Nuclear Power Plant 

Fire Modeling Application 

Guide (NPP FIRE MAG)

Second Draft Report for Comment 

U.S. Nuclear Regulatory Commission Electric Power Research Institute 

Office of Nuclear Regulatory Research 3412 Hillview Avenue 

Washington, DC 20555-0001 Palo Alto, CA 94303 

 

NUREG-1934 EPRI 1023259 

 
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Nuclear Power Plant 

Fire Modeling Application Guide 

NUREG-1934 EPRI 1023259

Second Draft Report for Comment 

July 2011 

U.S. Nuclear Regulatory Commission Electric Power Research Institute (EPRI) 

Office of Nuclear Regulatory Research (RES) 3412 Hillview Avenue 

Washington, DC 20555-0001 Palo Alto, CA 94303 

U.S. NRC-RES Project Manager EPRI Project Manager 

M.H. Salley R. Wachowiak
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CITATIONS 

This report was prepared by: 

U.S. Nuclear Regulatory Commission, 

Office of Nuclear Regulatory Research (RES) 

Washington, DC 20555-0001 

Principal Investigator: 

D. Stroup 

Electric Power Research Institute (EPRI) 

3412 Hillview Avenue 

Palo Alto, CA 94303 

Principal Investigator: 

R. Wachowiak 

Science Applications International Corp (SAIC) 

1671 Dell Ave, Suite 100

Campbell, CA 95008

Principal Investigators: 

F. Joglar 

D. Birk 

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 

University of Maryland 

Principle Investigator: 

J. Milke 

Hughes Associates, Inc. 

Principal Investigator: 

S. Hunt 

Westinghouse 

Principal Investigator: 

C. Worrell 

ERIN Engineering 

Principal Investigator: 

K. Zee 

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

(NRC), Office of Nuclear Regulatory Research (RES) and the Electric Power Research Institute 

(EPRI). 

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

Nuclear Power Plant Fire Modeling Application Guide (NPP FIRE MAG), U.S. Nuclear 

Regulatory Commission, Office of Nuclear Regulatory Research (RES), Washington, DC, 2010 

and Electric Power Research Institute (EPRI), Palo Alto, CA, NUREG-1934 and EPRI 1023259.
iii 

ABSTRACT 

There is a movement to introduce risk-informed and performance-based (RI/PB) analyses into 

fire protection engineering practice, both domestically and worldwide. This movement exists in 

both the general fire protection and the nuclear power plant (NPP) fire protection communities. 

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

regulatory decision making since the 1990s. 

In 2001, the National Fire Protection Association (NFPA) issued NFPA 805, Performance-Based 

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 RI/PB approaches and insights to support fire protection decision making in general. 

One key element in RI/PB fire protection is the availability of verified and validated (V&V) fire 

models that can reliably estimate the effects of fires. The U.S. NRC, together with the Electric 

Power Research Institute (EPRI) and the National Institute of Standards and Technology 

(NIST), conducted a research project to verify and validate five fire models that have been used 

for NPP applications. The results of this effort are documented in a seven-volume NUREG 

report, NUREG-1824 (EPRI 1011999), Verification & Validation of Selected Fire Models for 

Nuclear Power Plant Applications. 

This report describes the implications of the V&V results for fire model users and reviewers. 

The features and limitations of the five fire models documented in NUREG-1824 are discussed 

relative to NPP fire hazard. Finally, the report provides information on the use of fire models in 

support of NFPA 805, NRC fire protection inspection oversight programs, and other commercial 

NPP applications. 

 
iv

 
v 

CONTENTS 

ABSTRACT ................................................................................................................................. iii

CONTENTS .................................................................................................................................. v

FIGURES ..................................................................................................................................... xi

TABLES ...................................................................................................................................... xv

REPORT SUMMARY ............................................................................................................... xvii

PREFACE .................................................................................................................................. xix

ACKNOWLEDGEMENTS ......................................................................................................... xxi

LIST OF ACRONYMS ............................................................................................................. xxiii

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

1.1 Background ..................................................................................................................... 1-1

1.2 Objective ......................................................................................................................... 1-2

1.3 Scope .............................................................................................................................. 1-2

1.3.1 User Capabilities ..................................................................................................... 1-2

1.3.2 Training Resources ................................................................................................. 1-3

1.4 Fire Modeling Theory ...................................................................................................... 1-4

1.4.1 Algebraic Models ..................................................................................................... 1-7

1.4.2 Zone Models ............................................................................................................ 1-8

1.4.3 CFD Models ............................................................................................................. 1-9

1.4.4 V&V ....................................................................................................................... 1-12

1.5 NFPA 805 Fire Modeling Applications ........................................................................... 1-12

1.5.1 Requirements Associated with the Implementation of a Performance Based 

Fire Modeling Analysis ................................................................................................... 1-12

1.5.2 Requirements Associated with the Selected Analytical Fire Models ..................... 1-14

1.6 Fire Modeling in Support of Fire PRA ............................................................................ 1-14

1.7 MSO Fire Modeling Applications ................................................................................... 1-17

1.8 Organization of the Guide ............................................................................................. 1-19

2 THE FIRE MODELING PROCESS ......................................................................................... 2-1

2.1 Step 1: Define Fire Modeling Goals ................................................................................ 2-2

2.2 Step 2: Characterize Fire Scenarios ............................................................................... 2-3

2.2.1 General Considerations ........................................................................................... 2-4

2.2.2 Enclosure Details ..................................................................................................... 2-5

2.2.3 Fire Location ............................................................................................................ 2-5

2.2.4 Credited Fire Protection ........................................................................................... 2-6

2.2.5 Ventilation Conditions .............................................................................................. 2-7

2.2.6 Target Locations ...................................................................................................... 2-8

2.2.7 Secondary Combustibles ......................................................................................... 2-8

2.2.8 Source Fire .............................................................................................................. 2-9

2.3 Step 3: Select Fire Models .............................................................................................. 2-9

2.3.1 Fire Dynamics Tools (FDTs

) .................................................................................. 2-13

2.3.2 FIVE-Rev1 ............................................................................................................. 2-15

2.3.3 Consolidated Fire Growth and Smoke Transport (CFAST) Model ........................ 2-18

2.3.4 MAGIC ................................................................................................................... 2-18

2.3.5 Fire Dynamics Simulator (FDS) ............................................................................. 2-19

2.3.6 Verification and Validation ..................................................................................... 2-22

2.3.7 Fire Modeling Parameters Outside the Validation Range ..................................... 2-26

2.3.7.1 Sensitivity Analysis ...................................................................................... 2-26
vi

2.3.7.2 Additional Validation Studies ....................................................................... 2-28

2.4 Step 4: Calculate Fire-Generated Conditions ................................................................ 2-29

2.5 Step 5: Conduct Sensitivity and Uncertainty Analyses .................................................. 2-30

2.6 Step 6: Document the Analysis ..................................................................................... 2-31

2.7 Summary ....................................................................................................................... 2-32

3 GUIDANCE ON FIRE MODEL SELECTION AND IMPLEMENTATION ................................ 3-1

3.1 Model Implementation of Fire Scenario Elements ........................................................... 3-1

3.1.1 Heat Release Rate .................................................................................................. 3-1

3.1.2 Plant Area Configuration ......................................................................................... 3-2

3.1.3 Ventilation Effects .................................................................................................... 3-3

3.1.4 Targets .................................................................................................................... 3-4

3.1.5 Intervening Combustibles ........................................................................................ 3-5

3.2 Guidance on Model Selection and Analysis .................................................................... 3-6

3.2.1 Targets in the Flames or Plume .............................................................................. 3-9

3.2.1.1 General Objective .......................................................................................... 3-9

3.2.1.2 Modeling Strategy .......................................................................................... 3-9

3.2.1.3 Recommended Models ................................................................................ 3-10

3.2.1.4 Detailed Examples ....................................................................................... 3-11

3.2.2 Scenario 2: Targets Inside or Outside the Hot Gas Layer ..................................... 3-12

3.2.2.1 General Objective ........................................................................................ 3-12

3.2.2.2 Modeling Strategy ........................................................................................ 3-12

3.2.2.3 Recommended Modeling Tools ................................................................... 3-13

3.2.2.4 Detailed Examples ....................................................................................... 3-14

3.2.3 Scenario 3: Targets Located in Adjacent Rooms .................................................. 3-15

3.2.3.1 General Objective ........................................................................................ 3-15

3.2.3.2 Modeling Strategy ........................................................................................ 3-15

3.2.3.3 Recommended Modeling Tools ................................................................... 3-16

3.2.3.4 Detailed Examples ....................................................................................... 3-16

3.2.4 Scenario 4: Targets in Rooms with Complex Geometries ..................................... 3-17

3.2.4.1 General Objective ........................................................................................ 3-17

3.2.4.2 Modeling Strategy ........................................................................................ 3-17

3.2.4.3 Recommended Modeling Tools ................................................................... 3-18

3.2.4.4 Detailed Examples ....................................................................................... 3-18

3.2.5 Scenario 5: Main Control Room Abandonment ..................................................... 3-19

3.2.5.1 General Objective ........................................................................................ 3-19

3.2.5.2 Modeling Strategy ........................................................................................ 3-19

3.2.5.3 Recommended Modeling Tools ................................................................... 3-20

3.2.5.4 Detailed Examples ....................................................................................... 3-20

3.2.6 Scenario 6: Smoke Detection and Sprinkler Activation ......................................... 3-21

3.2.6.1 General Objective ........................................................................................ 3-21

3.2.6.2 Modeling Strategy ........................................................................................ 3-22

3.2.6.3 Recommended Modeling Tools ................................................................... 3-22

3.2.6.4 Detailed Examples ....................................................................................... 3-23

3.2.7 Scenario 7: Fire Impacting Structural Elements .................................................... 3-24

3.2.7.1 General Objective ........................................................................................ 3-24

3.2.7.2 Modeling Strategy ........................................................................................ 3-24

3.2.7.3 Recommended Modeling Tools ................................................................... 3-25

3.2.7.4 Detailed Examples ....................................................................................... 3-25

4 MODEL UNCERTAINTY ........................................................................................................ 4-1

4.1 Validation of the Fire Models ........................................................................................... 4-2

4.2 Derivation of the Model Uncertainty Statistics ................................................................. 4-5
vii 

4.3 How to Calculate the Model Uncertainty ......................................................................... 4-7

4.3.1 Example 1: Target Temperature .............................................................................. 4-8

4.3.2 Example 2: Critical Heat Flux .................................................................................. 4-9

4.4 Sensitivity Analysis ........................................................................................................ 4-10

4.5 Chapter Summary ......................................................................................................... 4-14

5 REFERENCES ....................................................................................................................... 5-1

A CABINET FIRE IN MAIN CONTROL ROOM........................................................................ A-1

A.1 Modeling Objective ........................................................................................................ A-1

A.2 Description of the Fire Scenario ..................................................................................... A-1

A.3 Selection and Evaluation of Fire Models ........................................................................ A-7

A.4 Estimation of Fire-Generated Conditions ..................................................................... A-10

A.4.1 Algebraic Model (FIVE) ........................................................................................ A-10

A.4.2 Zone Model (CFAST) ........................................................................................... A-11

A.4.3 CFD Model (FDS) ................................................................................................ A-12

A.5 Evaluation of Results ................................................................................................... A-14

A.5.1 Temperature Criterion .......................................................................................... A-14

A.5.2 Heat Flux Criterion ............................................................................................... A-15

A.5.3 Visibility Criterion .................................................................................................. A-16

A.5.4 Uncertainty ........................................................................................................... A-16

A.5.5 Sensitivity ............................................................................................................. A-18

A.6 Conclusion ................................................................................................................... A-18

A.7 References................................................................................................................... A-18

A.8 Attachments ................................................................................................................. A-19

B CABINET FIRE IN SWITCHGEAR ROOM ........................................................................... B-1

B.1 Modeling Objective ........................................................................................................ B-1

B.2 Description of the Fire Scenario ..................................................................................... B-1

B.3 Selection and Evaluation of Fire Models ........................................................................ B-5

B.4 Estimation of Fire-Generated Conditions ....................................................................... B-9

B.4.1 Zone Model (CFAST) ............................................................................................. B-9

B.4.2 CFD Model (FDS) ................................................................................................ B-11

B.5 Evaluation of Results ................................................................................................... B-13

B.5.1 Cable Ignition and Damage .................................................................................. B-13

B.5.2 Cabinet Damage .................................................................................................. B-15

B.5.3 Smoke Detector Activation ................................................................................... B-15

B.5.4 Uncertainty ........................................................................................................... B-16

B.5.5 Sensitivity ............................................................................................................. B-17

B.6 Conclusion ................................................................................................................... B-17

B.7 References................................................................................................................... B-17

C LUBRICATING OIL FIRE IN PUMP COMPARTMENT ........................................................ C-1

C.1 Modeling Objective ........................................................................................................ C-1

C.2 Description of the Fire Scenario .................................................................................... C-1

C.3 Selection and Evaluation of Models ............................................................................... C-4

C.4 Estimation of Fire-Generated Conditions ....................................................................... C-6

C.4.1 Zone Model (MAGIC) ............................................................................................. C-6

C.4.2 CFD Model (FDS) .................................................................................................. C-7

C.5 Evaluation of Results ..................................................................................................... C-9

C.5.1 The Fire .................................................................................................................. C-9

C.5.2 Hot Gas Layer Temperature .................................................................................. C-9
viii

C.5.3 Cable Temperature .............................................................................................. C-10

C.5.4 Uncertainty ........................................................................................................... C-11

C.5.5 Sensitivity ............................................................................................................. C-11

C.6 Conclusion ................................................................................................................... C-12

C.7 References .................................................................................................................. C-12

C.8 Attachments ................................................................................................................. C-12

D MOTOR CONTROL CENTER FIRE IN SWITCHGEAR ROOM ........................................... D-1

D.1 Modeling Objective ........................................................................................................ D-1

D.2 Description of the Fire Scenario .................................................................................... D-1

D.3 Selection and Evaluation of Fire Models ....................................................................... D-4

D.4 Estimation of Fire-Generated Conditions ....................................................................... D-6

D.4.1 Algebraic Models (FDTs

) ........................................................................................ D-6

D.4.2 Zone Models (CFAST) ........................................................................................... D-6

D.4.3 CFD Model (FDS) .................................................................................................. D-7

D.5 Evaluation of Results ..................................................................................................... D-9

D.5.1 Damage to Cabinet ................................................................................................ D-9

D.5.2 Cable Damage Based on Temperature ................................................................. D-9

D.5.3 Cable Damage Based on Incident Heat Flux ....................................................... D-10

D.5.4 Uncertainty ........................................................................................................... D-12

D.5.5 Sensitivity ............................................................................................................. D-12

D.6 Conclusion ................................................................................................................... D-13

D.7 References .................................................................................................................. D-13

D.8 Attachments ................................................................................................................. D-14

E TRANSIENT FIRE IN CABLE SPREADING ROOM ............................................................ E-1

E.1 Modeling Objective ........................................................................................................ E-1

E.2 Description of the Fire Scenario ..................................................................................... E-1

E.3 Selection and Evaluation of Fire Models ........................................................................ E-5

E.4 Estimation of Fire-Generated Conditions ....................................................................... E-8

E.4.1 Zone Model (CFAST) ............................................................................................. E-8

E.4.2 CFD Model (FDS) .................................................................................................. E-9

E.5 Evaluation of Results ................................................................................................... E-11

E.5.1 Smoke Detection .................................................................................................. E-12

E.5.2 Cable Damage ..................................................................................................... E-12

E.5.3 Uncertainty ........................................................................................................... E-12

E.5.4 Sensitivity ............................................................................................................. E-15

E.6 Conclusion ................................................................................................................... E-15

E.7 References................................................................................................................... E-16

E.8 Attachments ................................................................................................................. E-16

F LUBRICATING OIL FIRE IN A TURBINE BUILDING ........................................................... F-1

F.1 Modeling Objective......................................................................................................... F-1

F.2 Description of the Fire Scenario ..................................................................................... F-1

F.3 Selection and Evaluation of Fire Models ........................................................................ F-5

F.4 Estimation of Fire-Generated Conditions ..................................................................... F-13

F.4.1 Zone Model (CFAST) ........................................................................................... F-13

F.4.2 CFD Model (FDS) ................................................................................................. F-17

F.5 Evaluation of Results ................................................................................................... F-18

F.5.1 Column Heat Flux and Column Temperature ....................................................... F-19
ix 

F.5.2 Uncertainty ........................................................................................................... F-26

F.5.3 Sensitivity ............................................................................................................. F-28

F.6 Conclusion ................................................................................................................... F-29

F.7 References ................................................................................................................... F-29

F.8 Attachments ................................................................................................................. F-30

G TRANSIENT FIRE IN A MULTI-COMPARTMENT CORRIDOR .......................................... G-1

G.1 Modeling Objective ........................................................................................................ G-1

G.2 Description of the Fire Scenario .................................................................................... G-1

G.3 Selection and Evaluation of Models .............................................................................. G-2

G.4 Estimation of Fire-Generated Conditions ...................................................................... G-6

G.5 Evaluation of Results ..................................................................................................... G-9

G.5.1 Heat Release Rate ................................................................................................ G-9

G.5.2 HGL Temperature .................................................................................................. G-9

G.5.3 Smoke Detection ................................................................................................. G-10

G.5.4 Uncertainty ........................................................................................................... G-10

G.5.5 Sensitivity ............................................................................................................. G-11

G.6 Conclusion ................................................................................................................... G-11

G.7 References .................................................................................................................. G-11

G.8 Attachments ................................................................................................................ G-11

H CABLE TRAY FIRE IN ANNULUS ....................................................................................... H-1

H.1 Modeling Objective ........................................................................................................ H-1

H.2 Description of the Fire Scenario .................................................................................... H-1

H.3 Selection and Evaluation of Fire Models ....................................................................... H-5

H.4 Estimation of Fire-Generated Conditions ....................................................................... H-8

H.4.1 Algebraic Models (FDTs

) ........................................................................................ H-8

H.4.2 Zone Models (CFAST) ......................................................................................... H-13

H.4.3 CFD Model (FDS) ................................................................................................ H-15

H.5 Evaluation of Results ................................................................................................... H-17

H.5.1 Fire Protection Systems ....................................................................................... H-18

H.5.2 Uncertainty ........................................................................................................... H-19

H.5.3 Sensitivity ............................................................................................................. H-19

H.6 Conclusion ................................................................................................................... H-20

H.7 References .................................................................................................................. H-20

H.8 Attachments ................................................................................................................. H-21

 
x

 
xi 

FIGURES 

Figure 1-1. Characteristics of compartment fires ....................................................................... 1-6 

Figure 1-2. A two-zone enclosure fire with an HGL above and a cool lower layer below .......... 1-8 

Figure 1-3. A CFD visualization of compartment fire experiment ............................................ 1-11 

Figure 1-4. Event tree depicting scenario progression modeled in a Fire PRA ....................... 1-15 

Figure 1-5. Conceptual representation of the severity factor ................................................... 1-16 

Figure 2-1. Fire Modeling Process ............................................................................................. 2-1 

Figure 3-1. Pictorial representation of the fire scenario and corresponding technical 

elements described in this section. .................................................................................... 3-7 

Figure 3-2. Legend for fire modeling sketches presented in this chapter. ................................. 3-8 

Figure 3-3. Pictorial representation of scenario 1 ...................................................................... 3-9 

Figure 3-4. Pictorial representation of scenario 2 .................................................................... 3-12 

Figure 3-5. Pictorial representation of scenario 3 .................................................................... 3-15 

Figure 3-6. Pictorial representation of scenario 4 .................................................................... 3-17 

Figure 3-7. Pictorial representation of scenario 5 .................................................................... 3-19 

Figure 3-8. Pictorial representation of scenario 6 .................................................................... 3-21 

Figure 3-9. Pictorial representation of scenario 7 .................................................................... 3-24 

Figure 4-1. Sample set of results from NUREG-1824 ................................................................ 4-4 

Figure 4-2. Two examples demonstrating how the validation data is tested for normality. ........ 4-7 

Figure 4-3. Normal distribution of the “true” value of the cable temperature in a 

hypothetical fire. ................................................................................................................. 4-9 

Figure 4-4. FDS predictions of HGL Temperature as a function of time due to a 

1,000 kW fire (solid line) and a 1,150 kW fire (dashed). .................................................. 4-12 

Figure A-1. Geometry of the Main Control Room. The cabinet is at lower right. ..................... A-2 

Figure A-2. Main Control Room Details. ................................................................................... A-3 

Figure A-3. Photograph of a typical “open grate” ceiling. .......................................................... A-4 

Figure A-4. Photograph of a typical control cabinet. ................................................................. A-4 

Figure A-5. Time history of the HRR used by all models in the MCR scenario......................... A-5 

Figure A-6. Schematic diagram of the FIVE calculation. ........................................................ A-10 

Figure A-7. Snapshot of the CFAST simulation of the MCR fire. ............................................ A-12 

Figure A-8. FDS/Smokeview rendering of the Main Control Room, as seen from above. ...... A-13 

Figure A-9. Hot Gas Layer Temperature and Height for the Main Control Room scenario. ... A-15 

Figure A-10. Predicted heat flux at the location of the operator. ............................................. A-15 

Figure A-11. Visibility criterion for the Main Control Room scenario. ...................................... A-16 

Figure B-1. Geometry of the Switchgear Room. ....................................................................... B-4 

Figure B-2. CFAST/Smokeview rendering of Switchgear Room. ............................................. B-9 

Figure B-3. FDS/Smokeview rendering of the Switchgear Room. .......................................... B-12 

Figure B-4. FDS/Smokeview rendering of the Switchgear Room Fire showing localized 

ignition of extinction of secondary cable fires resulting from initial cabinet fire. .............. B-12 

Figure B-5. Heat release rate inputs to CFAST and FDS for Switchgear Room cabinet 

fire scenario. .................................................................................................................... B-13 

Figure B-6. Estimated temperatures for Cable Tray A directly above fire source for 

Switchgear Room cabinet fire scenario. .......................................................................... B-14 

Figure B-7. Estimated temperature and heat flux on cabinet adjacent to fire source in 

Switchgear Room cabinet fire scenario. .......................................................................... B-15 

Figure C-1. Geometry of the Pump Room. ............................................................................... C-3 

Figure C-2. MAGIC View of the Pump Room ........................................................................... C-7 
xii

Figure C-3. FDS/Smokeview rendering of the Pump Room scenario at the early stage of 

the fire, before the compartment becomes underventilated .............................................. C-8 

Figure C-4. Heat Release Rate Predicted by MAGIC and FDS for the Pump Room Fire 

Scenario. ........................................................................................................................... C-9 

Figure C-5. Hot Gas Layer Temperature Predicted by MAGIC and FDS for the Pump 

Room Fire Scenario. ....................................................................................................... C-10 

Figure C-6. Cable Surface Temperature Predicted by MAGIC and FDS for the Pump 

Room Fire Scenario. ....................................................................................................... C-11 

Figure D-1. Geometry of the MCC/Switchgear Room. .............................................................. D-2 

Figure D-2. Typical electrical cabinet in the lower part of the Switchgear Room. ..................... D-3 

Figure D-3. View of the high ceiling space. ............................................................................... D-3

Figure D-4. Geometry of two-height ceiling Switchgear Room as modeled in CFAST. ............ D-7 

Figure D-5. FDS/Smokeview representation of the MCC/Switchgear Room scenario. ............ D-8 

Figure D-6. Heat flux and temperature predictions for the adjacent cabinet. ............................ D-9 

Figure D-7. Summary of cable results for the MCC/Switchgear Room. .................................. D-11 

Figure E-1. Geometry of Cable Spreading Room ..................................................................... E-3 

Figure E-2. Photograph of typical Cable Spreading Room ....................................................... E-4 

Figure E-3. Geometric detail of the Cable Spreading Room. .................................................... E-4 

Figure E-4. CFAST rendering of the Cable Spreading Room scenario. ................................... E-8 

Figure E-5. FDS/Smokeview rendering of the Cable Spreading Room scenario.................... E-10 

Figure E-6. Heat release rate and estimated HGL temperature for Cable Spreading 

Room scenario ................................................................................................................ E-11 

Figure E-7. Estimated cable conditions for the Cable Spreading Room. ................................ E-14 

Figure F-1. Geometry of the Turbine Building ............................................................................ F-2 

Figure F-2. Structural Steel Column in the Turbine Building ...................................................... F-3 

Figure F-3. Main Turbine Lubricating Oil Tanks in the Turbine Building .................................... F-3 

Figure F-4a. CFAST Geometry for the Two-Compartment Representation of the Turbine 

Building ............................................................................................................................ F-14 

Figure F-4b. CFAST Geometry for the Single-Compartment Representation of the 

Turbine Building ............................................................................................................... F-15 

Figure F-5. FDS Geometry for the Turbine Building Fire Scenario .......................................... F-18 

Figure F-6. Heat Release Rates Used by CFAST and FDS for Lubricant Oil Fire 

Scenario ........................................................................................................................... F-19 

Figure F-7a. Predicted Incident or Total Heat Flux and Column Temperature for Column 

A – Curb Location 1. ........................................................................................................ F-20 

Figure F-7b. Predicted Incident or Total Heat Flux and Column Temperature for Column 

B – Curb Location 1. ........................................................................................................ F-20 

Figure F-7c. Predicted Incident or Total Heat Flux and Column Temperature for Column 

C – Curb Location 1. ........................................................................................................ F-20 

Figure F-7d. Predicted Incident or Total Heat Flux and Column Temperature for Column 

D – Curb Location 1. ........................................................................................................ F-21 

Figure F-7e Predicted Incident or Total Heat Flux and Column Temperature for Column 

E – Curb Location 1. ........................................................................................................ F-21 

Figure F-7f. Predicted Incident or Total Heat Flux and Column Temperature for Column 

F – Curb Location 1. ......................................................................................................... F-21 

Figure F-8a. Predicted Incident or Total Heat Flux and Column Temperature for Column 

A – Curb Location 2. ........................................................................................................ F-22 

Figure F-8b. Predicted Incident or Total Heat Flux and Column Temperature for Column 

B – Curb Location 2. ........................................................................................................ F-22 

Figure F-8c. Predicted Incident or Total Heat Flux and Column Temperature for Column 

C – Curb Location 2. ........................................................................................................ F-22 
xiii 

Figure F-8d. Predicted Incident or Total Heat Flux and Column Temperature for Column 

D – Curb Location 2. ........................................................................................................ F-23 

Figure F-8e Predicted Incident or Total Heat Flux and Column Temperature for Column 

E – Curb Location 2. ........................................................................................................ F-23 

Figure F-8f. Predicted Incident or Total Heat Flux and Column Temperature for Column 

F – Curb Location 2. ......................................................................................................... F-23 

Figure F-9a. Column A Boundary Heat Flux Fractions Predicted by CFAST – Curb 

Location 1 in One Compartment Geometry ..................................................................... F-24 

Figure F-9b. Column E Boundary Heat Flux Fractions Predicted by CFAST – Curb 

Location 1 in One-Compartment Geometry ..................................................................... F-24 

Figure F-10a. Hot Gas Layer Temperature Predicted by CFAST in the Turbine Building. ...... F-25 

Figure F-10b. HGL Elevation Predicted by CFAST in the Turbine Building. ............................ F-25 

Figure G-1. Geometry of the Multi-Compartment Corridor. ...................................................... G-4 

Figure G-2. Geometry Details of the Multi-Compartment Corridor. .......................................... G-5 

Figure G-3. Effective corridor layout for implementation in zone models (not to scale). ........... G-6 

Figure G-4. MAGIC rendering of the Corridor scenario. ........................................................... G-8 

Figure G-5. Heat Release Rate produced by MAGIC for the Corridor Scenario. ..................... G-9 

Figure G-6. Hot Gas Layer Temperature Predictions by MAGIC for the Corridor 

Scenario. ......................................................................................................................... G-10 

Figure H-1. Geometry of the Annulus. ...................................................................................... H-3

Figure H-2. Geometry details of the Annulus ............................................................................ H-4 

Figure H-3. FDS/Smokeview rendering of the Annulus scenario. ............................................. H-7 

Figure H-4. Screenshot showing FDTs

 Heat Flux Calculation using Point Source 

Approximation. .................................................................................................................. H-9 

Figure H-5. Screenshot showing CFAST Geomtry Input Screen. ........................................... H-14 

Figure H-6. Screenshot showing CFAST Fire Input Screen. .................................................. H-14 

Figure H-7. FDS/Smokeview rendering of the Annulus scenario showing burning cable 

tray. ................................................................................................................................. H-16 

Figure H-8. Heat Release Rate Used by the FDTs, CFAST, and FDS for the Cable Tray 

Fire Scenario ................................................................................................................... H-17 

Figure H-9. Summary of simulation results for the Annulus. ................................................... H-18 

 
xiv

 
xv 

TABLES 

Table 2-1. Summary of Common Fire Model Tools ................................................................. 2-12 

Table 2-2. Routines included in the FDTs

 ................................................................................ 2-14 

Table 2-3. Routines included in FIVE-Rev1 ............................................................................. 2-17 

Table 2-4. NUREG-1824/EPRI 1011999 (2007) Validation and Verification Parameters 

for Various Fire Models .................................................................................................... 2-23 

Table 2-5. Selected Normalized Parameters for Application of the Validation results to 

Nuclear Power Plant (NPP) Fire Scenarios (NUREG-1824/EPRI 1011999, 2007) .......... 2-25 

Table 3-1. Boundary Material Properties ................................................................................... 3-3

Table 3-2. Listing of generic fire scenarios described in this chapter ........................................ 3-6 

Table 4-1. Results of the V&V study, NUREG-1824. Note that I.D. indicates that there is 

insufficient data for the statistical analysis. N/A indicates that the model does not 

have an algorithm to compute the given Output Quantity.. ................................................ 4-2 

Table 4-2. Experimental uncertainty of the experiments performed as part of the 

validation study in NUREG-1824 ....................................................................................... 4-7 

Table 4-3. Sensitivity of model outputs from Volume 2 of NUREG-1824 ................................ 4-11 

Table A-1. Normalized parameter calculations for the MCR fire scenario. ............................... A-9 

Table A-2. Uncertainty analysis of the model predictions of the MCR scenario ..................... A-17 

Table B-1. Key parameters and their ranges of applicability to NUREG-1824 ......................... B-7 

Table B-2. Estimated time to ignition of lowest cable tray, CFAST, Switchgear Room 

cabinet fire ....................................................................................................................... B-14 

Table B-3. Smoke detector activation times, Switchgear Room cabinet fire........................... B-16 

Table B-4. Uncertainty analysis of the model predictions of the cabinet fire scenario ............ B-17 

Table C-1. Normalized parameter calculations for the Pump Room fire scenario. ................... C-5 

Table D-1. Normalized parameter calculations for the MCC fire scenario. ............................... D-5 

Table D-2. Uncertainty analysis of the model predictions of the MCC scenario ..................... D-13 

Table E-1. Key parameters and their ranges of applicability to NUREG-1824.......................E-7 

Table E-2. Cross-sectional area as a function of height used for CFAST calculation.............E-8 

Table E-3. Smoke detector activation times, Cable Spreading Room .................................... E-12 

Table E-4. Uncertainty analysis of the model predictions of the CSR scenario ...................... E-15 

Table F-1. Material Properties of Concrete and Steel in the Turbine Building ........................... F-4 

Table F-2. Structural Steel Failure Criteria (ASTM E119-10a) .................................................. F-4 

Table F-3. Lubricant Fuel Properties (NUREG-1805, 2005) ...................................................... F-5 

Table F-4. Normalized Parameter Calculations for the Turbine Building Fire Scenario ............. F-8 

Table F-5. Primary Compartment Dimensions ......................................................................... F-13 

Table F-6. Maximum Column Temperatures among the Six Columns Considered 

Predicted by CFAST and FDS. ........................................................................................ F-26 

Table F-7. Mean Maximum Column Temperatures and Standard Deviations among the 

Six Columns Considered Based on Model Uncertainty for CFAST and FDS .................. F-27 

Table G-1. Normalized parameter calculations for the Multi-Compartment Corridor fire 

scenario. ............................................................................................................................ G-3 

Table G-2. Compartment dimensions for Corridor scenario ..................................................... G-6 

Table H-1. Normalized parameter calculations for the Annulus fire scenario ........................... H-6 

Table H-2. Uncertainty analysis of the model predictions of the annulus scenario ................. H-20 

 
xvi

 
xvii 

REPORT SUMMARY 

Background 

Since the 1990s, when the NRC adopted the policy of using risk-informed methods to make 

regulatory decisions whenever 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 within the fire protection field, including 

risk-informed, performance-based fire protection programs (FPPs) compliant with Title 10, 

Section 50.48(c) of the Code of Federal Regulations (10 CFR 50.48(c)) and FPP change 

evaluation under the existing Title 10 Section 50.48 and Regulatory Guide 1.189. RI/PB fire 

protection often relies on fire modeling to estimate the effects of fires. 

Objectives 

 To provide guidance on the application of fire models to NPP hazard 

 To provide guidance on fire hazard and risk assessment 

Approach 

The project team developed fire scenarios of interest in NPPs. The five fire models used in the 

Verification and Validation (V&V) study (NUREG-1824, EPRI 1011999)—(1) NRC’s Fire 

Dynamics Tools (FDTs), (2) EPRI’s Fire-Induced Vulnerability Evaluation Revision 1 (FIVERev1), (3) the National Institute of Standards and Technology’s (NIST) Consolidated Model of 

Fire Growth and Smoke Transport (CFAST), (4) Electricité de France’s (EdF) MAGIC, and (5) 

NIST’s Fire Dynamics Simulator (FDS)—were used to develop this report. Finally, the project 

team developed guidance on the selection and application of each model and treatment of 

uncertainty and/or sensitivity as part of the fire modeling analysis. 

Results 

The results of this effort are presented in a step-by-step process for using fire modeling in 

nuclear power plant applications. The recommended methodology consists of six steps: (1) 

define fire modeling goals, (2) characterize fire scenarios, (3) select fire models, (4) calculate 

fire-generated conditions, (5) conduct sensitivity and uncertainty analyses, and (6) document 

the results. 

EPRI Perspective 

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

their limitations and predictive capabilities, and also 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. EPRI, with NRC support, will continue to provide training to 

the fire protection community, using this document to promote fire modeling and gain feedback 

on how the results of this work may affect known applications of fire modeling. In the long term, 

model improvement and additional experiments should be considered. 

This report supersedes EPRI 10002981, Fire Modeling Guide for Nuclear Power Plant 

Applications, August 2002, as guidance for fire modeling practitioners in nuclear power plants 

(NPPs). The report has benefited from the insights gained since 2002 on the predictive 

capability of selected fire models in improving confidence in the use of fire modeling in NPP 

decision making. 
xviii

Keywords 

Fire 

Verification and Validation (V&V) 

Risk-Informed Regulation 

Fire Safety 

Nuclear Power Plant (NPP) 

Fire Modeling 

Performance-Based 

Fire Hazard Analysis (FHA) 

Fire Protection 

Probabilistic Risk Assessment (PRA) 
xix 

PREFACE 

This report is the fifth in a series designed to assist those responsible for performing and 

reviewing fire modeling in nuclear power plant applications. 

In August 2002, EPRI published EPRI 1002981, Fire Modeling Guide for Nuclear Power Plant 

Applications. This report offered step-by-step guidance that analysts could follow when using 

fire modeling to support nuclear power plant algebraic models. It also included FIVE Rev 1, an 

Excel-based library of fire models previously documented by EPRI, and additional models from 

fire protection literature. 

In December 2004, the NRC published NUREG-1805, Fire Dynamics Tools (FDTs) Quantitative 

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

Inspection Program. This report provided an introduction to the principles of fire dynamics, and 

included an Excel-based library of fire models comparable to EPRI FIVE Rev 1. 

In a follow-up effort as a part of the NRC/RES-EPRI Memorandum of Understanding, NRC/RES 

and EPRI jointly conducted a verification and validation of selected fire models for use in 

nuclear power plant fire modeling to gain insight into the predictive capabilities of these models. 

The results of this work were published in NUREG-1824 (EPRI 1011999), Verification and 

Validation of Selected Fire Models for Nuclear Power Plant Applications, May 2007. Using, in 

part, the findings of this work, the NRC conducted a Phenomena Identification and Ranking 

Table (PIRT) study to evaluate the current state of knowledge for fire modeling for NPP 

applications. The results of this work were published in NUREG/CR-6978, A Phenomena 

Identification and Ranking Table (PIRT) Exercise for Nuclear Power Plant Fire Modeling 

Applications, November 2008. 

 
xx

 
xxi 

ACKNOWLEDGEMENTS 

The authors wish to thank those members of the peer review panel who provided comments on 

this draft. Their major comments were resolved prior to this draft’s release for public comment, 

while minor comments and suggestions, along with public comments, will be incorporated in the 

final document. 

Professor Jose L. Torero and his students at BRE Centre for Fire Safety Engineering, The 

University of Edinburgh, Scotland 

Professor Frederick Mowrer, formerly of the Department of Fire Protection Engineering, 

University of Maryland, and currently with the Department of Fire Protection Engineering, 

California Polytechnic State University 

Mr. Patrick Finney, NRC Resident Inspector at Susquehanna Nuclear Plant 

Mr. Naeem Iqbal, Fire Protection Engineer, Office of Nuclear Reactor Regulation (NRR), 

NRC 

Mr. Thomas Gorman, Project Manager, Pennsylvania Power and Light, Susquehanna 

Nuclear Plant 

The authors express their thanks to Laurent Gay and Eric Wizenne, Electricité de France (Edf), 

for reviewing the MAGIC calculations. The authors would also like to acknowledge Mr. Bryan 

Klein of Thunderhead Engineering and Drs. Nathan Siu and Raymond Galluci of the NRC for 

their valuable contributions to this report. The authors also express appreciation to Ms. Aixa 

Belen, Mr. Ken Canavan, Mr. Stuart Lewis, Mr. Nicholas Melly, Ms. Carolyn Siu, and Mr. Robert 

Vettori for their reviews of and comments on various drafts of this document. 

 
xxii
xxiii 

LIST OF ACRONYMS 

AGA American Gas Association 

AHJ Authority Having Jurisdiction 

ASET Advanced Science and Engineering Technologies 

ASME American Society of Mechanical Engineers 

ASTM American Society for Testing and Materials 

BE Benchmark Exercise 

BFRL Building and Fire Research Laboratory 

BRE Building Research Establishment 

BWR Boiling Water Reactor 

CAROLFIRE Cable Response to Live Fire 

CDF Core Damage Frequency 

CFAST Consolidated Fire Growth and Smoke Transport Model 

CFD Computational Fluid Dynamics 

CFR Code of Federal Regulations 

CHRISTIFIRE Cable Heat Release, Ignition, and Spread in Tray Installations during Fire 

CSR Cable Spreading Room 

ECCS Emergency Core Cooling Systems 

EdF Electricité de France 

EPRI Electric Power Research Institute 

ERFBS Electrical Raceway Fire Barrier System 

FDS Fire Dynamics Simulator 

FDTs

 Fire Dynamics Tools (NUREG-1805) 

FHA Fire Hazard Analysis 

FIVE-Rev1 Fire-Induced Vulnerability Evaluation, Revision 1 

FFT Fast Fourier Transform 

FM/SNL Factory Mutual & Sandia National Laboratories 

FPA Foote, Pagni, and Alvares 

FPRA Fire probabilistic risk assessment 

FRA Fire Risk Analysis 

GRS Gesellschaft für Anlagen- und Reaktorsicherheit (Germany) 

HGL Hot Gas Layer 

HRR Heat Release Rate 

HRRPUA Heat release rate per unit area 

IAFSS International Association of Fire Safety Science 

iBMB Institut für Baustoffe, Massivbau und Brandschutz 

ICFMP International Collaborative Fire Model Project 

IEEE Institute of Electrical and Electronics Engineers 

IPEEE Individual Plant Examination of External Events 

LERF Large Early Release Frequency 

LES Large eddy simulation 

LFS Limiting fire scenarios 

LLNL Lawrence Livermore National Laboratory 

LOL Low oxygen limit 

MCC Motor Control Center 

MCR Main Control Room 

MEFS Maximum expected fire scenarios 
xxiv 

MOVs Motor-operated valves 

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) 

PE Polyethylene 

PMMA Polymethyl-Methacrylate 

PRA Probabilistic Risk Assessment 

PVC Polyvinyl chloride 

PWR Pressurized Water Reactor 

RCP Reactor Coolant Pump 

RES Office of Nuclear Regulatory Research (NRC) 

RI/PB Risk-Informed, Performance-Based 

RIS Regulatory Issue Summary 

RTE Radiation Transport Equation 

RTI Response Time Index 

SBDG Stand-By Diesel Generator 

SDP Significance Determination Process 

SFPE Society of Fire Protection Engineers 

SNL Sandia National Laboratory 

SWGR Switchgear Room 

THIEF Thermally-Induced Electrical Failure 

TP Thermoplastic 

TS Thermoset 

UL Underwriters Laboratory 

V&V Verification & Validation 

XPE Cross-linked polyethylene and neoprene 
1-1 

1

INTRODUCTION 

1.1 Background 

In 2001, the National Fire Protection Association (NFPA) issued the first edition of NFPA 805, 

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

Plants, 2001 Edition1

. Effective July 16, 2004, the Nuclear Regulatory Commission (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 following a performance-based approach as an 

alternative to the existing deterministic fire protection requirements. One important element in a 

performance-based approach is the estimation of fire hazard using mathematical fire models. 

