NUREG-1824 EPRI 1011999

Final Report

Verification and Validation

of Selected Fire Models for

Nuclear Power Plant

Applications

Volume 3:

Fire Dynamics Tools (FDTS)

U.S. Nuclear Regulatory Commission

Office of Nuclear Regulatory Research

Washington, DC 20555-0001

U.S.NR 

P-shqP-p, nd hAFm .mC

Electric Power Research Institute

3420 Hillview Avenue

Palo Alto, CA 94303

~I~I2 ~ELECTRIC POWER

RESEARCH INSTITUTE
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Verification & Validation of Selected

Fire Models for Nuclear Power Plant

Applications

Volume 3: Fire Dynamics Tools (FDTs)

NUREG-1824 EPRI 1011999

Final Report

May 2007

U.S. Nuclear Regulatory Commission

Office of Nuclear Regulatory Research (RES)

Two White Flint North, 11545 Rockville Pike

Rockville, MD 20852-2738

U.S. NRC-RES Project Manager

M. H. Salley

Electric Power Research Institute (EPRI)

3420 Hillview Avenue

Palo Alto, CA 94303

EPRI Project Manager

R.P. Kassawara
DISCLAIMER OF WARRANTIES AND LIMITATION OF LIABILITIES

THIS DOCUMENT WAS PREPARED BY THE ORGANIZATION(S) NAMED BELOW AS AN

ACCOUNT OF WORK SPONSORED OR COSPONSORED BY THE ELECTRIC POWER

RESEARCH INSTITUTE, INC. (EPRI). NEITHER EPRI NOR ANY MEMBER OF EPRI, ANY

COSPONSOR, THE ORGANIZATION(S) BELOW, OR ANY PERSON ACTING ON BEHALF

OF ANY OF THEM:

(A) MAKES ANY WARRANTY OR REPRESENTATION WHATSOEVER, EXPRESS OR

IMPLIED, (1) WITH RESPECT TO THE USE OF ANY INFORMATION, APPARATUS,

METHOD, PROCESS, OR SIMILAR ITEM DISCLOSED IN THIS DOCUMENT, INCLUDING

MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE, OR (11) THAT SUCH

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IS SUITABLE TO ANY PARTICULAR USER'S CIRCUMSTANCE; OR

(B) ASSUMES RESPONSIBILITY FOR ANY DAMAGES OR OTHER LIABILITY

WHATSOEVER (INCLUDING ANY CONSEQUENTIAL DAMAGES, EVEN IF EPRI OR ANY

EPRI REPRESENTATIVE HAS BEEN ADVISED OF THE POSSIBILITY OF SUCH

DAMAGES) RESULTING FROM YOUR SELECTION OR USE OF THIS DOCUMENT OR

ANY INFORMATION, APPARATUS, METHOD, PROCESS, OR SIMILAR ITEM DISCLOSED

IN THIS DOCUMENT.

ORGANIZATION(S) THAT PREPARED THIS DOCUMENT:

U.S. Nuclear Regulatory Commission, Office of Nuclear Regulatory Research

Science Applications International Corporation

National Institute of Standards and Technology

NOTE

For further information about EPRI, call the EPRI Customer Assistance Center at

800.313.3774 or

e-mail askepri@epri.com.

Electric Power Research Institute, EPRI, and TOGETHER... SHAPING THE FUTURE OF

ELECTRICITY are registered service marks of the Electric Power Research Inst itute, Inc.
CITATIONS

This report was prepared by

U.S. Nuclear Regulatory Commission,

Office of Nuclear Regulatory Research (RES)

Two White Flint North, 11545 Rockville Pike

Rockville, MD 20852-273 8

Principal Investigators:

K. Hill

J. Dreisbach

Electric Power Research Institute (EPRI)

3420 Hillview Avenue

Palo Alto, CA 94303

Science Applications International Corp (SAIC)

4920 El Camino Real

Los Altos, CA 94022

Principal Investigators:

F. Joglar

B. Najafi

National Institute of Standards and Technology

Building Fire Research Laboratory (BFRL)

100 Bureau Drive, Stop 8600

Gaithersburg, MD 20899-8600

Principal Investigators:

K McGrattan

R. Peacock

A. Hamins

Volume 1, Main Report: B. Najafi, F. Joglar, J. Dreisbach

Volume 2, Experimental Uncertainty: A. Hamins, K. McGrattan

Volume 3, FDT5 : J. Dreisbach, K. Hill

Volume 4, FIVE-Rev 1: F. Joglar

Volume 5, CFAST: R. Peacock, P. Reneke (NIST)

Volume 6, MAGIC: F. Joglar, B. Guatier (EdF), L. Gay (EdF), J. Texeraud (EdF)

Volume 7, FDS: K. McGrattan

This report describes research sponsored jointly by U.S. Nuclear Regulatory Commission, Office

of Nuclear Regulatory Research (RES) and Electric Power Research Institute (EPRI).

The report is a corporate document that should be cited in the literature in the following manner:

Verification and Validation of Selected Fire Models for Nuclear Power Plant Applications,

Volume 3: Fire Dynamics Tools (FD78), U.S. Nuclear Regulatory Commission, Office of

Nuclear Regulatory Research (RES), Rockville, MD, 2007, and Electric Power Research

Institute (EPRI), Palo Alto, CA, NUREG-1824 and EPRI 1011999.

iii
NIJREG-1824, Volume 3, has been

reproduced from the best available copy.
ABSTRACT

There is a movement to introduce risk-informed and performance-based analyses into fire protection

engineering practice, both domestically and worldwide. This movement exists in the general

fire protection community, as well as the nuclear power plant (NPP) fire protection community.

The U.S. Nuclear Regulatory Commission (NRC) has used risk-informed insights as part of its

regulatory decision making since the 1990's.

In 2002, the National Fire Protection Association (NFPA) developed NFPA 805, PerformanceBased Standard for Fire Protection for Light- Water Reactor Electric Generating Plants,

2001 Edition. In July 2004, the NRC amended its fire protection requirements in Title 10,

Section 50.48, of the Code of Federal Regulations (10 CFR 50.48) to perm-it existing reactor

licensees to voluntarily adopt fire protection requirements contained in NFPA 805 as an alternative

to the existing deterministic fire protection requirements. In addition, the NPP fire protection

community has been using risk-informed, performance-based (RI/PB) approaches and insights to

support fire protection decision-ma king in general.

One key tool needed to further the use of RI/PB3 fire protection is the availability of verified and

validated fire models that can reliably predict the consequences of fires. Section 2.4.1.2 of

NFPA 805 requires that only fire models acceptable to the Authority Having Jurisdiction (AHJ)

shall be used in fire modeling calculations. Furthermore, Sections 2.4.1.2.2 and 2.4.1.2.3 of

NFPA 805 state that fire models shall only be applied within the limitations of the given model,

and shall be verified and validated.

This report is the first effort to document the verification and validation (V&V) of five fire models

that are commonly used in NPP applications. The project was performned in accordance with the

guidelines that the American Society for Testing and Materials (ASTM) set forth in ASTM E 1355,

Standard Guide for Evaluating the Predictive Capability of Deterministic Fire Models.

The results of this V&V are reported in the form of ranges of accuracies for the fire model

predictions.

v

FOREWORD

Fire modeling and fire dynamics calculations are used in a number of fire hazards analysis (FHA) studies and

documents, including fire risk analysis (FRA) calculations; compliance with and exemptions to the regulatory

requirements for fire protection in 10 CFR Part 50; the Significance Determination Process (SDP) used in the

inspection program conducted by the U.S. Nuclear Regulatory Commission (NRC); and, most recently, the

risk-informed performance-based (RI/PB) voluntary fire protection licensing basis established under

10 CFR 50.48(c). The RI/PB method is based on the National Fire Protection Association (NFPA)

Standard 805, Performance-Based Standard for Fire Protection for Light- Water Reactor Generating P/ants.

The seven volumes of this NUTREG-series report provide technical documentation concerning the predictive

capabilities of a specific set of fire dynamics calculation tools and fire models for the analysis of fire hazards in

postulated nuclear power plant (NPP) scenarios. Under a joint memorandum of understanding (MOU), the NRC

Office of Nuclear Regulatory Research (RES) and the Electric Power Research Institute (EPRI) agreed to develop

this technical document for NPP application of these fire modeling tools. The objectives of this agreement

include creating a library of typical NPP fire scenarios and providing information on the ability of specific fire models

to predict the consequences of those typical NPP fire scenarios. To meet these objectives, RES and EPRI initiated

this collaborative project to provide an evaluation, in the form of verification and validation (V&V), for a set of five

commonly available fire modeling tools.

The road map for this project was derived from NFPA 805 and the American Society for Testing and Materials

(ASTM) Standard E 1355, Standard Guide for Evaluating the Predictive Capability of Deterministic Fire

Models. These industry standards form the methodology and process used to perform this study. Technical

review of fire models is also necessary to ensure that those using the models can accurately assess the adequacy of

the scientific and technical bases for the models, select models that are appropriate for a desired use, and understand

the levels of confidence that can be attributed to the results predicted by the models. This work was performed

using state-of-the-art fire dynamics calculation methods/models and the most applicable fire test data. Future

improvements in the fire dynamics calculation methods/models and additional fire test data may impact the results

presented in the seven volumes of this report.

This document does not constitute regulatory requirements, and NRC participation in this study neither

constitutes nor implies regulatory approval of applications based on the analysis contained in this text.

The analyses documented in this report represent the combined efforts of individuals from RES and EPRI.

Both organizations provided specialists in the use of fire models and other FHA tools to support this work.

The results from this combined effort do not constitute either a regulatory position or regulatory guidance.

Rather, these results are intended to provide technical analysis of the predictive capabilities of five fire

dynamic calculation tools, and they may also help to identify areas where further research and analysis are needed.

Brian W. Sheron, Director

Office of Nuclear Regulatory Research

U.S. Nuclear Regulatory Commission

Vii

CONTENTS

I INTRODUCTION...........................1-1

2 MODEL DEFINITION................................................................................ 2-1

2.1 Name and Version of the Model............................................................ 2-1

2.2 Type of Model................................................................................ 2-1

2.3 Model Developers ........................................................................... 2-1

2.4 Relevant Publications ....................................................................... 2-1

2.5 Governing Equations and Assumptions.................................................... 2-2

2.6 Input Data Required to Run the Model .................................................... 2-2

2.7 Property Data ................................................................................ 2-2

2.8 Model Results................................................................................ 2-2

2.9 Uses and Limitations of the Model ......................................................... 2-3

3 THEORETICAL BASIS FOR FDTs................................................................ 3-1

3.1 Estimating Hot Gas Layer Temperature................................................... 3-3

3.1.1 Natural Ventilation: Method of McCaffrey, Quintiere, and Harkleroad (MQH)......3-3

3.1.2 Natural Ventilation (Compartment Closed): Method of Beyler ....................... 3-6

3.1.3 Forced Ventilation: Method of Foote, Pagni, and Alvares (FPA) .................... 3-7

3.1.4 Forced Ventilation: Method of Deal and Beyler ....................................... 3-7

3.2 Estimating Smoke Layer Height ............................................................ 3-8

3.2.1 Natural Ventilation (Smoke Filling): The Non-Steady-State Yamana

and Tanaka Method............................................................................. 3-8

3.3 Assumptions and Limitations for Hot Gas Layer Calculations.......................... 3-10

3.4 Flame Height ............................................................................... 3-11

3.4.1 Assumptions and Limitations........................................................... 3-12

3.5 Estimating Radiant Heat Flux from Fire to a Target ..................................... 3-13

3.5.1 Point Source Radiation Model ......................................................... 3-13

3.5.2 Solid Flame Radiation Model with Target at and Above Ground Level............. 3-14

3.5.3 Assumptions and Limitations........................................................... 3-19

ix.
3.6 Estimating the Centerline, Temperature of a Buoyant Plume........................... 3-20

3.6.1 Assumptions and Limitations........................................................... 3-22

4 MATHEMATICAL AND NUMERICAL ROBUSTNESS .......................................... 4-1

5 MODEL SENSITIVITY .............................................................................. 5-1

5.1 Definition of Base Case Scenario for Sensitivity Analysis...................--....... -15-1

5.2 Sensitivity Analysis for FDTS................................................................ 5-2

5.3 Sensitivity to Heat Release Rate........................................................... 5-2

5.4 Sensitivity to Radial Distance..............................................................5.. 53

5.5 Sensitivity to Radiation Fraction ............................................................ 5-4

5.6 Sensitivity to Diameter ...................................................................... 5-5

5.7 Conclusions.................................................................................. 5-6

6 MODEL VALIDATION .............................................................................. 6-1

6.1 Hot Gas Layer Temperature and Height................................................... 6-3

6.2 Plume Temperature ......................................................................... 6-8

6.3 Flame Height ............................................................................... 6-10

6.4 Target/Radiant Heat Flux.................................................................. 6-10

6.5 Summary ................................................................................... 6-14

7 REFERENCES ...................................................................................... 7-I

A TECHNICAL DETAILS OF THE FDTS VALIDATION STUDY................................. A-I

A.1 Hot Gas Layer Temperature and Height .................................................. A-i

A.1 -1 ICFMP BE#2 ............................................................................ A-2

A.1.2 ICFMP BE #3 ............................................................................ A-4

A.1.3ICFMP BE#4 ........................................................................... A-1 2

A.1.4 ICFMP BE #5........................................................................... A-1 3

A. 1.5 The FM/SNL Test Series .............................................................. A-i15

A. 1.6 The NBS Test Series .................................................................. A-17

A.1.7 Summary: Hot Gas Layer Temperature and Height ................................ A-19

A.2 Plume Temperature ....................................................................... A-20

A.2-1 ICFMP BE #2........................................................................... A-21

A.2.2 The FM/SNL Test Series .............................................................. A-23

A.2.3 Summary: Plume Temperature....................................................... A-24

X
A.3 Flame Height .............................................................................. A-25

A.3.1 ICFMP BE #2........................................................................... A-25

A.3.2 ICFMP BE #3........................................................................... A-27

A.4 Target Heat Flux........................................................................... A-27

AA4.1 ICFMP BE #3........................................................................... A-27

A.4.2 Summary: Radiant Heat Flux......................................................... A-45

Xi

FIGURES

Figure 3-1: Characteristics of Flame Height Fluctuations ........................................ 3-11

Figure 3-2: Radiant Heat Flux from a Pool Fire to a Floor-Based Target Fuel

(Point Source Model)........................................................................... 3-14

Figure 3-3: Solid Flame Radiation Model with No Wind and Target at Ground Level.......... 3-15

Figure 3-4: Solid Flame Radiation Model with No Wind and Target Above Ground ........... 3-15

Figure 3-5: Cylindrical Flame Shape Configuration Factor Geometry

for Vertical and Horizontal Targets at Ground Level with No Wind......................... 3-17

Figure 3-6: Cylindrical Flame Shape Configuration Factor Geometry

for Vertical and Horizontal Targets Above Ground with No Wind .......................... 3-17

Figure 3-7: Point Source Fire Plume ............................................................... 3-21

Figure 5-1: Sensitivity of Various Output Quantities to Changes in HRR ........................ 5-3

Figure 5-2: Sensitivity of Various Output Quantities to Changes in Radial Distance............ 5-4

Figure 5-3: Sensitivity of Various Output Quantities to Changes in Radiation Fraction......... 5-5

Figure 5-4: Sensitivity of Various Output Quantities to Changes in Diameter ................... 5-6

Figure 6-1: Relative Differences for HGL Temperature............................................ 6-7

Figure 6-2: Measured vs. Predicted HGL Temperatures .......................................... 6-7

Figure 6-3: Relative Differences for Plume Temperature.......................................... 6-9

Figure 6-4: Measured vs. Predicted Plume Temperatures ........................................ 6-9

Figure 6-5: Relative Differences for Radiant Heat Flux Using Point Source Radiation

Model ............................................................................................ 6-12

Figure 6-6: Measured vs. Predicted Radiant Heat Flux: Point Source Radiation Model .....6-12

Figure 6-7: Relative Differences for Radiant Heat Flux Using Solid Flame Radiation

Model ............................................................................................ 6-13

Figure 6-8: Measured vs. Predicted Radiant Heat Flux: Solid Flame Radiation Model......6-13

Figure A-i: Hot Gas Layer Temperature, ICFMP BE #2, Cases 1, 2, and 3 .................... A-4

Figure A-2: Hot Gas Layer Temperature, ICEMP BE #3, Closed Compartment Tests......... A-8

Figure A-3: Hot Gas Layer Temperature, ICFMP BE #3, Open Compartment Tests........... A-9

Figure A-4: Hot Gas Layer Temperature, ICEMP BE #3, Forced Ventilation Tests ........... A-10

Figure A-5: Hot Gas Layer Height, ICFMP BE #3, Open Compartment Tests ................ A-I 1

Figure A-6: Hot Gas Layer Temperature, ICFMP BE #4 ........................................ A-13

Figure A-7: Hot Gas Layer Temperature, ICFMP BE #5 ........................................ A-is5

Figure A-8: Hot Gas Layer Temperature, FM/SNL Tests........................................ A-17

Figure A-9: Hot Gas Layer Temperature, NBS Tests............................................ A-19

xiii
Figure A-10: Plume Temperature, ICFMP BE #2, Cases 1, 2, and 3 .......................... A-22

Figure A-i 1: Plume Temperature, FM/SNL Tests ............................................... A-24

Figure A-12: Photographs of Heptane Pan Fires, ICEMP BE #2, Case 2

(Courtesy of Simo Hostikka, VTT Building and Transport, Espoo, Finland)............... A-26

Figure A-13: Photograph and Simulation of ICFMP BE #3, Test 3,

as Seen Through the 2 m x 2 m Doorway (Photo courtesy of Francisco Joglar,

SAIC) ............................................................................................ A-27

Figure A-14: Radiant Heat Flux, ICFMP BE #3, Tests 1 and 7.................................. A-29

Figure A-i5: Radiant Heat Flux, ICFMP BE #3, Tests 2 and 8.................................. A-30

Figure A-16: Radiant Heat Flux, ICFMP BE #3, Tests 3 and 9.................................. A-31

Figure A-17: Radiant Heat Flux, ICFMP BE #3, Tests 4 and 10 ................................ A-32

Figure A-18: Radiant Heat Flux, ICFMP BE #3, Tests 5 and 14 ................................ A-33

Figure A-19: Radiant Heat Flux, ICFMP BE #3, Tests 13 and 16............................... A-34

Figure A-20: Radiant Heat Flux, ICFMP BE #3, Tests 15 and 18............................... A-35

Figure A-21: Radiant Heat Flux, ICFMP BE #3, Test 17 ........................................ A-36

Figure A-22: Radiant Heat Flux, ICFMP BE #3, Tests 1 and 7.................................. A-38

Figure A-23: Radiant Heat Flux, ICFMP BE #3, Tests 2 and 8.................................. A-39

Figure A-24: Radiant Heat Flux, ICFMP BE #3, Tests 3 and 9.................................. A-40

Figure A-25: Radiant Heat Flux, ICFMP BE #3, Tests 4 and 10 ................................ A-41

Figure A-26: Radiant Heat Flux, ICFMP BE #3, Tests 5 and 14 ................................ A-42

Figure A-27: Radiant Heat Flux, ICFMP BE #3, Tests 13 and 16............................... A-43

Figure A-28: Radiant Heat Flux, ICEMP BE #3, Tests 15 and 18............................... A44

Figure A-29: Radiant Heat Flux, ICFMP BE #3, Test 17 ........................................ A-45

xiv
TABLES

Table 3-1: Spreadsheets Included in the V&V Study............................................... 3-2

Table A-i: Input Values for ICEMP BE #2, Cases 1 and 2 ....................................... A-2

Table A-2: Input Values for ICEMP BE #2, Case 3 ................................................ A-3

Table A-3: ICFMP BE #2 Heat Release Rates .................................................... A-3

Table A-4: Input Values for ICEMP BE#3 Closed Compartment Tests.......................... A-5

Table A-5: Input Values for ICEMP BE #3 Open Compartment Tests ........................... A-6

Table A-6: Input Values for ICFMP BE #3, Forced Ventilation Tests............................ A-7

Table A-7: Input Values for ICEMP BE #4 ........................................................ A-1 2

Table A-8: Input Values for ICFMP BE #5 ........................................................ A-14

Table A-9: Input Values for FM/SNL Tests ....................................................... A-1 6

Table A- 10: Input Values for NBS Tests .......................................................... A-1 8

Table A-i 1: Hot Gas Layer Temperature Relative Differences ................................. A-20

Table A-12: Input Values. for ICFMP BE #2 Plume Temperature Calculations ................ A-21

Table A-i13: Input Values for FM/SNL Tests Plume Temperature Calculations................ A-23

Table A-14: Plume Temperature Relative Differences .......................................... A-24

Table A-1 5: Radial Distance and L/D from Fire to Radiant Heat Flux Gauges (meters) .....A-28

Table A-i 6: Horizontal Distance from Fire to Radiant Heat Flux Gauges (meters) ........... A-37

Table A-17: Relative Differences, Radiant Heat Flux - Point Source ......................... A-46

Table A-i 8: Relative Differences, Radiant Heat Flux - Solid Flame .......................... A-47

xv

REPORT SUMMARY

This report documents the verification and validation (V&V) of five selected fire models

commonly used in support of risk-informed and performance-based (RI/PB) fire protection

at nuclear power plants (NPPs).

Background

Since the 1990s, when it became the policy of the NRC to use risk-informed methods to make

regulatory decisions where possible, the nuclear power industry has been moving from prescriptive

rules and practices toward the use of risk information to supplement decision-making. Several

initiatives have furthered this transition in the area of fire protection. In 2001, the National Fire

Protection Association (NFPA) completed the development of NFPA Standard 805,

Performance-Based Standard for Fire Protection for Light- Water Reactor Electric Generating

Plants, 2001 Edition. Effective July 16, 2004, the NRC amended its fire protection requirements

in Title 10, Section 50.48(c), of the Code of Federal Regulations [10 CFR 50.48(c)] to permit

existing reactor licensees to voluntarily adopt fire protection requirements contained in NFPA

805 as an alternative to the existing deterministic fire protection requirements. RI/PB3 fire

protection often relies on fire modeling for determining the consequence of fires. NFPA 805

requires that the "fire models shall be verified and validated," and "only fire models that are

acceptable to the Authority Having Jurisdiction (AHJ) shall be used in fire modeling

calculations."

Objectives

* To perform V&V studies of selected fire models using a consistent methodology (ASTM I

1335)

" To investigate the specific fire modeling issue of interest to NPP fire protection applications

* To quantify fire model predictive capabilities to the extent that can be supported by

comparison with selected and available experimental data.

Approach

This project team performed V&V studies on five selected models: (1) NRC's NUREG- 1805

Fire Dynamics Tools (FDTS), (2) EPRI's Fire-Induced Vulnerability Evaluation Revision 1

(Fl VE-Revl), (3) National Institute of Standards and Technology's (NIST) Consolidated Model

of Fire Growth and Smoke Transport (CFAST), (4) Electricit6 de France's (EdF) MAGIC, and

(5) NIST's Fire Dynamics Simulator (FDS). The team based these studies on the guidelines of

the ASTM E 13 55, Standard Guide for Evaluating the Predictive Capability ofDeterministic

Fire Models. The scope of these V&V studies was limited to the capabilities of the selected fire

models and did not cover certain potential fire scenarios that fall outside the capabilities of these

fire models.

xvii
Results

The results of this study are presented in the form of relative differences between fire model

predictions and experimental data for fire modeling attributes such as plume temperature that are

important to NPP fire modeling applications. While the relative differences sometimes show

agreement, they also show both under-prediction and over-prediction in some circumstances.

These relative differences are affected by the capabilities of the models, the availability of

accurate applicable experimental data, and the experimental uncertainty of these data. The

project team used the relative differences, in combination with some engineering judgment as to

the appropriateness of the model and the agreement between model and experiment, to produce a

graded characterization of each fire model's capability to predict attributes important to NPP fire

modeling applications.

This report does not provide relative differences for all known fire scenarios in NPP applications.

This incompleteness is attributable to a combination of model capability and lack of relevant

experimental data. The first problem can be addressed by improving the fire models, while the

second problem calls for more applicable fire experiments.

EPRI Perspective

The use of fire models to support fire protection decision-making requires a good understanding

of their limitations and predictive capabilities. While this report makes considerable progress

toward this goal, it also points to ranges of accuracies in the predictive capability of these fire

models that could limit their use in fire modeling applications. Use of these fire models presents

challenges that should be addressed if the fire protection community is to realize the full benefit

of fire modeling and performance-based fire protection. Persisting problems require both shortterm and long-ternm solutions. In the short-term, users need to be educated on how the results of

this work may affect known applications of fire modeling, perhaps through pilot application of

the findings of this report and documentation of the resulting lessons learned. In the long-term,

additional work on improving the models and performing additional experiments should be

considered.

