer codes. Uncertainties in the predictions based on validations of each code will

provide a basis for the confidence on the set of results developed in the exercise. Three

zone, three Computational Fluid Dynamic (CFD), and two lumped-parameter models

were used by eight organizations in the exercise.

A representative emergency switchgear room for a Pressurized Water Reactor (PWR)

was selected for the benchmark exercise. There were two parts to the exercise. The

objective of Part I was to determine the maximum horizontal distance between a

specified transient (trash bag) fire and a cable tray that results in the ignition of the

cable tray. Part II examined whether a target cable tray will be damaged by a fire of a

cable tray stack that is separated by a horizontal distance, d. The effects of a fire door

position (open & closed) and mechanical ventilation system are examined in both parts

of the benchmark exercise.

Results

For Part I, none of the analyses conducted for the benchmark exercise predicted the

ignition of the target cable (specified at 643 K) by the postulated trash bag fire for
1

The concept of safe separation distance is not directly applicable in all countries.

xii

varying ventilation conditions in the room. The predicted temperature rise for all the

cases in Part I were similar. Given the dimensions of the room and the heat release

rate of the trash bag, the maximum surface temperature of the target outside the fire

plume region for all the cases analyzed is less than 350 K. This temperature is much

less than 643 K, which is specified for target damage. The target cable may ignite only

if it is in the plume region of the fire. The temperature of the target cable is predicted to

significantly increase when the distance between the trash bag and cable is between

0.4 m and 0. 5 m, and the target is exposed to the high plume gas temperature. The

predicted maximum surface temperature of the target in this region is predicted to be

550 K. Although the maximum predicted heat flux from the plume incident on the target

is predicted to be . 14 kW/m2, the duration of the exposure is not long enough to

increase the surface of the cable to the ignition temperature. A fire of similar intensity

sustained over a longer period could ignite the cable. Based on this, one could

establish a minimum horizontal safe separation distance1

 of 1.0 m between the trash

bag and the target cable. 

The predicted maximum temperatures of the target cable, using a lower oxygen limit of

12 %, were below 400 K for all the cases analyzed in Part II. The cable tray fire was

limited between 10 min and 15 min by the depletion of oxygen near the cable tray.

Given the elevation of the fire source and the predicted extinction of the fire, cable

damage is unlikely for the scenarios examined. The analysis of an elevated fire source

is key to the accuracy of the predicted result.

Input Parameters

The process for defining the input parameters for the fire models resulted in three main

issues: (1) specification of the fire source; (2) modeling of the target; and (3) value for

the lower oxygen limit (LOL). The specification of the fire source is fundamental to the

input for fire models, and can significantly affect the predicted thermal environment. The

specification of the above three parameters could lead to "user effects," and are the

largest sources of uncertainty in the predicted results from the input parameter

specification process for the types of scenarios examined in the benchmark exercise.

Verification and Validation

Verification is defined here as the process of determining that a model implementation

accurately represents the developer’s conceptual description of the model and the

solution to the model. Validation is defined as the process of determining the degree to

which a model is an accurate representation of the real world from the perspective of

the intended uses of the model.
xiii

Verification

The results of the analyses indicate that the trends predicted by the sub-models are

reasonable for the intended use of the models for analyzing the specified scenarios.

The constitutive equations for mass and energy balances in the fire models provide a

reasonable prediction of the hot gas layer development and temperatures in the

compartment. The fire models generally provide an adequate method to balance and

estimate the concentration of oxygen. Mass flows that result from the pressurization of

the compartment, or natural and mechanical ventilation are reasonably predicted by the

zone, CFD, and lumped-parameter models. Convective and radiative heat fluxes to the

boundaries and target are comprehensively treated in the models but utilize different

approaches. The thermal response of the target is coupled to the thermal environment

created by the fire and would benefit from further investigation.

The analyses of the scenarios also demonstrate the complexity in modeling an elevated

fire source which can be affected by a limited oxygen environment. The extinction submodels utilized in the computer codes are approximations of the interaction of the

complex combustion process with a limited oxygen environment. Therefore, the results

from the extinction sub-models represent an approximation of the conditions expected

for the fire scenarios. The assumption for the LOL will affect the predicted peak target

temperature. Therefore, conservative assumptions are warranted due to the uncertainty

in the extinction models used in the computer codes. Also, the target sub-model in

some of the computer codes requires the specification of target orientation by the user.

This may result in a non-conservative result and a "user effect" since the orientation of

the target will determine the heat flux incident on it. This limitation may be overcome by

establishing procedures for the use of the models to obtain conservative and consistent

results. In some cases it may be difficult to define conservatism, therefore, the

development of best-estimate methods may be desirable.

The inclusion of emission/absorption due to soot, water vapor, and carbon dioxide may

play a significant role both in the radiation heat transfer to the target cable and also in

the general thermodynamics inside the compartment. The latter will influence various

matters including heat loss to the compartment boundaries and the mass flow rates

through the opening(s). Radiation from the flaming region will be important in

determining damage to cables close to the fire source.

Validation

Most of the fire models used in the benchmark exercise have been compared with test

data for fires ranging from 100 kW to 2.5 MW in compartments with volumes ranging

from 10 m3

 to 1300 m3 . The comparisons are generally satisfactory, with different

accuracies reported for the range of data sets. Tests conducted in a compartment with a

similar volume and fire source indicated that the relative variation of pressure,

temperature, and oxygen concentration predicted with test data was within 20 %. The

comparison of cable surface temperature evolution was less successful due to the
xiv

vertical temperature gradient in the test data for the compartment and the vertical

position of the target in the hot gas layer. The validations of the fire models conducted

to date indicates that they generally provide a reasonably accurate representation of

physical phenomena for the types of scenarios in the benchmark exercise.

Although the exercise reported here did not include comparisons of model results with

test data, the analyses reported did include the comparison of the magnitudes of the

parameters predicted by different fire models. Generally, the predictions were similar. 

Models developed independently, if based on the same fundamental laws, are expected

to produce similar results. Codes that produce similar results in a benchmark exercise

should accurately represent the physical phenomena modeled if the input parameters

are representative (in particular for the fire source), and at least one of the codes has

been validated for the studied configurations.

A distinction is made here between the variability of results due to differences in input

parameters and to differences in the physics of the model. As indicated earlier, different

assumptions of fire source power can significantly affect the results from the models.

Other important input data are the thermophysical parameters, e.g., the convective heat

transfer coefficient. It is judged that differences in model results due to the uncertainty of

the models is less than differences caused by variations in input data and assumptions.

Conclusions

The international panel determined that the analysis of the results of the benchmark

exercise demonstrates that current zone, CFD, and lumped-parameter fire models

provide a comprehensive treatment of most physical phenomena of interest in the

scenarios analyzed. The results indicate that the trends predicted by the sub-models

are reasonable for the intended use of the models for analyzing the specified scenarios.

The results obtained from these fire models can provide useful insights for nuclear

power plant fire safety analysis for the types of scenarios analyzed.

There are benefits to extending the current validation database, especially for target

response calculations. The continued validation of current models in international blind

exercises will add confidence for the widespread use of these models in nuclear power

plant fire safety analysis.

Most of the insights gained and conclusions drawn on the capabilities and limitations of

fire models from this benchmark exercise is applicable to a broad range of fire scenarios

expected in nuclear power plants. However, further benchmark and validation exercises

are necessary for some specific configurations such as large compartments (like the

turbine building) with large pool fires, multi compartments with horizontal and vertical

vent connections, and control room configurations. Insights on some further specific

modeling issues are likely to be developed from such exercises.
xv

Foreword

This technical reference document was developed in the International Collaborative

Project to Evaluate Fire Models for Nuclear Power Plant Applications. The objective of

the collaborative project is to share the knowledge and resources of various

organizations to evaluate and improve the state of the art of fire models for use in

nuclear power plant fire safety and fire hazard analysis. The project is divided into two

phases. The objective of the first phase is to evaluate the capabilities of current fire

models for fire safety analysis in nuclear power plants. The second phase will extend

the validation database of those models, and implement beneficial improvements to the

models that are identified in the first phase. Currently, twenty-two organizations from

six countries are represented in the collaborative project.

This volume reports on the results of the first task in the international collaborative

project. The objective of the first task was to evaluate the capability of fire models to

analyze cable tray fires of redundant safety systems in nuclear power plants. The

evaluation of the capability of fire models to analyze these scenarios was conducted

through an international benchmark exercise. Three zone, three computational fluid

dynamic (CFD), and two lumped-parameter fire models were used by eight

organizations in the exercise. The benchmark exercise simulated a basic scenario

defined in sufficient detail to allow the evaluation of the physics modeled in the fire

computer codes. Consideration of appropriate input parameters and assumptions, and

the interpretation of the results to evaluate the adequacy of the physical sub-models

established useful technical information regarding the capabilities and limitations of the

fire models. This technical information is presented in this volume which is the first of a

series of technical reference documents for fire model users. The objective of the

exercise was not to compare the capabilities and strengths of specific models, address

issues specific to a model, nor to recommend specific models over others. Future

volumes of this series will report on the findings of other benchmark and validation

exercises that are planned for this project.

This document is not intended to provide guidance to users of fire models. Guidance on

the use of fire models is currently being developed by several national and international

standards organizations, industry groups, and utilities. This document is intended to be

a source and reference for technical information and insights gained through the

exercises conducted, and provided by the experts participating in this project. This

information may be beneficial to users of fire models and developers of guidance

documents or standards for the use of fire models in nuclear power plant applications.

xvii

Acronyms and Initialisms

BFS Bundesamt fur Strahlenschutz

BRE Building Research Establishment

CIB International Council for Research and Innovation in Building and

Construction

CFAST Consolidated Model for Fire and Smoke Transport

CFD Computational Fluid Dynamics

CL centerline

COCOSYS Containment Code System

EdF Electricite de France

EPRI Electric Power Research Institute

FDS Fire Dynamics Simulator

GRS Gesellschaft fuer Anlagen-und Reaktorsicherheit

HGL hot gas layer

HRR Heat Release Rate

iBMB Institut fuer Baustoffe, Massivbau und Brandschutz

IPSN Institute for Protection and Nuclear Safety

JASMINE Analysis of Smoke Movement in Enclosures

LL Lower layer

LOL Lower Oxygen Limit

NII H. M. Nuclear Installations Inspectorate

NIST National Institute of Standards and Technology

NPP Nuclear Power Plant

NRC Nuclear Regulatory Commission

PRA Probabilistic Risk Analysis

PWR Pressurized Water Reactor

TUV Technical University of Vienna

UL upper layer

VTT Valtion Teknillinen Tutkimuskeskus

WPI Worcester Polytechnic Institute

1

1 Introduction

The 1st planning meeting of the International Collaborative Project to Evaluate Fire

Models for Nuclear Power Plant Applications was held at the University of Maryland at

College Park, USA, on October 25-26, 1999. Attendees at the meeting agreed to share

their knowledge and resources to evaluate and improve the state of the art of fire

models for use in nuclear power plant (NPP) safety. It was decided that the project

would be divided into two phases. The objective of the first phase would be to evaluate

the capabilities of current fire models (zone, CFD, and lumped-parameter) for fire safety

analysis in NPPs. The second phase will implement beneficial improvements to current

fire models that are identified in the first phase, and extend the validation database of

those models. The summary of the 1st meeting and the details of the objectives

established for the project, including the goals for the benchmark exercise reported in

this document may be found in NRC (2000). The benchmark exercise was defined at

the 2nd project meeting at the Institute for Protection and Nuclear Safety (IPSN),

Fontenay-aux-Roses, France, on June 19 and 20, 2000. The summary of the 2nd

meeting is reported in NRC (2001). 

The definition of the benchmark exercise is presented in Chapter 2. Chapter 3 provides

a summary of the main issues that arose in the consideration of input parameters and

assumptions for the scenarios in the exercise, and how participants decided to address

the issues. Chapter 4 presents a summary of the main results that were sought in the

definition of the benchmark exercise presented in Chapter 2. Chapter 5 finally provides

a discussion of the general conclusions and issues derived from the benchmark

exercise. Appendices A through I include the detailed results of the analyses for the

benchmark exercise conducted by participants using different fire models.

