NUREG-1824 EPRI 1011999

Final Report

Verification and Validation

of Selected Fire Models for

Nuclear Power Plant

Applications

Volume 4:

Fire-Induced Vulnerability Evaluation

(FIVE-Revl)

U.S. Nuclear Regulatory Commission

Office of Nuclear Regulatory Research

Washington, DC 20555-0001

<i'WU.S.NRC

Electric Power Research Institute

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Palo Alto, CA 94303

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Verification & Validation of Selected

Fire Models for Nuclear Power Plant

Applications

Volume 4: Fire-Induced Vulnerability Evaluation

(FIVE-Revi)

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

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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 Institute, 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 20852-2738

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, FDTS: 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 4: Fire-Induced Vulnerability Evaluation (FIVE-Rev]), U.S. Nuclear Regulatory

Commission, Office of Nuclear Regulatory Research (RES), Rockville, MD, 2007, and Electric

Power Research Institute (EPRI), Palo Alto, CA, NUREG-l1824 and EPRI 1011999.

iii
NUREG-1824, Volume 4, 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 permit 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-making in general.

One key tool needed to further the use of RI/PB 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 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 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 Plants.

The seven volumes of this NUREG-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 texL

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

1 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 .................................................................................................................. 2-3

2.8 Model Results .................................................................................................................. 2-3

3 THEORETICAL BASIS FOR FIVE-REV1 ......................................................................... 3-1

3.1 Average Room Temperature ........................................................................................... 3-2

3.2 Flame Height ................................................................................................................... 3-3

3.3 Radiant Heat Flux ........................................................................................................... 3-4

3.4 Plume Tem perature ......................................................................................................... 3-4

3.5 Ceiling Jet Tem perature .................................................................................................. 3-6

3.6 Plume and Ceiling Jet Temperatures in Hot Gas Layer Environments ........................... 3-6

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

5 M ODEL SENSITIVITY ............................................................................................................ 5-1

5.1 Sensitivity Analysis for Average Room Tem perature ...................................................... 5-1

5.1.1 Sensitivity Analysis for the MQH Model ................................................................. 5-1

5.1.2 Sensitivity Analysis for the FPA Model .................................................................... 5-4

5.2 Sensitivity Analysis for Flame Height .............................................................................. 5-5

5.3 Sensitivity Analysis for Radiant Heat Flux ....................................................................... 5-6

5.4 Sensitivity Analysis for Plume Tem perature .................................................................... 5-8

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

6.1 Hot Gas Layer (HGL) Tem perature ............................................................................ 6-4

6.2 Ceiling Jet Temperature ........................................... 6-8

6.3 Plume Temperature ................................................................................................. 6-10

6.4 Flame Height ........................................................................................................... 6-12

6.5 Radiative Heat Flux ..................................................................................................... 6-13

7 REFERENCES ..................................................................................................................... 7-1

A TECHNICAL DETAILS OF FIVE-REV1 VALIDATION STUDY ....................................... A-1

A.1 Hot Gas Layer Temperature ......................................................................................... A-2

A.1.1 ICFMP BE #3 ....................................................................................................... A-2

A.1.2 ICFMP BE #4 ....................................................................................................... A-7

A.1.3 ICFMP BE #5 ....................................................................................................... A-9

A.1.4 FM/SNL Test Series ....................................................................................... A-10

A. 1.5 The NBS Multi-Room Test Series ....................................................................... A-12

A.2 Ceiling Jet Temperature ............................................................................................. A-15

A.2.1 ICFMP BE #3 ................................................................................................. A-15

A.2.2 The FM/SNL Test Series ................................................................................ A-19

A.3 Plume Temperature ................................................................................................... A-21

A.3.1 ICFMP BE #2 ..................................................................................................... A-21

A.3.2 The FM/SNL Test Series .................................................................................... A-25

A.4 Flame Height ............................................................................................................. A-26

A.4.1 ICFMP BE #2 ..................................................................................................... A-27

A.4.2 ICFMP BE #3 ..................................................................................................... A-29

A.5 Radiant Heat Flux ...................................................................................................... A-32

x
FIGURES

Figure 5-1: Surface Plot for Average Room Temperature. Surface plot summarizes

room temperatures for a range of vent factor and heat release rate values ...................... 5-4

Figure 5-2: Surface Plot for Flame Height. Surface plot summarizes flame heights

for a range of vent factor and heat release rate values ...................................................... 5-6

Figure 5-3: Surface Plot for Flame Radiation. Surface plot summarizes flame radiation

values for a range of vent factor and heat release rate values .......................................... 5-8

Figure 5-4: Surface Plot for the McCaffrey Correlation for Plume Temperature.

Surface plot summarizes plume temperature values for a range of vent factor

and heat release rate values ............................................................................................ 5-10

Figure 5-5: Surface Plot for the Ceiling Jet Temperature. Surface plot summarizes

ceiling jet temperature values for a range of horizontal radial and heat release rate

va lues ............................................................................................................................... 5-12

Figure 6-1: Sample Temperature Profile from MQH and FPA Temperature Correlations ........ 6-6

Figure 6-2: Scatter Plot for Hot Gas Layer Temperature Relative Difference Results .............. 6-7

Figure 6-3: Scatter Plot of Relative Differences for Ceiling Jet Temperatures

in ICFMP BE #3, and the Selected FM/SNL Tests ............................................................. 6-9

Figure 6-4: Scatter Plot of Relative Differences for Plume Temperatures in ICFMP BE

#2, and the Selected FM/SNL Tests ............................................................................... 6-11

Figure 6-5: Scatter Plot of Relative Differences for Radiant Heat Flux ................................... 6-14

Figure A-I: Hot Gas Layer (HGL) Temperature, ICFMP BE #3, Closed Door Tests

w ith M echanical V entilation ............................................................................................... A-4

Figure A-2: Hot Gas Layer Temperature ICFMP BE #3, Open Door Tests ......................... A-5

Figure A-3: Heat Release Rate for ICFMP BE #4 ..................................................................... A-7

Figure A-4: Hot Gas Layer Temperature, ICFMP BE #4, Test 1 ............................................. A-8

Figure A-5: Heat Release Rate Profile for ICFMP BE #5 ........................................................ A-9

Figure A-6: Hot Gas Layer Temperature, ICFMP BE #5, Test 4 ............................................ A-9

Figure A-7: Heat Release Rate Profiles for the Selected FM/SNL Tests ......................... A-11

Figure A-8: Hot Gas Layer Temperature, FM/SNL Test Series ......................................... A-i 1

Figure A-9: Hot Gas Layer Temperature in the NBS Multi-Room Test 100A ......................... A-14

Figure A-10: Near-Ceiling (Ceiling Jet) Temperatures, ICFMP BE #3, Closed Door Tests... A-1 6

Figure A-11: Near-Ceiling (Ceiling Jet) Temperatures, ICFMP BE #3, Closed Door Tests ... A-17

Figure A-12: Near-Ceiling (Ceiling Jet) Temperatures, FM/SNL Series, Sections 1 & 3 ....... A-20

Figure A-13: Fire Plumes in ICFMP BE #2,

Courtesy of Simo Hostikka, VTT Building and Transport, Espoo, Finland ...................... A-22

xi
Figure A-14: Near-Ceiling Gas Temperatures, ICFMP BE #2, Sections 1 & 3 Compared

with Heskestad's Plume Temperature Correlation ......................................................... A-23

Figure A-1 5: Near-Ceiling Gas Temperatures, ICFMP BE #2 Series,

Sectors I& 3 Compared with McCaffrey Plume Temperature Correlation ..................... A-24

Figure A-16: Near-Plume Temperatures, FM/SNL Series, Sector 13 ................................... A-26

Figure A-17: Flame Heights for ICFMP BE #2 ...................................................................... A-27

Figure A-18: Photographs of Heptane Pan Fires, ICFMP BE #2, Case 2,

Courtesy of Simo Hostikka, VTT Building And Transport, Espoo, Finland ..................... A-28

Figure A-19: Photographs of ICFMP BE #3, Test 3, as seen through the 2 m by 2 m

Doorway, Courtesy of Francisco Joglar, SAIC ............................................................... A-29

Figure A-20: Near-Ceiling Gas Temperatures, ICFMP BE #3, Closed Door Tests ............... A-30

Figure A-21: Flame Heights, ICFMP BE #3, Open Door Tests ..................... A-31

Figure A-22: Heat Fluxes to Cable B .................................................................................... A-33

Figure A-23: Heat Fluxes to Cable B .................................................................................... A-34

Figure A-24: Heat Fluxes to Cable D ................................................................................... A-35

Figure A-25: Heat Fluxes to Cable D ................................................................................... A-36

Figure A-26: Heat Fluxes to Cable F .................................................................................... A-37

Figure A-27: Heat Fluxes to Cable F .................................................................................... A-38

Figure A-28: Heat Fluxes to Cable G ................................................................................... A-39

Figure A-29: Heat Fluxes to Cable G ................................................................................... A-40

xii
TABLES

Table 3-1: Summary of Plume Temperature Correlations ....................................................... 3-5

Table 5-1: Sensitivity Analysis for MQH Room Temperature Correlation ................................ 5-2

Table 5-2: Typical Thermal Penetration Times (Minutes) ........................................................ 5-2

Table 5-3: Input Values for ICFM P BE #3 ............................................................................... 5-3

Table 5-4: Sensitivity Analysis for Heskestad's Flame Height Correlation ............................... 5-5

Table 5-5: Sensitivity Analysis for the Point Source Flame Radiation Model ........................... 5-7

Table 5-6: Sensitivity Analysis for the Plume Temperature Correlations ................................. 5-9

Table 5-7: Sensitivity Analysis for Ceiling Jet Temperature ................................................... 5-11

Table A-1: Inputs to the MQH and FPA Models in ICFMP BE #3 .................... A-3

Table A-2: Relative Differences for HGL Temperature in ICFMP BE #3 ................................. A-6

Table A-3: Inputs to the MQH Model in ICFMP BE #4 ............................................................ A-7

Table A-4: Relative Differences for Hot Gas Layer Temperature in ICFMP BE #4 ................. A-8

Table A-5: Inputs to the MQH Model in ICMFP BE #5 ............................................................ A-9

Table A-6: Relative Differences for Hot Gas Layer Temperature in ICFMP BE #5 ........... A-10

Table A-7: Input Parameters for the FPA Model in FM/SNL Tests ....................................... A-10

Table A-8: Relative Differences for Hot Gas Layer Temperature in the FM/SNL Tests ........ A-12

Table A-9: Input Parameters for the MQH Model in the NBS Tests ...................................... A-13

Table A-1 0: Relative Differences for Hot Gas Layer Temperature in the NBS Tests ...... A-14

Table A-i 1: Target Location Information for Ceiling Jet Correlation ................................. A-15

Table A-12: Relative Differences for Ceiling Jet Temperature in ICFMP BE #3 .................... A-18

Table A-13: Target Location Information for Ceiling Jet Correlation ..................................... A-19

Table A-14: Relative Differences for Ceiling Jet Temperature in FM/SNL Tests ................... A-21

Table A-15: Target Location Information for Plume Correlation ............................................ A-22

Table A-16: Relative Differences for Plume Temperature, ICFMP BE #2 ............................. A-24

Table A-17: Target Location Information for Plume Correlations .......................................... A-25

Table A-18: Relative Differences for Plume Temperature in FM/SNL Tests ......................... A-26

Table A-19: Effective Horizontal Distances from the Fire to the Rad Gauges ........................ A-32

Table A-20: Relative Differences for Radiative Heat Flux ..................................................... A-41

xiii

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/PB 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-1 805

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

(FIVE-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 1355, Standard Guide for Evaluating the Predictive Capability of Deterministic

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.

xv
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-term 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)

xvi
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 (FDTs)

Volume 4 Fire-Induced Vulnerability Evaluation, Revision I (FIVE-Revl)

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

Volume 6 MAGIC

Volume 7 Fire Dynamics Simulator (FDS)

xvii

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 ICFMP Benchmark Exercise (BE) #2, as well as

Gesellschaft ifir Anlagen-und Reaktorsicherheit (GRS) and Institut fUr Baustoffe, Massivbau und

Brandschutz (iBMB) in Germany, 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

xix
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

xx
LIST OF ACRONYMS

AGA

AHJ

ASME

ASTM

BE

BFRL

BRE

BWR

CDF

CFAST

CFD

CFR

CSR

EdF

EPRI

FDS

FDTs

FHA

FIVE-Revl

FM/SNL

FPA

FRA

GRS

HGL

HRR

IAFSS

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 I

Factory Mutual & Sandia National Laboratories

Foote, Pagni, and Alvares

Fire Risk Analysis

Gesellschaft ffir Anlagen-und Reaktorsicherheit (Germany)

Hot Gas Layer

Heat Release Rate

International Association of Fire Safety Science

xxi
iBMB Institut ffir Baustoffe, Massivbau und Brandschutz

ICFMP International Collaborative Fire Model Project

IEEE Institute of Electrical and Electronics Engineers

IPEEE Individual Plant Examination of External Events

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

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

SWGR Switchgear Room

V&V Verification & Validation

xxii
LIST OF ACRONYMS

AGA

AHJ

ASME

ASTM

BE

BFRL

BRE

BWR

CDF

CFAST

CFD

CFR

CSR

EdF

EPRI

FDS

FDTs

FHA

FIVE-Rev1

FM/SNL

FPA

FRA

GRS

HGL

HRR

IAFSS

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

Electricitd 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 & Sandia National Laboratories

Foote, Pagni, and Alvares

Fire Risk Analysis

Gesellschaft ffir Anlagen-und Reaktorsicherheit (Germany)

Hot Gas Layer

Heat Release Rate

International Association of Fire Safety Science

xxiii
iBMB Institut ftir Baustoffe, Massivbau und Brandschutz

ICFMP International Collaborative Fire Model Project

IEEE Institute of Electrical and Electronics Engineers

IPEEE Individual Plant Examination of External Events

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

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

SWGR Switchgear Room

V&V Verification & Validation

xxiv
I

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 for these tools also increases. V&V studies afford fire modeling analysts confidence

in the application of analytical tools by quantifying 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.

In August 2002, the Electric Power Research Institute (EPRI) published for the first time

the Fire Modeling Guide for Nuclear Power Plant Applications (EPRI TR-1002981) [Ref. 1].

This fire modeling guide provides fire protection engineers in the commercial nuclear industry

a broad overview of fire modeling theory and applications, including representative calculations

performed with various state-of-the-art fire models. With this guide, EPRI included a library

of pre-programmed in Microsofto Excel® equations, which are used to estimate some aspects

of fire-generated conditions. This collection of equations is referred to as Revision 1

of the Fire-Induced Vulnerability Evaluation model (FIVE-Rev 1).

In general, the equations in the library are closed-form analytical expressions that can be solved

by hand. The capabilities of the various equations in the library include predicting temperature

and convective heat fluxes in the fire plume or ceiling jet, irradiated heat flux, upper-layer

temperature, time to detection, and target heating, among others.

The main objective of this study is to document a V&V study for selected models in the FIVERev 1 library, in accordance with ASTM E 1355, Standard Guide for Evaluating the Predictive

Capability of Detenninistic Fire Models [Ref. 2]. As such, this report is structured to follow

the guidance provided in the ASTM standard:

* Chapter 2 provides qualitative background information about FIVE-Rev 1 and the V&V process.

" Chapter 3 presents a technical description of FIVE-Rev 1, which includes the underlying

physics and chemistry inherent in the model. The description 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.

* Chapter 4 documents the mathematical and numerical robustness of FIVE-Rev 1, which

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

" Chapter 5 presents a sensitivity analysis, which discusses variations in the output parameters

with respect to changes in the input parameters.

1-1
Introduction

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

on the basis of relevant attributes of enclosure fires in NPPs. The calculated relative

differences are based on comparisons between experimental results and fire model predictions

of environmental conditions.

" Appendix A lists the calculated relative differences, which form the basis for the evaluation

results discussed in Chapter 6. Appendix A also includes graphical comparisons between

experimental measurements and corresponding modeling results.

1-2
2

MODEL DEFINITION

This chapter provides qualitative background information about FIVE-Rev 1 and the V&V process,

as suggested by ASTM E 1355.