Keywords

Fire Fire Modeling

Verification and Validation (V&V) Performance-Based

Risk-Informed Regulation Fire Hazard Analysis (FHA)

Fire Safety Fire Protection

Nuclear Power Plant Fire Probabilistic Risk Assessment (PRA)

Fire Probabilistic Safety Assessment (PSA)

xviii
PREFACE

This report is presented in seven volumes. Volume 1, the Main Report, provides general

background information, programmatic and technical overviews, and project insights and

conclusions. Volume 2 quantifies the uncertainty of the experiments used in the V&V study of

the five fire models considered in this study. Volumes 3 through 7 provide detailed discussions

of the verification and validation (V&V) of the fire models:

Volume 3 Fire Dynamics Tools (FDT5 )

Volume 4 Fire-Induced Vulnerability Evaluation, Revision 1 (FIVE-Revi)

Volume 5 Consolidated Model of Fire Growth and Smoke Transport (CFAST)

Volume 6 MAGIC

Volume 7 Fire Dynamics Simulator (FDS)

xix

ACKNOWLEDGMENTS

The work documented in this report benefited from contributions and considerable technical

support from several organizations.

The verification and validation (V&V) studies for FDTS (Volume 3), CFAST (Volume 5), and

FDS (Volume 7) were conducted in collaboration with the U.S. Department of Commerce,

National Institute of Standards and Technology (NIST), Building and Fire Research Laboratory

(BFRL). Since the inception of this project in 1999, the NRC has collaborated with NIST

through an interagency memorandum of understanding (MOU) and conducted research to provide

the necessary technical data and tools to support the use of fire models in nuclear power plant

fire hazard analysis (FHA).

We appreciate the efforts of Doug Carpenter and Rob Schmidt of Combustion Science

Engineers, Inc. for their comments and contributions to Volume 3.

In addition, we acknowledge and appreciate the extensive contributions of Electricit6 de France

(EdF) in preparing Volume 6 for MAGIC.

We thank Drs. Charles Hagwood and Matthew Bundy of NIST for the many helpful discussions

regarding Volume 2.

We also appreciate the efforts of organizations participating in the International Collaborative

Fire Model Project (ICFMP) to Evaluate Fire Models for Nuclear Power Plant Applications,

which provided experimental data, problem specifications, and insights and peer comment for

the international fire model benchmarking and validation exercises, and jointly prepared the

panel reports used and referred to in this study. We specifically appreciate the efforts of the

Building Research Establishment (BRE) and the Nuclear Installations Inspectorate in the United

Kingdom, which provided leadership for ICEMP Benchmark Exercise (BE) #2, as well as

Gesellschaft Mur Anlagen-und Reaktorsicherheit (GRS) and Institut fiur Baustoffe, Massivbau und

Brandschutz (iBMB) in Germnany, which provided leadership and valuable experimental data for

ICFMP BE #4 and BE #5. In particular, ICFMP` BE #2 was led by Stewart Miles at BRE; ICFMP

BE #4 was led by Walter Klein-Hessling and Marina Rowekamp at GRS, and R. Dobbernack and Olaf

Riese at iBMB; and ICFMP BE #5 was led by Olaf Riese and D. Hosser at iBMB, and Marina

Rowekamp at GRS. Simo Hostikka of VTT, Finland also assisted with ICFMP BE#2 by

providing pictures, tests reports, and answered various technical questions of those experiments.

We acknowledge and sincerely appreciate all of their efforts.

We greatly appreciate Paula Garrity, Technical Editor for the Office of Nuclear Regulatory

Research, and Linda Stevenson, agency Publications Specialist, for providing editorial and

publishing support for this report. Lionel Watkins and Felix Gonzalez developed the graphics

xxi
for Volume 1. We also greatly appreciate Dariusz Szwarc and Alan Kouchinsky for their

assistance finalizing this report.

We wish to acknowledge the team of peer reviewers who reviewed the initial draft of this report

and provided valuable comments. The peer reviewers were Dr. Craig Beyler and Mr. Phil

DiNenno of Hughes Associates, Inc., and Dr. James Quintiere of the University of Maryland.

Finally, we would like to thank the internal and external stakeholders who took the time to

provide comments and suggestions on the initial draft of this report when it was published in the

Federal Register (71 FR 5088) on January 31, 2006. Those stakeholders who commented are

listed and acknowledged below.

Janice Bardi, ASTM International

Moonhak Jee, Korea Electric Power Research Institute

U.S. Nuclear Regulatory Commission, Office of Nuclear Reactor Regulation Fire Protection

Branch

J. Greg Sanchez, New York City Transit

David Showalter, Fluent, Inc.

Douglas Carpenter, Combustion Science & Engineering, Inc.

Nathan Siu, U.S. Nuclear Regulatory Commission, Office of Nuclear Regulatory Research

Clarence Worrell, Pacific Gas & Electric

xxii
LIST OF ACRONYMS

AGA

AHJ

ASME

ASTM

BE

BFRL

BRE

BWR

CDF

CFAST

CFD

CFR

CSR

EdF

EPRI

FDS

FDTS

FHA

FIVE-Rev 1

FMRC

FM/SNL

FPA

FRA

GRS

HGL

HRR

American Gas Association

Authority Having Jurisdiction

American Society of Mechanical Engineers

American Society for Testing and Materials

Benchmark Exercise

Building and Fire Research Laboratory

Building Research Establishment

Boiling-Water Reactor

Core Damage Frequency

Consolidated Fire Growth and Smoke Transport Model

Computational Fluid Dynamics

Code of Federal Regulations

Cable Spreading Room

Electricit6 de France

Electric Power Research Institute

Fire Dynamics Simulator

Fire Dynamics Tools (NUREG- 1805)

Fire Hazard Analysis

Fire-Induced Vulnerability Evaluation, Revision 1

Factory Mutual Research Corporation

Factory Mutual & Sandia National Laboratories

Foote, Pagni, and Alvares

Fire Risk Analysis

Gesellschaft ffir Anlagen-und Reaktorsicherheit (Germany)

Hot Gas Layer

Heat Release Rate

xxiii
IAFSS International Association of Fire Safety Science

iBMB3 Institut fir Baustoffe, Massivbau und Brandschutz

ICFMP International Collaborative Fire Model Project

IEEE Institute of Electrical and Electronics Engineers

IPEEE Individual Plant Examination of External Events

LIFT Lateral Flame Ignition Test

LLNL Lawrence Livermore National Laboratory

LNG Liquified Natural Gas

MCC Motor Control Center

MCR Main Control Room

MQH McCaffrey, Quintiere, and Harkleroad

MOU Memorandum of Understanding

NBS National Bureau of Standards (now NIST)

NFPA National Fire Protection Association

NIST National Institute of Standards and Technology

NPP Nuclear Power Plant

NRC U.S. Nuclear Regulatory Commi ssion

NRR Office of Nuclear Reactor Regulation (NRC)

PMMA Polymethyl-methacrylate

PRA Probabilistic Risk Assessment

PWR Pressurized Water Reactor

RCP Reactor Coolant Pump

RES Office of Nuclear Regulatory Research (NRC)

RI/IPB Risk-Informed, Performance-Based

SBDG Stand-By Diesel Generator

SDP Significance Determination Process

SFPE Society of Fire Protection Engineers

SNL Sandia National Laboratory

SWGR Switchgear Room

V&V Verification & Validation

xxiv
LIST OF ACRONYMS

AGA

AHJ

ASME

ASTM

BE

BFRL

BRE

BWR

CDF

CFAST

CFD

CFR

CSR

EdF

EPRI

FDS

FDT'

FHA

FIVE-Rev 1

FMRC

FM/SNL

FPA

FRA

GRS

HGL

HRR

American Gas Association

Authority Having Jurisdiction

American Society of Mechanical Engineers

American Society for Testing and Materials

Benchmark Exercise

Building and Fire Research Laboratory

Building Research Establishment

Boiling-Water Reactor

Core Damage Frequency

Consolidated Fire Growth and Smoke Transport Model

Computational Fluid Dynamics

Code of Federal Regulations

Cable Spreading Room

Electricit6 de France

Electric Power Research Institute

Fire Dynamics Simulator

Fire Dynamics Tools (NUREG- 1805)

Fire Hazard Analysis

Fire-Induced Vulnerability Evaluation, Revision 1

Factory Mutual Research Corporation

Factory Mutual & Sandia National Laboratories

Foote, Pagni, and Alvares

Fire Risk Analysis

Gesellschaft ffir Anlagen-und Reaktorsicherheit (Germany)

Hot Gas Layer

Heat Release Rate

xxv
IAFSS international Association of Fire Safety Science

iBMB Institut flir Baustoffe, Massivbau und Brandschutz

ICFMP International Collaborative Fire Model Project

IEEE Institute of Electrical and Electronics Engineers

IPEEE Individual Plant Examination of External Events

LIFT Lateral Flame Ignition Test

LLNL Lawrence Livermore National Laboratory

LNG Liquified Natural Gas

MCC Motor Control Center

MCR Main Control Room

MQH McCaffrey, Quintiere, and Harkleroad

MOU Memorandum of Understanding

NBS National Bureau of Standards (now NIST)

NFPA National Fire Protection Association

NIST National Institute of Standards and Technology

NPP Nuclear Power Plant

NRC U.S. Nuclear Regulatory Commission

NRR Office of Nuclear Reactor Regulation (NRC)

PMMA Polymethyl-methacrylate

PRA Probabilistic Risk Assessment

PWR Pressurized Water Reactor

RCP Reactor Coolant Pump

RES Office of Nuclear Regulatory Research (NRC)

RI/PB Risk-Informed, Performance-Based

SBDG Stand-By Diesel Generator

SDP Significance Determination Process

SFPE Society of Fire Protection Engineers

SNL Sandia National Laboratory

SWGR Switchgear Room

V&V Verification & Validation

xxvi
INTRODUCTION

As the use of fire modeling tools increases in support of day-to-day nuclear power plant (NPP)

applications including fire risk studies, the importance of verification and validation (V&V)

studies of these tools also increases. V&V studies give fire modeling analysts confidence

in applying analytical tools by quantify"ing and discussing the performance of the given model

in predicting the fire conditions measured in a particular experiment. The underlying assumptions,

capabilities, and limitations of the model are discussed and evaluated as part of the V&V study.

This volume documents the V&V study of the library of quantitative fire hazards analysis (FHA)

models known as Fire Dynamics Tools (FDTs). Quantitative FHA tools can be useful in

predicting the risks of fire hazards in various settings within an NPP. Consequently, a number of

quantitative FHA tools (including the FDTs library) have been developed - with varying

capabilities and levels of complexity - to serve this purpose.

The U.S. Nuclear Regulatory Commission (NRC), Office of Nuclear Reactor Regulation (NRR),

developed the FDT5 library [1] using state-of-the-art principles of fire dynamics to assist fire

protection inspectors in performing risk-informed evaluations of credible fires that may cause

critical damage to essential safe-shutdown equipment. Toward that end, the FDTs library

comprises a series of Microsoft® Excel® spreadsheets, which are pre-programmed with fire

dynamics equations and correlations to assist inspectors in performing quick, first-order

calculations for potential fire scenarios. The technical bases for the models included in the FDTs

library were primarily derived from the National Fire Protection Association (NFPA) Fire

Protection Handbook [2], the Society of Fire Protection Engineers (SFPE) Handbook of Fire

Protection Engineering [3], and other fire science literature. This report describes the equations

included in the spreadsheets that have been subjected to V&V, the technical bases of those

equations, and evaluation of the sensitivities and predictive capabilities of the component

spreadsheets.

The V&V methodology employed in this report generally follows the guidelines outlined in

ASTM E 13 55, Standard Guide for Evaluating the Predictive Capability of Deterministic

Fire Models [4]. These guidelines were published by the American Society for Testing and Materials

(ASTM). As such, this report presents the fire model evaluation methodology in terms of the

following basic focuses of evaluation:

" Define the model and scenarios for which the evaluation is to be conducted.

* Assess the appropriateness of the theoretical basis and assumptions used in the model.

* Assess the mathematical and numerical robustness of the model.

* Quantify' the uncertainty and accuracy of the model results in predicting the course of events

in similar fire scenarios.

1-1
Introduction

In accordance with ASTM E 1355, it is critical to evaluate fire models to establish their

acceptable uses and limitations. Evaluation is also necessary to ensure that those using the models

can assess the adequacy of their scientific and technical bases, select appropriate models for

a desired use, and understand the levels of confidence that can be placed on the results predicted

by the models. Adequate evaluation will also help to prevent unintended misuse of fire models.

Evaluation of a fire model includes model verification and validation. Verification is the process to

determine that a model correctly represents the developer's conceptual description. It is used to

decide whether the model was "built" correctly. Validation is the process to determine that a

model is a suitable representation of the real world and is capable of reproducing phenomena of

interest. As such, validation is used to decide whether the right model was "built."

It is not possible to evaluate a fire model in its entirety. Thus, guidance such as that provided

in ASTM E 1355 is intended to define a methodology for evaluating the predictive capabilities

for a specific use. Validation for one application does not indicate validation for a different scenario.

In accordance with ASTM E 1355, this report is structured as follows:

* Chapter 2 provides qualitative background information about FDTS and the V&V process.

* Chapter 3 describes the technical and theoretical bases of the FDTS correlations that were

included in this V&V study. This chapter also discusses the assumptions and limitations

associated with each of the evaluated correlations.

" Chapter 4 discusses the mathematical and numerical robustness of the FDTS correlations.

* Chapter 5 presents a sensitivity analysis, for which the researchers defined a "base case"

scenario and varied selected input parameters in order to test each correlation's response

to changes in the input parameters.

" Chapter 6 presents the results of the V&V study in the form of relative differences classified

according to relevant attributes of enclosure fires in NPPs.

* Appendix A presents the technical details supporting the calculated accuracies discussed

in Chapter 6.

1-2
2

MODEL DEFINITION

This chapter provides qualitative background information about FDTs and the V&V process,

as suggested by ASTM E 1355. Sufficient documentation of calculation methods is necessary

to assess. the adequacy of their scientific and technical bases, as well as the accuracy of the

computational procedures for the scenarios of interest. In addition, adequate documentation

helps to prevent the unintentional misuse of the models.

This chapter briefly describes the FDTs library, following the framework suggested by ASTM E

1355 [4]. As such, this chapter identifies the version of the library that was evaluated in this study;

identifies its type, developers, and relevant publications; discusses its governing equations

and assumptions, as well as the required input data, property data, and results; and outlines

the uses and limitations of the library. Chapter 3 presents more detailed information concerning

the equations and correlations that comprise each of the library's component spreadsheets.

2.1 Name and Version of the Model

The majority of this study evaluated Version 1805.0 of the Fire Dynamics Tools (FDTs), which

the NRC released in December 2004. However, certain spreadsheets have been corrected and

were released in June and August 2005 as Version 1805. 1. When the analysts used these

spreadsheets, they used Version 1805. 1. The versions of the specific spreadsheets are identified

in Chapter 3.

2.2 Type of Model

The FDTs library contains a series of Microsofto Excels spreadsheets, which are pre-programmed

with fire dynamics equations and correlations to assist users in performing quick, first-order

calculations for potential fire scenarios. Each spreadsheet also contains a list of the physical

and thermal properties of the materials commonly encountered in NPPs.

2.3 Model Developers

The FDTs library was developed by the staff of the NRC's Office of Nuclear Reactor Regulation

(NRR).

2.4 Relevant Publications

The FDTs library is documented in NUREG- 1805, "Fire Dynamics Tools (FDTs): Quantitative

Fire Hazard Analysis Methods for the U.S. Nuclear Regulatory Commission Fire Protection

Inspection Program" [ I]. NUREG- 1805 contains the FDTs Excelo worksheets and a detailed

discussion of the technical and theoretical bases for each of the fire dynamics tools included in

the package. The document also describes the uses and limitations of the spreadsheets and

includes sample applications for each.

2-1
Model Definition

Other relevant texts include the NFPA Fire Protection Handbook [2] and the SFPE Handbook of

Fire Protection Engineering [3 ], as well as other references in NUREG- 1805.

2.5 Governing Equations and Assumptions

The governing equations and assumptions used in the FDTs spreadsheets come primarily from

the principles described in the NFPA Fire Protection Handbook [2] , the SEPE Handbook of Fire

Protection Engineering [3], and other fire science literature. Those governing equations and

assumptions are generally accepted within the fire science community as the state-of-the-art

in calculation methods for fire phenomena. Chapter 3 provides detailed descriptions of the equations

programmed into the spreadsheets included in this V&V study.

2.6 Input Data Required to Run the Model

Each FDTs spreadsheet requires the user to input certain fire parameters that are necessary

for the equations to compute the output of interest. For example, a spreadsheet may require

information about the dimensions of the fire enclosure, the fire size, the ambient room conditions,

material properties and so forth. To reduce the chance of user error, the spreadsheets include

drop-down selection menus for pre-programmed properties of various materials that are

commonly found in NPPs.

2.7 Property Data

Some of the models in the FDTs library require the following property data:

* thermal properties of enclosure surfaces:

);; thermal inertia

);o thermal conductivity

Sspecific heat

> density

" fuel properties:

> mass burning rate

> effective heat of combustion

> density

> fuel vapor mass

> fuel vapor density

" target properties:

Smaterial thermal inertia

Smaterial ignition temperature

Smaterial critical heat flux for ignition

2.8 Model Results

The FDTs spreadsheets use simple algebraic calculations that require little or no computation time

to produce first-order results. The output generated by each FDTs spreadsheet is presented

as either a single point value numerical result or a series of point values accompanied by a plot

showing the trend in the results within the Excel® spreadsheet.

2-2
Model Definition

2.9 Uses and Limitations of the Model: ;:.

Chapter 3 discusses the limitations and assumptions associated with each of the fire dynamics tools,

within the context of its technical basis.

The primary objective of the FDT5 library and the accompanying documentation (NUREG- 1805)

is to provide a methodology for NRC fire protection inspectors to use in assessing potential

fire hazards in NRC-licensed NPPs. The methodology uses simplified, quantitative FHA techniques

to evaluate the potential hazard associated with credible fire scenarios. One purpose of these

evaluations is to determine whether a potential fire can cause critical damage to safe-shutdown

components. Its intent is to provide insights into fire dynamics, without using the sophisticated

mathematics that are normally associated with the study of fire dynamics. Inspectors using these

tools need a working knowledge of algebra, graphical interpretation, scientific notation, formulas,

and use of some simple mathematics functions to understand the quantitative aspects of fire

phenomena.

2-3

3,

THEORETICAL BASIS FOR FOTs

This chapter presents a technical description of the FDTs library, including theoretical background

and the underlying physics and chemistry inherent in the component models. The discussion

includes assumptions and approximations, an assessment of whether the open literature provides

sufficient scientific evidence to justify the approaches and assumptions used, and an assessment

of empirical or reference data used for constant or default values in the context of the model.

In so doing, this chapter addresses the ASTM E 1355 guidance to "'verify the appropriateness

of the theoretical basis and assumptions used in the model."

FDTs is a set of algebraic hand calculations pre-programmed into Microsoft® Excelo

spreadsheets. The FDTs library includes 23 distinct spreadsheets that can be used to calculate

various fire parameters under varying conditions. Documentation of the theoretical bases

underlying the equations used in the FDT5 spreadsheets will help to ensure that users understand

the significance of the inputs that each spreadsheet requires, and why a particular spreadsheet

should (or should not) be selected for a particular analysis. This chapter explains the predictive

equations used in the FDTS spreadsheets that were subjected to V&V in this study, as listed in

Table 3-1. Note that some spreadsheets in the FDTs library have not been subjected to V&V

in this study because of a lack of applicable and useable experimental data for comparison.

NUREG- 1805 provides complete documentation of the equations and theoretical bases for the

FDTs library.

3-1
Theoretical Basis for FDTS

Table 3-1: Spreadsheets Included in the V&V Study _________

Spreadsheet Name Excel File Name V&V

Predicting Hot Gas Layer Temperature 02.1_-TemperatureNV.xls

and Smoke Layer Height in a Room Fire (v. 1805.0) Yes

With Natural Ventilation Compartment

Predicting Hot Gas Layer Temperature in 02.2_-TemperatureFV.xls

a Room Fire With Forced Ventilation (v. 1805.0) Yes

Compartment

Predicting Hot Gas Layer Temperature in 02.3_-TemperatureCC.xls Yes

a Fire Room With Door Closed (v. 1805.1)

Estimating Burning Characteristics of 03_HRR_-Flame_-Height-Burning Yes

Liquid Pool Fire, Heat Release Rate, _Duration_Calculation.xls (flame height only) Bumning Duration and Flame Height (v. 1805.0)

Estimating Wall Fire Flame Height, Line 04_Flame Height Calculations.xls

Fire Flame Height Against the Wall, and No

Corner Fire Flame Height

Estimating Radiant Heat Flux From Fire to 05.1_-Heat_-Flux_-Calculations_ Yes

a Target Fuel at Ground Level Under WindFree.xls (Point Source

Wind-Free Condition (v. 18F05.0) Radiation, and Solid

Flame 2 Models)

Estimating Radiant Heat Flux From Fire to 05.1_-Heat_-Flux_-Calculations_

a Target Fuel above Ground Level Under WindFree.xls No

Wind-Free Condition

Estimating Radiant Heat Flux From Fire to 05.2_HeatFluxCalculations- No

a Target Fuel Under Presence of Wind Wind.xls

Estimating Thermal Radiation from 05.3_-ThermalRadiationFrom- No

Hydrocarbon Fireball HydrocarbonFireballs.xls

Estimating the Ignition Time of a Target 06 IgnitionTimeCalculations.xls

Fuel Exposed to a Constant Radioactive No

Heat Flux

Estimating Full-Scale Heat Release Rate 07_CableHRRCalculations.xls No

of a Cable Tray Fire

Estimating Burning Duration of Solid 08_BurningDurationSoild.xls No

Combustibles

Estimating Centerline Temperature of a 09_-Plume -Temperature_

Buoyant Fire Plume Calculations.xls Yes

(v. 1805.0) _________

Estimating Detector Response Time 10_DetectorActivationTime.xls No

Predicting Compartment Flashover 13_Compartment- Flashover- No

Calculations.xls

3-2
Theoretical Basis for FDTS

Spreadsheet Name Excel File Name V&V

Estimating Pressure Rise Attributable to 14_Compartment_-OverPressure- No

a Fire in a Closed Compartment Calculations.xls

Estimating the Pressure Increase and 15_Explosion Claculations.xls

Explosive Energy Release Associated No

with Explosions

Calculating the Rate of Hydrogen Gas 16_BatteryRoom_FlammableGas No

Generation in Battery Rooms _Conc.xls

Calculating the Fire Resistance of 17.1_-FRBeamsColumns_

Structural Steel Members-Empirical SubstitutionCorrelation.xls No

Correlations

Calculating the Fire Resistance of 17.2_-FRBeams_-ColumnsQuasi_

Structural Steel Members- Beam and Steady__StateSpray lnsulated.xls

Column Substitution Correlations and No

Heat Transfer Analysis using Numerical

Methods (Spray Applied)________________

Calculating the Fire Resistance of 17.3_FRBeamsColumnsQuasi_

Structural Steel Members- Beam and SteadyStateBoard-lnsulated.xls No

Column Heat Transfer Analysis using

Numerical Methods (Board Materials) __________________________

Calculating the Fire Resistance of 17.4_FRBeamsColumnsQuasi_

Structural Steel Members- Unprotected SteadyState Uninsulated.xls No

Beam and Column Heat Transfer

Analysis using Numerical Methods

Estimating Visibility Through Smoke 18 Visibility ThroughSmoke.xls No

3.1 Estimating Hot Gas Layer Temperature

The various FDT s spreadsheets include a number of correlations for estimating the average hot

gas layer (HGL) temperature under varying conditions. The correlations assume a homogenous

upper layer in a compartment; thus, the output is an average. The spreadsheet for calculating

HGL temperature in a compartment with natural ventilation also includes a calculation for HGL

or smoke layer height. This section discusses the predictive equations for each of the correlations

used to estimate HGL temperature; while Section 3.2 discusses the correlations for smoke layer

height. Section 3.3 summarizes the assumptions and limitations inherent to these spreadsheets.

Chapter 2 of NUREG- 1805 [1I] is the reference for the following discussion on estimating HGL

temperature and smoke layer height.

3. 1.1 Natural Ventilation: Method of McCaffrey, Quintiere, and Harkleroad (MQH)

A compartment with a single rectangular wall opening (such as a door or window) is commonly used

for room fire experiments. Such compartments are also commonly involved in real fire scenarios,

in which a single door or vent opening serves as the only path for fire-induced natural ventilation

to the compartment. The hot gas layer that forms in compartment fires descends within the opening

3-3
Theoretical Basis for FDTS

until a quasi-steady balance is struck between the rate of mass inflow to the layer and the rate

of mass outflow from the layer.

The temperatures throughout a compartment in which a fire is burning are affected by the amount

of air supplied to the fire and the location at which the air enters the compartment. Ventilationlimited fires produce different temperature profiles in a compartment than well-ventilated fires.

As the flow of air into the fire affects the temperature, as does the flow out of the compartment.