This international panel report was developed by the following members that contributed

either through the performance of analysis in the benchmark exercise, and/or by

providing peer comments at various stages of the exercise:

ALVAREZ, Alberto, IPSN, France

BARNETT, Jonathan, WPI, USA

BERG, Heinz-Peter, BFS, Germany

BERTRAND, Remy, IPSN, France

BOUTON, Eric, IPSN, France

BRANDES, Doug, Duke Power Co., USA

CASSELMAN, Chantal, IPSN, France

COUTTS, Alan, Westinghouse, USA 

DEY, Monideep, NRC/NIST, USA

ELICSON, Tom, Fauske & Assoc., USA

GAUTIER, Bernard, EDF, France

HEITSCH, Matthias, GRS, Germany

IQBAL, Naeem, NRC, USA
2

JOGLAR, Francisco, SAIC/EPRI, USA

JONES, Geoffrey, NII, UK

JONES, Walter, NIST, USA

JOYEUX, Daniel, CTICM, France

KAERCHER, Maurice, EDF, France

KASSAWARA, Bob, EPRI, USA

KESKI-RAHKONEN, Olavi, VTT, Finland

KLEIN-HESSLING, Walter, GRS, Germany

KLOOS, Martina, GRS, Germany

KRUPPA, Joel, CTICM, France

LACOUE, Jocelyne, IPSN, France

LEBEDA, Christian, TUV, Austria

MCGRATTAN, Kevin, NIST, USA

MILES, Stewart, BRE, UK

NAJAFI, Bijan, SAIC/EPRI, USA

PAGES, Olivier, EDF, France

PLYS, Marty, Fauske & Assoc., USA

REW, Peter, W S Atkins, UK

RIESE, Olaf, iBMB

ROEWEKAMP, Marina, GRS, Germany

ROY, Jean-Francois, EdF, France

SCHWINGES, Bernd, GRS, Germany

SUCH, Jean-Marc, IPSN, France

WILL, Juergen, iBMB, of Braunschweig Tech. Univ., Germany

The following organizations sponsored or collaborated with the organizations

represented at the meeting:

• Industry Management Committee, UK 

• National Institute of Standards and Technology, USA

The main report of this document is a result of the collective efforts of the individuals

and organizations listed above. It is based on the separate reports included in the

appendices and discussions at project meetings on the task. The separate reports in

the appendices are authored by the analyst(s) identified in the title pages. It is not

possible to provide all the results and insights gained from the analyses presented in

the appendices in the main text. The reader is encouraged to review the discussions in

the appendices to obtain a more comprehensive understanding of the results of the

benchmark exercise reported here.
3

2 Definition of the Benchmark Exercise

2.1 Background

The benchmark exercise was developed to evaluate the capability of fire modeling

analyses to provide results for a probabilistic risk analysis (PRA). In a PRA study, fire

models are used to estimate the conditional probability of safe-shutdown equipment

damage given a postulated fire. The main fire protection features that effect the

development of a fire are: 

• Automatic or manual isolation of the fire rooms by the closure of fire doors and

dampers.

• Automatic fire detection (detection by operators is also important).

• Fire suppression (automatic and manual) with gaseous suppression systems (Halon

or CO2), and nongaseous water-based suppression (sprinkler) systems.

In a PRA study, the target damage time is compared with the duration of a specific fire

scenario identified in an event tree. The conditional probability of damage to the safe

shutdown equipment is equal to the probability of that fire scenario if the damage time is

less than the duration of the fire scenario.

Given the state of the art of fire modeling, the adequacy of fire detection and

suppression is normally not included in fire modeling analyses to support a PRA. 

Therefore, the benchmark exercise did not include the evaluation of these systems or

events.

The benchmark exercise is for a basic fire scenario for an NPP defined in sufficient

detail to allow the evaluation of the physics modeled in the fire computer codes. This

approach is similar to that adopted by the CIB W14 effort (Keski-Rahkonen, 1998) for

fire code assessment. An assessment of appropriate input parameters and

assumptions, interpretation of results, and determination of the adequacy of the physical

models in the codes for specific scenarios will establish useful technical information

regarding the capabilities and limitations of the codes. Generic insights regarding the

capabilities of the models will also be developed in this process.

The comparisons between fire codes can be used to understand the physics in them,

i.e., if all the codes produce similar results over a range of fire scenarios then the

physics modeled in the codes is probably adequate for the proposed scenario. 

However, the compounding effects of different phenomena will also need to be

evaluated. Some uncertainty in the results may be acceptable depending on how the

results will be used. Uncertainties in the predictions of the fire models based on

validations of each fire code can provide a basis for the confidence on the set of results

developed in the benchmark exercise.
4

2.2 Procedure

The following procedure was adopted for the benchmark exercise:

• Analysts should discuss and agree on the input data for the various fire codes that

will be used in the benchmark exercise. The goal is to analyze the same problem

and minimize the variation of results due to different input parameters. “User

effects” will be examined at a later stage.

• The form of the results to be compared should be agreed upon by participants prior

to the commencement of the exercise.

• Developers of the fire codes, and those not involved in the development of the

codes, can conduct the code analyses for the benchmark exercise.

• Blind simulations will be conducted, i.e., each analyst will independently conduct his

or her analyses. The results will be shared between participants when all the

analyses by participants have been completed and the results are available. The

results will be simultaneously posted on the collaborative project web portal prior to

a meeting of the participants.

• If desired, the same code (e.g., CFAST) can be used by different organizations since

this will provide useful information on whether the results vary with different users. 

However, the same version of the code should be used (for CFAST, use Version

3.1.6).

• A series of benchmark exercises will be defined and conducted in this project. This

will allow the evaluation of the full spectrum of fire model features and applications,

and facilitate the formulation of a comprehensive technical reference for users on the

capabilities and limitations of the current fire models.

2.3 Fire Codes Used in the Exercise

The following fire models were used in the benchmark exercise by the organizations

listed:

Organization Codes

1. IPSN FLAMME-S (zone)

2. NRC/NIST CFAST (zone), FDS (CFD)

3. GRS COCOSYS (lumped parameter), CFX (CFD)

4. EdF MAGIC (zone)

5. BRE/NII CFAST, JASMINE (CFD)

6. iBMB/GRS CFAST

7. CTICM MAGIC
5

A description of these models with references is presented in the Appendices that

document the results of analyses using the models.

2.4 Room Size and Conditions

A representative pressurized water reactor emergency switchgear room is selected for

this benchmark exercise. A simplified schematic of the room, illustrating critical cable

tray locations, is shown in Figure 1. The room is 15.2 m (50 ft) deep, 9.1 m (30 ft) wide,

and 4.6 m (15 ft) high. The room contains the power and instrumentation cables for the

pumps and valves associated with redundant safe-shutdown equipment. The walls,

floor and ceiling are composed of concrete and 152 mm thick. The power and

instrument cable trays run the entire depth of the room, and are separated horizontally

by a distance, D. The value of D, the safe separation distance, is varied and examined

in this problem. The cable trays are 0.6 m (.24 in) wide and 0.08 m (.3 in) deep. 

The postulated fire scenario is the possibility of the initial ignition of the cable tray

labeled as “A,” located at 0.9 m (.3 ft) from the right wall of the room at an elevation of

2.3 m (7.5 ft) above the floor, by a trash bag fire on the floor. Cables for the redundant

train are contained in another tray, labeled “B,” the target. A horizontal distance, D, as

shown in Figure 1, separates tray B from tray A. The room has a door, 2.4 m x 2.4 m (8

ft x 8 ft), located at the midpoint of the front wall, assumed to lead to the outside. The

room has a mechanical ventilation system with a flowrate of 5 volume changes per hour

into and out of the room. A constant flowrate of the mechanical ventilation system was

assumed. The midpoint of the vertical vents for the supply and exhaust air are located

at an elevation of 2.4 m and have area of 0.5 m2 each. The vents were assumed to be

square and located at the center of the side walls (parallel to the cable trays). The air

was assumed to be supplied from the outside through the right wall, and exhausted to

the outside from the left wall. The effects of the fire door being open or closed, and the

mechanical ventilation on and off were examined. 

It was also assumed that other cable trays (C1 and C2) containing critical and noncritical cables are located directly above tray A, and no combustible material is found

between trays A and B.

2.5 Objectives of Exercise

There are two parts to the benchmark exercise. The objective of Part I is to determine

the maximum horizontal distance between the trash bag fire and the target, tray A, that

results in the ignition of tray A. This information is of use in a fire PRA to calculate the

area reduction factor for the transient source fire frequency, which are derived to be

applicable to the total area of the rooms. Analyses of this part of the problem will also

provide insights regarding the capabilities of the models to predict simpler fire scenarios

for risk analyses than those associated with fires of redundant cable trays.
6

The goal of the analyses for Part II was to determine the time to damage of the target

cable tray B for several heat release rates of the cable tray stack (A, C2, and C1), and

horizontal distance, D. The effects of target elevation and ventilation were also

examined.

2.6 Properties and Ambient Conditions

2.6.1 Properties

The following are properties used in Part I and/or II of the exercise. Table 1 presents

the thermophysical data for the concrete walls, floor, and ceiling, and Table 2 lists the

thermophysical data for the electrical cables.

Table 1 Thermophysical Data for Walls, Floor, and Ceiling (Concrete)

Specific Heat 1000 J/(kg.K)

Thermal

Conductivity

1.75 W/(m.K)

Density 2200 kg/m3

Emissivity 0.94

Table 2 Thermophysical Data for Cables

Heat of combustion of cable

insulation

16 MJ/kg

Fraction of flame heat released

as radiation

0.48

Density 1710 kg/m3

Specific Heat 1040 J/(kg.K)

Thermal Conductivity 0.092 W/(m.K)

Emissivity 0.8

The chemical properties of cables are obtained from Tewarson (1995). The cable

insulation was assumed to be polyvinyl chloride (PVC) with a chemical formula of

C2H3Cl, and oxygen-fuel mass ratio of 1.408. The yields (mass of species/mass of fuel)

of PVC are listed in the following Table 3 from Tewarson, 1995. 

Table 3 Yields for PVC

Species Yield

CO2 0.46

CO 0.063

HCl 0.5
2

Derived from information in NFPA 80 and SFPE Handbook.

7

Soot 0.172

The smoke potential of PVC is 1.7 ob.m3/g, where the smoke potential is defined as the

optical density (db/m or ob) x Volume of the compartment (m3

)/mass of the fuel

pyrolyzed (g).

The following are details of the construction and properties of the fire door2 that could be

used in models that allow the incorporation of such features. The fire door is a metalclad door with a wood core, and insulating panels between the wood core and the metal

clad (on both sides of the wood core). The thickness of the metal clad, wood core, and

insulating panels are 0.6 mm, 40 mm, and 3 mm respectively. The properties of the fire

door are listed in Table 4.

Table 4 Properties of Fire Door

Thermal

Conductivity

(W/(m.K))

Density

(kg/m3)

Specific

Heat

(kJ/(kg.K))

Metal Clad - Carbon Steel 43 7801 0.473

Wood Core - Yellow Pine 0.147 640 2.8

Fiber, insulating panel 0.048 240

2.6.2 Ambient Conditions and Other Constants

Table 5 lists the internal and external ambient conditions, and Table 6 lists other

constants and indices used in the exercise.

Table 5 Ambient Conditions

Temperature 300 K

Relative Humidity 50 %

Pressure 101300 Pa

Elevation 0

Wind Speed 0
8

Table 6 Other Constants and Indices

Constriction coefficient for flow through

door

0.68

Convective heat transfer coefficient

(assumed the same for all surfaces)

15 Wm-2K-1

Lower Oxygen Limit 12 %*

*The fire source should pyrolyze at a rate corresponding to the specified heat release rate in Part II if

oxygen depletion terminates combustion, i.e., the mass loss rate of the fuel is fixed rather than the "true"

heat release rate associated with the oxidation process.

2.7 Heat Release Rates and Target Model

The following are the heat release rate data used for the two parts of the exercise.

2.7.1 Part I

The heat release rate for a 0.121-m3

 (2-gallon) trash bag fire (Lee, 1985, & Van

Volkinburg, 1978) that was used for Part I of the exercise is characterized in Table 7. A

linear growth between the data points was assumed for the calculation.