2.1 Name and Version of the Model

This V&V study focused on Revision I of the Fire-Induced Vulnerability Evaluation model

(FIVE-Rev 1). The latest version of FIVE-Rev 1 was released in August 2002.

2.2 Type of Model

In August 2002, EPRI published for the first time the Fire Modeling Guide for Nuclear Power

Plant Applications (EPRI TR-1002981) [Ref. 1]. This fire modeling guide provides fire protection

engineers in the commercial nuclear industry a broad overview of fire modeling theory

and applications, including representative calculations performed with various state-of-the-art

fire models. With this guide, EPRI included a library of pre-programmed Microsoft® Excelo

equations, which are used to estimate some aspects of fire-induced conditions. This collection

of hand calculations is referred as FIVE-Rev 1.

In general, the equations in the library are closed-form analytical expressions that can be solved

by hand. The capabilities of the various equations in the library include predicting temperature

and convective heat fluxes in the fire plume or ceiling jet, irradiated heat flux, upper-layer

temperature, time to detection, and target heating, among others.

NOTE: This study did not address all of the equations in the FIVE-Revl library;

those subjected to the V&V process are identified throughout this report. See Chapter 3

for more details.

2.3 Model Developers

The FIVE-Rev 1 model was compiled and is maintained by the Electric Power Research Institute

(EPRI).

2.4 Relevant Publications

Technical descriptions of FIVE-Rev 1 are provided in EPRI's Fire Modeling Guide for Nuclear

Power Plant Applications (EPRI TR-1002981) [Ref. 1] and in Chapter 3 of this report.

In addition, EPRI's Methods of Quantitative Fire Hazard Analysis (EPRI TR-100443) [Ref. 3]

documents the quantitative fire modeling methods used in FIVE-Rev1.

2-1
Model Definition

2.5 Governing Equations and Assumptions

As previously mentioned, FIVE-Rev 1 is a library of equations for use in estimating various

aspects of fire-induced conditions. Each equation has its own assumptions, as detailed

in Chapter 3 of this report.

2.6 Input Data Required To Run the Model

The various equations in the FIVE-Rev1 library require different inputs, which are listed

in Chapter 3 of this report. However, the following parameters are generally necessary to use

the equations in the FIVE-Rev1 library:

(1) Parameters for describing the compartment geometry and ventilation conditions:

" The compartment (or each compartment in a multi-room scenario) is assumed to have

a rectangular floor base and flat ceiling. Its compartment geometry is defined by its

length, width, and height.

* The material properties of the floor, ceiling, and walls include density, specific heat,

and thermal conductivity. Depending on the selected material, this information may be

available in generic fire protection engineering handbooks or similar references.

* Natural ventilation is determined by the height and width of doors; height, width, and

elevation of windows; time to open/close doors and windows during a fire simulation;

and leakage paths.

* Mechanical ventilation is determined by supply and return rates, vent elevations, and time

to start/stop the system.

(2) Parameters for describing the fire characteristics:

* Fuel type and fire heat release rate (HRR) profile, which is specified using the heat

of combustion and the mass loss rate of the fuel

* Fire location (elevation, near a wall, near a comer, or center of room)

" Footprint area of the fire, which is circular (e.g., pool fires specified by diameter) or

rectangular (e.g., bounded pool fires, electrical cabinets specified by length and width)

* Fuel mass, irradiated fraction, and stochiometric fuel-oxygen ratio

(3) The two sets of parameters that describe targets are (a) thermo-physical properties, which

include the density, specific heat, and thermal conductivity of the material, and (b) location,

which refers to where the target is with respect to the fire (expressed in three-dimensional

coordinates).

(4) The inputs for sprinklers and detectors are (a) the device's location with respect to the fire

and (b) its response characteristics, including activation temperature and response time index.

2-2
Model Definition

2.7 Property Data

Some of the equations in the FIVE-RevI library require the following property data:

" For walls, ceiling, and floor: density, thermal conductivity, and specific heat

* For targets: damage temperature, density, thermal conductivity, and specific heat

* For fuels: heat of combustion, mass loss rate, stochiometric fuel-oxygen ratio, specific area,

and radiated fraction

These properties may be available in fire protection engineering handbooks or similar references.

However, depending on the application, properties for specific materials may not be readily

available.

2.8 Model Results

Each equation in the FIVE-Rev 1 library provides a single numerical output.

2-3

3

THEORETICAL BASIS FOR FIVE-REV1

This chapter presents a technical description of the FIVE-Revl library, including theoretical

background and the underlying physics and chemistry inherent in the different models. In doing so,

this chapter addresses the ASTM E 1355 guidance to "verify the appropriateness of the

theoretical basis and assumptions used in the model."

The description provided in this chapter 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 models.

The models included in the FIVE-Rev 1 library have been developed, reviewed, and documented

over the past 30 years. In addition, most of the engineering calculations in the FIVE-Rev 1

library are available in the open fire protection engineering literature, particularly in the Society

of Fire Protection Engineers [SFPE] Handbook of Fire Protection Engineering (3 rd Edition)

[Ref. 4]. As a result, this chapter references previous publications describing assumptions and

theoretical bases of some of the models included in the V&V process.

The modeling capabilities of FIVE-Rev 1 are restricted to the individual capabilities and limitations

of each model in the library. That is, each model was developed based on specific assumptions

and conditions, which restrict its application. This section provides the mathematical formulation

of the FIVE-Revl models included in this V&V study and a summary of the assumptions and

limitations related to their use. The following models in the FIVE-Rev 1 library were selected for

V&V:

1. Hot gas layer temperature

a. McCaffrey, Quintiere, Harkleroad (MQH) model, used in naturally ventilated

compartments

b. Foote, Pagni, Alvares (FPA) model, used in compartments with forced ventilation

2. Flame height

a. Heskestad's flame height correlation

3. Radiant heat flux

a. Point source radiation model

4. Plume temperature

a. Heskestad's plume temperature correlation

b. McCaffrey's plume temperature correlation

5. Ceiling jet

a. Alpert's ceiling jet correlation

3-1
Theoretical Basis for FIVE-Revl

3.1 Average Room Temperature1

The first model in this section, developed by McCaffrey, Quintiere, and Harkleroad [Refs. 5, 6]

(commonly known as the MQH model), estimates the average room temperature, as follows:

T ="T +6.85 j 2 1/3(OP

p Ii "~rnC t omot,,

h k d k c ttp d=4cp th2 

where:

T. = ambient temperature ('C)

Q = fire heat release rate (kW)

Ao = opening area (or sum of opening areas) (m2)

Ho = height of opening [in]

AT = internal surface area of the room (not including opening area) (in2)

k = thermal conductivity of wall material (kW/m-°C)

dm= density of wall material (kg/n 3)

Cp= specific heat of wall material (kJ/kg-°C)

th = wall thickness (in)

t = time value (sec)

The term A, JFoli is referred as the ventilation factor (or vent factor). This term captures the

natural ventilation characteristics of the room. The following additional considerations also

apply to the use of the MQH model [Ref. 5].

" The rise in temperature must be between 20 'C and 600 'C (68 'F and 1,112 'F).

* The model applies to both transient and steady fire growths.

The equations in this section (MQH & FPA) assume the room is a uniform control volume resulting in a

calculation for average room temperature. This approach is different than the one used by "two zone" fire

models for calculating hot gas layer temperature. However, in practical applications, the average room

temperature resulting from MQH or FPA is considered equivalent to a hot gas layer temperature resulting from

two zone fire model calculations.

3-2
Theoretical Basis for FIVE-Rev]

* The model attributes heat loss to mass flowing out through openings. Therefore, the model

does not apply to situations where significant time passes before hot gases begin leaving

the compartment through openings (e.g., large enclosures with relatively small fires, where it

may take the smoke layer some time to reach the opening height).

* The model assumes that the fire is fuel-controlled.

* Once the fire duration exceeds the thermal penetration time tp, the effective heat transfer

coefficient effecting heat conduction parameters is constant.

Following the basic correlation of the MQH model, Foote, Pagni, and Alvares developed a model

[Ref. 6] for use in estimating temperatures in mechanically ventilated rooms. The mathematical

expression for this formulation is as follows:

AT j- 0.72 ( A -0.36

-0.63 --

where mg is the compartment mass ventilation rate. The following additional considerations also

apply to the use of the Foote, Pagni, and Alvares model [from Ref. 6]:

* The expression for doorway flow is not considered.

* The coefficients and exponents are based on data from well-ventilated fire tests.

* The experimental compartment size is 6 x 4 x 4.5 m3 (19.7 x 13.1 x 14.7 ft3).

* Experimental ventilation rates range from 110 to 325 g/s (0.25 to 0.7 lb/sec).

* Experimental heat release rates range from 150 to 490 kW (142 to 465 Btu/sec).

3.2 Flame Height

According to Heskestad, the flame height marks the level where the combustion reaction is complete

and the inert plume begins [Ref. 6]. The flame height is estimated using the following equation:

L = 0.235Q0Y - 1.02D (in)

where:

O f = fire heat release rate (kW)

D = fire diameter (in)

Heskestad's flame height correlation is not appropriate for estimating jet flame lengths, or for

scenarios where atmospheric conditions deviate significantly from normal. Furthermore, the above

equation is valid for combustibles in which the heat liberated per unit mass of air entering the

combustion reaction ranges between 2,900 and 3,200 kJ/kg. That is, the equation is not valid for

very small HRR values where the resulting length is negative.

The above equation correlates well with data for L/D values up to 20 (note that L/D is a dimensionless

term), and Q* up to 100 [Ref. 6]. QD is also a dimensionless term, which is defined as follows

(see Volume 1 of this report series for more details):

3-3
Theoretical Basis for F1VE-Revl

Q; pc,r = ~TQI 04D2

Beyler [Ref. 7] indicates that a flame height determination based on a circular fuel source with

an area equal to the real source may overestimate the flame height. The above correlation

is intended for horizontal pool-type sources, but is likely to work reasonably well for more

complex sources if the calculated flame height is large relative to the diameter of the source.

3.3 Radiant Heat Flux

As described by Karlsson and Quintiere, the point source model for flame radiation assumes a fire

as a point source of heat release [Ref. 5]. Therefore, this model is appropriate for remote targets,

which "see" the fire as a point in space. A distance of twice the diameter of the fire is probably

appropriate. The critical distance from the target to a burning fuel can then be obtained by solving

the following equation for R and providing a critical heat flux required for target damage:

q.rr = 47rd2 (kW/m2)

where:

Q f = fire heat release rate (kW)

R = distance from center of flame (in)

Xr = irradiated fraction of the heat release rate (FIVE-Rev1 recommends 0.4)

3.4 Plume Temperature

The FIVE-Rev 1 library includes three semi-empirical correlations for estimating fire plume temperatures.

The two that are within the scope of this study are Heskestad's and McCaffiey's fire plume correlations.

These correlations have essentially the same underlying assumptions, limitations, and input

parameters. In general, these correlations predict the average temperature at some predetermined

height above the fire. In each case, the temperature estimate is derived by applying the principles

of conservation of mass, momentum and energy in the fire plume, combined with experimental

observations. Heskestad fundamentally analyzed the problem in terms of the total mass,

momentum, and energy integrated across the plume cross-section, assuming that the entrainment

velocity is proportional to the plume velocity, with the constant of proportionality being the

entrainment constant [Ref. 6].

Results from these three semi-empirical correlations are expected to be adequate for unobstructed

vertical plumes. Nonetheless, it should be noted that the correlations do not consider hot gas

layer (HGL) effects, which are discussed in Section 3.6. The following table lists the plume

temperature models.

3-4
Theoretical Basis for FIVE-Rev)

Table 3-1: Summary of Plume Temperature Correlations

Heskestad [Ref. 6] McCaffrey [Ref. 5]

IF=TT_, +9 +H, 1 T 2- 23 2

z, =0.083Q7• -1.02D

Continuous flame region:

For normal atmospheric conditions (T,,mb = 293 K,

iC=6.8,rj= 1⁄22

Pmb = 1.2 kg/m3, g = 9.81 m/s 2

, and c% = 1.00 kJ/kg-K),

the factor Intermittent region:

K = 1.9, j = 0

9.1( T.mb 3

gcp Pamb Inert plume region:

K= 1.1,r1 = -1/3

has a numerical value of 25.0

where:

Tamb = ambient temperature (OC)

Pamb = ambient air density (kg/m3

)

kf = fire location factor (kf = 1 for fires in the center of the room, Y2 for fires along a

wall, and 1⁄4 for fires in a comer)

Q f= fire heat release rate (kW), Note: Qc is the convected portion of the heat release

rate or 0C = of (1-Xr)

Fe = fire elevation (in)

HP= target height measured from the floor (m)

Xr = irradiated fraction of the heat release rate

D = plume diameter (m)

The factor (Hp - Fe) is the distance between the base of the fire and the elevation at which the

temperature is calculated.

3-5
Theoretical Basis for FIVE-Rev]

3.5 Ceiling Jet Temperature

Alpert developed the ceiling jet temperature correlation [Ref. 8] for unobstructed flat ceilings

without the effect of a smoke layer. The ceiling jet correlation predicts gas temperatures as the

hot gases spread radially from the plume. The mathematical form of the correlation is as follows:

5.3 8(kf-Of /Rf3+ TCJ h-Fe(C)

where:

Tamb = ambient temperature (°C)

kf = fire location factor (kf = 1 for fires in the center of the room, 1⁄2 for fires along a

wall, and 1⁄4 for fires in a comer)

Of= fire heat release rate (kW)

h = room height (m)

Fe fire elevation (m)

R = horizontal radial distance from the centerline of the fire

to where the temperature is reported (m)

The experimental data collected for developing the correlation consisted of various types

of solid and liquid fuels with energy release rates ranging from roughly 500 kW to 100 MW

under ceiling heights ranging from 4.6 to 15.5 m (15.09 ft to 50.85 ft). The correlation has good

agreement with the data in the range of R/(H-F.) from 1 to 2 [note that R/(H-F,) is a

dimensionless term] and ATe /(Tamb (Q* Y') ranging from 1 to 6 [Ref. 5].

The following equation resulted from the analysis of ceiling jet flows that produced

the temperature model shown above:

0.195 .(k:_ )/ 3 (h - Fe )1/2

V'j= R516 (mis)

The above correlations assume that no walls exist to channel the flow of gases or cause

the formation of a hot gas layer. The presence of walls or a hot gas layer will always increase

the temperature of the ceiling jet flow [Ref. 8].

3.6 Plume and Ceiling Jet Temperatures in Hot Gas Layer Environments

The correlations for plume and ceiling jet temperatures (discussed in Sections 3.4 and 3.5) were

developed using experimental data collected from controlled environments with no HGL effects.

If such correlations are used to analyze fire scenarios involving a hot gas layer, a correction must

be made to account for the thermal effects of the hot gas layer in the plume or ceiling jet

temperature. In the case of fire plume temperatures, the correlations can be used without the

correction if the target elevation above the fire source is below the HGL interface. By contrast,

in the case of ceiling jet temperatures, HGL effects may not be important (1) in the early phases of

3-6
Theoretical Basis for FIVE-Rev]

the fire event, when a hot gas layer has not been established, and (2) in relatively large rooms

with relatively small fires, where the HGL temperature is close to ambient.

Some zone models (e.g. MAGIC) consider the fire plume effects in the hot gas layer temperature

following the research documented by Cooper [Ref. 10]. This approach is based on the premise

that above the HGL interface, the fire plume entrains hot gases from the upper layer instead of

fresh air at ambient temperature.

In the first version of FIVE [Ref. 3], the HGL effects were included in the analysis by adding the

calculated temperature rise in the fire plume or ceiling jet temperature to the HGL temperature

using the following equation:

TPHGL = THGL + ATp = THGL + T, - Tob

In most cases, this simplification produces conservative estimates of plume and ceiling jet

temperature in the hot gas layer. Although FIVE-Revl does not include a model that directly

adds the HGL temperature and the ceiling jet or plume temperature, this approach continues to

be recommended when applicable for FIVE-Rev 1 users.