Fire modeling is one possible approach that can be used for this purpose, according to NFPA 

805, to demonstrate compliance with the regulatory requirements noted in 10 CFR 50.48(c). 

NFPA 805 also allows the use of a fire probabilistic risk assessment (Fire PRA) in regulatory 

applications. Fire modeling is used in Fire PRAs to determine the effects of fire hazard so that 

the associated risk can be quantified. 

As part of its fire modeling requirements, NFPA 805 states that “fire models shall be verified and 

validated” (section 2.4.1.2.3) and that “only fire models that are acceptable to the authority 

having jurisdiction (AHJ) shall be used in fire modeling calculations” (section 2.4.1.2.1). This is 

an important requirement because the verification and validation (V&V) of fire models is 

intended to ensure the correctness, suitability, and overall quality of the method. Specifically, 

verification is the process used to determine whether a model correctly represents the 

developer’s conceptual description (i.e., whether it was “built” correctly), while validation is used 

to determine whether a model is a suitable representation of the real world and is capable of 

reproducing phenomena of interest (i.e., whether the correct model was “built”). 

In 2007, the NRC’s Office of Nuclear Regulatory Research (RES) and the Electric Power 

Research Institute (EPRI) as a part of the NRC/RES-EPRI Memorandum of Understanding 

(MOU) completed a collaborative project for the V&V of five select fire modeling tools to support 

the implementation of the voluntary fire protection rule that adopts NFPA 805 as a RiskInformed/Performance-Based (RI/PB) alternative. The results of this study are documented in 

NUREG-1824 (EPRI 1011999), “Verification and Validation of Selected Fire Models for Nuclear 

Power Plant Applications.” The National Institute of Standards and Technology (NIST) was also 

an important partner in developing this publication, providing extensive fire modeling and 

experimentation expertise. The V&V effort is intended to increase the confidence of reviewers 

who evaluate fire models used in NRC inspection oversight programs, such as the Fire 

Protection Significance Determination Process (SDP). 

 

1

 All references in this chapter to NFPA 805 are specific to the 2001 edition of the standard, which is the 

code of record (COR) required by 10 CFR 50.48(c). 
Introduction 

1-2 

This report builds on the V&V research described earlier by incorporating the results into a set 

of guidelines and recommendations for conducting fire modeling studies in support of NFPA 

805, Fire PRAs, Fire Protection SDPs, and/or other commercial nuclear industry applications. 

When the NRC Advisory Commission on Reactor Safeguards (ACRS) issued a letter to Luis 

Reyes, Executive Director for Operations, recommended publication of NUREG-1824 (EPRI 

1011999), they identified two major items to be included in the user’s guide (Wallis, 2006). 

Specifically, the ACRS recommended that the user’s guide include: 

 Estimates of the ranges of normalized parameters to be expected in nuclear plant 

applications 

 Quantitative estimates of the uncertainties associated with each model’s predictions, 

preferably in the form of probability distributions 

The ACRS indicated that quantitative estimates of the “intrinsic model uncertainty” would be a 

valuable input in risk-informed as well as non-risk-informed applications. Chapters 2 and 3 

address the first ACRS recommendation. Chapter 4 specifically addresses developing the V&V 

results into quantitative estimates of model uncertainty which is the second ACRS 

recommendation. Finally, the appendices contain examples which illustrate the entire process 

for several NPP scenarios. 

1.2 Objective 

The objective of this guide is to describe the process of conducting a fire modeling analysis 

principally for commercial nuclear power plant (NPP) applications. The process described in 

this guide addresses most of the technical elements relevant to fire modeling analysis, such as 

the selection and definition of fire scenarios and the determination and implementation of input 

values, sensitivity analysis, uncertainty quantification, and documentation. In addition, 

requirements associated with fire modeling analyses and analytical fire modeling tools in NFPA 

805 are addressed through generic guidance, recommended best practices, and example 

applications. 

1.3 Scope 

1.3.1 User Capabilities 

This guide should be used as a complement to, not a substitute for, “user’s manuals” for specific 

fire modeling tools, fire dynamics textbooks, technical references, education and training. This 

guide only compiles information and organizes it procedurally for NPP applications. Analysts 

are encouraged to review the references made throughout the guide for in-depth coverage of 

the advantages and the range of applicability of specific models or assumptions. Once a fire 

scenario has been selected, this guide will help the fire model user define the necessary 

modeling parameters, select an appropriate model, and properly interpret the fire modeling 

results. Since all models are merely approximations of reality, this guide also provides useful 

insights for translating real configurations into modeling scenarios. Due to the technical nature 

of this guide, users with the following areas of expertise will benefit the most from it: 
Introduction 

1-3 

 General knowledge of the behavior of compartment fires 

 General knowledge of basic engineering principles, specifically thermodynamics, heat 

transfer, and fluid mechanics 

 Ability to understanding the basis of mathematical models involving algebraic and 

differential equations 

This guide focuses on the capabilities of the models selected for V&V. However, some generic 

guidance is also provided, and most of the discussion is applicable to any fire model of the 

respective type (algebraic model, zone model, or computational fluid dynamics (CFD) model). 

Five specific models are discussed in this guide: 

(1) The NRC’s Fire Dynamics Tools (FDTS

), NUREG-1805 and Supplements 

(2) EPRI’s Fire-Induced Vulnerability Evaluation, Revision 1 (FIVE-Rev1) 

(3) NIST’s Consolidated Model of Fire Growth and Smoke Transport (CFAST) Version (6) 

(4) Electricite de France’s (EdF) MAGIC code Version (4.1.1) 

(5) NIST’s Fire Dynamics Simulator (FDS) Version (5) 

1.3.2 Training Resources 

For individuals seeking to enhance or update their expertise in the areas noted in section 1.3.1, 

there are several resources available, including academic courses, short courses, and written 

materials. The following three U.S. institutions have established undergraduate and/or graduate 

degree programs in fire protection engineering: 

 California Polytechnic Institute, San Luis Obispo (http://fpe.calpoly.edu/) 

 University of Maryland (http://www.fpe.umd.edu) 

 Worcester Polytechnic Institute (http://www.wpi.edu/Academics/Depts/Fire/) 

Information on academic institutions with degree programs or single classes in fire protection 

engineering can also be found at: 

http://www.careersinfireprotectionengineering.com/career_types.htm

A background in engineering fundamentals is essential for fire modelers, especially in the areas 

of fluid mechanics, thermodynamics, and heat transfer. These subjects are offered at virtually 

any academic institution with programs in fire protection, mechanical, aerospace, civil, and 

chemical engineering. While general courses provide basic background discussions, courses 

involving fire applications are preferable, and would be provided by the institutions offering 

courses or degree programs in fire protection engineering. 

In addition to the academic programs, short courses in fire behavior and fire modeling are 

available through professional and industry associations, such as the Society of Fire Protection 

Engineers (SFPE) (http://www.sfpe.org) and the Electric Power Research Institute 

(http://www.epri.com). 
Introduction 

1-4 

Key written references on fire behavior and fire modeling include: 

ASTM E1355–05a (2005), “ASTM Standard Guide for Evaluating the Predictive 

Capability of Deterministic fire Models,” American Society for Testing and 

Materials, West Conshohocken, PA, 2005. 

Buchanan, A. H. (2001), Structural Design for Fire Safety, John Wiley and Sons, LTD, 

Chichester, England, 2001. 

Babrauskas, V., Ignition Handbook, Fire Science Publishers/Society of Fire Protection 

Engineers, Issaquah WA (2003). 

Drysdale, D., An Introduction to Fire Dynamics, 2nd Ed., John Wiley, 2002. 

Karlsson, B. and Quintiere, J., Enclosure Fire Dynamics, CRC Press, 1999 

Quintiere, J.G., Principles of Fire Behavior, Delmar Publishers, 1998. 

Quintiere,J.G., Fundamentals of Fire Phenomena, John Wiley, 2006. 

Fire Protection Handbook, National Fire Protection Association, 20th Ed., A.E. Cote, 

(Editor) 2008. 

M.H. Salley and R.P. Kassawara, “Verification and Validation of Selected Fire Models for 

Nuclear Power Plant Applications,” NUREG-1824, EPRI 1011999, Nuclear 

Regulatory Commission, 2007. 

SFPE Handbook of Fire Protection Engineering, 4th Ed., P.DiNenno, (Editor), National 

Fire Protection Association, 2008. 

SFPE, “SFPE Engineering Guide to Assessing Flame Radiation to External Targets from 

Pool Fires,” SFPE Engineering Guide, Society of Fire Protection Engineers, 

Bethesda, MD, March 1999. 

SFPE, “SFPE Engineering Guide to Fire Exposures to Structural Elements,” SFPE 

Engineering Guide, Society of Fire Protection Engineers, Bethesda, MD, 

November, 2005. 

SFPE, “SFPE Engineering Guide to Piloted Ignition of Solid Materials Under Radiant 

Exposure,” SFPE Engineering Guide, Society of Fire Protection Engineers, 

Bethesda, MD, January, 2002. 

SFPE, “SFPE Engineering Guide to Predicting Room of Origin Fire Hazards,” SFPE 

Engineering Guide, Society of Fire Protection Engineers, Bethesda, MD, 

November, 2007. 

1.4 Fire Modeling Theory 

Fire development in compartments is often divided into phases depending on the dominant 

processes at any given stage of development. Ignition is dictated by the characteristics of the 

fuel item being ignited (i.e., ignition temperature, geometry, orientation, and thermophysical 

properties2

) and the strength of the ignition source. Once the flames are sustained on a burning 

fuel item, a smoke plume develops; transporting mass and heat vertically as a result of the 

buoyancy of the smoke (see Figure 1-1). The plume will entrain air as it rises, thereby causing 

the smoke to cool and become diluted; as a result, the quantity of smoke being transported will 

increase with increasing elevation. After a smoke plume strikes the ceiling, the smoke travels 

 

2

 Thermophysical properties include thermal conductivity, specific heat, and density. 
Introduction 

1-5 

horizontally under the ceiling in a relatively thin layer, referred to as a ceiling jet. As the ceiling 

jet travels, the smoke cools with increasing distance from the plume impingement point, in part 

because of air entrainment into the ceiling jet as well as heat losses from the ceiling jet to the 

solid ceiling boundary. 

In an ideal situation, once the ceiling jet reaches the enclosing walls, a Hot Gas Layer3

 (HGL) 

develops. As a result of the continuing supply of smoke mass and heat via the plume, the HGL 

becomes deeper, and its temperature increases. Other properties of the smoke in the HGL also 

increase (including concentration of gas species and solid particulates). 

Radiant heat from the HGL to other combustibles not involved in the fire increases their 

temperature. Similarly, the temperature of non-burning combustibles will also increase as a 

result of receiving thermal radiation from the burning item(s). As the other combustibles reach 

their respective ignition temperatures, they will also ignite. In some cases, the ignition of many 

other combustibles in the space caused by heating from the HGL occurs within a very short time 

span. This is commonly referred to as flashover. 

Several aspects of fire behavior may be of interest when applying fire models, depending on the 

purpose of the modeling application. Analysts may seek to determine the effects associated 

with heating of targets submerged in smoke or receiving radiant heat from the flames, the 

response of ceiling-mounted detectors or sprinklers to the fire environment, or other 

phenomena. 

 

3

 Hot Gas Layer or HGL is also called “smoke layer” or “hot upper layer” in other publications in fire 

protection engineering. 
Introduction 

1-6 

Figure 1-1. Characteristics of compartment fires. 

The aspects of fire behavior that may be of interest in such analyses include: 

 Rate of smoke production 

 Rate of smoke filling 

 Properties of the ceiling jet 

 Properties of the HGL 

 Target response to incident heat flux via either thermal radiation or convection 

A detailed review of each of these aspects is provided in texts on fire dynamics. A brief review 

of each is provided here. 

Rate of smoke production 

Smoke is defined as a combination of the gaseous and solid particulates resulting from the 

combustion process, plus the air that is entrained into the flame and/or smoke plume. 

Consequently, the rate of smoke production at a particular height in the plume is the 

combination of the generation rate of combustion products and air entrainment rate into the 

flame and/or smoke plume between the top of the fuel and the height of interest. In most cases, 

the air entrainment rate greatly exceeds the generation rate of combustion products. Hence, 

the correlations used to estimate the rate of smoke production are usually taken from 

experimental research on entrained air. 
Introduction 

1-7 

Rate of smoke filling 

The rate of smoke filling is dependent on the rate of smoke production, the heat release rate, 

floor area and height of the space, and time from ignition. For a fire with a steady heat release 

rate, the rate of smoke filling in a compartment will decrease with time due to a decrease in the 

smoke production rate, which decreases as the height available to entrain air decreases when 

the HGL deepens. 

Properties of the ceiling jet 

The ceiling jet transports smoke and heat horizontally away from the region of plume impact 

with the ceiling. The response of ceiling-mounted fire detectors or sprinklers is governed 

primarily by their interaction with a ceiling jet. The temperature and concentration of smoke in a 

ceiling jet is principally dependent on the height of the space, distance between the impact point 

of the smoke plume and the ceiling, and the heat release rate of the fire. 

Properties of the HGL 

As smoke and heat are transported to the HGL via the smoke and fire plumes, the properties of 

the HGL will change. The principal properties of interest include the depth, temperature and 

gas concentrations in the HGL. The magnitude of the properties depends on the heat release 

rate of the fire, geometry of the space, ventilation openings (permitting material from the HGL to 

leave the space, providing air to the fire, and/or causing a stirring action), yields of combustion 

products, and the elapsed time after ignition. These changes can be tracked by considering the 

conservation of energy, mass, and species relative to the HGL. 

Target response to incident heat flux via either thermal radiation or convection 

The targets’ temperature will increase as a result of receiving heat via either thermal radiation or 

convection. Radiation heat transfer is dependent on the intensity of thermal radiation emitted by 

a source, the size of the source, and the proximity of the target to the source. For this 

application, the flame height, the portion of heat released from the fire as radiation, and the 

distance separating the target from the flame are the dominant parameters. Convection heat 

transfer occurs whenever the target is submerged in the smoke plume or HGL. 

1.4.1 Algebraic Models 

Algebraic models may be standalone equations found in literature or may be contained within 

spreadsheets (such as the NRC’s FDTs

), and can help give a general understanding of one of 

the fire environment phenomena. These equations are typically closed-form algebraic 

expressions, many of which were developed as correlations from empirical data. In some 

cases, they may take the form of a first-order ordinary differential equation, and, when used 

properly, can provide an estimate of fire variables, such as HGL temperature, heat flux from 

flames or the HGL, smoke production rate, depth of the HGL, and the actuation time for 

detectors. 
Introduction 

1-8 

Algebraic models are helpful because they require minimal computational time and a limited 

number of input variables. When applying the results of the algebraic models, users need to be 

aware that the development of most equations involved assumptions to simplify the analysis. 

Other than for very simple situations, algebraic models are useful primarily as screening tools 

(i.e., to provide a rough approximation to an analysis, perhaps as a check of an aspect of the 

results of the computer-based models), and are also applicable when only one phenomenon 

can be treated in isolation: for instance, plume or ceiling jet correlations are not applicable if 

there is a significant HGL unless they are modified to account for this effect. 

1.4.2 Zone Models 

A zone model, such as the Consolidated Fire and Smoke Transport Model (CFAST) or MAGIC, 

calculates fire environment variables using control volumes, or zones, of a space. The zones 

correspond to a cooler lower layer and an HGL, as depicted in Figure 1-2. The fundamental 

idea behind a zone model is that each zone is well-mixed and that all fire environment variables 

(temperature, smoke concentration, etc.) are therefore uniform throughout the zone. Conditions 

in each zone are calculated by applying conservation equations and the ideal gas law. The 

variables in each zone change as a function of time and rely on the initial conditions specified by 

the user. It is assumed that there is a well-defined boundary separating the two zones, though 

this boundary may move up or down throughout the simulation. 

Figure 1-2. A two-zone enclosure fire with an HGL above and a cool lower layer below. 

Zone models are most applicable in situations involving simple geometries or where spatial 

resolution within a compartment is not important. The preparation of input for a zone model, the 

computation time, and the amount of output data generated are slightly more extensive than a 

simple algebraic model; however, the overall computational time cost is still low. 

HGL 

Mass 

outflow 

Mass inflow 

Plume mass 

flow 
Introduction 

1-9 

Zone models can easily analyze conditions resulting from fires involving single compartments or 

compartments with adjacent spaces, and are often used to compute the HGL temperature, HGL 

composition, and target heat fluxes. They are also capable of modeling some effects of natural 

and mechanical ventilation in both horizontal and vertical directions. Some zone models allow 

the user to select a thermal plume model, which may assist in better characterization of a known 

fire scenario, while others assume an axisymmetric smoke plume. Other features of a zone 

model may include a user-specified one-zone assumption or multiple fire plumes. 

Simulations of spaces with complex ceilings or numerous compartments can be challenging 

with a zone model. Because zone models assume uniform conditions in the HGL and lower 

layer, results cannot be distinguished for a location situated in the upper part of the space over 

another, nor is an analysis of different fire locations in the compartment possible. 

Because of the uniform layer assumption, applying zone models to characterize large horizontal 

flow paths is challenging, and greater errors are obtained with increasing deviation from 

parallelepiped geometries. These limitations result from the conflict between the assumptions 

of the model and actual fire phenomena, such as the cooling of an HGL with continued mixing in 

ambient air. As the layer cools, the HGL assumption is no longer applicable. Due to the zone 

approach, smoke transport time lags are not considered in the simulation, which is an 

acceptable approximation in relatively small spaces but may lead to significant error in largevolume spaces or spaces with large aspect ratios. 

Smoke production, fire plume dynamics, ceiling jet characteristics, heat transfer, and ventilation 

flows are all algebraic models embedded within zone models. Other parameters that can be 

calculated with a zone model include thermal behavior, detection response, and suppression 

response. The output of a zone model is typically simple to understand and is generally 

presented through an automatic user interface. 

1.4.3 CFD Models 

A CFD model is often useful when trying to determine fire variables at a specific location or 

when there are geometric features that are expected to play a significant role in the results 

beyond what is calculated in a zone model approximation. A typical CFD model consists of a 

preprocessor, a solver, and a postprocessor. CFD models can provide a detailed analysis in 

both simple and complex geometries. 

CFD models essentially apply a series of conservation and state equations across multiple cell 

boundaries in a space. The number of cell boundaries depends on the mesh size, which breaks 

the geometry into three-dimensional subvolumes called cells. Solutions to partial derivatives of 

the conservation equations are updated as a function of time within each numerical grid cell, 

with the solutions in all cells, collectively describing the fire environment within the geometry at 

the cell resolution. 

The number of grid cells defines the type of mesh. A fine mesh is made up of numerous grid 

cells. Since the equations are applied at each cell’s boundaries, a more detailed distribution of 

fire parameters is characterized. A coarse mesh is made up of fewer grid cells and can result in 
Introduction 

1-10 

less accurate results. The type of mesh and number of grid cells should be based on the 

geometry and the desired results. If a more detailed simulation is needed, then a finer mesh 

should be used. Be aware that a finer mesh significantly increases the computational running 

time of the model as well as the quantity of output data. 

CFD models have much better spatial fidelity than zone models, being able to distinguish 

conditions in one part of the space from another. Because of the appreciable amount of time 

and effort required to apply CFD models as compared to zone models or algebraic models, CFD 

models are generally applied when: 

 Spatial resolution is important, either relative to the locations of fuel packages or targets. 

 Large compartments relative to the fire size are involved. 

 Compartments have complex geometries, flow connections, or numerous obstructions in 

the upper part of the compartment. 

 Large numbers of compartments are within the area of interest and the presence of each 

compartment is expected to affect the fire environment in the area of interest. 

An example of a CFD fire simulation of a fire experiment is shown in Figure 1-3. The purpose of 

the calculation was to simulate an experiment that was part of the validation study described in 

NUREG-1824 (EPRI 1011999). In the experiment, a pan fire was placed in a relatively small 

compartment, and temperatures and heat fluxes were measured at various locations. The CFD 

simulation is able to describe the changing behavior of the fire as it interacts with its 

surroundings. 
Introduction 

1-11 

Figure 1-3. A CFD visualization of compartment fire experiment. 

While CFD models provide a detailed analysis of a space, they are costly to create, simulate 

and maintain. The input files created in the preprocessing stage require a significant effort to 

create. The user must understand the code syntax and the implications and assumptions 

embedded in the model. A firm understanding of fire dynamics is important in providing input 

data that is relevant to the application. Most CFD models have default values that must be 

recognized and adjusted as necessary if the simulation is going to be accurate. The relevance 

of the default values needs to be confirmed for any application. User manuals and technical 

references for each CFD model outline such values and may provide recommended ranges for 

the parameters. 

Depending on the complexity of the scenario and the computer computational power, the solver 

within the model can take a few hours to weeks to complete all the calculations. This time cost 

depends on the measured parameters, the size of the geometry, and the mesh size of the 

calculations. Outputs of field models are visualized through a post-processing program. The 

CFD model developed at NIST, Fire Dynamics Simulator (FDS), employs the program 

“Smokeview” to represent distributions of temperature, mass, heat flux, burning rate, etc. 

throughout the geometry. These parameters can be described through point locations, 

isocontours, or vector diagrams. Output data may also be stored in a comma-separated value 

file format that can be read by a standard spreadsheet program. 
Introduction 

1-12 

1.4.4 V&V 

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

of their limitations and predictive capabilities. NFPA 805 states that fire models shall only be 

applied within the limitations of the given model and shall be verified and validated. 

Verification is the process of determining that a model preserves the laws of science and math, 

thereby assessing whether it was “built” correctly. In this assessment, the theoretical basis of 

the model is reviewed to confirm that the scientific and mathematical foundation of the model is 

correct, that is, that the laws of physics and chemistry are upheld and proper numerical 

techniques are employed. 

Validation is the process of determining that a model is a suitable representation of the real 

world and is thus capable of reproducing the phenomena of interest. Validating a model 

requires that the output of subroutines or the entire model provide predictions that compare 

reasonably well with experimental data. 

As noted in Section 1.1, the NRC RES and the EPRI conducted a collaborative project for V&V 

of the five selected fire models described in Sections 2.3.1 through 2.3.5 that may be used to 

support RI/PB fire protection and implementation. The results of this project were documented 

in NUREG-1824 (EPRI 1011999), Verification and Validation of Selected Fire Models for 

Nuclear Power Plant Applications. 

1.5 NFPA 805 Fire Modeling Applications 

The NFPA 8054 requirements associated with fire modeling are organized in two sections, 

Section 4.2.4.1 and Section 2.4.1.4. Section 4.2.4.1 describes requirements for the 

implementation of a performance-based fire modeling analysis. Section 2.4.1.4 describes the 

requirements associated with the analytical fire modeling tools selected for the analysis. 

1.5.1 Requirements Associated with the Implementation of a 

Performance Based Fire Modeling Analysis 

NFPA 805 Section 4.2.4.1 describes the process to follow when using fire modeling to address 

variances from deterministic requirements (VFDRs). The term VFDR is currently used in the fire 

protection community within the commercial nuclear industry to refer to plant conditions that 

deviate from deterministic requirements of NFPA 805 Section 4.2.3. Section 4.2.4.1 of NFPA 

805 is subdivided by process element as follows: 

Identify Targets (NFPA 805 § 4.2.4.1.1): This subsection requires the description of the 

VFDRs and the targets (e.g., equipment or cables) and target locations (specific locations of 

raceways/conduits containing the cables, electrical panels, or equipment) associated with them. 

Establish Damage Thresholds (NFPA 805 § 4.2.4.1.2): This subsection requires the 

description of damage thresholds for the equipment and cables needed to achieve the nuclear 

safety performance criteria. The damage threshold (i.e., target vulnerability) for cables exposed 

to fire is expressed in most cases in the form of an incident heat flux on the cables or the cables’ 

surface temperature as follows: 

 

4

 References to NFPA 805 in this document specifically refer to the 2001 Edition, which is the edition 

endorsed in 10 CFR 50.48(c). 
Introduction 

1-13 

Damage or ignition temperature: Temperature at which the target is considered 

damaged or ignited. In the case of cables, the damage and ignition temperatures are 

assumed to be the same. In the context of a Fire PRA, damage refers to the presence 

of a predefined cable failure mode, such as a hot short, a short to ground, etc. 

Damage or ignition incident heat flux: The heat flux received by a target material with the 

intensity necessary to degrade the cable jacket and insulation, exposing the conductors 

and allowing specific cable failure modes. 

Determine Limiting Conditions (NFPA 805 § 4.2.4.1.3): This subsection requires the 

description of the combination of equipment or required cables with the highest susceptibility to 

any fire environment. This determination is needed since multiple targets (or cables) may 

appear in the same VFDR, or multiple VFDRs may have been identified in the fire area. These 

targets (or cables) may be located in various parts of the fire area and may thus be exposed to 

various fire sources and fire-generated conditions. The above consideration may lead to the 

selection of more than one limiting condition. 

Establish Fire Scenarios (NFPA 805 § 4.2.4.1.4): This subsection requires the description of 

the fire conditions for the area under consideration resulting from the identified and analyzed fire 

scenarios. It should be noted that the scenario definition is consistent with the requirements 

listed under § 2.4.1.3 of NFPA 805 as follows: 

Maximum Expected Fire Scenario: The maximum expected fire scenario (MEFS) is 

defined in NFPA 805 as the scenario that “represents the most challenging fire that 

could be reasonably anticipated in the occupancy type and conditions in the space.” 

The definition continues to indicate that the scenarios “can be established based on 

electric power industry experience with consideration for plant-specific conditions and 

fire experience.” Establishing the MEFS involves defining the problem in sufficient detail 

to perform calculations and to ensure that the input parameter set represents reasonable 

conditions. 

Limiting Fire Scenario: The limiting fire scenario (LFS) is defined in NFPA 805 as the 

scenario in which “one or more of the inputs to the fire modeling calculation are varied to 

the point that the performance criteria are not met.” Development of the LFS essentially 

involves a sensitivity analysis that identifies which combinations of input parameters or 

variables are critical to the analysis. The intent of LFS development is to determine if 

there is a reasonable margin between the MEFS and the point of failure. 

For each fire scenario, the environmental conditions resulting from each MEFS are compared to 

the damage thresholds for the targets in the fire area. If damage thresholds are not exceeded, 

the targets associated with the VFDR in the fire area can be considered free of fire damage 

under the conditions of the postulated MEFS. 

By definition, the effects of the LFS include damage to the targets in the fire area under 

consideration. Fire modeling parameters that have been varied to establish the LFS conditions 

are identified and described. 

Protection of Required Nuclear Safety Success Paths (NFPA 805 § 4.2.4.1.5): This section 

requires the description of the effectiveness of fire protection systems and features in protecting 

and maintaining the operation of the circuits and components associated with the VFDRs. 
Introduction 

1-14 

Operations Guidance (NFPA 805 § 4.2.4.1.6): This section requires the description of any 

operational guidance to plant personnel, including the performance of recovery actions based 

on the fire modeling analysis assumptions, inputs and results in the corresponding fire area. 

1.5.2 Requirements Associated with the Selected Analytical Fire 

Models 

Section 2.4.1.2 describes the requirements for the use of fire models, which include: 

 The use of fire models acceptable to the authority having jurisdiction (i.e., the US 

Nuclear Regulatory Commission) 

 The application of fire models within their range and limitations. Section 2 of this 

document provides guidance on ensuring the model is within the range of limitations and 

what steps are necessary if the application is outside existing V&V data ranges 

NFPA 805 stipulates that the fire models used shall be verified and validated. In the context of 

this application, the specific analytical capabilities within the fire model need to be verified and 

validated. Model capabilities not invoked in specific calculation are outside the scope of this 

requirement. NUREG-1824 (EPRI 1011999) is an example of a verification and validation study 

for fire models specifically developed for NPP applications. Refer to Section 2 of this document 

for guidance on ensuring specific fire model applications are within the scope of existing V&V 

studies or what steps should be taken if they are not. 

1.6 Fire Modeling in Support of Fire PRA 

The Fire PRA primarily applies fire modeling in the fire scenario development and analysis 

process. A fire scenario in a Fire PRA is often modeled as a progression of damage states over 

time, which is initiated by a postulated fire involving an ignition source. Each damage state is 

characterized by a time and a set of targets damaged within that time. Fire modeling is used to 

determine the targets affected in each damage state and the associated time at which this 

occurs. The first damage state usually consists of damage only to the ignition source itself. 

Depending on the characteristics and configuration of the scenario, the last damage state may 

consist of an HGL formation that leads to a full room burnout. Damage states between the first 

and final states capture target sets compromised as the fire propagates through intervening 

combustibles. Figure 1-4 depicts an example of scenario progression through five damage 

states. 

 
Introduction 

1-15 

Ignition 

Damage State 1 

(Ignition Source 

Only) 

Damage State 

2 

Damage State 

3 

Damage State 4 

(Hot Gas Layer) 

 

 No additional damage outside the ignition source 

 

 No damage outside target set 1 

 t = t1 

 No damage outside target set 2 

 t = t2 

 

No damage outside target set 

3 

 t = t3 

 t = t4 

Figure 1-4: Event tree depicting scenario progression modeled in a Fire PRA 

The initiating event (ignition) is characterized by the ignition source frequency. The first damage 

state captures the event in which damage is limited to the ignition source itself. The time t1 (as 

well as any subsequent time milestones in the progression) at which this damage is postulated 

can be determined using fire modeling tools. Fire modeling tools are also used to determine 

which targets are damaged. The second and third damage states capture additional targets as 

the fire continues to grow or propagate through intervening combustibles. In this example, the 

fourth damage state is associated with HGL formation (i.e., compartment-wide damage or full 

room burnout). 

Each scenario progression postulated in a Fire PRA is quantified to determine its contribution to 

fire risk. The fire risk metrics are Core Damage Frequency (CDF) and Large Early Release 

Frequency (LERF). The CDF is quantified using the following equation: 

൯௝݌ܿܿ݀ · ௝,ேௌܲ௝ · ܨܵ൫௜ · ෍ߣ ൌ௜ ܨܦܥ

௡

௝ୀଵ

(1-1) 

Where i is the fire scenario associated with the ignition source, j is the damage state postulated 

in the scenario (the maximum number of damage states postulated, n, equals 4 in the 

conceptual example presented in Figure 1-4), ߣ ௜is the ignition frequency, SFj is the severity 

factor for damage state j, PNS,j is the non-suppression probability for damage state j, and ccdpj is 

the conditional core damage probability associated with the damage state represented in that 

branch of the event tree. Simply stated, the equation above is used to quantify CDF of a 

scenario where a fire: 

 (௜ߣ) Initiates 1.

2. Grows large enough to damage targets external to the ignition source (SF) 

3. Is not controlled or suppressed (PNS) 

4. Generates the potential for core damage conditions (ccdp) 
Introduction 

1-16 

The severity factor, SFj, represents the fraction of fires associated with each damage state. SFj

is calculated by first determining the minimum fire size required to damage the nearest target. 

For example, if a target is located in the plume at a certain height above the fire source, the 

minimum Heat Release Rate (HRR) required to damage that target could be calculated using 

Heskestad’s plume correlation (Heskestad, 2008). This minimum HRR can then be compared 

to an HRR probability distribution characterizing the ignition source to determine the fraction of 

fire intensities that would exceed the critical value. Figure 1-5 provides a conceptual 

representation of the severity factor parameter. 

Figure 1-5: Conceptual representation of the severity factor 

The non-suppression probability, PNS, represents the probability of automatic and manual fire 

suppression systems failing to suppress the fire prior to it damaging targets within the 

postulated damage state. Fire modeling can lend support to the calculation of this term 

because target damage and the response of detection and suppression systems are functions 

of time. 

The ccdp represents the probability of core damage given that the target damage for that 

damage state occurs. Fire modeling can be used in the calculation of ccdp by identifying which 

targets have failed within that damage state. For example, the dimensions of the physical 

space where damage is expected, referred to as the zone of influence of the fire, can be 

determined using radiation, plume, and ceiling jet correlations. The target failures can then be 

mapped into the plant response model (i.e., the PRA model), which is quantified to calculate 

scenario ccdp. 
Introduction 

1-17 

The Fire PRA standard (ASME/ANS RA-Sa-2008 and Addenda RA-Sa-2009), which lists 

requirements for all the technical elements associated with a Fire PRA, includes specific 

requirements for the use of fire models. 

In terms of the models itself, the standard addresses (1) the selection of appropriate fire 

modeling tools for estimating fire growth and damage behavior, considering the physical 

behaviors relevant to the selected fire scenarios, and (2) implementation of fire models that are 

sufficiently capable of modeling the conditions of interest within known limits of applicability. In 

the case of analytical fire models, the standard requires the use of appropriate fire modeling 

tools with the ability to model the conditions of interest within known limits of applicability. It 

should be noted that the Fire PRA standard does not explicitly require fire models to be verified 

and validated (as is the case of Section 2.4.1.2 in NFPA 805). However, the term “known limits 

of applicability” from the Supporting Level Requirement FSS-D2 is intended to ensure the 

availability of appropriate technical justification for the use of the model in specific applications. 

In this context, V&V results as discussed and applied in this guide can serve as appropriate 

justification, but the standard does not limit analytical fire model applications to specific 

verification and validation ranges. 

In terms of input parameters, the standard requires a technical basis for fire modeling tool input 

values used in the analysis, given the context of the fire scenarios being analyzed. 

The requirements listed above not only apply to analytical fire models (which are the primary 

scope of this report) but also apply to any empirical or statistical model that may be used in the 

Fire PRA to assess the extent and timing of fire conditions. Requirements associated with 

these types of models include (1) establishing a technical basis for any applied statistical 

models in the context of the fire scenarios being analyzed, and (2) establishing a technical basis 

for any applied algebraic models in the context of the fire scenarios being analyzed. 

1.7 MSO Fire Modeling Applications 

The disposition of specific Multiple Spurious Operation (MSO) interactions is another type of fire 

modeling application frequently encountered in commercial NPPs. MSOs involve one or more 

fire-induced component failures that include spurious operation due to hot shorts as a result of 

fire damage to electrical control cables. The consideration of MSOs arises from the post-fire 

safe shutdown circuit analysis. MSOs are divided into two categories: those involving 

components necessary for safe shutdown (“green box”) and those involving components that 

could adversely affect the shutdown capability or cause safe shutdown systems to fail (“orange 

box”) (NEI 00-01, Rev. 2). Because MSOs are induced by circuit damage, the threshold 

conditions under which an MSO is postulated are typically those associated with cable failure; 

however, there may be situations involving a sensitive component with a lower damage 

threshold, such as a transmitter or a relay. 

Green box MSOs need to be addressed by means other than fire modeling (NEI 00-01, Rev. 2; 

RG 1.189, Rev. 2). Orange box MSOs may be evaluated using fire modeling tools (NEI 00-01, 

Rev. 2; RG 1.189, Rev. 2). When two or more circuits are involved, the fire modeling objective 

is to demonstrate that at least one circuit remains free of damage for the postulated fire 
Introduction 

1-18 

scenario. If the MSO is successfully dispositioned using fire modeling tools, it would show that 

the damage necessary to cause the MSO would not occur for the postulated fire scenario while 

there is a reasonable margin of safety. 

Orange box MSO fire modeling is similar to the deterministic fire modeling described in NFPA 

805. NEI 00-01, Section 4.5.2.2 outlines a process that should be followed when attempting to 

disposition orange box MSO interactions. Key aspects of the analysis process are as follows: 

 Ignition sources are characterized by the 98th percentile severity fire as defined in 

NUREG/CR-6850 (EPRI 1011989) 

 Transient combustible materials are assumed anywhere in the plant unless it is 

physically impossible 

 Fire modeling tools should be verified and validated for the application 

 Fire modeling should be performed in a manner consistent with the methods described 

in NUREG/CR-6850 (EPRI 1011989). Consideration of process enhancements in NFPA 

805 is encouraged 

 The analysis should include an assessment of model sensitivity to uncertainty 

RG 1.189 (2009) emphasizes the need for a V&V basis for the selected fire model. Section 

5.3.1.4 of RG 1.189 recommends demonstrating a reasonable safety margin (which assists in 

the uncertainty and sensitivity analysis) or providing fixed automatic suppression. A reasonable 

safety margin is left undefined, but it should at least be larger than the results sensitivity to the 

model uncertainties. Section 2 of this guide addresses the means by which a V&V basis is 

demonstrated for a fire model application. 

In the simplest applications, a fire modeling analysis would be used to show that at least one 

circuit in the MSO interaction remains free of damage for a set of fire scenarios postulated in the 

area of interest. As a minimum, when two or more circuits are involved in the MSO interaction, 

the fixed or transient fuel package fire that is nearest to all circuits involved (i.e., the “pinch 

point”) is evaluated. As with other fire modeling applications, care is necessary in selecting the 

most appropriate location and the model that captures all relevant exposure mechanisms. The 

analysis can become complicated when it is found that the MSO could occur, given the 

postulated fire. MSO interactions frequently have a time component, especially if there is an 

operator action taken elsewhere that mitigates the MSO but a specific amount of time is needed 

to perform the action. In this case, the timing of the MSO event becomes a significant aspect of 

the analysis and a successful outcome could be predicted if failure occurs after the operator 

action has taken place, provided there is a reasonable margin of safety. 

The process described in NEI 00-01, Rev. 2 is fairly specific in terms of the types of fires and 

their location to postulate. NE 00-01, Draft Rev. 3 provides additional guidance on the selection 

of fires and the ability to credit existing fire protection features, such as combustible free zones 

or spaces that normally would not contain combustible material. If a specific feature were 

credited, the postulated fire size would reflect the conditions present and would not necessarily 
Introduction 

1-19 

be equal to a generic 98th percentile. In this regard, the fire selection process is analogous to 

the NFPA 805 MEFS. 

Passive fire protection systems, such as fire-rated barriers, Electrical Raceway Fire Barrier 

Systems (ERFBS), and thermal insulation, may be credited, though the performance of these 

systems would need to be demonstrated under the postulated conditions. There is no specific 

guidance on the means by which active systems may be credited, including fixed suppression or 

manual intervention, in either version of NEI 00-01; however, it would be consistent with the 

original intent to credit these features if the potential for success is in the 98th percentile. It 

should be noted, however, that at this writing NEI 00-01 Draft Rev. 3 has not yet been endorsed 

by the NRC, but that its methods and guidance are consistent with NFPA 805. 

1.8 Organization of the Guide 

The guidance material provided in this document is divided into four chapters and a number of 

appendices, as outlined below. 