Table 7 32 Gallon Trash Bag Fire

Fire

Growth

Time

(minutes)

Heat Release

Rate (kW)

1 200

2 350

3 340

4 200

5 150

6 100

7 100

8 80

9 75

10 100

The trash bag consists of: (1) straw and grass cuttings (1.55 kg); (2) eucalyptus duffs

(2.47 kg); and (3) a polyethylene bag (0.04 kg). The contents were thoroughly mixed,

and then placed in the bag in a loose manner before ignition. The trash bag was

approximated as a cylinder with a diameter of 0.49 m, and height of 0.62 m. A fraction

of 0.3 for heat released as radiation was assumed, and the heat of combustion of the

trash bag material is 24.1 MJ/kg.
3

 The 1 MW to 3 MW range was chosen as bounding values for a stack of 3 cable trays. Considering a heat of

combustion of 25 MJ/Kg and a surface controlled specific mass loss rate of about 3 g/m2

-sec for cables that pass the

IEEE tests, a cable tray 15 m long and 0.6 m wide will have an effective heat release rate of 0.9 MW. An earlier

study (NUREG/CR-4230), and fire tests reported in EPRI NP-2660 and EPRI NP-2751 also concluded that the peak

heat release rate for a cable tray is limited from 0.8 MW to 2 MW for a well ventilated room. 

4

 EdF CNPP tests (1997)

9

The trash bag and the target (representing the tray A) were assumed to be at the center

of the cable tray lengths. In order to conduct a simplified and conservative analysis, a

single power cable with a diameter of 50 mm at the bottom left corner of the cable tray A

was assumed as the target. For models in which the target is represented as a

rectangular slab, the slab was assumed to be oriented horizontally with a thickness of

50 mm. The cable was assumed to ignite when the centerline of the cable reaches 643

K.

2.7.2 Part II

Predicting the heat release rate of a burning cable tray stack is extremely complex, and

current models are not capable of realistically predicting such phenomena. Therefore,

the mass loss rate of the burning cable tray stack was defined as input in the exercise.

The consecutive ignition and burning of all 3 cable trays (trays A, C2, and C1) were

modeled as one fire. The analyses were conducted assuming a peak heat release rate

for the whole cable tray stack3

 between 1 MW – 3 MW. A t-squared fire growth with t0

= 10 min, and Q0 = 1 MW was assumed4, where:

Q=Q0 (t/t0)

2

The cable fire was assumed to last for 60 minutes at the peak heat release rate, and

decay in a t-squared manner with similar constants as for growth.

For point source calculations, the heat source (trays A, C2, and C1) was assumed to be

at the center of the cable tray length and width and at the same elevation as the bottom

of tray C2. For 3-D calculations, the fire source was assumed to be the entire length of

tray C2 (15.2 m), width (0.6 m), and height of 0.24 m (0.08 x 3). The target

(representing tray B) was assumed to be at the center of the cable tray length. In order

to conduct a simplified and conservative analysis, the target was assumed to be a

single power or instrumentation cable, without an electrical conductor inside the cable,

and with a diameter of 50 mm or 15 mm respectively at the bottom right corner of cable

tray B. For models in which the target is represented as a rectangular slab, the slab

was assumed to be horizontally oriented with a thickness of 50 mm or 15 mm. The

cable was assumed to be damaged when the centerline of the cable reached 473 K.
5

The oxygen present in the fuel was neglected in the calculation of the oxygen concentration in

the compartment.

10

2.8 Cases for Exercise

The following defines the cases for Part I and II of the exercise.

2.8.1 Part I

For the base case, the distance between the midpoints of the trash bag and tray A was

2.2 m (.7 ft), the door was closed, and mechanical ventilation system was off. In order

to facilitate comparisons of code results, simulations for horizontal distances between

the trash bag and tray A of 0.3, 0.9, and 1.5 (.1, . 3, and . 5 ft) were conducted (Cases

1–3). Simulations were also conducted with (a) the door open and mechanical system

turned off; and (b) mechanical ventilation system on and the door closed (Cases 4-5). 

Table 8 provides a summary of the cases analyzed in Part I.

Table 8 Summary of Cases for Part I

Fire Scenario Distance from Fire (m) Door Ventilation System

Base Case 2.2 Closed* Off

Case 1 0.3+

Case 2 0.9

Case 3 1.5

Case 4 Open

Case 5 On

* For simulations with the door closed, a crack (2.4 m x 0.005 m) at the bottom of the doorway was

assumed.

+

A value in a cell indicates the parameter was varied from the base case.

The maximum horizontal distance between the trash bag and tray A, which results in

the ignition of tray A, was to be determined by the extrapolation of results for the

simulations with the door closed and mechanical ventilation system off (Base Case to

Case 3). 

The resulting centerline temperature (CL) of the cable was calculated for these

simulations. In addition, the following parameters were reported:

• Upper layer temperature

• Lower layer temperature

• Depth of the hot gas layer

• Heat release rate

• Oxygen content5 (upper and lower layer)

• Flow rates through the door and vents
11

• Radiation flux on the target

• Target surface temperature

• Total heat loss to boundaries

For CFD and lumped-parameter models, the profiles at the midpoint of the room were

presented. All results are presented in SI units.

 

2.8.2 Part II

For the base case, the heat release rate for the cable tray stack was 1 MW, reaching

peak heat-release rate and decaying as specified above. The horizontal distance, D,

was 6.1 m (20 ft). The door was closed and the ventilation system was off. The target

was a power cable 1.1 m (3.5 ft) above tray A. The distance, D, was varied to 3.1 (.10

ft), and 4.6 m (.15 ft) for Cases 1 and 2. The peak heat release rate for the cable tray

stack was varied at 2 MW, and 3 MW (reaching a peak heat-release rate and decaying

as specified above) at a horizontal distance, D, of 3.1, 4.6, and 6.1 m (Cases 3-8). The

door was closed and ventilation system operating initially; and the door opened, and

ventilation system shut after 15 minutes in Case 9. The door and ventilation system

was open throughout the simulation in Case 10. Two elevations for tray B were

analyzed to examine the possible effects of the ceiling jet sublayer and the elevation of

the target: (1) 2.0 m (6.5 ft) above tray A, (i.e., 0.3 m (1 ft) below the ceiling)in Case 11;

and (2) at the same elevation as tray A in Case 12. An instrumentation cable with a

diameter of 15 mm was used in Case 13.

The resulting centerline temperature of the target, and time to damage of the target,

were to be calculated for these analyses. In addition, the following parameters were

reported:

• Upper layer temperature

• Lower layer temperature

• Depth of the hot gas layer

• Heat release rate

• Oxygen content (upper and lower layer)

• Flow rates through the door and vents

• Radiation flux on the target

• Target surface temperature

• Total heat loss to boundaries

• Chemical species (CO, HCl, soot) in the upper layer

• Optical density of smoke (optional)

For CFD and lumped-parameter models, profiles at the midpoint of the room were

reported. All results were presented in SI units.
12

Table 9 Summary of Cases for Part II

Fire

Scenario

HRR

(MW)

D (m) Door Position Mech.

Vent. Sys.

Target Target

Elev. (m)

Base

Case

1 6.1 Closed*

Off Power

Cable

1.1 

Case 1 3.1+

Case 2 4.6

Case 3 2 3.1

Case 4 2 4.6

Case 5 2 6.1

Case 6 3 3.1

Case 7 3 4.6

Case 8 3 6.1

Case 9 Open>15 min Off>15 min

Case 10 Open On

Case 11 2.0

Case 12 Same

Case 13 Instrument

Cable

* For simulations with the door closed, a crack (2.4 m x 0.005 m) at the bottom of the doorway was

assumed.

+

A value in a cell indicates the parameter is varied from the base case.
13

3 Input Parameters and Assumptions

In accordance with the procedure established for the benchmark exercise presented

above, efforts were made by the participants to arrive at a consensus on values for all

the input parameters needed for the various codes to be used in the exercise. The

following is a summary of the main issues that arose in the consideration of input

parameters and assumptions for the scenarios in the exercise, and how participants

decided to dispose the issues.

3.1 Summary

Three main issues arose regarding input parameters and assumptions for the fire

scenarios in the benchmark exercise:

A. Specification of the fire source;

B. Modeling of the target in the compartment; and

C. Lower oxygen limit (LOL).

The specification of the fire source is fundamental to the input for fire models, and can

significantly affect the predicted compartment thermal environment. A consensus was

reached on the characterization of the heat release rate (HRR) for the fire scenarios for

the benchmark exercise. However, it was noted that presently there is a lack of a 

consolidated source of information or guidance from where one can select data for heat

release rates for different NPP fire scenarios. Although agreement was reached on the

specification and values for the target model and LOL to be used for the benchmark

exercise, participants did not reach a consensus on the most appropriate specification

that could be recommended for model users. The specification of the above three

parameters could lead to “user effects,” and are the largest sources of uncertainty in the

predicted results from the input parameter specification process for the types of fire

scenarios examined in the benchmark exercise. These three main issues are

summarized below followed by a discussion of other issues of importance.

3.2 Main Issues

1. HRR Curves for Cable Tray Fires:

Predicting the HRR of a burning cable tray stack is extremely complex, and current

models are not capable of realistically predicting such phenomena. Therefore, it is

recommended that the HRRs of the burning cable tray stack be defined as input in the

problem. For the benchmark exercise, the consecutive ignition and burning of all three

cable trays (trays A, C2, and C1) were modeled as one fire. The analyses assumed

peak HRRs for the whole cable tray stack between 1 MW and 3 MW. The 1 MW to 3

MW range was chosen as bounding values for a stack of 3 cable trays. Considering a

heat of combustion of 25 MJ/Kg and a surface controlled a specific mass loss rate of
14

about 3 g/(m2.s) for cables that pass the IEEE-383 tests, a cable tray 15 m long and 0.6

m wide will have an effective HRR of 0.9 MW. An earlier study (NRC, 1985), and fire

tests reported in EPRI (1992) and EPRI (1983) also concluded that the peak HRR for a

cable tray is limited from 0.8 MW to 2 MW for a well-ventilated room. The growth

characteristic of cable tray fires depends on the fire source, cables ignited with liquid

combustibles result in rapid growth, whereas cables ignited by another cable tray fire

result in slower growth. Based on tests conducted by EdF (Grondeau, 1997), a tsquared growth was assumed with t0 = 600 s, and Q0 = 1 MW, where:

& & Q Qtt = 0 0 (/ ) 2

A fire duration of 60 min at peak HRRs was assumed, followed by a t-squared decay

with similar constants as for growth. The experiments conducted by EdF have shown

that peak HRRs for cable tray fires generally do not last more than 60 minutes. 

Given the complexity of modeling flame spread, and the developmental state of flame

spread models, it is recommended that current fire modeling analyses use heat release

rates derived from tests conducted that have configurations similar to that being

analyzed.

The development of a comprehensive database of heat release rate test data for

combustible materials in NPPs will be beneficial for the broader application of fire

models for NPP fire safety analysis. Further, HRR’s to be used for specific NPP fire

scenarios will need to be established to avoid “user effects.”

2. Cable Target Model and Dysfunction Temperature

A detailed heat transfer model for a cable tray will be fairly complex. Cable trays

generally have a number of cables bundled together in layers, and most cables consist

of several conductors. Cables configured in a single layer will get damaged and ignite

at a lower flux than cables in a multilayer configuration because the flux to a single layer

will not be shielded by cables above that layer. The damage or ignition temperature for

cables in a multilayer configuration will depend on the volume-to-surface area ratio. 

Generally, current fire models are not capable of modeling complex cable

configurations. As stated above in Chapter 2, for simplicity the target in the benchmark

exercise was assumed to be one power cable conservatively composed only of PVC. 

Some of the codes used for the benchmark exercise have simple one-dimensional slab

models for targets, and others have incorporated a 1-D radial model to approximate

radial heat transfer in cables. 

As stated in Chapter 2, simulations were conducted for power cables (50 mm

diameter), and instrumentation cables (15 mm diameter). For models in which the

target is represented as rectangular slabs, the slabs were assumed to be oriented

horizontally with a thickness of 50 mm and 15 mm correspondingly. Some participants

expressed concern regarding the adequacy of a one-dimensional target model since the
15

incident radiative flux would vary with the orientation of the slab. Also, the specification

of the slab thickness, and selection of the criterion for cable damage (surface

temperature versus centerline temperature) would be key to the success of a onedimensional target model. The cable surface temperature is not indicative of the effects

of the thermal environment on cable functionality. Experiments in the PEPSI tests

conducted by IPSN indicate that the temperature of the PVC insulation immediately

surrounding the electrical conductors reaches about 473 K when cable malfunctions

occur (Such, 1997). This corresponds to the temperature at which the PVC insulation

softens. Experience from experiments conducted at VTT, indicated that the centerline

temperature of a target slab, with a thickness equal to the diameter of the cable, best

approximates the temperature of the PVC insulation surrounding the individual

conductors. However, some participants felt that the slab dimensions specified for the

benchmark exercise may be too thick and result in the simulation of a larger thermal

inertia of the target than exists in reality.