In this effect, the energy transferred from the fire to the air and hot gases can be exhausted as

fresh air comes into the compartment. In addition, heat from the fire is lost to and through the

compartment boundaries. The losses of heat and energy out through openings, as well as to

and through the walls, balance the energy in the compartment attributable to the fire itself.

McCaffrey, Quintiere, and Harkleroad (MQH) [5] have developed a simple best fit dimensionless

correlation for evaluating HGL temperature in a compartment with natural ventilation. This MQH

correlation is based on 100 experimental fires (from 8 test series involving several types of fuel)

in conventional-sized rooms with a variety of wall lining materials and openings. The

temperature differences varied from AT = 20 'C to 600 'C (68 to 1, 112 'F). The fire source was

away from walls (i.e., data were obtained from fires located in the center of the compartment).

The larger the heat release rate (HRR) and the smaller the vent, the higher we expect the upperlayer gas temperature to increase.

The approximate formula for the HGL temperature increase, ATg, above ambient (Tg - Ta)

is as follows:

A g=6.8 [ Q.2x l

hAT(~h,

i(AvF(3-1)

Where:

ATg = upper-layer gas temperature rise above ambient (Tg - Ta) (K)

Q = heat release rate of the fire (kW)

A,= area of ventilation opening(s) (in 2

)

hv= height of ventilation opening (in)

hk = heat transfer coefficient (kW/in 2

-K)

AT = total area of the compartment enclosing surfaces (in 2 ) , excluding area of vent

opening(s)

This method assumes that heat loss occurs as a result of mass flowing out through openings.

The compartment interior surface area, AT, is calculated as follows:

AT =[2 (w, x I + 2(hc x wj+ 2(h,,x 1,)] -A, (3-2)

Where:

AT = total compartment interior surface area (m 2 ) , excluding area of vent opening(s)

w,= compartment width (in)

3-4
Theoretical Basis for FDTS

1,= compartment length (in)

=, compartment height (in)

A, total area of ventilation opening(s) (in)

To determine the heat transfer coefficient, hik, in Eq. 3 -1, we have to consider the time when

conduction through the boundary walls reaches steady-state. This time is referred to as the

thermal penetration time, ti,, which can be calculated as follows:

k 2 (3 -3)

Where:

p =density of the interior lining (k g/rn3)

=p thermal capacity of the interior lining (kJ/kg-K)

k =thermal conductivity of the interior lining (kW/in-K)

8 thickness of the interior lining (in)

For very thin solids, or for conduction through a solid that continues for a long time, the process

of conduction becomes steady-state. These solids are said to be "thermally thin." The thermal

penetration time (tp) is greater than or equal to the time of interest (t Ž: tp). The heat transfer

coefficient, hk, after long heating times, can be written as follows:

k

hk =-~-(3-4)

Where:

k = thermal conductivity (kW/m-K) of the interior lining

5 = thickness of the interior lining (in)

However, if the burning time is less than the thermal penetration time, tp, the boundary material

retains most of the energy transferred to it and little will be lost out the non-fire (cold) side.

The solid is referred to as "thermally thick." The thermal penetration time (tp) is less than

the time of interest (t < tp). In this case, the heat transfer coefficient, hk, can be estimated using

the following equation:

h= kpc

1t_ (3-5)

Where:

kpc =interior construction thermal inertia [(kW/M2

-K)2-sec]

3-5
Theoretical Basis for FDTS

t = time after ignition in seconds (characteristic burning time)

As previously indicated, the kpc parameter is a thermal property of the material responsible for

the rate of temperature increase. This is the product of the material thermal conductivity (k),

material density (p), and heat capacity (c). Collectively, kpc is known as the thermal inertia of a

solid material. For most materials, c does not vary significantly, and the thermal conductivity is

largely a function of material density. This means that density tends to be the most important

material property.

Thermal inertias (kpc), for a variety of generic materials have been reported in the literature.

These values have been derived from measurements in the small-scale lateral ignition and flame

spread test (LIFT) apparatus [6].

3.1.2 Natural Ventilation (Compartment Closed): Method of Beyler

Beyler [7] developed a correlation based on a non-steady energy balance to the closed compartment, by

assuming that the compartment has sufficient leaks to prevent pressure buildup (also reported by

Walton and Thomas [8]). For constant HRR, the compartment HGL temperature increase, ATg,

above ambient (T9 - Ta) is given by the following equation:

AT's = Tg Ta 2(KV-+eK)

Ki (3-6)

Where:

K,=2(O.4,fkip)A, K Q

And:

ATg = upper-layer gas temperature rise above ambient (Tg - Ta) (K)

AT = total area of internal compartment boundaries (in)

k = thermal conductivity of the interior lining (kW/m-K)

p =density of the interior lining (kg/in 3)

c = thermal capacity of the interior lining (kJ/kg-K)

4) = heat release rate of the fire (kW)

mn = mass of the gas in the compartment (kg)

cp= specific heat of air (kJ/kg-k)

t = exposure time (sec)

This correlation has been favorably compared against data from experiments that ranged from

50kW to 400kW (0.2 > Qd> 1.5). These tests were ventilation-controlled.

3-6
Theoretical Basis for FDTS

3.1.3 Forced Ventilation: Method of Foote, Pagni, and Alvares (FPA)

Foote, Pagni, and Alvares [ 10] developed another method that follows the basic correlations

of the MQH method, but adds components for forced-ventilation fires (also reported in

references 8 and 9). This method is based on temperature data that were obtained from a series

of tests conducted at Lawrence Livermore National Laboratory (LLNL), in which fresh air was

introduced at the floor and pulled out the ceiling by an axial fan. Test fires from 150 to 490 kW

(0.5 > Qd*> 1.9) were used, producing ceiling jet temperatures of 100 to 300 'C (212 to 572 'F).

The approximate constant ventilation rates were roughly 200 to 575 cfmn, and were chosen to be

representative of possible fires in rooms with seven room air changes per hour. These tests were

well-ventilated.

The upper-layer gas temperature increase above ambient is given as a fuinction of the fire HRR,

compartment ventilation flow rate, gas-specific heat capacity, compartment surface area, and

effective heat transfer coefficient. The non-dimensional form of the resulting temperature

correlation is as follows:

AT = O.63( hcý a 0.72( ji -0.36 (7

Where:

ATg = hot gas layer temperature rise above ambient (T9 - Ta) (K)

Ta = ambient air temperature (K)

Q = HRR of the fire (kW)

mh = compartment mass ventilation flow rate (kg/sec)

cp= specific heat of air (UJ/kg-K)

hk = heat transfer coefficient (kW/m2-K)

AT= total area of compartment enclosing surfaces (in2 )

3.1.4 Forced Ventilation: Method of Deal and Beyler

Deal and Beyler [111] developed a simple model of forced-ventilation compartment fires

(also reported in reference 9). The model is based on a quasi-steady simplified energy equation

with a simple wall heat loss model. The model is based on data up to 2,000 seconds into fire tests.

At longer times, the heat loss model breaks down as a result of the simple formulation

of the steady-state heat loss model [ 12]. The approximate compartment HGL temperature

increase, ATg, above ambient (Tg -Ta) is given by the following equation:

Q

A~g = ~Ta= 11 + hkAT (3-8)

Where:

3-7
Theoretical Basis for FDTS

ATg = hot gas layer temperature rise above ambient (Tg - Ta) (K)

Ta = ambient air temperature (K)

Q = HRR of the fire (kW)

mh = compartment mass ventilation flow rate (kglsec)

cp=specific heat of air (kJ/kg-K) WM

hk = convective heat transfer coefficient (kW/m-K)

AT =total area of compartment enclosing surfaces (in)

The convective heat transfer coefficient is given by the following expression:

hk=O0.4rnx kpc1

Where:

k = thermal conductivity of the interior lining (kW/m-K)

p = density of the interior lining (kg/in3)

c =thermal capacity of the interior lining (kJ/kg-K)

t =exposure time (sec)

6 =thickness of the interior lining (in)

This correlation has been compared against an expansive database of experiments with favorable

results [9].

3.2 Estimating Smoke Layer Height

The smoke layer can be described as the accumulated thickness of smoke below a physical

or thermal barrier (e.g., ceiling). The smoke layer is not necessarily a homogeneous mixture,

and it does not typically have a uniform temperature. However, for first-order approximations,

the calculation methods presented below assume homogeneous conditions. The smoke layer

includes a transition zone that is non-homogeneous and separates the hot upper layer

from the smoke-free air (i.e., two zones).

3.2.1 Natural Ventilation (Smoke Filling): The Non-Steady-State Yamana

and Tanaka Method

In a compartment with larger openings (windows or doors), there will be little or no buildup

of pressure attributed to the volumetric expansion of hot gases, with the exception of rapid

accumulation of mass or energy. Thus, for first-order approximations, pressure is assumed

to remain at the ambient pressure. The opening flows are thus determined by the hydrostatic

pressure differences across the openings, and mass flows out of and into the compartment.

We also assume that the upper-layer density (pg) is some average constant value at all times

throughout the smoke-filling process.

3-8
Theoretical Basis for FDTS

Assuming a constant average density in the upper hot gas layer allows one to form an analytical

solution of the smoke-filling rate, and we can use the conservation of mass to get an expression

for the smoke-filling rate. This expression allows one to calculate the height of the smoke layer

as a function of time, and we can use the conservation of energy to check the stipulated value of pg..

Yamana and Tanaka [ 13 ] developed a general expression for the height of the smoke layer

interface, z, as a function of time. The general expression can be simplified as follows

for a constant HRR (also reported in reference 14):

3

z ~+ -

Where:

z =height (in) of the smoke layer interface above the floor

Q=heat release rate of the fire (kW)

t =time after ignition (sec)

A, compartment floor area (in 2 )

h, compartment height (in)

And:

k = a constant given by the following equation:

Pg ~cpTa)

Where:

Pg= hot gas density kg/rn 3 g

Pa = ambient density =1.20 kg/rn

g =acceleration of gravity = 9.81 rn/sec

=p specific heat of air = 1.0 kJ/kg-K

Ta =ambient air temperature = 298 K

Substituting the above numerical values in Equation 3-1 1, we obtain the following expression:

0.076

Pg (3-12)

Where density of the hot gas layer (pg) is given by the following equation:

353

Pg=

g9 (3-13)

3-9
Theoretical Basis for FDTS

Where:

Tg = hot gas layer temperature (K) calculated from Equation 3-1

3.3 Assumptions and Limitations for Hot Gas Layer Calculations

The methods discussed in this chapter have several underlying assumptions and limitations.

The following assumptions and limitations apply to all forced and natural ventilation situations:

(1) These methods best apply to conventional-sized compartments; they have not been

validated as extensively for large compartments.

(2) These methods apply to both transient and steady-state fire growth, subject to

the limitations of each individual method for the scenario being examined.

(3) The HRR must be known; it does not need to be constant, and can be allowed to change

with time.

(4) Compartment geometry assumes that a given space can be analyzed as a rectangular space

with no beam pockets. This assumption affects the smoke filling rate within a space

if the space has beam pockets. For irregularly shaped compartments, equivalent

compartment dimensions (length, width, and height) must be calculated and should yield

slightly higher layer temperatures than would actually be expected from a fire

in the given compartment.

(5) These methods predict average temperatures and do not apply to cases in which

prediction of local temperature is desired. For example, this method should not be used

to predict detector or sprinkler actuation or the material temperatures resulting from

direct flame impingement.

(6) Caution should be exercised when the compartment overhead are highly congested

with obstructions such as cable trays, conduits, ducts, and so forth.

(7) A single heat transfer coefficient may be used for the entire inner surface of the compartment.

(8) The heat flow to and through the compartment boundaries is unidimensional

(i.e., comners and edges are ignored, and thermally thick boundaries are assumed to be

semi-infinite slabs).

The following assumptions and limitations apply only to natural ventilation situations:

(1) The correlations hold for compartment upper-layer gas temperatures up to approximately

600 IC (1,112 'F) only for naturally ventilated spaces in which a quasi-steady balance

develops between the rates of mass inflow and outflow from the hot gas layer.

(2) These correlations assume that the fire is located in the center of the compartment

or away from the walls. If the fire is flush with a wall or in a comner of the compartment,

the MQH correlation is not valid with coefficient 6.85. The smoke layer height correlation

assumes an average constant value of upper-layer density throughout the smoke-filling process.

The following assumptions and limitations apply only to forced ventilation situations:

(1) These correlations assume that the test compartment is open to the outside at the inlet,

and its pressure is fixed near 1 atmosphere.

3-10
Theoretical Basis for FDTS

(2) These correlations do not explicitly account for evaluation of the fire source, and they

assume that the fire is located in the center of the compartment or away from the walls.

If the fire is flush with a wall or in a corner of the compartment, the EPA correlation

is not valid with coefficient 0.63.

3.4 Flame Height

As documented in Chapter 3 of NUREG- 1805 [1I], the height of a flame is a significant indicator

of the hazard posed by the flame. Flame height directly relates to flame heat transfer

and the propensity of the flame to impact surrounding objects. The height and temperature

of the flame are important in estimating the ignition of adjacent combustibles. Figure 3-1 shows

a characteristic sketch of the flame height fluctuations associated with the highly intermittent

pulsing structure of a flame, particularly along its perimeter and near its top. This intermittence

is driven largely by the turbulent mixing of air and subsequent combustion. The pulsing behavior,

in turn, affects the temperature of the flame. Thus, the temperature at a fixed position fluctuates

widely, particularly around the edges and near the top of the flame. This is why flame temperature

is usually reported in terms of the centerline temperature or average flame temperature.

I

Figure 3-1: Characteristics of Flame Height Fluctuations

Above the fuel source, the flaming region is characterized by high temperature and is generally

luminous. Flames from pool fires fluctuate periodically so that the tip of the flame is significantly

different from the length of the continuous combustion (or luminous) region. Consequently,

flame height has been defined by various criteria in order to correlate data. Researchers define

flame height as the height at which the flame is observed at least 50% of the time.

The flame height is an important quantitative characteristic of a fire and may affect fire detection

and suppression system design, fire heating of building structures, smoke filling rates, and fire ventilation.

The Heskestad correlation is widely used to determine the flame height of pool fires [ 15]:

2

H f= 0.235Q 5 - 1.02D (3-14)

3-11
Theoretical Basis for FDTS

Where:

Hf = flame height (in)

Q = heat release rate of the fire (kW)

D = diameter of the fire (in)

The HRR of the fire can be determined by laboratory or field testing. In the absence

of experimental data, the maximum HRR for the fire is given by the following equation [16]:

Where:

Q=heat release rate of the fire (kW)

iiv' = burning or mass loss rate per unit area (k/ 2-sec)

AHc,eff = effective heat of combustion (kJ/kg)

Af= burning area of the fuiel (in)

kJ3 = empirical constant (m-1)

D = diameter of burning area (in)

For non-circular pools, the effective diameter is defined as the diameter of a circular pool

with an area equal to the actual pool area given by the following equation:

D 4A f

7rZ (3-16)

Where:

Af is the surface area of the non-circular pool

3.4.1 Assumptions and Limitations

(1) The flame height correlation described in this chapter was developed for horizontal pooi fire

sources in the center or away from thle center of the compartment. The pool fires were assumed

to be circular or nearly circular.

(2) The size of the fire (flame height) depends on the diameter of the fuel and the HRR.

(3) There is no fire growth period. (As previously stated, real liquid pool fires grow very quickly,

and it is realistic to assume that the pool fire instantaneously reaches its maximum HRR.)

3-12
Theoretical Basis for FDTS

3.5 Estimating Radiant Heat Flux from Fire to a Target

Chapter 5 of NUREG-1805 [1] provides a complete discussion on the methods FDTs uses

to estimate radiant heat flux from fire to a target. The two methods used in this V&V study

are summarized below.

3.5.1 Point Source Radiation Model

A point source estimate of radiant flux is conceptually the simplest model of a radiant source used

in calculating the heat flux from a flame to target located outside the flame. The point source model

assumes that radiation emanates from a single point located in the middle of the flame to predict the

thermal radiation field of the flame.' The point source model provides a simple relationship

that varies as the inverse square of the distance, R. Figure 3-2 illustrates the point source model.

For an actual point source of radiation or a spherical source of radiation, the distance, R,

is simply the distance from the point or from the center of the sphere to the target.

The thermal radiation hazard from a fire depends on a number of parameters, including the composition

of the fuel, size and shape of the fire, its duration, proximity to the object at risk, and thermal

characteristics of the object exposed to the fire. The point source method may be used for either

fixed or transient combustibles.

The radiant heat flux at any distance from the source fire is inversely related to the horizontal

separation distance (R), by the following equation [ 17]:

X irO (3-17)

Where:

q=radiant heat flux (kW/M2 )

Q ==heat release rate of the fire (kW)

Ri radial distance from the center of the flame to the edge of the target (in)

Xr =fraction of total energy radiated

In general, Xr depends on the fuel, flame size, and flame configuration, and can vary from

approximately 0. 15 for low-sooting fuels (e.g., alcohol) to 0.60 for high sooting fuels

(e.g., higher-order hydrocarbons). For large fires (several meters in diameter), cold soot

enveloping the luminous flames can considerably reduce Xr,.

More realistic radiator shapes give rise to very complex configuration factor equations.

3-13
Theoretical Basis for FDTS

Ground Level D2

Figure 3-2: Radiant Heat Flux from a Pool Fire to a Floor-Based Target Fuel

(Point Source Model)

The IIRR of a fire can be determined by laboratory or field testing. In the absence

of experimental data, the maximum HRR for the fire, is given by Equation 3-15.

For non-circular poois, the effective diameter is defined as the diameter of a circular pool

with an area equal to the actual pooi area, given by Equation 3-16.

3.5.2 Solid Flame Radiation Model with Target at and Above Ground Level

The solid flame radiation model is a more detailed method for assessing the impact of radiation

from pool fires to potential targets using configuration factor algebra. This method covers

a range of detailed calculations, some of which are most appropriate for first-order initial hazard

assessments, while others are capable of more accurate predictions.

The solid flame model assumes that (1) the fire can be represented by a solid body of a simple

geometrical shape, (2) thermal radiation is emitted from its surface, and, (3) non-visible gases

do not emit much radiation. Figure 3-3 and Figure 3-4 illustrate the solid flame model.

To ensure that the fire volume is not neglected, the model must account for the volume, because

a portion of the fire may be obscured as seen from the target. The intensity of thermal radiation

from the pool fire to an element outside the flame envelope for no-wind conditions and for

windblown flames is given by the following equation [ 18]:

"=EFI, 2 (3-18)

Where:

q=incident radiative heat flux (kW/m2

)

E =average emissive power at flame surface (kW/M2)

F1 -2 = configuration factor

3-14
Theoretical Basis for FDTS

Ground Level .- D12-*-L ---- -

.41 R

Figure 3-3: Solid Flame Radiation Model with No Wind and Target at Ground Level

around Level

Figure 3-4: Solid Flame Radiation Model with No Wind and Target Above Ground

Emissive power is the total radiative power leaving the surface of the fire per unit area per unit time.

Emissive power can be calculated using Stefan's law, which gives the radiation of a black body

in relation to its temperature (black body is defined as a perfect radiator; a surface with an emissivity

of unity and, therefore, a reflectivity of zero). Because a fire is not a perfect black body,

the emissive power is a fraction (F,) of the black body radiation [ 18]:

E = PoT 4 (3-19)

Where:

E =flame emissive power (kW/M2 )

= flame emissivity

a Stefan-Boltzmann constant = 5.67 x 10- 11 (kW/m 2 -K 4 )

T =temperature of the fire (K)

3-15
Theoretical Basis for FDTS

The use of the Stefan-Boltzmann constant to calculate radiation heat transfer requires knowledge

of the temperature and emissivity of the fire; however, turbulent mixing causes the fire temperature

to vary. Consequently, Shokri and Beyler [19] correlated experimental data of flame radiation to

external targets in terms of an average emissive power of the flame. For that correlation,

the flame is assumed to be a cylindrical, black body, homogeneous radiator with an average

emissive power. Thus, effective emissive power of the pool fire in terms of effective diameter

is given by the following equation:

E = 58(1 0-0.00823D) (3-20)

Where:

E = flame emissive power (kW/m2)

D = diameter of pool fire (in)

This represents the average emissive power over the entire the flame and is significantly less

than the emissive power that can be attained locally. The emissive power is further reduced

with increasing pool diameter as a result of the increasing prominence of black smoke outside

the flame, which obscures the radiation from the luminous flame.

For non-circular pools, the effective diameter is defined as the diameter of a circular pool

with an area equal to the actual pool area, given by Equation 3-16.

The configuration factor is a purely geometric quantity, which provides the fraction

of the radiation leaving one surface that strikes another surface directly. In other words,

the configuration factor gives the fraction of hemispherical surface area seen by one differential

element when looking at another differential element on the hemisphere.

The configuration factor is a fuinction of target location, flame size (height), and fire diameter,

and is a value between 0 and 1. When the target is very close to the flame, the configuration

factor approaches 1, because everything viewed by the target is the flame. The flame is idealized

with a diameter equal to the pool diameter, D, and a height equal to the flame height, Hf.

If the pool has a length-to-width ratio near 1, an equivalent area circular source can be used

in determining the flame length, Hf, for non-circular pools. Figure 3-5 and Figure 3-6 illustrate

the cylindrical flame model under wind-free conditions.

3-16
Theoretical Basis for FDTS

I-f lýf

Vertical Target Horizontal Target

Figure 3-5: Cylindrical Flame Shape Configuration Factor Geometry

for Vertical and Horizontal Targets at Ground Level with No Wind

Hf 2

Hf Hf w

H

'fi

V

Figure 3-6: Cylindrical Flame Shape Conifiguration Factor Geometry

for Vertical and Horizontal Targets Above Ground with No Wind

The flame height of the pool can be determined by Equation 3-14.

The radiation exchange factor between a fire and an element outside the fire depends on

the shape of the flame, the relative distance between the fire and the receiving element, and

the relative orientation of the element. The turbulent diffusion flame can be Approximated by

a cylinder. Under wind-free conditions, the cylinder is vertical, as shown by Figure 3-5. If the

target is either at ground level or at the flame height, a single cylinder can represent the flame.

However, if the target is above the ground, two cylinders should be used to represent the flame.

For horizontal and vertical target orientations at ground level with no-wind conditions, given the

diameter and height of the flame, the configuration (or view factor) F 1.- 2 is determined using the

following equations related to cylindrical radiation sources [ 18]:

3-17
Theoretical Basis for FDTS

FI,, a- (B -IXS +1) (3-21)

(A-kJ_ _ _

stan-' FA-+ TS--Ij

gj ý_l (A-IXS+1)

I tan-' (h h ta-, ___-1

F, 2,= l n FA+IF _ (3-22)

7ES¶J 2 1 (ýA -1XS +1)

Where:

A h 2 +S 2 +1 B 1I-S 2

2S 2S

S 2R, h _=__

D D

And:

R = the distance between the center of the cylinder (flame) to the target (in)

Hf = the height of the cylinder (flame) (in)

D = the cylinder (flame) diameter (in)

The maximum configuration factor (or view factor) at a point is given by the vectorial sum

of the horizontal and vertical configuration factors:

F F H ~ 2 F~ 2 (-23)

As previously stated, for targets above the ground, two cylinders should be used to represent

the flame. In such instances, one cylinder represents the flame below the height of the target,

while the other represents the flame above the height of the target, as shown by Figure 3-6.

Thus, the following expressions are used to estimate the configuration factor (or view factor)

under wind-free conditions for targets above ground level:

-.tan - J~L tan-' S +

F F as 2,V (K2_ s V (S +1) (3-24) Alll tan- FA-,+-IT S-I1

t~K A2 -1 (Al -lXS + )

3-18
Theoretical Boasisfor FDTS

Where:

S=2R

D

2Hf

h, = _

D

h

2+S2+1

A hi2S

=,2V E 1 E SI (3-25) K~ tanK -

11 it tanS 

7ISFA2(1 2 -lXs + 1)

Where:

S2R

D

h2-2HfI

2D

A2 2 S+

2S

And:

R = the distance between the center of the cylinder (flame) to the target (in)

Hf =the height of the cylinder (flame) (in)

D =the cylinder (flame) diameter (in)

The total configuration factor or (view factor) at a point is given by the sum of two configuration

factors, as follows:

F,2Vn-id = FI2V + F-.2,V2 (3-26)

3.5.3 Assumptions and Limitations

The methods discussed in this chapter are subject to several assumptions and limitations.

For all radiation models, we assume that the pooi is circular or nearly circular.

The following assumptions and limitations apply to point source radiation models:

(1) Except near the base of pool fires, radiation to the surroundings can be approximated as

being isotropic or emanating from a point source.

(2) The point source model overestimates the intensity of thermal radiation at the observer's (target)

locations close to the fire. This is primarily because the near-field radiation is greatly influenced

by the flame size, shape, and tilt, as well as the relative orientation of the observer (target).

(3) A theoretical analysis of radiation from small pool fire by Modak [20] indicated that

the point source model is within 5% of the correct incident heat flux when LID > 2.5.