This V&V study used the original FIVE model described above to calculate plume temperatures

inside the hot gas layer. The fire plume temperature data for this study was collected in rooms

where the HGL effects appeared to be significant. Therefore, the calculated accuracies include

such effects. The HGL temperature added to the plume or ceiling jet temperature was calculated

with the MQH or FPA room temperature models.

3-7

4

MATHEMATICAL AND NUMERICAL ROBUSTNESS

This chapter documents the mathematical and numerical robustness of FIVE-Rev 1, which

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

Specifically, ASTM E 1355 suggests the following analyses to address the mathematical and

numerical robustness of models:

" Analytical tests involve testing the functionality 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.

" 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.

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

solved system of equations (as an indicator of numerical accuracy) and the reduction in residuals

(as an indicator of numerical convergence).

In general, the series of analyses that ASTM E 1355 describes for the mathematical and

numerical robustness of models do not apply to the models in the FIVE-Rev 1 library within the scope

of this V&V study, for the following reasons:

" Analytical tests: The models in the FIVE-Rev 1 library do not solve problems with known

mathematical solutions. Therefore, the model results cannot be compared to assess

the functionality of the models.

* Code checking: The models in the FIVE-Rev 1 library are pre-programmed as user-defined functions

in a Microsoft® Excel® workbook. Like any typical built-in Excelw function, each of these functions

requires a set of inputs and returns a single value. In this case, the returned value is the solution

of the model. (Section 3.1 discusses the models and their required inputs.) The user-defined

Excel® functions programmed in the FIVE-Rev I library are relatively brief. The structure

of each function includes a variable declaration section and the mathematical solution

of the equation. In addition, all of the models are consistent in their use of input variable names.

Therefore, no problems are expected with regard to irregularities and inconsistencies

within the computer code.

* Numerical tests: These models in the FIVE-Revl library are closed-form mathematical

expressions that are not solved using numerical methods. As a result, there are no numerical

instabilities or convergence issues associated with the solution of the models.

4-1
Mathematical and Numerical Robustness

The FIVE-Rev 1 library passed the EPRI software usability tests, which are intended to ensure

that the computer program can be installed on and uninstalled from a computer, the user's guide

is adequate for a first-time user, error messages are clear and displayed when required,

and examples in the user's guide can be reproduced. More details on the EPRI software usability

tests are available at www.epri.com.

4-2
5

MODEL SENSITIVITY

According to ASTM E 1355, a sensitivity analysis of a model is 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.

This chapter documents a sensitivity analysis for each of the models described in Chapter 3. Because

the models in the FIVE-Rev 1 library are algebraic equations, the derivatives are readily determined

and the sensitivities to the different parameters can be assessed. This type of analysis is also found in

Volume 2 of this report. Specifically -

1. The sensitivity to individual parameters is assessed determining the partial derivatives with

respect to the input parameters.

2. The sensitivity of the model to variations in more than one input parameter is assessed

numerically by plotting model results corresponding to the individual ranges of the input

parameters.

5.1 Sensitivity Analysis for Average Room Temperature

As previously discussed, the average room temperature is calculated using the MQH model

for naturally ventilated rooms, or the FPA model for mechanically ventilated rooms.

5.1.1 Sensitivity Analysis for the MQH Model

Recall that the MQH model for average room temperature is as follows:

T = Tamb + 6.85. A0 •TP~hk

The model has input parameters for (1) heat release rate Qf, (2) ventilation factor A0 o,,

(3) internal surface area of the room AT, and (4) the effective heat conduction term hk. Table 5-1

summarizes the partial derivative of average room temperature T with respect to these four

parameters.

5-1
Model Sensitivity

Table 5-1: Sensitivity Analysis for MQH Room Temperature Correlation

Parameter Partial Derivative Comment

The rate of room temperature change with respect to

aT Const * changes in the heat release rate is Const/Ql/3

Heat release rate -;Z! 3,f assuming all other inputs are constant.

The partial derivative suggests that rate of room

temperature change with respect to the ventilation

Vent factor aT Const 3 factor is Const (A0 4 Y )'. .For example, an

VentfacAorA 0 (A . i increase in the vent factor increases, and assuming all

ol other inputs are constant the room temperature will

increase at a rate of Const/(A0 •-H. )Y 3

aT Const The partial derivative suggests that rate of room

Internal room T temperature with respect to the room size (as

-surface area D(AT) (AT )4/3 represented by the surface area) is Const/(AT )4/3.

The partial derivative suggests that rate of room

Effective heat 5T Cons temperature rise with respect of the effective heat

conduction term O(hk) (hk)4/3 conduction term is Const/(hk)4/3.

*The constant term "Const" in the numerator depends on the remaining input parameters in the MQH model, which are

assumed constant in this exercise.

The effective heat conduction term, hk, is not always constant as assumed in the analysis

presented in Table 5-1. Recall from Chapter 3 the following definition for hk:

=fL-kd-_:'cP: t :tp

hk

-l t>tp

L th

where tp th2

4jk"d Cp$J

That is, hk is constant after the fire duration t exceeds the thermal penetration time tp. Table 5-2

lists tP values for some boundary materials.

Table 5-2: Typical Thermal Penetration Times (Minutes)

Thickness (m) 0.025 0.05 0.1 0.2 0.4 0.6

Marnite 17 69 276 1106 4422 9950

Concrete 4.375 17.5 70 280 1120 2520

Steel 0 1 3 10 41 93

5-2
Model Sensitivity

Notice that for good heat conductors such as steel, tp can be on the order of seconds to minutes

depending on the thickness. Before t reaches tp, however, the term hk is a function of the fire

duration. Accordingly, the rate of change of hk will decrease as t increases. The heat loss rate

to the boundaries will decrease as the fire duration increases until tp, at which time hk is a constant.

Let us explore how these sensitivities are reflected in an example. Consider the ICFMP BE #3,

Test 3 configuration. The input values for the MQH equation are listed in Table 5-3:

Table 5-3: Input Values for ICFMP BE #3

Ambient temp [*C] 22

Room Size

Room length [m] 21.7

Room width [m] 7.04

Room height [ml 3.82

Wall Properties

Wall k [kW/m-K] 0.00013

Wall Cp [kJ/Kg-K] 1.17

Wall p [kg/M3] 737

Thickness [m] 0.025

Nat & Mech Vent

Opening height Ho [m] 2

Opening area Ao [m2] 4

Solving the MQH equation for heat release ranging from 100 to 2500 kW (reflected in the y axis

of the surface plots in Figure 5-1) and vent factors from 0.5 to 10 M51 2 (reflected in the x axis of

the surface plots in Figure 5-1) the resulting room temperatures range from ambient to 1250 'C

(2,282 'F), as illustrated by the different shades in the surface plots. The surface plots provide a

graphical representation of average room temperature predictions for a range of vent factors and

heat release rates. The curve patterns bounding the different shades are consistent with the

sensitivities discussed above.

5-3
Model Sensitivity

Average Room Temp (C)

0 0-250 E 250-500 0 500-750 o 750-1000 a 1000-1250

-2500

2000 :

1500 e"

1000

500 a

x

I ! I i 100

q) q~ q~ Lq U U) q) U) )UFire duration = 20 mir

Vent Factor (m51 )

1

Figure 5-1: Surface Plot for Average Room Temperature. Surface plot summarizes room

temperatures for a range of vent factor and heat release rate values.

5.1.2 Sensitivity Analysis for the FPA Model

Recall that the FPA model for average room temperature is as follows:

-7 "" ( hkAT-0.36

AT 63(Q rhkAT

The key difference between the MQH and FPA model is the mechanical ventilation input. In

this model, the parameter mg represents the mass flow rate into the room. The sensitivities for

the parameters Q, AT, and hk are similar to the ones discussed in the previous section for the

MQH model. Differentiating the above equation with respect to mg suggests that the rate of

5-4
Model Sensitivity

room temperature change with respect to the mechanical ventilation is Const/rhl2 . That is, the

more air that is injected into the room will result in a lesser rate of temperature rise.

5.2 Sensitivity Analysis for Flame Height

The flame height is calculated using the Heskestad flame height correlation. The mathematical

form of the correlation is as follows:

L = 0.235Q0,/ -1.02D

Let's explore the flame height sensitivity to the input parameters QO and D. Table 5-4

summarizes the derivatives with respect to L.

Table 5-4: Sensitivity Analysis for Heskestad's Flame Height Correlation

Parameter Partial Derivative Comment

aL Const * The rate of flame height change with respect to the

Heat release rate of = _heat 5L/5 release rate is Const/Q3f/5 .

aL The partial derivative suggests that rate of flame height Fire diameter -- z -1.02 change with respect to the fire diameter is a constant

5D factor of -1.02.

*The constant term "Const" in the numerator depends on the remaining input parameters in the flame

height model.

The range of flame heights estimated with Heskestad's correlation is summarized in a surface

plot in Figure 5-2 for heat release rates ranging from 100 to 1000 kW and fire diameters ranging

from 0.5 to 4 m (1.6 to 13.1 ft).

The sensitivity analysis presented in Figure 5-3 suggests that the highest flame heights are

observed with the combination of high heat release rates and relatively small to medium fire

diameters [less than 2 m (6.6 ft)]. It is difficult to determine a typical range of fire diameters and

fire intensities for NPP applications in order to bound the sensitivity analysis for flame height.

Such ranges depend on the nature of the ignition source (oils spills, electrical cabinets, etc), and

the geometric characteristics of the scenario. Probably the largest flame-heights are associated

with high heat release rates and very small diameters [fires above 1 MW and diameters of-0.5 m

(1.6 ft)], which likely are unrealistic scenarios for diffusion flame fires in NPP applications.

5-5
Model Sensitivity

Flame Height (m)

a 0000-0.50 n 0.50-1.00 0 1.00-1.50 0 1.50-2.00 N 2.00-2.50 a 2.50-3.00 m 3.00-3.50

Z. ..1000

750 0

LU

500 0(0

250 *;

0

1 00

0.5 1 1.5 2 2.5 3 3.5 4

Fire Diameter (m)

Figure 5-2: Surface Plot for Flame Height. Surface plot summarizes flame heights

for a range of vent factor and heat release rate values.

5.3 Sensitivity Analysis for Radiant Heat Flux

The radiant heat flux model included in this V&V study is the point source model.

The mathematical form of the model is as follows:

. Qf

-4711?2

The point source model has three input parameters, including the heat release rate (Qf),

the radiative fraction (Zr), and the horizontal radial distance (R). The sensitivity of the radiant

heat flux to these parameters is summarized in Table 5-5.

5-6
Model Sensitivity

Table 5-5: Sensitivity Analysis for the Point Source Flame Radiation Model

Parameter Partial Derivative Comment

The rate of radiant heat flux change with respect to the

Heat re Const * heat release rate is a constant factor (assuming all

Heat release rate . other inputs are constant).

The rate of radiant heat flux change with respect to the

_qi,_ * radiative fraction is a constant factor (assuming all

Radiative fraction &Jfp 7 Const * other inputs are constant).

The partial derivative suggests that rate of radiant heat

Horizontal radial - Const flux change with respect to the horizontal radial

distance _R R3 distance is - Const/R 3 . That is, the radiant heat flux

will decrease significantly as the R increases.

*The constant term "Const" in the numerator depends on the remaining input parameters in the flame height

model, which are assumed constant in this study.

Figure 5-3 presents the sensitivity analysis for the point source model. 20 kW/m2 is considered

in the fire protection engineering literature as the threshold of flashover [Ref. 5], which in

practical terms means that any predicted incident heat flux above 20 kW/m2 is an indication of

damage for most types of targets. Note that in the context of this discussion the value of

20 kW/m2 does not refer to the damage criteria for any particular type of cable. This value only

provides a limit to the range of sensitivity analysis performed.

5-7
Model Sensitivity

Radiant Heat Flux (kWm 2 )

r0.0-4.0 n 4.0-8.0 o8.0-12.0 0 12.0-16.0 n 16.0-20.0

750

~~500_

100

0.5 1 1.5 2 2.5 3 3.5 4

Horizontal Radial Distance (m)

Figure 5-3: Surface Plot for Flame Radiation. Surface plot summarizes flame radiation

values for a range of vent factor and heat release rate values.

Variations in the radiated fraction may significantly impact the estimated heat fluxes because it

multiplies the HRR term in the point source model. Variations of around 10% in the resulting

heat flux are expected if the fraction is varied from 30% to 40%, which is the range typically

recommended.

5.4 Sensitivity Analysis for Plume Temperature

The three models available in the FIVE-Rev 1 library for calculating fire plume temperatures are

listed in Table 3-1. Some technical aspects of these models are discussed in Chapter 3. Perhaps

the most relevant input parameters for calculating fire plume are the heat release rate Of and the

distance above the base of the fire (Hp-F,). Let's review the fire plume temperature sensitivity to

these parameters by examining the partial derivatives listed in Table 5-6. The sensitivities are

very similar for the three models because the important relationship Qf/2 /(Hp - 3 is present

in the models.

5-8
Model Sensitivity

Table 5-6: Sensitivity Analysis for the Plume Temperature Correlations

Parameter Partial Derivative Comment

The rate of plume temperature cha.nge with respect to

Heat release rate ., Const , the heat release rate is Cons 1Q1 3. For example, as

5Q f the heat release rate increases the plume temperature

will increase at a lower rate.

The partial derivative suggests that the rate of plume

temperature with respect to the target elevation above

Elevation above aT Const the base of the fire is approximately

fire source - Fe) (H H(Hp -Fe )1/ Const/(H, - FJ , . That is, a relatively significant

reduction in plume temperature is expected as the

target elevation increase assuming all other inputs are

constant.

*The constant term "Const" in the numerator depends on the remaining input parameters in the flame

height model, which are assumed constant in this study.

The numerical outputs for the two correlations are presented in the form of surface plots in

Figures 5-4. For practical applications, the two correlations yield very similar results, as shown

in Figure 5-4. However, Figure 5-4 demonstrates a distinct feature of the McCaffrey temperature

correlation, which predicts lower temperatures near the flames (the combusting region of the

plume). That is expected because the correlation actually consists of three equations, including

one for each distinct region of the fire plume. The sensitivity analysis also demonstrated the

relatively high level of hazard for targets located in fire plumes. Notice that temperatures up to

250 'C (482 'F) are calculated around 7 m (23 ft) above the fire.

5-9
Model Sensitivity

Plume Temperature - Heskestad's Correlation (C)

3 0-200 m 200-400 o 400-600 o 600-800 a 800-1000 01000-1200

4000

3500

3000

2500

2000

1500 -

1000

100

1 2 3 4 5 6 7 8

Bevation Above Fire (m)

Plume Temperature - McCaffrey CorreltnorrPlation (C)

c et-200 ae 200-400 3. 400-600 m th a-800 a 800-1000 oh eon-1200

-4000

E -3500

-3000

-2500

-2000 =

-1500

-- 500 "

-100

2 3 4 5 6 7 8

Bevation AbovFe (m)

Figure 5-4: Surface Plot for the McCaffrey Correlation for Plume Temperature.

Surface plot summarizes plume temperature values for a range of vent factor

and heat release rate values.

5.5 Sensitivity Analysis for Ceiling Jet Temperature

The ceiling jet temperature is calculated using the Alpert correlation. Technical aspects of the

correlation are discussed in Chapter 3. The mathematical form of the equation is as follows:

Th h- Fe

5-10
Model Sensitivity

For practical applications, the important input parameters are the heat release rate (Q)

the horizontal radial distance (R), and the elevation above the fire (h-Fe). The ceiling jet

temperature sensitivities with respect to these parameters are listed in Table 5-7.

Table 5-7: Sensitivity Analysis for Ceiling Jet Temperature

Parameter Partial Derivative Comment

The rate of ceiling jet temperature change with respect

Cn* to the heat release rate is Const/Q3. As the heat a T 2,C o n s t t h e t r l a e r t s C n t Q

Heat release rate aoQ V/3 release rate increases (and assuming all other inputs

are constant), the ceiling jet temperature will increase

at the rate given by this factor.

The rate of ceiling jet temperature change with respect

Horizontal radial cT Const to the horizontal radial distance is Const/R5 /

3 . As the

distance Rheat release rate increases (and assuming all other inputs are constant), the ceiling jet temperature will

increase at the rate given by this factor.