This issue is discussed further later in this document when the results of the analyses

are presented, and the effect of the cable target model on the results is examined.

3. Lower Oxygen Limit

In order to conduct a conservative analysis, some participants advocated the use of a

value of zero for the LOL. This proposal was put forth based on experimental

observations which indicated that it was difficult to determine an LOL value because of

the complexity of the combustion phenomena, and effects of ventilation on combustion. 

Other participants felt that setting LOL at 0% for cases which were developed to

examine the effects of ventilation will be contradictory, and for other cases would not

yield best-estimate results. Based on this premise, it was suggested that the LOL be

set at 12% in order to examine these effects. Several participants in the exercise

conducted the analyses of the cases with LOL set at 0% and 12 % to determine the

effect. The impact of LOL on the results will be discussed later in this report.

3.3 Other Issues

4. Chemical Properties of Combustible Sources

Generally, fire models require the specification of the chemical properties of the fire

sources, and the species yielded in the combustion process. Such yields affect the

emissivity and absorption of radiation by the hot gas and may be important. The

content of the trash bag fire source was specified for the benchmark exercise as

composed of: (1) straw and grass cuttings(1.55 kg); (2) eucalyptus duffs (2.47 kg); and

a (3) polyethylene bag (0.04 kg). These contents were thoroughly mixed, and then

placed in the bag in a loose manner before the heat release data was obtained in the

tests. However, the chemical properties of the grass cuttings in the trash bag were not

available and specified for the exercise. This was a limitation since the chemical

properties of the fuel were necessary input for the fire models, especially in the
16

calculation of radiation from the hot gas. Several analysts assumed the trash bag to

contain wood for which the properties were available.

The cable insulation was assumed to be polyvinyl chloride (PVC), and its chemical

properties were available. The chemical formula of PVC is C2H3Cl, and the oxygen-fuel

mass ratio is 1.408. The yields (mass of species/mass of fuel) are 0.46 for CO2, 0.063

for CO, 0.5 for HCL, and 0.172 for soot.

The development of a comprehensive database of chemical properties of combustible

materials in NPPs will facilitate the modeling of specific fire scenarios.

5. User Effects

As proposed in the procedure for the benchmark exercise, analysts discussed and

agreed on the input data for the various codes that will be used in the benchmark

exercise. The goal was for participants to analyze the same problem and minimize the

variation of results due to differing input data. Even with such efforts to minimize “user

effects,” some effects were evident in the benchmark exercise. “User effects,” and their

impacts are discussed later in the document after the results are presented.

6. Corner/Wall Effects

In practice, cable trays are installed nearer than 0.9 m from walls as specified in the

proposed benchmark exercise. Also, transient combustibles may be present in the

corner or along walls. In order to minimize the number of cases for the benchmark

exercise, corner/wall effects were not examined. Corner/wall effects may be important

for specific configurations when combustibles are near a corner or wall, and it is

recommended that their impact on the results be examined.

7. Conditions Outside Compartment

In NPPs, doors in most compartments typically open to another compartment, and not

to the outside ambient conditions. In order to simplify and make feasible the evaluation

of model effects, multi compartment analysis was not included in the benchmark

exercise since that would include additional considerations and effects on the results. 

In modeling realistic fire scenarios, the conditions outside the compartment may be

important, and it is recommended that such effects be examined.

8. Constriction or Orifice Coefficient for Vents

Based on expert opinion of the participants, it was decided that a value of 0.68 used in

some computer codes will be used for the benchmark exercise. The adequacy of this

value is discussed later in the document when the results are presented.
17

9. Convective Heat Transfer Coefficient

Based on expert opinion of the participants, it was decided that the convective heat

transfer coefficient would be set at 15 W/m2

K for the benchmark exercise. The

adequacy of this value is discussed later in the document when the results are

presented.

6

The concept of safe separation distance is not directly applicable in all countries.

19

4 Results of Analyses

The following presents a summary of the results that were sought in the benchmark

exercise presented in Chapter 2. The main results for the ignition of a cable tray by the

trash bag fire, and damage of cable trays of redundant safety systems are presented in

Section 4.2. This is followed by a discussion in Section 4.3 on an assessment of the

adequacy of the physical models used in the codes for the specific scenario by

examining and comparing the trends of the output variables.

The detailed results of the analyses for the benchmark exercise conducted by

participants using different fire models are presented in Appendices A through I.

4.1 Summary of Results

4.1.1 Part I

None of the analyses conducted for the benchmark exercise predicted the ignition of the

target cable (at 643 K) by the postulated trash bag fire for any of the ventilation

conditions in the room. The predicted temperatures for all the cases in Part I are very

similar. Given the dimensions of the room and the heat release rate of the trash bag, the

maximum surface temperature of the target outside the fire plume region for all the

cases analyzed is less than 350 K. The target cable may ignite only if it is in the fire

plume region of the fire. The temperature of the target cable is predicted to significantly

increase when the distance between the trash bag and cable is between 0.4 m and 0. 5

m and the target becomes exposed to the high plume gas temperature. The predicted

maximum surface temperature of the target in this region is predicted to be . 550 K. 

Although the maximum predicted heat flux from the plume incident on the target is

predicted to be . 14 kW/m2, the duration of the exposure is not long enough to increase

the surface of the cable to the ignition temperature. Based on this, one could establish

a minimum horizontal safe separation distance6

 of 1.0 m between the trash bag and the

target cable. A fire of similar intensity sustained over a longer period could ignite the

cable.

4.1.2 Part II

The predicted maximum temperatures of the target cable were below 400 K for all the

cases analyzed in Part II. The cable tray fire was limited between 10 min and 15 min by

the depletion of oxygen near the cable tray. Given the elevation of the fire source and

the predicted extinction of the fire, cable damage is unlikely for the scenarios examined. 

The analysis of an elevated fire source is key to the accuracy of the predicted result.
20

4.2 Verification of Sub-models

This section mainly discusses the verification of the sub-models based on an

examination and comparison of the trends from the different fire models used in the

exercise. Verification is defined here as the process of determining that a model

implementation accurately represents the developer’s conceptual description of the

model and the solution to the model. Validation, which is discussed in Section 4.3, is

defined as the process of determining the degree to which a model is an accurate

representation of the real world from the perspective of the intended uses of the model

(AIAA, 1998). This section includes the comparison of the magnitudes of the

parameters predicted by different fire models. These comparisons will be summarized

and discussed in Section 4.3.

The benchmark exercise was aimed mainly at comparing zone models since there is

more experience with these models in NPP applications. Therefore, this report mainly

addresses zone models and their sub-models. In some instances, comparisons are

made with CFD and lumped-parameter models in order to derive insights regarding the

model assumptions in the different approaches. Experience with fire models that have

been used for the first time for the type of problem posed in the benchmark exercise is

discussed. The advantages of more advanced approaches, compared to the two-zone

approach, are discussed in Chapter 5.

The following is a list of the major sub-models implemented in the two-zone fire

computer codes for modeling the physical phenomena in the scenarios:

! combustion chemistry (tracking concentrations of oxygen and combustion

products)

! plume and ceiling jet flow

! mass and energy balance in the two zones (stratification)

! ventilation through doors and cracks

! forced ventilation

! heat transfer to boundaries

! heat transfer to targets

! thermal response of the target

4.2.1 Part I

The measured heat release rate of the trash bag fire which was used as input for Part I

is shown in Figure 2. The peak heat release rate for the trash bag fire is . 350 kW, and

peaks at . 150 s.

Base Case 

Figure 3 shows the plume flow development during this scenario predicted by some of

the fire models used in the exercise. The main plume flow increases rapidly at the
7

The oxygen concentration output by the MAGIC code is the mass fraction, whereas the other

codes output the mole fraction.

21

initiation of the fire, and does not follow the fire heat release rate, as expected. This is

due to the nature of the correlations used in the codes. CFAST over predicts mass

entrainment at the initial stages of the fire because of the plume height used in the

calculation of the entrained air. Initially, the plume height is assumed to be from the fire

to the ceiling. This leads to an over prediction of the initial mass flow to the upper layer,

and the rate of descent of the gas layer interface. The peak plume flow from the

CFAST (BRE) analysis is less than that from the CFAST (NRC) analysis because of the

assumed height of the fire (on the floor in CFAST (NRC) versus at the height of the top

of the garbage bag (0.62 m) in CFAST (BRE)). This difference is caused by a “user

effect” and is discussed further in Section 5. The peak plume flow predicted by

FLAMME_S is less than CFAST by a factor of . 2. Table 10 lists the peak plume flow

predicted by the various fire models that were used in the exercise. Plume flow is not a

normal output parameter from MAGIC. Plume flow is not directly computed in CFD and

lumped-parameter models.

Figure 4 shows the predicted hot gas layer development predicted by some of the fire

models used in the exercise. The interface height decreases rapidly initially due to high

plume flow (see Figure 3). The rate of descent of the interface height decreases after .

230 s when the HGL temperature has peaked (see Figure 8). Because of the two-zone

assumption, the hot gas layer is prevented from reaching the floor due to air inflow at

the crack below the door caused by a negative pressure in the compartment (see Figure

7). In reality, the hot gas layer is expected to reach the floor in parts of the room

farthest from the door. CFAST predicts a more rapid descent of the HGL interface than

FLAMME-S because of the higher predicted plume flow as shown in Figure 3. The

trend of HGL development predicted by the fire models used in the exercise are as

expected, given the two-zone assumption in the zone models. The HGL interface height

is not directly computed in CFD and lumped-parameter models.

Figure 5 shows the oxygen depletion for the Base Case predicted by the fire models

used in the exercise. The oxygen concentration in the upper layer decreases by . 1%

to 19.2 % generally7

. The oxygen depletion predicted by the various models is similar. 

The fire will not be limited by oxygen in this fire scenario for the assumed HRR of the

fire and dimensions of the room. 

Figure 6 shows the pressure development predicted by the fire models used in the

exercise, and Figure 7 shows the resulting flows in and out of the compartment. The

pressure is predicted to peak at . 150 s when the fire heat release rate peaks, as would

be expected. At some point after the fire peaks, the heat released into the compartment

by the fire is less than the heat loss through the concrete walls (see Figure 10 for a
8

The unsteady behavior of the curve is due to the numerical derivation of the integral heat inside

the wall and door structure.

22

typical heat loss trend8) resulting in the decrease of compartment temperature and

pressure. The pressure swings to a negative value resulting in flow into the

compartment through the door crack. The predicted peak in the outflow is consistent

with the pressure profile, and the outflow goes to zero when the pressure in the

compartment is less than the outside. The predicted initiation of inflow is consistent with

the pressure profile, and is much less than the outflow. Table 10 lists the peak pressure

and lower layer outflows that were predicted by the various fire models used in the

exercise. The peak over-pressure predicted generally varies between 600 Pa to 2000

Pa, resulting in an outflow of 0.4 kg/s to 0.6 kg/s from the crack under the door. The

pressure evolution predicted by JASMINE is discussed by Miles (Appendix G) and was

found to be sensitive to the heat release mechanism and amount of heat lost to the

boundaries. The trends of pressure and vent flow predicted by zone, CFD, and lumpedparameter fire models used in the exercise vary by a factor of . 3 and 1.5, respectively.

Figure 8 shows the hot gas layer (HGL) temperature. The upper layer temperature

peaks at . 200 s, about 50 s after the fire peaks, when the heat released into the

compartment is less than the heat loss from the concrete walls. Table 10 lists the peak

HGL temperatures predicted by the various fire models that were used in the exercise. 

The predicted peak temperature is between 330 K to 360 K. Therefore, in this scenario,

the upper layer temperature is predicted to increase by only about 30 K to 60 K. The

maximum temperature in the HGL under the ceiling is predicted to be between 400 K to

450 K by JASMINE, FDS, and COCOSYS. The trend of the HGL temperature predicted

by the various fire models (zone, CFD, and lumped-parameter) used in the exercise is

similar and as expected. The predicted peak HGL average temperature varies by up to

50 %.