(4) The energy radiated from the flame is a specified fr-action of the energy released during combustion.

3-19
Theoretical Basis for FDTS

The following limitation applies to solidflame radiation models at and above ground level:-

(1) The correlation of emissive power was developed on the basis of data from experiments that

included kerosene, fuel oil, gasoline, JP-4, JP-5, and liquified natural gas (LNG). With the

exception of the LNG, these are quite luminous flames, so the correlation should be suitable

for most fuels. The pool diameters ranged from I to 50 mn (3.3 to 164 ft).

3.6 Estimating the Centerline Temperature o f a Buoyant Plume

As discussed in Chapter 9 of NUREG- 1805 [1I], the peak temperature is found in the plume

centerline, and decreases toward the edge of the plume where more ambient air is entrained

to cool the plume. The centerline temperature, denoted as Tp(centerline), varies with height.

In the continuous flame region, for example, the centerline temperature is roughly constant

and represents the mean flame temperature. By contrast, the temperature decreases sharply

above the flames as an increasing amount of ambient air is entrained into the plume. ATp(,enterline)

describes the increase in centerline plume temperature above the ambient temperature, Ta,

as shown in the following equation:

A Twenterine) =: Tp(M,,t&ine) - Ta (3-27)

Numerous correlations are available to estimate the plume centerline temperature. These correlations

relate the temperature as a function of HRR and of height above the source.

Heskestad [ 15] provided a simple correlation for estimating the maximumn centerline temperature of a

fire plume as a function of ceiling height and HRR.

-Z =O (-8

Where:

Tp(centerline) = plume centerline temperature (K)

Ta =ambient air temperature (K)

Qc convective HRR (kW)

g = acceleration of gravity (mlsec2

)

cp= specific heat of air (kJ/Kg-K)

Pa = ambient air density (kg/rn3)

z = elevation above the fire source (in)

zo = vertical distance of the virtual origin relative to the fire source (in)

The virtual origin is the equivalent point source height of a finite area fire (Figure 3-7).

The location of the virtual origin is needed to calculate the thermal plume temperature for fires

that originate in an area heat source. The thermal plume calculations are based on the assumption

that the plume originates in a point heat source. Area heat sources include pool fires and burning

three-dimensional objects such as cabinets and cable trays. The use of a point heat source model

for area sources is accomplished by calculating the thermal plume parameters at the virtual point

source elevation, rather than the actual area source elevation.

3-20
Theoretical Basis for FDTS

Fire Plume

Fig 

re 

3-7 

P intSo 

rce 

Fie 

lume

Th irul rgnz, eenso tedimte fth ir ouc ndte oaleegyrlesd

zo ~~~lm Heiruaioggnhin

D ~ ~ ~ dimeeeoiirgouch(n ~ ý me 

with areaequal-to-th-actual-are-given an byrEuation r3-16

orign. Hwevr, te covecivue 3-7: Po~ist used wh ren estimatne te lm rpris

bhevrtaus thiis, iseenso partte the energ of release the rate cassboac.thea that energy rlosses,

atiua ole b ow rdainfosh:lm aetpclyo h re o 04%o .Tehge

of hee s ald ales or hesotir ad or lmiousflme, fte fomfuls ha bm it

a ~ ~ lo ~ cobsinefcec.Q5s z hrfrotni h ag f6-0 fQ

3-21
Theoretical Basis for FDTS

3.6.1 Assumptions and Limitations

The methods discussed in this chapter are subject to several assumptions and limitations:

(1) All heat energy is released at a point.

(2) The correlation was developed for two-dimensional area sources.

(3) If the surrounding air is at an elevated temperature, the temperature difference between

the plume and the surrounding environment is small. In this situation, the thermal plume

cools less effectively, so Equation 3-28 will underestimate the temperature.

(4) The thermal plume equation is not valid when the momentum forces in a plume dominate

the buoyant forces, as in a jet fire. If this type of situation is encountered, specialized

calculation approaches should be used.

(5) Equation 3-28 is only valid above the flame.

3-22
4

MATHEMATICAL AND NUMERICAL ROBUSTNESS

This chapter documents the mathematical and numerical robustness of the FDTS library,

which involves verifying that the implementation of the model matches the stated documentation.

A model's mathematical and numerical robustness refers to its stability and ability to reliably

produce the results that the model developers intended it to produce. Specifically, ASTM E 1355

suggests the following analyses to address the mathematical and numerical robustness of models:

* Analytical tests involve testing the correct fimnctioning of the model. In other words, these tests

use the code to solve a problem with a known mathematical solution. However, there are

relatively few situations for which analytical solutions are known. The models in the FDTs

library used in this study do not solve problems with known mathematical solutions.

Therefore, the model results cannot be compared with known solutions to assess the correct

functioning of the models.

* The correlations pre-programmed in the spreadsheets of FDTS have been compared against

hand calculations using the same equations. This comparison verified the correctness

of the spreadsheet algorithms, as well as the handling of data. These comparisons have been

documented by the NRC [2 1].

" Code checking refers to verifying the computer code on a structural basis. This verification

can be achieved manually or by using a code-checking program to detect irregularities

and inconsistencies within the computer code. Code checking can increase the level of confidence

in the program's ability to correctly process the data to the program; however, it does not

give any indication of the likely adequacy or accuracy of the program in use. The FDT5

s library

comprises relatively simple closed-form equations that are pre-programmed into Excelo

spreadsheets. Each function requires a set of inputs and returns either a single point value

or a series of values showing a trend. Problems related to irregularities and inconsistencies

within the computer code are not expected; therefore, code checking in this sense is not

necessary for the FDT5 library.

* Numerical tests investigate the magnitude of the residuals from the solution of a numerically

solved system of equations employed in the model (as an indicator of numerical accuracy)

and the reduction in residuals (as an indicator of numerical convergence). The models

in the FDTs library are closed-formn mathematical expressions that are not solved using

numerical methods. As a result, there are no numerical instabilities or convergence issues

associated with the solutions to the models.

The spreadsheets used in this study of the FDTS library have been verified against hand

calculations. The equations and data within the tables used in the FDTS spreadsheets are primarily

described in the SFPE4Handbook of Fire Protection Engineering [31, the NFPA Fire Protection

Handbook [2], and other fire science literature. They are generally reliable and accepted within

the fire science community as the state-of-the-art in calculation methods for fire phenomena.

4-1
Mathematical and Numerical Robustness

In FDTs version 1805.0, an error was identified in the algorithm for estimating the HGL

temperature in a closed compartment. This error was identified because it was found that

the output for this algorithm was not consistent with the conceptual basis for this calculation.

The algorithm was subsequently corrected and re-released in version 1805.1 on the NRC's Web

page

[http://www.nrc .gov/reading-rm/doc-collections/nuregs/staff/srl 805/final-report/index.html].

4-2
5

MODEL SENSITIVITY

This chapter discusses sensitivity analysis, which ASTM E 1355 defines as a study of how

changes in model parameters affect the results. In other words, sensitivity refers to the rate

of change of the model output with respect to input variations. The standard also indicates

that model predictions may be sensitive to (1) uncertainties in input data, (2) the level of rigor

employed in modeling the relevant physics and chemistry, and (3) the accuracy of numerical

treatments. Thus, the purpose of a sensitivity analysis is to assess the extent to which uncertainty

in the model inputs is manifested as uncertainty in the model results of interest. The information

obtained can be used to determine the dominant variables in the models, define the acceptable

range of values for each input variable, quantify the sensitivity of output variables to variations

in input data, and inform and caution any potential users about the degree and level of care

that should be taken in selecting inputs and running the model.

When an i nput parameter is changed, there is also a relative magnitude change in the output.

A sensitivity analysis has been conducted to determine and examine this relative magnitude

change, which varies with each input. Some might have a greater effect on the output than others.

When examining the results obtained from the sensitivity analysis, the goal is to determine which

inputs cause the greatest changes in the final output. In order to stay consistent, a base case must

be established. The inputs for each base case are set at a value, and then each input is varied

over a defined percentage change. If the percentage change in the output is greater than

the percentage change in the input, the model is more sensitive to the input parameter.

Conversely, if the relative change in output is less than the relative change in input, the model

is less sensitive to the parameter that was changed.

5.1 Definition of Base Case Scenario for Sensitivity Analysis

A sensitivity analysis involves defining a base case scenario, and varying selected input parameters.

The resultant variations in the model output are then measured with respect to the base case

scenario, in order to consider the extent to which uncertainty in model inputs influences model

output. The base case scenario used in this study is Benchmnark Exercise (BE) #3, Test 3 (Cable F),

conducted as part of the International Collaborative Fire Model Project (ICFMP).

Of all the physical input parameters, the simulation results are most sensitive to the heat release

rate. In this section, one of the validation experiments (ICFMP BE #3, Test 3) is used to

demonstrate the result of increasing and decreasing the specified HRR by 15%. Figure 5-1

shows plots of various output quantities, demonstrating their sensitivity to the change in HRR.

Gas and surface temperatures, oxygen concentration, and compartment pressures show roughly

10% diversions from baseline, whereas the heat fluxes show roughly 20% diversions. The height

of the hot gas layer is relatively insensitive to changes in the HRR. The results are not

unexpected and consistent with the analysis described in Volume 2.

541
Model Sensitivity

5.2 Sensitivity Analysis for FDTs

FDTs contains a number of algorithms; however, for this study, only the HGL temperature and

two heat flux radiation models included in the validation were analyzed. Most of the correlations

are linear; therefore, it is expected that a small change in input will not result in a large change

in output. For this study, each input was varied by +15% and -15% from the base case.

Figures 5-1 through 5-4 show the inputs changed along with corresponding sensitivity ratio,

the maximum, minimum, and average values for each ratio.

5.3 Sensitivity to Heat Release Rate

Of all the physical input parameters, the simulation results are most sensitive to the heat release

rate. In this section, one of the validation experiments (ICFMP BE #3, Test 3) is used to

demonstrate the results of increasing and decreasing the specified HRR by 15%. Figure 5-1

displays plots of various output quantities demonstrating their sensitivity to changes in HRR.

The hot gas layer temperature shows roughly 10% differences from baseline, whereas the heat

fluxes show roughly 15% diversions for the point source model and 6-30% diversions for the

solid flame model. These results for the point source model are not unexpected and consistent

with the analysis described in Volume 2 to assess the sensitivity of the quantities of interest to

the uncertainty in the measured HRR. The large range from baseline for the solid flame model is

primarily attributable to the effect of the configuration factor. As the fire changes in height and

power output, the configuration factor will change as a result of more or less exposure to the

flame. The results for the solid flame model show that sensitivity to heat release rate can be

significant.

5-2
Model Sensitivity

*Heat Release Rate

lCFMP BE#3, Test 3

2000 

+ 5

S1000+---------------150/

S500t---

0 5 10 15 20 25 30

Time (min)

H-ot Gas Layer Temperature

ICFMP BE#3. Test 3

400.

E

300

200

100

0

0 10 15 20

Time (min)

Radiative Heat Flux to Power Cables

ICFMP BE#3, Test 3 (Point Source)

8

124

Power...... Cable.D

-- j-1

- Power Cable G

E

U-

'6(

X

Radiative Heat Flux to Power Cables

ICFMP BE#3, Test 3 (Solid Flame)

12

10 - Power Cable D

8 -

4 ----------- -------

Power Cable G

0

0 0 5 10 15 20 25 30

Time (min)

5 10 15 20 25 30

Time (min)

Figure 5-1: Sensitivity of Various Output Quantities to Changes in HRR

5.4 Sensitivity to Radial Distance

In this section, one of the validation experiments (ICFMP BE #3, Test 3) is used to demonstrate

the results of increasing and decreasing the specified radial distance to the target by 15%. Figure

5-2 displays plots of various output quantities demonstrating their sensitivity to the change in

radial distance. Both the point source radiation and solid flame radiation models were analyzed.

The heat fluxes show roughly 25-39% differences for the point source model and 22-32%

differences for the solid flame model. The results for the point source model are expected

because the heat flux has an inverse squared relationship with the radial term. The large range

from baseline for the solid flame model is primarily attributable to the effect of the configuration

factor. As the target changes its distance to the fire, the configuration factor changes

respectively as a result of more or less exposure to the flame. As the radial distance from the

target to the fire gets smaller, the configuration factor approaches 1, which implies that the target

receives all radiation released from the fire. The results for both the point source and solid flame

models show that sensitivity to radial distance is relatively significant.

5-3
Model Sensitivity

Radiatiw Heat Flux with %onjing radial distance

lCFMP BE#3, Test 3 (Point Source)

8 ....

2-

0

0 5 10 15 20 25 30

Time (min)

Radiative Heat Flux wvith xerying radial distance

ICFMP BE#3, Test 3 (Sol id Flame)

8-

E 2.

0it

0 5 10 15 20 25 30

. Time (min)

Figure 5-2: Sensitivity of Various Output Quantities to Changes in Radial Distance

5.5 Sensitivity to Radiation Fraction

In this section, one of the validation experiments (ICFMP BE #3, Test 3) is used to demonstrate

the results of increasing and decreasing the specified radiation fraction of the fuel by 15%.

Figure 5-3 displays a plot demonstrating the sensitivity of the point source radiation model to a

varying radiation fraction. Only the point source radiation model was analyzed. The heat flux

shows roughly 15% difference for the point source model. The results for the point source

model are expected because the effective heat flux has a direct dependence on radiation fraction.

5-4
Model Sensitivity

Radiative Heat Flux with varying radiation fraction

ICFMP BE#3, Test 3 (Point Source)

8

6----

0

0 5 10 15 20 25 30

lime (min)

Figure 5-3: Sensitivity of Various Output Quantities to Changes in Radiation Fraction

5.6 Sensitivity to Diameter

In this section, one of the validation experiments (ICFMP BE #3, Test 3) is used to demonstrate

the results of increasing and decreasing the diameter of the fire by 15%. Figure 5-4 displays a

plot demonstrating the sensitivity of the solid flame radiation model to a varying diameter fire.

The solid flame radiation model was analyzed, and the resulting heat flux showed roughly a 6%

difference for the solid flame model. The "effective" emissive power is very insensitive to

changes in diameter (0.28%), so the overall heat flux sensitivity to diameter depends on the

configuration factor. However, this sensitivity is very low, as shown by the results.

5-5
Model Sensitivity

Radiative Heat Flux with varying diameter

ICFMP BE#3, Test 3 (Solid Flame)

8

N~

E

x 4

0

0 5 10 15 20 25 30

lime (min)

Figure 5-4: Sensitivity of Various Output Quantities to Changes in Diameter

5.7 Conclusions

This chapter describes the sensitivity of FDTs results to changes of numerical and physical input

parameters for the point source and solid flame radiation models, as well as HGL temperature.

Chapter 6 (Model Validation) and Appendix A of this volume, as well as Chapter 5 of Volume 2,

provide additional examples that demonstrate how changes in various input parameters affect the

FDTs predictions.

5-6
6

MODEL VALIDATION

Consistent with Section I11 of ASTM E 1355, "Model Evaluation," this chapter summarizes

the results of the validation study conducted for the FDTs library. Appendix A to this volume

presents the technical details supporting the validation, including model output and comparison

with experimental data.

Six experimental test series were used in the V&V study. A brief description of each is given

here. Further details can be found in Volume 7 and in the individual test reports.

ICFMP BE #2: Benchmark -Exercise #2 consisted of eight experiments, representing three sets

of conditions, to study the movement of smoke in a large hail with a sloped ceiling. The results

of the experiments were contributed to the International Collaborative Fire Model Project

(ICFMP) for use in evaluating model predictions of fires in larger volumes representative of

turbine halls in NPPs. The tests were conducted inside the VTT Fire Test Hall, which has

dimensions of 19 mn high x 27 m long x 14 mn wide (62 ft x 89 ft x 46 fi). Each case involved

a single heptane pool fire, ranging from 2 MW to 4 MW.

ICFMP BE #3: Benchmark Exercise #3, conducted as part of the ICFIMP and sponsored by the

NRC, consists of 15 large-scale tests perfonned at NIST in June, 2003. The fire sizes range from

350 kW to 2.2 MW in a compartment with dimensions 21.7 mn high x 7.1 mn long x 3.8 mn wide

(71.2 ft x 23.3 ft x 2.5 ft), designed to represent a variety of spaces in a NPP containing power

and control cables. The walls and ceiling are covered with two layers of marinate boards, with

each layer 0.0 125 mn (0.5 in) thick, while the floor was covered with one layer of 0.01 125-in (0.5-

in) thick gypsum board on top of a 0.0183-mn (23/32-in) layer of plywood. The room has one door

with dimensions of 2 mn x 2 mn (6.6 ft x 6.6 ft), and a mechanical air injection and extraction

system. Ventilation conditions and fire size and location are varied, and the numerous

experimental measurements include gas and surface temperatures, heat fluxes, and gas velocities.

ICFMP BE #4: Benchmark Exercise #4 consists of kerosene pooi fire experiments conducted at

the Institut ffir Baustoffe, Mass ivbau und Brandschutz (iBMB) of the Braunschweig University

of Technology in Germany. The results of two experiments were contributed to the ICFMP.

These fire experiments involve relatively large fires in a relatively small [3.6 in x 3.6 mn x 5.7 in

(12 ft x 12 ft x 19 ft)] concrete enclosure. Only one of the two experiments was selected for the

present V&V study (Test 1).

ICFMP BE #5: Benchmark Exercise #5 consists of fire experiments conducted with realistically

routed cable trays in the same test compartment as BE #4. The compartment was configured

slightly differently, and the height was 5.6 mn (18.4 ft) in BE #5. Only Test 4 was selected for the

present evaluation, and only the first 20 minutes during which an ethanol pool fire pre-heats

the compartment.

FM/SNL Series: The Factory Mutual & Sandia National Laboratories (FMISNL) Test Series is a

series of 25 fire tests conducted for the NRC by Factory Mutual Research Corporation (FMRC),

6-1
Model Validation

under the direction of Sandia National Laboratories (SNL). The primary purpose of these tests

was to provide data with which to validate computer models. for various types of NPP compartments.

The experiments were conducted in an enclosure measuring 18 m long x 12 mn wide x 6 m high

(60 ft x 40 ft x 20 ft), constructed at the FMRC fire test facility in Rhode Island. All of the tests

involved forced ventilation to simulate typical NPP installation practices. The fires consist of a

simple gas burner, a heptane pooi, a methanol pool, or a polymethyl-methacrylate (PMMA) solid

fire. Four of these tests were conducted with a full-scale control room mockup in place.

Parameters varied during testing were fire intensity, enclosure ventilation rate, and fire location.

Only three of these tests have been used in the present evaluation (Tests 4, 5 and 21). Test 21

involves the full-scale mock-up. All are gas burner fires.

NBS Multi-Room Series: The National Bureau of Standards (NBS, now the National Institute of

Standards and Technology, NIST) Multi-Compartment Test Series consists of 45 fire tests

representing 9 different sets of conditions, with multiple replicates of each set, which were

conducted in a three-room suite. The suite consists of two relatively small rooms, connected via

a relatively long corridor. The fire source, a gas burner, is located against the rear wall of one

of the small compartments. Fire tests of 100, 300, and 500 kW were conducted, but only three

I100-kW fire experiments were used for the current V&V study (Test I OOA, 1000, and I OOZ).

The results for FDTs comparisons are organized by the following quantities:

" hot gas layer temperature and height

* plume temperature

* flame height

" target/radiant heat flux

As previously defined, validation is the process of determining the degree to which a calculation

method accurately represents the real world from the perspective of its intended uses. To fulfill

the need for validation, the experiments described above were modeled using the appropriate

FDTs spreadsheets, and the results from the FDTs computations were then compared to the

experimental measurements and presented in the formn of relative differences. Peak values were

compared from both the model predictions and the experimental data. For the comparison, the

following equation was used to calculate the relative difference between model and experiment:

AM -AE = (M - Mj- (Ep -EO)

where AM is the difference between the modeled peak value (M,,) of the evaluated parameter and

its original value (M.), and AE is the difference between the experimental observation (E,) and

its original value (Eo). For this study, we assumed M. = E.. Appendix A lists the calculated

relative differences for the fire modeling parameters listed above using FDTs.

The measure of model "accuracy" used throughout this study is related to experimental

uncertainty. Volume 2 discusses this issue in detail. In brief, the accuracy of a measurement

(e.g., gas temperature) is related to the measurement device (e.g., a thermocouple). In addition,

the accuracy of the mode/prediction of the gas temperature is related to the simplified physical

description of the fire and the accuracy of the input parameters (e.g., the specijied heat release

rate, which is based on experimental measurements). Ideally, the purpose of a validation study is

to determine the accuracy of the model in the absence of any errors related to the measurement

6-2
Model Validation

of both its inputs and outputs. Because it is impossible to eliminate experimental uncertainty, at

the very least a combination of the uncertainty in the measurement of model inputs and output

can be used as a yard stick. If the numerical prediction falls within the range of uncertainty

attributable to both the measurement of the input parameters and the output quantities, it is not

possible to quantify its accuracy further. At this stage, it is said that the prediction is within

experimental uncertainty.

Each section in this chapter contains a scatter plot that summarizes the relative difference results

for all of the predictions and measurements of the quantity under consideration. Details of the

calculations, the input assumptions, and the time histories of the predicted and measured output

are included in Appendix A. Only a brief discussion of the results for each test series is included

in this chapter. Included in the scatter plots are an estimate of the combined uncertainty for the

experimental measurements and uncertainty in the model inputs. It is important to understand

that these are simply estimates of the lower bounds of uncertainty and do not include systematic

uncertainty in the experimental measurements or model predictions. Along with expert

engineering judgment of the project team, these uncertainty bounds serve as guidelines to judge

the predictive capability of the model.

At the end of each section, a color rating is assigned to each of the output categories, indicating,

in a very broad sense, how well the model treats that particular quantity. A detailed discussion

of this rating system is included in Volume 1. For FDTs, the Green, Yellow+, and Yellow

ratings have been assigned to 4 of the 13 quantities of interest because these quantities fall within

the capability of the FDTs library. The Green rating indicates that the research team concluded

the physics of the model accurately represent the experimental conditions and the calculated

relative differences comparing the model and the experimental are consistent with the combined

experimental and input uncertainty. The Yellow+ rating indicates that the research team

concluded the physics of the model accurately represent the experimental conditions and the

model consistently over predicted the experimental measurements outside the combined

experimental and input uncertainty. The user should take care and use caution when interpreting

the results of the model for these parameters. The Yellow rating suggests that one exercise

caution when using the model to evaluate this quantity; consider carefully the assumptions made

by the model, how the model has been applied, and the accuracy of its results. There is specific

discussion of model limitations for the quantities assigned a Yellow rating. Parameters that are

not given a color rating indicate that the model does not include output to be able to evaluate that

parameter in its as-tested version.

6.1 Hot Gas Layer Temperature and Height

The single most important prediction a fire model can make is the temperature of the hot gas

layer (HGL). After all, the impact of the fire is not so much a function of the heat release rate,

but rather the temperature of the compartment. Following is a summary of the accuracy

assessment for the HGL temperature predictions of the six test series. Relative differences for

HGL Height calculations were not evaluated because FDTs does not contain a method applicable

to any of the test series. Figure 6-1 illustrates the relative differences in the form of a scatterplot.

ICFMP BE #2: FDTs, using the method of Beyler, over-predicted the HGL temperature for

Cases 1 and 2 of BE #2. The method of Foote, Pagni, and Alvarez also over-predicted for Case 3.

For Cases I and 2, the doors were closed; for Case 3, a fan was extracting smoke throughout

6-3
Model Validation

the test. None of the predictions fell within the combined uncertainty bands. The relative differences

may stem from an imprecise accounting of leakage in the model. The model calculations were

performed using mineral wool as the wall material because it is much less conductive than steel

and results in more realistic model results. In the actual experiment, the walls were made up

of a 1 -mm. (0.04-in) thick layer of sheet metal covering a 0.5-cm (2-in) layer of mineral wool.

Figure A- I illustrates both the experimental and predicted temperature profiles.

HGL height calculations were not possible for this test series because the Yamana and Tanaka

method is not applicable.

ICFMP BE #3: FDTs over-predicted the HGL temperature for all 15 tests. The method of

McCaffrey, Quintiere, and Harkleroad (MQH) was used for the open door tests (Tests 3, 9, 14,

15, and 18). Beyler's method was used for the closed door tests (Tests 1, 2, 7, 8, 13, 17). The

FPA method was used for the tests that included forced ventilation (Tests 4, 5, 10, 16). The

predictions for the open door tests are closer to experimental data than the closed door tests, with

.the exception of Test 5. In this test, the combination of open doors and mechanical ventilation

led to experimental temperatures that were lower than similar tests without mechanical

ventilation. None of the predictions fell within the combined uncertainty bands. For the closed

compartment predictions, the relative differences may-be the result of actual leakage. Beyler's

correlation for closed compartments assumes a small leakage rate that will prevent a pressure

buildup in the compartment, but energy lost through this leakage is ignored. If significant

leakage did exist during the actual tests it could have contributed to lower temperatures by

allowing the hot gases inside the compartment to escape. Beyler's method does not account for

this. Another possible explanation for large relative differences for closed compartment tests

may be the sensitivity of the Beyler correlation to the thermal inertia of the wall materials. The

wall materials used in BE #3 had a thermal inertia about 7 times lower than the wall materials in

the tests Beyler used validate his correlation. A relatively small variation between the actual

thermal inertia of the materials used in the test and the properties we assumed in modeling may

cause a higher relative difference. Figures A-2, A-3, and A-A illustrate both the experimental

and predicted temperature profiles.