 Chapter 2 presents a qualitative overview of the process for conducting fire modeling, 

including the basic principles of fire simulation, advantages and limitations of the 

technology, and brief descriptions of the five models 

 Chapter 3 provides specific guidance on selecting models to address typical scenarios in 

commercial nuclear power plants 

 Chapter 4 contains information on determining the sensitivity and uncertainty associated 

with fire modeling calculations 

 Chapter 5 contains the list of references identified throughout this document 

 Appendices A through H provide detailed examples of fire modeling analyses of typical 

NPP scenarios: 

o Appendix A – Cabinet Fire in Main Control Room 

o Appendix B – Cabinet Fire in Switchgear Room 

o Appendix C – Lubricating Oil Fire in Pump Compartment 

o Appendix D – Motor Control Center Fire in Switchgear Room 

o Appendix E – Trash Fire in Cable Spreading Room 

o Appendix F – Lubricating Oil Fire in Turbine Room 

o Appendix G – Transient Fire in Multi-Compartment Corridor 

o Appendix H – Cable Tray Fire in Annulus 

 
Introduction 

1-20 
2-1 

2

THE FIRE MODELING PROCESS 

This chapter provides a general step-by-step process for modeling fires in commercial nuclear 

power plants. The recommended methodology comprises six steps: (1) define fire modeling 

goals, (2) characterize the fire scenarios, (3) select fire models, (4) calculate fire-generated 

conditions, (5) conduct sensitivity and uncertainty analyses, and (6) document the analysis. A 

simplified process involving the six steps is shown in Figure 2-1. 

 

Start

Define fire modeling

goals (Section 2.1)

Characterize fire 

scenarios (Section 2.2)

Select fire 

models (Section 2.3)

Is model 

suitable?

Is 

another

model 

available?

Can

problem

be redefined?

An alternate analysis

may be required

End

Calculate fire generated

conditions (Section 2.4)

Conduct sensitivity

and uncertainty 

analyses(Section 2.5)

Are 

goals 

addressed?

Document the analysis

(Section 2.6)

End

Yes

No No

No

Yes Yes

Yes

No

Figure 2-1. Fire Modeling Process 
The Fire Modeling Process 

2-2 

2.1 Step 1: Define Fire Modeling Goals 

The first step in a fire model analysis is to identify and state the fire modeling goals. A clearly 

defined goal provides focus and is needed to correctly select the fire scenarios that will be 

evaluated and the fire modeling tools that will be used. The goal should be specific, and it 

should describe the end result in engineering terms. This implies some understanding of the 

conditions by which success or failure are measured (i.e., the performance criteria) at the 

analysis outset. The goal(s) should also identify whether the analysis results are intended to 

help resolve a deterministic issue or are intended as input for a probabilistic risk assessment 

(PRA). This distinction can affect the types of fire scenarios that would be evaluated, as well as 

the treatment of uncertainty in the analysis. 

Any fire modeling goal may thus be viewed as a statement defining what needs to be 

accomplished, which criteria will be used to define success or failure, and which analysis 

process will be followed (e.g., probabilistic or deterministic). The criteria should be stated in 

terms that can be achieved by the fire modeling analysis. Some common situations in 

commercial nuclear power plants where fire modeling may be used include: 

 Evaluating whether or when a fire could damage a single electrical cable or component 

 Evaluating whether or when a fire could damage multiple electrical cables or 

components 

 Evaluating whether conditions are habitable in an enclosure 

 Evaluating the potential for fire propagation through or across a fire barrier 

 Evaluating detection or sprinkler actuation 

 Evaluating the potential for fire propagation between fire zones or fire areas, or to 

secondary combustibles 

The performance criteria will be specific to the fire modeling application, but will often include 

one or more of the following: 

 Maximum acceptable surface temperature for a cable, component, secondary 

combustible, structural element, or fire-rated construction 

 Maximum acceptable incident heat flux for a cable, component, structural element, or 

secondary combustible 

 Maximum acceptable exposure temperature for a cable, component, structural element, 

or secondary combustible 

 Maximum acceptable enclosure temperature 

 Maximum smoke concentration or minimum visibility 

 Maximum or minimum concentration of one or more gas constituents, such as carbon 

monoxide, oxygen, hydrogen cyanide, etc. 
The Fire Modeling Process 

2-3 

The performance criteria may also involve sequences of events, such as “detection or sprinkler 

actuation before cable damage, which occurs when the surface temperature reaches 330 °C 

(625 °F).” NUREG/CR-6850 (EPRI 1011989) provides some performance thresholds for 

common nuclear power plant targets (see, for example, Appendix H) as well as for habitability 

(for example, Section 11.5.2.11). 

A few simple examples will illustrate the various ways in which a fire modeling goal may be 

stated. In many nuclear power plant fire modeling applications, the motivation for a fire 

modeling analysis is a need to know whether or not an electrical cable or a component remains 

free of damage from a fire. This could be very specific (i.e., a particular exposure fire exposing 

a particular cable) or general (i.e., the maximum distance from which a particular type of fire 

could damage cables). In addition, it may only be necessary for a single fire to damage a single 

cable, or it may be necessary to simultaneously damage two particular cables with a known 

separation. If the particular cable or cables in the area of interest are physically damaged when 

the surface temperature exceeds 330 °C (625 °F), the following goals could apply: 

 “Deterministically evaluate whether a fire in Fire Area “X” involving Panel “Y” could 

cause the surface temperature of Cable “Z” to exceed 330 °C (625 °F).” 

 “Evaluate the maximum distance from any surface of an electrical panel that a 98th

percentile heat release rate fire in Fire Zone “X” could cause a cable surface 

temperature to exceed 330 °C (625 °F) for use in screening ignition sources in the PRA.” 

 “Deterministically evaluate whether a fire in Fire Area “X” involving a transient fuel 

package could cause the surface temperature of both Cables “Y” and “Z” to exceed 

330 °C (625 °F).” 

 “Determine for PRA input if any ignition sources in Fire Zone “X” could damage cables in 

Raceway “Y” before the sprinkler system actuates.” 

Each of the goals explicitly states the purpose of the analysis and the means by which success 

is determined in terms that can be achieved by a fire modeling analysis. 

2.2 Step 2: Characterize Fire Scenarios 

The second step in the fire modeling process is to characterize the relevant fire scenarios that 

capture those technical elements necessary to address the goals. A fire scenario is defined 

within this guide as a set of elements needed to describe a fire event. These elements usually 

include the following: 

 the enclosure details (i.e., compartment) 

 the fire location within the enclosure 

 the fire protection features that will be credited 

 the ventilation conditions 

 the target locations 

 the secondary combustibles 

 the fire, which is sometimes referred to as the “ignition source” 
The Fire Modeling Process 

2-4 

A number of the fire scenario elements may also be viewed as fire model input. Section 3 

provides additional guidance on specific fire scenario elements as they apply to various fire 

modeling goals evaluated with a particular fire model. This section provides a broad 

perspective on the considerations that apply when formulating the appropriate fire scenario, 

given a fire modeling goal. 

Note that when characterizing the fire scenarios, preliminary consideration should also be given 

to how many scenarios are needed to address a particular goal and which specific fire event 

characteristics each scenario should capture (i.e., which scenarios are needed). In general, at 

least one fire scenario would be necessary to assess the effects for a single ignition sourcetarget set pair. The analyst should become familiar with the information necessary to develop 

input files for the fire modeling tools. In practice, this information should be collected during the 

process of selecting and describing fire scenarios to minimize the number of walkdowns and 

document/drawing reviews. 

2.2.1 General Considerations 

Various documents provide guidance for describing fire scenarios from a technical and 

regulatory perspective. Most of these documents are “application”-specific; for instance, NFPA 

805 defines two general categories of fire scenarios, limiting fire scenarios (LFSs) and 

maximum expected fire scenarios (MEFSs). The input values necessary to determine the 

MEFS should be best estimates of the actual parameter values. The input values for the LFS 

can exceed those which are probable or even possible. The margin between the LFSs and the 

MEFSs can be used to identify those weaknesses in the analysis that could result in 

unacceptable effects. 

In a Fire PRA, for example, the goal is to quantify the risk contribution from individual scenarios 

and to identify potential risk-contributing scenarios (e.g., fires impacting important targets in the 

compartment). Although specific elements in the scenario selection process are “standardized” 

for guidance and completeness purposes, a certain degree of fire protection engineering 

judgment is also necessary. NUREG/CR-6850 (EPRI 1011989) contains information on fire 

frequency, cable (target) selection, heat release rate (HRR), damage criteria, and other 

information that would be useful in developing fire scenarios. 

Selected scenarios should represent a complete set of fire conditions that are important to the 

fire modeling goal. For example, if the goal of the fire modeling analysis is to estimate whether 

specific cable(s) will remain free of fire damage, the analyst should examine consider exposures 

that are close to the cables as well as exposures that are farther away. A small, localized fire 

exposure could be a greater challenge than a larger fire that is farther away, or vice versa. It 

may not always be appropriate to select, or at times even possible to define, the worst case fire 

scenario prior to conducting the analysis, due to the different exposure mechanisms associated 

with various ignition sources. In large enclosures with a limited number of targets to protect, 

such as a turbine building in a Pressurized Water Reactor (PWR) when the protection of a 

safety-related circuit is the fire modeling goal, it is easier to locate the targets of interest and 

then identify those fire sources capable of affecting that target. 

When attempting to characterize the fire scenario, plant walkdowns should be an essential 

aspect of the scenario selection. Many key decisions relevant to fire modeling, including those 

related to model selection and input parameters, and are influenced by observations made 

during walkdowns. The occupants, the access level to a particular area, and the fire brigade/fire 

department access should be observed during the walkdowns, as applicable. 
The Fire Modeling Process 

2-5 

It should also be noted that not all the elements associated with a commercial nuclear plant fire 

scenario can be directly modeled using the tools within the scope of this guide (e.g., the effect of 

suppression activities by the fire brigade or the conditions in a space after a sprinkler system 

has actuated). It is important, however, not to limit the scenario selection and description to 

those elements that can be modeled. 

2.2.2 Enclosure Details 

The enclosure details include the identity of the enclosures that belong in the fire model 

analysis, the physical dimensions of the enclosures included in the fire model, and the boundary 

materials of each enclosure. The enclosure(s) that belong in the fire model may depend on the 

fire modeling goal, the complexity and connectivity of the spaces in the general area of interest, 

the type of analysis conducted (deterministic or probabilistic), and the type of fire model 

selected. It is possible that no enclosure may be involved, as would be the case for an exterior 

transformer fire. As a minimum, the space containing the fire would normally be included in the 

fire model, though treatments involving empirical plume temperature or flame height correlations 

would not model the enclosure effects per se. Multiple enclosures might be necessary if there 

are flow connections (natural or forced) to adjacent areas and if the conditions in both areas 

could affect the analysis results or are of interest. Care should be taken to consider the 

potential effects of fires in adjacent areas on the targets of interest. In some cases, an HVAC 

recirculation system may involve areas that are fairly remote from the area of interest. 

Depending on the type of analysis conducted, the conditions within either or both areas may be 

of interest, and the fire model would thus include both spaces. 

The physical dimensions of the enclosure and the boundary materials are model input and 

should be determined once the fire model has been selected, since the level of detail varies 

considerably among the fire models. One-zone models may only require a volume and 

boundary area; two-zone models will typically require the length, width, and height; and CFDtype models will require details commensurate with the model grid resolution. The 

determination of the correct physical dimensions and boundary materials are described in 

Chapter 3 for various types of nuclear power plant fire scenarios. 

2.2.3 Fire Location 

The location of the fire will depend strongly on the fire modeling goal, the target location, and 

the fire modeling tool selected. For example, when evaluating the performance of a fire barrier 

system, fire scenarios challenging the barriers are of interest; when conducting a risk analysis, 

fire scenarios impacting safety-related circuits may be of primary interest. The selected 

scenarios for these two applications may not be the same. 

When selecting the fire location, the fire scenario should challenge the conditions being 

estimated. For example, if the goal is to evaluate flame radiation to a target, locating the ignition 

source relatively far from the target may not provide the best representation of the fire hazards. 

If the goal is to determine whether a fire can cause two circuits in different raceways to fail, it 

may be appropriate to locate the fire between the two raceways. There will be situations in 

which the target location is fixed within the plan area of a space, but there is some flexibility in 

the vertical placement. A good example of this is an electrical panel fire. For a given electrical 

panel, the floor position is fixed; however, the base of the fire is not. Depending on the type of 

panel, it may be appropriate to locate the fire base at the panel floor (e.g., open back and 

containing thermoplastic cables), at the top (open top and no side vents), or somewhere in 
The Fire Modeling Process 

2-6 

between. EPRI 1019259 (2009) recommends a fire elevation equal to the top of the upper vent 

or 0.3 m (1 ft) below the panel top for panels meeting certain physical constraints. 

In the case of transient fuel package fires or other types of fires that are not fixed, some 

consideration of the effects of the wall or corner on the upper gas layer temperature is 

necessary. If the primary exposure mechanism is the Hot Gas Layer (HGL), assuming the fire 

is located in a corner or near a vertical boundary will produce higher HGL temperatures. 

However, if the analysis is performed in support of a PRA, then multiple locations should be 

postulated and the results weighted accordingly. Other features that affect the fire location 

could include the presence or slope of a floor, particularly when a melting plastic or liquid 

hydrocarbon fuel is considered and transient fuel packages may be staged on mezzanine 

levels, scaffolding, or platforms. 

The following general guidelines and considerations for locating the fire for different fire 

exposure mechanisms may be followed as applicable: 

 Targets in the fire plume or ceiling jet. Locating a source on top of a cabinet ignition 

source usually results in the most severe fire conditions, since it assumes that cabinet 

walls will not affect fire-generated conditions. Furthermore, since the fire is located in 

the highest possible position, flames are expected to be higher, and temperatures in the 

plume and ceiling jet will also be high. The user should judge whether this is a 

conservative assumption based on the goal of the analysis. For example, this would not 

necessarily be a conservative assumption if detection of the fire was a critical aspect of 

the analysis. 

 Targets affected by flame radiation. Combustible materials that are not fixed, such as 

transient fuel packages and unconfined liquid spills, should be located so that there is an 

unobstructed (assuming that no passive fire protection system is credited) view between 

the source and the target. A horizontal path between flame and target provides the 

highest heat flux to the target. 

 Targets engulfed in flames. Flame height calculations should be performed to determine 

whether the selected location will result in targets engulfed in flames. Proper justification 

should be provided as to the location of the fire to ensure that the target is out of the 

flames. For example, consider the case where the analyst locates the fire on top of an 

enclosed cabinet, resulting in a cable tray engulfed in flames. This would represent the 

most severe exposure for the cable tray since the fire is expected to start somewhere 

inside the cabinet. The analyst may choose to lower the fire’s position and ignore the 

cabinet walls after a visual examination identifies the actual location of the combustibles. 

 Targets immersed in the Hot Gas Layer. The fire’s elevation may influence how far 

down the Hot Gas Layer will develop as predicted by some fire models, although other 

important scenario characteristics will also be influential. 

2.2.4 Credited Fire Protection 

The fire protection features that will be credited in a fire modeling analysis usually require a fire 

protection engineering evaluation of the system’s effectiveness in performing its design 

objectives. This may include both an assessment of the system compliance with applicable 

codes, including maintenance and inspection, and an assessment of the system performance 

against the particular fire scenario considered. The evaluation should determine whether the 
The Fire Modeling Process 

2-7 

detection, suppression, and/or passive systems can protect the selected target from firegenerated conditions. Once the decision to credit a fire protection system is made, the analyst 

should specify the type of system selected for the scenario. 

There are several common fire protection features that may be present in a typical nuclear 

power plant area: 

 Fire detection systems. These include smoke, heat detectors, or high sensitivity 

detection systems 

 Fire suppression systems. These include automatic or manually activated fixed 

systems, fire extinguishers, and fire brigades 

 Passive fire protection systems. These include structural fire barriers, fire doors, 

ERFBS’s, radiant shields, and fire stops 

 Administrative controls. These include combustible or transient-free zones, combustible 

fuel load limits, and hotwork procedures 

When assessing the performance of a system against the postulated fire hazard, it is necessary 

to consider the conditions under which the system is designed (fire size, fuel load, exposure 

temperature, plant operation mode, etc.). For example, an ordinary hazard sprinkler system 

may not have a sufficient water spray delivery to protect against a large hydrocarbon pool fire. 

Another example would be passive fire protection systems that are rated against an ASTM 

E119 (2008) fire exposure. Such systems may not provide sufficient fire resistance for a flame 

impingement fire exposure or a hydrocarbon pool fire scenario. In addition, for active fire 

protection systems, a valid set of response characteristics of the system are needed. 

When crediting a manually actuated fixed suppression system or manual intervention, additional 

information relating to the occupants, the fire brigade, and the fire department are usually 

necessary. This may include the means of access to the area considered, the presence of a fire 

watch, the potential for plant personnel to be in the area, etc. 

Notice that the fire modeling tools within the scope of this guide may not have the capability to 

model the impact of some of the fire protection features that may be credited in a given 

scenario. Nevertheless, fire protection features are designed to impact the outcome of a 

scenario, so their effects should be included in the analysis. 

2.2.5 Ventilation Conditions 

Ventilation conditions collectively refer to the operation of the mechanical ventilation system 

(e.g., the system will continue in normal operational mode, the system will transfer to smoke 

purge mode, the system will transfer off with close dampers, etc.) and the position of doors or 

other openings during the fire event (e.g., doors closed, doors open, doors opening at fire 

brigade arrival, etc.). Typically, both normal and off-normal ventilation conditions are 

considered. Spaces in which doors are normally closed may have the doors propped open or 

opened during the fire by plant personnel, or damaged during the fire. HVAC flows that are 

normally present in a space may change during the fire due to dampers closing, activation of 

purge modes, filter plugging, or fan damage by the hot gases. Characterization of the flow field 

from mechanical devices may be important in some scenarios, especially if the inlet or outlet of 

the mechanical system is in close proximity to the fire or target. 
The Fire Modeling Process 

2-8 

2.2.6 Target Locations 

The target location refers to the physical dimensions of the target relative to the source fire or 

the fire model coordinate system. These could include the horizontal and vertical distance from 

the ignition source or source fire or the spatial position within the room itself. It may be 

necessary to further specify the location of a vulnerable portion of a target, such as the junction 

box on a service water pump motor. The orientation of the target with respect to the exposure 

fire may be of interest as well. An elevated target that is exposed only in the vertically upward 

direction may be susceptible to thermal radiation from an HGL, but possibly shielded from 

thermal radiation from the source fire itself. Note that in some types of analyses (e.g., a control 

room abandonment calculation), occupants may be a target. 

The fire exposure mechanisms should also be assessed when quantifying the target location. 

Fire exposure mechanisms, such as flame impingement, fire plume, ceiling jets, HGLs, and/or 

flame radiation, should be considered based on the relative location of the ignition source, 

intervening combustibles, and the targets. The subsequent fire model analysis should quantify 

relevant fire conditions and include a discussion of the proper disposition of those that are not 

expected to affect the target. 

2.2.7 Secondary Combustibles 

Secondary combustibles include any combustible materials that, if ignited, could affect the 

exposure conditions to the target set considered. Intervening combustibles, which are 

classically assumed to be those combustibles that are located between the ignition source or 

source fire and the target, are examples of secondary combustibles. However, secondary 

combustibles would also include combustible materials that are not between the fire and the 

target but are exposed to the fire effects. In this case, if the secondary combustibles were to 

ignite, the total heat release rate in the enclosure (if applicable) would increase, resulting in a 

hotter gas layer, and the radiant energy from the burning secondary combustible would 

augment the exposure from the initial source fire, regardless of its location. 

Secondary combustibles would include both fixed and transient materials. Typical fixed 

combustibles include exposed cable jackets or cable insulation, combustible thermal insulation, 

and combustible wall lining materials. Transient combustibles vary considerably from plant to 

plant and plant area to plant area, but they may include trash containers, waste accumulations, 

hoses, hand tools, cleaners and solvents, protective clothing, plastic containers, and so on. It is 

essential to perform a visual survey of an area to obtain an understanding of the types of 

combustibles present and the activities in the space, which can provide insight into the types of 

combustibles that may be present from time to time. The combustible load calculations, fire 

protection procedures, and fire hazards analysis could provide additional details on the nature of 

fixed and transient fuel packages in a particular plant area. 

Combustible materials in sealed or rated containers may be excluded from consideration if the 

container is capable of resisting the effects of the fire. Some examples include cabinets 

containing flammable liquids, solid bottom cable trays with fixed top covers, and bus ducts. 

Secondary combustibles will take on the characteristics of a target prior to their ignition (see 

Section 2.2.6). In this regard, the physical location and orientation of the secondary 

combustibles with respect to both the ignition source and the target set are determined. The 

performance criterion for a secondary combustible target is the ignition condition, which will 
The Fire Modeling Process 

2-9 

usually be a critical radiant heat flux or exposure temperature or an integrated heat flux. Unlike 

a true target, once the performance criterion has been met, the secondary combustible is 

assumed to ignite and then takes on the characteristics of a second source fire (see Section 

2.2.8). 

2.2.8 Source Fire 

The source fire is the forcing function for the fire scenario. As all fire effects are directly related 

to the characterization of the source fire, great care must be taken in characterizing it. A source 

fire is often described as the “ignition source,” which introduces the concept of having both a 

fuel package and a credible ignition mechanism. There are many ignition mechanisms in a 

nuclear power plant; however, ignition sources are typically grouped into electrical panels, 

transient fuel packages, self-ignited cable trays, hotwork-ignited cable fires, and overheated 

motors. A deterministic analysis will typically assume that an ignition source is present and treat 

any combustible material as potentially ignited. 

Common fuel packages include electrical panels and transformers, cables, transient 

combustible material, lubricant reservoirs, and motors. Transient combustibles can vary 

considerably and may include trash containers, waste accumulations, hoses, hand tools, 

cleaners and solvents, protective clothing, plastic containers, and so on. It is essential to 

perform a visual survey of an area to obtain an understanding of the types of combustibles 

present and the activities in the space, which can provide insight into the types of combustibles 

that may be present from time to time. The combustible load calculations, fire protection 

procedures, and the fire hazards analysis could provide additional details on the nature of fixed 

and transient fuel packages in a particular plant area. 

The source fire is typically characterized by a heat release rate, though other important aspects 

include the physical dimensions of the burning object, its composition, and its behavior when 

burning. The heat release rate may be specified as a continuous function of time (e.g., a t

2

 fire), 

or it may be an array of heat release rate and time data. Algebraic models may only permit a 

constant heat release rate. There may be situations in which the heat release rate is a function 

of the ventilation rather than the object burning. Burning behaviors that may need consideration 

include whether the material can melt and form a liquid pool, whether it can spread by dripping, 

and where a liquid could pool. 

When fire modeling is used to support a fire PRA, the heat release rate for a source fire may be 

represented as a frequency distribution. In this case, depending on the type of analysis, a 

conservative screening value may be selected (e.g., a 98th percentile peak heat release rate), or 

the effects may be represented using multiple points on the frequency distribution. 

As was the case with secondary combustibles, combustible materials in sealed or rated 

containers may be excluded from consideration if the container is capable of resisting the 

effects of the fire. In addition, self-ignited cable fires are generally postulated only for non-IEEE383 qualified power cables (NUREG/CR-6850/ EPRI 1011989). 

2.3 Step 3: Select Fire Models 

A number of models are available for performing fire simulations. These models range from 

algebraic models to sophisticated computational fluid dynamics (CFD) computer codes that 

require days to set up a scenario and perform the associated calculations. Given the availability 

of different models, the analyst is responsible for understanding the advantages and limitations 

of a particular model in a specific situation in order to achieve the established goals. In general, 
The Fire Modeling Process 

2-10 

fire models can be classified into three groups: (1) algebraic models, (2) zone models, and (3) 

CFD models. The level of effort required to describe a scenario and the computational time 

consumed by each group increase in the order in which they are listed. Table 2-1 provides a 

summary of the three groups of models, their advantages and disadvantages, and typical 

applications. 

In practical fire modeling applications, it is likely that a combination of all three types of models 

would be useful for analyzing a specific problem. For example, algebraic models might be used 

to estimate the radiative flux to a target for determination of a zone of influence or minimum 

separation distance. A zone model would provide the temperature of the HGL and height as a 

function of time for evaluating cable temperatures. CFD model calculations could be used to 

provide more detailed information on fire-induced conditions in areas where the algebraic 

models and zone models are not conclusive. Complex models can also be used as a means of 

estimating the degree of conservatism in a simple model analysis. 

The first step in selecting a model is to determine whether the scenario can be analyzed using 

algebraic models, zone models, or CFD models. This guide focuses on the models: FDTs

(NUREG-1805, 2004), FIVE-Rev1 (EPRI 1002981, 2002), CFAST (Jones et al., 2004), MAGIC 

(Gay et al., 2005), and FDS (McGrattan et al., 2009). The FDTs

 and FIVE-Rev1 are a set of 

relatively simple algebraic models codified in the form of electronic spreadsheets. CFAST and 

MAGIC represent the class of fire models commonly referred to as zone models, which divide a 

compartment of interest into two zones, an elevated temperature upper layer and a cool lower 

layer. FDS is an example of a CFD model, which divide each compartment into thousands or 

millions of cells. Temperatures and other quantities of interest are calculated for each cell. 

Algebraic models can be performed by hand with relatively little computational effort. Karlsson 

and Quintiere (2000) classify algebraic models into three categories: (1) those that deal with 

combustion, (2) those that estimate resultant environmental conditions, and (3) those that 

address heat transfer. Algebraic models related to the combustion process estimate fire 

intensity based on the flammability characteristics of the fuel. Equations that estimate firegenerated conditions include plume, ceiling jet, and compartment temperatures. Heat transfer 

equations deal with target temperatures and heat fluxes in the plume, ceiling jet, and lower and 

upper layer regions. 

Zone models are computer algorithms that solve conservation equations for energy and mass. 

The fundamental assumption associated with zone models is that the enclosure is divided into a 

limited number of distinct gas zones of uniform properties. In fire applications, the enclosure is 

usually divided in two zones. The HGL is the volume of smoke generated by the fire and 

accumulated below the ceiling of the enclosure. This layer is assumed to be homogeneous, 

and is therefore also assumed to have uniform density and temperature. Its temperature and 

depth are affected by the amount of mass and energy entering or leaving the volume in each 

time step during the simulation. The lower layer, which can also experience a temperature 

increase, is characterized by colder fresh air between the floor and the bottom of the HGL. This 

layer is also assumed to have uniform density and temperature. 

CFD models are sophisticated algorithms that solve a simplified version of the Navier-Stokes 

equations. To run CFD codes, the enclosure must be divided into a large number of control 

volumes (perhaps several million), and the equations solved for each control volume. CFD 

models then provide a detailed estimate of temperature profiles because calculations are 

performed for each control volume specified in the enclosure. CFD models also handle 

turbulent gas flows. Another advantage of CFD models is their ability to simulate fire conditions 

in geometries other than rectangular floor compartments with flat ceilings. Some CFD models 
The Fire Modeling Process 

2-11 

also attempt to estimate HRR values based on flammability properties of fuels provided by the 

analyst. The drawback of CFD models is the computational time and the level of effort required 

to set up a scenario, as computational times are usually on the order of days. The time required 

to set up a problem usually depends on the complexity of the geometry. 

Another consideration when selecting a CFD-type model is that the amount of detail supplied to 

the model is significantly greater than it is for the simpler empirical and zone models. These 

details could include ductwork, cable trays, electrical panels, and other fixed contents that may 

be modified, relocated, or removed. In addition, new panels, cable trays, or other fixed contents 

that would have been included in the fire model had they been present may be added to an 

area. Although these changes may be minor, at the very least they would require an 

assessment by a fire modeler as to whether the original analysis is still applicable or the model 

needs to be adapted for the change. In some situations, such as the determination of a 

sprinkler actuation time, such small modifications could have a significant effect on the model 

results. 

 
The Fire Modeling Process 

2-12 

Table 2-1. Summary of Common Fire Model Tools 

Fire Model 

Class Examples Typical Applications Advantages Disadvantages 

Algebraic 

models 

FDTS

FIVERev1 

Screening calculations; 

zone of influence; 

target damage by 

thermal radiation, Hot 

Gas Layer, or thermal 

plume acting in 

isolation. 

Simple to use; 

minimal inputs; 

quick results; 

ability to do multiple 

parameter sensitivity 

studies. 

Limited 

application range; 

treats phenomena 

in isolation; 

typically 

applicable only to 

steady state or 

simply defined 

transient fires 

(e.g., proportional 

to the square of 

time or t2 fires). 

Zone Model CFAST 

MAGIC 

Detailed fire modeling 

in simple geometries; 

often used to compute 

hot gas temperatures 

and target heat fluxes. 

Simple to use; 

couples Hot Gas Layer 

and localized effects; 

quick results; 

ability to do multiple 

parameter sensitivity 

studies. 

Error increases 

with increasing 

deviation from a 

rectangular 

enclosure; 

large horizontal 

flow paths not well 

treated. 

Computation 

Fluid 

Dynamics 

Model 

FDS Detailed fire modeling 

in complex geometries, 

including computing 

time to target damage 

and habitability (MCR 

abandonment or 

manual action 

feasibility). 

Ability to simulate fire 

conditions in complex 

geometries and with 

complex vent 

conditions. 

Significant effort 

to create input 

files and postprocess the 

results; 

long simulation 

times; 

difficult to model 

curved geometry, 

smoke detector 

performance, and 

conditions after 

sprinkler 

actuation. 

An important consideration in the fire model selection process is the type of analysis performed. 

Because of the large number of potential ignition sources in a typical nuclear power plant, it is 

usually not practical to default to the most sophisticated tool available. Frequently, a series of 

screening analyses (NUREG/CR-6850/EPRI 1011989) are performed to identify a subset of fire 

scenarios and targets that require further analysis with greater resolution. The screening 

process will typically use fairly simple fire modeling tools, such as algebraic models or generic 

solutions. When such screening is conducted, it is important to remain within the model 

limitations and the verification and validation (V&V) basis for the screening model. Section 2.3.6 

and Chapter 4 provide additional guidance on the significance of the fire model V&V basis and 

steps that the user should take to ensure that the fire model is used within acceptable limits. 
The Fire Modeling Process 

2-13 

2.3.1 Fire Dynamics Tools (FDTs) 

Fire Dynamics Tools (FDTs) is a set of algebraic models preprogrammed into Microsoft® Excel®

spreadsheets. The FDTs

 library is documented in NUREG-1805, “Fire Dynamics Tools (FDTs): 

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

Protection Inspection Program” (NUREG-1805, 2004) and Supplement 1 (NUREG-1805 

Supplement 1, 2011). The primary objective of the FDTs

 library and the accompanying 

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

assessing potential fire hazards in NRC-licensed NPPs. The methodology uses simplified, 

quantitative fire hazard analysis techniques to evaluate the potential hazard associated with 

credible fire scenarios. 

The FDTs

 library includes a suite of spreadsheets that can be used to calculate various fire 

parameters under varying conditions. Documentation of the theoretical bases underlying the 

equations used in the FDTs spreadsheets helps to ensure that users understand the 

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

should (or should not) be selected for a specific analysis. The governing equations and 

assumptions for FDTs

 are well established within the fire science community and are 

documented in handbooks and scientific publications, such as the NFPA Fire Protection 

Handbook (NFPA Handbook, 2008), the SFPE Handbook of Fire Protection Engineering (SFPE 

Handbook, 2008), and other fire science literature. 

The complete list of spreadsheets included in the FDTs

 library is shown in Table 2-2. A number 

of the calculation methods included in the FDTs

 were part of the V&V study conducted by the 

NRC, EPRI, and NIST (NUREG-1824 Vol. 3, EPRI 1011999, 2007). The NRC maintains a 

website at http://www.nrc.gov/reading-rm/doc-collections/nuregs/staff/sr1805/finalreport/index.html, where both new and updated spreadsheets are posted. 
The Fire Modeling Process 

2-14 

Table 2-2. Routines included in the FDTs

Function Name Description 

02.1_Temperature_NV.xls 

02.2_Temperature_FV.xls 

02.3_Temperature_CC.xls

Chapter 2. Predicting Hot Gas Layer Temperature and Smoke Layer 

Height in a Compartment Fire with Natural Ventilation (Compartment 

with Thermally Thick/Thin Boundaries) 

Method of McCaffrey, Quintiere, and Harkleroad (MQH) 

Chapter 2. Predicting Hot Gas Layer Temperature in a Compartment 

Fire with Forced Ventilation (Compartment with Thermally Thick/Thin 

Boundaries) 

Method of Foote, Pagni, and Alvares (FPA) 

Method of Deal and Beyler 

Chapter 2. Predicting Hot Gas Layer Temperature in a Compartment 

Fire with Door Closed (Compartment has Sufficient Leaks to Prevent 

Pressure Buildup; leakage is Ignored) 

Method of Beyler 

03_HRR_Flame_Height_Burning_ 

Duration_Calculation.xls 

Chapter 3. Estimating Burning Characteristics of Liquid Pool Fire, 

HRR, Burning Duration and Flame Height

04_Flame_Height_Calculations.xls Chapter 4. Estimating Wall Fire Flame Height, Line Fire Flame 

Height Against the Wall, and Corner Fire Flame Height

05.1_Heat_Flux_Calculations_Win

d_Free.xls 

05.2_Heat_Flux_Calculations_Win

d.xls 

05.3_Thermal_Radiation_From_ 

Hydrocarbon_Fireballs.xls 

Chapter 5. Estimating Radiant Heat Flux from Fire to a Target Fuel 

Wind-Free Condition 

 Point Source Radiation Model (Target at Ground Level) 

 Solid Flame Radiation Model (Target at Ground Level) 

 Solid Flame Radiation Model (Target Above Ground Level) 

Presence of Wind 

 Solid Flame Radiation Model (Target at Ground Level) 

 Solid Flame Radiation Model (Target Above Ground Level) 

Estimating Thermal Radiation from Hydrocarbon Fireballs

06_Ignition_Time_Calculations.xls

Chapter 6. Estimating the Ignition Time of a Target Fuel Exposed to 

a Constant Radiative Heat Flux 

Method of Estimating Piloted Ignition Time of Solid Materials Under 

Radiant Exposures Method of (1) Mikkola and Wichman, (2) Quintiere 

and Harkleroad, and (3) Janssens 

Method of Estimating Piloted Ignition Time of Solid Materials Under 

Radiant Exposures; Method of Toal, Silcock, and Shields 

Method of Estimating Piloted Ignition Time of Solid Materials Under 

Radiant Exposures; Method of Tewarson 

07_Cable_HRR_Calculations.xls Chapter 7. Estimating Full-Scale Heat Release Rate of a Cable Tray 

Fire

08_Burning_Duration_Soild.xls Chapter 8. Estimating Burning Duration of Solid Combustibles

09_Plume_Temperature_Calculatio

ns.xls

Chapter 9. Estimating Centerline Temperature of a Buoyant Fire 

Plume
The Fire Modeling Process 

2-15 

Function Name Description 

10_Detector_Activation_Time.xls

Estimating Detector Response Time 

Chapter 10. Estimating Sprinkler Response Time 

Chapter 11. Estimating Smoke Detector Response Time 

Chapter 12. Estimating Heat Detector Response Time

13_Compartment_Flashover_ 

Calculations.xls

Chapter 13. Predicting Compartment Flashover 

Compartment Post-Flashover Temperature: Method of Law 

Minimum Heat Release Rate 

 Required to Compartment Flashover: 

 Method of (1) McCaffrey, Quintiere, and Harkleroad (MQH); 

 (2) Babrauskas; and (3) Thomas

14_Compartment_Over_Pressure_

Calculations.xls

Chapter 14. Estimating Pressure Rise Attributable to a Fire in a 

Closed Compartment

15_Explosion_Claculations.xls

Chapter 15. Estimating the Pressure Increase and Explosive Energy 

Release 

Associated with Explosions

16_Battery_Compartment_Flamma

ble_Gas_Conc.xls

Chapter 16. Calculating the Rate of Hydrogen Gas Generation in 

Battery Compartments 

Method of Estimating Hydrogen Gas Generation Rate in Battery 

Compartments 

Method of Estimating Flammable Gas and Vapor Concentration 

Buildup in Enclosed Spaces 

Method of Estimating Flammable Gas and Vapor Concentration 

Buildup Time in Enclosed Spaces

17.1_FR_Beams_Columns_ 

Substitution_Correlation.xls 

17.2_FR_Beams_Columns_Quasi_ 

Steady_State_Spray_Insulated.xls 

17.3_FR_Beams_Columns_Quasi_ 

Steady_State_Board_Insulated.xls 

17.4_FR_Beams_Columns_Quasi_ 

Steady_State_Uninsulated.xls

Chapter 17. Calculating the Fire Resistance of Structural Steel 

Members 

Algebraic models: 

Beam Substitution Correlation (Spray-Applied Materials) 

Column Substitution Correlation (Spray-Applied Materials) 

Heat Transfer Analysis using Numerical Methods Protected 

Steel Beams and Columns (Spray-Applied) 

Heat Transfer Analysis using Numerical Methods Protected Steel 

Beams and Columns (Board Materials) 

Heat Transfer Analysis using Numerical Methods Unprotected Steel 

Beams and Columns

18_Visibility_Through_Smoke.xls Chapter 18. Estimating Visibility Through Smoke

19_THIEF_of_Cables_Calculation. 

xls 

Chapter 19. Estimating the Thermally-Induced Electrical Failure 

(THIEF) of Electrical Cables

2.3.2 FIVE-Rev1 

In August 2002, the Electric Power Research Institute (EPRI) published the Fire Modeling Guide 

for Nuclear Power Plant Applications (EPRI 1002981, 2002) for the first time. Since then, it has 

provided fire protection engineers in the commercial nuclear industry with 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 preprogrammed 

Microsoft® Excel® equations, which are used to estimate some aspects of fire-induced 
The Fire Modeling Process 

2-16 

conditions. This collection of algebraic models/algebraic models is referred to as the FireInduced Vulnerability Evaluation model (FIVE-Rev1). 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. Some of the equations in FIVE were included in the V&V study 

(NUREG-1824 vol. 4, EPRI 1011999, 2007). Like the FDTs

, several of the equations used in 

the examples have not been subject to V&V. Subsequent efforts will be directed at V&V of 

these equations and models. The calculations included in the FIVE-Rev1 are summarized in 

Table 2-3. 
The Fire Modeling Process 

2-17 

Table 2-3. Routines included in FIVE-Rev1

Function Description 

Qf Heat release rate profile considering t2 growth and four stages. 

Firr Estimates flame irradiation a distance r from the fire source. Point source 

approximation for REMOTE targets. 

FHeight Flame height based on Heskestad's flame height correlation. 

TpAlpert Plume temperature at a specific height based on Alpert plume temperature 

correlation. 

TpMcCaffrey Plume temperature at a specific height based on McCaffrey plume temperature 

correlation. 

TpHeskestad Plume temperature at a specific height based on Heskestad plume temperature 

correlation. 

Plcflux Estimates convective heat flux in the fire plume. 

VpAlpert Plume velocity at a specific height based on Alpert's plume temperature 

correlation. 

VpMcCaffrey Plume velocity at a specific height based on McCaffrey plume temperature 

correlation. 

VpHeskestad Plume velocity at a specific height based on Heskestad plume temperature 

correlation. 

EpZukoski Air entrainment into plume based on Zukoski plume entrainment correlation. 

EpThomas Air entrainment into plume based on Thomas plume entrainment correlation. 

EpHeskestad Air entrainment into plume based on Heskestad plume entrainment correlation. 

PdHeskestad Estimates plume diameter based on Heskestad's plume correlation. 

TcjAlpert Unconfined ceiling jet temperature based on Alpert ceiling jet correlation. 

TcjDelichatsios Confined ceiling jet temperature based on Delichatsios ceiling jet correlation. 

Cjcflux Estimates convective heat flux in the ceiling jet. 