One important difference in the results from the zone, CFD, and lumped-parameter

codes for the type of scenarios examined for the Benchmark Exercise is the hot gas

temperature. A two-zone code, calculates the average temperature of the hot gas layer,

whereas CFD codes compute the entire temperature profile in the compartment. The

peak average HGL temperature predicted by zone models for the Base Case is . 350

K. The temperature profiles that were predicted by CFD codes for this case ranges

from . 350 K in the lower region to . 400 K in the upper region of the hot gas. This

temperature gradient in the hot gas will determine the convective heat flux to the cable

tray depending on its vertical position and may become more prominent and important

for scenarios with a high fire intensity. 

Figure 9 shows the target surface temperatures predicted by the fire models used in the

exercise. The target temperature is predicted to peak at . 250 s, approximately 100 s

after the fire and target flux reaches its peak due to the thermal inertia of the target. 

The trend of the target surface temperature predicted by the various fire models used in
23

the exercise is similar and as expected. Table 10 lists the peak flux and temperature of

the target. The low thermal conductivity of PVC induces a strong temperature gradient

between the surface and center of the cable. The target surface temperature is

generally predicted to only increase . 20 K for this case. It should be noted that,

although not evident in the results for this case, the fire models utilize different

approaches for calculating the heat flux incident on the target. The target is modeled as

a slab in CFAST. The orientation specified for the slab will determine the incident flux

on it (Miles:Appendix G) and may be a source of “user effects.” This is discussed

further in Chapter 5. The target is also modeled as a slab in FLAMME_S (see

Bouton:Appendix A). MAGIC and COCOSYS employ a 1-D radial model for cable

targets in order to eliminate the need to specify the orientation of a slab and improve the

predictive capability. CFX includes a 3-D conduction model for the target. The

predicted fluxes on the target by these models will vary because of the different

assumptions and approaches embedded in them.

Cases 1, 2 and 3: Effect of Distance

Cases 1, 2 and 3 examine the effect of the distance between the target and fire on

target heating. The heating of the cable in this scenario is mainly due to the radiative

heat flux from the fire and the convective heat transfer from the hot gas. Figure 11

shows the typical evolution of the target surface temperature for various distances (d)

between the fire and target. The target surface temperature peaks at . 200 s, . 50 s

after the fire reaches its peak intensity due to the thermal inertia of the target. The

increase in target surface temperature between distances (d) of 0.9 m and 0.5 m is due

to the increase in radiative flux from the fire that is incident on the target. Figure 12

shows the typical strong effect of distance on the radiative flux incident on the target. 

The target is within the plume region at a distance of . 0.4 m and is heated by

convection by the hot plume gas. Target heating in the plume region is not currently

modeled in CFAST. The MAGIC code provides an option for a side calculation of target

heating in the plume region. The heating can be calculated by hand using plume

correlations. CFD codes can calculate target heating based on the principal

formulations in the approach which does not explicitly require an empirical plume model. 

In lumped-parameter approaches, the plume is not really modeled and therefore the

form of the plume is dependent on the nodalization around the fire (KleinHessling:Appendix F). Also, momentum is not balanced in the lumped-parameter

approach. Figure 13 graphically illustrates the exposure of the target in the plume

region in a CFD analysis.

Tables 11, 12 and 13 lists the peak fluxes and target surface and centerline

temperatures predicted by the fire models used in the exercise. The Tables indicate

that the target does not reach the ignition temperature even when it is in the plume

region according to the criteria established for ignition, i.e., target centerline temperature

of 643 K. The tables again indicate the strong gradient between the target surface and

centerline due to the low thermal conductivity of PVC. As indicated above, it should

also be noted here that the fire models used for the benchmark exercise utilized
24

different approaches for calculating the heat flux incident on the target. The result of the

different approaches is evident in Tables 11, 12 and 13. In Case 1, some of the fire

models include a calculation for target heating in the plume region (e.g., FLAMME_S

and CFX).

Cases 4 and 5: Effect of Natural and Mechanical Ventilation

The following presents some key features of the results of Cases 4 and 5. Figure 14

shows a typical development of the interface height for Case 4 versus the Base Case. 

The interface height approaches a constant value at . 140 s, after the HGL reaches the

top of the door at . 100 s. Figure 15 shows a typical development of the upper layer

outflow and lower layer inflow after the HGL interface reaches the door at . 100 s,

indicating the establishment of a neutral plane below the top of the door (at . 2.2 m). 

Figure 18 is a typical vector plot of temperature in a plane parallel to the cable trays at

the midpoint of the room (and the door), and illustrates the typical flow patterns

predicted by a CFD code for Case 4 in which the door is open. Outflow and inflow at

the door around the neutral plane are illustrated, as also predicted by the zone models. 

Figure 16 shows typical HGL temperature development for Cases 4 and 5. The HGL

temperature for Case 4 is less than the Base Case after . 270 s because of the outflow

of hot gas from the upper layer (which reaches its peak value at . 200 s) through the

door, and higher plume flow. The HGL temperature for Case 5 is less than that in the

Base Case after . 100 s when the HGL reaches the mechanical vents, and ambient air

is injected into and hot gas ejected from the hot gas layer in the two-zone formulation.

Figure 17 shows a typical development of flows in the mechanical ventilation system

(for Case 5) simulated by zone models. The transitions in flows from the mechanical

vents in and out of the gas layers occurs at about . 100 s when the HGL reaches the

mechanical vents. Figures 19, 20, and 21 show typical flow patterns predicted by CFD

models that can be caused by the mechanical ventilation. This type of information will

be useful for examining the local effects of ventilation on target heating, where

assuming the target is exposed to the average conditions of the HGL will yield

conservative results. 

The above indicates that the predicted flow patterns for natural and mechanical

ventilation by both zone, CFD, and lumped-parameter models are similar, as expected. 

CFD models have the advantage of providing more detailed flow information for

examining local effects.

Tables 14 and 15 list the peaks of some parameters predicted by the fire models used

in the exercise. The natural ventilation through the door (Case 4) and mechanical

ventilation (Case 5) do not have a strong effect on the target temperature which is in the

HGL. The target surface temperature for Case 4 and 5 is less than in the Base Case

because of cooler hot gas layer temperatures, but by only 2 K to 4 K of a total increase

of 20 K. The predicted peak outflow from the door for Case 5 ranges from 0.4 to 1.3

kg/s. The variation in the predicted outflow is generally consistent with the variation in
25

the plume flows listed in Table 10. The predicted oxygen concentration in Case 5 is

consistently slightly higher than the Base Case due to inflow of ambient air into the

HGL. The maximum variation in the predicted HGL temperature by the various codes is 

. 45 % for Case 4, and . 30 % for Case 5. 

Conclusion

The international panel determined that the above analysis of the results for Part I

demonstrate that current zone, CFD, and lumped-parameter fire models provide a

comprehensive treatment of most physical phenomena of interest in the scenarios

analyzed. The results indicate that the trends predicted by the sub-models are

reasonable for the intended use of the models for analyzing the specified scenarios. 

The results of the analyses for the specified scenarios provide useful insights for

nuclear power plant fire safety analysis.
26

4.2.2 Part II

Base Case

Figures 22 to 26 show the predicted results of the main parameters of interest with the

fire models used for the benchmark exercise. Figure 27 shows a typical result of the

species concentrations predicted by the fire models, and Figure 28 shows the pyrolysis

rate specified for the case.

The predicted trends for the heat release rate, interface height, and oxygen

concentration in Figures 22, 23, and 24 are collectively examined. The fire models

predict the HGL lowers to the fire source (at an elevation of 3.4 m) between 200 s and

400 s. This variation is due to the different approaches used in modeling the fire source

(e.g., the cable tray is divided into 10 fire sources in the FLAMME_S analysis). The fire

models predict the heat release rate decreases rapidly between 500 s and 700 s when

the oxygen concentration in the HGL reaches the LOL of 12 % specified for the

exercise. The variation of the predicted time at which the fire is extinguished is due to

slight variations of the predictions of oxygen concentration in the HGL. It should be

noted that the MAGIC (CTICM) and COCOSYS utilized LOL values of 0 % and 4 % for

the analyses. The effect of a lower LOL on the heat release profile is evident in Figure

22 which shows the fire is sustained over a longer period. The HRR predicted by

COCOSYS is sustained even longer due to the higher predicted oxygen concentration

as seen in Figure 24. Fluctuations in the HRRs predicted by CFAST (shown in Figure

22) are due to the movement of the interface height around the fire source as shown in

Figure 23. The extinction models utilized in all the computer codes are approximations

of the interaction of the complex combustion process with a limited oxygen environment. 

Therefore, the results represent an approximation of the conditions expected for this fire

scenario.

The HGL profiles shown in Figure 25 are consistent with the HRR profiles shown in

Figure 22. As listed in Table 16, the fire models generally predict a peak HGL

temperature of . 450 K. The MAGIC (CTICM) and FLAMME_S profiles indicate a

decrease in the slope of the HGL temperature when the HRR becomes constant at 1

MW (see Figure 22). The change in the slope is due to the dynamic balance of heat

addition to the HGL and loss to the boundaries. The peak temperature predicted by

JASMINE and COCOSYS under the ceiling is . 500 K and . 650 K respectively. The

higher prediction by COCOSYS is due to the lower LOL value (4 %) used for the

analysis, however, other modeling assumptions may also account for the difference. 

Table 16 lists the peak flux on the target, and Figure 26 shows the target surface

temperature profiles. As indicated earlier, the fire models utilize different approaches

for computing the heat flux on the target. For example, the effect of the orientation of

the slab in CFAST analyses is seen in Table 16 and Figure 26. The heat flux reported

for COCOSYS is only from convection since radiative fluxes are not calculated for Part

II (Klein-Hessling:Appendix F). The variation of the peak target surface temperature
27

predicted by models with similar predictions of heat flux on the target are due to the fire

HRR and HGL temperature profiles, i.e., the target temperature increase is based on

the duration of its exposure to the environment.

The species concentration predicted by FLAMME_S shown in Figure 27 is consistent

with its predicted HRR profile shown in Figure 22. The production of the species from

combustion is terminated at . 700 s when the fire is extinguished.

The analysis demonstrates the complexity in modeling an elevated fire source which

can be affected by a limited oxygen environment. The assumption for the LOL will have

a significant effect on the predicted peak target temperature. Conservative assumptions

are warranted due to the uncertainty in the extinction models used in the computer

codes.

Cases 1 and 2: Effect of Distance

Tables 17 and 18 list the peak heat fluxes and target temperatures for Cases 1 and 2

reported by the fire models used for the exercise. A consistent trend in the effect of

distance on target heating is not evident from the Tables due to the different

approaches used for computing heat fluxes. The typical strong effect of the distance

between the fire and target on the radiative flux incident on the target was discussed in

Section 4.2.1.

Cases 3 to 8: Effect of Fire Intensity and Distance

As discussed above, the cable tray fire in the Base Case is limited by the oxygen

depletion in the environment. Cable tray fires that could be potentially more intense (as

specified by the pyrolysis rate for these cases) are also limited, i.e., the HRRs are

similar to that specified for the Base Case. Therefore, these cases are not discussed

further here.

Case 10: Effect of Ventilation

Table 19 lists the peak values of the heat flux, and HGL and target temperatures for

Case 10. The peak values predicted by the zone models are generally similar to those

for the Base Case because the fire source is in the HGL. The mechanical ventilation

system inserts ambient air and ejects air for the lower layer in the two-zone formulation

without affecting the HGL. The two-zone approach establishes an artificial boundary

between the two zones. In reality, there will be some mixing of mass between the

zones. Figures 19, 20, and 21 graphically present the effects of mechanical ventilation

on the plume and flow patterns in the compartment predicted by CFD codes. The fire

source could be exposed to higher concentrations of oxygen than the HGL average

predicted by zone models, if the fire source is near a mechanical ventilation inlet vent. 

Conservative values of the LOL could be assumed in analyses with zone models to

account for this uncertainty. 
28

Cases 11 and 12: Effect of Cable Tray Elevation

Table 20 and 21 lists the peak values for heat flux and target temperatures for Cases 11

and 12. The model used for the target cable will determine the manner in which the

target elevation affects the incident heat flux and heating of the cable. As indicated

earlier, different approaches are utilized by the fire models used in the exercise leading

to the variation in results listed in the tables. Generally, a higher target elevation would

expose it to the HGL for a longer period leading to higher temperatures. However, the

effect of target elevation is not significant. It should be noted that the target remains

outside the ceiling jet layer in this scenario. None of the zone models used in the

exercise include a model to predict target heat by the ceiling jet. It will be useful to have

this capability for other scenarios in which the target is located in the ceiling jet.