The algorithm used to deduce HGL heigh t from compartment temperatures is not appropriate for

the closed compartment tests [22]. HGL height calculations were possible for the open door

tests, but not useful for this study. The algorithm used to determine layer height from

compartment temperatures showed the layer descending to the top of the door within 1-2 minutes,

and spilling out of the compartment. This means the Yamana and Tanaka method would only be

applicable for these 1-2 minutes, before the smoke layer spills out of the room. Plots of the

experimental data and FDTs predictions for these 1-2 minutes can be found in Section A. 1.2

of Appendix A. Relative differences for layer height were not calculated for these tests.

ICEMP BE #4: Using the MQH method, FDTs predicted the IJGL temperature for this test

within the combined uncertainty bands. However, the experimental temperatures reached levels

outside the recognized bounds where this correlation is applicable. Figure A-6 illustrates both

the experimental and predicted temperature profiles.

HGL height comparisons were not made for this test series. The algorithm used to deduce HGL

height from compartment temperatures is not appropriate for this test [22]. The test included a

relatively large fire in a relatively small room, which resulted in a rapidly descending HGL,

creating one zone in the compartment very quickly.

6-4
Model Validation

ICFMP BE #5: Test ICFMP BE #5 was conducted in the same compartment as test ICFMP BE

#4, but the compartment had a smaller doorway and a lower HRR fire. As a result, FDTs, using

the MQH method for a naturally ventilated compartment, over-predicted by a small margin the

combined experimental uncertainty. Figure A-7 illustrates both the experimental and predicted

temperature profiles.

HGL height calculation was possible for this test, but not useful for this study. The algorithm

used to determine layer height from compartment temperatures showed the layer height lower

than the top of the opening before 1 minute. This means the Yamana and Tanaka method would

only be applicable for a limited amount of time. The relative difference for layer height was not

calculated for this test.

FMISNL: The Foote, Pagni, and Alvares (FPA) method was used to predict the HGL temperatures

in the FM/SNL tests. FDTS over-predicted the HGL temperature for the three tests, outside of

the combined experimental uncertainty. Tests 4 and 21 had a ventilation rate of approximately

0.38 m3/S (800 cfmn), while Test 5 had a ventilation rate of approximately 3.78 mn3/S (8,000 cfm).

The likely reason the FPA method over-predicts the temperature in these tests is the location of

the inlet ports for the ventilation system. The compartment had six inlet ports located 1.2 mn (3.9

ft) below the ceiling, injecting downward. This configuration means the air was injected toward

the lower layer of the compartment, most likely promoting more mixing between the relatively

hot upper layer and the relatively cooler lower layer. This mixing reduces the applicability

of the two-layer assumption used in the EPA method. Figure A-8 illustrates both the

experimental and predicted temperature profiles.

HGL height calculations u 'sing the Yamana and Tanaka method were not possible for this test

series because of the forced ventilation in the compartment.

NBS Multi-Room: Using the MQJJ method FDTs predicted the HGL temperature to within the

experimental uncertainty for the three NBS tests. The model calculations were performed with a

ceramic fiber as the wall material because it is less conductive than fire brick and results in more

realistic model results. It is also important to note that the standard reduction method was not

used to compute the experimental HGL temperature or height for this test series. Rather, the test

director reduced the layer information individually for the eight thermocouple arrays using an

alternative method [23]. Figure A-9 illustrates both the experimental and predicted temperature

profiles.

HGL height calculations were not possible for these tests. The algorithm used to determine layer

height from compartment temperatures showed the layer height less than the height of the

doorway before the test began. This is non-physical and precludes the calculation of relative

differences using the Yamana and Tanaka method to calculate layer heights.

The scatter plot shown in Figure 6-1 depicts the relative differences between the peak HGL

temperature recorded in the experiments and the predictions made by the FDTs correlations.

The lines shown at -14% and 14% represent the approximate combined uncertainty of the input

values and the measurement of the experimental outputs as determined in Volume 2. In these

cases, it appears that the maximum HGL temperature estimates for the given conditions were

always either over predicted or were predicted within experimental uncertainty. Figure 6-2

presents the same results in a different format, emphasizing the actual values of the HGL

temperature.

6-5
Model Validation

Summary: HGL Temperature - YELLOW+

*The FDTs models for HGL temperature capture the appropriate physics and are based on

appropriate empirical data.

* FDTs generally over-predicts HTGL temperature, outside of uncertainty.

6-6
Model Validation

0

U

C

0

1... 0

0

(U

0

200%

150%

100%

50%

0%

-50%

FDTs HGL Temperature Predictions

p0

0

000 0 0 0

00

0 0 

00

-14%

(NI

wUwwwwwww w uz ý,

Figure 6-1: Relative Differences for HGL Temperature

800

(U

0.

E

W

a.

600

400

200

0

0 200 400 600 800

Measured Temperature (C)

Figure 6-2: Measured vs. Predicted HGL Temperatures

6-7
Model Validation

6.2 Plume Temperature

Plume temperature data used to assess the accuracy of FDTs predictions were taken from ICFMP

BE #2 at 6 and 12 mn (20 and 40 ft) above the fire source and in the FM/SNL test at 5.66 mn

(18.57 ft) above the fire source. A total of nine plume temperature data points were included

in this study. The spreadsheet in the FDTs library used to estimate the centerline temperature

of a buoyant plume is 09_-Plume_-Temperature Calculations.xis.

The primary user inputs to the plume temperature algorithm in FDTs are HRR, the ambient air

temperature of the enclosure, the elevation above the fuel source, and the area of combustible

fuel. The inputs and assumptions required for the spreadsheet in FDTs used to estimate

the plume temperature are discussed in detail in Section 3.7. The correlation used for plume

temperature in FDTs was developed from data where the plume was unobstructed, and no

hot gas layer developed. This study compares data from tests where a hot gas layer did develop.

Figure 6-3 illustrates the relative differences in the form of a scatterplot.

ICFMP BE #2: Heskestad's correlation in FDTs under-predicts the plume temperature in four of

the six cases in this test series. At 12 mn above the fire source FDTs under-predicts by around

40% in all three cases. This is likely attributable to the thermocouple being enveloped by the hot

gas layer in the upper part of the compartment in the tests. The correlation used in FDTs does

not account for the effect of the hot gas layer on the plume centerline temperature. At 6 mn (20 ft)

above the fire source, FDTs is more accurate, predicting within experimental uncertainty in

Cases I and 3 and under-predicting in Case 2. At 6 mn ( 20 ft) above the fire, the hot gas layer

has less of an effect on the centerline plume temperature, except for Case 2, which had a very

large fire. Figure A- 10 illustrates the experimental and predicted plume temperatures for this

test series.

FMISNL: In this test series, FDTs under-predicts the plume temperature in Tests 4 and 5 and

predicts within experimental uncertainty in Test 21. In Tests 4 and 5, we again see the hot gas

layer affecting the plume centerline thermocouple temperature. The correlation does not account

for this effect, and so FD~ under-predicts. In Test 2 1, the fire was located inside an electrical

cabinet, so the comparison for this test is somewhat suspect as the FDTs correlation has no way

of taking this effect into account. Figure A-lII illustrates the experimental and predicted plume

temperatures for this test series.

The scatter plot shown in Figure 6-3 below depicts the relative differences between the peak plume

temperature recorded in the experiments and the predictions made by the FDTs algorithm. The

lines shown at -14% and 14% represent the approximate combined uncertainty of the input

values and the measurement of the experimental outputs as determined in Volume 2. In these

cases, it appears that the maximum plume temperature estimates for the given conditions were

always either under predicted or were predicted within experimental uncertainty. Figure 6-4

presents the same results in a different format, emphasizing the actual values of the HGL

temperature.

Summary: Plume Temperature - YELLOW

" The EDT5 model for plume temperature is based on appropriate empirical data and is

physically appropriate.

" EDT5 generally under-predicts plume temperature, outside of uncertainty, because of

the effects of the hot gas layer on test measurements of plume temperature.

6-8
Model Validation

*The FD)TS model is not appropriate for predicting the plume temperatures at elevations within

a hot gas layer.

a)

C.)

a)1..

a)

a

a)

a)

a)

50%

25%

0%

-25%

FDTs Plume Temperature Predictions

14%

0

0 -14%

0

0 0 0

0 0

mmmm COM M zzm , wwwwww ULUL WL L UW 5U

Cý C C4 4 W C4W W U W L M M U..

-50%

Figure 6-3: Relative Differences for Plume Temperature

400

~.300-

CL

16-

CE 200-

FDTs Plume Temperature 14%/'

le

IC

A M

M1P BE #2 TG 1

NIP BE #2 TG 2

SNL

0 -

0 100 200 300 400

Measured Temperature (C)

Figure 6-4: Measured vs. Predicted Plume Temperatures

6-9
Model Validation

6.3 Flame Height

Flame height is recorded by visual observations, photographs or video footage. Photographs

from the ICFMP BE #2 test series and video from BE #3 test series are available. It is difficult

to precisely measure the flame height, but the photos and videos allow one to make estimates

accurate to within a pan diameter. Such observations can be compared with outputs from

Heskestad's flame height correlation.

Heskestad's correlation was developed using more extensive data than the data in these studies,

including pool fires and horizontal surface fires.

ICFMP BE #2: The height of the visible flame in these tests has been estimated to be between

2.4 and 3 pan diameters [3.8 to 4.8 m (12.5 to 15.7 ft)]. From Heskestad's flame height

correlation in the FDTS the estimated flame height is 4.3 m (14.1 ft).

ICFMP BE #3: During BE #3, Test 3, the peak flame height is estimated to be 2.8 m (9.2 ft),

roughly consistent with the view through the doorway in compartment. FDTS results in a flame

height of 3.0 mn (9.8 ft) using Heskestad's flame height prediction.

Summary: Flame Height - GREEN

0 The FDTs model predicted flame heights consistent with visual test observations.

6.4 Target/Radiant Heat Flux

As described in Chapter 3 of this volume, the FDTs library of correlations includes radiation heat

flux models that estimates heat flux at a specific distance away from a fire. Two models were

compared to radiant heat flux data from the ICFMP BE #3 experiments. The first was the point

source radiation model, and the second was the solid flame radiation model. The FDTs

spreadsheet used to calculate radiant heat flux is 05.1_-Heat_-FluxICalculations_-WindFree.xls.

Figure 6-5 and Figure 6-7 illustrate the relative differences in the form of a scatterplot.

ICFMP BE #3: Neither the graphs in Figures A- 14 through A-21 in Appendix A nor the

scatterplot shown in Figure 6-5 indicates any specific trends about the accuracy of FDTs

in calculating radiant heat flux using the poinf source model. For a number of tests, the model

predicts the peak radiant heat flux at the gauge within the uncertainty of the input parameters and

the experimental measurements. For other tests, the model both under-predicts and over-predicts

the radiant heat flux at a target, outside uncertainty bands. The reason that the model predictions

varied so greatly can be attributed to the fact that the point source radiation model is not meant

to be used for locations within a hot gas layer or relatively close to the fire.

As can be seen in Figure 6-5, the majority of the under-predictions occurred at gauge 10, which

was located at 1.8 m (5.9 ft) above the floor. This gauge was likely influenced by radiation

from the hot gas layer, which is not accounted for in the point source model. Most of the overpredictions occurred at locations higher in the hot gas layer. Gauges 1, 3, and 7 were located

at 2, 2.5, and 3 m (6.6, 8, and 9.8 ft), respectively, above the floor. These gauges were immersed

in smoke during all the tests by the time that the radiation measurements were selected for comparison.

in these cases, the HGL likely prevented the radiation from the fire from reaching the gauge.

Again, the correlation does not account for the effects of the HGL.

6-10
Model Validation

The scatter plot shown in Figure 6-5 depicts the relative differences between the peak radiant

heat flux recorded in the experiments and the predictions made by the FDTs correlations.

The lines shown at -20% and 20% represent the approximate combined uncertainty of the input

values and the measurement of the experimental outputs as determined in Volume 2. In these

cases, it appears that the maximum radiant heat flux estimates for the given conditions do not

indicate a trend of either over- or under-prediction.

Neither the graphs in Figures A-22 through A-29 in Appendix A nor the scatterplot shown in

Figure 6-7 indicates any specific trends about the accuracy of FDTs in calculating radiant heat

flux using the solid flame model. For a number of tests, the model predicts the peak radiant

heat flux at the gauge within the uncertainty of the input parameters and the experimental

measurements. For other tests, the model over-predicts the radiant heat flux at a target for the

majority of them, outside uncertainty bands. The model also under-predicts in some situations.

The reason that the model predictions varied so greatly can be attributed to the fact that the solid

flame radiation model is not meant to be used for locations within a hot gas layer. Another

reason may be that all of the experiments used in this study had a diameter of I meter whereas

the solid flame model was developed using data from pool fires with diameters of 1 to 50 m

(3.3 to 164 ft). From the data, a least squares fit was determined for the overall trend of the

"effective". emissive power (Equation 3-20). However, for smaller diameter pool fires on the

order of I m (3.3 fi), the data are sparse for differing fuel types. This would ultimately affect

the results of the radiant heat flux, depending on the fuel type.

As can be seen in Figure 6-7, the majority of the under-predictions occurred at gauge 10,

which was located at 1.8 m (5.9 ft) above the floor. This gauge was likely influenced by

radiation from the hot gas layer, which is not accounted for in the solid flame model. Most of

the over-predictions occurred at locations higher. in the hot gas layer. Gauges 1, 3, and 7 were

located at 2, 2.5, and 3 m (6.6, 8, and 9.8 ft), respectively, above the floor. These gauges were

immersed in smoke during all the tests by the time that the radiation measurements were selected

for comparison. In these cases, the HGL likely prevented the radiation from the fire from

reaching the gauge. Again, the correlation does not account for the effects of the HGL.

The scatter plot shown in Figure 6-8 depicts the relative differences between the peak radiant

heat flux recorded in the experiments and the predictions made by the FDTs correlations.

The lines shown at -20% and 20% represent the approximate combined uncertainty of the input

values and the measurement of the experimental outputs as determined in Volume 2. In these

cases, it appears that the maximum radiant heat flux estimates for the given conditions do not

indicate a trend of either over- or under-prediction.

Summary: Radiant Heat Flux - YELLOW

" The FDTs point source radiation and solid flame radiation model in general are based on

appropriate empirical data and is physically appropriate with consideration of the simplifying

assumptions.

" The FDTs point source radiation and solid flame radiation model are not valid for elevations

within a hot gas layer.

* FDTS predictions had no clear trend. The model under- and over-predicted, outside

uncertainty.

* The point source radiation model is intended for predicting radiation from flames in an

unobstructed and smoke-clear path between flames and targets.

6-11
Model Validation

a

0

0)

C.)

a) I-a)

0

a)

EU

0)

350%

300%

250%

200%

150%

100%

50%

0%

-50%

-100%

FD)Ts Radiant Heat Flux Predictions - Point Source

A Cal_

0 Cable B

10Cable D

Al -~Cable G

A 20%

20%

CNI

w

eCý C?

Cq Cj

LUwww wwwC O 'TOcýC' (0

wnýýV ~wwAAw in U U wU

wf

w

I?,

w

LO ~

CO Ce)

ww L in in w

in

wwzg

4 6

Z -)

-Cl)

UC/,

z Z Z

Figure 6-5: Relative Differences for Radiant Heat Flux Using Point Source Radiation Model

20

,'-' 5

E

~10

05

0 5 10 15

Measured Flux (kW/M2)

20

Figure 6-6: Measured vs. Predicted Radiant Heat Flux: Point Source Radiation Model

6-12
Model Validation

ac

600%

500%

400%

300%

200%

100%

0%

-100%

FDTs Radiant Heat Flux Predictions - Solid Flame

A Cable F

* Cable B

E Cable D

* *Cable G

A A

.1 20%

EE~ - -20%/

(%J

w

a,

CI I? S

sj C-4(VA

Uw ww M M Mw

a,

C..,

~c) 1-

w w AAAAw aMMWWWWa, an ca M M

TwcI c') ,W

w ,

CI,

w

IM

w

M,

ww Z-i

ULL~

C,,

a,

z

0

z

N

U)

z

Figure 6-7: Relative Differences for Radiant Heat Flux Using Solid Flame Radiation Model

20

E 15

0

0

0 5 10 15 20

Measured Flux (kWIM2)

Figure 6-8: Measured vs. Predicted Radiant Heat Flux: Solid Flame Radiation Model

6-13
Model Validation

6.5 Summary

This chapter summarizes numerous comparisons of the FDT5 model with a range of

experimental results conducted as part of this V&V effort. Four quantities were selected

for comparison and a color rating assigned to each of the output categories, indicating, in a very

broad sense, how well the model treats that particular quantity:

* Hot Gas Layer (HGL) Temperature: Yellow+

* Plume Temperature: Yellowi

* Flame Height: G~

*Radiant Heat Flux: Yellow

One of the quantities (flame height) was assigned a Green rating, indicating that the research

team concluded the physics of the model accurately represent the experimental conditions and

the calculated relative differences comparing the model and the experimental are consistent with

the combined experimental and input uncertainty.

*FDTs predicts the flame height consistent with visual observations of flame height for the

experiments.

One of the quantities (HGL temperature) was assigned a Yellow+ rating, indicating that the

research team concluded the physics of the model accurately represent the experimental

conditions, but the calculated relative differences comparing the model and the experimental

results are not consistent with the combined experimental and input uncertainty. The Yellow+

rating indicates that most of the results outside the relative uncertainty resulted in overpredictions of the HGL temperatures. The user should take caution when using the model to

evaluate IJGL temperatures and should not automatically assume that the model will always

over-predict these values.

Two of the quantities (plume temperature and radiant heat flux) were assigned a Yellow rating,

indicating the user should take caution when using the model to evaluate that quantity. This

typically indicates limitations in the use of the model. A few notes on the comparisons are

appropriate:

* The FDTs plume temperature, point source radiation, and solid flame radiation models are

not valid for elevations within a hot gas layer.

* The point source radiation model is only intended for predicting radiation from flames in an

unobstructed and smoke-clear path between flames and targets.

* FDT' predictions had no clear trend for either parameter. The model under- and overpredicted, outside uncertainty.

The FDTs predictions in this validation study used physically appropriate models with some

limitations, but often resulted in predictions outside of the relative uncertainty. As such, it is

important for the user to exercise caution when using the FDTs spreadsheets to model fire

scenarios. Like all predictive models, the best predictions come with a clear understanding of

the limitations of the model and of the inputs provided to do the calculations.

6- 14
7

REFERENCES

1. NUREG-1805, "Fire Dynamics Tools (FDTs): Quantitative Fire Hazard Analysis Methods for

the U.S. Nuclear Regulatory Commission Fire Protection Inspection Program," U.S. Nuclear

Regulatory Commission, Washington, DC, December 2004.

2. NFPA Fire Protection Handbook, 18th Edition (A.E. Cote, Editor-in-Chief), National Fire

Protection Association, Quincy, MA, 1997.

3. SFPE Handbook of Fire Protection Engineering, Pr Edition (P.J. DiNenno, Editor-in-Chief),

National Fire Protection Association and The Society of Fire Protection Engineers, Quincy,

MA, 2002.

4. Standard Guide for Evaluating the Predictive Capability of Deterministic Fire Models,

ASTM E 1355-05a, American Society for Testing and Materials, West Conshohocken, PA,

2005.

5. McCaffrey, B.J, J.G. Quintiere, and M.F. Harkleroad, "Estimating Room Temperature and

Likelihood of Flashover Using Fire Test Data Correlation," Fire Technology, Volume 17,

No. 2, pp. 98-119, Quincy, MA, 1981.

6. Standard Test Method for Determining Material Ignition and Flame Spread Properties,

ASTM E1I321-97a, American Society for Testing and Materials, West Conshohocken, PA,

2002.

7. Beyler, C.L., "Analysis of Compartment Fires with Overhead Forced Ventilation,"

Proceedings of the 3 'rd International Symposium, International Association of Fire Safety

Science (IAFSS), Cox and Langford, Editors, Elsevier Applied Science, New York, NY,

pp. 291-300, 1991.

8. Walton, W.D., and P.H. Thomas, Chapter 3, Section 6, "Estimating Temperatures

in Compartment Fires," SFPE Handbook of Fire Protection Engineering, 2nd Edition

(P.J. DiNenno, Editor-in-Chief), National Fire Protection Association and The Society

of Fire Protection Engineers, Quincy, MA, 1995.

9. Walton, W.D., and P.H. Thomas, Chapter 3, Section 6, "Estimating Temperatures

in Compartment Fires," SFPE Handbook of Fire Protection Engineering, 3rd Edition

(P.J. DiNenno, Editor-in-Chief), National Fire Protection Association and The Society

of Fire Protection Engineers, Quincy, MA, 2002.

10. Foote, K.L, P.J. Pagni, and N.L. Alvares, "Temperature Correlations for Forced-Ventilated

Compartment Fires," Fire Safety Science - Proceedings of the First International

Symposium, International Association of Fire Safety Science (IAFSS), Grant and Pagni,

Editors, Hemisphere Publishing Corporation, New York, NY, pp. 139-148, 1985.

7-1
References

11. Deal, S., and C.L. Beyler, "Correlating Preflashover Room Fire Temperatures," SFPE

Journal of Fire Protection Engineering, Volume 2, No. 2, pp. 33-48, The Society of Fire

Protection Engineers, Quincy, MA, 1990.

12. Thomas, P.H., "The Size of Flames from Natural Fires," Ninth Symposium (International) on

Combustion, The Combustion Institute, Pittsburgh, Pennsylvania, PA, pp. 844-859, 1962.

13. Yamana, T., and T. Tanaka, "Smoke Control in Large Spaces, Part 1: Analytical Theories

for Simple Smoke Control Problems," Fire Science and Technology, Volume 5, No. 1, 1985.

14. Karlsson, B., and J.G. Quintiere, Enclosure Fire Dynamics, Chapter 8, "Conservation

Equations and Smoke Filling," CRC Press LLC, New York, NY, p.206, 1999.

15. Heskestad, G., Chapter 2, Section 2-2, "Fire Plumes," SFPE Handbook of Fire Protection

Engineering, 2 nd Edition (P.J. DiNenno, Editor-in-Chief), National Fire Protection

Association and The Society of Fire Protection Engineers, Quincy, MA, 1995.

16. Babrauskas, V., Chapter 3, Section 3- 1, "Burning Rates," SFPE Handbook of Fire Protection

Engineering, 2 nd Edition (P.J. DiNenno, Editor-in-Chief), National Fire Protection

Association and The Society of Fire Protection Engineers, Quincy, MA, 1995.

17. Drysdale, D.D., An Introduction to Fire Dynamics, Chapter 4, "Diffusion Flames and Fire

Plumes," 2 nd Edition, John Wiley and Sons, New York, NY, pp. 109-15 8, 1998.

18. Beyler, C.L., Chapter 3, Section 1, "Fire Hazard Calculations for Large Open Hydrocarbon

Fires," SEPE Handbook of Fire Protection Engineering, Pr Edition (P.J. DiNenno, Editor-inChief), National Fire Protection Association and The Society of Fire Protection Engineers,

Quincy, MA, 2002.

19. Shokri, M., and C.L. Beyler, "Radiation Hazards from Release of LPG Fires from

Pressurized Storage," Fire Safety Journal, Volume 4, pp. 197-2 12, 1982.

20. Modak, A., "Thermal Radiation from Pool Fires," Combustion and Flames, Volume 29,

pp. 177-192, 1977.

2 1. "Verification of NUREG- 1805 by Hand Calculations," U.S. Nuclear Regulatory

Commission, Washington, DC (available in ADAMS under Accession #ML062020082),

July 2006.

22. Hamins, A., A. Maranghides, R. Johnsson, M. Donnelly, J. Yang, G. Mulholland,

R.L. Anleitner, "Report of Experimental Results for the International Fire Model

Benchmarking and Validation Exercise #3," NUREG/CR-6905/NIST SP 10 13- 1,

U.S. Nuclear Regulatory Commission, Washington, DC, May 2006.

23. Peacock, R.D., S. Davis, and B.T. Lee, "An Experimental Data Set for the Accuracy

Assessment of Room Fire Models," NBSIR 88-3752, U.S. Department of Commerce,

Gaithersburg, MD, April 1988.