VcjAlpert Unconfined ceiling jet velocity based on Alpert ceiling jet correlation. 

MQHTemperature Compartment temperature after a specified time, given a steady HRR based on 

MQH approach. 

MQHFlashover Heat release rate required for flashover after a specified time based on MQH 

approach. 

FiveTemp Estimates compartment temperature based on FIVE. 

Detact Activation time of heat detection devices based on heat release rate profiles. 

Aset Time required by Hot Gas Layer to reach a specific height based on heat 

release rate profiles and openings at the bottom of the enclosure. 

CThrr 

Estimates heat release rate from cable trays. The correlation is based on 14 

experiments with a stack of 12 horizontal cable trays and 2 experiments with a 

combination of 12 horizontal cable trays and 3 vertical trays. 

Visib Estimates the length of a visible path in a smoke environment. The correlation 

applies to light-reflecting signs. 

Ttar Estimates target temperature under constant heat flux. 

Ttdam Time to target damage under constant heat flux. 
The Fire Modeling Process 

2-18 

2.3.3 Consolidated Fire Growth and Smoke Transport (CFAST) Model 

CFAST is a two-zone computer fire model. For a given fire scenario, the model subdivides a 

compartment into two control volumes, which include a relatively hot upper layer (i.e., the HGL) 

and a relatively cool lower layer. In addition, mass and energy are transported between the 

layers via the fire plume and mixing at the vents. By contrast, combustion products accumulate 

via the plume in the HGL. Each layer has its own energy and mass balances. The most 

important assumption for the model is that each zone has uniform properties, that is, that the 

temperature and gas concentrations are constant throughout the zone, only changing as a 

function of time. The CFAST model describes the conditions in each zone by solving equations 

for conservation of mass, species, and energy, along with the ideal gas law. The Technical 

Reference Guide for CFAST (Jones et al., 2004) provides a detailed discussion concerning the 

specific derivation of these conservation laws. Documentation for CFAST also includes a 

User’s Guide (Peacock et al., 2008b), which details the use of the model, and a Model 

Development and Evaluation Guide (Peacock et al., 2008a), which presents the latest model 

V&V results. 

For some applications, including long hallways or tall shafts, the two-zone assumption may not 

be appropriate. To address this, CFAST includes empirical algorithms to simulate smoke flow 

and filling in long corridors and for a single well-mixed volume in tall shafts. CFAST also 

includes several correlations (as sub-models), based on experimental data that are used to 

calculate various physical processes during a fire scenario: smoke production, fire plume 

dynamics, heat transfer by radiation, convection, conduction, natural flows through openings 

(vertical and horizontal), forced or natural ventilation, thermal behavior of targets, heat 

detectors, and water spray from sprinklers. 

CFAST models horizontal flow through vertical vents (doors, windows, wall vents, etc), vertical 

flow through horizontal vents (ceiling holes, hatches, roof vents, etc), and mechanical ventilation 

through fans and ductwork. Natural flow is determined by the pressure difference across a vent, 

using Bernoulli’s law for horizontal vent flow, and by algebraic models for vertical vent flow. 

Mechanical ventilation is based on an analogy to electrical current flow in series and parallel 

paths where flow is split in parallel paths proportional to the flow resistance in each path and 

resistance to flow is additive for paths in series. 

CFAST includes algorithms to account for radiation, convection, and conduction within a 

modeled structure. Radiative transfer occurs among the fire(s), gas layers, and compartment 

surfaces (ceiling, walls, and floor). It is a function of the temperature differences and emissivity 

of the gas layers, as well as the compartment surfaces. Convective heat transfer between gas 

layers and compartment or target surfaces is based on typical correlations available in the 

literature. CFAST uses a finite difference scheme that utilizes a non-uniform spatial mesh to 

advance the wall temperature solution consistent with the flux conducted into the wall 

(calculated using Fourier’s law). The V&V results for CFAST are documented in Volume 5 of 

NUREG-1824 (EPRI 1011999). Additional validation results, particularly for plume temperature 

predictions that were not included in the NUREG-1824 (EPRI 1011999) results, are included in 

the CFAST Model Development and Evaluation Guide (Peacock et al., 2008a). 

2.3.4 MAGIC 

MAGIC is also a two-zone computer fire model, developed and maintained by Electricité de 

France (EdF) specifically for use in NPP analysis. MAGIC is supported by three EdF 

publications, including (1) the technical manual, which provides a mathematical description of 
The Fire Modeling Process 

2-19 

the model (Gay et al., 2005b); (2) the user’s manual, which details how to use the graphical 

interface (Gay et al., 2005a); and (3) the validation studies, which compare MAGIC’s results to 

experimental measurements (Gay et al., 2005c). These three proprietary publications are 

available through EPRI to EPRI members. In addition, V&V results for MAGIC are documented 

in Volume 6 of NUREG-1824 (EPRI 1011999). 

MAGIC is fundamentally the same type of model as CFAST and thus solves the same basic set 

of differential equations. The combustion model and vent flow models are similar as well. 

Despite this, MAGIC still differs from CFAST in that it does not have the corridor or shaft submodels, and the ceiling jet and wall jet treatments are different. The user should consult the 

technical manual for a complete description of the MAGIC sub-models (Gay et al., 2005b). 

Once a given simulation is completed, MAGIC generates an output file with all of the solution 

variables. Through a “post-processor” interface, the user selects the relevant output variables 

for the analysis. Typical outputs include the temperatures of hot and cold zones, concentrations 

of oxygen and unburned gases, smoke migration into each compartment, the mass flow rates of 

air and smoke through the openings and vents, the pressures at the floor level of each 

compartment, the temperatures at the surfaces of the walls, and the thermal fluxes (radiative 

and total) exchanged by the targets placed by the user. 

2.3.5 Fire Dynamics Simulator (FDS) 

FDS (McGrattan et al., 2007) is a CFD model of fire-driven fluid flow. The model numerically 

solves a form of the Navier-Stokes equations appropriate for low-speed, thermally driven flow, 

with an emphasis on smoke and heat transport from fires. The partial derivatives of the 

equations for conservation of mass, momentum, and energy are approximated as finite 

differences, and the solution is updated in time on a three-dimensional, rectilinear grid. Thermal 

radiation is computed using a finite volume technique on the same grid as the flow solver. 

Lagrangian particles are used to simulate smoke movement and sprinkler discharge. FDS 

computes the temperature, density, pressure, velocity, and chemical composition within each 

numerical grid cell at each discrete time step. There are typically hundreds of thousands to 

several million grid cells, and thousands to hundreds of thousands of time steps. In addition, 

FDS computes the temperature, heat flux, mass loss rate, and various other quantities at solid 

surfaces. 

Time histories of various quantities at a single point in space, or global quantities, such as the 

fire’s HRR, are saved in simple, comma-delimited text files that can be plotted in a spreadsheet 

program. However, most field or surface data are visualized with a program called Smokeview, 

a tool specifically designed to help analyze results generated by FDS. FDS and Smokeview are 

used in concert to model and visualize fire phenomena. Smokeview does this by presenting 

animated tracer particle flow, animated contour slices of computed gas variables, and animated 

surface data, and also presents contours and vector plots of static data anywhere within a 

scene at a fixed time. The FDS User’s Guide (McGrattan et al., 2007) provides a complete list 

of FDS output quantities and formats, while the Smokeview User’s Guide (Forney, 2008) 

explains how to visualize the results of an FDS simulation. Volume 7 of NUREG-1824 (EPRI 

1011999) contains the results of V&V efforts for FDS. Additional V&V results for FDS are 

contained in the FDS documentation series (McGrattan et al., 2007). 

FDS solves conservation equations of mass, momentum, and energy for an expandable mixture 

of ideal gases in the low Mach number limit. This means that the equations do not permit 

acoustic waves, the result of which is that the time step for the numerical solution is bounded by 

the flow speed, rather than the sound speed. Situations in which this limitation may be 
The Fire Modeling Process 

2-20 

encountered include jet fires, deflagrations, and detonations. The assumption also reduces the 

number of unknowns by one, as density and temperature can be related to a known background 

pressure. Flow turbulence is treated by large eddy simulation. 

For most simulations, FDS uses a mixture fraction combustion model. The mixture fraction is a 

conserved scalar that represents, at a given point, the mass fraction of gases originating in the 

fuel stream. In short, the combustion is assumed to be controlled by the rate at which fuel and 

oxygen mix. Unlike versions of FDS prior to 5, the reaction of fuel and oxygen is not necessarily 

instantaneous and complete, and there are several optional schemes that are designed to 

estimate the extent of combustion in underventilated spaces. The mass fractions of all of the 

major reactants and products can be derived from the mixture fraction by means of “state 

relations,” expressions arrived at by a combination of simplified analysis and measurement. 

The combustion model used by FDS is an area of active development. Consequently, FDS 

users should consult the latest code documentation for a description of new features or submodels. 

Numerical parameters play a very important role in a CFD model like FDS. A numerical 

parameter is any input value that is needed for the mathematical solution of the equations, but 

has little or no physical meaning. For example, the time step with which the numerical solution 

of the HGL temperature is computed does have units of seconds, but it is not a value that has 

meaning outside of that particular algorithm; nevertheless, these numerical parameters can 

affect the solution, and their sensitivity should be assessed in some way. For the spreadsheet 

and zone models, this procedure is relatively straightforward because the calculations run in 

less than a minute. One simply varies the value and ensures that the solution does not change 

appreciably. Specifically, one should simply demonstrate that the solution converges towards a 

particular value as the parameter is varied; for instance, using a smaller and smaller time step 

ought to lead to convergence of any evolution equation. 

The numerical parameter in FDS that has the greatest importance is cell size. CFD models 

solve an approximate form of the conservation equations of mass, momentum, and energy on a 

numerical grid. The error associated with the discretization of the partial derivatives is a function 

of the size of the grid cells and the type of differencing used. FDS uses second-order accurate 

approximations of both the temporal and spatial derivatives of the Navier-Stokes equations, 

meaning that the discretization error is proportional to the square of the time step or cell size. In 

theory, reducing the grid cell size by a factor of 2 reduces the discretization error by a factor of 

4; however, it also increases the computing time by a factor of at least 16 (a factor of 2 for the 

temporal and each spatial dimension). Clearly, there is a point of diminishing returns as one 

refines the numerical mesh. Determining which size grid cell to use in any given calculation is 

known as a grid sensitivity study.

Determining an optimal grid size in FDS is usually a matter of assessing the size of the fire. The 

physical diameter of the fire is not always a well-defined property; a compartment fire does not 

have a well-defined diameter, whereas a circular pan filled with a burning liquid fuel has an 

obvious diameter. Regardless, it is not the physical diameter of the fire that matters when 

assessing the “size” of the fire, but rather its characteristic diameter, כܦ: 

כܦ ൌ ቆ ܳሶ

݃ඥ∞ܶ௣ܿ∞ߩ

ቇ

ଶ/ହ

(2-1) 
The Fire Modeling Process 

2-21 

where ܳሶ is the fire heat release rate (kW), ߩ∞is the ambient density of air (kg/m3), ܿ௣ is the 

specific heat of air (kJ/kg/K),ܶ∞ is the ambient air temperature (K), and g is the acceleration of 

gravity (m/s2

). 

In many instances, כܦ is comparable to the physical diameter of the fire. FDS employs a 

numerical technique known as large eddy simulation (LES) to model the unresolvable or “subgrid” motion of the hot gases. The effectiveness of the technique is largely a function of the ratio of 

the fire’s characteristic diameter, כܦ, to the size of a grid cell, ݔߜ. In short, the greater the ratio 

כܦ/ݔߜ, the more the fire dynamics are resolved directly, and the more accurate the simulation. 

Past experience has shown that a ratio of 5 to 10 usually produces favorable results at a 

moderate computational cost for problems where gross smoke movement is of interest. 

As an example, suppose the HRR of the fire were 700 kW. The characteristic diameter may 

then be calculated as follows: 

כܦ ൌ ቆ 700 kW

1.2 kg/mଷ ۭ 1.012 kJ/kg/K ۭ 293 K √9.81 m/sଶ

ቇ

ଶ/ହ

ൌ 0.63 m 

(2-2)

To perform a grid sensitivity analysis, a good place to start might be 15 cm (6 in), which means 

that כܦ/ݔߜ ൌ 5. Then choose a grid of 10 cm (4 in), and then 5 cm (2 in). At this point, the 

calculation time will have increased by a factor of roughly 300, making it potentially impractical 

to compute; however, if it can be shown that there is little difference between the 5 cm and 

10 cm grids, then the objective has been achieved. The meaning of “little difference” can be 

interpreted in several ways. Given that NUREG-1824 (EPRI 1011999), the fire model V&V 

study, lists the relative error expected of the various models for the various quantities, it is 

reasonable to interpret the difference in results on different grids in light of what is expected of 

the model accuracy. 

Although the fire size and dimensions often determine the optimum grid resolution, there are 

other factors that can influence the selection of the grid resolution. These include the number of 

cells used to resolve a flow path dimension, the number of cells used to describe the fire 

dimension, and the number of cells used to resolve the conditions in a partially isolated volume. 

These considerations are related in that it is generally advisable to include at least three cells 

across any flow path, such as a door or a window, and fire dimension, regardless of the 

minimum number of cells computed using the fire characteristic diameter. In some cases, 

partially isolated volumes are created by various obstructions; if the temperature and flow 

conditions are of interest in these areas, a minimum of three cells across any dimension should 

be provided. Another consideration that could influence the grid resolution is the dimension of 

the obstructions that are expected to influence the result. For example, if it is necessary to 

quantitatively assess the effect that various conduits and light fixtures may have on the 

actuation time of a nearby sprinkler, the maximum grid resolution would be comparable to the 

dimensions of the smallest distinct obstruction included in the model. 
The Fire Modeling Process 

2-22 

FDS input files are frequently created with the assistance of preprocessing software, which may 

include commercial software packages that can create input files for FDS, drawings, 

spreadsheet tools created by a user to insert obstructions or create stair-step approximations, 

and curved geometry. This type of software can reduce the tediousness of creating the 

geometric representation of a space, but is not part of the FDS model. Any input files created 

by such software should be carefully checked by the user to ensure that the geometry or 

boundary data are exactly as intended. 

2.3.6 Verification and Validation 

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

of their limitations and predictive capabilities. NFPA 805 states that fire models shall only be 

applied within the limitations of the given model and shall be verified and validated. To support 

risk-informed/performance-based fire protection and implementation of the voluntary rule that 

adopts NFPA 805 as an RI/PB alternative, the NRC’s Office of Nuclear Regulatory Research 

(RES) and the Electric Power Research Institute (EPRI) conducted a collaborative project for 

V&V of the five selected fire models described in Sections 2.3.1 through 2.3.5. The National 

Institute of Standards and Technology (NIST) was also an important partner in this project. The 

results of this project were documented in NUREG-1824 (EPRI 1011999), Verification and 

Validation of Selected Fire Models for Nuclear Power Plant Applications. 

The parameters for which NUREG-1824 (EPRI 1011999) provide V&V information are shown in 

Table 2-4. Not all output parameters are available in all models. The information in Table 2-4 

may be a useful element to consider when selecting the appropriate fire model tool. For 

example, it is clear that the libraries of algebraic models (FDTs

, FIVE-Rev1) have limited 

capabilities when compared to the zone and CFD models. These libraries do not have 

appropriate methods for estimating many of the fire scenario attributes evaluated in this study. 

The correlations that the libraries do contain are typically empirically deduced from a broad 

database of experiments; they are based on fundamental conservation laws, and have gained a 

considerable degree of acceptance in the fire protection engineering community. However, 

because of their empirical nature, they are subject to many limiting assumptions. The user must 

be cautious when using these tools. 

CFD model predictions can be more accurate in complex scenarios; however, the time it takes 

to obtain and understand a prediction may also be an important consideration in the decision to 

use a particular model for a specific scenario. FDS is computationally expensive in all respects 

(preprocessing, simulation, and post-processing), and, while the two-zone models produce 

answers in seconds to minutes, FDS provides comparable answers in days to weeks. In 

general, FDS is better suited to estimate fire environments within more complex configurations. 

The fire experiments selected for inclusion in the V&V were limited to high-quality, real-scale 

experiments with direct applicability to nuclear power plant applications. As it was not possible 

to consider all possible NPP applications, a method for determining the applicability of validation 

results to other specific NPP fire scenarios has been described in NUREG-1824 vol. 1 (EPRI 

1011999). The applicability of the validation results is determined using normalized parameters 

traditionally used in fire modeling applications. Normalized parameters allow users to compare 

results from scenarios of different scales by normalizing the physical characteristics of the 

scenarios. 
The Fire Modeling Process 

2-23 

Table 2-4. Fire Modeling Attributes Included in NUREG 1824/EPRI 1011999 (2007)

Fire Modeling Attributes 

Fire Model 

FDTs FIVE-Rev1 CFAST MAGIC FDS 

Hot Gas Layer (HGL) Temperature YES YES YES YES YES 

Hot Gas Layer (HGL) Height NO NO YES YES YES 

Ceiling Jet Temperature NO YES YES YES YES 

Plume Temperature YES YES NO YES YES 

Flame Height YES YES YES YES YES 

Radiated Heat Flux to Targets YES YES YES YES YES 

Total Heat Flux to Targets NO NO YES YES YES 

Total Heat Flux to Walls NO NO YES YES YES 

Wall Temperature NO NO YES YES YES 

Target Temperature NO NO YES YES YES 

Smoke Concentration NO NO YES YES YES 

Oxygen Concentration NO NO YES YES YES 

Room Pressure NO NO YES YES YES 

 
The Fire Modeling Process 

2-24 

Table 2-5 lists selected normalized parameters that may be used to compare NPP fire scenarios 

with validation experiments. This table was derived from NUREG-1824 (EPRI 1011999), Table 

2-4 and is intended to provide guidance on which groups of validation experiments to consider 

when evaluating a certain attribute based on the validation results. These parameters may not 

be the only ones appropriate for evaluating the applicability of a specific experiment; Table 2-5 

of NUREG-1824 (EPRI 1011999), vol. 1 lists the ranges of values for different physical 

characteristics and normalized parameters based on the experiments considered in the 

validation study. 

For a given set of experiments and NPP fire scenarios, the user can calculate the relevant 

normalized parameters. If the fire scenario parameters fall within the ranges evaluated in the 

study, then the results of the study offer appropriate validation for the scenario. If they fall 

outside the range, then a validation determination cannot be made based on the results from 

the study. For any given fire scenario, more than one normalized parameter may be necessary 

for determining the applicability of the validation results. 

The V&V study provides valuable insight into the predictive capability of the five fire models. 

This insight is ultimately characterized in terms of a bias and a standard deviation for a number 

of output parameters. The closer the bias is to unity, the more accurate the fire model is at 

predicting the given parameter, on average. The smaller the standard deviation, the smaller the 

expected scatter about the mean bias. Section 4 of this guide describes how the V&V 

uncertainty information can be used to assign a probability function to the output data. 

NUREG-1824 (EPRI 1011999) provides verification and validation documentation for specific 

versions of fire models. Because the fire models considered are under active development, 

new releases occur and are expected. The user has the option of using the model version that 

has been verified and validated in NUREG-1824 (EPRI 1011999) or re-evaluating cases in 

NUREG-1824 (EPRI 1011999) to demonstrate that the predictive capability of the model has not 

decreased for the application at hand. It is expected that NUREG-1824 (EPRI 1011999) will be 

updated from time to time as the need arises. 

 
The Fire Modeling Process 

2-25 

Table 2-5. Selected Normalized Parameters for Application of the Validation Results to 

NPP Fire Scenarios (NUREG-1824/EPRI 1011999, 2007)

Quantity Normalized Parameter General Guidance Validation 

Range 

Fire Froude 

Number ܳሶ

כ ൌ ܳሶ

ܦ݃ଶඥܦ∞ܶ௣ܿ∞ߩ

Ratio of characteristic 

velocities. A typical 

accidental fire has a 

Froude number of order 1. 

Momentum-driven fire 

plumes, like jet flares, 

have relatively high 

values. Buoyancy-driven 

fire plumes have relatively 

low values. 

0.4 – 2.4 

Flame Length, 

ܮ௙, relative to 

Ceiling Height, ܪ

௙ܮ

ܪ

௙ܮ

ܦ ൌ 3.7 ܳሶ

כଶ/ହ െ 1.02

A convenient parameter 

for expressing the “size” of 

the fire relative to the 

height of the compartment. 

A value of 1 means that 

the flames reach the 

ceiling. 

0.2 – 1.0 

Ceiling Jet 

Radial 

Distance,ݎcj, 

relative to the 

Ceiling Height, ܪ

cjݎ

ܪ

Ceiling jet temperature 

and velocity correlations 

use this ratio to express 

the horizontal distance 

from target to plume. 

1.2 – 1.7 

Equivalence 

Ratio, ߮, as an 

indicator of the 

Ventilation Rate 

߮ ൌ

݉ሶ F/݉ሶ Oమ

ݎ

݉ሶ F ൌ ܳሶ

ܪ∆/

݉ሶ Oమ ൌ ቐ

0.23 ൈ

1

(Natural଴ (ܪඥ଴ܣ 2

0.23 ߩஶܸሶ ሺMechanicalሻ

The equivalence ratio 

relates the mass loss rate 

of fuel, ݉ሶ F, to the mass 

flow rate of oxygen into the 

compartment, ݉ሶ Oమ. The 

fire is considered over or 

underventilated based on 

whether ߮ is less than or 

greater than 1, 

respectively. The 

parameter, ݎ, is the 

stoichiometric ratio. 

0.04 – 0.6 

Compartment 

Aspect Ratio 

L/H or W/H, where L is the Length, W

is the Width, and H is the Height of 

the compartment.

This parameter indicates 

the general shape of the 

compartment. 

0.6 – 5.7 

Radial Distance, 

ݎ, relative to the 

Fire Diameter, ܦ

ݎ

ܦ

This ratio is the relative 

distance from a target to 

the fire. It is important 

when calculating the 

radiative heat flux. 

2.2 – 5.7 

 
The Fire Modeling Process 

2-26 

2.3.7 Fire Modeling Parameters Outside the Validation Range 

The development of the sample problems documented in the appendices to this report suggests 

that many commercial nuclear power plant fire modeling applications can fall outside the range 

of applicability of the validation study documented in NUREG-1824 (EPRI 1011999). The 

primary reason for this is that the range of applicability, as defined by the dimensionless 

parameters, is governed by the experiments selected for the validation study. The selected 

experiments are representative of various types of spaces in commercial nuclear power plants 

but do not encompass all possible geometries or applications. There will thus be many areas or 

applications that will fall outside this application range. It is the consensus opinion of this 

guide’s writing team that the predictive capabilities of the fire models in specific scenarios can 

extend beyond the range of applicability defined in NUREG-1824 (EPRI 1011999). 

Nevertheless, additional analysis would be required to address situations where some of the 

analysis parameters fall outside the range of applicability defined in NUREG-1824 (EPRI 

1011999). This section describes the recommended strategies for addressing this situation. 

2.3.7.1 Sensitivity Analysis 

In the context of applicability of validation results, sensitivity analysis refers to varying selected 

input parameters in the “conservative” direction so that they fall within the applicability range. If 

the fire modeling conclusions are not affected by the variations in the parameters, the analyst 

may use the sensitivity analysis results to further justify the conclusions. Based on the 

dimensionless terms listed above, the following sensitivities could be evaluated: 

1. Froude number: The two parameters that can be practically varied are the fire diameter and 

the heat release rate. For fire sizes (i.e., heat release rates) that are small for the 

postulated diameter, the resulting Froude number can fall under the low end of the 

applicability range. Similarly, for fire sizes that are relatively large for the postulated 

diameter, the Froude number can fall above the applicability range. In the former situation, 

the analysts may consider reducing the fire diameter and keeping the heat release rate 

profile unchanged. In most fire modeling tools, the fire diameter is simply used for 

determining heat release rates or for calculating the fire plume conditions, such as the flame 

height or plume temperature. Considering that the heat release rate is “fixed” in this 

sensitivity study, the fire diameter may not be a relevant parameter in the analysis, with the 

important exception of scenarios where the fire plume conditions are relevant. A similar 

approach could be used for the latter situation. Increasing the fire diameter can “force” the 

dimensionless term into range. It should be stressed that fire diameter is often a parameter 

that influences predicted flame height and fire plume conditions, and that the effects of 

diameter variations should be explicitly address in the analysis. This includes other 

dimensionless terms where the fire diameter is a key input (e.g., target distance to diameter 

(r/D), etc.). 

2. Flame length relative to ceiling height: This is a convenient parameter for expressing the 

“size” of the fire relative to the height of the compartment. A value of 1 means that the 

flames reach the ceiling. The validation range extends up to a value of 1.0, which should 

cover most of the scenarios of interest in commercial nuclear plants. Scenarios that are 

expected out of the range are: 

a. Those associated with relatively short flames. Typical ceiling heights in power plant 

scenarios range from about 10’ to 20’ (excluding the containment and turbine 
The Fire Modeling Process 

2-27 

buildings, which have relatively large openings between elevations). Consequently, 

flame lengths shorter than 2’ to 4’ will be considered out of validation range. A 

sensitivity analysis increasing the heat release rate values should provide a 

conservative estimate of fire conditions within the validation range. In cases where 

the conclusion of the analysis does not change given the increased fire intensity 

(e.g., no damage within the flame length of fire plume), the suggested sensitivity 

analysis can be used as the justification for the evaluation of a compartment that 

falls outside the validation range. 

b. Flame extensions under ceilings. In this particular case, not only are such flame 

lengths out of the range of validation, but also the models for predicting this 

phenomenon have not been verified or validated with a process similar to the one 

documented in NUREG-1824 (EPRI 1011999). 

3. Ceiling Jet Radial Distance relative to the Ceiling Height: Ceiling jet temperature and 

velocity correlations use this ratio to express the horizontal distance from target to plume. 

Ceiling jet applications in commercial nuclear power plants should be carefully evaluated 

due to the numerous obstructions near the ceiling (e.g., cable trays, HVAC ducts, piping, 

etc.). Most of its applications include determination of time to detection and sprinkler 

activation, in which the ceiling jet velocity is a sub-model in the analysis. An alternative 

option is a sensitivity analysis consisting of moving the fire location to distances that would 

fall within the validation range; it is recognized, however, that in many situations the fire 

location cannot be altered, particularly in the case of fixed ignition sources or transient fires 

postulated near “pinch-points.” In general, longer horizontal distances will result in longer 

activation time results; by contrast, shorter horizontal distances would result in 

“conservative” time-to-damage results. 

4. Equivalence Ratio, φ, as an indicator of the Ventilation Rate: The validation available is for 

well-ventilated fires. That is, no model validation information is available for under 

ventilated compartment fires, including fire extinction due to lack of oxygen. In general, 

assuming that fires are well ventilated in the enclosure should result in bounding conditions 

as long as the heat release rate profile is appropriate. The underlying consideration is that 

conditions in the enclosure are not expected to be worse in a fire where the combustion 

process is affected by lack of oxygen than they would be under fire conditions where the 

combustion process is assumed unaffected. It should be noted that this assumption must 

be invoked with caution, as sudden air inflows into closed/under ventilated fire conditions 

could produce relatively severe fire conditions. 

5. Compartment Aspect Ratio: It is expected that some compartments in the commercial 

nuclear plants would have geometric characteristics outside the validation range (e.g., 

relatively long/narrow corridors with high ceilings, etc.). These parameters are important in 

fire scenarios involving Hot Gas Layer calculations, as the size and configuration of the 

compartment are important input parameters. Clearly, these parameters should not be 

applicable in scenarios where the enclosure conditions are not considered, such as flame 

radiation calculations using the point source model and plume temperature calculations 

using semi-algebraic models where it has been determined that enclosure conditions are 

not a factor. As part of the sensitivity analysis, the analyst may consider “shortening” the 

length, width, or height of the compartment to values that fall within the validation range 

under the expectation that this will result in an elevated level of hazardous fire-generated 

conditions as predicted by the model (i.e., a conservative calculation). In cases where the 

conclusion of the analysis does not change given the “smaller” compartment (e.g., the Hot 
The Fire Modeling Process 

2-28 

Gas Layer temperature does not exceed damage threshold of cables in either case), the 

suggested sensitivity analysis can be used as the justification for the evaluation of a 

compartment that falls outside the validation range. 

6. Radial Distance, r, relative to the Fire Diameter: This ratio is the relative distance from a 

target to the fire, and is important when calculating the radiative heat flux. Notice that the 

validation range starts at a distance approximately twice the length of the fire diameter. In 

practice, targets at very close distance (approximately less than two fire diameters from the 

fire) to the fire should be expected to fail given the relatively low damage threshold levels for 

cables. An alternative option is a sensitivity analysis consisting of moving the fire location to 

distances that would fall within the validation range; it is recognized, however, that in many 

situations the fire location cannot be altered, particularly in the case of fixed ignition sources 

or transients fires postulated near “pinch-points.” In general, shorter horizontal distances 

will result in higher heat flux levels. 

2.3.7.2 Additional Validation Studies 

There are, of course, other fire model validation studies besides NUREG-1824 (EPRI 1011999) 

that can serve as a basis for establishing the applicability of fire modeling results. In developing 

the examples documented in the appendices to this report, the research team identified relevant 

validation studies outside of NUREG-1824 (EPRI 1011999), as summarized below: 

 Scenarios involving targets within the fire plumes: A useful discussion of fire plumes is 

contained in Gunnar Heskestad’s chapter in the SFPE Handbook of Fire Protection 

Engineering (4th ed.), “Fire Plumes, Flame Height, and Air Entrainment.” The plume 

correlations used in the empirical and zone models are described, as well as their range 

of applicability. NUREG-1824 (EPRI 1011999) contains experimental measurements of 

fire plumes, but the range is somewhat limited. The plume correlations used by the 

models have a much wider range of applicability than that exercised in NUREG-1824 

(EPRI 1011999). 

 Scenarios involving targets within the ceiling jet: Similarly, Ronald Alpert’s chapter 

“Ceiling Jet Flows” in the SFPE Handbook contains a description of the various 

correlations used to estimate the temperature and gas velocity of ceiling jets. There are 

extensive references to the original experimental test reports from which the correlations 

were derived. 

 Scenarios involving targets exposed to flame radiation: A useful collection of techniques 

and validation data for thermal radiation calculations is found in the SFPE Engineering 

Guide for Assessing Flame Radiation to External Targets from Pool Fires, written by the 

SFPE Task Group on Engineering Practices, 1999. 

 Scenarios involving Flashover/Post-Flashover conditions: A series of experiments was 

conducted at NIST as part of an investigation of the collapse of the World Trade Center 

towers. Validation calculations with FDS are described in the report NIST NCSTAR 1-

5F, Federal Building and Fire Safety Investigation of the World Trade Center Disaster: 

Computer Simulation of the Fires in the WTC Towers, September 2005. 

 Scenarios involving electrical failure of cables: The CAROLFIRE (Cable Response to 

Live FIRE) program led to the development and validation of the THIEF (Thermally-
The Fire Modeling Process 

2-29 

Induced Electrical Failure) model (NUREG/CR-6931, Vol. 3). The model is used to 

estimate the temperature within an electrical cable that is exposed to an elevated 

temperature or heat flux. 

 Scenarios involving cable burning: The CHRISTIFIRE (Cable Heat Release, Ignition, 

and Spread in Tray Installations in FIRE) program led to the development and validation 

of the FLASH-CAT (Flame Spread in Horizontal Cable Trays) model (NUREG/CR-7010, 

Vol. 1). This model addresses the growth and spread of fire within vertical stacks of 

horizontal, open-back cable trays. 

In addition to NUREG-1824 (EPRI 1011999) and the various documents cited above, the 

individual model developers typically maintain a collection of validation cases that are included 

as part of the model documentation. The algebraic spreadsheet models, Fire Dynamics Tools 

and FIVE, are based directly on experimental correlations. Validation of these models is 

typically not part of the model documentation; rather, there are references to source material 

like the SFPE Handbook or the original test reports. Validation studies by the CFAST and FDS 

developers are contained within: 

CFAST – Consolidated Model of Fire Growth and Smoke Transport, Software Development and 

Model Evaluation Guide, NIST Special Publication 1086, 2008. 

Fire Dynamics Simulator, Technical Reference Guide, Volume 3, Validation, NIST Special 

Publication 1018, 2007. 

2.4 Step 4: Calculate Fire-Generated Conditions 

This step involves running the model(s) and interpreting the results. When running a computer 

model, the following general steps are recommended: 

1. Determine the output parameters of interest. If the goal of the simulation is to estimate 

wall temperatures, for example, the analyst should be interested in internal and external 

wall temperatures. The analyst should ensure that the model will provide the output of 

interest, or at least the fire conditions that can help achieve the objectives of the 

analysis. The output file should be labeled with a distinctive file name. 

2. Prepare the input file. In this step, the analyst enters the input parameters into the 

model. The best way to enter input parameters is to follow the same guidelines 

described in the scenario description section. Each model has a user’s manual with 

instructions on creating the respective input file. These files are created either through 

user-friendly menus and screens or through a text editor. If a text editor is used, it is 

strongly recommended that the analyst start with an example case prepared by code 

developers, and make appropriate changes to that file. 

3. Run the computer model. The running time for zone models is on the order of minutes, 

depending on the complexity of the scenario and the speed of the computer. 

Calculations using a CFD model may take up to days or weeks in complex scenarios, 

including multiple compartments, multiple fires, and mechanical ventilation systems. 

4. Interpret the model results. Verify that the results are intuitively consistent with the input 

and expectations. Verify that the output results accurately reflect the desired input; 

common verifications would include the fire size and location, the location and status of 

any doors or boundary openings, and the forced ventilation flow rate and location. The 
The Fire Modeling Process 

2-30 

model output should be checked for indications of a solution error. For example, the 

pressure should be within reasonable bounds; the Hot Gas Layer temperature should be 

sensible; the Hot Gas Layer temperature should be greater than the lower gas layer 

temperature; and there should not be anomalous areas of flow acceleration or 

temperature change. Determine whether or not the fire scenario resulted in conditions 

that exceed the performance criteria, as applicable. 

5. Arrange output data in a form that is suitable for the goal. If the results are used in a 

PRA screening analysis, this may take the form of a zone of influence (ZOI) dimension 

or a maximum HGL temperature. If the results are part of a deterministic analysis, the 

output form may be a conclusion with regard to the performance of some component 

and an associated safety margin if the component is predicted to be free of damage. 

For the FDTs

 and FIVE-Rev1, the input data is entered directly into a spreadsheet, and the 

results are presented in the spreadsheet. Some of the FDTs

 spreadsheets include graphical 

and tabular results. FIVE-Rev1 typically provides a single result for a given set of input data; 

however, many of the calculations in FIVE-Rev1 are implemented as Microsoft Excel functions. 

These functions can be called from any cell in the spreadsheet. It is possible, for example, to 

specify a heat release rate in one cell and the plume temperature at a specific location above 

the fire for that heat release rate. By entering a list of heat release rates that vary with time, the 

analyst could obtain the plume temperature or other calculations as a function of time. 

CFAST, MAGIC, and FDS can handle user-specified transient heat release rates, as they 

calculate the results for each zone or cell at each time step. The time step required to maintain 

stable calculations is typically determined by the model. The interval at which results are 

presented is a user-specified value. CFAST, MAGIC, and FDS can output results as text files, 

which can be read or plotted using commercially available spreadsheet programs; CFAST and 

FDS can also output their results in a form appropriate for SMOKEVIEW (Forney, 2008). 

SMOKEVIEW is a software tool that visualizes smoke and other attributes of the fire using 

traditional scientific methods, such as displaying tracer particle flow, two- or three-dimensional 

shaded contours of gas flow data (e.g., temperature), and flow vectors showing flow direction 

and magnitude. MAGIC includes its own post-processor for visually analyzing the results of a 

simulation. Post-processing may also be performed using other graphical or graphical 

animation software. If a software package other than one designed for viewing the particular 

fire model results is used, the user should verify that the output parameters are interpreted and 

displayed as intended. 

2.5 Step 5: Conduct Sensitivity and Uncertainty Analyses 

This guide recommends a comprehensive treatment of uncertainty and/or sensitivity analysis as 

part of a fire modeling analysis for the following reasons: 

 Models are developed based on idealizations of the physical phenomena and simplifying 

assumptions, which unavoidably introduces the concept of model uncertainty (i.e., model 

error) into the analysis. 

 A number of input parameters are based on available/generic data or on fire protection 

engineering judgment, which introduces the concept of parameter uncertainty into the 

analysis. 

The concepts of model and parameter uncertainty have traditionally been addressed in fire 

modeling using uncertainty and/or sensitivity analysis. The uncertainty in a variable represents 
The Fire Modeling Process 

2-31 

the lack of knowledge about the variable, and is often represented with probability distributions. 

Its objective is to assess the variability in the model output, that is, how uncertain the output is 

given the uncertainties related to the inputs and structure of the model. By contrast, the 

sensitivity of a variable in a model is defined as the rate of change in the model output with 

respect to changes in the variable. A model may be insensitive to an uncertain variable. 

Conversely, a parameter to which a model is very sensitive may not be uncertain. 

Details of the uncertainty and sensitivity analysis are included in Chapter 4 of this guide for both 

a deterministic- and a probabilistic-type evaluation. 

2.6 Step 6: Document the Analysis 

The amount of information required and generated by a fire modeling analysis can vary widely. 

Simple algebraic models may not require a large number of inputs, and the complete analysis, 

including output results, can be documented on a single piece of paper. On the other hand, 

some fire modeling exercises may require use of multiple computer models, where outputs from 

one are inputs to others. These cases, for the most part, will require a significant number of 

input parameters and will produce outputs requiring documentation. Regardless of the amount 

of information required or generated by the analysis, proper documentation is vital to identifying 

the important findings of the exercise and providing clear, focused conclusions. 

Documentation of the fire scenario selection and description process should include enough 

information so that the final report is useful in current and future applications. This is particularly 

relevant in the commercial nuclear industry, where compartment and equipment layouts or 

processes do not change much over time. It is likely that fire scenarios analyzed for one 

application may be useful for other applications as well; the key, however, is to develop and 

maintain good documentation of the selected fire scenarios, including all the technical elements 

discussed in this section. The SFPE “Engineering Guide to Substantiating a Fire Model for a 

Given Application” (SFPE, 2011) provides general guidance on information to be included in fire 

modeling analyses. 

It is likely that the information necessary for documenting the fire scenario selection will be 

gathered from a combination of observations made during engineering walkdowns and a review 

of existing plant documents and/or drawings. The documentation process then involves 

compiling the information from different sources into a well-organized package that can be used 

in future applications and for NRC regional inspections. The documentation package may 

consist of: 

 Marked up plant drawings. Plant layout, detection, suppression, cable tray, Heating, 

Ventilation and Air-Conditioning (HVAC), and conduit drawings are often marked to 

highlight the location of the compartment, the ignition sources, the targets, the ventilation 

flow paths, and the fire protection features. The drawings also serve as sources of fire 

model input values, such as compartment dimensions, ventilation flow rates, and relative 

locations of fire protection systems or targets. 

 Design basis documents (DBDs). DBDs provide in-depth assessments of plant features 

in various operation modes, such as the HVAC system. 

 Sketches. Sketches are perhaps one of the most useful ways of documenting a fire 

scenario. A sketch typically consists of a drawing illustrating the ignition source, 

intervening combustibles, targets, and fire protection features. A first draft of the sketch 

is usually prepared during walkdowns. The analyst should take the opportunity to 
The Fire Modeling Process 

2-32 

include details such as raceways and conduit identifications (IDs), and other information 

relevant to the fire modeling analysis. Pictures often supplement sketches. 

 Write-ups and input tables. Write-ups and input tables are used to compile the 

information collected from drawings and walkdowns in an organized way. The write-up 

should include a brief scenario description and detailed documentation supporting 

quantitative inputs to the fire modeling analysis, as well as any relevant sketches or 

pictures associated with each scenario. 

 Software versions, descriptions, and input files. The documentation package should 

include the version numbers of any software, brief descriptions of the software, and 

copies of the input files. 