Case 13: Effect of Target Structure

Table 22 lists peak target surface and centerline temperatures that were predicted by

the fire models used in the exercise. The structure of the cable has a strong effect on

its thermal resistance and heating. The power cable has more thermal inertia and

resists heating for a longer period as compared to the instrumentation cable. Table 22

shows that the peak centerline temperatures for the instrumentation cable for Case 13

are much higher than those for the power cable in the Base Case. Figure 29 shows the

typical temperature profiles for the power and instrumentation cables. The difference

between the core temperature profiles for Case 13 and the Base Case are evident in

the figure. The core temperature of the target is much less than the surface

temperature due to the low thermal conductivity of the cable insulation, PVC (0.092

W/m.K), except for Case 13. In Case 13, the core temperature is much higher because

the diameter of the instrumentation cable is less than that of the power cable by a factor

of three. Also, note that the core cable temperature continues to increase after the

surface temperature has peaked for all the cases. The figure shows that the maximum

temperature (core or surface) is less than the specified damage temperature of 473 K

for all the cases in Part II.

A comparison of the fire duration with the time needed for heat to reach the core of the

target provides an insight as to why the target is not damaged (Bouton:Appendix A). An

estimate of the time taken for the rear face of the target to increase in temperature when

the front face is exposed to a heat flux is given by the formula:

)

c

λ 16(

e

t

2

p

ρ

≈

where e is the wall thickness, 8 the thermal conductivity, D the density, and c the

specific heat. This equation provides a thermal penetration time of 200 s and 20 s for

the power and instrumentation cables, respectively. The duration of the fire is . 720 s
29

for all the cases. For the power cable, the thermal penetration time and fire duration are

of the same magnitude. Therefore, the core of the power cable does not approach the

surface temperatures. For the instrumentation cable, the thermal penetration time is

much less than the fire duration. Therefore, with a short delay, the temperature profile

of the cable centerline is similar to that at the surface.

Special Cases

Since the fire was extinguished after . 720 s and well before 4800 s, the expected

duration of the fire, several participants in the exercise analyzed special cases. These

cases varied slightly but mainly analyzed a cable tray fire at an elevation below the top

of the door. Natural ventilation of the hot gases through the door prevented the HGL

from reaching and extinguishing the cable tray fire. Therefore, a fire that was sustained

at the specified intensity for 3600 s was achieved. Table 23 lists the results of the

analyses. All the cases listed analyzed similar conditions, except Case S3 which

analyzed a 3 MW fire and a shorter distance between the fire and the cable target. 

Case S4 analyzed similar conditions but with LOL set at 0 %.

Figure 30 shows the HGL and target surface temperature development for typical

results from two fire models. Both models predict an initial rapid rise in the HGL

temperature followed by a less rapid increase after the fire intensity has peaked. As

indicated earlier, the change in the slope is due to the dynamic balance of heat addition

to the HGL from the fire and loss to the boundaries. The target surface in these cases

approaches the HGL temperature due to longer exposure of the target to the thermal

environment in the compartment. The difference in the peak HGL temperatures

predicted by the two models is 35 %. The peak HGL temperatures predicted by other

models listed in Table 23 vary by less than this, e.g., the difference between the CFAST

and FLAMME_S predictions is . 17 %. Case S4 produces a less severe condition than

Case S5 because the fire is extinguished after . 900 s even though LOL is set at 0 %

(see MAGIC (CTICM) results in Figure 22).

Table 23 shows that the cable centerline temperatures approach the surface

temperatures for these cases because of the long duration of the fire. The thermal

penetration time of the power cable, 200 s, is much less than the duration of the fire

(sustained for 3600 s) in these cases. Table 23 also shows that the target centerline

temperature exceeds the specified damage criteria of 473 K only for Case S3 which

analyzed a target 3.1 m from a 3-MW fire sustained for 3600 s.

Conclusion

The international panel determined that the above analysis of the results for Part II

demonstrates that current zone, CFD, and lumped-parameter fire models provide a

comprehensive treatment of most physical phenomena of interest in the scenarios

analyzed. The results indicate that the trends predicted by the sub-models are

reasonable for the intended use of the models for analyzing the specified scenarios.
30

The analyses of the scenarios also demonstrate the complexity in modeling an elevated

fire source which can be affected by a limited oxygen environment. The extinction submodels utilized in all the computer codes are approximations of the interaction of the

complex combustion process with a limited oxygen environment. Therefore, the results

from the extinction sub-models represent an approximation of the conditions expected

for the fire scenarios. The assumption for the LOL will affect the predicted peak target

temperature. Therefore, conservative assumptions are warranted due to the uncertainty

in the extinction models used in the computer codes. Also, as indicated earlier, the

target sub-model in some of the computer codes requires the specification of target

orientation by the user. This may result in non-conservative results and "user effects."

This limitation may be overcome by establishing procedures for the use of the models to

obtain conservative and consistent results. The results of the analyses for the specified

scenarios provide useful insights for nuclear power plant fire safety analysis.

4.3 Validation of Models

This section presents a brief discussion of model validation which was defined above as

the process of determining the degree to which a model is an accurate representation of

the real world from the perspective of the intended uses of the model.

4.3.1 Validation Studies and Uncertainty Estimate

The fire models used in the benchmark exercise have all been compared with test data

for fires ranging from 100 kW to 2.5 MW in compartments with volumes ranging from 10 

m3 to 1300 m3 . These comparisons are summarized and referenced in the individual

reports for the fire models included in the appendices. The comparisons are generally

satisfactory, with different accuracies reported for the range of data sets. Gautier

(Appendix C) reports that the difference in temperatures between those predicted by the

model and measured for steady fires is rarely less than 10 K, but predictions that are 50

K or higher are common. The data sets in the validation database include data for the

configuration (power, compartment volume) analyzed in the benchmark exercise

reported here. IPSN has reported (Such, 1997) tests conducted in a compartment with a

volume of 400 m3

 volume and a 1 MW fire for 4200 s. The relative variation of pressure,

temperature, and oxygen concentration predicted by FLAMME_S with test data was

within 20 %. The comparison of cable surface temperature evolution was less

successful due to the compartment vertical temperature gradient in the test data and the

difficulty in measuring the cable surface temperature. The validations of the fire models

conducted to date indicates that they generally provide a reasonably accurate

representation of the real world for the types of scenarios in the benchmark exercise.

Although the exercise reported here did not include comparison of model results with

test data, the analysis reported above did include the comparison of the magnitudes of

the parameters predicted by different fire models. Generally, the predictions were

similar. Models developed independently, if based on the same fundamental laws, are

expected to produce similar results.
31

A distinction is made here between the variability of results due to different assumptions

of input data, either for model coefficients, compartment configuration, or fire source

data, and the uncertainty of model predictions given the inherent approximations

contained in them. As indicated earlier, different assumptions of fire source power can

significantly affect the results from the models. Other important input data are the

thermophysical parameters, e.g., the convective heat transfer coefficient. The

international panel judged that differences in model results due to the uncertainty of the

models is less than differences that can be caused by variations in input data and

assumptions.

4.3.2 Benefit of Extending Validation Database

Although the above discussion proposes a certain degree of confidence in the current

fire models, there are benefits to extending the validation database. As discussed in

previous sections, the sub-model for the target, and issues regarding the thermal

environment of the target, is a source of uncertainty for these types of scenarios. As

indicated in the analysis of the results, the target response is sensitive to the magnitude

and duration of the heat flux incident on it. A target may be more sensitive to the

duration of the exposure than the magnitude of the heat flux and intensity of the thermal

environment if it has a high thermal inertia. It will be useful to conduct international

collaborative validation exercises in which the sensitivity of target response is explored

and the predictive capability of target damage is the main focus of the program. Also,

more refined measurements and data analyses will be useful to estimate the

quantitative uncertainties of the parameters predicted in the analyses of these fire

scenarios. The computer code results, with quantitative estimates of the uncertainties in

the predicted parameters, will extend the confidence in the models for supporting

engineering judgments in nuclear power plant fire safety analysis.

33

5 General Conclusions and Recommendations

This final chapter provides a discussion of the general conclusions and issues derived

from the benchmark exercise.

5.1 Capabilities and Limitations

As indicated above, the international panel determined that the analysis of the results of

the benchmark exercise demonstrates that current zone, CFD, and lumped-parameter

fire models provide a comprehensive treatment of most physical phenomena of interest

in the scenarios analyzed. The results indicate that the trends predicted by the submodels are reasonable for the intended use of the models for analyzing the specified

scenarios. The results obtained from these fire models can provide useful insights for

nuclear power plant fire safety analysis for the type of scenarios analyzed.

Capabilities

The constitutive equations for mass and energy in the fire models provide a reasonable

prediction of the hot gas layer development and temperatures in the compartment. The

fire models generally provide an adequate method to balance and estimate the

concentration of oxygen and combustion products in the compartment. Mass flows that

result from the pressurization of the compartment, and natural or mechanical ventilation,

are reasonably predicted for the zone, CFD, and lumped-parameter models. Convective

and radiative heat fluxes to the boundaries and target are comprehensively treated in

the models. The thermal response of the target is also adequately estimated in the

models.

Limitations

Fire Source

The mass loss rate in the models is generally not coupled with the thermal behavior of

the source. This limitation necessitates the specification of the mass loss rate profile.

The heat release rate is then calculated in the model based on the availability of

oxygen. The coupling of mass loss and heat release, which entails modeling the

combustion process, is complex and difficult, especially for solid fires. Until further

research is conducted and accurate models developed to overcome this limitation,

characteristic mass loss rate profiles will need to be developed and specified. An

international effort to develop standardized mass loss profiles is recommended.

A related limitation exists for the extinction sub-models utilized in the computer codes.

The sub-models used are approximations of the interaction of the complex combustion

process with a limited oxygen environment. The results from the extinction sub-models

represent an approximation of the conditions expected for the fire scenarios. Some
34

tests have shown that fires can be maintained at low oxygen concentrations through the

establishment of flames distant from the source. Conservative assumptions for the LOL

may be warranted to compensate for the limitations in the extinction models used in the

computer codes. Participants in the exercise reported here used an LOL value ranging

from 0 % to 12 % based on their experience and judgment, and degree of conservatism

needed for the analysis. It is recommended that users of fire models determine an

appropriate value based on the ventilation conditions for their application, scenario

configuration (single versus multi-compartment), and desire for conservatism in the

analysis. A sensitivity analysis for different LOL values may be appropriate for a bestestimate calculation.

Target Model

The fire models generally include a simple sub-model for the target that allows the

modeling of one cable. This is acceptable as long as the goal of the analysis is to

provide a conservative estimate. The modeling of a cable bundled with other cables in a

tray will result in lower cable temperatures. The ability to model bundled cables, and the

structure of the cable tray may be beneficial. The target sub-model in some of the

computer codes requires the specification of target orientation by the user. This may

result in non-conservative results (for a single cable) and a "user effect." This limitation

may be overcome by including a 1-D radial heat transfer model for the target, or

establishing procedures for the use of the slab model in a consistent manner. The ability

to model a target with more than one material may also be useful to determine the

temperature gradient in the cable, otherwise the property of the single material to be

specified needs to be developed. Target heating in the plume and ceiling jet is not

included in most of the models, thereby limiting the analysis of certain types of

scenarios.

Given the above complexity in estimating cable damage, an evaluation should be

conducted to determine whether consistent results can be obtained in modeling cable

damage directly (modeling heat conduction into a cable or tray of cables) or defining a

conservative safety criterion based on gas temperature and/or incident flux may be

prudent.

Two-Zone Approximation

The two-zone approximation may limit the analysis of certain types of scenarios and

issues. This includes issues for which the local effects of natural and mechanical

ventilation need to be examined (e.g., under ventilated scenarios), or the local

temperature in the HGL is necessary to calculate the target temperature.

Other Modeling Issues

The following is a summary of modeling issues that are discussed in the reports by the

analysts in the appendices, or that were raised and discussed at the 4th meeting when
35

the results of the analyses were presented.