The rate of ceiling jet temperature change with respect

Elevation above t9T__ Const to the elevation above the fire is Const/(h - F )2.

the fire a(h - Fe ) (h - F )2 As other the heat release rate increases (and assuming all inputs are constant), the ceiling jet temperature

will increase at the rate given by this factor.

*The constant term "Const" in the numerator depends on the remaining input parameters in the flame

height model, which are assumed constant in this study.

The surface plot in Figure 5-5 provides an example of ceiling jet calculations using the Alpert

correlation. For this calculation, the ceiling height above the base of the fire is 4 m (13.1 ft).

The surface plot groups temperature results for a range of heat release rates and horizontal radial

distances.

5-11
Model Sensitivity

Ceiling Jet Temperature - Alpert Correlation (C)

o 0-50 m 50-100 E3 100-150 o 150-200 u 200-250 to 250-300 m 300-350 o 350-400

4000

3500

•2000

1500

14100058

•100

1 2 3 4 5 6 7 8

Horizontal Radial Dist (m)

Figure 5-5: Surface Plot for the Ceiling Jet Temperature. Surface plot summarizes

ceiling jet temperature values for a range of horizontal radial and heat release rate values.

5-12
6

MODEL VALIDATION

Consistent with Section 11 of ASTM E 1355, "Model Evaluation," this chapter summarizes

the results of the validation study conducted for the engineering calculations in the FIVE-Rev 1

library of engineering calculations. The validation study consisted of comparing results obtained

from a selected number of models in the FIVE-Rev 1 library with experimental measurements

of the corresponding quantity. A brief description of each set of experiments is given here.

Further details can be found in Volume 2 and in the individual test reports.

ICFMP BE #2: Benchmark Exercise #2 consists of eight experiments, representing three sets of

conditions, to study the movement of smoke in a large hall 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 m

high x 27 m long x 14 m wide (62 ft x 88.5 ft x 46 ft). 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 ICFMP and sponsored by the

NRC, consists of 15 large-scale tests performed at NIST in June 2003. The fire sizes range from

350 kW to 2.2 MW in a compartment with dimensions 21.7 m high x 7.1 m long x 3.8 m wide

(71 ft x 23 ft x 12.5 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, while the

floor is covered with two layers of gypsum boards. The room has one door with dimensions of 2 m

x 2 m (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 pool fire experiments conducted at

the Institut ftir Baustoffe, Massivbau 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 m x 3.6 m x 5.7 m

(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 m (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 preheated the

compartment.

FM/SNL Series: The Factory Mutual & Sandia National Laboratories (FM/SNL) Test Series is a

series of 25 fire tests conducted for the NRC by Factory Mutual Research Corporation (FMRC),

under the direction of Sandia National Laboratories (SNL). The primary purpose of these tests

was to validate computer models for various types of NPP compartments. The experiments were

6-1
Model Validation

conducted in an enclosure measuring 18 m long x 12 m 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 pool, 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 are the heat release rate, enclosure ventilation rate, and fire location. Only Tests 4,

5, and 21 were used in the present evaluation. Test 21 involves the full-scale mockup. All were

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

100-kW fire experiments (Test 1OA, 1000, and 100Z) were used for the current V&V study.

This chapter documents the comparison of models in the FIVE-RevI library predictions with the

experimental measurements for the six test series. Not all models in the FIVE-Rev 1 library

described in Chapter 3 are subjected to this evaluation. In general, the model was evaluated if

the selected tests series included data supporting the evaluation. At the same time, the models

evaluated are those usually used in evaluating NPP scenarios.

Technical details of the calculations, including output of the model and comparison with

experimental data are provided in Appendix A. The results are organized by quantity as follows:

" Section 6.1 discusses the evaluation of HGL temperature correlations in FIVE-Rev 1.

The MQH model was evaluated using data from compartment fire tests with open doors,

whereas the FPA model was evaluated using data from compartment fire tests with closed

doors and mechanical ventilation.

* Section 6.2 discusses the evaluation of the Alpert ceiling jet temperature correlation.

* Section 6.3 discusses the evaluation of the Heskestad and McCaffrey plume temperature

correlations.

" Section 6.4 discusses the evaluation of Heskestad's flame height correlation.

" Section 6.5 discusses the evaluation of the point source radiation model.

The model predictions are compared to the experimental measurements in terms of the relative

difference between the maximum (or where appropriate, minimum) values of each time history:

AM- ALE (M, -M,,- (E, -E0 )

where AM is the difference between the peak value of the model prediction, Mp, and its original

value, Mo. AE is the difference between the experimental measurement, Ep, and its original

value, Eo.

6-2
Model Validation

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 modelprediction of the gas temperature is related to the simplified physical

description of the fire and the accuracy of the input parameters (e.g., the specified 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

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. The details of

the calculations, input assumptions, and time histories of the predicted and measured output are

included in Appendix A. 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. Colors are assigned based on the following criteria:

Criterion 1: Are the physics of the model appropriate for the calculation being made? This

criterion reflects an evaluation of the underlying physics described by the model and the physics

of the fire scenario. Generally, the scope of this study is limited to the fire scenarios that are

within the stated capability of the selected fire models (e.g., this study does not address the fire

scenarios that involve flame spread within single and multiple cable trays).

Criterion 2: Are there calculated relative differences outside the experimental and model input

uncertainty? This criterion is used as an indication of the accuracy of the model prediction.

Because fire experiments are used as a way of establishing confidence in model prediction,

the confidence can only be as good as our experiments and the model inputs derived from

experiments. Therefore, if model predictions fall within the ranges of these combined

uncertainties, the predictions are determined to be as accurate as the experiments and data.

Section 2.6.3 and Volume 2 of this report provide an introduction and technical details for the

uncertainty analysis.

The predictive capability of the model is characterized as follows based on the above criteria:

•: If both criteria are satisfied (i.e., the model physics are appropriate for the calculation

being made and the calculated relative differences are within or very near experimental

uncertainty), the V&V team concluded that the fire model prediction is accurate for the ranges of

experiments in this study, and as described in Tables 2-4 and 2-5. A grade of Green indicates the

model can be used with confidence to calculate the specific attribute. The user should recognize,

however, that the accuracy of the model prediction is still somewhat uncertain and for some

attributes, such as smoke concentration and room pressure, these uncertainties may be rather

large. It is important to note that a grade of Green indicates validation only in the parameter

space defined by the test series used in this study; that is, when the model is used within the

ranges of the parameters defined by the experiments, it is validated.

6-3
Model Validation

WA :W If the first criterion is satisfied and the calculated relative differences are outside

the experimental uncertainty but indicate a consistent pattern of model over-prediction or underprediction, then the model predictive capability is characterized as Yellow+ for over-prediction,

and Yellow- for under-prediction. The model prediction for the specific attribute may be useful

within the ranges of experiments in this study, and as described in Tables 2-4 and 2-5, but users

should use caution when interpreting the results of the model. A complete understanding of

model assumptions and scenario applicability to these V&V results is necessary. The model may

be used if the grade is Yellow+ when the user ensures that model over-prediction reflects

conservatism. The user must exercise caution when using models with capabilities described as

Yellow±.

ELLO : If the first criterion is satisfied and the calculated relative differences are outside

experimental uncertainty with no consistent pattern of over- or under-prediction, the model

predictive capability is characterized as Yellow. A Yellow classification is also used despite a

consistent pattern of under- or over-prediction if the experimental data set is limited. Caution

should be exercised when using a fire model to predict these attributes. In this case, the user is

referred to the details related to the experimental conditions and validation results documented in

Volumes 2 through 6. The user is advised to review and understand the model assumptions and

inputs, as well as the conditions and results to determine and justify the appropriateness of the

model prediction to the fire scenario for which it is being used.

As suggested in the criteria above, there is a level of engineering judgment in the classification

of fire model predictive capabilities. Specifically, the V&V project team exercised engineering

judgment in the following two areas:

1. Evaluation of the modeling capabilities of the particular tool if the model physics are

appropriate.

2. Evaluation of the magnitude of relative differences when compared to the experimental

uncertainty. Judgment in this area impacts the determination of Green versus Yellow colors.

The team included fire model developers, NPP fire modeling experts, and code users. In general,

a Green or Yellow classification suggests that the V&V team determined that the model physics

are appropriate for the calculation been made, within the assumptions of the specific model.

The difference between the colors is attributable to the magnitude of the calculated relative

differences. Judgment considerations include general experimental conditions, experimental

data quality, and the characterization of the experimental uncertainty.

6.1 Hot Gas Layer (HGL) Temperature

The single most important prediction a fire model can make is the temperature of the hot gas

layer. After all, the impact of the fire is often assessed not only as a function of the heat release

rate, but also as a function of the compartment temperature. A good prediction of the height of

the hot gas layer is largely a consequence of a good prediction of its temperature because smoke

and heat are largely transported together and most numerical models describe the transport of

both with the same type of algorithm. Hot gas layer temperatures were predicted using the MQH

or FPA temperature models depending on the ventilation characteristics of the test (natural or

mechanically ventilated enclosure). The following is a summary of the accuracy assessment for

6-4
Model Validation

the HGL predictions of the six test series. The results of the V&V for HGL temperature are

summarized in Figure 6-2.

ICFMP BE #2: ICFMP BE #2 scenarios presented a significant challenge for the room

temperature correlations in FIVE-Rev 1. In the first two cases, which consist of a "closed" room

with significant leakages, the MQH significantly over-predicted the HGL temperature.

The experimental description suggests wall boundaries as having a layer of steel that was 1 mm

(0.04 in) thick and an outside layer of mineral wool. If the HGL temperature is calculated

assuming steel only, results are under-predictions. That is, most of the heat generated by the fire

is lost through the boundaries resulting in a temperature increase of a few degrees only. If the

analysis is conducted assuming walls with wool properties, the results are the over-predictions

mentioned above.

Given that both the wall properties and the room openings are important inputs to the MQH

model, and those values, as described in the experimental reports are uncertain, MQH results can

be misleading. At the same time, the MQH model over-predicts the HGL temperature if the

boundary materials are relatively poor heat conductors (e.g., wool). Because the results are

considered misleading, they are not included in the V&V analysis.

Case 3 consists of a mechanically ventilated room. However, the FPA model is not applicable

because the mechanical ventilation is operated only in the exhaust mode.

ICFMP BE #3: The MQH (open door tests) and FPA (closed door with mechanical ventilation

tests) models over-predict the HGL temperature for all nine tests for which calculations were

made. Both models over-predicted temperatures by approximately 50%. This analysis does not

include Tests 1, 2, 7, 8, 13, and 17 because no model was available in the FIVE-RevI library for

the corresponding experimental conditions (closed door and no mechanical ventilation).

The collection of graphical comparisons between MQH and FPA models predictions for HGL

temperatures and heights for ICFMP BE #3 is presented in Figures A-1 through A-2. The

relative differences calculated for peak values are summarized in Table A-2 and Figure 6-2.

ICFMP BE #4: The MQH model slightly over-predicts the temperature for this test. However,

the over-prediction is within the experimental uncertainty of ±3%. Furthermore, both the

experimental measurement and MQH predictions are above 500 'C (932 'F), which are well

above typical target damage values for targets in the commercial nuclear industry. Figure A-4

illustrates both the experimental and predicted temperature profiles.

ICFMP BE #5: The MQH model predicts the room temperature within experimental

uncertainty in this test. The graphical comparison between experimental measurements and

model predictions, illustrated in Figure A-6 suggests very good agreement between the profiles.

The calculated relative differences for peak HGL temperature and height are listed in Table A-6.

FM/SNL: The FPA model considerably over-predicts the HGL temperature for Tests 4, 5, and

21. Graphical comparisons are provided in Figure A-8, whereas relative differences are listed in

Table A-8.

NBS Multi-Room: MQH predictions in this test series are within the experimental uncertainty

for the fire room. These under-predictions are depicted in Figure A-11. It should be noted that

the ceramic fiber insulating material covering the fire-brick was selected for the room boundaries.

6-5
Model Validation

This selection resulted in significant under-predictions. Table A- 10 lists corresponding relative

differences.

Summary: HGL Temperature - YELLOW+

" Evaluation results suggest that the MQH and FPA models over-predict room temperatures by

50% or more. It should be stressed that in the case of rooms with different layers of wall

boundaries (NBS), the most insulating one was selected. Based on the results of this study,

if relatively poor heat conductive boundary materials like concrete, marinate, or wool are used

in the MQH or FPA correlations and all other inputs are well known, the correlations should

over-predict the HGL temperature.

* Recall from Chapter 3 that the MQH and FPA equations require the calculation of the thermal

penetration time (tp) before determining the effective heat conduction parameter (hk). For

temperature calculations after the time value tp, hk results in a constant value, which at the same

time produces a constant temperature result, given that all other inputs are constant. This

technical characteristic impacted some of the calculated relative differences. Consider as an

example Figure 6-1 below. The thermal penetration time is approximately 17 minutes. At this

point in time, the predicted temperature (solid line) "jumps" to a higher temperature. This

artificial "jump" results from the hk calculation after time exceeds tp. Consequently, a higher

relative difference will result if it is calculated after 17 minutes. Notice from the profile that

the relative difference would still be positive before or after the "jump."

350 100 1Hot Gas Layer Tenperature 90 _ __

300 .Y F BE #3, Test 3 Hot Gas Lay Temperature

80 FMT 5

250+ 70

200 60

10

00

0 5 10 15 20 25 0 5 10 15

Tni (rin) Tirff (rrr)

Figure 6-1: Sample Temperature Profile from MQH and FPA Temperature Correlations

" The MQH and FPA correlations were not validated for relatively large rooms (turbine

buildings), in this study.

* The scatter plots in Figure 6-1 summarize the relative differences calculated for HGL

temperatures.

* Because most of the validation results are above the experimental uncertainty, a color

assignment of Yellow+ is recommended for the room of fire origin. Analysts should consider

that these are correlations developed for specific scenario conditions. Furthermore, models

should be used with caution if wall materials are good heat conductors because results can be

under-predictions.

6-6
Model Validation

800

700

!