The examples presented in Appendices A through H of this guide illustrate techniques for the 

proper documentation of fire modeling calculations using the format described. In conclusion, a 

properly documented analysis will enable the reviewer to reproduce the results from the 

information contained within the fire scenario analysis. 

2.7 Summary 

This chapter described a recommended process for conducting and documenting a fire 

modeling analysis. Chapter 3 provides guidance on selecting the appropriate fire modeling tool 

and input parameters for typical commercial nuclear power plant applications. Fire model 

uncertainty is addressed in Chapter 4 of this guide. Specific fire modeling examples evaluated 

using the process described in this Chapter are provided in Appendices A through H. 
3-1 

3

GUIDANCE ON FIRE MODEL SELECTION AND 

IMPLEMENTATION 

This chapter provides guidance and recommendations for modeling fire scenarios in a 

commercial nuclear power plant. It can be considered a catalogue of generic fire scenarios and 

corresponding modeling objectives for which a modeling strategy is discussed, relevant fire 

modeling elements are described, and model selection recommendations are offered. The 

chapter begins with a description of key fire modeling elements applicable to most of the 

scenarios presented in the guide, which are intended to direct the analyst to the specific section 

in this chapter where guidance and recommendations are provided. 

3.1 Model Implementation of Fire Scenario Elements 

This section provides a description of fire modeling elements typically present in commercial 

nuclear power plant scenarios. The following fire modeling elements are described: 

 Heat Release Rate 

 Plant Area Configuration 

 Ventilation Parameters 

 Targets 

 Intervening Combustibles 

3.1.1 Heat Release Rate 

The heat release rate (HRR) in a fire model is perhaps the most important parameter to specify. 

All enclosure fire models solve a conservation of energy equation (i.e., the energy released by 

the fire in the form of heat causes the temperature to increase and hot and cold air to flow in 

and out of the enclosure). The fire as a heat source is the driving parameter for all the modeled 

physical phenomena. The models track the energy being added to the enclosure and estimate 

the fire-induced temperature and flow of hot gases. Three questions usually have to be 

answered to adequately assess the heat release rate of a fire: 

1. How fast does the fire grow? This is the time it takes for the fire to reach its peak intensity 

from the time of ignition. It is also equally important to define the growth profile to the peak 

intensity as a function of time. The t2

 growth profile (see Karlsson and Quintiere, p. 38) is a 

convenient mathematical structure to represent this growth. In some cases, experimental 

data of actual fuel commodities may be available, where the profile may or may not follow a 

t

2

-type profile. 

2. What is the peak intensity of the fire? The peak intensity, or peak heat release rate, 

represents the phase of the heat release rate profile where the fuel reaches its maximum 

burning rate, assuming that oxygen is available to support fuel-controlled burning. In 

practical applications, the peak intensity is obtained from experimental data. Alternatively, it 

can be estimated using the heat of combustion and the maximum burning rate of the fuel 
Guidance on Fire Model Selection and Implementation 

3-2 

(perhaps considering the effective heat of combustion rather than the theoretical, maximum 

value). The peak heat release rate may also be dictated by the air supply available to the 

fire. Estimates of the maximum heat release rate associated with a particular ventilation 

opening or airflow are available in fire protection engineering handbooks. 

3. How long does the fire burn? The duration is a function of the amount of fuel available and 

the rate at which the fuel is consumed. 

The HRR vs. time curve typically has four stages: incipient, growth, steady burning at peak 

intensity, and decay. 

In the incipient stage, the fire burns at a low intensity (i.e., smoldering insulation or a small trash 

can fire). The duration of this stage may vary from seconds to hours, and the energy release is 

relatively low. Because of the uncertainty in the intensity of the fire during this stage, and the 

exact time that the fire will transition to a significant fire, the incipient stage is often not 

considered in the analysis. 

Depending on the combustible and its arrangement, the growth to a fully developed stage will 

vary from seconds to minutes. The duration of the steady burning phase depends on the 

amount of fuel and the amount of oxygen available. 

The following elements are also important in characterizing the fire source: 

 The fire elevation: The fire elevation refers to the elevation of the base of the fire, measured 

from the floor. It is important because (1) in scenarios involving targets in the fire plume 

where the relative distance between the fire and the target strongly influences the resulting 

plume temperature, and/or (2) in scenarios where the position of the Hot Gas Layer is 

relevant, the fire elevation influences the air entrainment into the plume, and, consequently, 

the position of the layer as well as the actual heat release rate (since any air entrained from 

the Hot Gas Layer may be oxygen-depleted). 

 The fire location: In scenarios where the fire is located along a wall and in the corner (i.e., 

the fire is postulated either flush with or at most a few inches from the wall or the corner), the 

plume is expected to entrain less air at ambient temperature, resulting in higher plume 

temperatures (see Karlsson and Quntiere, p. 72). 

 Additional combustion properties are often necessary. Some of these properties include: 

 Fuel mass: The total (or initial) fuel mass, which is an important factor in determining the 

burning duration 

 Soot yield: The soot yield is an important factor in radiative heat transfer (e.g., targets 

immersed in the Hot Gas Layer), visibility calculations, and smoke detector response 

estimates 

 Radiated fraction: The fraction of the energy released by the fire that is radiated from the 

flames 

 Release Fractions (Yields): In some models, species production is calculated based on 

production yields prescribed by the user 

3.1.2 Plant Area Configuration 

The plant area configuration refers to the geometrical layout and construction of the enclosure. 

Each of these elements is described in detail next. 
Guidance on Fire Model Selection and Implementation 

3-3 

Compartment Geometry 

Compartment geometry refers to the physical layout of the volume in which the fire is 

postulated. The length, width, and height of the room are the typical inputs required by the 

model. The size of a compartment is an important factor in the volume used to solve the 

fundamental conservation equations. Empirical and zone models employ considerable 

simplifications of the geometry, while CFD models attempt to replicate as much of the geometry 

as possible. 

Compartment Boundary Materials 

Boundary (e.g., wall) materials are characterized with thermophysical properties, which include 

the density, specific heat, and thermal conductivity of the material. In the majority of commercial 

nuclear power plant applications, the wall material is concrete. Other materials may include 

steel, gypsum board, etc. Properties for these materials are often available in “drop down” 

menus in the fire models or in fire protection engineering handbooks. Table 3-1 provides typical 

boundary material properties.

Table 3-1. Boundary Material Properties 

Material Thermal conductivity W/m/K Density kg/m3 Specific heat kJ/kg/K 

Concrete 1.6 2400 0.75 

Gypsum 1.7 960 1.1 

Brick 0.8 2600 0.8 

Steel 54 7850 0.465 

Source: NUREG-1805 

3.1.3 Ventilation Effects 

Ventilation effects include natural ventilation through vertical or horizontal openings, the effects 

of leakage paths, and/or the effects of mechanical ventilation. Each of these elements is 

described next. 

Vertical Openings 

Vertical openings refer for the most part to doors, though they can also comprise other openings 

in walls, such as open windows. In some cases, a selected compartment will have more vertical 

openings than the number that can be specified in a specific model; for example, the MQH 

model for calculating room temperature available in FDTs

 and FIVE-Rev1 accept only one 

opening. The most important consideration in addressing the issue of vertical openings is to 

conserve the ventilation factor. If the number of vertical openings needs to be reduced in order 

to describe the scenario in a specific model, a weighted average for the vent factor needs to be 

estimated. The ventilation factor is defined as the product of the area of an opening and the 

square root of the height of the opening  HA oo  (Karlsson et al., 2000; Drysdale, 1996). The 

following steps can be used to determine the combined effective height, Ho, and area, Ao, of 

multiple vertical openings: 

1. Add up the areas of the selected openings: 



n

i

o AA i

1
Guidance on Fire Model Selection and Implementation 

3-4 

2. Divide the sum of the product of the area and height of each opening by the total area 

calculated in step 1: 

o

n

i

ii

o A

hA

H





 1

where Ai and hi are the area and height of door i, respectively, and n is the total number of 

vertical openings that need to be combined. The effective width of the multiple vertical openings 

can be estimated by the ratio, Ao/Ho. 

Regarding doors (and other operable openings), consideration should be given to the doors 

being opened (or closed) during a fire. For example, when the fire brigade arrives, they will 

open the doors to the fire area to gain access, which will affect the ventilation and possibly 

result in smoke spread. 

Leakage Paths 

The doors of most compartments in commercial NPPs are normally closed, but are not perfectly 

sealed. Consequently, the resulting pressure and the rate of pressure increase are often kept 

very small by gas leaks through openings in the walls and cracks around doors, or “leakage 

paths.” Leakage paths must be specified in compartments with closed doors during the fire 

event unless the analysis considers a completely sealed enclosure where pressure rise is an 

important variable. By contrast, compartments with at least one open door or window can 

maintain pressure close to ambient during the fire event. Leakage paths therefore do not need 

to be specified, since the leakage opening area is negligible when compared with the opening 

areas of doors and windows. 

Horizontal Openings 

Horizontal openings consist of hatches or stairwells. For modeling purposes, the areas of 

horizontal openings can simply be added. Any zone model should provide similar answers with 

single or multiple horizontal openings as long as the total opening area is the same. Note that 

CFAST allows only a single connection between any pair of compartments included in a 

simulation. For a CFD model, no special provisions are necessary to describe a horizontal 

opening. 

Mechanical Ventilation 

Mechanical ventilation refers to any air injected into or extracted from a compartment by 

mechanical means. This has a number of practical applications, such as extracting smoke from 

the Hot Gas Layer (e.g., a smoke purge system). The ventilation rate and the vent position are 

the two most important mechanical ventilation parameters. For some applications, the velocity 

of the airflow may also be important. These mechanically induced flows have the potential to 

alter the fire-induced flows. Mechanical ventilation often consists of a supply and an exhaust 

system that are maintained to achieve a certain pressure level. 

3.1.4 Targets 

Targets refer to objects of interest than can be affected by the fire-generated conditions and 

typically consist of cables in conduits, cables in raceways, or plant equipment. Targets are 

characterized by their location, damage criteria, and thermophysical properties. 

A target’s location simply refers to its location relative to the fire. The location is represented by 

three-dimensional coordinates within the volume of the room in which the fire conditions are 
Guidance on Fire Model Selection and Implementation 

3-5 

simulated. Where the target faces in a particular direction, an orientation vector to indicate that 

direction needs to be entered. 

The damage criteria refers primarily to a damage/response threshold. In general, the damage 

criteria for scenarios involving cable damage is expressed in terms of damage temperature or 

incidental heat flux. These thresholds are available in commercial nuclear industry documents 

such as NUREG-1805, NUREG/CR-6931, and NUREG/CR-6850 (EPRI 1011989). 

The models within the scope of this guide require specification of the target’s thermophysical 

properties, primarily the density, specific heat, and thermal conductivity, for the analysis. These 

parameters are used for estimating heat conducted into the targets. The predicted time for the 

gas temperature surrounding a target to reach a specific limit is usually less than the time it 

takes the target to reach the same limit because the heat conduction inside the target will delay 

the temperature rise at the surface during the heating process. These data are also available in 

documents such as NUREG-1805, NUREG/CR-6931, and NUREG/CR-6850 (EPRI 1011989). 

3.1.5 Intervening Combustibles 

In many cases, commercial nuclear plant PRA fire scenarios do not require burning targets to 

be modeled because it is sufficient to determine only when the target is damaged. This is 

clearly not the case with intervening combustibles, whose flammability characteristics need to 

be incorporated into the model so that the fire progression is considered. Therefore, the 

intervening combustibles should be described not only in terms of their proximity to the fire and 

the targets, but also in terms of their relevant thermophysical and flammability properties. 

In many cases, intervening combustibles consist of cables in ladder back trays. Representing 

intervening combustibles like cables in fire models presents technical challenges that the 

analyst should also consider, including (1) obtaining the necessary geometric and 

thermophysical properties representing the intervening combustible and (2) the ability of the 

computer tools to model the fire phenomena (e.g., fire propagation). Because of these 

challenges, industry methodologies for applications (e.g., Fire PRAs) include a number of 

simplified models to estimate fire-generated conditions that are currently beyond the capabilities 

of the fire models described in this Guide. The simplified approach consists of determining the 

contribution to the heat release rate due to flame spread and fire propagation through cable 

trays. Appendix R of NUREG/CR-6850 (EPRI 1011989) provides guidance on the calculation of 

fire spread and heat release rates for cables trays. In addition, research is underway to develop 

improved methods for predicting the heat release rate and flame spread of electrical cables. A 

simple model called FLASH-CAT that predicts flame spread over cables in horizontal trays has 

been developed as part of the Cable Heat Release, Ignition, and Spread in Tray Installations 

during Fire (CHRISTIFIRE) project (NUREG/CR-7010, vol. 1), sponsored by the NRC and 

conducted by NIST. 

 
Guidance on Fire Model Selection and Implementation 

3-6 

3.2 Guidance on Model Selection and Analysis 

This section provides guidance on model selection and analysis of specific fire scenarios. Each 

subsection is devoted to a specific fire scenario, as listed in Table 3-2. In addition, Figure 3-1 

provides a pictorial representation of each of these scenarios. The circled numbers are 

intended to direct the reader to the section in which the scenario is described. 

Table 3-2. Listing of generic fire scenarios described in this chapter 

Number Chapter Section Scenario Description 

1 3.2.1 Scenarios consisting of determining time to damage of cables above the ignition 

source located inside the flames or the fire plume. 

2 3.2.2 

Scenarios consisting of determining time to damage of cables located inside or 

outside the Hot Gas Layer. This scenario also includes a secondary fuel source 

(i.e., propagation to cable trays). 

3 3.2.3 Scenarios consisting of determining time to damage of cables located in an 

adjacent room to the room of fire origin. 

4 3.2.4 Scenarios consisting of determining time to damage of cables located inside or 

outside the Hot Gas Layer in rooms with complex geometries. 

5 3.2.5 Scenarios consisting of determining time to loss of habitability of the main control 

room. 

6 3.2.6 Scenarios consisting of determining time to smoke or heat detector activation. 

7 3.2.7 Scenarios consisting of determining temperature of structural elements. 

Each of the sections listed above is organized as follows: 

1. A sketch capturing most of the technical elements relevant to the analysis. A legend 

summarizing the different elements presented in the sketches is provided in Figure 3-2. 

2. A scenario objective stating the purpose of the modeling exercise in engineering terms. 

3. A description of the relevant technical fire scenario elements, such as mechanical 

ventilation, the room geometry, etc. Recall that fire scenario elements refer to the different 

characteristics of the fire scenario that are relevant to the analysis, and should be properly 

represented in the model. 

4. A modeling strategy section summarizing the recommended steps for performing the 

calculation. 

5. A section listing fire model recommendations for the analysis. 

6. A section referencing relevant detailed fire modeling examples documented in the Appendix 

section of this guide. 
Guidance on Fire Model Selection and Implementation 

3-7 

Figure 3-1. Pictorial representation of the fire scenario and corresponding technical 

elements described in this section. 

1

2

3

4

5

6

7
Guidance on Fire Model Selection and Implementation 

3-8 

 Figure 3-2. Legend for fire modeling sketches presented in this chapter. 

 

HVAC

1. Supply 

2. Exhaust

Smoke 

Detector

Cable 

Tray

1. Exposed 

2. Target

Junction 

Box and 

Conduit

Electrical 

Cabinet

Fire

Sprinkler

Open 

Door

Closed 

Door

Pump

Plant 

Employee

Control 

Board

1.

2.

1.

2.
Guidance on Fire Model Selection and Implementation 

3-9 

3.2.1 Targets in the Flames or Plume 

This scenario consists of a target, such as an electrical cable in a raceway immediately above 

an ignition source, such as an electrical cabinet. An example of this type of scenario is depicted 

in Figure 3-3, where the target is identified in the sketch by a dashed circle. 

Figure 3-3. Pictorial representation of scenario 1

3.2.1.1 General Objective 

The objective of this scenario is to calculate the time to damage for a target immediately above 

a fire. For the case shown in Figure 3-3, the target is an electrical raceway and the fire source 

is an electrical cabinet. 

3.2.1.2 Modeling Strategy 

The recommended modeling strategy is summarized in the following steps: 

1. Determine whether the target cable, which is directly above the fire, is within the flame zone 

or within the fire plume. The target should be considered inside the flame zone if it is 

located directly above the base of the fire and its distance from the base of the fire is less 

than the flame height. If the target is above the fire but is not within the flame zone, then it is 

considered to be within the fire plume. It should be noted that unobstructed fire plumes will 

increase in diameter as a function of height. Consequently, a target may not need to be 

directly above the ignition source to be immersed in the fire plume. 

2. Calculate the time to damage by finding the minimum of either: 

a. The time at which the flame reaches the target. This is achieved by calculating the 

flame height as a function of time using the heat release rate profile (e.g., heat 

release rate as a function of time) and fire diameter as input. 
Guidance on Fire Model Selection and Implementation 

3-10 

b. The time it takes the fire plume temperature to exceed the target damage 

temperature. This is achieved by calculating the plume temperature at the specified 

height as a function of time using the heat release rate profile (e.g., heat release rate 

as a function of time) as an input. This approach can be considered conservative, as 

it assumes that cable damage occurs when the gas temperature surrounding the 

target reaches the damage temperature (i.e., heating of the cable is ignored). 

c. The surface temperature of the cable as a function of time, given a heat flux profile 

generated by the flame or plume. 

If non-target raceways are located between the ignition source and the target, the contributions 

of intervening combustibles need to be considered in the analysis. For example, consider a 

panel fire that ignites the first of a stack of trays overhead. The fire involving the combination of 

the panel and first tray may then ignite the second tray in the stack, and the fire may progress to 

damaging the target raceway. Considerations of the intervening combustibles in the analysis 

include the heat release rate contribution and the corresponding effects on the target heating 

time. See Scenario 2 below for guidance on treatment of intervening combustibles. 

In addition to the guidance provided above, the analyst should determine whether Hot Gas 

Layer effects are relevant in the scenario. The portion of the fire plume immersed in the Hot 

Gas Layer entrains air at higher temperatures (i.e., the Hot Gas Layer temperature) and is 

expected to have increased temperatures when compared with portions of the fire plume 

outside the Hot Gas Layer. In scenarios consisting of targets located relatively close to the 

ignition source (which is the case of the scenario discussed in this section), the Hot Gas Layer 

effects on the plume temperature are generally not considered, as the time to target damage is 

expected to be relatively short. For scenarios involving targets in the fire plume, located 

relatively far from the ignition source, the Hot Gas Layer effects on target heating should be 

considered. In the latter case, the room geometry and ventilation (both natural and mechanical) 

conditions should be captured by the analysis. 

3.2.1.3 Recommended Models 

Algebraic Models 

The applicable models in the FIVE-REV1 are recommended for this scenario, provided that the 

configuration is within the correlation basis and that there are no significant Hot Gas Layer 

effects. Heskestad’s flame height correlation is an alternative for determining flame height. 

Similarly, Heskestad’s fire plume temperature correlation is an alternative for determining plume 

temperature and diameter (Heskestad, 2002). The FDTs

 models do not allow the HRR to be 

input as a function of time, and, as a result, cannot be used to determine a failure time based on 

an HRR. 

The correlations listed above are particularly applicable for scenarios consisting of targets 

relatively close to the ignition source, where Hot Gas Layer effects are not considered in the 

analysis. 

As noted above, the time to damage is the minimum of either (1) the time at which the flame 

reaches the target or (2) the time it takes the fire plume temperature to exceed the target 

damage temperature. For FIVE, this is simply the time at which the HRR reaches the value 

required for either of the failure criteria. 
Guidance on Fire Model Selection and Implementation 

3-11 

Zone Models 

Zone models can be used for this scenario. To do so, set up the necessary input file that 

includes a “target” in the location of the electrical cable of interest with the corresponding 

thermophysical properties so that the surface temperature of the cable can be tracked. Zone 

models have the ability to include Hot Gas Layer effects in their calculation of plume 

temperature, and are thus particularly appropriate for scenarios where the Hot Gas Layer 

temperature interacts with the fire plume at the location of the target. 

Again, the time to damage is the minimum of either (1) the time at which the flame reaches the 

target or (2) the time it takes the fire plume temperature to exceed the target damage 

temperature. The zone models routinely calculate and report these values. 

CFD Model 

Although a CFD model could be used for analyzing this scenario, the level of detail and 

resolution offered by a CFD calculation is not necessary. On the other hand, the model would 

be particularly applicable if the scenario involves obstructions between the fire and the target 

inside the fire plume or if Hot Gas Layer effects are significant. The effects of these 

obstructions on the exposure conditions are not captured by algebraic models or zone models. 

3.2.1.4 Detailed Examples 

Readers are referred to Appendix B, which describes the analysis of an electrical cabinet fire in 

the switchgear room, and Appendix E, which describes the analysis of a transient fire in a cable 

spreading room. 
Guidance on Fire Model Selection and Implementation 

3-12 

3.2.2 Scenario 2: Targets Inside or Outside the Hot Gas Layer 

This scenario consists of a target, such as an electrical cable in a raceway, located inside or 

outside the Hot Gas Layer produced by a fire involving an ignition source, such as an electrical 

cabinet, and a secondary fuel source, such as an electrical raceway. An example of this type of 

scenario is depicted in Figure 3-4. 

Figure 3-4 Pictorial representation of scenario 2

3.2.2.1 General Objective 

The objective of this scenario is to calculate the time to damage for a target inside or outside the 

Hot Gas Layer produced by a fire. Also, the time to ignition of a secondary fuel source and the 

resulting contribution to the total heat release rate can be determined. For the case shown in 

Figure 3-4, the target is a cable in an electrical raceway and the fire source is an electrical 

cabinet.. 

3.2.2.2 Modeling Strategy 

Two levels of analysis can be employed: (1) algebraic models for the average room temperature 

as an indicator of the gas temperature surrounding the target, or (2) detailed heat transfer 

analysis for determining the target temperature. 

The first strategy consists of determining the overall room temperature using a algebraic model 

(e.g., the MQH room temperature model) (McCaffrey et al., 1981). Such a calculation will 

indicate whether the target may be subjected to damaging temperatures and the time at which 

such temperatures may be observed. It should be noted that the room needs to be represented 

as a rectangular parallelepiped and the area of all the surfaces in the room must be conserved. 

In addition, if the target cable tray is relatively close, the target may be damaged by radiant 

heating. This can be assessed with simple point source estimates that only require the heat 

release rate of the fire, the separation distance between the fire and the target, and the damage 

criteria (i.e., critical flux for damage). 
Guidance on Fire Model Selection and Implementation 

3-13 

The second strategy is best addressed with a model capable of including detailed heat transfer 

analysis for determining the target temperature. A raceway outside the fire plume may be 

exposed to Hot Gas Layer conditions if the smoke accumulating in the upper part of the room 

(i.e., the Hot Gas Layer) descends to the location of the raceway. Consequently, targets 

outside the fire plume are initially exposed to “lower layer” (i.e., below the Hot Gas Layer) 

conditions. As the smoke continues to accumulate, the target is immersed in Hot Gas Layer 

conditions. As heat transfer conditions will be different for each case, a model with the 

capability of tracking the relevant/applicable heat transfer interaction and calculations as a 

function of time, such as a zone or a CFD model, should be selected to handle this scenario at 

the desired level of resolution. 

With regard to the secondary fuel source, three distinct additional analyses must be made to 

determine: 

 The time at which the secondary fuel source ignites, 

 The heat release rate of the secondary fuel source, and 

 The combined heat release rate of the primary and secondary fires. 

The more detailed models, such as FDS, can handle the ignition and contribution of multiple 

fires, provided that the ignition criteria and source heat release rate characteristics are provided 

as input. Other models, especially the algebraic models, only accept the total heat release rate 

as a function of time, which is found by summing up the individual heat release rates. 

In the present example, consider a cable tray directly above the fire. The time to ignition of the 

cable tray can be determined via algebraic models that estimate the flame height and plume 

temperature as a function of time for the initial cabinet fire (see Scenario 1 above). Once the 

flames from the cabinet reach the cable tray, it can be assumed to ignite. The same is true 

when the plume temperature at the elevation of the cable tray reaches the ignition temperature 

of the cables. Both calculations should be completed, and the shorter time used as the ignition 

time. 

The heat release rate from the cable tray can be added to the heat release rate of the cabinet to 

determine a combined heat release rate as a function of time. This total rate can then be used 

in the various models as an approximation of the heat release rate as a function of time. 

Appendix R of NUREG/CR-6850 (EPRI 1011989) addresses cable fires, including methods for 

calculating the heat release rate for a variety of cable configurations. 

It should be noted that the simple summation of the two heat release rates is a simplification of 

a complex phenomenon and only provides a first-order approximation of the conditions created 

by the two separate fires. 

3.2.2.3 Recommended Modeling Tools 

Algebraic Models 

Select the appropriate Hot Gas Layer (or room temperature) model and then collect the required 

inputs, including room size, opening sizes, boundary material properties, forced ventilation, and 

the heat release rate profiles for the initial and secondary fuel packages. For screening 

purposes, the use of algebraic models is recommended as long as the contributions of the first 

item ignited and intervening combustibles are considered. As was mentioned earlier, this 

approach will provide a first-order approximation of the room temperature in which the target 

may be immersed. The methods used by algebraic models to address the secondary fire 
Guidance on Fire Model Selection and Implementation 

3-14 

source are discussed above. Target damage due to radiant heating can be estimated using 

algebraic models; all that is required is the heat release rate of the fire (as a function of time), 

the separation distance between the fire and the target, and damage criteria (i.e., critical flux for 

damage). 

Zone Models 

Zone models provide a good alternative for modeling this scenario, as they provide the incident 

heat flux profile, the surface temperature, and the internal temperature of the target in one 

simulation. Set up the necessary input file with the required inputs, including room size, 

opening sizes, boundary material properties, heat release rate, fire diameter and a target, and 

fire location so that the cable’s surface temperature can be predicted. 

Zone models also have the benefit of being able to handle secondary fire sources as separate 

entities. Secondary fires can be ignited at a prescribed time, temperature, or heat flux. 

However, zone models have limited capabilities for handling obstructions. 

Target damage due to radiant heating from the fire is easily handled by zone models, as long as 

there are no obstructions between the fire and the target that block radiant heat transfer. Zone 

models can also account for radiant heating of targets by the Hot Gas Layer. 

CFD Model 

The use of CFD models for this scenario is recommended for complex geometries capable of 

affecting the location of the Hot Gas Layer and the incident heat flux to the targets, or when 

greater accuracy of the ignition and contribution of secondary fires is warranted. For instance, 

obstructions between the ignition source and the target affect the heat balance at the surface of 

the target. The CFD model will require inputs similar to the ones collected for the zone models; 

however, the compartment geometry will need to be specified in greater detail. 

Due to their detailed calculations, CFD models are best able to model secondary fire sources, 

including their ignition and subsequent contribution to the heat release rate within the enclosure. 

Like zone models, CFD models can handle targets damaged by radiant heating from the fire 

and the Hot Gas Layer. CFD models can also include the effects of obstructions between the 

fire and the target. 

3.2.2.4 Detailed Examples 

Appendix C describes the analysis of a relatively large oil fire affecting a raceway in a pump 

room, and Appendix E describes the analysis of a transient fire in a cable spreading room. 
Guidance on Fire Model Selection and Implementation 

3-15 

3.2.3 Scenario 3: Targets Located in Adjacent Rooms 

This scenario consists of a target, such as an electrical cable in a raceway, in a room adjacent 

to the room of fire origin. An opening connecting the room of origin to the adjacent room allows 

combustion products to enter the adjacent room. An example of this type of scenario is 

depicted in Figure 3-5 for the case in which there is an opening in the wall. 

Figure 3-5. Pictorial representation of scenario 3

3.2.3.1 General Objective 

The objective of this scenario is to calculate the time to damage for a target in the Hot Gas 

Layer in a room adjacent to the room of fire origin. For the case shown in Figure 3-5, the target 

is a cable in an electrical raceway and the fire source is an electrical cabinet. 

3.2.3.2 Modeling Strategy 

The recommended strategy for determining the temperature of targets located in a room 

adjacent to the room of fire origin consists of four basic steps: 

1. Determine the following characteristics for the Hot Gas Layer in the room of fire origin and 

the adjacent compartment: 

a. Temperature as a function of time 

b. Depth as a function of time 

2. Determine the incident heat flux surrounding the target cable. 

3. Determine the surface and internal temperature of the target cable. 

4. Compare the surface or internal temperature of the target with its damage temperature. 

Note that this approach assumes that the effort required to model adjacent rooms is justified. 

One way to approach this (using algebraic models or zone models) is to first model the HGL 

temperature in the room of origin and the resulting effect on remote targets in the room. If this 

approach indicates that target damage/ignition is unlikely in the room of origin, it would be safe 

to assume that there would be little benefit in evaluating similar targets in adjacent spaces. 

However, if target damage is possible in the room of origin, the next step may be to model the 
Guidance on Fire Model Selection and Implementation 

3-16 

room of origin and the adjacent room as one combined volume and determine whether the 

resulting HGL is capable of causing damage/ignition of the target(s). If target damage in the 

combined volume is not likely, then it may not be worth the added effort to model the adjacent 

room(s) as separate volumes using more detailed modeling methods. 

3.2.3.3 Recommended Modeling Tools 

Algebraic Models 

Generally, algebraic models are not recommended for this calculation, as a model capable of 

tracking fire conditions in adjacent rooms is necessary. Zone and CFD models will provide this 

capability. However, as an approximation, algebraic models could be used to model the HGL 

temperatures for determining whether damage to targets in adjacent rooms is possible. One 

way to approach this, using algebraic models, is to model the room of origin and the adjacent 

room as one combined volume to determine whether the resulting HGL is capable of causing 

damage to/ignition of the target(s). If this approach indicates that target damage/ignition is 

unlikely, it may not be worth the added effort to model the rooms as separate volumes using 

more detailed modeling methods, such as zone models. 

Zone Models 

The zone model is an appropriate tool for addressing this scenario. Zone models would provide 

an efficient tool for scenarios involving relatively simple geometries (i.e., geometries and 

openings that can be easily represented in rectangular parallelepipeds without compromising 

the technical elements in the analysis). Consequently, the room geometry should be 

represented as accurately as possible. One of the primary outputs of zone models is the height 

and temperature of the Hot Gas Layer versus time in each of the rooms specified in the 

computational domain. Zone models are also capable of determining target temperature (not 

just the temperature of the gases surrounding the target), given the boundary conditions 

generated by the fire and the thermophysical properties of the target. 

CFD Model 

A CFD model would be particularly appropriate for addressing targets located in adjacent rooms 

in scenarios with complex geometries (i.e., geometries that can’t be easily represented as 

rectangular parallelepipeds). CFD models will be able to describe the geometry of the 

compartment in detail, including the opening(s) providing smoke migration paths to the adjacent 

room. 

3.2.3.4 Detailed Examples 

Readers are referred to Appendix G, which describes the analysis of targets in rooms remote 

from the fire room. 
Guidance on Fire Model Selection and Implementation 

3-17 

3.2.4 Scenario 4: Targets in Rooms with Complex Geometries 

This scenario involves a room with an irregular ceiling height. Figure 3-6 provides a pictorial 

representation of an example of this type of scenario. The target in the example shown in 

Figure 3-6 is a cable tray located away from the ignition source that may eventually be 

immersed in the Hot Gas Layer. 

Figure 3-6. Pictorial representation of scenario 4

3.2.4.1 General Objective 

The objective of this scenario is to calculate the time to damage for a target in the Hot Gas 

Layer in a room with a complex geometry. For the case shown in Figure 3-6, the target is a 

cable in an electrical raceway and the fire source is an electrical cabinet. 

3.2.4.2 Modeling Strategy 

Two strategies are available: (1) a first-order approximation using algebraic models and a 

simplification of the complex geometry for determining the room temperature as an indicator of 

the gas temperature surrounding the target, or (2) a detailed heat transfer analysis to determine 

the target’s temperature while attempting to capture the details of the complex geometry. 

The first strategy consists of determining the overall room temperature with an algebraic model 

(e.g., the MQH room temperature model), which would indicate whether the target may be 

subjected to damaging temperatures and the time at which such temperatures may be 

observed. This approach requires that the complex geometry be reduced to a single equivalent 

volume, which in turn requires some caution. In the case of two different ceiling heights, a 

correlation like MQH may underestimate the temperature of the smaller volume and 

overestimate the temperature of the larger. The fire’s energy is conserved, but it is not 

expected to be uniformly distributed if the ceiling height is not uniform. 
Guidance on Fire Model Selection and Implementation 

3-18 

The second alternative is best addressed by a model capable of capturing more than one room 

in a computational domain. A raceway outside the fire plume may be exposed to Hot Gas Layer 

conditions if the smoke accumulating in the upper part of the room eventually reaches the 

location of the raceway. In complex geometries, HGL development can be significantly 

impacted by mixing associated with spilling and venting, and these can only be modeled by 

zone and field models. Clearly, complex geometries will have complex heat transfer conditions, 

and should be handled by a model capable of tracking the relevant/applicable heat transfer 

interaction and calculations as a function of time, such as a zone or a field model. 

3.2.4.3 Recommended Modeling Tools 

Algebraic Models 

Detailed analyses of complex geometries typically cannot be accomplished with algebraic 

models. However, for screening purposes, it is possible to use algebraic models. As mentioned 

earlier, this approach can provide a first-order approximation of the HGL temperature in which 

the target may be immersed. To utilize this approach, first select the appropriate Hot Gas Layer 

(or room temperature) model and then collect the required inputs, including room size, opening 

sizes, boundary material properties, and heat release rate. Next, the complex geometry must 

be reduced to a single equivalent volume while maintaining total surface area (due to the 

importance of energy losses through the bounding surfaces) and ceiling height, It should be 

noted that the more complex the space, the less ideal the equivalent volume/area approximation 

becomes. Based on the estimates derived using the algebraic models, more detailed modeling 

may be indicated. 

Zone Models 

Zone models should also be used with caution when modeling this scenario. If the entire space 

is modeled, the interface between lower and upper compartments is treated as a big door. The 

entrainment correlations used by the zone model to handle vertical vents were not designed for 

such large open “doors.” 

CFD Model 

CFD models may be required when detailed analyses of complex geometries capable of 

affecting fire development and the location of the Hot Gas Layer and the incident heat flux to the 

target are desired. CFD models are expected to better estimate the overall compartment 

temperatures, both upper and lower, because there are no assumptions in the basic 

methodology about uniform ceilings. 

3.2.4.4 Detailed Examples 

Readers are referred to Appendix D, which consists of a switchgear fire in a room with a 

complex geometry, and Appendix H, which consists of a fire inside the containment annulus. 
Guidance on Fire Model Selection and Implementation 

3-19 

3.2.5 Scenario 5: Main Control Room Abandonment 

This scenario consists of a fire, such as an electrical cabinet fire within the main control board, 

that may force operators out of the control room. A schematic diagram of an example of this 

type of scenario is shown in Figure 3-7. Notice the presence of a suspended ceiling in the 

control room in the example shown. 

Figure 3-7. Pictorial representation of scenario 5

3.2.5.1 General Objective 

The object of this scenario is to determine when control room operators will need to abandon 

the control room due to fire-generated conditions inside the room. 

3.2.5.2 Modeling Strategy 

Control room abandonment is assumed to be solely dependent on habitability conditions. As 

mentioned in the previous sections, control room operators are considered “targets” in this 

scenario, so it is necessary to establish the fire conditions that would force operators out of the 

control room. This can be considered as the “abandonment criteria”; for example, visibility, 

temperature, heat flux, and toxicity are often the habitability indicators in these scenarios. 

Keeping track of these conditions may suggest the time at which the operator may need to 

abandon the control room. Once the criteria have been established (see Chapter 11 of 

NUREG/CR-6850 (EPRI 1011989) for details on habitability conditions), the fire-generated 

conditions in the room can be calculated so that the abandonment time can be determined. 

For Main Control Room analyses, two ventilation conditions should be taken into consideration: 

(1) the ventilation system is turned off, causing hot gases and smoke to accumulate inside the 

control room, and (2) the ventilation system is on smoke-purge mode. 
Guidance on Fire Model Selection and Implementation 

3-20 

3.2.5.3 Recommended Modeling Tools 

Algebraic models 

Algebraic models are not recommended for this analysis. Determining habitability and time to 

abandonment in a fire scenario often requires tracking numerous output variables 

simultaneously. Algebraic models do not provide this capability. 

Zone Models 

Unlike algebraic models, zone models are capable of simultaneously tracking a number of 

relevant output variables (i.e., habitability conditions) in this scenario, so they provide a good 

solution to modeling fires in main control rooms. They are also capable of modeling the impact 

of various ventilation configurations required for modeling control room abandonment. 

CFD Model (FDS) 

Field models are also a good alternative to address this scenario, particularly if complex 

geometries are involved. Field models have the added advantage of handling rooms with 

complex geometries, intervening combustibles and obstructions, and varying ventilation 

conditions. 

3.2.5.4 Detailed Examples 

Readers are referred to Appendix A, which describes the analysis of a fire in a main control 

room. 
Guidance on Fire Model Selection and Implementation 

3-21 

3.2.6 Scenario 6: Smoke Detection and Sprinkler Activation 

This scenario consists of calculating smoke/heat detector or sprinkler response. In some 

situations, the detection devices may be shielded from the combustion products by an 

obstruction (e.g., beams, cable trays, HVAC ducts, etc.). Failure of a detector to respond to a 

fire will delay the appropriate response of either the fire brigade or an automatic suppression 

system. Typical scenarios are shown in Figure 3-8. 

Figure 3-8. Pictorial representation of scenario 6

3.2.6.1 General Objective 

The objective of this scenario is to calculate the response time of a smoke or heat detector that 

may be obstructed by ceiling beams, ventilation ducts, etc. 
Guidance on Fire Model Selection and Implementation 

3-22 

3.2.6.2 Modeling Strategy 

For scenarios involving unobstructed smoke detector devices: 

1. Determine the location of the detection device relative to the fire. 

2. Select the detector response (activation) criteria. Chapter 11 of NUREG/CR-1805 contains 

guidance on estimating smoke detector response times. 

3. Calculate the detection time using the appropriate model. 

For scenarios involving obstructed smoke detector devices: 

1. Determine the following characteristics of the Hot Gas Layer using all the necessary inputs 

for a Hot Gas Layer calculation, as described earlier in this chapter. 

a. Temperature as a function of time. 

b. Depth as a function of time. The smoke detector is expected to activate shortly after 

the Hot Gas Layer reaches the bottom of the obstruction and spills into the location 

of the device. 

2. Select the detector response (activation) criteria. Chapter 11 of NUREG/CR-1805 contains 

guidance on estimating smoke detector response times. 

3. Calculate the response time of the given smoke detector once the combustion products 

reach the detector. 

For scenarios involving thermal devices (e.g., sprinklers, fusible links, or heat detectors), the 

process is similar. The only difference is that the thermal device needs to be characterized with 

relevant parameters, typically an activation temperature and the response time index (RTI). In 

addition, the selected model should account for the heating process of thermally thin elements 

(i.e., the heat detector device). 

3.2.6.3 Recommended Modeling Tools 

Algebraic models 

Algebraic models can be used to determine time to heat or smoke detection when the fireinduced flows are not obstructed before reaching the detection device. By contrast, algebraic 

models are typically not recommended when fire-induced flows, such as fire plumes or ceiling 

jets, will be obstructed before reaching the detection device. In some cases, algebraic models 

that estimate the HGL temperature as a function of time may be used for rough estimates of 

activation times. 

Zone Models 

Zone Models can address the different scenario conditions presented above; for instance, 

CFAST and MAGIC are capable of determining time to smoke or heat detection, assuming no 

obstructions, and can simultaneously calculate smoke accumulation so that the time for smoke 

detection activation can be estimated. This would provide a first-order approximation, as zone 

models do not directly account for complex geometries, including obstructions. These models 

are not recommended for determining time to heat detection in obstructed geometries, since the 

velocity of the gases impacting the heat detector is not available in zone model calculations. As 

mentioned above, in some cases the HGL temperature alone may be used as a rough indicator 

of smoke and heat activation times. 
Guidance on Fire Model Selection and Implementation 

3-23 

CFD Model 

CFD models are the best tool for estimating time to fire detection in complex geometries, 

including obstructions, as they can describe the compartment’s complex geometries and 

mechanical ventilation conditions in detail. 