7-2
A

TECHNICAL DETAILS OF THE FDTS. VALIDATION

STUDY

This appendix provides technical basis for the relative difference values listed in Chapter 6 of

Volume 2 for the output parameters in the compilation of quantitative fire hazard analysis tools,

FDT5 . This appendix is organized into sections for the parameters that have been verified and

validated in this study for this specific tool. Not all of the spreadsheets included in FDTs have

been subjected to V&V because of a lack of experimental data for comparison. Each section

presents a graph of the experimental data and the model output and a table of relative differences

at the peaks between experimental data and the model output. The sections also describe the

process and the values selected for input to the model. Within each section, the graphs are

grouped by experimental test series. Discussion and analysis of the relative differences can

found in Chapter 6 of Volume 2. This appendix is organized into four sections, as follows:

A.1 Hot Gas Layer Temperature and Height

A.2 Plume Temperature

A.3 Flame Height

A.4 Target Heat Flux

Volume 2 includes detailed discussion of the uncertainties associated with both the experimental

data and model predictions presented in this appendix.

A.1 Hot Gas Layer Temperature and Height

Hot gas layer (HGL) temperatures in the experiments were estimated using data from ICFMP

benchmark exercises (BE) 2, 3, 4, and 5, the FMI/SNL test series, and the NBS multicompartment fire test series for the room of fire origin. Specifically, thermocouple tree data

from those experiments was reduced to an instantaneous average temperature above the

estimated layer interface height at a specific time step. The layer interface height is deduced

from the continuous vertical profile of temperature indicated by the thermocouple tree data.

Relative differences were calculated by comparing the peak HGL temperatures and heights

estimated from the experiment to the peak predicted HGL temperatures calculated using FDTs.

Peak or, where available, steady-state heat release rates were used as inputs to the spreadsheets.

The heat release rate values for the different experiments are located in tables in this volume.

A-1
Technical Details of the FDTS Validation Study

A. 1.1 ICFMP BE #2

This test series consisted of three full-scale experiments with replicates. The experimental data

reported here are averages of the replicate tests. In Cases I and 2, the test compartment was

sealed with the exception of small openings incorporated as "infiltration ventilation," which

amounted to approximately 2 M2 (22 ft2

). Beyler's method for calculating HGL temperature in a

closed compartment was used for Cases 1 and 2 (02.3 -Temperature -CC.xls). The "infiltration

ventilation" was considered small enough compared to the volume of the space so that a natural

ventilation condition would not exist and Beyler's method would be appropriate. Also, as a

result of a non-natural ventilation condition, the Yamana and Tanaka method for calculating

HGL height will not apply.

In Case 3, mechanical extraction [11 Imn3/S (388 ft3/s)] was employed, as well as two doorway

openings [3.2 m2 each (34 ft3/s)] . Although there is no specific correlation for the scenario with

mechanical extraction and open doorways, the method of Foote, Pagni, and Alvares was used

(0.2.2_-Temperature_FV.xls) to calculate a relative difference for this case. The plot for Case 3

in Figure A- I also includes a calculation using the Deal and Beyler method, which is also found

in the FD spreadsheet, for comparison purposes. When compared with the experimental

temperatures from Cases I and 2, the experimental data shows that the ventilation rate had

relatively minimal effect on the temperatures in the compartment.

Because the Yamana and Tanaka correlation for HGL height is not applicable to any of the

experiments in BE #2, we did not make relative difference calculations for HUL height.

For Cases I and 2, experimental HRR data at specific times was used as input to the spreadsheet.

The interior wall material for these cases was assumed to be a 0.05 mn layer of mineral wool.

The experimental HRRs can be found in Volume 2 and Table A-3. Tables A- I and A-2 provide

the rest of the input data. Figure A- I illustrates the experimental and calculated HGL

temperature for these tests.

Table A-I: Input Values for ICFMP BE #2, Cases I and 2

____________________________ Case I Case 2

Air__ _ _ _ _ _

Ambient Air Temperature (C) 20 20

Ambient Air Density (kg/rn3) 1.2 1.2

Room Size

Compartment Width (in) 27 27

Compartment Length (in) 13.8 13.8

Compartment Height (in) 15.9 15.9

Wall Properties

Interior Lining Thermal Inertia [(kW/M2 -K)2_secl 0.015 0.015

Interior Lining Thermal Conductivity (kW/m-K) 0.0002 0.0002

Interior Lining Specific Heat (kJ/kg-K) 0.15 0.15

Interior Lining Density (kg/rn3) 500 500

Interior Lining Thickness (in) 0.05 0.05

A-2
Technical Details of the FDTS Validation Study

Table A-2: Input Values for ICFMP BE #2, Case 3

Air

Ambient Air Temperature (C) 20

Ambient Air Density (kg/rn3) 1.2

Room Size

Compartment Width (in) 27

Compartment Length (mn) 13.8

Compartment Height (in) 15.8

Wall Properties ____

Interior Lining Thermal Inertia [(kW/M2 -K)2_secl 0.015

Interior Lining Thermal Conductivity (kW/m-K) 0.0002

Interior Lining Specific Heat (kJ/kg-K) 0.15

Interior Lining Density (kg/in3) 500

Interior Lining Thickness (in) 0.05

Ventilation

Forced Ventilation Flow Rate (cfm) 23500

Heat Release Rate ____

Fire Heat Release Rate (MW) 3640

Table A-3: ICFMP BE #2 Heat Release Rates

Case 1 Case 2 Case 3

Time (sec) HRR (kW) Time (sec) HRR (kW) Time (sec) HRR (kW)

0 0 0 0 0 0

13.2 1251 13.8 2161 13.2 2426

90 1706 30 2540 63 3184

288 1858 91.2 3071 166.2 3601

327 1782 193.2 3260 256.2 3639

409.2 1365 282 3146 292.2 3450

438 0 340.2 2729 330 2654

372 2275 345 0

__ __ __ __ __ __ __ __394.8 0 _ _ _ _ _ _ _ _ _ _ _ _

A-3
Technical Details of the FDTS Validation Study

HGL Temperature

ICFMP BE # 2, Case I

HGL Temperature

ICFMP BE # 2, Case 2

C.

E

250

200

150

100

50

0

1rase 1 FDTs

250

200

?.150-

a.

10-

0

~<~~Case 2.--- -..FDTs

0 ------ ~--------- - -.-

0 2 4 6 8

Time (min)

2 4 6

Time (min)

8 10

HGL Temperature

ICFMP BE # 2, Case 3

250

200

*100

5-

50

0 2 4

Time (min)

6 8

Figure A-I: Hot Gas Layer Temperature, ICFMP BE #2, Cases 1, 2, and 3

A. 1.2 ICFMP BE #3

The experiments in this test consisted of hept ane and toluene spray fires varying nominally from

350 kW to 2 MW. There were 15 tests conducted with more than 370 channels of data for each

test. Six of the 15 tests were conducted with open doors (Tests 3, 5, 9, 14, 15, 18) and 9 with

closed doors (Tests 1, 2, 4, 7, 8, 10, 13, 16, 17). One of the open door tests (Test 5) and three of

the closed door tests (Tests 4, 10, 16) also had mechanical ventilation of approximately 0.8 1 m3/s

(29 ft/s). The MQH model (02.1_-Temperature NV.xls) was used for open door tests without

mechanical ventilation. The input values for these tests can be found in Table A-5, and plots

are in Figure A-3. Beyler' s method for calculating HGL temperature in closed compartments

(02.3_Temperature -CC.xls) was used for closed door tests without mechanical ventilation.

The input values for these tests can be found in Table A-4, and plots are in Figure A-2. The FPA

model was used for all tests with forced ventilation (02.2 -Temperature_-FV.xls). The input

values for these tests can be found in Table A-6, and plots are in Figure A-4. For Test 5, the

combination of mechanical ventilation and open doors cannot be directly modeled using FDTS,

so there are two predictions reported - one using the forced ventilation model, and another

using the natural ventilation model. The HRRs used for inputs were taken from the experimental

A-4
Technical Details of the FDTS Validation Study

report issued by NIST. For all tests, we assumed a constant HRR that represented the steadystate average HRR of the test data. This does introduce some additional error when the

experimental HRR is changing with time. No attempt is made to quantify this error other than to

lump it in with general uncertainties in the HRR, as described in Volume 2. The wall material

was assumed to be Marinite I and the thermal properties were taken from manufacturer's data.

Table A-4: Input Values for ICFMP BE#3 Closed Compartment Tests

Test 1 Test 2 Test 7 Test 8 Test 13 Test 17

Air___ __ _

Ambient Air Temperature (C) 21.1 23.9 22.2 28.9 32.2 25.6

Ambient Air Density (kg/M 3) 1.2 1.19 1.2 1.17 1.16 1.18

Room Size________ ____ ________ ____

Compartment Width (in) 7.04 7.04 7.04 7.04 7.04 7.04

Compartment Length (mn) 21.7 21.7 21.7 21.7 21.7 21.7

Compartment Height (in) 3.82 3.82 3.82 3.82 3.82 3.82

Wall Properties ____ ___

Interior Lining Thermal Inertia

[(kW/n 2 -K) 2_sec] 0.11 0.111 0.11 0.11 0.11 0.11

Interior Lining Thermal Conductivity

(kW/m-K) 0.00012 0.00012 0.00012 0.00012 0.00012 0.00012

Interior Lining Specific Heat (kJ/kg-K) 1.26 1.26 1.26 1.26 1.26 1.26

Interior Lining Density (kg/rn3) 737 737 737 737 737 737

Interior Lining Thickness (in) 0.0254 0.0254 0.0254 0.0254 0.0254 0.0254

Fire Heat Release Rate (kW)____

60 sec 410 1190 400 1190 2330 1160

120 sec 410 1190 400 1190 2330 1160

180 sec 410 1190 400 1190 2330 1160

240 sec 410 1190 400 1190 2330 1160

270 sec ________1160

30sc410 1190 400 1190 2330 1160

360___ sec__ 2330 ____

600________sec____ 410 1190 400 1190 2330 1160

900________sec____ 410 400 ____ 2330 1160

120sc410 400 ___ ___

1380 ________sec____ 410 400 _ ______

A-5
Technical Details of the FDTS Validation Study

Table A-5: Input Values for ICFMP BE #3 Open Compartment Tests

______________________ Test 3 Test 9 Testl14 Testl15 Testl18

Air__ _ __ ___ _ __ _

Ambient Air Temperature (C) 27.8 28.9 25.6 23.3 24.4

Ambient Air Density (kg/rn 3) 1.2 1.2 1.2 1 1.2 1.2

Room Size________________

Compartment Width (in) 7.04 7.04 7.04 7.04 1 7.04

Compartment Length (in) 21.7 21.7 21.7 21.7 21.7

Compartment Height (mn) 3.82 3.82 3.82 3.82 3.82

Wall Properties____

Interior Lining Thermal Inertia [(kW/M2 -K) 2 -sec] 0.11 0.11 0.11 0.11 0.11

interior Lining Thermal Conductivity (kW/m-K) 0.00012 0.00012 0.00012 0.00012 0.00012

Interior Lining Specific Heat (kJ/kg-K) 1.26 1.26 1.26 1.26 1.26

Interior Lining Density (kg/in3) 737 737 737 737 737

Interior Lining Thickness (mn) 0.0254 0.0254 0.0254 0.0254 10.0254

Ventilation_________

Vent Width (m) 2 2 2 2 2

Vent Height (in) 2 2 2 2 2

Top of Vent from Floor (in) 2 2 2 2 2

Heat Release Rate________

Fire Heat Release Rate (W) 1190, 1170 1 11801 11801 1180

A-6
Technical Details of the FDTS Validation Study

Table A-6: Input Values for ICFMP BE #3, Forced Ventilation Tests

Test 4 Test 5 Testl10 Testl16

Air _ _ _ _ _ __ _ _

Ambient Air Temperature (C) 26.7 25 24.4 21.1

Ambient Air Density (kg/in3) 1.2 1.2 1.2 1.2

Coinparlment Width (m) 7.04 7.04 7.04 7.04

Compartment Length (in) 21.7 21.7 21.7 21.7

Compartment Height (in) 3.82 3.82 3.82 3.82

Wall Properties_________

Interior Lining Thermal Inertia [(kW/M2 -K)2 -sec] 0.11 0.11 0.11 0.11

Interior Lining Thermal Conductivity (kW/m-K) 0.00012 0.00012 0.00012 0.00012

Interior Lining Specific Heat (kJ/kg-K) 1.26 1.26 1.26 1.26

Interior Lining Density (k g/rn3) 737 737 737 737

Interior Lining Thickness (in) 0.0254 0.0254 0.0254 0.0254

Ventilation_________

Forced Ventilation Flow Rate (cfm) 1907 1907 1907 1907

Heat Release Rate____ ____________

Fire Heat Release Rate (MW) 12001 1190 1190 2300

A-7
Technical Details of the FDTS Validation Study

HGL Temperature

ICFMP BE #3, TestlI

HGL Temperature

ICFMP BE # 3, Test 7

250

200

E

CL

E0.

150

250

200

~.150

E

a)100

50

0

100 -1

-x - -.FDTs

0 10 20 30 40

rime (mmi)

HGL Temperature

ICFMP BE # 3, Test 2

400

350

300 --- A--

250 ,

200 j- --

150 j ---

100 ', - -

50 Ex - - .FDTs

0 .

0 10 20 30 40

Timie (mmi)

HGL Temperature

ICFMP BE # 3, Test 13

0 10 20

Time (min)

30 40

HGL Temperature

ICFMP BE # 3, Test 8

C.)

E

a)

400

350

300

250

200

ý150

100

50 Exp - FDTs

0 10 20

Time (min)

30 40

HGL Temperature

ICFMP BE #3, Testl17

600

500

400

300

200

100

0

250

200

~.150

100

50

I

-x - FOTs

0 10 20

Time (min)

30 40 0 5 10

Time (min)

15 20

Figure A-2: Hot Gas Layer Temperature, ICFMP BE #3, Closed Compartment Tests

A-8
Technical Details of the FDTS Validation Study

HOL Temperature

ICFMP BE # 3, Test 3

E

I--

300

250

200

150

100

50

0

HGL Temperature

ICFMP BE# 3, Test 9

0.

E

0

I0 10 20

Time (min)

30 40 0 10 20

Time (min)

30 40

HGL Temperature

ICFMP BE #3, Test 14

HGL Temperature

ICFMP BE # 3, Test 15

300

250

Ey200

0. 150

50

50

C.)

E

300 ___________ _

200-

150

0 10 20 30 4

Time (mmd)

-Ep- - - FDTs

0 10 20 30 40 0

Time (mmd)

HGL Temperature

ICFMP BE #3, Test 18

a.

0.

E

jul1 i~Exp ----FDTs

0 10 20 30 40

Time (min)

Figure A-3: Hot Gas Layer Temperature, ICFMP BE #3, Open Compartment Tests

A-9
Technical Details of the FDTS Validation Study

HGL Temperature

ICFMP BE #3, Test 4

HGL Temperature

ICFMP BE # 3, Test 10

a.

E

300

250

200

150

100

50

0

a.

E

4)

300

250

200

150

100

50

0

Ep-- FDTs

0 10 20 30 40

Time (min)

0 10 20 30 40

Time (min)

HGL Temperature

ICFMP BE # 3, Test 5

HGL Temperature

ICFMP BE # 3, Test 16

E

350

300

250

200

150

100

50

0

E

. 600

500*

400

300

200

100

0-

Exp - - FDTs

0 10 20 30 .40

Time (min)

0 10 20 30 40

Time (min)

Figure A-4: Hot Gas Layer Temperature, ICFMP BE #3, Forced Ventilation Tests

A calculation method for HGL height is only found on the spreadsheet for open door conditions.

However, this calculation method is only valid before the layer descends to an opening and spills

out of the fire room. Figure A-5 depicts the HGL height comparisons for open door rooms only

during the early times of the test, before the layer spills out of the room. A relative difference

comparison is not made because of the restricted application of layer height calculation. The

correlation would always over-predict the layer height as it is limited to the top of the doorway,

whereas, the experimental results show the layer descending well below the top of the doorway.

Other phenomena that are not captured in the correlation are the transport lag of the smoke to the

ceiling and the filling time of large ceiling areas before the layer develops and descends. The

correlation assumes that the layer is fully formed at the ceiling at time t = 0. The transport lag

and filling time is captured in the experimental data and can be seen in Figure A-5 as an early

delay in the descent of the layer height.

A-10
Technical Details of the FDTS Validation Study

HGL Height

ICFMP BE #3, Test 3

HGL Height

ICFMP BE #3, Test 9

5

4

0

5

4

'3

IM

1

0

5

4

-3

CM

Z~ 2

0

Time (min)

HGL Height

ICFMP BE #3, Test 14

-*-Ep-~ - --OFTs

o 1 2

Time (min)

HGL Height

ICFMP BE #3, Test 18

0M

5

4

3

2

1

0Ep- -- - FDTs

2 0 1

Time (min)

HGL Height

ICFMP BE #3, Test 15

r,

4

E-3

2

0

0 Ep- - - - FDTs

0

Time (min)

2

-Exp.- 0 - - - FOTs

0 1

Time (min)

2

Figure A-5: Hot Gas Layer Height, ICFMP BE #3, Open Compartment Tests

A-]Il
Technical Details of the FOTS Validation Study

A. 1.3 ICFMP BE #4

This experiment included a relatively large fire in a relatively small compartment.

The compartment included a doorway of about 2.1 m2 (23 ft2 ) and no mechanical ventilation.

The spreadsheet in FDT5 used to estimate the HGL temperature for this exercise was

02. 1_TemperatureNV.xls. The maximum experimental HRR was input as a steady-state value

for the spreadsheet as a conservative assumption. This does introduce some additional error

when the experimental HRR is changing with time. No attempt is made to quantify this error

other than to lump it in with general uncertainties in the HRR, as described in Volume 2. The

experimental HRR, thermal properties of the wall materials, and other input values can be found

in Table A-7. The plot of HGL temperature in this test is Figure A-6. There is some time lag

in the data that may be associated with an ambiguous test start, thermocouple lag, or time for fire

to spread across the pool surface. These effects are not accounted for in the correlation.

Experimental data for HGL Height during this test is not available for comparison.

Table A-7: Input Values for ICFMP BE #4

Air

Ambient Air Temperature (C) 20

Ambient Air Densit (kfin3) 1.2

Room Size____

Compartment Width (in) 3.6

Compartment Length (mn) 3.6

Compartment Height (in) 5.7

Wall Properties ____

Interior Lining Thermal Inertia [(kW/M2 -K)2 -sec] 9.45

Interior Lining Thermal Conductivity (kW/m-K) 0.00075

Interior Lining Specific Heat (kJ/kg-K) 0.84

Interior Lining Density (kg/rn3) 1500

Interior Lining Thickness (in) 0.3

Ventilation

Vent Width (in) 0.7

Vent Height (in) 3

Top of Vent from Floor (mn) 3.6

Heat Release Rate ____

Fire Heat Release Rate (MW)31

A-12
Technical Details of the FDTS Validation Study

800

700

600

S500

CL400

10300

200

innA

HGL Temperature

ICFMP BE # 4, Test 1

100? _____________

0 1 -.. 4-~---F~

0 10 20 30 40

Time (min)

Figure A-6: Hot Gas Layer Temperature, ICFMP BE #4

A. 1.4 ICFMP BE #5

This experiment was conducted in the same compartment as ICEMP BE #4, except the doorway

was smaller, about 1.5 M2 (16 ft2) , again with no mechanical ventilation. The HRR of this test

was an order of magnitude less than in BE #4. The spreadsheet in FDTs used to estimate the

HGL temperature for this exercise is 02.1_-Temperature -NV.xls. The maximum experimental

HRR was input as a steady-state value for the spreadsheet as a conservative assumption.

This does introduce some additional error, when the experimental HRR is changing with time.

No attempt is made to quantify this error other than to lump it in with general uncertainties in

the HRR, as described in Volume 2. The ERR and other input values can be found in Table A-8.

Figure A-7 illustrates the experimental and calculated HGL temperature for this test.

A-13
Technical Details of the FDTS Validation Study

Table A-8: Input Values for ICFMP BE #5

Air

Ambient Air Ternperature (C) 20

Ambient Air Density (kg/rn 3) 1.2

Room Size____

Compartment Width (m) 3.6

Compartment Length (in) 3.6

Compartment Height (in) 5.7

Wall Properties

Interior Lining Therrnal Inertia [kW/rn -K2 -secl 9.45

Interior Lining Thermal Conductivity (kW/rn-K) 0.0075

Interior Lining Specific Heat (kJ/kg-K) 0.84

Interior Lining Density (k g/rn 3

) 1500

Interior Lining Thickness (in) 0.3

Ventilation ____

Vent Width (mn) 0.7

Vent Height (in) 2.2

Top of Vent from Floor (in) 3.6

Heat Release Rate____

Fire Heat Release Rate (kW) 716

Experimental data for HGL height during this test are not available for comparison.

A- 14
Technical Details of the FDTS Validation Study

HGL Temperature

ICFMP BE # 5, Test 4

250

200 - -. -

150

-.- Exp. -- FDTs_

0 ý

0 10 20 30 40

Time (min)

Figure A-7: Hot Gas Layer Temperature, ICFMP BE #5

A. 1.5 The FMISNL Test Series

This test series was conducted in a large closed room with mechanical ventilation. Tests 4 and 21

had a ventilation rate of approximately 0.37 M3 /s (13 ft3/s), while Test 5 had a ventilation rate

of approximately 3.7 in3

/S (131 ft3/s) . The FPA model was used for these tests with forced

ventilation (02.2 -TemperatureFV.xls). A steady-state HRR of 516 kW based on experimental

data was used as input to the spreadsheets. This value represents the steady-state average I{RR

during the tests. This does introduce some additional error when the experimental HRR is

changing with time. No attempt is made to quantify this error other than to lump it in with

general uncertainties in the HRR, as described in Volume 2. The input values used for these

three tests can be found in Table A-9. Figure A-8 illustrates the experimental and calculated

HGL temperature for these tests.

A-15
Technical Details of the FDTS Validation Study

Table A-9: Input Values for FMISNL Tests

___________________________ Test 4 Test 5 Test 21

Air _ _ _ _ _ _ _ _ _

Ambient Air Temperature (C) 20 20 20

Ambient Air Density (kg/in3) 1.2 1.2 1 1.2

Room Size____ ____ ____

Compartment Width (in) 12.2 12.2 12.2

Compartment Length (in) 18.3 18.3 18.3

Compartment Height (in) 6.1 6.1- 6.1

interior Lining Thermal Inertia [kW/M2 -K 2 -sec] 0.108 0.108 0.108

Interior Lining Thermal Conductivity (kW/m-K) 0.00012 0.00012 0.00012

Interior Lining Specific Heat (kJ/kg-K) 1.25 1.25 1.25

Interior Lining Density (kg/rn3) 720 720 720

Interior Lining Thickness (mn) 0.025 0.025 0.025

Ventilation ____ ________

Forced Ventilation Flow Rate (cfm) 800 8000. 800

Heat Release Rate ____

Fire Heat Release Rate (MW) 516, 516 , 516

A-16
Technical Details of the FDTS Validation Study

HGL Temperature HGL Temperature

FMISNL Test 4 FMISNL Test 21

200

100

50

-r -- 4---Exp - - -- FOTs

50

0 10 20 30

Time (min)

I

0 5 10 15 20

Time (min)

120

100,

80

CL 60 E 40

2- 0

20

HGL Temperature

FMISN L Test 5

-.- Exp --- FDTs

0 5 10 15

Time (min)

Figure A-8: Hot Gas Layer Temperature, FMISNL Tests

A. 1.6 The NBS Test Series

This test series involved a three compartment configuratio n with two smaller rooms opening off

of a long corridor. One of the smaller rooms contained the fire source. All experimental data

used to compare with FDTs came from the fire room because FDTs does not have the capability

to model conditions in rooms other than the fire room. The three tests considered are labeled

1 OOA, 1000, and 1 OOZ, respectively. The differences between these three tests concerned

ventilation conditions in the corridor. Test 1 00A involved closed doors from the corridor to the

outside and from the corridor to the third room. Test 1000 involved an open door from the

corridor to the outside and a closed door from the corridor to the third room. Test I OOZ involved

open doors from the corridor to the outside and from the corridor to the third room. Because all

tests involved an open door between the fire room and the corridor, the spreadsheet with the

MQH model (02.1I_Temperature_-NV.xls) was used to estimate HGL temperature for the NBS

tests. All three tests used a HRR of 1 10 kW, based on experimental HRR data. This value

represents the steady-state average HRR during the tests. This does introduce some additional

error when the experimental HRR is changing with time. No attempt is made to quantify this

error other than to lump it in with general uncertainties in the L{RR, as described in Volume 2.

Material properties and other input values can be found in Table A- 10. Figure A-9 illustrates

the experimental and calculated HGL temperatures for these tests.