1 MQH/FPA Room Temp Models

A

CL

E

I600

500

400

M -*

30

2(

00 MirICFvIPBE #2

S aICFVP BE #3

00 -aICFVP BE #4

~~~ .. >- oFMP BE #5

00 - ~FMSNL x 

I~~ ?' NBS

0 200 400 600 800

1C

Measured Temp Rise (C)

200%

Hot Gas Layer Temperature S

150%/

1000,

500,

0%

0,/

-500/

-1005/

%

%

0

0

0o i p. - -- O--&-.- ----O--O °___

0 - o

o - MQH model, . - FPA model

BE# 2, Cases 1- 3: See discussion in Section 6.1

(,- a- N _) a a. - r- • a. N) a- a. 0~ C*) C. 'CD t.L) r- C') C' a. a 0) a. ) U. C) It U C . a a -) 0 U Z U. ZLLU. ULLL W ~LLLL L w .w U LL zz 9uuu 9 L ooo L)LL.U 0 0LLU L

Figure 6-2: Scatter Plot for Hot Gas Layer Temperature Relative Difference Results

6-7
Model Validation

6.2 Ceiling Jet Temperature

The FIVE-Rev I library includes the Alpert correlation for ceiling jet temperature. The

correlation applies to the flow of hot gases under flat unobstructed ceilings, which usually limits

its applications in NPP scenarios. Furthermore, the correlation is not intended to model the

ceiling jet temperature in compartments with a well-developed hot gas layer.

Only two of the six test series (ICFMP BE #3 and FM/SNL) involve a ceiling jet formed over a

relatively wide, flat ceiling; however, these experiments developed a hot gas layer. See Sections

3.5 and A.2 for additional technical details on this issue. V&V results for ceiling jet temperature

are summarized in Figure 6.3.

ICFMP BE #3: The Alpert correlation consistently under-predicts the ceiling jet temperature by

approximately 80%. This under-prediction is most likely attributable to the presence of a hot gas

layer in the room, which makes the Alpert correlation not applicable for this scenario. Figure 6-2

illustrates this consistent pattern of under-predictions. As previously mentioned in this report,

FIVE studies in the early 1990s conservatively added the ceiling jet and layer temperatures in

order to obtain an upper bound of the expected gas temperature in the ceiling jet. This continues

to be the recommended approach for FIVE-Rev 1 users for calculating ceiling jet temperatures in

rooms with well-developed hot gas layer. Nonetheless, that practice appears to result in overpredictions of the ceiling jet temperature. The over-predictions range accordingly with the overpredictions of the HGL temperature calculated with the MQH and FPA models. Notice that

Figure 6-1 does not include markers for ICFMP BE #3 tests with closed doors and no mechanical

ventilation because no HGL temperature was calculated for them.

The graphical comparisons between experimental measurements and Alpert's correlation

predictions for ceiling jet temperature are grouped in Figures A-10 and A-11. Table A-12 lists

the calculated relative differences.

FM/SNL: The Alpert correlation again under-predicts the ceiling jet temperature by

approximately 80%. However, if the HGL temperature is considered, temperatures are overpredicted. The graphical comparisons are provided in Figure A- 12. The calculated relative

differences are listed in Table A-14 and plotted in Figure 6-3.

Summary: Ceiling Jet Temperature - YELLOW+

" The Alpert correlation under-predicts ceiling jet temperatures in compartment fires with an

established hot gas layer. This result is expected because the correlation was developed

without considering HGL effects. The original version of FIVE accounted for HGL effects

by adding the ceiling jet and HGL temperature. This practice results in consistent overpredictions of the ceiling jet temperature. The approach of adding ceiling jet temperatures to

the calculated hot gas layer continues to be the recommended method for FIVE-Rev 1 users.

" Based on the above discussion, a classification of Yellow+ is recommended if HGL effects on

the ceiling jet temperature are considered using the approach described in the above bullet.

The Alpert correlation by itself is not intended to be used in rooms with an established hot gas

layer.

6-8
Model Validation

450-

400

350

300 0

U)

R 250 a.

E

" 200 S

Ceiling Jet Temperature

* ICFMPBE #3 No HGL

SICFVP BE #3 With HGL

A FR/SNL No HGL

e FM/SNL With HGL

0

so

400

04b

15

IL

10

0-6

0-S

0

* *

.. w . 5

Mewa.

200 300

sured Temp Rise (C)

200%

Ceiling Jet Temperature

150% a

100% ý-- •HGL + Alpert N

% * Alpert

i pe

------------------------------------ - -50% 0% ........... * •. * $ :• ... .. ................... ........ ............................................. ...................

-50%

-100% -_.....

7 c"J c?. 7 1- C'. TD '4 0 m' to P- m' 0) CD 't 0 w- v "TLO < N C' C4 " A 6 C) 6AC' c; 7-C) C7 C) CA , * 4 U') -ý, - ý, LU LUJ ILU LU ILU LU LU jj CU ' C') C') L UJ ' o J Z Z -ZJ O •0 0 

m com .• " U) U) U

LL LL 2 mm m

u_ z z Z

Figure 6-3: Scatter Plot of Relative Differences for Ceiling Jet Temperatures

in ICFMP BE #3, and the Selected FM/SNL Tests

6-9
Model Validation

6.3 Plume Temperature

This section evaluates the McCaffrey and Heskestad's plume temperature correlations included

in the FIVE-Rev1 library. Recall that these correlations were developed considering

unobstructed plumes in rooms with no hot gas layer. Data from ICFMP BE #2 and the FM/SNL

test series have been used to assess the accuracy of plume temperature predictions. However,

fires in these tests did generate a hot gas layer.

ICFMP BE #2: McCaffrey's and Heskestad's correlations suggested under-predictions of the

plume temperature. It is interesting to note, however, that predictions for TG1 are close to or

within experimental uncertainty, while those for TG2 are not. Thermocouple TG1 is closer to

the fire where HGL effects may not influence the plume temperature as much. Both under- and

over-predictions were observed. Figures A-14 and A-15 provide the graphical comparisons

between model predictions and experimental measurements. The calculated relative differences

are listed in Table A- 16 and plotted in Figure 6-4. The HGL temperature was not added to the

plume temperature because no HGL temperature was calculated for this test series with the tools

available in FIVE-Rev 1.

FMISNL: McCaffrey's and Heskestad's correlations under-predicted plume temperatures in

Tests 4 and 5. See Figure A-16 and Table A-18 for the graphical comparisons and the calculated

relative differences. No comparison was made in Test 21 because the fire was inside a cabinet

and is not clear how this configuration affected the plume flow. As illustrated in Figure 6-4,

summing the HGL temperature and plume temperature results in over-predictions of more than 50%.

Summary: Plume Temperature - YELLOW+

* McCaffrey's and Heskestad's correlations under-predict plume temperatures in compartment

fires with an established hot gas layer. For these cases, correlation results should be corrected.

The original version of FIVE made this correction by adding the plume and HGL temperature.

The approach of adding plume temperatures to the calculated hot gas layer continues to be the

recommended method for FIVE-Rev 1 users.

o Based on the above discussion, a classification of Yellow+ is recommended if HGL effects on

the plume temperature are considered using the approach described in the bullet above. The

McCaffrey and Heskestad correlations are not intended to be used in rooms with an established

hot gas layer.

6-10
Model Validation

~nn OUU

500 -

400

0

._

E 300.

I200

LU

Plume Temperature

* KCFMP BE#2 - No HGL

* FMvSNL - No HGL

* FM/SNL - With HGL

3 * ~

3.-.-

-- .-- ~~* ji *

100 -

.4 • -

0

0 50 100 150 200 250

Measured Temp Rise (C)

30C

150% ,

Plume Temperature

100% * TG.1-rMcCaffrey

a TG.1-Heskestad

50% TG.2-MCaffrey + HGL

n TG.2-McCaffrey

x TG.2-Heskestad

o TG.2-Heskestad + HGL 0

50% *LX

-100%~ - ----- - D - - 0- N

Cýr M- CCm()l M M i t LO M q

w w ~w w w w w z 0 mm mm M Mm M w4 w4 w4 M M M m - W W M M m mm W O Q

mm mm mm CO MM Lz zZ

Figure 6-4: Scatter Plot of Relative Differences for Plume Temperatures in ICFMP BE #2,

and the Selected FM/SNL Tests

6-11
Model Validation

6.4 Flame Height

Flame height is recorded by visual observations, photographs, or video footage. Videos from the

ICFMP BE #3 test series and photographs from BE #2 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. In FIVE-Revl, flame height is calculated using Heskestad's correlation.

ICFMP BE #2: The height of the visible flame in the photographs of BE #2 has been estimated

to be between 2.4 and 3 pan diameters [3.8 m to 4.8 m (12.5 ft to 15.7 ft)]. From Figure A-17,

which reports flame height predictions, flame heights are 3 to 5 m (9.8 ft to 16.4 ft). Those

predictions are consistent with the experimental observations.

ICFMP BE #3: The Heskestad correlation appears to accurately predict the flame height in this

test series, at least to the accuracy of visual observations and a few photographs taken before

the HGL obscures the upper part of the fire. The experiments were not designed to measure the

flame height other than through visual observation. Flame height pictures and model predictions

can be found in Figures A-20 through A-21.

Summary: Flame Height - GREEN

" Based on a comparison between visual observations and Heskestad's correlation predictions,

the correlation is appropriate to calculate flame height for scenarios similar to the ones

evaluated in this study.

* Visual observations of flames compared with Heskestad's predictions suggest good agreement.

It is not possible to provide a quantitative assessment of the comparison given that no flame

height data was collected during the experiments. However, this evaluation does not suggest

that the Heskestad correlation is consistently under- or over-predicting flame height. A Green

classification is recommended for applications involving flames away from walls.

6-12
Model Validation

6.5 Radiative Heat Flux

Radiant heat flux data is available from ICFMP BE #3 only. This evaluation compares point

source model results with experimental measurements using radiation gauges. Graphical

comparisons of experimental measurements and model results are included in Figures A-22

through A-29. Relative differences are listed in Table A-20.

ICFMP BE #3: Four radiation gauges were selected for comparison, Gauges 1, 3, 7, and 10.

The experimental uncertainty is about 20 % for both heat flux and surface temperature.

Figure 6-4 shows the relative differences. The following observations are relevant:

" Experimental measurements for Gauge 10 are consistently under predicted by

approximately 50%.

* Gauges 1, 3, and 7 show similar patterns per test of over and under predictions. Closed

door tests are over predicted, and opened door tests are either within experimental

uncertainty or under predicted.

* The point source model is intended for predicting radiation from flames in an

unobstructed and smoke-clear path between flames and targets. That is not the case in

most of these comparisons. Gauge 10 has the lowest elevation from the floor, but its

location alone does not explain a consistent under-prediction in open and close door tests.

Gauges 1, 3, and 7 were located 2, 2.5, and 3 m (6.6 ft, 8 ft, and 9.8 ft) respectively above

the floor. The hot gas layer in opened door tests descended to 1 m (3.3. ft) above the

floor. Therefore, these three gauges were immersed in smoke during all tests by the time

where the radiation measurements were selected for comparison. Given that the point

source inputs are the same for all tests with the exception of the heat release rate, the

difference between the over predictions in closed door tests and under predictions is open

door tests is due to the experimental measurements. That is, experimental measurements

are lower in open door tests than in close door tests. This observation is difficult to

generalize for practical purposes since conditions like location of the hot gas layer, soot

concentration and location of the target relative to the fire will need to be considered on a

case by case basis.

* Based on the above discussion, a yellow classification is recommended. Analysts should

consider that the point source model is intended for predicting radiation from flames in an

unobstructed and smoke-clear path between flames and targets. In addition, results

indicate a difference in the model predictions capabilities for scenarios in room with

closed and open door. No data was available in this study from a scenario with such

conditions.

Summary: Radiant Heat Flux - YELLOW

Based on the above discussion, a Yellow classification is recommended. Analysts should

consider that the point source model is intended for use in predicting radiation from flames

in an unobstructed and smoke-clear path between flames and targets. No data were

available in this study from a scenario with such conditions.

6-13
Model Validation

20

18 Radiar

* Gauge

16 m Gauge

;714 A Gauge

o Gauge

121

LL

t 1o11

6" 4

4

2!

0'

it Heat Flux

1 - Cable F

3 - Cable B

7 - Cable D

10 - Cable G

I

A A

U.

t

LAA A.AýA

Pip.

0 S

0

0 5 10 15

Measured Heat Flux (kW/m2)

350%

300%

250%

200%

150%

100%

50%

0%

-50%

-100%

Radiant Heat Flux

£v

* Gauge 3 (Cable F)

A Gauge 3 (Cable B)

A Gauge 7 (Cable D)

0 Gauge 10 (Cable G)

3

........... . .. ... ......... .......... . . . i . t .• . . : . . . . . . . . . . . . . . - - .--- ----- - - -- - - -- - -

7 7p 0 < N

C mD D mDCC CO CO CO CO wU W L CO Wn () Z

LI. Z Z Z

Figure 6-5: Scatter Plot of Relative Differences for Radiant Heat Flux

6-14
7

REFERENCES

1. Fire Modeling Guide for Nuclear Power Plant Applications, EPRI TR- 1002981,

Electric Power Research Institute, Palo Alto, CA, August 2002.

2. Standard Guide for Evaluating Predictive Capability of Deterministic Fire Models,

ASTM E1355-05a, American Society for Testing and Materials, West Conshohocken,

PA, 2004.

3. Methods of Quantitative Fire Hazard Analysis, EPRI TR-100443, Electric Power