3.2.6.4 Detailed Examples 

Readers are referred to Appendices B and E, which discuss the calculation of the time to smoke 

and heat activation.
Guidance on Fire Model Selection and Implementation 

3-24 

3.2.7 Scenario 7: Fire Impacting Structural Elements 

This scenario consists of fire, such as an electrical cabinet, impacting exposed structural 

elements in the room. A typical example of this type of scenario is depicted in Figure 3-9. 

Figure 3-9. Pictorial representation of scenario 7

3.2.7.1 General Objective 

The objective of this scenario is to characterize the temperature of structural elements exposed 

to a nearby fire source. For the case shown in Figure 3-9, the exposure fire is an electrical 

cabinet. 

3.2.7.2 Modeling Strategy 

The fire modeling tools within the scope of this guide should indicate whether the exposed 

structural element will reach damaging temperatures. However, this information is often not 

enough to determine whether the structural integrity of the compartment will be compromised by 

the exposing fire conditions. A more detailed structural analysis (i.e., one that involves complex 

temperature-dependent load-bearing calculations) may be necessary if such a determination is 

necessary. 

Considering the limitations listed above, the following general guidance is provided: 

1. Determine whether the structural element is directly above the fire, within the ceiling jet, 

exposed to radiant heating, or within the Hot Gas Layer. The results of this determination 

will suggest which model or combination of models should be used. 

2. Calculate the temperature of the structural element based on the fire conditions affecting it. 

This will require an initial estimate of the fire-generating conditions surrounding the structural 

element, and, subsequently, the temperature of the element itself. 
Guidance on Fire Model Selection and Implementation 

3-25 

3.2.7.3 Recommended Modeling Tools 

Algebraic models 

Provided that the fire conditions affecting the structural element are appropriately identified 

(e.g., a fire plume, a ceiling jet, flame radiation, or a Hot Gas Layer exposure without significant 

contributions from any of the other three exposure mechanisms), algebraic models may be 

capable of determining whether the structural element will be exposed to damaging conditions. 

For example, plume temperature correlations can be used to determine the gas temperature 

surrounding an element inside the fire plume. MQH calculations can indicate whether 

compartment temperatures are near the critical temperature of structural elements; however, 

these may provide overly conservative estimates, as the algebraic models do not account for 

the heating of those structural elements that typically have large masses. Point source radiation 

calculations can be used to estimate the heat flux to structural elements that are not directly in 

the plume but close enough to the fire to become significantly heated. 

Zone Models (CFAST and MAGIC) 

Zone models are an appropriate tool to address this scenario, as the input file can be developed 

to capture the relative location of the fire and the structural element(s). Structural elements can 

be represented as a target, and the incident fire conditions can be tracked during the fire. 

Importantly, zone models are also capable of performing conduction heat transfer calculations 

for the structural element, resulting in a prediction of the temperature of the element itself. 

CFD Model (FDS) 

Field models are the best tool for estimating temperatures in structural elements in complex 

geometries, including obstructions, as they can handle the compartment’s complex geometries, 

fire development, and mechanical ventilation conditions in detail, as well as the heating of the 

structural elements. 

3.2.7.4 Detailed Examples 

Readers are referred to Appendix F, which describes the analysis of a lubricating oil fire’s effect 

on structural elements. 

 
Guidance on Fire Model Selection and Implementation 

3-26 

 
4-1 

4

MODEL UNCERTAINTY 

The fire models discussed in this Guide are classified as deterministic to distinguish them from 

statistical models. In essence, this means that each model takes as input a set of values, 

known as input parameters, that describe a specific fire scenario, and the model’s algorithms 

then calculate the thermal conditions within the compartment. The output of the models usually 

takes the form of time histories of the various quantities of interest. In a sense, the model 

calculation is a virtual experiment because the design of a model simulation often involves the 

same thought process as the design of a physical experiment. The results of the calculation are 

likewise expressed in terms similar to those of an experiment, including an estimate of the 

uncertainty. The sources of uncertainty in a model prediction are different than those in an 

experimental measurement. According to NUREG-1855, Volume 1, Guidance on the Treatment 

of Uncertainties Associated with PRAs in Risk-Informed Decision Making (2009), there are three 

types of uncertainty associated with a model prediction: 

Parameter Uncertainty: Input parameters are often chosen from statistical distributions or 

estimated from generic reference data. In either case, the uncertainty of these input parameters 

is propagated through the calculation, and the resulting uncertainty in the model prediction is 

known as the parameter uncertainty. The process of determining the extent to which the 

individual input parameters affect the results of the calculation is known as a sensitivity analysis. 

Model Uncertainty: Idealizations of physical phenomena lead to simplifying assumptions in the 

formulation of the model equations. In addition, the numerical solution of equations that have 

no analytical solution can lead to inexact results. Model uncertainty is estimated via the 

processes of verification and validation. The first seeks to quantify the error associated with the 

mathematical solution of the governing equations, typically through numerical analysis, while the 

second seeks to quantify the error associated with the simplifying physical assumptions, 

typically through comparison of model predictions and full-scale experiments. 

Completeness Uncertainty: This refers to the fact that a model may not be a complete 

description of the phenomena it is designed to predict. Some consider this a form of model 

uncertainty because most fire models neglect certain physical phenomena that are not 

considered important for a given application. For example, a model of sprinkler activation might 

neglect water condensation. 

The focus of this chapter is Model Uncertainty. The issue of Parameter Uncertainty will be 

addressed by discussing various ways to conduct a sensitivity analysis. Completeness 

Uncertainty is addressed by the description of the algorithms found in the model documentation. 

It is addressed, indirectly, by the same process used to address the Model Uncertainty. 
Model Uncertainty 

4-2 

4.1 Validation of the Fire Models 

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

of their limitations and predictive capabilities. NFPA 805 (NFPA, 2001) states that fire models 

shall only be applied within the limitations of the given model and shall be verified and validated. 

To support risk-informed/performance-based fire protection and implementation of the voluntary 

rule that adopts NFPA 805 as an RI/PB alternative, the NRC RES and EPRI conducted a 

collaborative project for the V&V of the five selected fire models described in Chapter 2. The 

results of this project were documented in NUREG-1824 (EPRI 1011999), Verification and 

Validation of Selected Fire Models for Nuclear Power Plant Applications. 

Twenty-six full-scale fire experiments from six different test series were used to evaluate the 

models’ ability to estimate thirteen quantities of interest for fire scenarios that were judged to be 

typical of those that might occur in an NPP. The results of the study are summarized in Table 

4-1. An explanation of this table is to follow. 

Table 4-1. Results of the V&V study, NUREG-1824 (EPRI 1011999). 

Output Quantity 

FDTs FIVE CFAST MAGIC FDS Exp 

ா෤ߪ ெ෤ߪ ߜ ெ෤ߪ ߜ ெ෤ߪ ߜ ெ෤ߪ ߜ ெ෤ߪ ߜ

HGL Temperature Rise 1.44 0.25 1.56 0.32 1.06 0.12 1.01 0.07 1.03 0.07 0.07

HGL Depth N/A N/A 1.04 0.14 1.12 0.21 0.99 0.07 0.07

Ceiling Jet Temp. Rise N/A 1.84 I.D. 1.15 I.D. 1.01 0.08 1.04 0.08 0.08

Plume Temperature Rise 0.73 I.D. 0.94 I.D. 1.25 0.28 1.01 0.07 1.15 I.D. 0.07

Flame Height* I.D. I.D. I.D. I.D. I.D. I.D. I.D. I.D. I.D. I.D. I.D. 

Oxygen Concentration N/A N/A 0.91 I.D. 0.90 0.18 1.08 0.14 0.05

Smoke Concentration N/A N/A 2.65 I.D. 2.06 I.D. 2.70 I.D. 0.17

Room Pressure Rise N/A N/A 1.13 0.37 0.94 0.39 0.95 0.51 0.20

Target Temperature Rise N/A N/A 1.00 0.27 1.19 0.27 1.02 0.13 0.07

Radiant Heat Flux 2.02 I.D. 1.42 0.55 1.32 0.54 1.07 0.36 1.10 0.17 0.10

Total Heat Flux N/A N/A 0.81 0.47 1.18 0.35 0.85 0.22 0.10

Wall Temperature Rise N/A N/A 1.25 0.48 1.38 0.45 1.13 0.20 0.07

Wall Heat Flux N/A N/A 1.05 0.43 1.09 0.34 1.04 0.21 0.10

I.D. indicates insufficient data for the statistical analysis. 

N/A indicates that the model does not have an algorithm to compute the given Output Quantity 

* All of the models except FDS use the Heskestad Flame Height Correlation (Heskestad, SFPE 

Handbook). These models were shown to be in qualitative agreement with the experimental 

observations, but there was not enough data to further quantify this assessment. 
Model Uncertainty

4-3 

The Models: Five fire models were selected for the study, based on the fact that they are 

commonly used in fire analyses of NPPs in the U.S. Two of the models consist of simplified 

engineering correlations (FDTs and FIVE), two are “zone” models (CFAST and MAGIC), and 

one is a CFD model (FDS). 

The Experiments: Six series of experiments (26 individual fire experiments in all) were selected 

for the NRC/EPRI fire model validation study (NUREG-1824/EPRI 1011999). Each series 

represented a typical fire scenario (for example, a fire in a switchgear room or turbine hall); 

however, the test parameters could not encompass every possible NPP fire scenario. To better 

understand the range of applicability of the validation study, Table 2-5 of NUREG-1824 (EPRI 

1011999), Volume 1 lists various normalized parameters that may be used to compare NPP fire 

scenarios with the validation experiments. These parameters express, for instance, the size of 

the fire relative to the size of the room, or the relative distance from the fire to critical equipment. 

This information is important because typical fire models are not designed for fires that are very 

small or very large in relation to the volume of the compartment or the ceiling height. 

For a given set of experiments and NPP fire scenarios, the user can calculate the relevant 

normalized parameters. These parameters will either be inside, outside, or on the margin of the 

validation parameter space. Consider each case in turn: 

1 If the parameters fall within the ranges that were evaluated in the validation study, then 

Table 4-1 can be referenced directly. 

2 If only some of the parameters fall within the range of the study, additional justification is 

necessary. This is a common occurrence because realistic fire scenarios involve a variety 

of fire phenomena, some of which are easier to estimate than others. A case in point is the 

burning of electrical cabinets and cables. NUREG-1824 (EPRI 1011999) does not address 

these fires directly, even though some of the experiments used in the study were intended 

as mock-ups of control or switchgear room fires. For scenarios involving these kinds of 

fires, the heat release rates are often taken from experiments rather than predicted by a 

model. It has been shown, in NUREG-1824 (EPRI 1011999) and other validation studies, 

that the models can estimate the transport of smoke and heat with varying degrees of 

accuracy, but they have not been shown (at least not in NUREG-1824 (EPRI 1011999)) to 

estimate the details of the fire’s ignition and growth. While this does not eliminate the 

models from the analysis, it still restricts their applicability to only some of the phenomena. 

3 If the parameters fall outside the range of the study, then a validation determination cannot 

be made based on the results from the study. The modeler needs to provide independent 

justification for using the particular model. For example, none of the experiments 

considered in NUREG-1824 (EPRI 1011999) were under-ventilated. However, several of 

the models have been independently compared to under-ventilated test data, and the results 

have been documented either in the literature or in the model documentation. As another 

example, suppose that the selected model uses a plume, ceiling jet, or flame height 

correlation outside the parameter space of NUREG-1824 (EPRI 1011999) but still within the 

parameter space for which the correlation was originally developed. In such cases, 

appropriate references are needed to demonstrate that the correlation is still appropriate 

even if not explicitly validated in NUREG-1824 (EPRI 1011999). 

The Predicted Quantities: The experimental data for the validation study consisted of 

measurements of one or more of the 13 physical quantities listed in the table. The FDTs

 and 

FIVE do not possess algorithms to estimate every quantity, in which case the table cell is 

labeled N/A. 
Model Uncertainty 

4-4 

The Statistics: For each model and output quantity, a summary plot of the results is presented 

in NUREG-1824 (EPRI 1011999). For example, Figure 4-1 compares the measured and 

predicted target temperatures for the model FDS. If a particular prediction and measurement 

are the same, the resulting point falls on the solid diagonal line. The longer-dashed off-diagonal 

lines indicate the experimental uncertainty. Roughly speaking, points within the longer dashed 

lines are said to be “within experimental uncertainty,” and in such cases it is not possible to 

further quantify the accuracy of the prediction. Points falling outside the experimental 

uncertainty bounds cannot be said to be free of model uncertainty. At the time of the publication 

of NUREG-1824 (EPRI 1011999), the writing team decided to assign the colors Green and 

Yellow to indicate the degree to which the model predictions are inside or outside of the 

experimental uncertainty bounds. However, since the writing of NUREG-1824 (EPRI 1011999), 

it was decided by the authors of the Fire Model User’s Guide to replace the color system with a 

more quantifiable metric of model accuracy. 

Figure 4-1. Sample set of results from NUREG-1824 (/EPRI 1011999). 

Consider again Figure 4-1. To better make use of results such as these, two statistical 

parameters5

 have been calculated for each model and each predicted quantity. The first 

parameter, ߜ, is the bias factor. It indicates the extent to which the model, on average, under or 

overpredicts the measurements of a given quantity. For example, the bias factor for the data 

shown in Figure 4-1 is 1.02. This means that the model has been shown to slightly overestimate target temperatures by 2%, on average, and this is shown graphically by the red dashdot line just above the diagonal. The bias factor for each model and each output quantity is 

listed in Table 4-1. 

 

5

 The statistical parameters listed in Table 4-1 are based on the versions of the fire models used in the 

V&V study, circa 2006. As the models are improved and new validation data introduced, these values 

may change. 

FDS Target Temperature

Measured Temperature (°C)

0 100 200 300 400 500 600 700

Predicted Temperature (°C)

0

100

200

300

400

500

600

700
Model Uncertainty

4-5 

The second statistic6 in Table 4-1 is the relative standard deviation of the model, ߪ෤ெ, and the 

experiments, ߪ෤ா. These indicate the uncertainty or degree of “scatter” of the model and the 

experiments, respectively. Referring again to Figure 4-1, there are two sets of off-diagonal 

lines. The first set, shown as long-dashed black lines, indicate the experimental uncertainty. 

The slopes of these lines are 1 േ 2ߪ෤ா (it is customary to express uncertainties in the form of “2-

sigma” or 95% confidence intervals). The second set of off-diagonal lines, shown as shortdashed red lines, indicates the model uncertainty. The slopes of these lines are ߜ േ 2ߪ෤ெ. If the 

model is as accurate as the measurements against which it is compared, the two sets of offdiagonal lines would merge. The extent to which the data scatters outside of the experimental 

bounds is an indication of the degree of model uncertainty. 

The derivation of the statistical parameters in Table 4-1 is provided in the next section, while 

their use is described here. Suppose that a model prediction is denoted ܯ. It is assumed that 

the “true” value of the predicted quantity is a normally distributed random variable with a mean, 

ߤ ൌ ܯ/ߜ, and a standard deviation, ߪൌߪ෤ெሺܯ/ߜሻ. Using these values, the probability of 

exceeding a critical value, ݔ௖, is: 

ܲሺݔ൐ݔ௖ሻ ൌ 1

2 erfc ൬

ߤ െ௖ ݔ

(4-1) ൰ 2√ߪ

Note that the complimentary error function is defined as follows: 

erfcሺݔሻ= 2

ߨ√

න ݁ି௧మ ஶ

௫

(4-2) ݐ݀

It is a standard function in mathematical or spreadsheet programs like Microsoft Excel7

. 

To summarize, the procedure for determining the probability that a quantity predicted by a 

model could exceed a critical value is as follows: 

1. Express the model prediction as a rise above its ambient value. Call this number ܯ. Note 

that the ambient value of most output quantities is zero. Temperature, oxygen 

concentration, and smoke layer height are exceptions. For these quantities, express the 

predicted value as a temperature rise, oxygen decrease below ambient, and layer depth. 

2. Using the values of ߜ and ߪ෤ெ from Table 4-1, compute the mean, ߤ ൌ ܯ/ߜ, and standard 

deviation, ߪൌߪ෤ெሺܯ/ߜሻ, of the normal distribution for the quantity of interest. 

3. Use the equation to compute the probability that the predicted quantity could exceed a 

critical value, ݔ௖. Remember to also express this critical value as a rise above ambient in 

the same way as the predicted value, ܯ.

A few examples of this procedure are included in Section 4.3. 

4.2 Derivation of the Model Uncertainty Statistics 

This section describes the derivation of the statistics listed in Table 4-1. These values 

summarize the results of the NRC/EPRI fire model validation study documented in NUREG1824 (EPRI 1011999). This section is included for information only; there is no need for a 

 

6

 For some models/quantities, there was an insufficient amount of data to calculate the relative standard 

deviation of the distribution, in which case I.D. is shown in the Table. 7

 Excel 2007 does not evaluate erfcሺݔሻ for negative values of ݔ, even though the function is defined for all 

real ݔ. In such cases, use the identity erfcሺെݔሻ ൌ 2 െ erfcሺݔሻ.
Model Uncertainty 

4-6 

model user to perform this type of calculation. McGrattan and Toman (2011) provide additional 

details on the development of these uncertainty calculations. 

For each of the fire models and each of the output quantities that were evaluated in the study, a 

plot similar to that shown in Figure 4-1 was produced. For each measurement point, a single 

experimental measurement was plotted against a single model prediction. The plot shows all 

the comparison points. The calculation of the statistics uses this set of measured and predicted 

values, along with an estimate of the experimental uncertainty. The purpose of the calculation 

is to “subtract off,” in a statistical sense, the experimental uncertainty so that the model 

uncertainty can be estimated. Before describing the calculation, a few assumptions must be 

made: 

1. The experimental measurements are assumed to be unbiased, and their uncertainty is 

assumed to be normally distributed with a constant relative standard deviation,  E

~ (that is, 

the standard deviation as a fraction of the measured value). Table 4-2 provides estimates of 

relative experimental uncertainties for the quantities of interest. 

2. The model error is assumed to be normally distributed about the predicted value multiplied 

by a bias factor, ߜ. The relative standard deviation of the distribution is denoted as ߪ෤ெ. 

The computation of the estimated bias and scatter associated with model error proceeds as 

follows. Given a set of ݊ experimental measurements, ܧ௜, and a corresponding set of model 

predictions, ܯ௜, compute the following: 

lnሺܯ/ܧሻ തതതതതതതതതതത ൌ 1

ሻ௜ܧ/௜ܯlnሺ෍ ݊

௡

௜ୀଵ

(4-3)

The standard deviation of the model error, ߪ෤ெ, can be computed from the following equation: 

ටߪ෤ெ

ଶ ൅ ߪ෤ாଶ ؆ ඩ 1

݊െ1෍ൣlnሺܯ௜/ܧ௜ሻ െ lnሺܯ/ܧሻ തതതതതതതതതതത൧

ଶ

௡

௜ୀଵ

(4-4)

The bias factor is: 

ߜ ൌ exp ቆlnሺܯ/ܧሻ തതതതതതതതതതത ൅

ெ෤ߪ

ଶ െ ߪ෤ாଶ

2 ቇ (4-5)

For a given model prediction, ܯ, the “true” value of the quantity of interest is assumed to be a 

normally distributed random variable with a mean of ܯ/ߜ and a standard deviation of ߪ෤ெሺܯ/ߜሻ. 

There are a few issues to consider when using this procedure: 

1. All values need to be positive, and each value needs to be expressed as an increase over 

its ambient value. For example, the oxygen concentration should be expressed as a 

positive number (i.e., the decrease in concentration below its ambient value). 

2. If the measurement uncertainty is overestimated, the model error will be underestimated. If 

the model error is less than the experimental uncertainty, the latter should be reevaluated. 

The model cannot be shown to have less error than the uncertainty of the experiment with 

which it is compared 
Model Uncertainty

4-7 

3. The procedure assumes that the quantity lnሺܯ/ܧሻ is normally distributed. This is not 

necessarily true, especially in cases where there are an insufficient number of points in the 

sample. Figure 4-2 provides two examples in which the normality of the validation data is 

tested8

. In cases where the data is not normally distributed, only the bias is reported. 

Table 4-2. Experimental uncertainty of the experiments performed as part of the validation 

study in NUREG-1824(EPRI 1011999) 

ࡱ෥࣌૛ Quantity

HGL Temperature Rise 0.14 

HGL Depth 0.13 

Ceiling Jet Temperature Rise 0.16 

Plume Temperature Rise 0.14 

Gas Concentration 0.09 

Smoke Concentration 0.33 

Pressure (no forced ventilation) 0.40 

Pressure (with forced ventilation) 0.80 

Heat Flux 0.20 

Surface or Target Temperature 0.14 

Figure 4-2. Two examples demonstrating how the validation data is tested for normality. 

4.3 How to Calculate the Model Uncertainty 

This section contains a few exercises to explain the procedure for calculating model uncertainty. 

These examples consider model uncertainty only; that is, it is assumed in each case that the 

input parameters are not subject to uncertainty. 

 

8

 The Kolmogorov-Smirnov test for normality has been applied using the software package SigmaPlot®10, 

Systat Software, Inc. The default P value of 0.05 was used. 

Interval Number

1 2 3 4 5 6 7 8 9 10

Number of Data Points

0

10

20

30

40

Wall Temperature

Normality Test: Pass

Plume Temperature, FDTs

Normality Test: Fail

Interval Number

1 2 3 4 5 6 7 8 9 10

Number of Data Points

0

1

2

3
Model Uncertainty 

4-8 

4.3.1 Example 1: Target Temperature 

Suppose that cables within a compartment are assumed to fail if their surface temperature 

reaches 330 °C (625 °F). The model FDS predicts that the maximum cable temperature due to 

a fire in an electrical cabinet is 300 °C (570 °F). What is the probability that the cables could 

fail? 

Step 1: Subtract the ambient value of the cable temperature, 20 °C (68 °F) to determine the 

predicted temperature rise. Refer to this value as the model prediction: 

ܯ ൌ 300 െ 20 ൌ 280Ԩ (4-6)

Step 2: Refer to Table 4-1, which indicates that, on average, FDS overpredicts Target 

Temperatures with a bias factor, ߜ, of 1.02. Calculate the adjusted model prediction: 

ൌ ߤ

ܯ

280 ൌ ߜ

1.02 ൌ 275°C (4-7)

Referring again to Table 4-1, calculate the standard deviation of the distribution: 

ߪൌߪ෤ெ ൬

ܯ

ߜ ൰ ൌ 0.13 ൬

280

1.02൰ ൌ 36°C (4-8)

Step 3: Calculate the probability that the actual cable temperature would exceed 330°C: 

ܲሺܶ ൐ 330ሻ ൌ 1

2 erfc ൬

ܶെܶ଴ െ ߤ

ߪ√2 ൰ ൌ 1

2 erfc ൬

330 െ 20 െ 275

36√2 ൰ ൌ 0.16 (4-9)

The process is shown graphically in Figure 4-3. The area under the “bell curve” for 

temperatures higher than 330 °C (625 °F) represents the probability that the actual cable 

temperature would exceed that value. Note that this estimate is based only on the model 

uncertainty. 
Model Uncertainty

4-9 

Figure 4-3. Normal distribution of the “true” value of the cable temperature in a 

hypothetical fire. 

4.3.2 Example 2: Critical Heat Flux 

As part of a screening analysis, the model MAGIC is used to estimate the radiant heat flux from 

a fire to a nearby group of thermoplastic cables. According to NUREG/CR-6850 (EPRI 

1011989), Appendix H, one of the damage criteria for thermoplastic cables is a radiant heat flux 

to the target cable that exceeds 6 kW/m2

. The model, by coincidence, predicts a heat flux of 

6 kW/m2

. What is the probability that the actual heat flux from a fire will be 6 kW/m2 or greater? 

Assume for this exercise that the model input parameters are not subject to uncertainty, only the 

model itself. 

Step 1: Unlike in the previous example, there is no need to subtract an ambient value of the 

heat flux (it is zero). Thus, the model prediction is: 

ܯൌ6 kW/mଶ (4-10)

Step 2: Refer to Table 4-1, which indicates that, on average, MAGIC overpredicts Radiant Heat 

Flux with a bias factor, ߜ, of 1.15. Calculate the adjusted model prediction: 

ൌ ߤ

ܯ

6 ൌ ߜ

1.15 ൎ 5.2 kW/mଶ (4-11)

Referring again to Table 4-1, calculate the standard deviation of the distribution: 

ߪൌߪ෤ெ ൬

ܯ

ߜ ൰ ൌ 0.36 ൬ 61.15൰ ൎ 1.9 kW/mଶ (4-12)

Step 3: Calculate the probability that the actual heat flux, ݍሶᇱᇱ, will exceed the critical value of the 

heat flux, ݍሶ௖

ᇱᇱ ൌ 6 kW/mଶ: 

Temperature (°C)

100 150 200 250 300 350 400 450 500

Probability Density Function

0.000

0.002

0.004

0.006

0.008

0.010

0.012

0.014

Model Prediction

Adjusted Model Prediction

P(T>330 °C)
Model Uncertainty 

4-10 

ܲሺݍሶᇱᇱ ൐ 6ሻ ൌ 1

2 erfc ቆ

௖ሶݍ

ᇱᇱ െ ߤ

ߪ√2 ቇ ൌ 1

2 erfc ൬

6 െ 5.2

1.9√2 ൰ ൎ 0.34 (4-13)

This is a somewhat surprising result. Even though the model predicts a peak radiant heat flux 

equal to the critical value, there is only a one in three chance that the actual heat flux would 

exceed this value. This is mainly due to the fact that MAGIC has been shown to over-estimate 

the heat flux by about 15%. 

It is important to note that this calculation of model uncertainty does not take into account the 

input parameters, such as the heat release rate of the fire. It is only an assessment of how well 

the model MAGIC can estimate the radiant heat flux to a target. 

4.4 Sensitivity Analysis 

The previous sections describe how to express the uncertainty of a model prediction resulting 

from the inherent limitations of the model itself. For that discussion, it was assumed that the 

input parameters for the model were not subject to uncertainty. However, there will always be 

uncertainty associated with the model input parameters. This section suggests ways to assess 

the impact of this kind of uncertainty on the final prediction. 

The more complex fire models discussed in this Guide may require dozens of physical and 

numerical input parameters for a given fire scenario. However, only a few of these parameters, 

when varied over their plausible range of values, will significantly impact the results. For 

example, the thermal conductivity of the compartment walls will not significantly affect a 

predicted cable surface temperature. Table 4-3 lists the input parameters whose impact on the 

given output quantity significantly outweighs all the other parameters. The heat release rate is 

almost always one of these. 

In Volume 2 of NUREG-1824 (EPRI 1011999), Hamins quantifies the functional dependence of 

these key input parameters (see Table 4-3). These relationships are based either on the 

governing mathematical equations or on algebraic models. The basic mathematical form of the 

relationship is: 

Output Quantity ൌ Constant × (Input Parameter)Power (4-14)

The exact value of the Constant is not important; rather, it is the Power that matters. The larger 

its absolute value, the more important the Input Parameter. According to the McCaffrey, 

Quintiere, Harkleroad (MQH) correlation, for example, the Hot Gas Layer (HGL) temperature 

rise in a compartment fire is proportional to the heat release rate raised to the two-thirds power: 

ܶെܶ଴ ൌ ܥܳሶ

ଶ/ଷ (4-15)

It is not the value of the constant, ܥ, that is important here, but rather the amount that the HGL 

temperature, ∆ܶ, changes due to a shift in the HRR, ∆ܳሶ. It is the two-thirds power dependence, 

as found in Table 4-3, that matters. To see why, take the first derivative of ܶ with respect to ܳሶ

and write the result in terms of differentials: 

∆ܶ

ܶെܶ଴

ൎ 2

3

∆ܳሶ

ܳሶ (4-16)
Model Uncertainty

4-11 

This is a simple formula with which one can readily estimate the relative change in the model 

output quantity, ∆ܶ/ሺܶ െ ܶ଴ሻ, due to the relative change in the model input parameter, ∆ܳሶ

/ܳሶ. 

The uncertainty in a measured quantity is often expressed in relative terms9

. Suppose that the 

uncertainty in the HRR of the fire, ∆ܳሶ/ܳሶ, is 0.15, or 15 %. The expression above indicates that 

a 15 % increase in the HRR should lead to a 2/3 x 15 = 10 % increase in the prediction of the 

HGL temperature. The result is equally valid for a reduction – if the HRR is reduced by 15 %, 

the HGL temperature is reduced by 10 %. 

This relationship is based on an algebraic model, and has nothing to do with any particular 

model; however, an effective way to check a fire model is to take a simple compartment fire 

simulation, vary the HRR, and ensure that the change in the HGL temperature agrees with the 

correlation. Consider the two curves shown in Figure 4-4. For Benchmark Exercise #3 of the 

International Collaborative Fire Model Project (ICFMP), Test 3 was simulated with FDS, using 

HRR values of 1000 kW and 1150 kW. An examination of the peak values confirms that the 

relative change in the HGL temperature (10 %) is two-thirds the relative change in the HRR 

(15 %), consistent with the empirical result of the MQH correlation. Even though FDS is a much 

more complicated model than the simple expression shown above, it still exhibits the same 

functional dependence on the HRR. 

Table 4-3. Sensitivity of model outputs from Volume 2 of NUREG-1824 (EPRI 1011999). 

Output Quantity Important Input 

Parameters Power Dependence 

HGL Temperature 

HRR 

Surface Area 

Wall Conductivity 

Ventilation Rate 

Door Height 

2/3 

-1/3 

-1/3 

-1/3 

-1/6 

HGL Depth Door Height 1 

Gas Concentration HRR 

Production Rate 

1/2 

1 

Smoke Concentration HRR 

Soot Yield 

1 

1 

Pressure 

HRR 

Leakage Rate 

Ventilation Rate 

2 

2 

2 

Heat Flux HRR 4/3 

Surface/Target 

Temperature HRR 2/3 

 

9

 Note that a differential relationship is only approximate. This method of relating input parameters to 

output quantities is valid for relative differences that are less than approximately 30% in absolute value. 
Model Uncertainty 

4-12 

Figure 4-4. FDS predictions of HGL Temperature as a function of time due to a 1,000 kW 

fire (solid line) and a 1,150 kW fire (dashed). 

This section describes the usefulness of sensitivity analysis. NFPA 805 uses the term 

“Maximum Expected Fire Scenario” to describe a severe fire that could be “reasonably 

anticipated” to occur within a compartment and the term “Limiting Fire Scenario” to describe a 

severe fire that exceeds one or more performance criteria. The analyst is often asked to 

determine the model inputs for both of these scenarios. For example, choosing the 98th

percentile HRR from a distribution of, say, cabinet fires, along with other extreme but plausible 

values of the ventilation rate and material properties, produces what might be considered the 

Maximum Expected Fire Scenario. Determining the parameters for the Limiting Fire Scenario, 

however, is more difficult because it is a mathematically ill-posed problem to take a given 

outcome of a fire and go backwards in time and determine the conditions that might lead to it. 

Rather than the trial and error approach to determining parameters for a Limiting Fire Scenario, 

it is better to first calculate the Maximum Expected Fire Scenario and then perform a sensitivity 

analysis for the most important input parameters to determine which values of each will lead to 

the Limiting Fire Scenario. 

Suppose, for example, that as part of an NFPA 805 analysis the problem is to determine the 

Limiting Fire Scenario for a particular compartment whose HGL temperature is not to exceed 

500 °C (930 °F). Assume that the geometrical complexity of the compartment rules out the use 

of the empirical and zone models, and that FDS has been selected for the simulation. 

Step 1: Determine an appropriate maximum expected fire heat release rate. For this example, 

suppose that a 98th percentile HRR for the electrical cabinet fire, 702 kW, has been determined 

to be the MEFS. Choose a model and calculate the peak HGL temperature. 

Step 2: Assume that FDS predicts 450 °C (840 °F) for the selected fire scenario. Adjust the 

prediction to account for the model bias, ߜ) See Table 4-1): 

ܶadj ൌ ܶ଴ ൅

ܶെܶ଴

൅ 20 ൌ ߜ

450 െ 20

1.03 ൎ 437°C (4-17)

Hot Gas Layer Temperature

ICFMP BE #3, Test 3

Time (min)

0 5 10 15 20 25 30

Temperature (°C)

0

100

200

300

400
Model Uncertainty

4-13 

Step 3: Calculate the change in HRR required to increase the HGL temperature to 500 °C 

(930 °F): 

∆ܳሶ ൎ 3

2ܳሶ ∆ܶ

ܶadj െ ܶ଴

ൌ 3

2 702

500 െ 437

417 ൌ 159 kW (4-18)

This calculation suggests that adding an additional 159 kW to the original 702 kW will produce 

an HGL temperature in the vicinity of 500 °C (930 °F). This result can be double-checked by rerunning the model with the modified input parameters. 

Table 4-3 lists several other parameters besides the HRR that can affect the HGL temperature. 

Following the example just discussed, similar calculations can be performed in which these 

other parameters are varied to determine how else the LFS might be reached. For example, 

suppose that the surface area, ܣ, of the compartment is 400 m2

 (4300 ft2). How much would the 

surface area have to increase or decrease to raise the HGL temperature to 500 °C (930 °F)? Or 

if the thermal conductivity of the walls, ݇, is 0.1 W/m/K, how much would it have to change? If 

the ventilation rate is 1 m3

/s, how much would it have to change? If the door height, ݄, is 2 m, 

how much would it have to change? Following the example for the HRR, the required changes 

in these parameters can be calculated as follows: 

ܣ3െ ൎ ܣ∆

∆ܶ

ܶadj െ ܶ଴

ൌ െ3ሺ400ሻ

500 െ 437

417 ൌ െ181 mଶ (4-19)

∆݇ ൎ െ3݇

∆ܶ

ܶadj െ ܶ଴

ൌ െ3ሺ0.1ሻ

500 െ 437

417 ൌ െ0.045 W/m/K (4-20)

∆ܸሶ ൎ െ3ܸሶ ∆ܶ

ܶadj െ ܶ଴

ൌ െ3ሺ1ሻ

500 െ 437

417 ൌ െ0.45

mଷ

s (4-21)

∆݄ ൎ െ6݄

∆ܶ

ܶadj െ ܶ଴

ൌ െ6ሺ2ሻ

500 െ 437

417 ൌ െ1.8 m (4-22)

For this example, to increase the HGL temperature by 63 °C (145 °F), one could increase the 

HRR by 159 kW, decrease the surface area of the compartment by 181 m2

 (1948 ft2), decrease 

the thermal conductivity of the walls by 0.045 W/m/K, decrease the ventilation rate by 0.45 m3

/s, 

or decrease the door height by 1.8 m (5.9 ft). Of course, some of these options are not 

physically possible. Room dimensions and thermal properties are not subject to significant 

change, but the HRR and ventilation rates can vary significantly. 
Model Uncertainty 

4-14 

4.5 Chapter Summary 

This chapter describes the three forms of uncertainty related to fire modeling: parameter, model, 

and completeness uncertainty. Model and completeness uncertainty are closely related, and it 

would be impractical to evaluate them separately. The most practical way to quantify their 

combined effect is to compare model predictions with as many experimental measurements as 

possible in order to develop a robust statistical description of the model’s accuracy. The five 

models considered in this Guide underwent a validation study (NUREG-1824 (EPRI 1011999)) 

in which their predictions were compared with measurements from a variety of full-scale 

experiments. It is possible to take a given model’s prediction of a given quantity and assume a 

distribution for the “true” value of this quantity. Rather than reporting the result of a calculation 

as a single value, it is preferable to report the probability that the true value of a predicted 

quantity exceeds a given critical value. 

Regardless of the application, the assessment of model uncertainty is the same. However, the 

issue of parameter uncertainty is dependent on the application. Some analyses, PRAs for 

example, make use of “best estimate” input parameters. More complex forms of PRAs can 

involve a broad statistical sampling of input parameters from assumed distributions. 

Deterministic applications usually consider “worst case” or “bounding” analyses, in which 

extreme, yet plausible, input parameters are used. In mathematical terms, all of these 

applications involve selecting parameters from relatively narrow or broad regions of the 

parameter “space.” It is impossible to consider all possible combinations of input parameters, 

which is why a simple form of sensitivity analysis, outlined in this chapter, can be used to extend 

the range of outcomes. For example, algebraic models indicate the extent to which all of the 

output quantities of interest are sensitive to changes in the specified HRR, reducing the need to 

re-run model simulations for an extensive number of values. Sensitivity analysis can help 

determine which input parameters are necessary to bring about the Limiting Fire Scenario in an 

NFPA 805 analysis. 
5-1 

5

REFERENCES 

10 CFR 50, “Voluntary Fire Protection Requirements for Light-Water Reactors,” 10 CFR Part 

50, Section 50.48(c), RIN 3150-AG48, Federal Register, Volume 69, Number 115, 

U.S. Nuclear Regulatory Commission, Washington, DC, June 16, 2004. 

ASME/ANS RA-Sa-2009, Standard for Level 1/Large Early Release Frequency 

Probabilistic Risk Assessment for Nuclear Power Plant Applications, Addendum 

a, ASME/ANS RA-S-2009, American Society of Mechanical Engineers, 2009. 

ASTM E119-10a, Standard Test Methods for Fire Tests of Building Construction 

Materials, American Society for Testing and Materials, West Conshohocken, PA, 

2010. 

ASTM E1355–05a (2005), ASTM Standard Guide for Evaluating the Predictive 

Capability of Deterministic fire Models, American Society for Testing and 

Materials, West Conshohocken, PA, 2005. 

Babrauskas, V., Ignition Handbook, Fire Science Publishers/Society of Fire Protection 

Engineers, Issaquah WA (2003). 

Buchanan, A. H., Structural Design for Fire Safety, John Wiley and Sons, LTD, 

Chichester, England, 2001. 

Drysdale, D., An Introduction to Fire Dynamics, John Wiley and Sons, Chichester, pp. 14, 

283-284, 1996. 

EPRI 1002981, Fire Modeling Guide for Nuclear Power Plant Applications, Electric Power 

Research Institute, Palo Alto, CA, August 2002. 

Fire Protection Handbook, National Fire Protection Association, 20th Ed., A.E. Cote, 

(Editor), 2008. 

Fourney, G.P., User’s Guide for Smokeview Version 5 - A Tool for Visualizing Fire 

Dynamics Simulation Data, Volume II: Technical Reference Guide, NIST Special 

Publication 1017-2, National Institute of Standards and Technology, 

Gaithersburg, MD, October 2010. 

Gay, L., User Guide of MAGIC Software V4.1.1, EdF HI82/04/022/B, Electricité de France, 

France, April 2005. 

Gay, L., C. Epiard, and B. Gautier, MAGIC Software Version 4.1.1: Mathematical Model, 

EdF HI82/04/024/B, Electricité de France, France, November 2005. 

Gay, L., J. Frezabeu, and B. Gautier, Qualification File of Fire Code MAGIC Software 

Version 4.1.1: Mathematical Model, EdF HI82/04/024/B, Electricité de France, 

France, November 2005. 

Heskestad, G., Chapter 2, Section 2-2, “Fire Plumes,” SFPE Handbook off Fire Protection 

Engineering, 2nd Edition, (P.J. DiNenno, Editor-in-Chief), National Fire Protection 

Association and The Society of Fire Protection Engineers, Quincy, MA, 1995. 

Holman, J.P., Heat Transfer, 7th edition, McGraw-Hill, New York, 1990. 
References 

5-2 

Jones, W., R. Peacock, G. Forney, and P. Reneke, CFAST: An Engineering Tool for 

Estimating Fire Growth and Smoke Transport, Version 5 - Technical Reference 

Guide, NIST Special Publication 1030, National Institute of Standards and 

Technology, Gaithersburg, MD, 2004. 