A-17
Technical Details of the FDTS Validation Study

Table A-1O: Input Values for NBS Tests

Air

Ambient Air Temperature (C) 22.8

Ambient Air Density (kg/rn3) 1.19

Room Size____

Compartment Width (mn) 2.34

Compartment Length (in) 2.34

Compartment Height (mn) 2.16

Wall Properties ____

Interior Lining Thermal Inertia [(kW/M2 -K)2_sec] 0.012

Interior Lining Thermal Conductivity (kW/rn-K) 0.00009

Interior Lining Specific Heat (kJ/kg-K) 1.04

Interior Lining Density (kg/rn 3) 128

Interior Lining Thickness (mn) 0.05

Ventilation

Vent Width (m) 0.8

Vent Height (mn) 1.6

Top of Vent from Floor (in) 1.6

Heat Release Rate ____

Fire Heat Release Rate (MW) 110

A-18
Technical Details of the FDTS Validation Study

HGIL Temperature

NBS Test 1IOOA

HGL Temperature

NBS Test 1000

375

300

2.225

C.

w150

75

0

375

300

150

75

0

0 5 10

Time (min)

15 20 0 5 10

Time (min)

15 20

HGL Temperature NBS

Test 100Z

375

300

2.225

a.

150

75

0

0 5 10 15 20

Time (min)

Figure A-9: Hot Gas Layer Temperature, NBS Tests

A. 1.7 Summary: Hot Gas Layer Temperature and Height

Table A-IlI lists the relative differences between experimental data and model results for HGL

temperature. "AE" is the difference between the experimental peak and the experimental initial

condition. "AM" is the difference between model peak and the model initial conditions, which is

assumed to be the experimental initial condition. Because FDTs does not have an appropriate

calculation method for layer height for the experimental conditions in these tests, no relative

differences are given.

A-19
Technical Details of the FDTS Validation Study

Table A-Il1: Hot Gas Layer Temperature Relative Differences

_____ ______ A E A M % Difference

a- Case 1 55 69 5.

u- w Case 2 86 10825

Case 3 83 207 :150W%

Test 1 123 189 :,6___1_%

Test 2 229 333 47%

Test 3 207 259 54

Test 4 204 260 27%'

Test 5 175 283 :61%

Cf) Test 7 117 181 656/

CO Test 8 218 341 1 53W__

a- Test 9 204 255 '55%

LL Testl10 198 260 __ 1%__

o Testl13 290 475 61__0/__

Test 14 208 256 52%

Test 15 211 257 51%

Test 16 268 356: .33%

Test 17 135 194 45%___

Testi18 194 256 640/

BE #4 Test 1 701 734 --:9%<

BE #5 Test 4 186 2111%

-j 7

z Test 4 60 162 29

Test 5 47 75 69%

U.. Test 21 66 148 1700/

CO Test 1: 248 260 __6%__

Test 2 310 278 -10%

_____Test 4 284 277 '-2%

A.2 Plume Temperature

Plume temperatures are measured with thermocouple trees above the fire source. The test series

that included an arrangement for collecting plume temperature data include ICFMP BE #2, #4,

and #5, and FM/SNL. During BE #4 and BE #5, the fire and the plume tilted away firom the

plume thermocouples; therefore, those data will not be used. The following figures pre'sent the

experimental observations as well as FDTs predictions for plume temperature using Heskestad's

plume temperature correlation (FDT5 spreadsheet: 09_Plume TemperatureCalculations.xls).

A-20
Technical Details of the FDTS Validation Study

A.2. I ICFMP BE #2

In the experiment, the two thermocouples in the fire plume were located 6 mn (23 ft) and 12 mn (43 ft)

above the fire source, respectively. HRRs were calculated from fuiel mass loss rates during the

experiments, modified by an efficiency factor of 0.85. The convective heat release fraction used

was 0.65. The input values for this experiment can be found in Table A-12 while the heat release

rates can be found in Table A-3. Figure A- 10 illustrates the experimental and calculated plume

temperatures for these tests. The experimental temperatures are higher at the 12-rn (43-ft) level,

most likely because of the development of the HUL, and its effect on the thermocouples.

The plume correlation does not account for this effect. The HGL would have less of an effect

on the 6-rn (23-ft) level thermocouples.

Table A-12: Input Values for ICFMP BE #2 Plume Temperature Calculations

________________________ TGI TG2

Air

Ambient Air Temperature (C) 20 20

Ambient Air Density (kg/in3) 1.2 1.2

Fire Characteristics_________

Elevation Above the Fire Source (in) 7 13

Area of Combustible Fuel (Mn) 0.5 0.5

Convective Heat Release Rate Fraction (x,) 0.65 0.65

A-21
Technical Details of the FDTS Validation Study

Plums Temperature at 7 meters

ICFMP BE92 Case 1

Plume Temperature at 13 meters

ICFMP BEN2 Case I

200

~.150

S100

*50

0

C.,

E

160

140

120

100

80

60

40

20 -Ex.% TG.2 ..-- -FD s TG.2

0 2 4 6 8

Time (min)

Plume Temperature at 7 meters

ICFMP BE#2 Case 2

0 2 4 6 8

Time (min)

Plume Temperature at 13 meters

ICFMP BEN2 Case 2

350

300

250

.~200

CL

3E 00

250

3 00

2 50

L)

C.

-Exp.TG.1 ___

. .. FD sTG.

0 2 4 6 8

Time (min)

Plume Temperature at 7 meters

ICFMP BEN2 Case 3

160

140

U120

S100

60 E

a)40-

20

0

.. . ....... ,

0 2 4 6 8

Time (min)

Plume Temperature at 13 meters

ICFMP E#2 Case 3

-E 

F XD% TTGG. .1

160

140

~3120

S100

S80

S60 E

S40

20

Ex TG.2 - - - -FA TG.2

0

0 2 4 6 8

Time (min)

0 2 4 6 8

Time (min)

Figure A-10: Plume Temperature, lCFMP BE #2, Cases 1, 2, and 3

A-22
Technical Details of the FDTS Validation Study

A.2.2 The FM/SNL Test Series

The thermocouple for measuring plume temperatures was located 5.66 mn (18.6 ft) above the base

of the fire, approximately 5.95 m (19.5 ft) above the floor. The HRRs used as inputs were

calculated using a te curve with a peak of 516 kW, which matches the experimental data.

The convective heat release fraction used was 0.65. Additional input values can be found in

Table A- 13. Figure A-lII illustrates the experimental and calculated plume temperatures

for these tests.

Table A-13: Input Values for FMISNL Tests Plume Temperature Calculations

Air

Ambient Air Temperature (C) 20

Ambient Air Density (kg/rn 3) 1.2

Fire Characteristics____

Elevation Above the Fire Source (in) 5.66

Area of Combustible Fuel (mn2 ) 0.17

Convective Heat Release Rate Fractionkcx) 0.651

A-23
Technical Details of the FDTS Validation Study

Plume Temperature at 5.95 meters

FMISN L Test 4

Plume Temperature at 5.95 meters

FMISNL Test 21

140

120

-100

S80

~;60

E 40

20

0

120

100

OU

160

E 40

20

20

0 5 10

Time (min)

15 20 0 10 20 30

Time (Min)

Plume Temperature at 5.95 meters

FMISNL Test 5

140

120

C.)

2 00

0 5 10 15 20

Time (min)

Figure A-Il1: Plume Temperature, FMISNL Tests

A.2.3 Summary: Plume Temperature

Table A- 14 lists the relative differences between experimental data and model results for plume

temperature. "AE" is the difference between the experimental peak and the experimental initial

condition. "AM" is the difference between model peak and the model initial conditions, which is

assumed to be the experimental initial condition..

Table A-14: Plume Temperature Relative Differences

Sensor A E A M % Difference

TG1 166 168 1%

S Case 1 TG2 77 49 -36% wj 00TG1 288 239 -17%

0- Case 2 TG2 128 70 -45%

Li- oTGl 252 268 6%

Case 3 TG2 128 79 -38%

Test 4 5.66mrnabove fire 116 71 -39%

'~ITest 5 5.66 mn above fire 94 64 -32%

G-I Test 21 5.66mrnabovfr 79 44 1 -45%

A-24
Technical Details of the FDTS Validation Study

A.3 Flame Height

Flame height is recorded by visual observations, photographs or video footage. Photographs

from the ICFMP BE #2 test series and video from BE #3 test series are available. It is difficult

to precisely measure the flame height, but the photos and videos allow one to make estimates

accurate to within a pan diameter. Such observations can be compared with outputs from

Heskestad's flame height correlation. Although no accuracy can be calculated, this comparison

may provide insights about the capabilities and limitations of the model. The FD)Ts spreadsheet

used to calculate the flame height was 03_ERRFlameHeight Burning__DurationCalculations.xls.

A.3.1 ICFMP BE #2

Figure A- 12 contains photographs of the actual fire. The height of the visible flame

in the photographs has been estimated to be between 2.4 and 3 pan diameters [3.8 to 4.8 mn

(12.5 to 15.7 ft)]. Using Heskestad's method for estimating the height of a pool fire flame,

FD)Ts estimated flame height to be 4.3 mn (14.1 ft).

A-25
Technical Details of the FDTS Validation Study

Figure A-12: Photographs of Heptane Pan Fires, ICFMP BE #2, Case 2

(Courtesy of Simo Hostikka, VTT Building and Transport, Espoo, Finland)

A-26
Technical Details of the FDTS Validation Study

A.3.2 ICFMP BE #3

No measurements were made of the flame height during BE #3, but numerous photographs

were taken through the doorway, which measured 2 mn x 2 mn (6.6 ft x 6.6 ft). Figure A- 13 is one

such photograph. During BE #3, Test 3, the peak flame height is estimated to be 2.8 mn (9.2 ft),

roughly consistent with the view through the doorway in the figure below. FDTs results in

a flame height of 3.0 mn (9.8 ft) using Heskestad's flame height prediction.

Figure A-13: Photograph and Simulation of ICFMP BE #3, Test 3,

as Seen Through the 2 m x 2 m Doorway (Photo courtesy of Francisco Joglar, SAIC)

A.4 Target Heat Flux

A.4.1 ICFMP BE #3

The experimental results for radiant heat flux were obtained from Benchmark Exercise #3.

The FDTs spreadsheet used to calculate the radiant heat flux is

05.1_-HeatFluxCalculationsWindFree.xls. The Point Source Radiation and Solid Flame

Radiation model were used. The heat flux measurements were taken using 10 different gauges

located at varying distances from the fire. Five gauges measured total heat flux, and five

measured radiant heat flux. Because FDTs calculates radiant heat flux, only those data were

compared. Also, one of the five radiant heat flux gauges was oriented in the horizontal direction

and not with the proposed targets, so those data were not compared.

Point Source Radiation Model: The HRRs used as inputs are listed in Table A-4, Table A-5,

and Table A-6 and are consistent with the experimental measurements of HRR. For all tests,

we assumfed a constant HRR that represented the steady-state average HRR of the test data.

This does introduce some additional error when the experimental I-RR is changing with time.

No attempt is made to quantify this error other than to lump it in with general HRR uncertainties

as described in Volume 2. The radiation fraction for all tests except Test 17 was 0.44.

A-27
Technical Details of the FDTS Validation Study

The radiation fraction used for Test 17 was 0.40. Table A-i15 lists the radial distances from fire

to target for each test. This number also represents the ratio of distance to the diameter of the

fire (L/D) because the diameter of the fire was 1.00 m (3.3 ft). The position of the fire was

different for three of the 15 tests in BE #3, so the distances to targets are different for those tests.

The point source representing the fire is taken to be 1.00 m above the ground. It is interesting

to note that despite the limitation of the point source radiation model as applicable only for

L/D > 2.5, this trend is not seen in the data from BE #3. In some cases, for the same fire and

gauges at L/D < 2.5, relative differences are smaller than gauges at LID > 2.5. Two reasons for

this result may be either HGL effects or compartment effects. However, there is no clear trend,

and therefore, caution should be taken anytime the point source model is used in compartments.

Figures A- 14 through A-2 1 illustrates the experimental and calculated radiant heat fluxes for

these tests.

Table A-15: Radial Distance and LID from Fire to Radiant Heat Flux Gauges (meters)

Gauge Test 14 Test 15 Test 18 All Others

1 4.88 1.33 2.16 3.25

3 4.24 1.52 2.1 7 2.73

7 3.80 2.17 2.58 2.54

10 1.81 5.65 5.55 3.42

A-28
Technical Details of the FDTS Validation Study

Radiative Heat Flux to Power Cable F

ICFMP BE #3 Test 1

1.0

0.8

S0.5

'u0.3

0.0

Radiant Heat Flux to Power Cable F

ICFMP BEN3 Test?7

1.0

~'0.5 ---

0.3Gue1

..FDTs RedGauge I

0 10 20 30 40 50

Time (min)

Radiative Heat Flux to Cable B

lCFMP BE#3 Test i

0 10 20 30 40 50

Time (min)

Radiant Heat Flux to Cable B

lCFMP BEN3 Test 7

-1.5

1.0

IL. 0.5

0.0

1.

1.0

I.0.5

0.0

Exup. Red Gauge 3 ----FDTs Rad Gauge 3

0 10 20 30 40 50

Time (min)

Radiative Heat Flux to Tray D

IC FMP BEN3 Test I

1.5

3:1.0

~-0.5

0.0

-----------------

Exp. Red Gage 7

- - - -FDTs Red Gaugea

0 10 20 30 40 50

Time (min)

Radiant Heat Flux to Tray D

ICFMP B E#3 Test?7

1.5

u- 0.5-

EU Exp.Rad Gauge 7 X ---- FOTs Red Gauge 7

0 10 20 30 40 50

Time (min)

Radiant Heat Flux to Tray G

lCFMP BE#3 Test?7

0 10 20 30 40 50

Time (min)

Radiative Heat Flux to Tray G

lCFMP BE#3 Test I

2.0

1.5-

S1 .0-

Z 0.5

-Ex%.RadGauge 10 - - -- FD RG GaW 10

-2.0-

E

X 1.0-

j; 0.5

0.0

-E'.Rad Gauge 10 ----.. FE&sRad Gaugel10

0 10 20 30 40 50

Time (min)

0 10 20 30 40 50

Time (min)

Figure A-14: Radiant Heat Flux, ICFMP BE #3, Tests I and 7

A-29
Technical Details of the FDTS Validation Study

Radiative Heat Flux to Power Cable F

ICFMP BEN3 Test 2

Radiant Heat Flux to Power Cable F

ICFMP BE#3 Test 8

3

0 * FDs Red Gauge 1

3

Ir'

EU

0:

*-Exp tad Gauge 1 .. FD Red Gauge I -

0

0 5 10 15 20 25 0 5 10 15 20 25

Time (min) Time (min)

Radiant Heat Flux to Cable B

lCFMP BE#3 Test 2

Radiant Heat Flux to Cable B

lCFMP BEN3 Test 8

4

0

4

a2

U0

'Oe 00

0 5 10 15 20 25

Time (min)

Radiant Heat Flux to Tray D

lCFMP B E#3 Test 2

5 ~-

U6 22

01

I- I

-Eap Rad Gauge?7 - - - -FN.sRedGauge 7

4

3'

3U

21

-ERed Gauge3 ....... ExDad 1 Gag3

0 5 10 1 20 25

Time (min)

Radiant Heat Flux to Tray D

ICFMP BEN3 Test 8

-Exp.Rad Gauge?7 ...-- FDTs Rad Gauge?7

0 5 10 15 20 25

Time (min)

Radiant Heat Flux to Tray G

lCFMP BEN3 Test 2

0 5 10 15

Time (min)

20 25

8

a4

0

8

0

Radiant Heat Flux to Tray G

ICFMP BEN! Test 8

-Eap. Rad Gauge 10 - --- -FDs Rad Gauge 10

0 5 10 15 20 25 0 5 10 15 20 25

Time (min) Time (min)

Figure A-15: Radiant Heat Flux, ICFMP BE #3, Tests 2 and 8

A-30
Technical Details of the FDTS Validation Study

3-

2-*

'I

Radiant Heat Flux to Power Cable F

ICFMP 8BE#3 Test 3

Exp. Rd Gage I

Radiant Heat Flux to Power Cable F

ICFMP BE#3 Test 9

3

3: 2 -_

- a -%Rad Gauge I * FDýsRed GaugelI 0

0 10 20 30 40 50 60

Time (min)

Radiant Heat Flux to Cable 8

IC FMP BE#3 Test 9

0 10 20 30 40 50 60

Time (min)

5-

~4

0

Radiant Heat Flux to Cable B

ICFMP BE#3 Teat 3

----------- ExpRa~ddGaug . Ra Gauge

5

4S3

0-

E---G .RedGauge 3 - FD~sRed Gauge 3

0 10 20 30 40 50 60

Time (min)

Radiant Heat Flux to Tray 0 ICFMP

BEN3 Test 3

0 10 20 30 40 50 60

Time (min)

Radiant Heat Flux to Tray 0

lCFMP BEN3 Test 9

4

3:

X 2

0

- - - - FOTs Rad Gauge 7

6

34

0

.GAp. -xRad Gauge 7

-. - - -FDsRed Gauge 7

Red Gauge

0 10 20

Time (min)

30 40 0 10 20 30 40 50 60

Time (min)

Radiant Heat Flux to Tray G

lCFMP BEN3 Test 3

-Exp.Rad Gauge 10 -- . .FD~s RedGauge 10

6

a-5

3: 4

'C

0

6-

a.- 5

3: 4

U. 2

Radiant Heat Flux to Tray G

ICFMP BE#3 TestS9

----FD bR d 0 ge 10

...... ....

0

0 10 20 30 40 50 60

Time (min)

0 10 20 30 40 50 60

Time (min)

Figure A-16: Radiant Heat Flux, ICFMP BE #3, Tests 3 and 9

A-31
Technical Details of the FDTS Validation Study

Radiant Heat Flux to Power Cable F

ICFMP BEN3 Test 4

Radiant Heat Flux to Power Cable F

ICFMP BEN3 Test 10

3

2

0

- 3

E

2I

X

U

-- FD sRad Gauge.l

0

0 20 40 60

Time (min)

Radiant Heat Flux to Cable B

ICFMP BEN3 Test 4

4

-Exp. Rad Gauge 3

U-P

0 20 40 60

Time (min)

Radiant Heat Flux to Tray D

lCFMP BEN3 Test 4

0 20 40 60

Time (min)

Radiant Heat Flux to Cable B ICFMP

BEN3 Test 10

4

X 2

IL

---- ---------- --- -

ExR. Rd Gaug

0 20 40 60

Time (min)

Radiant Heat Flux to Tray D ICFMP BEN3

Test 10

4-

E~ 3 -

X 2

0-

-ExpRad Gaug --- OsRed Gauge 7

4

3-

0

- Ex% Red Gauge 7 . . . .FD Rod Gauge 7

0 20 40 60 0 20 40 60

Time (min) Time (min)

Radiant Heat Flux to Tray G

ICFMP BEN3Test 4

Radiant Heat Flux to Tray G ICFMP

B E#3 Test 10

7

6

4,

0

7

~-6

E

5

4,

0

0 20 40 60 20 40 60

Time (min) Time (min)

Figure A-17: Radiant Heat Flux, ICFMP BE #3, Tests 4 and 10

A-32
Technical Details of the FDTS Validation Study

Radiant Heat Flux to Power Cable F

ICFMP 8E#3 Test 5

Radiant Heat Flux to Power Cable F

ICFMP BEN3 Test 14

3

AL3:1

el

X~

3

0

10 20

Time (min)

30 40 0 10 20

Time (min)

30 40

5

4 3-

IL -

iz

Radiant Heat Flux to Cable B

ICFMP BEN3 Teat 5

Radiant Heat Flux to Cable 8 ICFMP

BE#3 Test 14

5

4:

M3

2

0

r: .. FD Rd G ge 3

0 10 20

Time (min)

30 40 0 10 20

Time (min)

30 40

6-

34-

X 3

2r

Radiant Heat Flux to Tray D

ICFMP BEN3 Test 5

6

.4I 5

3: 4

X 3

U.

0

Radiant Heat Flux to Tray D

ICFMP BEN3 Test 14

____________-Exp Red Gauge?7 ... . .FDTs Red Gauge 7

U

0 10 20 30 4

Time (min)

Radiant Heat Flux to Tray G

ICFMP BE#3 Test 5

0 0 10 20

Time (min)

30 40

41" 10

3: 6

-4

0

-Exp Red Gauge 10 . . ..FDs Red Gauge 10

4-E

(U

aL

12

10 -

8

6

4-

2

0-

Radiant Heat Flux to Tray G

ICFMP BE#3 Test 14

-Exp. Red Gauge 10 *- --- FDTs Red Gauge 10

...........

0 10 20

Time (min)

30 40 0 10 20

Time (min)

30 40

Figure A-18: Radiant Heat Flux, ICFMP BE #3, Tests 5 and 14

A-33
Technical Details of the FDTS Validation Study

Radiant Heat Flux to Power Cable F

ICFMP BE#3 Test 13

Radiant Heat Flux to Power Cable F

ICFMP 8E#3 Test 16

6 6

4r- 5 -r -

4 34

x' 3 --- FD~s RdGauge1 I _

.2 U.

0 I 0

- - - - FsRed Gauge 1

0 10 20 30 40

Time (min)

Radiant Heat Flux to Cable B

IC FMP BE#3 Teat 13

0 10 20

Time (min)

30 40

Radiant Heat Flux to Cable B

lCFMP BE#3 Test 16

R

7-

5.

x4

0

-%taGauge 3

FDRdGauge 3

8

7

X 4

0

0 10 20

Time (min)

30 40 0 10 20

Time (min)

30 40

Radiant Heat Flux to Tray D

lCFMP BEO3Test 13

Radiant Heat Flux to Tray D

ICFMP BE#3 Test 16

8 -

.- 7 -

.~5-

= 4

M 1

0

0

14

12

a4

Z2

0

8

7.

Raauge 7 X 4

S3

30 40 0

-ERdGauge7

10 20

Time (min)

0 10 20

Time (min)

30 40

Radiant Heat Flux to Tray G

IOFMP BEO3Testl13

Exp.Rad Gauge --- 10

... -. .FDs Red Gauge 10

Radiant Heat Flux to Tray G

ICFMP BE#3 Test 16

-.. ..-- - -Ds Red Gauge 1

fla-wýw- -----

E

L:

14

12

10

8

6

4

2

0

4:------___________

0 10 20

Time (min)

30 40 0 10 20

Time (min)

30 40

Figure A-19: Radiant Heat Flux, ICFMP BE #3, Tests 13 and 16

A-34
Technical Details of the FDTS Validation Study

Radiant Heat Flux to Power Cable F

lCFMP BE*3 Test I5

Radiant Heat Flux to Power Cable F

lCFMP BE#3 Test 18

201

.18 --- -- --

16--~ ---- F~ e ag

. ... ..

6

S4-

M3-

U.2

0

. . . .. . . . . ... 

EEx 1 .Rad Gauge1

0 20 40 60 0 20 40 60

Time (min) Time (min)

Radiant Heat Flux to Cable B

ICFMP BE#3 Test 15

Radiant Heat Flux to Cable B

lCFMP BEN3 Test 18

50

4-40

S30

S20

z10

6

4~- 5

X3

2

0

EX qjRldpauge 3

p Gauge 3

0 20 40 60

Time (min) 20 40 60

Time (min)

Radiant Heat Flux to Tray D

ICFMP BE#3 Test 15

Radiant Heat Flux to Tray D

ICFMP BEN3 Test 18

5-

"4

4S3

0

- - - - FOTs Red Gauge 7

PaId Gauge?7 neff=~tUwed

4

x 2

0.

---- FDTs Red Gauge 7

Ptad Gauge? neesnuded

0 20 40 60 0 20 40

Time (min) Time (min)

60

Radiant Heat Flux to Tray G

ICFMP BE#3 Test 15

Radiant Heat Flux to Tray G

lCFMP BE#3 Test 18

4

E 3

X 2

0

32

U0 20 40 60

0 20 40 60 Time (min)

Time (min)

Figure A-20: Radiant Heat Flux, ICFMP BE #3, Tests 15 and 18

A-35
Technical Details of the FDTS Validation Study

3

,C

U_

0

Radiant Heat Flux to Power Cable F

ICFMP BEN Test 17

.. . ... ... ...

-E edGauej

4-

0

Radiant Heat Flux to Tray D

IC FMP BEM3 Test 17

-Ex tad Gauge?7 - ~Rad Gauge 7

0 5 10 15 20

Time (min)

Radiant Heat Flux to Cable B ICFMP BEN3 Test 17

0 5 10 15 20

Time (min)

Radiant Heat Flux to Tray G

ICFMP BEN Test 17

4

U.

0

. . . . . . . . . . . . . . .

-ERdGag

3

3:2

0

. . .. FDsRdGue1

0 5 10 Time (min) 15 20 0 5 10

Time (min)

15 20

Figure A-21: Radiant Heat Flux, ICFMP BE #3, Test 17

Solid Flame Radiation Model: The HRRs used as inputs are listed in Table A-4, Table A-5,

and Table A-6 and are consistent with the experimental measurements of HRR. For all tests,

we assumed a constant HRR that represented the steady-state average HRR of the test data.

This does introduce some additional error when the experimental HRR is changing with time.