Research Institute, Palo Alto, CA, May 1992.

4. SFPE Handbook of Fire Protection Engineering, 3rd Edition (P.J. DiNenno, Editor-inChief), National Fire Protection Association and The Society of Fire Protection

Engineers, Quincy, MA, 2002.

5. Karlsson, B., and J. Quintiere, Enclosure Fire Dynamics, CRC Press, Boca Raton,

FL, 2000.

6. Heskestad, G., Section 2-1, "Fire Plumes, Flame Height, and Air Entrainment,"

SFPE Handbook of Fire Protection Engineering, 3 rd Edition (P.J. DiNenno, Editor-inChief), National Fire Protection Association and The Society of Fire Protection

Engineers, Quincy, MA, 2002.

7. Beyler, C., "Fire Plumes and Ceiling Jets," Fire Safety Journal, Vol. 11, pp 53-75,

1986.

8. Alpert, R., Section 2-2, "Ceiling Jet Flows," 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.

9. Thomas, P., and D. Walton, Section 3-6, "Estimating Temperatures in Compartment

Fires," SFPE Handbook of Fire Protection Engineering, 3 rd Edition (P.J. DiNenno,

Editor-in-Chief), National Fire Protection Association and The Society of Fire

Protection Engineers, Quincy, MA, 2002.

10. Cooper, L., "Fire Plume Generated Ceiling Jet Characteristics and Convective Heat

Transfer to Ceiling and Wall Surfaces in a Two-Layer Fire Environment: Uniform

Temperature, Ceiling and Walls," Fire Science & Technology, Vol. 13, No. 1 & No. 2,

pp. 1-17, 1993.

7-1

A

TECHNICAL DETAILS OF FIVE-REV1 VALIDATION

STUDY

This appendix provides technical basis for the relative difference values listed in Chapter

6 of this volume. This appendix is organized into sections for the parameters that have

been verified and validated in this study. Not all of the models in the FIVE-Rev 1 library

have been subjected to verification and validation (V&V) because of a lack of

experimental data or model applicability. 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 list the values

selected as model inputs. 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 3. This appendix is organized into the following sections:

A. 1 Hot Gas Layer Temperature

A.2 Ceiling Jet Temperature

A.3 Plume Temperature

A.4 Flame Height

A.5 Radiant Heat Flux

Volume 2 includes detailed discussion of the uncertainties associated with both the

experimental data and model predictions presented in this appendix.

The model predictions are compared to the experimental measurements in terms of the

relative difference between the maximum (or where appropriate, minimum) values of

each time history:

AM-AE (M, -Mo)-(EP -Eo)

AE E .

AM is the difference between the peak value of the model prediction, Mp, and its original

value, Mo. AE is the difference between the experimental measurement, Ep, and its

original value, Eo. A positive value of the relative difference indicates that the model has

over-predicted; for example, a higher temperature, lower oxygen concentration, higher

smoke concentration, etc.

Finally, all of the calculations performed in the evaluation were open; that is, the heat

release rate of the fire was a specified model input, and the results of the experiments were

provided to the analysts.

A-1
Technical Details of FIVE-Revl Validation Study

A.1 Hot Gas Layer Temperature

Relative differences for hot gas layer (HGL) temperature were calculated using

experimental data from ICFMP Benchmark Exercises (BE) #3, #4, and #5; the FM/SNL

test series; and the NBS multi-compartment fire test series. In the case of HGL

temperature, positive relative differences indicate that the temperature predictions are

higher than the experimental observations.

As described in Chapter 3, the HGL temperature in the FIVE-RevI library can be

calculated using the FPA model for closed mechanically ventilated rooms or the MQH

model for naturally ventilated enclosures.

A. 1.1 ICFMP BE #3

BE #3 consists of 15 liquid spray fire tests with different heat release rate, pan locations,

and ventilation conditions. Gas temperatures were measured using seven floor-to-ceiling

thermocouple arrays (or "trees") distributed throughout the compartment. The average

HGL temperature was calculated using thermocouple Trees 1, 2, 3, 5, 6, and 7. Tree 4

was not used because one of its thermocouples (4-9) malfunctioned during most of the

experiments.

It is important to indicate also that the HGL reduction method produces spurious results

in the first few minutes of each test because no clear layer has yet formed.

The comparison between MQH/FPA predictions and measured HGL temperatures are

compiled in Figure A-I through Figure A-2. Notice that comparisons are only available

for tests with opened doors with or without mechanical ventilation, and closed doors with

mechanical ventilation. The temperature for the former group was calculated using the

MQH model. The temperature for the later group was calculated using the FPA model.

No comparisons are provided for tests with closed doors and no mechanical ventilation

because the FIVE-Rev1 library does not include a model for such conditions. The inputs

for the MQH and FPA models are listed in Table A- 1. The HRR profiles are identical to

those used in the MAGIC simulations, and are described in Volume 2 of this report.

A-2
Technical Details of FIVE-Revl Validation Study

Table A-I: Inputs to the MQH and FPA Models in ICFMP BE #3

Ambient temp [°C] 22

Room Size

Room length [m] 21.7

Room width [m] 7.04

Room height [m] 3.82

Nall Properties

Nall k [kW/m-K] 0.00013

Nall Cp [kJ/Kg-K] 1.17

Nall p [kg/m3 ] 737

Thickness [m] 0.025

Nat & Mech Vent

Opening height Ho [m] 2

Opening area Ao [m2] 4

3FM 1907

A-3
Technical Details of FIVE-Revi Validation Study

No plot for BE #3, Test 1. This is a closed

door test with no mechanical ventilation.

No plot for BE #3, Test 2. This is a closed

door test with no mechanical ventilation.

No plot for BE #3, Test 7. This is a closed

door test with no mechanical ventilation.

No plot for BE #3, Test 8. This is a closed

door test with no mechanical ventilation.

350

300 -

Hot Gas Layer Terrperature

CRvP BE#3, Test 10

E

IE

I200-

150

50 _ -FPu -TLupper -

0 2 4 6

T11g (run)

8 10 12 0 2 4 6 8 10 12

Trn (rnin)

No plot for BE #3, Test 13. This is a

closed door test with no mechanical

ventilation. E

0 1 2 3 4 5 6

Tae (rin)

Figure A-I: Hot Gas Layer (HGL) Temperature, ICFMP BE #3, Closed Door Tests

with Mechanical Ventilation

A-4
Technical Details of FIVE-Revl Validation Study

No plot for BE #3, Test 17. This is a closed Open Door Tests

door test with no mechanical ventilation.

350 1 bt Gas Layer Temp~erature

300 ICFM WBE#3, Test 3

E

100 /I

= 200

150 E

100

50

4

50- -.- L.pr

0 5 10 15 20 25

TUrn (rrin)

0 5 10

Tare (nin)

15 20 25

E

I350 Hot Gas Layer Temrperature [-----

300 CRA' BE #3, Test14

15O

E

50 -- T~upper - MQ

0

0 5 10

Toae (rain)

15 20 25 0 5 10

T e(r)

15 20 25

350

300

250

S200

a150 E

100

350

300

250

200

a 150

E

0 5 10 15 20 25

T"na (nin)

0 5 10 15 20 25

Tare (rrin)

Figure A-2: Hot Gas Layer Temperature ICFMP BE #3, Open Door Tests

A-5
Technical Details of FIVE-Rev] Validation Study

Table A-2: Relative Differences for HGL Temperature in ICFMP BE #3

Hot Gas Layer Temrerature

Relative

Test AE (-C) AM (*C) Difference

ICFMP 3-1 N/A'

ICFMP 3-7 N/A1

ICFMP 3-2 N/A1

ICFMP 3-8 N/A'

ICFMP 3-4 204.3 295.5 45%

ICFMP 3-10 197.8 293.8 49%

ICFMP 3-13 N/A'

ICFMP 3-16 268.4 359.8 34%

ICFMP 3-17 N/A1

ICFMP 3-3 207.3 309.2 49%

ICFMP 3-9 204.0 306.1 50%

ICFMP 3-5 175.5 309.2 76%

ICFMP 3-14 208.2 307.6 48%

ICFMP 3-15 210.6 307.6 46%

ICFMP 3-18 193.4 307.6 59%

1. No relative differences calculated for closed-door rooms with

no mechanical ventilation. There is no model applicable to this

case in the FIVE-Rev1 library.

A-6
Technical Details of FIVE-Rev] Validation Study

A. 1.2 ICFMP BE #4

ICFMP BE #4 consisted of two experiments, of which one (Test 1) was chosen for

validation. Compared to the other experiments, this fire was relatively large in a relatively

small compartment. Thus, its HGL temperature is considerably higher than the other fire

tests under study. The HGL temperature was calculated using the MQH model. Table

A-3 lists the input parameters. The HRR profile is presented in Figure A-3.

Table A-3: Inputs to the MQH Model in ICFMP BE #4

Ambient temp [°C] 20

Heat Release Rate Rofile

Room Size IOFVPBE#4: Test 1

Room length [Im] 3.6 4.0

Room width [m] 3.6 3.5

Room height [m] 5.7 3.0o

Wall Properties t• 202.0

Wall k [kW/m-K] 0.00075 -r 1.5 - _ _

Wall Cp [kJ/Kg-K] 0.84

Wall p [kg/m 3

] 1500 1.0-

Thickness [ml 0.025 0.5 -

0.0 1, i

Nat & Mech Vent 0 5 10 15 20 25

Opening height Ho [m] 3.6 irme [rrin]

Opening area Ao [M 2] 2.1

Figure A-3: Heat Release Rate for ICFMP BE #4

A-7
Technical Details of FIVE-Revl Validation Study

Figure A-4 includes the comparison between experimental and predicted HGL

temperatures. The relative differences calculated for this experiment are listed in Table

A-4:.

80o

700 iHot Gas Layer Terrperature

I-I 400 "r,

300

0 5 10 15 20 25

Twre (min)

Figure A-4: Hot Gas Layer Temperature, ICFMP BE #4, Test 1

Table A-4: Relative Differences for Hot Gas Layer Temperature in ICFMP BE #4

Hot Gas Layer Temperature

Relative

Test AE (°C) AM (-C) Difference

ICFMP 4-1 700.1 589.0 -16%

A-8
Technical Details of FIVE-Revl Validation Study

A. 1.3 ICFMP BE #5

BE #5 was performed in the same fire test facility as BE #4. Only one of the experiments

(Test 4) from this test series was used in the evaluation, and only the first 20 minutes of

the test, during the "pre-heating" stage when only the ethanol pool fire was active. The

burner was lit after that point, and the cables began to burn. Figure A-5 presents the

HRR profile measured during the test. The inputs for the MQH equation are listed in

Table A-5:.

Table A-5: Inputs to the MQH Model in ICMFP BE #5

Ambient temp [°C] 20

Heat Release Rate PRofile

Room Size lFM BE # 5, Test 4

Room length [m] 3.6 40

Room width [m] 3.6 350

Room height [m] 5.7 3oo

250

Wall Properties 20

Wall k [kW/m-K] 0.00075 150

Wall Cp [kJ/Kg-K] 0.84 100o ... .... _....

Wall p [kg/m 3

] 1500 50

Thickness [m] 0.025 o .-

0 5 10 15 20

Nat & Mech Vent Time [nTn]

Opening height Ho [m] 2.2

Opening area Ao [m2] 1.54

Figure A-5: Heat Release Rate Profile for ICFMP BE #5

Figure A-6 summarizes the comparison between the experimental and predicted hot gas

layer and height during the first 20 minutes of the simulation. The corresponding relative

differences are listed in Table A-6:.

200

218 Hbt Gas Layer Tenperature BE 5, Test 4

o 140

120

- 60

40 M-O-H -T-Tup

0

a 5 10 15 20

Twns (rin)

Figure A-6: Hot Gas Layer Temperature, ICFMP BE #5, Test 4

A-9
Technical Details of FIVE-Revl Validation Study

Table A-6: Relative Differences for Hot Gas Layer Temperature in ICFMP BE #5

Hot Gas Layer Temperature

Relative

Test AE (°C) AM (°C) Difference

ICFMP 5-4 150.3 136.0 -10%

A. 1.4 FM/SNL Test Series

Tests 4, 5, and 21 from the FM-SNL test series were selected for comparison. Hot gas

layer temperatures were calculated using the FPA model. Figure A-7 and Table A-7:

provide the input parameters for the FPA model. The experimental HGL temperature and

height were calculated using the standard method. The thermocouple arrays that are

referred to as Sectors 1, 2, and 3 were averaged (with an equal weighting for each) for

Tests 4 and 5. For Test 21, only Sectors 1 and 3 were used, as Sector 2 fell within the

smoke plume.

Table A-7: Input Parameters for the FPA Model in FMISNL Tests

Test 5 Tests 4 & 21

Ambient temp [°C] 20 20

Room Size

Room length [ml 18.3 18.3

Room width [m] 12.2 12.2

Room height [m] 6.1 6.1

Wall Properties

Wall k [kW/m-K] 0.00012 0.00012

Wall Cp [kJ/Kg-K] 1.25 1.25

Wall p [kg/m31 720 720

Thickness [m] 0.0125 0.0125

Mech Vent

CFM 8000 800

I

A-10
Technical Details of FIVE-Revl Validation Study

Heat Release Rate Profile

600

500

400

- 300

200

100

0

0 2 4 6 8 10

Time [rrin]

Figure A-7: Heat Release Rate Profiles for the Selected FMISNL Tests

Figure A-8 summarizes the graphical comparison of HGL temperatures and heights for

Tests 4, 5, and 21. The relative differences are included in Table A-8:.

EE

200

150

100

50

0

W Gas Layer Terrperature

FWSNL. Test 4

-FPA .-- Tpper

E

I0 5 10 15

Tura (mrin)

5 10 15

Twre (nin)

5 10 15 20

Tirme (rin)

Figure A-8: Hot Gas Layer Temperature, FMISNL Test Series

A-1I
Technical Details of FIVE-Revl Validation Study

Table A-8: Relative Differences for Hot Gas Layer Temperature in the FM/SNL

Tests

Hot Gas Layer Temperature

Relative

rest AE (°C) AM (°C) Difference

FM/SNL 4 59.2 171.5 190%

LFM/SNL 5 46.6 74.9 61%

IFM/SNL 21 66.0 171.5 160%

A.1.5 The NBS Multi-Room Test Series

This series of experiments consisted of two relatively small rooms connected by a long

corridor. The fire was located in one of the rooms. Eight vertical arrays of

thermocouples were positioned throughout the test space (one in the bum room, one near

the door of the bum room, three in the corridor, one in the exit to the outside at the far

end of the corridor, one near the door of the other or "target" room, and one inside the

target room). Four of the eight arrays were selected for comparison with model

prediction (the array in the bum room, the array in the middle of the corridor, the array at

the far end of the corridor, and the array in the target room). In Tests 100A and 1000,

the target room was closed, in which case, the array in the exit doorway was used.

The standard reduction method was not used to compute the experimental HGL

temperature for this test series. Rather, the test director reduced the layer information

individually for the eight thermocouple arrays using an alternative method.

This evaluation was limited to the room of fire origin only. The MQH model was

selected for the evaluation because the room has an open door and no mechanical