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

2000. 

Köylu, U.O. and G.M. Faeth, “Carbon Monoxide and Soot Emissions from Liquid-Fueled 

Buoyant Turbulent Diffusion Flames,” Combustion and Flame, 87:61-76, 1991. 

McCaffrey, B.J., J.G. Quintiere, and M.F. Harkleroad, “Estimating Compartment 

Temperature and Likelihood of Flashover Using Fire Test Data Correlation,” Fire 

Technology, Volume 17, No. 2, pp. 98-119, Quincy, MA, 1981. 

McGrattan, K., et al., Fire Dynamics Simulator (Version 5) Technical Reference, Volume 3: 

Validation, NIST Special Publication 1018-5, National Institute of Standards and 

Technology, Gaithersburg, MD, 2010. 

McGrattan, K., B. Klein, S. Hostikka and J. Floyd, Fire Dynamics Simulator (Version 5) 

User’s Guide, NIST Special Publication 1019-5, National Institute of Standards and 

Technology, Gaithersburg, MD, 2009. 

McGrattan, K., and B. Toman, “Quantifying the predictive uncertainty of complex numerical 

models,” Metrologia, 48:173-180, 2011. 

Mulholland, G.W., and C. Croarkin, “Specific Extinction Coefficient of Flame Generated 

Smoke,” Fire and Materials, 24:227-230, 2000. 

NFPA Fire Protection Handbook, 20th Edition (A.E. Cote, Editor-in-Chief), National Fire 

Protection Association, Quincy, MA, 1997. 

NFPA 70 (NEC 2008), National Electric Code, National Fire Protection Association, Quincy, 

MA, 2008. 

NFPA 805, Performance-Based Standard for Fire Protection for Light Water Reactor Electric 

Generating Plants, National Fire Protection Association, Quincy, MA, 2001. 

NEI 00-01 (2009), Guidance for Post Fire Safe Shutdown Circuit Analysis, Revision 2, 

Nuclear Energy Institute, Washington, D.C., May, 2009. 

NEI 00-01 (2010), Guidance for Post Fire Safe Shutdown Circuit Analysis, Draft Revision 

3, Nuclear Energy Institute, Washington, D.C., 2010. 

NEI 04-02 (2009), Guidance for Implementing a Risk-Informed Performance-Based Fire 

Protection Program Under 10 CFR 50.48(c), Rev. 1, Nuclear Energy Institute, 

Washington, D.C., September, 2009. 

NIST NCSTAR 1-5F, Federal Building and Fire Safety Investigation of the World Trade 

Center Disaster: Computer Simulation of the Fires in the World Trade Center 

Towers, National Institute of Standards and Technology, Gaithersburg, MD, 2005. 

NUREG-1805, Fire Dynamics Tools (FDTs

): Quantitative Fire Hazard Analysis Methods for 

the U.S. Nuclear Regulatory Commission Fire Protection Inspection Program, U.S. 

Nuclear Regulatory Commission, Washington, DC, December 2004. 

NUREG-1824, Verification and Validation of Selected Fire Models for Nuclear Power Plant 

Applications, Volume 1: Main Report, U.S. Nuclear Regulatory Commission, Office 
References

5-3 

of Nuclear Regulatory Research (RES), Washington, DC, 2007, and EPRI 1011999, 

Electric Power Research Institute (EPRI), Palo Alto, CA. 

NUREG-1824, Verification and Validation of Selected Fire Models for Nuclear Power Plant 

Applications, Volume 3: Fire Dynamics Tools (FDTs

), U.S. Nuclear Regulatory 

Commission, Office of Nuclear Regulatory Research (RES), Washington, DC, 2007, 

and EPRI 1011999, Electric Power Research Institute (EPRI), Palo Alto, CA. 

NUREG-1824, Verification and Validation of Selected Fire Models for Nuclear Power Plant 

Applications, Volume 4: Fire-Induced Vulnerability Evaluation (FIVE-Rev1), U.S. 

Nuclear Regulatory Commission, Office of Nuclear Regulatory Research (RES), 

Washington, DC, 2007, and EPRI 1011999, Electric Power Research Institute 

(EPRI), Palo Alto, CA. 

NUREG-1824, Verification and Validation of Selected Fire Models for Nuclear Power Plant 

Applications, Volume 5: Consolidated Fire Growth and Smoke Transport Model 

(CFAST), U.S. Nuclear Regulatory Commission, Office of Nuclear Regulatory 

Research (RES), Washington, DC, 2007, and EPRI 1011999, Electric Power 

Research Institute (EPRI), Palo Alto, CA. 

NUREG-1824, Verification and Validation of Selected Fire Models for Nuclear Power Plant 

Applications, Volume 6: MAGIC, U.S. Nuclear Regulatory Commission, Office of 

Nuclear Regulatory Research (RES), Washington, DC, 2007, and EPRI 1011999, 

Electric Power Research Institute (EPRI), Palo Alto, CA. 

NUREG-1824, Verification and Validation of Selected Fire Models for Nuclear Power Plant 

Applications, Volume 7: Fire Dynamics Simulator (FDS), U.S. Nuclear Regulatory 

Commission, Office of Nuclear Regulatory Research (RES), Washington, DC, 2007, 

and EPRI 1011999, Electric Power Research Institute (EPRI), Palo Alto, CA. 

NUREG/CR-4680, Heat and Mass Release Rate for Some Transient Fuel Source Fires: A 

Test Report, U.S. Nuclear Regulatory Commission, Washington, DC, December 

2004. 

NUREG/CR-6850, EPRI/NRC-RES Fire PRA Methodology for Nuclear Power Facilities: 

Volume 1: Summary and Overview, U.S. Nuclear Regulatory Commission, Office of 

Nuclear Regulatory Research (RES), Washington, DC: 2005 and EPRI 1011989, 

Electric Power Research Institute (EPRI), Palo Alto, CA.

NUREG/CR-6850, EPRI/NRC-RES Fire PRA Methodology for Nuclear Power Facilities: 

Volume 2: Detailed Methodology, U.S. Nuclear Regulatory Commission, Office of 

Nuclear Regulatory Research (RES), Washington, DC: 2005 and EPRI 1011989, 

Electric Power Research Institute (EPRI), Palo Alto, CA.

NUREG/CR-6931, Cable Response to Live Fire (CAROLFIRE), Volume 1: Test 

Descriptions and Analysis of Circuit Response Data, U.S. Nuclear Regulatory 

Commission, Washington, DC, 2007. 

NUREG/CR-6931, Cable Response to Live Fire (CAROLFIRE), Volume 2: Cable Fire 

Response Data for Fire Model Improvement, U.S. Nuclear Regulatory Commission, 

Washington, DC, 2007. 

NUREG/CR-6931, Cable Response to Live Fire (CAROLFIRE), Volume 3: ThermallyInduced Electrical Failure (THIEF) Model, U.S. Nuclear Regulatory Commission, 

Washington, DC, 2007. 
References 

5-4 

NUREG/CR-7010, Cable Heat Release, Ignition, and Spread In Tray Installations during 

Fire (CHRISTIFIRE), Volume 1: Horizontal Trays, National Institute of Standards 

and Technology, Gaithersburg, MD, 2011. 

Peacock, R., K. McGrattan, B. Klein, W. Jones, and P. Reneke, CFAST – Consolidated 

Model of Fire Growth and Smoke Transport (Version 6) – Software Development 

and Model Evaluation Guide, Special Publication 1086, National Institute of 

Standards and Technology, Gaithersburg, MD, 2008. 

Peacock, R., W. Jones, P. Reneke and G. Forney, CFAST: An Engineering Tool for 

Estimating Fire Growth and Smoke Transport, Version 6 – User’s Guide, Special 

Publication 1041, National Institute of Standards and Technology, Gaithersburg, 

MD, 2008. 

Quintiere, J.G., Principles of Fire Behavior, Delmar Publishers, 1998. 

Quintiere, J.G., Fundamentals of Fire Phenomena, John Wiley, 2006. 

Regulatory Guide 1.189, Fire Protection for Nuclear Power Plants, U.S. Nuclear 

Regulatory Commission, Bethesda, MD, April, 2009. 

Schiffiliti, R. and W. Pucci, Fire Modeling, State of the Art, Fire Detection Institute, 1996 

SFPE, SFPE Engineering Guide to Assessing Flame Radiation to External Targets from 

Pool Fires, SFPE Engineering Guide, Society of Fire Protection Engineers, 

Bethesda, MD, March 1999. 

SFPE, SFPE Engineering Guide to Fire Exposures to Structural Elements, SFPE 

Engineering Guide, Society of Fire Protection Engineers, Bethesda, MD, 

November, 2005. 

SFPE, SFPE Engineering Guide to Piloted Ignition of Solid Materials Under Radiant 

Exposure, SFPE Engineering Guide, Society of Fire Protection Engineers, 

Bethesda, MD, January, 2002. 

SFPE, SFPE Engineering Guide to Predicting Room of Origin Fire Hazards, SFPE 

Engineering Guide, Society of Fire Protection Engineers, Bethesda, MD, 

November, 2007. 

SFPE, SFPE Engineering Guide to Substantiating a Fire Model for a Given Application, 

SFPE Engineering Guide, Society of Fire Protection Engineers, Bethesda, MD, 

June, 2010. 

SFPE Handbook of Fire Protection Engineering, 4th Edition (P.J. DiNenno, Editor-in-Chief), 

National Fire Protection Association and The Society of Fire Protection Engineers, 

Quincy, MA, 2008. 

Steel Construction Manual, 13th edition, American Institute of Steel Construction, New 

York, New York, 2006. 

UL 217, Single Station Fire Alarm Device, Underwriters’ Laboratories, Northbrook, Illinois. 

Wallis, G.B., “Draft Final NUREG-1824, Verification and Validation of Selected Fire Models 

for Nuclear Power Plant Applications”, Memorandum from Advisory Committee on 

Reactor Safeguards to Luis Reyes, ML062980154, US Nuclear Regulatory 

Commission, October 2006. 
A-1 

A 

CABINET FIRE IN MAIN CONTROL ROOM 

A.1 Modeling Objective 

The purpose of the calculations described in this Appendix is to determine the length of time 

that the Main Control Room (MCR) remains habitable after the start of a fire within a low-voltage 

control cabinet. These calculations are based on the guidance provided in Chapter 11 of 

NUREG/CR-6850 (EPRI 1011989), Volume 2, “Detailed Fire Modeling (Task 11).” MCR fire 

scenarios are treated differently than fires within other compartments, mainly because of the 

necessity to consider forced abandonment in addition to equipment damage. 

A.2 Description of the Fire Scenario 

General Description: A fire ignites within a control cabinet containing XPE/neoprene cables. 

The door to the MCR is normally closed, and normal ventilation conditions are in place at the 

start of the fire. Following guidance given in Chapter 11 of NUREG/CR-6850, two scenarios are 

considered, one in which the ventilation system is turned off and one in which the ventilation 

system is switched to smoke-purge mode at the start of the fire. 

Geometry: Drawings of the MCR are shown in Figure A-1 and Figure A-2. The compartment 

has a variety of control cabinets in addition to typical office equipment, such as computer 

monitors on table tops. There is an “open grate” ceiling above the floor, a photograph of which 

is shown in Figure A-3. One wall of the compartment is made of concrete with no additional 

lining material. The other exterior walls are constructed of five-eighth in gypsum board 

supported by steel studs. The floor is a slab of concrete covered with low-pile carpet. The 

ceiling is a slab of concrete with the same thickness as the floor, but with no lining material. 

Materials: Nominal values for the thermal properties of various materials in the compartment 

have been taken from NUREG-1805, Table 2-3 and are listed in Table 3-1. Carpet is not listed 

in the table, but, according to NUREG-1805, Table 6-5, the thermal inertia (kρc) for “Carpet 

(Nylon/Wool Blend)” is 0.68 (kW/m2

/K)2 s, its “Ignition Temperature” is 412°C (774°F), and its 

“Minimum Heat Flux for Ignition” is 18 kW/m2

. 

Detection System: Smoke detectors are located as shown in Figure A-1 below the plenum 

space at the open grate ceiling level and on the upper concrete ceiling. However, smoke 

detection plays no role in the fire scenarios under consideration. 

Ventilation: During normal operation, the ventilation system provides five air changes per hour. 

As seen in Figure A-1, ventilation is provided by six supply diffusers and two return vents of 

nominally the same size. The supply air to the compartment is equally distributed among the six 

supply vents, and the return air is drawn equally from the two returns. A 120 Pa overpressure 

(relative to the adjacent compartments) is maintained in the MCR. Leakage from the 

compartment occurs via a 2.5 cm (1 in) high crack under the 0.91 m (3 ft)-wide door on the west 

side of the compartment. All other penetrations are sealed. 
Cabinet Fire in Main Control Room 

A-2 

Figure A-1. Geometry of the Main Control Room. The cabinet is at lower right. 
Cabinet Fire in Main Control Room

A-3 

Figure A-2. Main Control Room Details. 
Cabinet Fire in Main Control Room 

A-4 

Figure A-3. Photograph of a typical “open grate” ceiling. 

Figure A-4. Photograph of a typical control cabinet. 

 
Cabinet Fire in Main Control Room

A-5 

NUREG/CR-6850 (EPRI 1011989), Volume 2, Chapter 11, recommends that two possibilities be 

taken into consideration regarding ventilation: (1) the ventilation system is turned off, and (2) the 

ventilation system is in smoke-purge mode. Smoke-purge mode provides 25 air changes per 

hour. 

Fire: The fire ignites in a control cabinet (Figure A-4), designated as the “Fire Origin” in Figure 

A-1, due to an electrical malfunction. The fire grows according to a “t-squared” curve to a 

maximum value of 702 kW in 12 min and remains steady for 8 additional minutes, consistent 

with NUREG/CR-6850 (EPRI 1011989), Appendix G, for a low-voltage cabinet fire involving 

more than one bundle of qualified cable. After 20 min, the fire’s HRR decays linearly to zero in 

19 min. A peak fire intensity of 702 kW represents the 98th percentile of the probability 

distribution for the HRR in cabinets of this general description. The heat release rate curve is 

shown in Figure A-5. 

Figure A-5. Time history of the HRR used by all models in the MCR scenario. 

The exterior panels of the burning cabinet do not open before or during the fire. The smoke, 

heat, and flames are exhausted from an air vent in the side of the cabinet. The top of the air 

vent is 0.3 m (1 ft) below the top of the cabinet. The air vent is 0.6 m (2 ft) wide and 0.2 m (8 in) 

high. The cabinet is 2.4 m (8 ft) tall. 

When estimating the composition of the fire’s exhaust products, the jacket and insulation 

material of the cable are taken as an equal-parts mixture of polyethylene (C2H4) and Neoprene 

(C2H5Cl), with the effective chemical formula C2H4.5Cl0.5. The heat of combustion of the burning 

cables is 10.3 kJ/g (NUREG-1805, Table 2-4). This number is appropriate for cross-linked 

polyethelene (XLPE)/Neoprene cables. The radiative fraction10 of the fire is 35%, consistent 

with typical sooty fires (Tewarson, SFPE Handbook, 4th ed., Table 3-4.16). 

For visibility calculations, soot yield11 is a very important parameter. According to Tewarson’s 

chapter in the SFPE Handbook, the soot yield for the various combustible materials within the 

 

10 The fraction of the fire’s total energy emitted as thermal radiation. 11 The soot yield is defined as the mass of smoke particulate generated per unit mass of fuel consumed. 

0

100

200

300

400

500

600

700

800

0 600 1200 1800 2400 3000 3600

HRR (kW)

Time (s)

Heat Release Rate
Cabinet Fire in Main Control Room 

A-6 

cabinet ranges from 0.01 to 0.20. For this scenario, the soot yield for the combustion reaction is 

taken to be 0.10, but the results of the calculation should be assessed in light of the wide 

variation in possible soot yields, and the fact that the fire could potentially be underventilated. 

This value of 0.10 is an estimate for a fire burning in an environment where the equivalence 

ratio approaches 1. The calculated optical density is directly proportional to this parameter; 

thus, the entire range of values can easily be assessed during post-processing of the results. 

The mass extinction coefficient is 8.7 m2

/g, based on measurements made by Mulholland and 

Croarkin (2000). 

The CO yield of the fire, ݕCO, can be estimated from the soot yield, ݕ௦, using a correlation 

developed by Köylu and Faeth: 

ݔ 12 ൌ COݕ

௙ߥ ௙ܯ

0.0014 ൅ 0.37 ݕ௦ (A-1) 

where x is the number of carbon atoms in a fuel molecule (two in this example), M୤ is the 

molecular weight of the fuel (46.26 g/mol, calculated from the effective chemical formula), yୱ is 

the soot yield, and ν୤ is the stoichiometric coefficient of the fuel, here taken to be one since all 

species yields are taken as a ratio to the mass of fuel consumed. For this example, the CO 

yield (ݕCO) is calculated from the above equation to be 0.038 kg/kg. 

Based on the yields of soot and CO for the fuel considered in this example, the complete 

chemical reaction can be written: 

CଶHସ.ହCl଴.ହ ൅ 2.59 Oଶ ՜ 0.06 CO ൅ 0.38 C ൅ 1.56 COଶ ൅ 2 HଶO ൅ 0.5 HCl (A-2) 

Note that the soot is treated as pure carbon, C, and that all of the chlorine produces HCl. 

Habitability: The MCR is manned 24 hours per day during normal plant operations. To assess 

habitability of the compartment, the operator stands at the position indicated in Figure A-1. 

According to NUREG/CR-6850 (EPRI 1011989), Volume 2, Chapter 11, “Detailed Fire 

Modeling,” a space is considered uninhabitable if at least one of the following occurs: 

1. The incident heat flux at 1.8 m (6 ft) exceeds 1 kW/m2

. A smoke layer temperature of 

approximately 95°C (200°F) generates this level of heat flux. 

2. The smoke layer descends below 1.8 m (6 ft) from the floor, and the optical density of 

the smoke is greater12 than 3 m-1. 

 

12 The original edition of NUREG/CR-6850 contains an error in the specification of the optical density 

(NRC ADAMS Accession Number ML061630360). 
Cabinet Fire in Main Control Room

A-7 

A.3 Selection and Evaluation of Fire Models 

NUREG/CR-6850 (EPRI 1011989), Volume 2, Chapter 11 recommends zone and CFD models 

for estimating the HGL temperature, heat flux, HGL descent rate, and smoke obscuration in the 

MCR. Algebraic models can also provide useful estimates of various fire-generated conditions. 

Following is a discussion of the strengths and weaknesses of the available models. 

Algebraic Models: FIVE and the FDTs

 both contain correlations to estimate the HGL 

temperatures within a closed, ventilated compartment. However, the FDTs

 do not allow the 

HRR to be input as a function of time. Because the objective of the calculation is to estimate 

the time to loss of habitability, FIVE is used to provide a first estimate of the compartment 

temperature. 

FIVE and the FDTs

 both contain methods to estimate the heat flux from a fire to a target. 

However, the description of the scenario indicates that the fire is ignited and remains largely 

within a closed control cabinet. Thus, distant targets, including the operators, may not be 

exposed directly to the thermal radiation. It is more likely that the descending Hot Gas Layer 

will be responsible for most of the heat flux to which the operator is exposed. Neither FIVE nor 

the FDTs

 have a method to account for this source of thermal radiation. 

Zone Models: The fire scenario outlined in the previous section falls within the range of 

applicability for a zone model. If the open grate-style ceiling below the actual concrete ceiling 

slab can be neglected, the overall geometry and fire size will lead to a fire environment in the 

control room volume that conforms to a basic two-zone approximation. For this analysis, the 

zone model CFAST version 6.1.1 is used. It has one advantage over MAGIC for this analysis; it 

computes the smoke obscuration, one of the critical parameters required to assess habitability. 

CFD Models: The primary advantage of a CFD model for this fire scenario is that the CFD 

model can estimate habitability conditions at the specific location of the operator. 

Validation: The principal source of validation data justifying the use of the fire models 

discussed above for this scenario is the NRC/EPRI V&V study documented in NUREG-1824 

(EPRI 1011999). NIST has expanded the NRC/EPRI V&V to include the latest versions of 

CFAST (6.1.1) (Peacock, 2008) and FDS (5.5.3) (McGrattan, 2010). In particular, the FM/SNL 

(Factory Mutual/Sandia National Labs) test series was designed specifically as a mock-up of a 

control room in an NPP. One of these experiments (Test 21) involves a fire within a hollow steel 

cabinet. 

Table A-1 lists various important model parameters and the ranges for which the NRC/EPRI 

validation study is applicable. A few parameters fall outside the validation parameter space and 

are addressed individually: 

 The Fire Froude Number falls outside the range. This parameter is essentially a measure of 

the fire’s heat output relative to its base area. In this example, the fire is assumed to 

emanate from the side of the cabinet with the vent opening serving as its “base.” This 

assumption leads to a higher value of ܳሶ

כ than would be calculated if it were not assumed 

that the fire burns completely outside of the cabinet. Thus, the high value of ܳሶ

כ is the result 

of an assumption that will lead to more severe fire conditions than would be expected if the 

fire were assumed to burn partially within the cabinet. 
Cabinet Fire in Main Control Room 

A-8 

 The relatively low Equivalence Ratio for the compartment is a result of the relatively large 

amount of air forced into the room during the smoke purge mode. Twenty-five air changes 

per hour is a considerable flow rate, and no validation experiment in NUREG-1824 involved 

such a high rate. However, the results of all the model simulations indicate that the scenario 

in which the ventilation is turned off is the more likely to compromise human habitability, and 

the presence of any level of ventilation reduces room temperature and heat flux and 

increases visibility. 
Cabinet Fire in Main Control Room

A-9 

Table A-1. Normalized parameter calculations for the MCR fire scenario. 

Quantity Normalized Parameter Calculation Validation Range In Range? 

Fire Froude 

כܳ Number

ሶ

ൌ

ܳ

ሶ

ܦ݃ଶඥܦஶܶ௣ܿஶߩ

ൌ

702

1.2 ൈ 1.012 ൈ 293 ൈ 0.4ଶ ൈ √9.8 ൈ 0.4 ؆ 6.2 0.4 – 2.4 No 

Flame Length, L୤, 

relative to the 

Ceiling Height, ܪ

௙ܮ

௖ܪ

ൌ

2.75.2 ؆ 0.5

ܮ ௙ൌ ܦ ቀ3.7 ܳכሶ ଶ/ହ െ 1.02ቁ ൌ 0.4 ሺ3.7 ൈ 6.2଴.ସ െ 1.02ሻ ؆ 2.7

0.2 – 1.0 Yes 

Ceiling Jet Radial 

Distance,rcj, 

relative to the 

Ceiling Height, H

N/A – Ceiling jet targets are not included in simulation. 1.2 – 1.7 N/A 

Equivalence Ratio, 

φ, of the Room, 

based on Forced 

Ventilation of 

Purge Mode 

߮ ൌ

݉ሶ F/݉ሶ Oమ

ݎ

ؠ

ܳ

ሶ

Oమ ሶ݉ ܪ∆ ݎ

ൌ

702

13,100 ൈ 3.7 ؆ 0.014

݉ሶ Oమ ൌ 0.23 ߩஶܸ

ሶ

ൌ 0.23 ൈ 1.2 ൈ 13.4 ؆ 3.7

0.04 – 0.6 No 

Compartment 

Aspect Ratio 

ܮ

ܪ

ൌ

24.6

5.2 ؆ 4.7

ܹ

ܪ

ൌ

16.2

5.2 ؆ 3.1 0.6 – 5.7 Yes 

Target Distance, r, 

relative to the Fire 

Diameter, D

N/A – The radiation heat flux to the operator is based on the 

temperature of the HGL, not the fire. 2.2 – 5.7 N/A 
Cabinet Fire in Main Control Room 

A-10 

A.4 Estimation of Fire-Generated Conditions 

This section provides specific details on how each model is set up and run. 

A.4.1 Algebraic Model (FIVE) 

General: The forced ventilation correlation of Foote, Pagni, and Alvares (FPA) is used in FIVE 

to estimate the HGL temperature of the MCR, but only for the smoke purge scenario. A 

schematic diagram indicating the assumptions is shown in Figure A-6. None of the FIVE 

algorithms were evaluated for a closed, unventilated compartment in the NRC/EPRI V&V study 

documented in NUREG-1824 (EPRI 1011999). 

Geometry: The FPA correlation requires that the room dimensions be given in terms of a 

length, width, and height. For this example, the selected compartment is not a rectangular 

parallelepiped; thus, it needs to be represented as such with an effective length, width, and 

height. The compartment height is taken directly as 5.2 m (17 ft) because it is important to 

maintain the same compartment height for the smoke filling calculation. Next, the effective 

length and width are calculated to maintain the same volume and surface area of the actual 

compartment. This is equivalent to maintaining the same floor area and perimeter. The floor 

area is 372 m2

 (4004 ft2), and the perimeter is 83.4 m (274 ft). Maintaining the total floor area 

and perimeter yields an effective compartment size of 28.8 m (94.5 ft) by 12.9 m (42.3 ft). 

Figure A-6. Schematic diagram of the FIVE calculation. 

Fire: The FPA correlation in FIVE uses the specified time-dependent HRR. It does not use the 

fire’s elevation above the floor or any other information about the fire. 

Materials: The walls, ceiling, and floor are all gypsum board rather than concrete because the 

FPA correlation only accounts for one type of lining material. Gypsum board was chosen 

because it is a better insulator and leads to a slightly higher HGL temperature, which in this 

scenario would more likely compromise human tenability. 

Point source fire with timedependent heat release rate 

but no specified location or 

height

Closed door Uniform

compartment 

temperature

Constant exhaust in balance 

with supply

Constant air supply

Uniform material properties and thickness 

for walls, floor and ceiling
Cabinet Fire in Main Control Room

A-11 

Ventilation: The ventilation rate of the smoke purge mode (5700 cfm) is a direct input 

parameter in the FPA algorithm of FIVE. 

A.4.2 Zone Model (CFAST) 

Geometry: CFAST divides the geometry into one or more compartments connected by vents. 

For this simulation, the entire compartment is modeled as a single compartment. As with the 

algebraic models, zone models simulate fires in compartments with rectangular floor areas. The 

strategy for selecting effective room dimensions is the same as described above. 

While there are numerous cabinets and tables in the compartment, most are well below the 

height of the fire (discussed below) and may be neglected. There are no mechanisms within 

CFAST to account for the open-grate ceiling. It is expected that neglecting it will lead to slightly 

higher HGL temperatures because there is less resistance for the rising smoke and hot gases. 

Fire: In CFAST, a fire is described as a source of heat placed at a specific point within a 

compartment that generates combustion products according to user-specified combustion 

chemistry. Consistent with typical practice for the use of zone fire models for electrical cabinet 

fires, the fire is positioned at the top of the air vent, 0.3 m below the top of the cabinet, at the 

center of the cabinet. The air vent dimensions of 0.6 m wide and 0.3 m constitute the area of 

the burning fire. A snapshot of the CFAST simulation is shown Figure A-7. 

Combustion chemistry in CFAST is described, at a minimum, by the production rates of CO, 

CO2, and soot. The basic stoichiometry of the reaction is given in Eq. (A-2). The CO2 yield is 

calculated: 

ݕCOమ ൌ ߥCOమܯCOమ

௙ܯ௙ߥ

ൌ 1.56 ൈ 44

1 ൈ 45.26 ؆ 1.52 kg/kg (A-3) 

Direct inputs for species production rates CFAST are normalized to this CO2 yield. Thus, the 

CFAST input of ݕCO/ݕCOమ is 0.038/1.52=0.025 and of ݕs/ݕCOమ is 0.1/1.52 = 0.066. A final input 

is the ratio of the mass of hydrogen to the mass of carbon in the fuel, or 0.15 kg/kg. 

Materials: CFAST does not include the ability to model individual walls of different materials. 

For this example, the compartment walls are assumed to be entirely made of gypsum wallboard, 

a conservative assumption given that its thermal conductivity is the lowest of all other wall 

materials. The floors and ceilings are modeled as 0.5 m (1.6 ft) thick concrete. 

CFAST does not use the thermal inertia, kρc, directly, but rather requires individual values of 

each. Based on typical thermal properties for hair, felt, and wool, the density of the carpet is 

200 kg/m3

, the specific heat is 2 kJ/kg/K, and the thermal conductivity is 

0.68/200/2=0.0017 kW/m/K (Holman, 1990). 

Ventilation: For the smoke-purge calculation, air is supplied to the MCR via the six supply 

vents and exhausted through the two returns. The total ventilation rate is 25 air changes per 

hour, 13.4 m3

/s. 
Cabinet Fire in Main Control Room 

A-12 

Figure A-7. Snapshot of the CFAST simulation of the MCR fire. 

A.4.3 CFD Model (FDS) 

Geometry: The entire compartment is included in the computational domain. The exterior 

concrete wall coincides with the boundary of the computational domain, meaning that the inside 

surface of the concrete wall is flush with the boundary of the computational domain, and the 

properties of concrete (including its thickness) are applied to this boundary. The tables (made 

out of wood) and the electrical cabinets (made out of steel) are included in the simulation. Note 

that the drop ceiling is not modeled because it is open and for this example provides a negligible 

resistance to the heat and air that go through it. 

The computational mesh consists of a uniform grid of cells that are 0.2 m on a side. A simple 

grid resolution study demonstrates that because the details of the fire (other than its specified 

heat and smoke production rates) within the cabinet are not important to the question asked, 

there is no need to further refine the grid in the vicinity of the cabinet. An explanation related to 

choosing the grid sizes appropriate for use can be found in NUREG-1824 (EPRI 1011999), 

Vol. 7. 

Fire: Following the guidance in NUREG/CR-6850 (EPRI 1011989), Supplement 1, Chapter 12, 

the fire is modeled as emanating from the upper vent of the burning cabinet. This assumption 

will result in higher HGL temperatures, as all of the fire’s energy is released outside of the 

cabinet; in reality, a certain fraction of the fire’s energy would be absorbed by the steel walls of 

the cabinet. An FDS/Smokeview rendering of the scenario is shown in Figure A-8. 

The fuel stoichiometry is input to the model as specified above. FDS requires the designation of 

a single gaseous fuel molecule via the number of carbon and hydrogen atoms in the “surrogate” 

fuel, plus the number of “other” atoms in the molecule that play no role in the reaction. The soot 

yield (0.10 kg/kg) and heat of combustion (10,300 kJ/kg) are input directly. 
Cabinet Fire in Main Control Room

A-13 

Materials: The cabinets are represented by closed boxes with the specified properties of steel. 

The tables are assigned the properties of plywood that is 5 cm thick. The table legs are not 

modeled because they play little role in the fire or heat transfer calculation to the solids. 

Concrete and gypsum properties are applied to the walls and ceiling. The floor is modeled as a 

1 cm-thick carpet over a 0.5 m-thick concrete slab. The concrete properties are taken directly 

as specified. The carpet properties are obtained in the same way as for CFAST above. 

Ventilation: Air is supplied to the MCR via the six supply vents and exhausted through the two 

returns. Steel plates are specified beneath the supply vent openings to mimic the effect of a 

diffusion grill: that is, air is pushed downwards from the vent opening, but is then redirected 

sideways by the plate. Because of the limited resolution of the numerical grid, this is the only 

way to account for the more detailed flow pattern of the real vent. 

The leakage from the compartment is modeled by specifying a small “vent” located at the base 

of the door through which air escapes at a rate determined by the pressure difference between 

the MCR and ambient. Note that the door crack itself is not modeled explicitly, as the numerical 

grid is not fine enough. Rather, the leak is spread over a slightly larger area. This assumption 

is justified by the fact that the volume flow through the leakage area is estimated via the 

equation: 

ܸሶ

௅ ൌ ܣ ௅ඨ2 Δ݌

ߩஶ (A-4) 

where AL is the actual leakage area (0.9 m by 0.025 m or 0.0225 m2

 in this case), ∆p is the 

pressure difference between the inside and outside of the compartment (Pa), and ρஶ is the 

ambient air density (1.2 kg/m3

). The supply rate is divided equally among the six supply vents, 

and the return rate is divided equally among the two returns. 

Figure A-8. FDS/Smokeview rendering of the Main Control Room, as seen from above. 
Cabinet Fire in Main Control Room 

A-14 

A.5 Evaluation of Results 

The habitability of the MCR depends on the temperature, heat flux, and smoke concentration to 

which the operators would be exposed. According to NUREG/CR-6850 (EPRI 1011989), 

Volume 2, Chapter 11, abandonment of the MCR is assumed if the gas temperature 2 m (6 ft) 

above the floor exceeds 95°C (200°F) or if the heat flux exceeds 1.0 kW/m2

 or if the optical 

density exceeds 3 m-1. Each of these criteria are discussed in the following sections. 

A.5.1 Temperature Criterion 

One of the room habitability criteria is the temperature near the operator. However, neither 

FIVE nor CFAST estimate the temperature at the operator location specifically. For the purpose 

of assessing habitability, the HGL temperature is used to approximate the temperature to which 

the operator would be exposed, regardless of whether the HGL descends to the operator’s 

height. The HGL temperature and depth predictions are shown in Figure A-9. 

FIVE predicts that the temperature would exceed 95°C (200°F) in approximately 12 min when 

the smoke purge system is on. However, it should be noted that the FPA algorithm in FIVE 

overestimated the HGL temperature by an average of 83% in the NRC/EPRI V&V study 

documented in NUREG-1824 (EPRI 1011999). FIVE does not have an algorithm to evaluate 

the fire scenario when the purge system is turned off. 

CFAST predicts that the HGL temperature would exceed the threshold in 15 min when the 

smoke purge system is off. Note that this is the HGL temperature, not the temperature in the 

lower layer where the operator is standing. The HGL descends to 2 m above the floor in 

approximately 20 min. When the smoke purge system is on, CFAST does not estimate that the 

temperature criterion would be reached and that the HGL would be limited to a small layer near 

the ceiling due to the action of the smoke exhaust system. 

FDS does not predict that the temperature near the operator would ever reach 95°C (200°F), 

either when the ventilation is off or in smoke purge mode. The FDS’s predictions of HGL 

temperature are lower than those of the other models because it accounts for the mixing of heat 

and smoke with ambient air due to the high purging flow, since it models flow within the 

compartment in detail. The other models are not capable of modeling the enhanced mixing of 

the high flow rates caused by the purging flows. 
Cabinet Fire in Main Control Room

A-15 

Figure A-9. Hot Gas Layer Temperature and Height for the Main Control Room scenario. 

A.5.2 Heat Flux Criterion 

In the fire scenario that includes the operation of the smoke purge system, neither CFAST nor 

FDS predict that the heat flux to the operator exceeds the tenability criterion (Figure A-10). In 

fact, both models estimate a peak flux of approximately 0.1 kW/m2

, a value that is one-tenth the 

critical value. However, with the smoke purge system turned off, FDS predicts a peak heat flux 

of 0.45 kW/m2

, and CFAST predicts 0.75 kW/m2. The latter prediction falls within 25% of the 

tenability criterion. According to NUREG-1824 (EPRI 1011999), 25% is comparable to the 

reported accuracy of the zone models in predicting heat flux; thus, it is important to assess the 

CFAST prediction in greater detail. This is taken up in the section on Uncertainty. 

Figure A-10. Predicted heat flux at the location of the operator. 

0

20

40

60

80

100

120

140

0 600 1200 1800 2400 3000 3600

Temperature (C)

Time (s)

HGL Temperature

FIVE (FPA Model)

CFAST

CFAST (Purge Mode)

FDS

FDS (Purge Mode)

0

1

2

3

4

5

6

0 600 1200 1800 2400 3000 3600

Height (m)

Time (s)

HGL Height

CFAST

FDS

0.0

0.2

0.4

0.6

0.8

1.0

0 600 1200 1800 2400 3000 3600

Heat Flux (kW/m2)

Time (s)

Heat Flux to Operator

CFAST

CFAST (Purge Mode)

FDS

FDS (Purge Mode)
Cabinet Fire in Main Control Room 

A-16 

A.5.3 Visibility Criterion 

The smoke optical density results are shown for CFAST and FDS in Figure A-11. The CFAST 

prediction is based on its upper layer smoke concentration calculation, whereas that of FDS is 

based on the actual operator location. Both models predict visibility that is still considerably less 

than the tenability criterion of 3 m-1 when the smoke purge system is on, but FDS predicts that 

the tenability criterion will be exceeded in about 12 min while CFAST predicts 18 min when the 

purge system is off. Such conditions could force abandonment of the MCR. It is not surprising 

that FDS predicts a higher smoke concentration near the operator than CFAST because FDS 

predicts lower gas temperatures due to increased mixing of the smoke and the heat from the fire 

with the surrounding air. This also demonstrates that the CFD model, FDS, does not always 

predict conditions that are less severe than those predicted by zone or algebraic models; in fact, 

a given model might estimate a more severe condition for one quantity and a less severe 

condition for another quantity. 

Figure A-11. Visibility criterion for the Main Control Room scenario. 

A.5.4 Uncertainty 

For the MCR fire scenario, the objective of the calculations is to estimate the time to 

abandonment; that is, the time at which the HGL temperature, heat flux, or optical density 

exceeds a critical value. Some of the predicted values do not exceed the critical value at any 

time in the simulation. To better quantify whether or not a critical value is exceeded, the 

uncertainty of the model predictions needs to be calculated. 

As an example of how to calculate model uncertainty, consider the CFAST prediction of the total 

heat flux to the operator. In the NRC/EPRI V&V study (NUREG-1824(EPRI 1011999)), it was 

found that CFAST predictions of total heat flux are, on average, 19 % less than corresponding 

measurements, and the relative standard deviation of its predictions about this average value is 

47 %. Following the guidance put forth in Chapter 4, this suggests that the true value of the 

heat flux in this scenario is normally distributed with a mean of 0.75/0.81=0.93 kW/m2

 and a 

0.0

3.0

6.0

9.0

12.0

15.0

18.0

0 600 1200 1800 2400 3000 3600

Optical Density (1/m)

Time (s)

Optical Density at Operator

CFAST

CFAST (Purge Mode)

FDS

FDS (Purge Mode)
Cabinet Fire in Main Control Room

A-17 

standard deviation of 0.47ۭ0.93=0.44 kW/m2. Therefore, the probability that the heat flux in the 

vicinity of the operator would exceed 1.0 kW/m2

 is: 

ܲሺݍሶᇱᇱ ൐ 1.0ሻ ൌ 1

2 erfc ൬

1.0 െ 0.93

0.44√2 ൰ ؆ 0.44 (A-5)

In other words, there is a 44% chance of exceeding the heat flux tenability criterion when the 

room ventilation system is off, as calculated by CFAST. 

Table A-2 lists the probability of exceeding the critical temperature and heat flux for all the 

models. Notice that even though some models have predicted a higher value than the critical, 

the fact that these models have been shown to over-estimate the given quantity lessens the 

likelihood that the critical threshold would be reached in an actual fire. 

Table A-2. Uncertainty analysis of the model predictions of the MCR scenario. 

Model Quantity Mode Predicted 

Value 

Critical 

Value 

Probability 

of Exceeding 

FIVE Temperature Purge 112 °C 95 °C 0.198 

CFAST Temperature Purge 80 °C 95 °C 0.003 

CFAST Temperature No Purge 105 °C 95 °C 0.705 

FDS Temperature Purge 50 °C 95 °C 0.000 

FDS Temperature No Purge 68 °C 95 °C 0.000 

CFAST Heat Flux Purge 0.15 kW/m2 1.0 kW/m2 0.000 

CFAST Heat Flux No Purge 0.75 kW/m2 1.0 kW/m2 0.432 

FDS Heat Flux Purge 0.15 kW/m2 1.0 kW/m2 0.000 

FDS Heat Flux No Purge 0.40 kW/m2 1.0 kW/m2 0.000 

Note again that the CFAST predictions of heat flux and HGL temperature with the smoke purge 

system off show a dramatically greater chance of exceeding critical values than FDS. The 

reason has less to do with model uncertainty and more to do with model assumptions. CFAST 

is a two-zone model and makes the assumption that all of the smoke and heat from the fire are 

confined to a descending upper layer, whereas FDS, a CFD model, makes no such assumption 

and allows for smoke and heat transport throughout the compartment. Since both models have 

the same production rate of smoke and heat, the fact that the CFD model mixes these exhaust 

products over the entire volume means that its predicted concentration and temperature will 

tend to be lower. 