Radiation from Hot Gas

Radiation from the hot gas in the upper layer or the plume region is likely to be the main

contributing factor to cable damage for the types of scenarios analyzed in the exercise. 

The predicted concentration of soot is an important factor in calculating the radiation

from the hot gas. A sensitivity study is recommended to examine the impact of soot

concentration on the overall radiative flux from the hot gas. A review should also be

conducted to assess the need for additional data for soot yields.

Plume Models

The plume correlation in zone models provides the driving force for the generation of

hot gases. Certain limitations in the plume model for CFAST were noted earlier. 

Although plume correlations and calculations have been extensively reviewed and used

in the development of zone, CFD, and lumped-parameter models, they should be

examined for any limitations for the types of fire sources of interest in nuclear power

plants.

Convective Heat Transfer Coefficient

During the development of input data for the models, it was decided that the convective

heat transfer coefficient would be set at 15 W/m2 K for the benchmark exercise. This

value may be too high and unrealistic, especially for some surfaces. This parameter

should be reviewed to determine if another value based on a free convection correlation

should be used, and if different values should be used for the floor, wall, ceiling, and

cable.

5.2 User Interface

The following are recommendations made regarding the user interface.

As evident from the discussions in this document, users of fire models should have

knowledge of basic heat transfer, thermodynamics, and fluid mechanics. A fundamental

course in fire dynamics, available at the graduate level in several universities, will

provide additional beneficial knowledge for the use of the models. It is not necessary to

be a developer or an expert to use the models. Short courses that provide basic

training in the use of specific models will also be beneficial.

In order to prevent misuse, the fire models should be adequately documented with a

technical reference manual, user’s guide, and verification and validation report. The

documentation should include sample problems which include input data and results for

the scenarios analyzed so that the user is able to replicate the analyses. The inclusion

of several sample problems will allow the user to verify the correct installation of a code,
36

gain confidence in the use of the model, and have access to input data for a range of

fire scenarios. Allowable options in the models should be adequately explained, e.g.,

constrained versus unconstrained fire in CFAST, to prevent misuse of the options for

conditions for which they were not intended (Will:Appendix H). Specific parameters that

may be subject to “user effects” should be identified and discussed, e.g., target

orientation in CFAST and the mesh for the conduction calculation in MAGIC.

Results may vary if different versions of the code are used. The legacy of the fire

models should be documented to identify the differences between various versions of

the code. The compatibility of older codes with newer operating platforms should be

identified, e.g. CFAST version 3.1.6 is not compatible with Windows NT (Will:Appendix

H). The effect of different compilers on the model installation should also be discussed. 

The fire models should have a graphical user interface (GUI) to allow users to efficiently

input data for the models and minimize errors in this process. The lack of a GUI for

CFAST Version 4.0 may have led to errors (Will:Appendix H). The GUI should provide

automatic controls for the input of data and alert the user when values are beyond

recommended ranges, or are incorrect. A GUI with this type of feature to check for

errors will minimize the input of incorrect data, and the improper use of the model.

5.3 Benefits of Hand Calculations

Although hand calculations can provide bounding results for many scenarios, the results

discussed above showed the strong coupling between the target response and the

thermal environment created by the fire. Therefore, for the types of scenarios analyzed

in the exercise reported here, zone models provide the minimum simulation capability to

examine the dynamic response of the target to the fire environment.

5.4 Need for Model Improvements

Several of the models used may benefit from an improved target model, especially to

address the “orientation” issue discussed above. However, the benefit from such an

improvement will need to be examined given zone models do not provide local

temperatures of the hot gas around the target. There may be a steep vertical

temperature gradient in the hot gas, especially for large fires. The fire models generally

include a simple sub-model for the target that allows the modeling of one cable. This is

acceptable as long as the goal of the analysis is to provide a conservative estimate. The

modeling of a cable bundled with other cables in a tray will result in lower cable

temperatures. The ability to model bundled cables, and the structure of the cable tray,

may be beneficial. The ability to model a target with more than one material may also

be useful to determine the temperature gradient in the cable. Target heating in the

plume and ceiling jet regions may also be beneficial improvements to the models that

do not have this feature.
37

5.5 Need for Advanced Models

The mass loss rate in the models is generally not coupled with the thermal behavior of

the source. This limitation necessitates the specification of the mass loss rate profile.

The coupling of mass loss and heat release, which entails modeling the combustion

process, is complex and difficult, especially for solid fires like cables. Several efforts are

underway to address this issue. CFD codes provide the opportunity to address this

issue because of the availability of localized information that is necessary for coupling

mass loss and heat release. A related benefit of this improvement will be the ability to

more accurately predict the point of extinction in under ventilated fires.

CFD models may be beneficial to verify the results of a zone model study. CFD

models, which are computationally more expensive, may be used following the analysis

of the problem with a zone model, including sensitivity calculations. A few important

scenarios can then be analyzed with a CFD model to provide a comparison and

verification of the results obtained from the zone model.

CFD models may also be beneficial for analyzing issues when local effects are

important. Figures 19, 20 and 21 illustrated the ability of CFD models to provide

detailed information of the flow patterns in the compartment. This type of information

can be useful in calculating target heating in the plume region, and for determining

effects of ventilation on the fire source and target. Lumped-parameter models also

provide local information to determine the effects of ventilation. Also, both CFD and

lumped-parameter models provide information on the temperature gradient in the hot

gas layer which may be important for determining target response.

The prediction of radiative fluxes from the plume in the near field is a complex problem. 

CFD models, in combination with a radiation model, can provide a better estimate of the

radiative fluxes from the flaming region and hot gas layer. The radiation model may be

as important as the fluid dynamics for thermal damage analysis. In order to maintain

efficiency in the computations, radiation fluxes and gas temperatures could be stored at

target locations, and used later in a separate conduction model. 

5.6 Need for Additional Test Programs

The need for additional test programs for supporting the use of fire models may be

divided into three categories.

1. Fire Model Validation

The need for additional fire model validation was discussed in Section 4.3.2. The submodel for the target, and issues regarding the thermal environment of the target, is a

source of uncertainty for the types of scenarios that are important in nuclear power

plants. It will be useful to conduct international collaborative validation exercises in
38

which the predictive capability of target damage is the main focus of the validation. Also,

more refined measurements and data analyses will be useful to estimate the

quantitative uncertainties of the parameters predicted in the analyses of these fire

scenarios. The data from tests can also be used for improving target models, and

developing models for target heating in the ceiling jet and plume regions.

2. Mass Loss Rate Data

Given the complexity of modeling flame spread, and the developmental state of flame

spread models, it was recommended earlier that current fire modeling analyses use

mass loss rates derived from tests conducted with configurations similar to that being

analyzed. The development of a comprehensive database of mass loss rate profiles for

combustible materials in NPPs will be beneficial for the broader application of fire

models in fire safety analysis.

3. Cable Damage Criteria

The temperature at a specific point in the cable was used in the exercise to specify the

criterion for cable damage. Information regarding cable damage criteria is limited. It will

be beneficial to generate damage criteria for cables and a broad range of equipment of

interest. This information is essential for fire safety analysis. The full benefit of fire

models in nuclear power plant fire safety analysis can be achieved by establishing a

broad database for damage criteria.

5.7 Generic Applicability of Conclusions

Most of the insights gained and conclusions drawn from this benchmark exercise are

applicable to a broad range of fire scenarios expected in nuclear power plants.

However, further benchmark and validation exercises are necessary for some specific

configurations such as large compartments (like the turbine building) with large pool

fires, multi compartments with horizontal and vertical vent connections, and control

room configurations. Insights on some further specific issues are likely to be developed

from such exercises.
39

Table 10 Comparison of Results for Part I, Base Case

O2 Conc.

in HGL at

600 s

(Vol. %)

Peak

Plume

Flow

(kg/s)

Peak

Pressure

(Pa)

Peak LL

Outflow

(kg/s)

Layer

Ht. at

240 s

(m)

Peak

HGL

Temp.

(K)

Peak

Flux on

Target

(W/m2)

Peak Target

Temp.

(K)

Surface CL

cb: 19.0

cn: 19.3

f: 19.9

me: 226

j: 19.9

o: 19.3

cb: 3.6

cn: 4.7

f: 2.2

o:0.3

cb: 1770

cn: 2057

f: 1444

me:961

o: 975

h: 210

j: 46

s: 6004

cb:0.54

cn:0.59

f: 0.41

me:0.39

o: 0.40

H: 0.35

j: 0.08

cb: 1.37

cn: 0.82

f: 1.83

me:1.37

h: 0.3

cb: 359

cn: 357

f: 347

me:336

mc:336

o: 4491

h: 349

x: 360

j: 4003

s: 4005

cb: 1330

cn: 1257

me:1839

o: 472

x: 210

j: 4287

s: 1197

cb:317

cn:322

mc:319

o: 312

s: 333

me: 318

x: 360

f: 3032

me:301

mc:300

o: 301

h: 310

x: 300

1

COCOSYS reported temperatures are maximum values at the ceiling.

2

FLAMME_S reported target temperatures for Part I are at the end of calculation (600 s). 3

JASMINE reported temperatures are the “center top” values which are higher than average “hot layer”

temperatures.

4

The crack area was twice the area specified due to grid size used in simulation.

5

FDS reported temperature is the maximum value at the ceiling.

6

The oxygen concentration from MAGIC are reported as mass percent.

cb: CFAST-BRE

cn: CFAST-NRC/NIST

f: FLAMME_S

me: MAGIC-EdF

mc: MAGIC-CTICM

o: COCOSYS

h: HADCRT

j: JASMINE

s: FDS

x: CFX
40

Table 11 Comparison of Results for Part I, Case 1

Peak Flux

on Target

(W/m2

)

Peak Target Temp.

(K)

Surface CL

cb: 3120

cn: 1932

me: 12,855

o: 26,763

x: 210

j: 4029

f: 7731

cb:353

cn:332

mc:346

o: 327

x: 5501

f: 349

me: 303

mc: 300

o: 300

x: 300

1

Target calculations by FLAMME_S and CFX account for the convective heat transfer from the hot gases

in the plume region to the target.

Table 12 Comparison of Results for Part I, Case 2

Peak Flux

on Target

(W/m2

)

Peak Target Temp.

(K)

Surface CL

cb: 2430

cn: 1808

me: 4665

o: 711

cb:340

cn:329

mc:333

o: 315

f: 308

me: 302

mc: 300

o: 300

Table 13 Comparison of Results for Part I, Case 3

Peak Flux

on Target

(W/m2

)

Peak Target Temp.

(K)

Surface CL

cb: 1770

cn: 1537

me: 2732

o: 648

cb:329

cn:321

mc:323

o: 314

f: 308

me: 302

mc: 300

o: 300
41

Table 14 Comparison of Results for Part I, Case 4

Peak UL

Outflow

(kg/s)

Layer

Ht. at

240 s

(m)

Peak HGL

Temp.

(K)

Peak

Flux on

Target

(W/m2

)

Peak Target Temp.

(K)

Surface CL

cb:0.92

cn:1.36

f: 0.50

me:0.86

o: 1.26

h: 0.4

j: 0.90

cb: 1.86

cn: 1.67

f: 2.03

me:1.77

h: 1.5

cb: 365

cn: 357

f: 348

me:336

mc:336

o: 452

j: 400

cb: 1340

cn: 1298

me:1845

o: 486

j: 4560

s: 981

cb:322

cn:318

mc:320

o: 311

s: 325

f: 303

me:301

mc:300

o: 301

h: 306

Table 15 Comparison of Results for Part I, Case 5

O2

Conc.

in HGL

at 600 s

(%)

Peak

Pressure

(Pa)

Layer Ht.

at 240 s

(m)

Peak HGL

Temp.

(K)

Peak

Flux on

Target

(W/m2)

Peak Target Temp.

(K)

Surface CL

cn: 19.7

f: 20.3

me:22.5

m: 19.7

o: 19.7

cn: 2200

f: 1071

me: 714

o: open

h: . 0

cn: 0.82

f: 1.83

me: 1.43

h: 1.0

cn: 348

f: 348

me: 334

mc: 334

o: 451

x: 350

cn: 1239

me: 2042

o: 396

x: 210

s: 890

cn: 319

s: 319

mc:318

o: 308

x: 360

f: 303

me: 301

mc: 300

o: 300

h: 309

x:300
42

Table 16 Comparison of Results for Part II, Base Case

O2 Conc.

of HGL

at 600 s

(%)

Peak

Pressure

(Pa)

Peak

HGL

Temp.