ventilation. Table A-9 lists the input parameters for the MQH model.

A-12
Technical Details of FIVE-Revl Validation Study

Table A-9: Input Parameters for the MQH Model in the NBS Tests

Ambient temp [°C] 20

Room Size

Room length [m] 2.3

Room width [m] 2.3

Room height [m] 2.16

Wall Properties

Wall k [kW/m-K] 0.00009

Wall Cp [kJ/Kg-KI 128

Wall p [kg/m 31 1.04

Thickness [m] 0.05

Nat & Mech Vent

Opening height Ho [m] 1.6

Opening area Ao [M2

] 1.28

Fire

HRR [kW] -- Constant 110

Figure A-9 compiles the graphical comparison between experimental measurements and

modeling results for HGL temperature for the three selected experiments. The

corresponding relative differences are listed in Table A-10:.

A-13
Technical Details of FIVE-Revl Validation Study

400 WU- ot Gas Layer Tenp. Bum Room

4MS, M1000_2

&

B

IU

B

300

100

a

0 5 10 15 20

The (ntn)

10 15 20

To(rrmn)

C.,

0.

E

C, I0 5 10 15 20

Time (min)

Figure A-9: Hot Gas Layer Temperature in the NBS Multi-Room Test 100A

Table A-10: Relative Differences for Hot Gas Layer Temperature in the NBS Tests

Hot Gas Layer Temperature

Relative

AE ( Difference 9CI AM (°CI

NBS A Bum Room 248 282 14%

NBS 0 Burn Room 310 282 -9%

NBS Z Burn Room 284 282 -1%

A-14
Technical Details of FIVE-Rev] Validation Study

A.2 Ceiling Jet Temperature

The FIVE-Rev I library includes the Alpert correlation for ceiling jet temperature.

Experimental measurements for the ceiling jet are available from ICFMP BE #3 and the

FM/SNL series only.

Positive relative differences are an indication that the model prediction is higher than the

experimental observation.

The ceiling jet temperature correlation was developed using experimental data collected

from controlled environments with no HGL effects. If such correlations are used to

analyze fire scenarios involving a hot gas layer, a correction is recommended to account

for the thermal effects of the hot gas layer on the ceiling jet temperature. In the case of

the ceiling jet, HGL effects may not be important (1) in the early phases of the fire event,

when a hot gas layer has not been established, and (2) in relatively large rooms with

relatively small fires, where the HGL temperature is close to ambient.

In the first version of FIVE, the HGL effects were included in the analysis by adding

(superimposing) the calculated temperature rise in the ceiling jet to the HGL temperature.

In some cases, this simplification produces over-predictions in the ceiling jet temperature.

The equation is TpHGL = THGL + AT,= THGL + Tp -Tamb.

This section presents both comparisons (with and without considerations for the HGL

effects).

A.2.1 ICFMP BE #3

The thermocouple nearest the ceiling in Tree 7, located toward the back of the

compartment, was chosen as a surrogate for the ceiling jet temperature. The 15 graphical

comparisons of experimental measurements and model results are grouped in Figure

A-10 and Figure A-11. The corresponding relative differences are listed in Table A-12.

Table A-1 1: lists specific location parameters required for the ceiling jet temperature

correlation. The HRR values are listed in Volume 2.

Table A-11: Target Location Information for Ceiling Jet Correlation

Ceiling Jet

Target height [m] 3.5

Fire elevation [m] 0

Instrument All Others Test 14 Test 15 Test 18

Radial dist [ml 5.9 6.1 6.3 4.8

A-15
Technical Details of FIVE-Rev] Validation Study

200

0

4,

o 120 j100

60

40

5 10 15 20 25

Tim (nin)

0 5 10 15 20 25 30

Trne (ran)

350 300

2501

ISO

100-

50

S

I0 2 4 6 8 10 12

Toe (rnin)

0 2 4 6 8 10 12

Tirne (rin)

3WO

~250]

150 L

50

0

U5

Tirn (rnin)

10 15 0 10 15

Tene (,tun)

500- Ceding Jet Ternperature -~- Tree 7-10 CiigJtTe

3 B eWBE#3, Test 161

30Te7-0400. A~rC,-

250---- 30

200 210 -

150'200

150

0 ..........-... -

0 2 4 6 8 10 12 0 2 4 6

hnm (nin) Twre (rnn)

Figure A-10: Near-Ceiling (Ceiling Jet) Temperatures, ICFMP BE #3, Closed Door

Tests

A-16
Technical Details of FIVE-Revl Validation Study

250

Cefling Jet Temperature

CFW BE#3, Test 17

200

-.Tree 7-10

S150-AprC

100

50

0

0 2 4 6 8 10 12

Tsre (rrn)

40040Ceilrng Jet Temperature ."--"-

350 KtFPO BE#3, Test3 3,- --

300 ,

20 ----.- Tres 7-10

100 . ....... WL + Alpert

50

0-

0 5 10 15 20 25

Tire (rin)

Open Door Tests

C)

I

400

3501

300-

250-

200-

150-

100-

50

0 5 10

Tire (in)

15 20 25

400

ceiflig Jet Temperature

350 -MPBE#3,Test14

300

250 .M ftp-f

300

250

W200

150

11

w - .7- 1 -Tree 7-10 150 - Alpert CJ

100 ... T-GL. A lpert_ j-.t

50-

0 --

0 5 10 15 20 25

Tirre (nin) 0 5 10 15 20 25 30 Tirne (nin)

250

0 200 - - Tree 7-10 i -Tree 7-10

• 150 - Alert W Alpert CJ -

100 -..... H -+Alpert , 100 THG-. + ert lp -- ...

s ____ ____,__-___ , 50. " :"_.

50 5

;r 0 -- , ...........

0 5 10 15 20 25 0 5 10 15 20 25 30

Tre (rin) Tinre (rin)

Figure A-11: Near-Ceiling (Ceiling Jet) Temperatures, ICFMP BE #3, Closed Door

Tests

A-17
Technical Details of FIVE-Revl Validation Study

Table A-12: Relative Differences for Ceiling Jet Temperature in ICFMP BE #3

No Hot Gas Layer Effects Hot Gas Layer Effects

Relative Relative

AE (-C) AM (-C) Difference AE (°C) AM (°C) Difference

ICFMP 3-1 Tree 7-10 154.9 23.3 -85%

ICFMP 3-7 Tree 7-10 139.3 23.3 -83%

ICFMP 3-2 Tree 7-10 270.6 47.0 -83%

ICFMP 3-8 Tree 7-10 246.9 47.0 -81%

ICFMP 3-4 Tree 7-10 228.9 47.4 -79% 228.9 342.8 50%

ICFMP 3-10 Tree 7-10 217.5 47.0 -78% 217.5 340.9 57%

ICFMP 3-13 Tree 7-10 330.5 73.4 -78%

ICFMP 3-16 Tree 7-10 277.7 72.7 -74% 277.7 432.6 56%

ICFMP 3-17 Tree 7-10 155.9 46.3 -70%

ICFMP 3-3 Tree 7-10 240.7 47.0 -80% 240.7 356.2 48%

ICFMP 3-9 Tree 7-10 234.6 46.6 -80% 234.6 352.6 50%

ICFMP 3-5 Tree 7-10 207.7 47.0 -77% 207.7 356.2 71%

ICFMP 3-14 Tree 7-10 240.8 46.8 -81% 240.8 354.4 47%

ICFMP 3-15 Tree 7-10 243.7 46.8 -81% 243.7 354.4 45%

ICFMP 3-18 Tree 7-10 235.1 46.8 -80% 235.1 354.4 51%

A-18
Technical Details of FIVE-Revl Validation Study

A.2.2 The FMISNL Test Series

The near-ceiling thermocouples in Sectors 1 and 3 were chosen as surrogates for the

ceiling jet temperature. The results are shown below. Table A-13: lists specific location

parameters required for the ceiling jet temperature correlation. The HRR values are listed

in Volume 2. Figure A-12 compiles the graphical comparisons between experimental

measurements for ceiling jet temperature and the correlation predictions. The

corresponding relative differences are listed in Table A-14:.

Table A-13: Target Location Information for Ceiling Jet Correlation

Ceiling Jet

Target height [m] 5.9

Fire elevation [m] 0

Instrument X Y Z

Fire 12.0 6.1 0.3 Radial dist [m]

3-98 3.04 2.032 5.97 9.8

1-98 15.24 6.09 5.97 7.1

A-19
Technical Details of FIVE-RevI Validation Study

C-)

E

I200 ... ..... .

150 • _" 1/(0.98 I

.: ....... Alpert+÷

0 2 4 6 8 .10 12

Tme (nin)

C,

E

250-

200-

150

100

50

0 2 4 6

Trrm (rrin)

8 10 12

Ceing Jet Termp

FIVSNL. Test 4 - Sector 3

I - Alpert

- 11/1(0.98 H) .I.. Alper + HGUL

120

100

80

Ceing Jet Tem. .

FMWSNL Test 5 - Sector 3

E

C-)

40

20

0

....... Alpert +

0 2 4 6 8 10 12

Tim (rrin)

0 2 4 6 8

Tom (rrn)

10 12

250 ing Jet Terrp

I FMSNL Test 21 - Sector 3

I- : ....................

P 150 -

Alpert

.....----.11/(0.98 H) : ...... Alpert + HGL

250

Ceing Jet Temp

FMSNL, Test 21- Sector 1

200 ................

______ Alpert

150 -a- 1/(0.98 H)

....... Alpert + HGL

U

loo C0 5 10 15 20 25 0 5 10 15 20

Tam (nt) TOm (nin)

Figure A-12: Near-Ceiling (Ceiling Jet) Temperatures, FM/SNL Series, Sections 1 &

3

A-20

25
Technical Details of FIVE-Rev] Validation Study

Table A-14: Relative Differences for Ceiling Jet Temperature in FM/SNL Tests

No Hot Gas Layer Effects Hot Gas Layer Effects

Relative Relative

AE (7C) AM (°C) Difference AE (°C) AM (°C) Difference

FM/SNL4 1/98H 82.8 11.8 -86% 82.8 183.3 121%

11/98H 66.1 14.7 -78% 66.1 186.2 182%

FMISNL 5 1/98H 73.7 11.8 -84% 73.7 86.7 18%

11/98H 52.6 14.7 -72% 52.6 89.5 70%

FM/SNL21 1/98H 75.9 11.8 -84% 75.9 86.7 14%

11198H 77.2 14.7 -81% 77.2 89.5 16%

A.3 Plume Temperature

Plume temperature measurements are available from ICFMP BE #2 and the FM/SNL

series. For all other series of experiments, the temperature was not measured above the

fire, the fire plume leaned because of the flow pattern within the compartment, or the fire

was set up against a wall. The plumes relatively free from perturbations only for BE #2

and the FM/SNL series.

The McCaffrey and Heskestad plume temperature correlations are considered in this

evaluation.

The plume temperature correlations were developed using experimental data collected

from controlled environments with no HGL effects. If such correlations are used for

analyzing fire scenarios involving a hot gas layer, a correction is recommended to

account for the thermal effects of the hot gas layer on the ceiling jet temperature. In the

case of the plume, HGL effects may not be important (1) in the early phases of the fire

event, when a hot gas layer has not been established, and (2) in relatively large rooms

with relatively small fires, where the HGL temperature is close to ambient.

In the first version of FIVE, the HGL effects were included in the analysis by adding

(superimposing) the calculated temperature rise in the ceiling jet to the HGL temperature.

In some cases, this simplification produces over-predictions in the ceiling jet temperature. The equation is TpHGL =THGL + ATp =THGL +Tp - Tamb

This section presents both comparisons (with and without considerations for the HGL

effects). The HGL temperature added to the ceiling jet was previously reported in

Section A. 1.

A.3.1 ICFMP BE #2

BE #2 consisted of liquid fuel pan fires conducted in the middle of a large fire test hall.

Plume temperatures were measured at two heights above the fire [6 m and 12 m (19.7 ft

and 39.4 ft)]. The flames extended to about 4 m (13.1 ft) above the fire pan (Figure

A-21
Technical Details of F1VE-Revl Validation Study

A-13). The suspended rectangle contains an array of thermocouples designed to locate the

plume centerline. Notice that the smoke plume does not always rise straight up because of

air currents within the large test hall.

Figure A-13: Fire Plumes in ICFMP BE #2,

Courtesy of Simo Hostikka, VTT Building and Transport, Espoo, Finland

Table A- 15: lists specific location parameters required for the plume temperature

correlation. The HRR values are listed in Volume 2. Figures A-14 and A-15 compile the

graphical comparisons between experimental measurements for plume temperature and

the correlation predictions. The corresponding relative differences are listed in Table

A-16: between experimental plume temperatures and model prediction for the three cases

in ICFMP BE #2. The corresponding relative differences are listed in Table A-16:.

Table A-15: Target Location Information for Plume Correlation

Plume TG.1 TG.2

Target height [m] 6 12

Fire elevation [m] 0

Fire diameter [m] 1.6

Rad fraction, Xr 0.4

A-22
Technical Details of FIVE-Revi Validation Study

I.. PRurmDTerm -I esestad

25 ~BE 2. Case I Haskestad

0 Tal

a 200 -

150 E

I--

00

0 2 4

Tom(nin) 6 8 10

Twm (nmn) 8

300

E

0 2 4 Tffrq (rd)

Figure A-14: Near-Ceiling Gas Temperatures, ICFMP BE #2, Sections 1 & 3

Compared with Heskestad's Plume Temperature Correlation

A-23
Technical Details of FIVE-Rev] Validation Study

2.

0

I

E

I2.

2 4 6 Twmo (nim)

10 0 2 4 Turn (rifm)

6 8

E

350

3W0

250

200

150

100

50

- BE2,, Cc3Hsksa Ru* TT73 o TGA

1.

0 1 2 3 4 TuT (mnl) 5 6

Figure A-15: Near-Ceiling Gas Temperatures, ICFMP BE #2 Series,

Sectors 1& 3 Compared with McCaffrey Plume Temperature Correlation

Table A-16: Relative Differences for Plume Temperature, ICFMP BE #2

Relative

_ __ AE (-C) AM (°C) Difference

TG.1 McCaffrey 166.0 163.2 2%,

ase 1 G.2 McCaffrey 79.0 51.7 ý35 /o.' rG.1 Heskestad 166.0 132.6 -2'%

rG.2 Heskestad 79.0 41.7 -. 047%

TG. 1 McCaffrey 288.0 237.1 -18%

Case 2 aG.2 McCaffrey 128.0 75.0 :.•41 ,'0-

G.1 Heskestad 288.0 218.0 -24%

rG.2 Heskestad 128.0 64.3 -50%

G.1 McCaffrey 252.0 254.9 A%

aG.2 McCaffrey 128.0 80.6 -37%

G.1 Heskestad 252.0 241.1 -4%

FG.2 Heskestad 128.0 70.1 -45%

A-24
Technical Details of FIVE-Revi Validation Study

A.3.2 The FMISNL Test Series

In Tests 4 and 5, thermocouples were positioned near the ceiling directly [5.9 m (19.4 ft)]

over the fire pan. In Test 21, the fire pan was inside a cabinet. For that reason, no plume

temperature comparison was made. Figure A-16 presents the graphical comparisons, and

Table A- 18: lists the corresponding relative differences. Target location inputs are listed

in Table A-17:.

Table A-17: Target Location Information for Plume Correlations

Plume TG.1

Target height [m] 5.9

Fire elevation [ml 0

Fire diameter [m] 0.8

Xr 0.4

A-25
Technical Details of FIVE-Rev] Validation Study

C.,

0

I.-

300•1-- -re-_ i FWSNL Test 4

2 5 0 .

200D "C affrey

28/(0.98 H)

.. tCaffry + H-L 150

50 ~.

0 5 10 15

Tom (nin)

300

250

200

0 150

. 100

50

0

Rume Terrp

FMNSNL, Test 4

- 28(0.98 H)

Fieskestad+ Ha3

0 5 10 15

Tam (rio)

180

E

C20 -120

004 -100

80 8-

601 ___6

40 ll-- t~affrey 4

o28o(0.98 H) 2 M

20 -C affrey 20 _eskestad+ I

010

0 2 4 6 8 10 0 2 4 6 8

Twm (nim) Tirm (rran)

Figure A-16: Near-Plume Temperatures, FMISNL Series, Sector 13

Table A-18: Relative Differences for Plume Temperature in FMISNL Tests

10

No Hot Gas Layer Effects Hot Gas Layer Effects

Relative Relative

AE (°C) AM (°C) Difference AE (°C) AM (°C) Difference

Test 4 McCaffrey 28/98H 115.8 70.7 -39% 115.8 242.2 109%

Heskestad 28/98H 115.8 59.6 -49% 115.8 231.1 100%

Test 5 McCaffrey 28/98H 93.8 70.7 -25% 93.8 145.5 55%

Heskestad 28/98H 93.8 59.6 -36% 93.8 134.5 43%

A.4 Flame Height

Flame height is recorded by visual observations, photographs, or video footage. Videos

from the ICFMP BE #3 test series and photographs from BE #2 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.