No attempt is made to quantify this error other than to lump it in with general HRR uncertainties

as described in Volume 2. Table A- 16 lists the horizontal distance to each target from the center

of the flame. The heights of the targets above the ground are listed in Volume 2. The position of

the fire was different for three of the 15 tests in BE #3, so the distances to targets are different for

those tests. The "effective" emissive power of the flame (Equation 3-20) was determined from a

wide range of experimental measurements of diameter from 1 to 50 m (3.3 to 164 ft) for radiant

flux from pool fires to targets. All measurements were made with vertical targets at the ground.

The radiation fraction is inherently taken into account by the emissive power, which includes the

effects of smoke obscuration of the flame. A least squares fit of the "effective" emissive power

data shows a reduction from about 60 kW/m2 at 1 meter diameter to 20 kW/m2 at about 60 m

(197 ft). The least squares fit is adequate for the scatter of data for the overall trend. However,

for smaller diameter pool fires on the order of 1 m (3.3 ft), the data are sparse for differing fuel

types. Because the BE#3 test series used a fire with a diameter of 1 m (3.3 ft), it is reasonable

for the relative differences to be outside the experimental uncertainty of 20%. Other reasons for

this result may be either HUL effects or compartment effects. However, there is no clear trend

A-36
Technical Details of the FDTS Validation Study

and, therefore, caution should be taken anytime the solid flame model is used in compartments.

Figures A-22 through A-29 illustrate the experimental and calculated radiant heat fluxes

for these tests.

Table A-16: Horizontal Distance from Fire to Radiant Heat Flux Gauges (meters)

Gauge Test 14 Test 15 Test 18 All Others

1 4.77 0.81 1.88 3.08

3 3.96 0.02 1.55 2.27

7 3.21 0.75 1.59 1.52

10 1 1.64 1 5.60 1 5.50 3.33

A-37
Technical Details of the FDTS Validation Study

Radiative Heat Flux to Power Cable F

ICFMP BE #3 Test i

Radiant Heat Flux to Power Cable F

ICFMP BEN3 Test 7

1.0

~0.8

M0.5

S0.3

0.0

0 10 20 30 40 50

Time (min)

Radiative Heat Flux to Cable B

ICFMP BEN Test I

1.0

~0.8

'0.5

LL

0.3

0.0

1.5

.91.0

u- 0.5

0 .

-Exp. Red Gauge 1 * ... FDTs Rad Gauge 1

0 10 20 30 40 50

Time (min)

Radiant Heat Flux to Cable B

lCFMP BEN3 Test 7

-1.5

~1.0

LL- 0.5

0.0

-Exp. Red Gauge 3 -- - - -FDTs Rad Gauge 3

0 10 20 30 40 50

Time (min)

0 10 20 30 40 50

Time (min)

Radiative Heat Flux to Tray D

ICFMP BE#3 Test 1

1.5

S1.0

S0.5

0.0-

Exp Re ag --FTs O Red Gauge 7

1.5

1.0

X

u 0.5

Radiant Heat Flux to Tray D

ICFMP BEN3 Test 7

-Exp. Red Gauge 7 ---- .FDTs RedGauge 7

00 0 10 20 30 40 50

lime (min)

Radiative Heat Flux to Tray G

ICFMP BEN3 Test 1

2.0

K1.0

0 10 20 30 40 50

Time (min)

0 10 20 30 40 50

Time (min)

Radiant Heat Flux to Tray G

IC FMP BE#3 Test 7

2D

. . .. FDsRed Gauge~ 10

----------

0 10 20 30 40 50

Time (min)

Figure A-22: Radiant Heat Flux, ICFMP BE #3, Tests I and 7

A-38
Technical Details of the FDTS Validation Study

3

0

Radiative Heat Flux to Power Cable F

IC FMP BEN3 Test 2

Radiant Heat Flux to Power Cable F

lCFMP BEN3 Test 8

-Ep Red Gauge I *- - - -FDTs RedGauge 1

3

E

0

5

Exp. Red Gauge I - - - -FDTs Red Gauge 1

0 5 10 15 20 2

Time (min)

Radiant Heat Flux to Cable 8

ICFMP BE#3 Test 2

4

0

4

X 2

U0

0 5 10 15 20 25

Time (min)

Radiant Heat Flux to Cable B

lCFMP BEN3 Test 6

0 5 10 15 20 25

Time (min)

0 5 10 15 20 25

Time (min)

Radiant Heat Flux to Tray D

lCFMP BEN3 Test 8

5

0

8

X 4

:2

0

Radiant Heat Flux to Tray D

ICFMP BEN3 Test 2

...... . . -E 5

3U

1 0

0 5 10 15 20 25

Time (min)

Radiant Heat Flux to Tray G

IC FMP BE#3 Test 2

0 5 10 15 20 25

Time (min)

Radiant Heat Flux to Tray G

ICFMP BE#3 Test 8

-ExpRed Gauge 10 * FO Red Gauge 10

- E sRdGauge 10 . D RdGauge 10

0

0 5 10 15 20 25

Time (min)

0 5 10 15 20 25

Time (min)

Figure A-23: Radiant Heat Flux, ICFMP BE #3, Tests 2 and 8

A-39
Technical Details of the FLITS Validation Study

3

0-

ICFMP BEN3Test 3

-- -FD Rd Gauge 1

-S

~4

LI0

0

z

Radiant Heat Flux to Power Cable F

ICFMP BE#3 Test 9

2 -- -- -- --- - - -

-~Red Gauge 1

0

0 10 20 30 40 50 60

Time (min)

0 10 20 30 40 50 60

Tine (rnan)

Radiant Heat Flux to Cable B

lCFMP BEN Test 3

5

4

0

EM-F GRed Gauge3 3 (D .Red Gauge 3 'U

0

Radiant Heat Flux to Cable B

ICFMP BEO3 Test 9

&EpRad Gauge 3 .FD RedGauge 3

0 10 20 30 40 50 60

Time (min)

Radiant Heat Flux to Tray D ICFMP

BEN3 Test 3

0 10 20 30 40 50 60

Time (min)

4

0

6

5

0

*- --- -FOTs RedGauge 7

* . Gaue 7 n.Noictoe~d

6

,-5

. 2

Radiant Heat Flux to Tray D

ICFMP BE#3 Test 9

.A -Ex .dGauge7

-r0

0 10 20 30 40

Time (min)

Radiant Heat Flux to Tray G

lCFMP BEN3 Teat 3

.... FDs Rad Gauge 10 5

0 10 20 30 40 50 60

Time (min)

0 10 20 30 40 50 60

Time (min)

Radiant Heat Flux to Tray G

ICFMP BEN3 Test 9

-Exgk.Rd Gauge 10

._._._.______RdGaug -10

0 10 20 30 40 50 60

Time (min)

Figure A-24: Radiant Heat Flux, ICFMP BE #3, Tests 3 and 9

A-40
Technical Details of the FDTS Validation Study

Radiant Heat Flux to Power Cable F

ICFMP SE#3 Test 4

3

2

0

4

3:

0

* ~ - %~EaR dGa Ie * ~ ~ F R- ld Ga2ge1

0 20 40 6'

Time (min)

Radiant Heat Flux to Cable B

lCFMP BENl3Test 4

0

3

it 2

S

X

0

4

3L

X

.2

Radiant Heat Flux to Power Cable F

ICFMP BE#3 Test 10

0 20 40

Time (min)

Radiant Heat Flux to Cable B ICFMP

BE#3 Test 10

60

.. . .. . . . . . . .

* - Exp. Red Gauge 3 * .-- FDTs Red Gauge 3

-- Ex. Red Gauge 3 - .FDTs - Red Gauge 3

0 20 40

Time (min)

Radiant Heat Flux to Tray D

ICFMP BE#3 Test 4

60

0 20 40 6(

Time (min)

0

E3:

X 2

0

Radiant Heat Flux to Tray D ICFMP BEN3

Test 10

=3:

X= 2 -ExRad Gauge?1; II-... Ds~a~u R* 7 

%i - - -

20 40 60 0 20 40

Time (min) Time (min)

Radiant Heat Flux to Tray G Radiant Heat Flux to Tray G lCFMP

ICFMP BEN3 Test 4 BE#3 Test 10

60

7

-6

z3:

L

2-

6-

E5

.23-

U.

Z

-Exp.RedGauge 10 0---O~ e Gaug 10

a

0 20 40 60 0 20 40

Time (min) Time (min)

Figure A-25: Radiant Heat Flux, ICFMP BE #3, Tests 4 and 10

60

A-41
Technical Details of the FDTS Validation Study

Radiant Heat Flux to Power Cable F

IC FMP BE#3 Test 5

Radiant Heat Flux to Power Cable F

lCFMP BEN3 Test 14

3:

IL

0

5

4

0

6

X 3

0

3

3:2

X

0

-.- e -- - - - - - - - -

10 20 30

Time (min)

Radiant Heat Flux to Cable B

ICFMP BEN3 Test 5

I R.. Rad Gag 3

40 0 10 20 30 40

lime (min)

Radiant Heat Flux to Cable B ICFMP

BE#3 Test 14

5-

4 EU

/ - Ex-O~ Red G a uge 3

0 10 20 30 4

Time (mlin)

Radiant Heat Flux to Tray D

IC FMP BE#3 Test 5

0 0 10 20 30

lime (min)

Radiant Heat Flux to Tray D

ICFMP BEN3 Test 14

40

_ -__ - - FD Rd Gauge 7

0 10 20 30 40

Time (min)

Radiant Heat Flux to Tray G

ICFMP BEM3 Test 5

a-- 5

'C

X 1

0

-E XG .. . .FD& C:gU;77

---- --------

It

0 10 20

Time (min)

30 40

A- 10

X 6

U.-4

2

EXRdGauge 10 ___._._._ . FDýs Red Gauge 10

12-

S10 -

=' 6-

-L4

M 2-

Radiant Heat Flux to Tray G

ICFMP BEN3 Test 14

---- Ds RadGage 10

..........

1:

0 10 20 30 40 0 10 20 30

Time (min) lime (min)

Figure A-26: Radiant Heat Flux, ICFMP BE #3, Tests 5 and 14

40

A-42
Technical Details of the FDTS Validation Study

Radiant Heat Flux to Power Cable F

lCFMP BE93 Test 13

Radiant Heat Flux to Power Cable F

ICFMP BE#3 Testi1S

6

@5

E

4

0

8

4-7

E 6

x4

u. 3

0

*-ExpRad Gauge 1

...FDTs RedGauge1

7S

6

~5

E

0

-ExpRad GaugelI XFDsRed Gauge I

0 10 20 30 41

Time (min)

Radiant Heat Flux to Cable B

ICFMP BE#3 Test 13

0 0 10 20

Time (min)

30 40

R

7 -6

-~Exp. RedGauge 3 x5

1 0

Radiant Heat Flux to Cable B

lCFMP BE#3 Test 16

--- Ex.aage 3 .... FDMsaG-a g3

0 10 20

Time (min)

30 40 0 10 20

Time (min)

30 40

8

-7

M 3

0

Radiant Heat Flux to Tray D

ICFMP BE#3 Test 13

8

1 7

-E~xjkRad Gauge 7

L3.

0 10 20 30 40 0

Time (min)

Radiant Heat Flux to Tray G

IDFMP BE#3 Test 13

4 -14

2 - . FDR~addGaugeIO E 12

-10

Radiant Heat Flux to Tray D

ICFMP BE3 Test 16

-Exp.RadGaugel

AI L ~ - ... ~FOs RaoGaugge7,

0 10 20

Time (min)

30 40

Radiant Heat Flux to Tray G

ICFMP BE#3 Test 16

1

@41

2

IL

U

U

I

6

4

2

0

-------- ----- .2 6

S2

0

-EX %RadGau1;10

0 10 20

Time (min)

30 40 0 10 20

Time (min)

30 40

Figure A-27: Radiant Heat Flux, ICFMP BE #3, Tests 13 and 16

A-43
Technical Details of the FDTS Validation Study

Radiant Heat Flux to Power Cable F

ICFMP BE#3 Test 15

Radiant Heat Flux to Power Cable F

ICFMP BEN3 Test 18

20

18

3147

X10

r8-

X4-

2-

0

- E %F Gae1 FD Gupgel

6-

.4- 5

34.

X 3.

U.2

0

... .. . .. . .. ..

0 20 40 60

Time (min)

20 40 60

Time (min)

Radiant Heat Flux to Cable B

lCFMP BE#3 Test 15

50

440

30

E: 20

M 10

0

6

45

34

Radiant Heat Flux to Cable B

ICFMP BEN3 Teat 18

UU.

0 20 40 60

Time (min)

Radiant Heat Flux to Tray D

ICFMP BE#3 Testi15

3j

0

0 20 40 60

Time (min)

Radiant Heat Flux to Tray D

ICFMP BE#3 Test 18

4-,-

5-

.4~

:S3

Mr 2

0

3

X 2

X

---. FDTs Red Gauge 7

P~d G.W 7 W-tionc~d

. . . .FDTs Red Gauge?7

Ftd Gesge 7 .a~uauomd

0 20 40 60 0 20 40 60

Time (min) Time (min)

4

"E3

X 2

Radiant Heat Flux to Tray G

ICFMP BEM3 Test 15

Ex.Rad Gauge 10 -- FD~s Red Gauge 10

Radiant Heat Flux to Tray G

lCFMP BEN3 Testi18

3L

it

1-

20 40 60

0 20 40 60 Time (min)

Time (min)

Figure A-28: Radiant Heat Flux, ICFMP BE #3, Tests 15 and 18

A-44
Technical Details of the FDTS Validation Study

3

2

0

Radiant Heat Flux to Power Cable F

ICFMP BE#3 Test 17

-Ex.pRaGauge I ---- Fos Red Coup1

4

42

2

URadiant Heat Flux to Tray D

ICFMP BE#3 Test 17

--- Exp Red Gauge 7

- -ý " - F s-_-age

0 5 10 15 20 0

Time (min)

5 10

Time (min)

i5 20

Radiant Heat Flux to Cable B

ICFMP BE#3 Test 17

4-

-EpRed Gauge 3 .. .. FDsRed Gauge

"2

~1

z0r

3

3:2

U.

Radiant Heat Flux to Tray G

IC FMP BE#3Testl17

-ElpRedGaugel10

-.FDsRed Gaugel10

0 5 10 15 20 0 5 10 15 20

Time (min) Time (min)

Figure A-29: Radiant Heat Flux, ICFMP BE #3, Test 17

A.4.2 Summary: Radiant Heat Flux

Table A-I 17 lists the relative differences between experimental data and the point source model

results for radiant heat flux. "AE" is the difference between the experimental peak and the

experimental initial condition. "AM" is the difference between model peak and the model initial

conditions, which is assumed to be the experimental initial condition.

A-45
Technical Details of the FDTS Validation Study

Table A-17: Relative Differences, Radiant Heat Flux - Point Source

Sensor Radiant Heat lux,(kW/m')

BE_ __3_ A E IA M % Difference

Gauge 1 0.87 1.36 51%

Gauge 3 1.12 1.93 72%

Gauge 7 1.43 2.23 58%

Test 1 Gauge 10 1.51 1.23 -19%

Gauge 1 1.99 13.95 98%

Gauge 3 2.88 5.59 94%

Gauge 7 4.16 6.46 55%

Test 2 Gauge- 10 5.97 3.56 -40%

Gauge 1 2.95 3.95 1 34%

Gauge 3 4.45 5.59 26%

Gauge 7 _____

Test 3 Gauge 10 5.36 3.56 -34%

Gauge 1 2.02 3.98 97%/

Gauge 3 2.92 5.64 1 93%

Gauge 7 3.26 6.52 100%

Test 4 Gauge 10 6.00 3.59 -40%

Gauge 1 2.65 3.95 49%

Gauge 3 3.88 5.59 44%

Gauge 7 4.78 6.46 350/%

Test 5 Gauge 10 5.45 3.56 -35%

Gauge 1 0.82 1.33 62%A

Gauge 3 1.21 1.88 56%

Gauge 7 1.35 2.17 61%

Test 7 Gauge 10 1.47 1.20 -19%

Gauge 1 1.93 3.95 104%

Gauge 3 2.92 5.59 92%

Gauge 7 3.56 6.46 82%

Test 8 Gauge 10 6.02 3.56 -41%

Gauge 1 2.72 3.88 43%

Gauge 3 4.27 5.50 29%

Gauge 7 5.23 6.35 22%

Test 9 Gauge 10 5.10 3.50 -31%

Gauge 1 1.92 3.95 105%/

Gauge 3 2.68 5.59 109%

Gauge 7 2.91 6.46 122%

Test 10 Gauge 10 5.42 3.56 -34%

Gauge 1 2.90 7.73 167%

Gauge 3 4.77 10.95 129%

Gauge 7 6.58 12.66 92%

Test 13 Gauge 10 10.06 6.98 -31%

Gauge 1 2.12 1.73 -18%

Gauge 3 2.84 2.30 -19%

Gauge 7 3.32 2.86 -14%

Test 14 Gauge 10 1.0 12.61 20%

Test 15 Gauge 1 18.02 I23.36 30%

A-46
Technical Details of the FDTS Validation Study

BE#3 Sensor ~Radiant Heat Flux~ kW/m.)

BE#3A E A M % Difference

Gauge 3 45.88 17.88 -61%

Gauge 7 _____

____Gauge 10 3.65 1.29 -614%

Gauge 1 2.73 7.63 180%

Gauge 3 4.05 10.81 167%

Gauge 7 4.74 12.49 164%/

Test 16 Gauge 10 11.79 6.89 -42%

Gauge 1 0.88 3.50 297%

Gauge 3 1.30 4.96 282%

Gauge 7 1.53 5.73 274%

Test 17 Gauge 10 -~2.42 3.16 31%

Gauge 1 5.18 8.86 7,1% -

Gauge 3 5.24 8.77 68%

Gauge 7

LTesti18 Gaugel10O 2.84 1.34 -53%/

Table A-1 18 lists the relative differences between experimental data and the solid flame model

results for radiant heat flux. "AE" is the difference between the experimental peak and the

experimental initial condition. "AM" is the difference between model peak and the model initial

conditions, which is assumed to be the experimental initial condition.

Table A-I 8: Relative Differences, Radiant Heat Flux - Solid Flame

BE #3 Sensor Radiant Heat Flux .(MWm 2

BE__3 A E A M %Difference

Gauge 1 0.87 2.35 170%

Gauge 3 1.12 2.18 95%

Gauge 7 1.43 0.83 -42%

Test 1 Gauge 10 1.51 2.36 56%

Gauge 1 1.99 5.22 162%

Gauge 3 2.88 7.51 161%,

Gauge 7 4.16 8.49 104%

Test 2 Gauge 10 5.97 14.70 -21%

Gauge 1 2.95 5.22 77%

Gauge 3 4.45 7.51 69%

Gauge 7 __________

Test 3 Gauge 10 5.36 4.70 -12%

Gauge 1 2.02 5.25 159%

Gauge 3 2.92 7.56 159%

Gauge 7 3.26 8.63 165%

Test 4 Gauge 10 6.00 4.72 -21%

Gauge 1 2.65 5.22 97%

Gauge 3 3.88 7.51 93%

Gauge 7 4.78 8.49 78%

Test 5 Gauge 10 5.45 4.70 -14%

Test 7 Gauge 1 0.82 2.29 180%

A-47
Technical Details of the FDTS Validation Study

BE #3 Sensor Radiant Heat Fx (~WMM)

BE#3A E IA M % Difference

Gauge 3 1.21 2.11 75%

Gauge 7 1.35 0.80 -41%

____Gauge 10 1.47 2.31 57%

Gauge 1 1.93 5.22 170%

Gauge 3 2.92 7.51 157%/

Gauge 7 3.56 8.49 139%

Test 8 Gauge 10 6.02 4.70 -22%

Gauge 1 2.72 5.17 90%

Gauge 3 4.27 7.40 73%

Gauge 7 5.23 8.19 57%

Test 9 1Gauge 10 5.10 4.66 .9%

Gauge 1 1.92 5.22 171%

Gauge 3 2.68 7.51 180%

Gauge 7 2.91 8.49 1 192%

Test 10 Gauge 10 5.42 4.70 -13%

Gauge 1 2.90 6.76 133%

Gauge 3 4.77 10.54 121%

Gauge 7 6.58 16.99 158%,

Test 13 Gauge 10 10.06 5.89 -41%

Gauge 1 2.12 2.33 10%

Gauge 3 2.84 3.04 7%

Gauge 7 3.32 3.57 8%

Test 14 Gauge 10 10.50 14.93 42%

Gauge 1 18.02 34.63 92%

Gauge 3 45.88 56.80 24%

Gauge 7 _____________

Test 15 Gauge 10 3.65 1.74 .52%

Gauge 1 2.73 6.74 147%

Gauge 3 4.05 10.50 159%

Gauge 7 4.74 16.93 257%

Test 16 Gauge 10 11.79 5.88 -50%

Gauge 1 0.88 5.15 484%/

Gauge 3 1.30 7.35 467%

Gauge 7 1.53 8.05 425%

Test 17 Gauge 10 2.42 4.65 92%

Gauge 1 5.18 11.68 126%

Gauge 3 5.24 13.05 149%

Gauge 7 _____________

Test 18 Gauge 10 2.84 1.80 -37%

A-48
NRC FORM 335 U.S. NUCLEAR REGULATORY COMMISSION 1. REPORT NUMBER

(9-201)4) (Assigned by NRC. Add Vol., Supp., Rev.,

NRCMO 3.7 and Addendum Numbers, If any.)

BIBLIOGRAPHIC DATA SHEET

(See instructions on the reverse) NUREG-1 824

2. TITLE AND SUBTITLE i3. DATE REPORT PUBLISHED

Verification and Validation of Selected Fire Models for Nuclear Power Plant Applications MONTH YEAR

Volume 3: FDTs;My20

4. FIN OR GRANT NUMBER

5. AUTHOR(S) 6. TYPE OF REPORT

J. Dreisbach (NRC), K. Hill (NRC) Technical

7. PERIOD COVERED (inclusive Dates)

B. PERFORMING ORGANIZATION - NAME AND ADDRESS (if NRC, provide Division, Office or Region. U.S. Nuclear Regulatory Commission, and mailing address; if contractor,

provide name and mailing address.)

U.S. Nuclear Regulatory Commission, Office of Regulatory Research (RES), Washington, DID 20555-0001

Electric Power Research Institute (EPRI), 3412 Hillview Avenue, Palo Alto, CA 94303

Science Applications International Corp. (SAIC), 4920 El Camino Real, Los Altos, CA 94022

National Institute of Standards and Technology (NIST/BFRL), 100 Bureau Drive, Stop 8600, Gaithersburg, MD 20899-8600

and mailing address.)

U.S. Nuclear Regulatory Commission, Office of Regulatory Research (RES), Washington, DC 20555-0001

Electric Power Research Institute (EPRI), 3412 Hillview Avenue, Palo Alto, CA 94303

10. SUPPLEMENTARY NOTES

11. ABSTRACT (200 words or less)

There is a movement to introduce risk-informed and performance-base analyses into fire protection engineering practice, both

domestically and worldwide. The move towards risk-informed decision-making in nuclear power regulation was directed by the

U.S. Nuclear Regulatory Commission.

One key tool needed to support risk-informed, performance-based fire protection is the availability of verified and validated fire

models that can accurately predict the consequences of fires. Section 2.4.1.2. of NFPA 805, Performance-Base Standard for

Fire Protection for Light-Water Reactor Electric Generating Plants, 2001 Edition requires that only fire models acceptable to the

Authority Having Jurisdiction (AHJ) shall be used in fire modeling calculations. Futhermore, Sections 2.4.1.2.2. and 2.4.1.2.3.

of NFPA 805 state that fire models shall be applied within the limitations of the given model, and shall be verified and validated.

This report is the first effort to document the verification and validation (V&V) of five models that are commomnly used in nuclear

power plant applications. The project was performed in accordance with the guidelines that the American Society for Testing

and Materials (ASTM) set forth in ASTM E 1355, Standard Guide for Evaluating the Predictive capability of Deterministic Fire

Models. The results of this V&V are reported in the form of color codes describing the accuracies for the model predictions.

12. KEY WORDS/DESCRIPTORS (List words or phrases that will assist researchers in locating the report.) 13. AVAILABILITY STATEMENT

fire, fire modeling, verification, validation, performance-based, risk-informed, firehazards analyses, unlimited

V&V, FHA, CEAST, FDS, MAGIC, FIVE, FDTs 14. SECURITY CLASSIFICATION

(This Page)

unclassified

(This Report)

unclassified

15. NUMBER OF PAGES

16. PRICE

NRC FORM 335 (9-2004) PRINTED ON RECYCLED PAPER
Federal Recycling Program

EPRI 1011999 NUCLEAR POWER PLANT APPLICATIONS

Volume 3: Fire Dynamics Tool (FDTS)

UNITED STATES

NUCLEAR REGULATORY COMMISSION

WASHINGTON, DC 20555-0001

OFFICIAL BUSINESS