(K)

Peak

Flux on

Target

(W/m2)

Peak Target Temp.

(K)

Surface CL

cb: 12.5

cn: 13.2

me: 17.02

f: 17.22

f: 17.6

j: 16.1

o: 17.62

cb: 715

cn: 805

me: 721

f: 676

o: 2104

j: 305

cb: 524

cn: 441

f: 465

me:440

o: 6461

x: 680

j: 500

cb: 31704

cn: 15945

me: 3785 

o: 2400

x: 840

j: 2420

cb: 357

cn: 323

o: 436

f: 403

f: 3253

o: 374

me: 311

x: 301

1

COCOSYS reported temperatures are maximum values at the ceiling.

2

Reported at 500 s.

3

FLAMME_S reported target temperatures for Part II are at the end of calculation (1200

s).

4

 Reported fluxes are incident on top side of target slab for Part II results

5 Reported fluxes are on bottom side of target slab for Part II results

Table 17 Comparison of Results for Part II, Case 1

Peak Flux

on Target

(W/m2

)

Peak Target Temp.

(K)

Surface CL

cb: 2740

j: 2620

me: 3784

o: 814

cb: 357

o: 438

f: 427

f: 325

me: 311

o: 374

Table 18 Comparison of Results for Part II, Case 2

Peak Flux

on Target

(W/m2)

Peak Target Temp.

(K)

Surface CL

cb: 2500

me: 3784

j: 2530

o: 2368

cb: 349

o: 435

f: 427

f: 325

me: 311

o:373
43

Table 19 Comparison of Results for Part II, Case 10

Peak HGL

Temp.

(K)

Peak Flux

on Target

(W/m2

)

Peak Target Temp.

(K)

Surface CL

cn: 448

f: 465

me: 441

o:702

x: 525

j: 550

cn: 2234

me: 3792

o: 2158

x: 500

j: 3310

cn: 373

o: 555

f: 324

me: 311

o:472

x: 335

Table 20 Comparison of Results for Part II, Case 11

Peak Flux

on Target

(W/m2

)

Peak Target Temp.

(K)

Surface CL

cb: 4080

cn: 2155

me: 3784

o: 2527

j: 3250

cb: 387

cn: 343

o:446

me: 311

o: 379

Table 21 Comparison of Results for Part II, Case 12

Peak Flux

on Target

(W/m2

)

Peak Target Temp.

(K)

Surface CL

cb: 2570

cn: 1626

me: 877

o: 1827

j: 1570

cb: 345

cn: 326

o: 398

me: 302

o: 355
44

Table 22 Comparison of Results for Part II, Case 13

Peak Flux

on Target

(W/m2

)

Peak Target Temp.

(K)

Surface CL

cb: 3170

o: 2400

cb: 358

o: 482

f: 421

f: 400

me: 352

o: 473

Table 23 Comparison of Results for Part II, Special Cases

Peak HGL

Temp.

(K)

Peak Flux

on Target

(W/m2)

Peak Target Temp.

(K)

Surface CL

Case S1 cn: 457 cn: 2172 cn: 435

Case S2 f: 489 f: 483 f: 458

Case S3 mc: 623 mc: 603 mc: 533

Case S4 me: 441 me: 4250 me: 408 me: 323

Case S5 me: 543 me: 531

Case S1: Part II, Base Case with fire source at 1.8 m, and door open.

Case S2: Part II, Case 10 with fire source at 2.3 m (elevation of tray A).

Case S3, Part II, HRR = 3 MW; D = 3.1 m; door open and ventilation system on; fire

source at 2.1 m, and LOL = 0 %.

Case S4: Part II, Base Case with LOL = 0 %.

Case S5, Part II, Case 10 with fire source at 1.0 m.
45

Figure 1 Representative PWR Room
46

0

50

100

150

200

250

300

350

400

0 50 100 150 200 250 300 350 400 450 500 550

Time (s)

Heat Release Rate (kW)

Figure 2 Trash Bag Fire (Part I)

0

0.5

1

1.5

2

2.5

3

3.5

4

4.5

5

0 100 200 300 400 500 600

Time (s)

Plume Flow (kg/s)

CFAST (NRC)

FLAMME_S

CFAST (BRE)

Figure 3 Plume Flow (Part I, Base Case)
47

0

0.5

1

1.5

2

2.5

3

3.5

4

4.5

5

0 100 200 300 400 500 600

Time (s)

Interface Height (m)

CFAST (NRC)

MAGIC (CTICM)

FLAMME_S

CFAST (BRE)

MAGIC (EdF)

Figure 4 HGL Development (Part I, Base Case)

19

19.5

20

20.5

21

21.5

22

22.5

23

23.5

0 100 200 300 400 500 600

Time (s)

Concentration (%)

CFAST (NRC)

MAGIC (EdF)

MAGIC (CTICM)

FLAMME_S

COCOSYS

JASMINE

Figure 5 Oxygen Concentration (Part I, Base Case)
48

-500

0

500

1000

1500

2000

2500

0 100 200 300 400 500 600

Time (s)

Pressure (Pa)

CFAST (NRC)

MAGIC (EdF)

MAGIC (CTICM)

COCOSYS

JASMINE

FLAMME_S

CFAST (BRE)

Figure 6 Pressure Development (Part I, Base Case)

-0.2

-0.1

0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0 100 200 300 400 500 600 700

Time (s)

Flow Rate (kg/s)

CFAST (NRC)

FLAMME_S

MAGIC (EdF)

MAGIC (CTICM)

COCOSYS

JASMINE

CFAST (BRE)

Figure 7 Flow from Crack (Part I, Base Case)
49

300

320

340

360

380

400

420

440

460

0 100 200 300 400 500 600

Time (s)

HGL Temperature (K)

CFAST (NRC)

FLAMME_S

MAGIC (EdF)

MAGIC (CTICM)

COCOSYS (at ceiling)

JASMINE (at ceiling)

CFAST (BRE)

Figure 8 HGL Temperature (Part I, Base Case)

300

305

310

315

320

325

0 100 200 300 400 500 600

Time (s)

Temperature (K)

CFAST (NRC)

FLAMMES_S

MAGIC (EdF)

MAGIC (CTICM)

COCOSYS

CFAST (BRE)

Figure 9 Target Surface Temperature (Part I, Base Case)
50

Figure 10 Total Heat Loss from Boundaries - COCOSYS

(from Klein-Hessling (Appendix F))

0

100

200

300

400

500

600

0 100 200 300 400 500 600

time (s)

surface temperature (°C)

d=0.3m

d=0.4m

d=0.5m

d=0.9m

d=2.2m

Figure 11 Effect of Distance between Fire and Target -

FLAMME_S (from Bouton:Appendix A)
51

Figure 12 Effect of Distance on Radiative Flux

- MAGIC (from Gautier:Appendix C)

Figure 13 Target Exposure in Plume Region in CFD Analysis - CFX

(from Heitsch (Appendix D))
52

0.0

0.5

1.0

1.5

2.0

2.5

3.0

3.5

4.0

4.5

5.0

0 50 100 150 200 250 300 350 400 450 500 550

Time (s)

HGL Interface Height (m)

Case 4

Base Case

Figure 14 HGL Development (Part I) - CFAST

(from Dey (Appendix B))

0

0.2

0.4

0.6

0.8

1

1.2

1.4

1.6

0 50 100 150 200 250 300 350 400 450 500 550

Time (s)

Flow Rate (kg/s)

Upper Outflow

Lower Layer Inflow

Figure 15 Door Flows (Part I, Case 4) - CFAST

(from Dey (Appendix B))
53

300

310

320

330

340

350

360

0 50 100 150 200 250 300 350 400 450 500 550

Time (s)

Temperature (K)

Case 4

Case 5

Base Case

Figure 16 HGL Temperature (Part I) - CFAST

(From Dey (Appendix B))

0

0.2

0.4

0.6

0.8

1

1.2

0 50 100 150 200 250 300 350 400 450 500 550

Time (s)

Flow (kg/s)

MV Upper Outflow 

MV Upper Inflow

MV Lower Inflow

MV Lower Outflow

Figure 17 Mechanical Ventilation Flows (Part I, Case 5) -

CFAST (from Dey (Appendix B))
54

Figure 18 Door Flows (Part I, Case 4) - FDS

(from Dey (Appendix B))

Part I base case – no mechanical

Part I case 5 - with mechanical ventilation

Figure 19 Effect of Mechanical Ventilation

- JASMINE (from Miles (Appendix G))
55

Figure 20 Effects of Mechanical Ventilation

(Part I, Case 5) - FDS (from Dey (Appendix B))

Figure 21 Effects of Mechanical Ventilation - CFX

(from Heitsch (Appendix D))
56

0

200

400

600

800

1000

1200

0 200 400 600 800 1000 1200 1400

Time (s)

Heat Release Rate (kW)

COCOSYS

(LOL=4%)

MAGIC - CTICM

(LOL=0%)

FLAMME_S

CFAST-BRE

CFAST-NRC

MAGIC-EdF

Figure 22 Heat Release Rate (Part II, Base Case)

0

0.5

1

1.5

2

2.5

3

3.5

4

4.5

5

0 200 400 600 800 1000 1200 1400

Time (s)

Interface Height (m)

MAGIC-CTICM

(LOL=0%)

MAGIC-EdF FLAMME-S

CFAST-BRE CFAST-NRC

Figure 23 HGL Development (Part II, Base Case)
57

0

5

10

15

20

25

0 200 400 600 800 1000 1200 1400

Time (s)

Oxygen Concentration (Vol. %)

MAGIC-CTICM

(LOL=0%)

COCOSYS

(LOL=4%)

CFAST-BRE

CFAST-NRC

JASMINE

MAGIC-EdF

FLAMME_S

Figure 24 Oxygen Concentration (Part II, Base Case)

300

350

400

450

500

550

600

650

700

0 200 400 600 800 1000 1200 1400

Time (s)

Temperature (K)

COCOSYS

(at ceiling)

CFAST-BRE

JASMINE

(at ceiling)

CFAST-NRC

MAGIC-EdF

MAGIC-CTICM

(LOL=0%)

FLAMME_S

Figure 25 HGL Temperature (Part II, Base Case)
58

300

320

340

360

380

400

420

440

460

0 200 400 600 800 1000 1200 1400

Time (s)

Temperature (K)

COCOSYS

(LOL=0%)

FLAMME_S

MAGIC-EdF

CFAST-NRC

CFAST-BRE

Figure 26 Target Surface Temperature (Part II, Base Case)

0

0.5

1

1.5

2

2.5

3

3.5

4

4.5

5

0 200 400 600 800 1000

Time (s)

Molar fraction (%)

CO2

CO

HCL, H20

Soot

Figure 27 Species Concentration (Part II, Base Case)

(from Bouton (Appendix A))
59

0

0.01

0.02

0.03

0.04

0.05

0.06

0.07

0 500 1000 1500 2000 2500 3000 3500 4000 4500 5000

Time (s)

Pyrolysis Rate (kg/s)

Figure 28 Pyrolysis Rate (Part II, Base Case)

(from Dey (Appendix B))

0

20

40

60

80

100

120

140

160

180

0 200 400 600 800 1000 1200

Time (s)

Temperature (°C)

Base case, case 1, 2

Surface Temperature

Core Temperature Case 13

Case 3, 4, 5

Case 6, 7, 8

Base case, case 1, 2

Case 6, 7, 8 Case 3, 4, 5

Figure 29 Effect of Cable Structure

(from Bouton (Appendix A))
60

300

350

400

450

500

550

600

0 500 1000 1500 2000 2500 3000 3500 4000 4500 5000

Time (s)

Temperature (K)

HGL - Case S1 (CFAST)

Target Surface - Case S1 (CFAST)

HGL - Case S5 (MAGIC)

Target Surface - Case S5 (MAGIC)

Figure 30 Temperature Development (Special Cases)
61

6 References

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Electric Power Research Institute, “Fire Tests in Ventilated Rooms: Extinguishment of

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Grondeau, P., “Rapport de Essai: Etude de la Evolution d’un Incendie dans des Cables

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Substances and Venting of Deflagrations, 11-15 August 1991, Moscow, Russia, AllRussian Research Institute for Fire Protection, pp. 87-101, 1998.

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Tewarson, A, “Generation of Heat and Chemical Compounds in Fires,” SFPE Handbook

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