A-26
Technical Details of FIVE-Revl Validation Study

A.4.1 ICFMP BE #2

Shown in Figure A-17 are Heskestad's correlation predictions for flame height. Figure

A- 18 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 m to 4.8 m

(12.5 ft to 15. 8 ft)]. The height of the simulated fire fluctuates from 5 m to 6 m (16.4 to

19.7 ft) during the peak HRR phase.

M

I:

4 6

TgM (rrin) 0 2 4

lmTire(in)

6 8

5.0

Rarm H-eight

4.5- BE 2, Case 3

3.5 _____

3.0

2.5

2.0

1.5 - -

5.

0 2 4

TOr (rin)

Figure A-17: Flame Heights for ICFMP BE #2

A-27
Technical Details of FIVE-Rev] Validation Study

Figure A-18: Photographs of Heptane Pan Fires, ICFMP BE #2, Case 2,

Courtesy of Simo Hostikka, VTT Building And Transport, Espoo, Finland

A-28
Technical Details of FIVE-Rev) Validation Study

A.4.2 ICFMP BE #3

No measurements were made of the flame height during BE #3, but numerous

photographs were taken. Figure A-19 is one of these photographs. These photographs

provide at least a qualitative assessment of the Heskestad flame height prediction. Recall

that the size of the door is 2.0 m (6.6 ft) high. Inspection of the picture suggests that the

flame height, at least is some of its oscillations, can be more than 2.0 m (6.6 ft) high.

Figure A-19: Photographs of ICFMP BE #3, Test 3, as seen through the 2 m by 2 m

Doorway, Courtesy of Francisco Joglar, SAIC

A-29
Technical Details of FIVE-Revl Validation Study

1.2

1.0

0.8

0.6

0.4

0.2

0.0

I

0 5 10 15 20 25 30

Tirn (ni') 0 5 10 15 20 25 30

Tire (rin)

3.0 3.0

1.5

1.0

0.5

0.0

3.0

2.5

2.0

S1.5

1.5

0 2 4 6

The (rmn)

8 10 12 0 2 4 6 8 10 12

Tiff (nin)

2.5

2.0

1.5

I 1.0

0.5

0.0

0 5 10 15 10 15

Twm (min) Trne (rmn)

4.0

3.5

3.0

? 2.5

Z 2.0

1.5

1.0

0.5

0.0

4.0

3.5

3.0

2.5

2.0

0 2 4 6 8 0 2 4 6

Th"n (min) Tuný (rrm)

Figure A-20: Near-Ceiling Gas Temperatures, ICFMP BE #3, Closed Door Tests

A-30
Technical Details of FIVE-Rev] Validation Study

Open Door Tests

E" 1-5

Z 1.0

0.5

0.0

2.5 2.5

I.5

1.5

I 1.0

0 5 10 15 20 25 30

Thu (rrin)

0 5 10 15 20 25 30

Thn (rnin)

2.5 T

2.0

Rarre f-bght

15 CFPBE#3, Test 14

1.5

1.04

0.5-

0.0-

I

0 5 10 15 20 25 30 0

Tame (nfi)

5 10 15 20 25 30

Tne (rndn)

2.5

2.0

1.5

I 1.0

0.5

0.0

M. 1.0

0.5

0.0

0 5 10 15 20 25 30 0 5 10 15 20 25 30

T-re (nin) Thre (inn)

Figure A-21: Flame Heights, ICFMP BE #3, Open Door Tests

A-31
Technical Details of FIVE-Rev] Validation Study

A.5 Radiant Heat Flux

Radiant heat flux data are available only from ICFMP BE #3. These data are compared

with results from the point-source radiant heat flux model available in the FIVE-Revl

library of equations.

The four radiometers selected for this study are labeled Rad Gauges 1, 3, 7 and 10. Table

A-19 lists the effective distance from the gauges to the fire. A radiation fraction of 0.4

was assumed for the analysis. The HRR profiles for each of the tests are described in

Volume 7 of this report.

Table A-19: Effective Horizontal Distances from the Fire to the Rad Gauges

Instrument All Others Test 14 Test 15 Test 18

R Gauge 1 [m] 3.25 4.85 1.29 2.12

R Gauge 3 [ml 2.80 4.28 1.55 2.19

R Gauge 7 [m] 2.59 3.83 2.18 2.59

R Gauge 10 [ml 3.40 1.82 5.70 5.61

Instrument Ill Others Test 14 Test 15 Test 18

R Gauge 1 [ml 3.25 4.85 1.29 2.12

R Gauge 3 [m] 2.80 4.28 1.55 2.19

R Gauge 7 [ml R.59 P.83 .18 2.59

R Gauge 10 [m] 3.40 1.82 .70 5.61

Figures A-22 through A-29 provide the graphical comparisons between the point source

radiation predictions and the experimental measurements. When available, the

corresponding measured total heat flux was also included in the comparison. Finally,

Table A-20 lists the calculated relative differences for this comparison.

A-32
Technical Details of FIVE-Revl Validation Study

3.0 2.5

Cable Rod Gauge 3

2.5 - Point Source

2.0 - -Cable Total lux 4

1.0

0.5 Target B-TS-14 -lest Flux

Z .: #3, Test I

H

E

I

0.0

0 5 10 15 20 25 30

Tern (rren)

6.0 Target B-TS-14 Heat Flux

5.0ICFMP BE #3. Test 2

40 f

•Ktfl

6.0Tagt-T14FotFu

5.0 K FBE #3, Test 8

4.0

1=

3.0

2.0

1.0

-.- Cable modGag

Polint Source

-- Cable Total Flux4

T8 2.0

0.0 Cable Total Flux 4

0 2 4 6 8 10 12

Torn (min)

u.ur

0 2 4 6

Tirne (rrin)

8 10 12

3:

6.0

5.0

4.0

3.0

2.0

1.0

Target B-TS-14 Heat Flux

ICFM BE#3. Test4 4 ,..._ IA,

.p4~.4-nt Sourc~.

Target B-TS-14 Heat Rux

ICRV BE #3, Test 10

4.0

3.0

e 2.0

1.0

Ao

Cable Rod Gauge 3

Point Source

Cable Total Flux 4

0 2 4 6 B 10 12 14

Tune (Orn)

00v

0 2 4 6 8 10 12 14

Time (Win)

10.0

9.0

8.0

7.0

6.0

5.0

u- 4.0

3.0

2.0

1.0

0.0

ýI

9.0

8"0 Poi-" n'Soul R ad •• •• - "

7.0 -e--CableT tatRux4 4 IT-r 

5.0 f

Target 6-13-14 Heat Flux

CFP BE#3, Tes

0 2 4 6 8

Trne (rrur) 2 4 Tamn (min)

8

Figure A-22: Heat Fluxes to Cable B

A-33
Technical Details of FIVE-Revl Validation Study

5.0

4.5- Cable Rad G~augee

4.0 -Point Source

3.5 1jeGbeoa x4

I

2.51--

2.01

15s

Open Door Tests

1.0

0.5

0.0

Target B-TS-14 eat Flux

Test 17

0 1 2 3 4 5 6

Tm (ran)

60 Target B-TS-14 I-leat Flux

60 .. FWBE Q. Test 9

5.01-

I

6

I

ýI

4.

3.

2.

!0

0.

0 5 10 15

TOM (rrin)

20 25

0

.Cable ed Gauge 3

.0

- Point Source .0

Cable Total lux 4

.0

0 5 10 1 5 20 2

Tme (finn)

.0

.5 aglBT-1 -etFu

0j sl 4

r,

5

4.

3.

3.

E 2.

-1

0.5

C.-Cable Red Gauge 3

-Fint Source

-u--Cable Total Flux 4

0 5 10 15 20 25 30

T"m (nmn)

70.0

; Target B-TS-14 Heat Flux

6O. .L CFP BE#3, Test 15

50.0 L-r - Cable Pad Gauge 3 -- Point Source

0.0 . ....

0 5 10 15 20 25

Tim (rmn)

0.0 -1

0 5 10 15 20 25

Trn (*n•)

8.0

E

7.0

2.0

-Point Source

--Cable Total Flux 4

0.0

0 5 10

Tme (nn)

15 20 25

Figure A-23: Heat Fluxes to Cable B

A-34
Technical Details of FIVE-Revl Validation Study

2.5

2.0

• 1.5

S1.0

0.5

0.0

2.5

ii

E

0 5 10 15 Tiff (nin) 20 25 30 0 5 10 15 20 25 30

Tine (rin)

EIF

E

m

U0 2 4 6 mire (rin) 8 10 12 0 2 4 6

Tine (nin)

8 10 12

.=

6.0

5.0

4.0

Target D-TS-12 Heat Flux

CFMP BE #3, Test 4

- .j A.

E 4

"3

2

3.0 1

2.0.

-Cable Rad Gauge 7

-Point Source

0.0 1

0 5 10 15

Tins (sin) 5 10 15

Tone (nin)

N

E

2

UI

14.0

12.0

10.0

8.0

6.0

4.0

2.0

0.0

Target D-TS-12 Heat Rux •.IC'WP BE#3_,_T(et 13 -Cable Rad Gauge 7

-- Point Source

-u Cable Tota 

.2

0 4 6 8 10 12

Tine (rrin)

2 0 2 4

Twe (rnn)

8

Figure A-24: Heat Fluxes to Cable D

A-35
Technical Details of FIVE-Revl Validation Study

I

6.0

4 -0 L - Cable P~ a d Gau x -- ge 7- 5.0 PoFint Source L

4.0 x 6

Target D-TS-12- a ....

I CRP 85*3. Test 17

Door Open Tests

V..

0 1 2 3 4 5 6

Trne (n*)

Target D-TS-12 Heat Flux

lCFMPF BE#3, Test3

.2

10.0

9.0

8.0

7.0

6.0

5.0

4.0

3.0

2.0

1.0

Target D-TS-12 Heat Ruxs

8.0 I WBE#3, Test 9

N

- -_____ - nt Source

--Cable Total flu 61

E

401 [ If ____ __

O.UgIN

3.0

2.0

1.0 f-.-~--A- Cablebl Total Flux 6

0 5 10

Tiff (rin)

15 20 25

0.0

0 5 10 15 20 25

Tur (nin)

8.0

S~

I I

7.0

6.0

5.0-

4.0

3.0-

2.0

1.0

0.0

- Cable Rad Gauge 7

-- Point Source

x- Cable Total

r Target D.TS12 Heat PYux

K;WBE#3, Test 14

0 5 10 15 20 25 30

Tie (rnin)

0 5 10 15

Thu (rrn)

20 25

S

I

20.0

18.0

16.0

14.0

12.0

10.0

8.0

6.0

4.0

2.0

0.0

4.0

3.0

2.0

1.0

0.0

Targ .0 TS12 Heat 1 so #3 Tet18I

Point Source

-Cable Total Rux 61

0 5

Tare (nin)

10 15 20 25 0 5 10 15 Tirne (emn) 20 25

Figure A-25: Heat Fluxes to Cable D

A-36
Technical Details of FIVE-Rev] Validation Study

.2

2.5 r

I[-Cable Rod Gauge 1

2.0 - Point Source

1.5 ---- Cable Total Flux 2

1.05. .

0.5 "0rTarget P--20FtatFux

1CFM BE #3, Test

0 5 10 15 20 25 30

The (nin)

u.

0 5 10 15 20 25 30

Twe (nin)

EIF

.2

6.0

5.0

4.0

3.0

2.0

1.0

0.0

Target F-TS-20 Flat Flu

CRAP BE #3, Teat 2

I

0 2 4 6 8 10 12

Tim (rxn)

0 2 4 6 8 10 12

Trn (rnin)

6.0

5.0

" 4.0

3.0

2.0

-- Cable To FGauge 1 b.0

6

i

Cable Rad Gauge 1

5.0 - Point Source

4.0 Cablate Total Flux 2

3.0

2.0 If 4Ai // AW~7~%4 1.

0.0

Target F-TS-20 'eat Flux

ICFIPBE #3, Test 4

0 5 10 15

Tim (nin)

Target F-TS-20 Fleat Flux

0.0~ IFTPBE#3, Test 10

0 5 10 15

Time (nin)

Rt n

7.0.

6.0-

5.0 6

i1-

.2

E

I

4.0.

3.0

2.0

-.. Cable Fad Gauge Ti

I-~ra T- I. I

1.0

0.0

4

Time (rni) 60 2 4

Tnm (rnne)

Figure A-26: Heat Fluxes to Cable F

6 8

A-37
Technical Details of FIVE-Rev] Validation Study

I

3.5

3.0

2.5

Target F-TS-20 Heat Flux

JF B # E t Cable Read Gauge 1

Point Source

. Cable Total Flux 2

2.0 /It Open Door Tests

0.5

0.0

0 2 4

J

6 a

T, a(rin)

I I0 5 10

Tire (ram

15 20 25 0 5 10 15

Tuina (ruin)

20 25

8.0

S Cable Rd Gauge 1 7.0 TII[ - Point Source . I,.•.

6.0

40 al- eTotal

5.0 -r II

.2

3.5 -

3.0-

2.5-

2.0

1.5

1.0-

0.5-

Target F-TS-20 Heat Flux

ICFUP BE #3. Test 14

- lint Source

lChP BE #3, Test 5 I~...Cable Total flux 2

0.0

0 5 10 15 20 25 30

Turn (ruin)

.0

Target F-TS-20 Heat Flux

SIF PBEQ3, Test 15

0 5 10 15 20 25

Tune (ran)

30

I ~ -- tL~L~6~

U- I

20.0 - *m -W X.- - 0- V~

15. 0 -/ , . •_

10.0 ---- Cable FRad Gauge]

• oint Source

5.0 Cable Total Flux 2

0.0

0 5 10 15 20 25

Tire (nin)

9.0 Target F-TS-20 Heat Rux

8.0

jq 7.0

S6.0

U- 4.0

3.0 auge 1

2.0

1.0

-a- Cable Total Flux 2 0.0I

0 5 10 15 20 25

Tifn (,rin)

Figure A-27: Heat Fluxes to Cable F

A-38
Technical Details of FIVE-Revl Validation Study

2.0

1.8 Target TS-33 Hleat Flux

lCFMWBE#3, Test 1 16 q

Z.u

1. Target T-3 Hat na

1.6

E 1.4

1 2.

100' :I

1.4

1.2

0. 81

0.4 • •J - Cable Rad Gauge 10 I 0.2 S- ...... 

0.4 -.- Calej age1 0.2 - Poit Source

0.0

0 5 10 15 20 25 30

Tee (min) 0 5 10 15 20

Tire (rrin)

25 30

Fir

E ýI

E.

0 2 4 6 8 10 12 Ter (rmn)

7

.2

0 5 10 15 5 10 15

E

6T

12.0

10.0

8.0

6.0

4.0

Thnu (man)

Target TS-33 Heat Flux

-1-4 

1

-

j

Tom (rrin)

Cable Rad Gauge 10

Point Source

- -Cable Total Flue 9

.RLU,

2.0

0.0

0 2 4

Twre (rnn)

6 8 2 4 6 8

Tine (rin)

Figure A-28: Heat Fluxes to Cable G

A-39
Technical Details of FIVE-Revi Validation Study

4.0 Target TS-33 Heat Flux 3.5 CFMPBE#3,Test7 1

3.0

2.54

.2 2.0

1.5 V ý--- : ý

a 5 , , • P~

00o •J/I--*-Cable Total Aux 9

0 2 4 6 8

Tim (rfrt)

7.0

7 Target TS-33 Heat RFux

6.0 17PBE#3,Test3

Open Door Tests

7.0 Target TS-33 Heat Flux

6.0 1 -a--r•t 9

6

5:

,..- 9 i4 o.u

.• 4.0

3.0

I 2.0-

1.0

I- -

-- I

2.0-

1.0

---- Cable Rad Gauge 10

Point Source

-- x-- Cable Total Flux 9

f-a--C able Rod Gauge 10

fili ;7.l e T1atFl.

0o.- U U gK•.-

0 5 10 15 20 25

7Ti (rrdn)

0 5 10 15 20

Time (rrin)

25

6l

E:

.2

10

I

4.0

2.0

0.0-

8.0

6.0

4.0 )-a-Cable Rad Gauge 10

20 " lPoint Source

2.0 T : i --e•- Cabte TotatlFlux 9

Target TS-33 Heat Rux

lCFb BE #3, Test 14

0 5 10 15 20 25 30

"Time (nnr) 0 5 10

Tana (rnn)

15 20 25

"I"

5.0

4.5

4.0

3.5

3.0

2.5

2.0

1.5

1.0

0.5

0.0

Target TS-33 Heat Flux MP6BE #3. Test 15 X• * ---

E

U.

5.0

4.5

4.0

3.5

3.0-

2.5

2.0-

1.5-

1.0-

0.5.

Target TS-33 Heat Rux

ICFMP BE#3, Test 18

-- Calnt Source Fx

-a.- Cable Rod Gauge 10

- Point Source

-- -- Cable Total Flux 9 -

5 10 15 20 25

Tirn (run)

r U.U ]- 0 0 5 10 15 20 25

"rie (nin)

Figure A-29: Heat Fluxes to Cable G

A-40
Technical Details of FIVE-Revl Validation Study

Table A-20: Relative Differences for Radiative Heat Flux

AE AM Relative AE AM Relative

Gauge I (kW/m 2) (kW/m 2

) DifferenceGauge 3 (kW/m 2

) (kWm 2) Difference

Test 1 0.9 1.2 42% Test 1 1.1 1.7 48%

Test 7 0.8 1.2 50% Test 7 1.2 1.7 38%

Test 2 2.0 3.6 80% Test 2 2.9 4.8 68%

Test 8 1.9 3.6 85% Test 8 2.9 4.8 66%

Test 4 2.0 3.6 79% Test 4 2.9 4.9 68%

Test 10 2.7 3.5 29% Test 10 2.7 4.8 80%

Test 13 2.9 7.0 142% Test 13 4.8 9.5 99%

Test 16 2.8 6.9 151% Test 16 4.1 9.4 127%

Test 17 0.9 3.5 296% Test 17 1.3 4.7 263%

Test 3 3.0 3.6 21% Test 3 4.4 4.8 9%

Test 9 1.9 3.6 85% Test 9 4.3 4.8 11%

Test 5 2.6 3.6 35% Test 5 3.9 4.8 24%

Test 14 2.1 1.6 -25% Test 14 2.8 2.0 -28%

Test 15 18.3 22.5 23% Test 15 1.1 1.7 48%

Test 18 5.2 8.3 60% Test 18 5.2 7.8 49%

AE AM Relative AE AM Relative

Gauge 7 (kW/m 2 ) (kWlm 2) Difference Gauge 10 (kW/m 2) (kW/m2) Difference

Test 1 1.4 1.9 35% Test I 1.5 1.1 -26%

Test 7 1.3 1.9 44% Test 7 1.5 1.1 -23%

Test 2 4.2 5.6 36% Test 2 6.0 3.3 -45%

Test 8 3.6 5.6 59% Test 8 6.0 3.3 -46%

Test 4 3.3 5.7 75% Test 4 6.0 3.3 -45%

Test 10 2.9 5.6 94% Test 10 5.4 3.3 -40%

Test 13 6.6 11.1 68% Test 13 10.1 6.4 -36%

Test 16 4.8 10.9 126% Test 16 12.0 6.3 -47%

Test 17 1.5 5.5 263% Test 17 2.4 3.2 32%

Test 3 Test 3 5.4 3.3 -39%

Test 9 5.3 5.6 6% Test 9 5.2 3.2 -38%

Test 14 3.3 2.6 -23% Test 5 5.4 3.3 -40%

Test 5 4.8 5.6 18% Test 14 10.5 11.3 8%

Test 15 Test 15 3.7 1.2 -69%

Test 18 Test 18 2.8 1.2 -58%

A-41

NRC FORM 335 U.S. NUCLEAR REGULATORY COMMISSION 1. REPORT NUMBER

(9-2004) (Assigned by NRC, Add Vol., Supp., Rev.,

NRCMD 3.7 and Addendum Numbers, if any.)

BIBLIOGRAPHIC DATA SHEET

(See instructions on the reverse) NUREG-1824

2. TITLE AND SUBTITLE 3. DATE REPORT PUBLISHED

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

Volume 4: FIVE-REV.1

May 2007

4. FIN OR GRANT NUMBER

5. AUTHOR(S) 6. TYPE OF REPORT

F. Joglar (EPRI/SAIC) Technical

7. PERIOD COVERED (Inclusive Dates)

8. 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, DC 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

9. SPONSORING ORGANIZATION - NAME AND ADDRESS (ff NRC, type 'Same as above*,, if contractor, provide NRC Division, Office or Region, U.S. Nuclear Regulatory Commission,

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 commomly 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, CFAST, 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

NUREG-1824

EPRI 1011999

VERIFICATION AND VALIDATION OF SELECTED FIRE MODELS FOR

NUCLEAR POWER PLANT APPLICATIONS

Volume 4: Fire-Induced Vulnerability Evaluation (FIVE-Revl)

MAY 2007

UNITED STATES

NUCLEAR REGULATORY COMMISSION

WASHINGTON, DC 20555-0001

OFFICIAL BUSINESS