The models show that the most likely cause of MCR abandonment is excessive smoke and loss 

of visibility. However, Table 4-1 indicates that both CFAST and FDS have been shown to overestimate smoke concentration by at least a factor of 2. Because of the scarcity of experimental 

data, however, it is not possible to better quantify this figure. Nevertheless, an examination of 

Figure A-11 indicates that if one were to adjust the predicted values of smoke concentration to 

account for this bias, the predicted times to abandonment would increase. Further 

consideration of the smoke and its effect on the optical density is taken up in the next section. 
Cabinet Fire in Main Control Room 

A-18 

A.5.5 Sensitivity 

The previous section considers how model uncertainty can affect the predicted results. Model 

sensitivity considers how input parameter uncertainty can affect the predicted results. Recall 

from the discussion in Section A.2 that there is considerable uncertainty in the smoke 

generation rate of real fires, especially in cases where the fire might be under-ventilated inside 

of a cabinet. A value of 10 % was chosen for the smoke yield in the models, even though 

literature values range from 1 % to 20 %. In addition to the uncertainty in the specified input 

value of the smoke yield, the NRC/EPRI V&V study (NUREG-1824 (EPRI 1011999)) indicates 

that both CFAST and FDS over-estimate measured smoke concentrations, on average, by 

factors of 2.65 and 2.70, respectively. In light of these uncertainties in both the models and the 

input parameters, it is prudent to consider the sensitivity of the results of the simulations to the 

selected value of the smoke yield. Table 4.2 indicates that the optical density is directly 

proportional to the smoke yield. This means that if the smoke yield is doubled to 20 %, the 

predicted optical density is doubled as well. If the smoke yield is reduced by a factor of 10 to 

1 %, so is the optical density. The curves in Figure A-11 can easily be adjusted to show the 

effect of a variation in the smoke yield. For example, if the smoke yield were doubled, the 

resulting FDS optical density would, too. But notice that the time to pass the threshold value of 

3 m-1 would only slightly decrease because the optical density is increasing rapidly at this stage 

in the fire. However, a decrease in the smoke yield from 10 % to 1 % would result in the optical 

density never reaching its threshold value, at least according to the model. 

A.6 Conclusion 

Three models were run to assess the conditions within the MCR from a 702 kW cabinet fire. Of 

the three abandonment criteria, it is most likely that the operators would be forced to abandon 

the MCR because the optical density would surpass 3 m-1 approximately 12 min after the fire 

ignites if the smoke purge system fails to operate, according to the FDS analysis. Because FDS 

has been shown to over-estimate smoke concentration by more than a factor of 2, the 12 min 

prediction could be extended to approximately 15 min on account of the model uncertainty. A 

sensitivity analysis indicates that a reduction in the smoke yield from the assumed 10 % could 

have a similar effect of extending the time to abandonment. Increasing the assumed smoke 

yield would not significantly decrease the abandonment time. 

If the smoke purge system does operate, removing smoke at a rate of 25 ACH, CFAST and 

FDS both predict that the room remains habitable, while the FPA calculation in FIVE predicts 

that the threshold temperature would be exceeded. However, FIVE has been shown to overpredict HGL temperature by approximately 50 %, which means that the likelihood of exceeding 

the critical HGL temperature, if one accounts for the model uncertainty, is approximately 20 %. 

A.7 References 

1. NUREG-1805, Fire Dynamics Tools, 2004.

2. NUREG/CR-6850 (EPRI 1011989), Fire PRA Methodology for Nuclear Power Facilities, 

2005. 

3. NUREG-1824 (EPRI 1011989, Verification and Validation of Selected Fire Models for Nuclear 

Power Plant Applications, 2007. 

4. SFPE Handbook of Fire Protection Engineering, 4th edition, 2008. 

5. NIST SP 1018-5, Fire Dynamics Simulator (Version 5), Technical Reference Guide, Vol. 3, 

Experimental Validation. 
Cabinet Fire in Main Control Room

A-19 

6. NIST SP 1030. CFAST: An Engineering Tool for Estimating Fire Growth and Smoke 

Transport, Version 5 - Technical Reference Guide, National Institute of Standards and 

Technology, Gaithersburg, Maryland, 2004. 

7. G.W. Mulholland and C. Croarkin. “Specific Extinction Coefficient of Flame Generated 

Smoke.” Fire and Materials, 24:227–230, 2000. 

8. U.O. Köylu and G.M. Faeth. “Carbon Monoxide and Soot Emissions from Liquid-Fueled 

Buoyant Turbulent Diffusion Flames,” Combustion and Flame, 87:61–76, 1991. 

9. J.P. Holman, Heat Transfer, 7th edition, McGraw-Hill, New York, 1990. 

A.8 Attachments 

1. FDS input files: 

a. Main_Control_Room_No_Purge.fds 

b. Main_Control_Room_Purge.fds 

2. CFAST input files: 

a. Cabinet fire in MCR No Ventilation.in 

b. Cabinet fire in MCR.in 

c. MCR 702 kW.o 

d. thermal.csv 

 
Cabinet Fire in Main Control Room 

A-20 
B-1 

B 

CABINET FIRE IN SWITCHGEAR ROOM 

B.1 Modeling Objective 

The calculations described in this appendix estimate the effects of fire in a cabinet in a 

Switchgear Room on nearby cable and cabinet targets. These calculations are part of a larger 

fire analysis described in Chapter 11 of NUREG/CR-6850 (EPRI 1011989), Volume 2, “Detailed 

Fire Modeling (Task 11).” The Switchgear Room contains both Train A and Train B safetyrelated equipment that is not separated as required by Appendix R. The lack of separation 

between the two has been identified as an unanalyzed condition. The purpose of the 

calculation is to analyze this condition and determine whether these targets fail, and, if so, at 

what time failure occurs. The time to smoke detector activation is also estimated. The 

calculation will provide information for a decision on the hazard and risk for this scenario. 

B.2 Description of the Fire Scenario 

General Description: The 4160 V Switchgear Room is located in the auxiliary building. The 

Switchgear Room contains three banks of cabinets (labeled A, B, and C in Figure B-1). The 

center cabinet bank (Cabinet B) serves Train A equipment necessary for safe shutdown in the 

event of a fire. The cabinet bank on the north side of the compartment serves both non-safety 

and safety-related Train A equipment. The cabinet bank on the south side of the compartment 

serves non-safety-related equipment. In addition to the cabinets in the compartment, there are 

nine cable trays, three stacks of three trays each, which run west to east, directly above each of 

the cabinet banks. The lower two trays above the middle bank of cabinets contain control 

cables for safety-related Train B equipment. The compartment is not typically manned. 

Geometry: A plan and section view of the Switchgear Room is shown in Figure B-1. 

Construction: The compartment floor, ceiling and walls are concrete, nominally 0.5 m (1.6 ft) 

thick. The cabinets and cable trays are made of steel, 1.5 mm (0.06 in) thick. 

Materials: Nominal values for the thermal properties of various materials in the compartment 

are listed in Table 3-1 (NUREG-1805, Table 2-3). The cable trays are filled with PE-insulated, 

PVC-jacketed control cables, which have a diameter of approximately 15 mm (0.6 in), a jacket 

thickness of approximately 1.5 mm (0.06 in), and seven conductors. They are contained in nine 

stacked cable trays. Cables are considered damaged when the temperature reaches 205°C 

(400°F) or the exposure heat flux reaches 6 kW/m2

 (NUREG-1805, Appendix A). The damage 

criteria for the adjacent cabinet is taken to be equal to that for PVC cable since the cables inside 

the cabinet are unqualified. 

Detection System: Two smoke detectors are located in the compartment at the locations 

shown in Figure B-1. The detectors are UL-listed with a nominal sensitivity of 4.9 %/m. 

Ventilation: There are three supply and three return registers located near the side walls, as 

seen in Figure B-1. Each register has a rate of 0.472 m3

/s. The mechanical ventilation is 

normally on, and normal operations continue during the fire. The supply air to the compartment 
Cabinet Fire in Switchgear Room 

B-2 

is equally distributed among the supply vents, and the return air is drawn equally from the 

returns. The compartment has only one door, which is normally closed. The room temperature 

is maintained at 20°C (68°F), and the pressure is comparable to adjacent compartments. 

Leakage from the compartment occurs via a 2.5 cm (1 in)-high crack under the 0.91 m (3 ft)-

wide door on the west side of the compartment. All other penetrations are sealed. 

Fire: The fire ignites in one electrical cabinet in the middle bank of cabinets, as specified in the 

drawing. The cabinet door is closed, but there are vents on the top of the cabinet for air 

circulation. It contains more than one bundle of unqualified cable. The fire grows following a “tsquared” curve to a maximum value of 464 kW in 12 min and remains steady for 8 additional 

minutes, consistent with NUREG/CR-6850 (EPRI 1011989), page G-5, for a cabinet with more 

than one cable bundle of unqualified cable. After 20 min, the fire’s HRR decays linearly to zero 

in 12 min. A peak fire intensity of 464 kW represents the 98th percentile of the probability 

distribution for HRRs in cabinets with unqualified cable in scenarios where flames propagate 

through cable bundles. From a cabinet configuration perspective, this selection is appropriate 

for control cables where cable loading is typically higher than in other types of cabinets. From 

an applications perspective, the use of the 98th percentile is consistent with the guidance 

provided in NUREG/CR-6850 (EPRI 1011989) for evaluating fire conditions with different fire 

intensities (including the 98th percentile) within the probability distribution range. 

There is an air vent on the top the cabinet. The air vent is 0.6 m (2 ft) wide and 0.3 m (1 ft) long. 

The cabinet is 2.4 m (8 ft) tall. Consistent with NUREG/CR-6850 (EPRI 1011989), the fire burns 

within the interior of the cabinet, and the smoke, heat, and possibly flames exhaust from the air 

vent at the top of the cabinet. 

The radiative fraction13 of the fire is 35%, consistent with sooty fires. Burning cables in an 

electrical cabinet would produce a sooty fire (Tewarson, SFPE Handbook, 4th ed., Table 3-4.16). 

The heat of combustion of the burning cables is 24 kJ/g (Table 2-4 of NUREG-1805). This 

number is appropriate for PE/PVC cable. A mixture of PE (C2H4) and PVC (C2H3Cl) would have 

an effective chemical formula of C2H3.5Cl0.5. 

For certain smoke detector activation calculations, soot yield14 is necessary. According to 

Tewarson’s chapter in the SFPE Handbook, the soot yield for the various combustible materials 

within the cabinet ranges from 0.01 to 0.20. The soot yield for this scenario is taken to be 0.10, 

but the results of the calculation should be assessed in light of the wide variation in possible 

soot yields, and the fact that the fire could potentially be underventilated within the cabinet. The 

value of 0.10 is an estimate for a well-ventilated fire close to an equivalency ratio of 1. The 

calculated optical density is directly proportional to this parameter; thus, the entire range of 

values can easily be assessed during post-processing of the results. 

The mass extinction coefficient is 8.7 m2

/g, based on measurements made by Mulholland and 

Croarkin [Mullholland and Croarkin, Fire and Materials]. 

The CO yield of the fire, ݕCO, can be estimated from the soot yield, ݕ௦, using a correlation 

developed by Köylu and Faeth: 

 

13 The fraction of the fire’s total energy emitted as thermal radiation. 14 The soot yield is defined as the mass of smoke particulate generated per unit mass of fuel consumed. 
Cabinet Fire in Switchgear Room

B-3 

ݔ 12 ൌ COݕ

௙ߥ ௙ܯ

0.0014 ൅ 0.37 ݕ௦ (B-1) 

where x is the number of carbon atoms in a fuel molecule (two in this example), M୤ is the 

molecular weight of the fuel (45.26 g/mol, calculated from the effective chemical formula), yୱ is 

the soot yield, and ν୤ is the stoichiometric coefficient of the fuel, here taken to be one since all 

species yields are taken as a ratio to the mass of fuel consumed. For this example, the CO 

yield (ݕCO) is calculated from the above equation to be 0.038 kg/kg. 

Based on the yields of soot and CO for the fuel considered in this example, the complete 

chemical reaction can be written: 

CଶHଷ.ହCl଴.ହ ൅ 2.34 Oଶ ՜ 0.06 CO ൅ 0.38 C ൅ 1.56 COଶ ൅ 1.5 HଶO ൅ 0.5 HCl (B-2) 

Note that the soot is treated as pure carbon, C, and that all of the chlorine produces HCl. 
Cabinet Fire in Switchgear Room 

B-4 

Figure B-1. Geometry of the Switchgear Room. 
Cabinet Fire in Switchgear Room

B-5 

B.3 Selection and Evaluation of Fire Models 

NUREG/CR-6850 (EPRI 1011989), Volume 2, Chapter 11 recommends empirical tools, zone 

models and field models for estimating the HGL temperature, heat flux, descent rate, and 

smoke obscuration in non-MCR fire scenarios. Following is a discussion of further strengths 

and weaknesses of the available models. 

Algebraic Models: FIVE and the FDTs

 both contain correlations to estimate the HGL 

Temperatures within a closed, ventilated compartment. However, the FDTs

 do not allow the 

HRR to be input as a function of time. With a constant HRR, the FDTs

 could be used by 

assuming an instantaneous, fully developed fire that remains at peak HRR for the duration of 

the fire scenario. This approach would likely estimate a shorter time to failure than tools that 

utilize a time-dependent HRR, but it may be useful as a screening tool. Care may be needed to 

ensure that such an approach would provide conservative results. In a time to failure analysis, 

the constant HRR may be conservative, but, for estimation of detection, a very short detection 

time is likely unrealistic and non-conservative. 

FIVE and the FDTs

 both contain methods to estimate the heat flux from a fire to a target. The 

FIVE analysis uses Alpert’s plume temperature correlations and Heskestad’s flame height 

correlation, whereas the FDTs

 analysis uses only Heskestad’s to estimate the temperature to 

which the cables are exposed. Neither analysis includes the effects of blockage due to the trays 

or the effect of thermal radiation from the Hot Gas Layer on the targets; thus, it is possible that 

the use of either of these models could lead to an underprediction of the heat flux. 

Zone Models: The fire scenario outlined in the previous section falls within the range of 

applicability for a zone model. The simple compartment geometry of this scenario lends itself 

well to the application of zone models. Both CFAST and MAGIC include algorithms to estimate 

the temperature of cable targets. 

In CFAST, target temperatures are calculated based on a one-dimensional heat transfer 

calculation that includes radiation from the fire, upper and lower gas layers, and bounding 

surfaces; convection from nearby gases; and conduction into the target. Radiation from the fire 

is modeled using a point source radiation calculation from the fire to the target. 

In MAGIC, cable target temperatures are also calculated based on a one-dimensional heat 

transfer calculation that includes radiation exchanges between compartment surfaces, the upper 

and lower gas layers, and the nearby compartment fires; and convective heat transfer that 

involves targets heating up in the HGL, fire plume, and ceiling jet sub-layers. Each cable is 

divided into 20 cm (8 in.)-long segments, and the maximum surface temperature calculated on 

all of the segments is the criterion to cable ignition (once the ignition temperature is reached, the 

reported surface temperature remains constant). Thus, the relative location of the cables to the 

flame, plume, ceiling jet, or layers will affect the temperature calculation and the time to failure. 

The relative position of the cabinet fire and cable trays may provide a challenge because the 

algorithms used by the zone models to assess target damage assume are based on a fire 

radiation point source. 

For this analysis, the zone model CFAST is used. 
Cabinet Fire in Switchgear Room 

B-6 

CFD Models: This scenario is a fairly typical application of FDS. Unlike the calculation 

performed for the Main Control Room scenario, however, the model is applied here in much the 

same way that the zone models approach it, with the fire on top of the cabinet. The primary 

advantage of a CFD model for this fire scenario is that the CFD model can estimate local 

conditions at the specific location of the target cables and adjacent cabinet. In the scenario 

under consideration, the fire is confined mainly within a closed cabinet. This could be modeled 

in FDS, and its results used to assess the effect of this detail on the overall result. For this 

analysis, FDS results are included as a comparison to the zone model calculations. 

Validation: NUREG-1824 (EPRI 1011999) contains experimental validation results for CFAST 

and FDS that are appropriate for this scenario. NIST has expanded the NRC/EPRI V&V to 

include the latest versions of CFAST (6.1.1) (Peacock, 2008) and FDS (5.5.3) (McGrattan, 

2010). In particular, the ICFMP (International Collaborative Fire Model Project) Benchmark 

Exercise #3 test series was designed specifically as a mock-up of a real Switchgear Room. 

These experiments include ventilation effects and heat fluxes to and temperatures of various 

targets, particularly cables. Fire sizes in these experiments bound those used in this scenario. 

Although NUREG-1824 (EPRI 1011999) includes validation results for both temperature and 

smoke concentration, it does not include validation results specific to detector activation. 

CFAST predictions are based on a temperature analogy for detector activation. Available 

studies have reported gas temperature rises in the range of about 5 oC (41 oF) to 15 oC (59 oF) 

at smoke detector activation (see Davis and Notarianni 1996 or Bukowski and Averill, 1998). 

The FDS Validation Guide (McGrattan, 2010) includes the results of validation studies on 

detector activation and concludes that the model is able to estimate the smoke and gas 

concentrations, heat, and flow velocities at detector locations to within 15% of measurements, a 

value consistent with FDS predictions included in NUREG-1824 (EPRI 1011989). 

Table 2-5 of Volume 1 of NUREG-1824 (EPRI 1011989) lists various important model 

parameters and the ranges for which the validation study is applicable. Table B-1 below lists 

the values of these parameters for this fire scenario, along with their ranges of applicability. The 

parameter, Fire Froude Number, is essentially a measure of the fire’s heat output relative to its 

base area. In this example, the fire is assumed to attach itself to the cabinet’s top vent with the 

vent opening serving as its “base” area. This assumption leads to a higher value of ܳሶ

 than כ

would be calculated if it were not assumed that the fire burns completely outside of the cabinet. 

Thus, the high value of ܳሶ

כ is the result of an assumption that will lead to more severe fire 

conditions than would be expected if the fire were assumed to burn partially within the cabinet. 

Therefore, it can be assumed that the model predictions would be valid for this scenario.
Cabinet Fire in Switchgear Room

B-7 

Table B-1. Key parameters and their ranges of applicability to NUREG-1824. 

Quantity Normalized Parameter Calculation Validation Range In Range? 

Fire Froude 

כܳ Number

ሶ

ൌ

ܳ

ሶ

ܦ݃ଶඥܦஶܶ௣ܿஶߩ

ൌ

464

1.2 ൈ 1.012 ൈ 293 ൈ 0.48ଶ ൈ √9.8 ൈ 0.48 ؆ 2.7 0.4 – 2.4 No 

Flame Length, Lf, 

relative to the 

Ceiling Height, H

௙ܮ

ܪ

ൌ

2.36.1 ؆ 0.4 0.2 – 1.0 Yes 

Ceiling Jet Radial 

Distance,rcj, 

relative to the 

Ceiling Height, H

N/A – Ceiling jet targets are not included in simulation. 1.2 – 1.7 N/A 

Equivalence Ratio, 

φ, as an indicator 

of the Ventilation 

Rate 

߮ ൌ

݉ሶ F/݉ሶ Oమ

ݎ

ؠ

ܳ

ሶ

Oమ ሶ݉ ܪ∆ ݎ

ൌ

464

13,100 ൈ 0.4 ؆ 0.09

݉ሶ Oమ ൌ 0.23 ߩஶܸ

ሶ

ൌ 0.23 ൈ 1.2 ൈ 1.42 ൌ 0.4

0.04 – 0.6 Yes 

Compartment 

Aspect Ratio 

ܮ

ܪ

ൌ

26.5

6.1 ؆ 4.3

ܹ

ܪ

ൌ

18.5

6.1 ؆ 3.0

0.6 – 5.7 Yes 

Target Distance, r, 

relative to the Fire 

Diameter, D

ݎ

ܦ

ൌ

1.5

0.48 ؆ 3.1 2.2 – 5.7 Yes 
Cabinet Fire in Switchgear Room 

B-8 
Cabinet Fire in Switchgear Room

B-9 

B.4 Estimation of Fire-Generated Conditions 

This section provides details specific to each model. 

B.4.1 Zone Model (CFAST) 

Geometry: The CFAST analysis defines the compartment as a single rectangular 

parallelepiped with the specified dimensions. While there are a number of cable trays in the 

compartment, the compartment is sufficiently large that it is not considered a significant fraction 

of the total volume, so the compartment dimensions are taken directly from the scenario 

description and Figure B-1. Figure B-2 illustrates the scenario as modeled by CFAST. 

Figure B-2. CFAST/Smokeview rendering of Switchgear Room. 

Fire: CFAST requires a user-specified time-dependent HRR and stoichiometry for the 

combustion of fuel and oxygen. For the initial fire source, the HRR is input as specified in the 

scenario description. For the secondary fuels, cable ignited by the initial fire, a relatively simple 

model for predicting the growth and spread of a fire within a vertical stack of horizontal cable 

trays is used. The model is referred to as FLASH-CAT, short for Flame Spread over Horizontal 

Cable Trays. The basic assumptions are taken from Appendix R of NUREG/CR-6850, with 

some additional information provided by the small- and intermediate-scale experiments 

described in NUREG/CR-7010. The FLASH-CAT model makes use of the following 

assumptions: 

 The cable trays are horizontal and stacked vertically. 

 There are no barriers separating the trays, and the tray tops and bottoms are open. 

 The cables are not protected with coatings, armor shielding, or thermal blankets of any 

kind. 

 There is a fire beneath the lowest tray. 
Cabinet Fire in Switchgear Room 

B-10 

 Each tray has at least a single row of cables, or roughly 25% of the NEC limit. 

Under these assumptions, the fire propagates upward through the array of cable trays according 

to an empirically determined timing sequence. In other words, the time for the fire to spread 

from one tray to the tray above is a function only of its order in the stack, not the thermal 

properties of the cables. The length of cables within a given tray that ignite initially increases as 

the fire spreads upwards. Lateral spread of the fire begins as soon as the cables within the tray 

ignite. This produces a solid V-shaped burning pattern that expands laterally with time. As the 

mass of combustible material within the center of the V is consumed, the V-shape becomes an 

expanding, open wedge of burning cable. The fires in each tray continue to spread until the end 

of the tray is reached. Further details are provided in NUREG/CR-7010, Volume 1. 

For species yields, the fuel molecule is taken to be C2H3.5Cl0.5 and the soot yield to be 0.1 kg/kg, 

as specified above. The basic stoichiometry of the reaction is given in Eq. (B-2). The CO2 yield 

is calculated as follows: 

ݕCOమ ൌ ߥCOమܯCOమ

௙ܯ௙ߥ

ൌ 1.56 ൈ 44

1 ൈ 45.26 ؆ 1.52 kg/kg (B-3) 

Direct inputs for production rates of CO and soot in CFAST are normalized to this CO2 yield. 

Thus, CFAST input of CO/CO2 is 0.025, and C/CO2 is 0.066. HCl production is input relative to 

the fuel and is 0.40 kg/kg for this example. A final CFAST input is the ratio of the mass of 

hydrogen to the mass of carbon in the fuel, or 0.15 kg/kg. 

Materials: CFAST takes the walls, floor, and ceiling as made of concrete, and uses the 

compartment drawing dimensions and target properties directly. 

Ventilation: Mechanical ventilation and leakage are specified as input to CFAST directly from 

the scenario description. CFAST uses three inlet and three outlet vents for the mechanical 

ventilation at the heights specified in the scenario description. Horizontal placement in the 

compartment does not affect the zone model calculation and is not part of the input. 

Fire/Smoke Detection: In CFAST, there is no direct way of calculating smoke density for 

smoke detector activation. The approach recommended by the developers is to model the 

smoke detector as a sprinkler with a low activation temperature and RTI15. An activation 

temperature of 30 o

C (a 10 oC rise above ambient) and an RTI of 5 (m/s)1/2 was selected 

consistent with the recommendations in the CFAST User’s Guide. A temperature-based 

surrogate for smoke detector activation should be used with caution, particularly in locations far 

removed from the fire source. Gas temperatures near the ceiling are cooled due to transfer of 

heat to the ceiling so that lower temperatures are to be expected further from the fire source, 

increasing estimates of detector activation times for temperature-based methods. Direct 

estimation of smoke concentration within the detector, such as that included in FDS, is not 

affected by heat losses to the ceiling and can be expected to provide more accurate estimates 

of smoke detector activation. 

 

15 The accuracy of smoke detector activation predictions was not evaluated in the NUREG-1824 (EPRI 

1011999) V&V study and has been identified as an area needing additional research (NUREG/CR-6978 

(SAND2008-3997P)). While this guide provides some recommendations in this area, the user should 

carefully evaluate the applicability of these recommendations for the specific scenario and in light of new 

research in the area. 
Cabinet Fire in Switchgear Room

B-11 

Cable Targets: In CFAST, target temperatures are calculated with a one-dimensional 

cylindrical heat transfer calculation based on the material properties and cable diameter, as 

specified in the scenario description. 

B.4.2 CFD Model (FDS) 

Geometry: The compartment has a simple rectangular geometry that coincides with the 

external boundary of the computational domain. In other words, the exterior walls are not 

explicitly declared, but are defined by default to be the external boundaries of the domain with 

the surface properties of concrete, given above. The cabinets are modeled simply as boxes 

constructed of steel, whose properties are specified above. No attempt is made to model the 

interior of the cabinets because the fire has been specified as originating at or near the top of 

one of the cabinets. Figure B-3 shows the compartment geometry used in FDS. 

The numerical mesh consists of uniform grid cells, roughly 0.2 m (8 in) on a side. This is a 

relatively coarse mesh for scenarios of this type. 

Materials: The material properties are applied directly as specified to the walls, floor, ceiling, 

and cabinet. The cabinet is models as a hollow steel box that is at ambient temperature inside 

because details of the interior are not available and are irrelevant to the question being asked. 

Fire: The initial fire source is specified via a “burner” atop the central cabinet with the specified 

HRR. This is meant to represent a fire burning near the top of the cabinet that exhausts through 

the vent. The fuel for the fire is the PE/PVC cables within the cabinet. The reaction is given in 

Eq. (B-2). 

The FLASH-CAT model (NUREG/CR-7010, Volume 1) is used to determine the ignition, HRR, 

flame spread, and extinction of the cables above the original fire source. Figure B-4 shows a 

snapshot of the burning cable during the simulation. First, ignition of the cables in the lowest 

tray is assumed to occur when the internal temperature of a target cable within that tray reaches 

the failure temperature of 200°C. This assumption is based on guidance given in NUREG/CR6850 (EPRI 1011989), Appendix R. The calculation of the cable’s internal temperature is based 

on the THIEF methodology (NUREG/CR-6931, Volume 3). Following ignition, the cables in the 

first tray burn at a rate of 250 kW/m2

, a value appropriate for thermoplastic cables (NUREG/CR7010, Volume 1). The area of the initial fire is bounded by the width of the tray (0.8 m) and the 

length of the vent in the cabinet (0.6 m). The fire in the first tray spreads laterally at a rate of 

3.2 m/h (NUREG/CR-6850 (EPRI 1011989), Appendix R). The fire in the second tray ignites 

4 min after the first, and the lateral extent of the initial fire in the second tray is widened based 

on the 35° upward spread angle described in NUREG/CR-6850 (EPRI 1011989), Appendix R. 

The burning and spread rates of the fire in the second tray are the same as the first. The fire in 

the third tray ignites 3 min after the fire in the second, and the initial lateral extent of the fire is 

widened yet again following the 35° spread angle. Local burnout of the fire occurs when the 

cable plastic is consumed. 

Ventilation: The door is included in the calculation merely as a surface of different properties 

from the default concrete wall. The supply and return vents are specified according to the 

drawing and given volume flow rates. Note that because of the relative coarseness of the 

underlying numerical grid, the ventilation rate is input directly in terms of the volume flow 

rate (m3

/s) rather than as a separate vent area (m2) and velocity (m/s). The model automatically 
Cabinet Fire in Switchgear Room 

B-12 

adjusts the dimensions of all objects to conform to the numerical mesh, and it also adjusts the 

velocity of the air stream to properly reflect the desired volume flow rate. 

Figure B-3. FDS/Smokeview rendering of the Switchgear Room. 

Figure B-4. FDS/Smokeview rendering of the Switchgear Room Fire showing localized 

ignition of extinction of secondary cable fires resulting from initial cabinet fire. 

Fire/Smoke Detection: FDS includes specific algorithms to estimate the response of heat and 

smoke detectors to the local conditions surrounding the detectors. For smoke detectors, the 

inputs are the smoke obscuration (taken directly from the scenario definition) and a 

characteristic length (taken as the recommended default value of 1.8 m). 
Cabinet Fire in Switchgear Room

B-13 

B.5 Evaluation of Results 

The purpose of the calculations is to assess (1) the potential damage to cables in trays above 

an electrical cabinet fire and (2) the potential damage to adjacent cabinets. Based on the 

analysis detailed below, the cabinet fire is likely to fail the electrical cables just overhead in 

approximately 10 min, based on the analyses of both CFAST and FDS; however, it is unlikely 

that the fire would damage the adjacent cabinets. 

B.5.1 Cable Ignition and Damage 

The algebraic models cannot be used in this case to assess the damage to cables. FIVE does 

not have an algorithm that considers the thermal inertia of the cables. FDTs

 does, but the model 

is only applicable when the exposing temperature is constant which is not the case for this 

example. 

CFAST and FDS estimate the ignition and burning of the cables. NUREG/CR-6850 (EPRI 

1011989) contains some guidance on modeling cable ignition, flame spread, and the fire’s 

resulting heat release based on a limited set of fire test data. The differences in HRR between 

the models (Figure B-5) result from variations in the implementation of this guidance. Figure B5(a) shows the HRR from the initial cabinet fire source only. Figure B-5(b) shows the overall 

HRR, including the initial cabinet fire source plus the addition of cables ignited by this initial fire. 

(a) (b) 

Figure B-5. Heat release rate inputs to CFAST and FDS for Switchgear Room cabinet fire 

scenario. 

There are several possibilities that can be used to assess the potential for ignition of the lowest 

cable tray from the initial fire source. Cables are considered damaged when the temperature 

reaches 205°C (400°F) or the exposure heat flux reaches 6 kW/m2

 (NUREG-1805, Appendix A). 

These criteria are intended to be indicative of electrical failure, but are routinely assumed to also 

apply as ignition criteria. In newer studies in NUREG/CR-7010, cable ignition was not observed 

at fluxes below 25 kW/m2

, and most often only with direct flame impingement. Handbook values 

for minimum ignition flux for power and communication cables are reported in the range of 15 

0

50

100

150

200

250

300

350

400

450

500

0 600 1200 1800 2400 3000 3600

HRR (kW)

Time (s)

Heat Release Rate

CFAST

FDS

0

200

400

600

800

1000

1200

1400

1600

1800

0 600 1200 1800 2400 3000 3600

HRR (kW)

Time (s)

Heat Release Rate

CFAST

FDS
Cabinet Fire in Switchgear Room 

B-14 

kW/m2 to 35 kW/m2 (SFPE Handbook, Table 3-4.2). For this scenario, CFAST predicts that the 

flame height reaches the cable tray in approximately 490 s, quite similar to the temperaturebased prediction. Table B-2 shows estimated time to ignition of the lowest cable tray for a 

variety of ignition criteria. For this simulation, 490 s was chosen. 

Table B-2. Estimated time to ignition of lowest cable tray, CFAST, Switchgear Room 

cabinet fire 

Ignition Criterion Time (s) 

Gas temperature ≥ 205 oC 270 s 

Cable temperature ≥ 205 oC 860 s 

Heat flux ≥ 6 kW/m2 490 s 

Heat flux ≥ 15 kW/m2 740 s 

Flame impingement 490 s 

The CFAST and FDS temperature predictions resulting from Tray A cables are shown in Figure 

B-6. FDS predicts cable failure in Tray A at about 495 s, CFAST in about 500 s. Peak 

temperatures from both models are well above the failure criteria for the cables, so it can be 

expected that the cables will ignite and provide an additional source of fire. 

Qualitatively, the results of the CFAST and FDS predictions are quite different, but this is largely 

after flames have reached the cable tray. The radiation from the fire source in CFAST is 

calculated based on a point source fire positioned at the base of the fire. Thus, once the fire 

grows and the flame height approaches the target cable tray, the CFAST can be expected to 

Figure B-6. Estimated temperatures for Cable Tray A directly above fire source for 

Switchgear Room cabinet fire scenario. 

0

100

200

300

400

500

600

700

800

900

1000

0 600 1200 1800 2400 3000 3600

Temperature (C)

Time (s)

Cable Tray A Temperature

CFAST

FDS
Cabinet Fire in Switchgear Room

B-15 

underestimate the local cable temperature and heat flux since the cable would actually be 

immersed within the flames. CFAST does include an estimate of the flame height, which can 

also be used as an indicator of damage to the cable. For this scenario, CFAST predicts the 

flame height reaches the cable tray in approximately 490 s, quite similar to the temperaturebased prediction. Past this point, CFAST estimates of the local target temperature are expected 

to be underpredictions. FDS predictions include the impact of direct flame impingement and 

immersion of the target in flames. Thus, the higher temperatures predicted by FDS are 

expected. 

Upon ignition of the bottom cable tray (Cable Tray A), the higher cable trays are ignited 

consistent with the FLASH-CAT model. 

B.5.2 Cabinet Damage 

To assess potential damage to adjacent cabinets, both the predicted temperatures and heat 

fluxes are evaluated. Because the two adjacent cabinets are equidistant from the fire and have 

similar properties, only one is considered here. The critical damage thresholds are the same for 

these cabinets as the cables in trays. Figure B-7 shows estimated temperature and heat flux on 

the cabinet surface. 

The algebraic models are not capable of estimating the temperature of a target such as an 

electrical cabinet, whereas the other models are. CFAST and FDS all estimate similar peak 

temperatures below 145°C (264°F), which is well below the threshold of 205°C (424°F). The 

somewhat higher cabinet temperature and heat flux predicted by CFAST is consistent with the 

higher HRR of the fire for the CFAST simulation. CFAST and FDS both estimate an incident 

heat flux below about 4 kW/m2

, with the difference again caused by different HRRs. 

Figure B-7. Estimated temperature and heat flux on cabinet adjacent to fire source in 

Switchgear Room cabinet fire scenario. 

B.5.3 Smoke Detector Activation 

Table B-3 shows the smoke detection activation times estimated by the models. CFAST bases 

activation estimates on a specified temperature rise, whereas FDS bases its prediction on the 

0

20

40

60

80

100

120

140

160

0 600 1200 1800 2400 3000 3600

Temperature (C)

Time (s)

Cabinet A Temperature

CFAST

FDS

0

1

2

3

4

5

0 600 1200 1800 2400 3000 3600

Heat Flux (kW/m2)

Time (s)

Cabinet A Heat Flux

CFAST

FDS
Cabinet Fire in Switchgear Room 

B-16 

local smoke concentration in the vicinity of the detector. The activation times based on 

temperature rise range from 3 to 5 min, whereas that based on smoke concentration is 

approximately 1 min. This is not surprising because the compartment is relatively large, and 

heat losses from the smoke plume to the ceiling cool the gases early in the fire, delaying the 

temperature-based activation estimate. 

Table B-3. Smoke detector activation times, Switchgear Room cabinet fire 

Model Detector 1 Detector 2 

CFAST 176 s 431 s 

FDS 50 s 140 s 

B.5.4 Uncertainty 

In this example, the objective of the calculations is to estimate the effects of fire in a cabinet in a 

Switchgear Room on nearby cable and cabinet targets; that is, to determine whether and when 

temperatures and/or heat flux on the cable and adjacent cabinets exceed established critical 

values. Chapter 4, Model Uncertainty, provides guidance on how to express the uncertainty of 

the predictions. In the NRC/EPRI V&V study (NUREG-1824 (EPRI 1011989)), it was found that 

predictions of target temperatures are, on average, equal for CFAST and 2 % greater for FDS 

than corresponding measurements, and the relative standard deviation of its predictions about 

this average value is 27 % for CFAST and 13 % for FDS. For CFAST (the higher estimated 

temperature), this suggests that the true value of the peak cable temperature in this scenario is 

normally distributed with a mean of 144 °C and a standard deviation of 34 °C. Therefore, the 

probability that the cable temperature would exceed 205 °C is: 

ܲሺܶ ൐ 205ሻ ൌ 1

2 erfc ൬

205 െ 145

34√2 ൰ ൌ 0.04 (B-4) 

In other words, there is a 4 % chance of exceeding the temperature threshold for cables inside 

cabinet A, according to the CFAST prediction. With a lower temperature and standard deviation, 

the probability estimate from FDS calculations would be lower. 

It should also be noted that these damage criteria are intended to be indicative of electrical 

failure, but are routinely assumed to also apply as ignition criteria. In newer studies in 

NUREG/CR-7010, cable ignition was not observed at fluxes below 25 kW/m2

, and most often 

only with direct flame impingement. Handbook values for minimum ignition flux for power and 

communication cables are reported in the range of 15 kW/m2

 to 35 kW/m2 (SFPE Handbook, 

Table 3-4.2). 

Table B-4 lists the probability of exceeding the critical temperature and heat flux for all the 

model calculations. 
Cabinet Fire in Switchgear Room

B-17 

Table B-4. Uncertainty analysis of the model predictions of the cabinet fire scenario 

Quantity Location Model Predicted 

Value 

Critical 

Value 

Probability 

of 

Exceeding 

Temperature 

Cable Tray A CFAST 533 °C 205 0.991 

FDS 864 °C 205 1.000 

Cabinet A CFAST 144 °C 205 0.036 

FDS 108 °C 205 0.000 

Heat Flux Cabinet A CFAST 4.12 kW/m2 11 0.007 

FDS 2.85 kW/m2 11 0.000 

B.5.5 Sensitivity 

Referring again to Table B-4, it is clear that the cables directly above the cabinet fire would be 

damaged by the fire and provide an additional fire source for the cables above. In addition to 

examining the accuracy of the models as is done in the previous section, it is also possible to 

estimate how large a fire would be required to damage the cables within the adjacent cabinet. 

Table 4-3 indicates that the temperature is proportional to the HRR to the 2/3 power. Following 

the methodology in Section 4.4.1, in order to increase the predicted heat flux by 7 kW/m2

 to 

reach 11 kW/m2

, the peak HRR, ܳሶ, must increase by approximately: 

∆ܳሶ ൎ 3

2ܳሶ ∆ܶ

ܶെܶ଴

ሶ ൌ 3

2 1600

61

124 ൎ 1180 kW (B-5) 

In other words, the peak HRR would have to be approximately 1600+1180=2880 kW to cause 

the cables in cabinet A to fail. 

B.6 Conclusion 

Based on the analysis, the cabinet fire is likely to fail the electrical cables directly overhead in 

approximately 10 min, based on the analyses of both CFAST and FDS. The additional cable 

trays directly above ignite in turn. However, it is unlikely that the fire would damage the 

adjacent cabinets. 

B.7 References 

1. NUREG-1805, Fire Dynamics Tool, 2004.

2. NUREG/CR-6850 (EPRI 1011989), Fire PRA Methodology for Nuclear Power Facilities. 

3. NUREG-1824 (EPRI 1011999), Verification and Validation of Selected Fire Models for 

Nuclear Power Plant Applications, 2007. 

4. SFPE Handbook of Fire Protection Engineering, 4th edition, 2008. 

5. G.W. Mulholland and C. Croarkin. “Specific Extinction Coefficient of Flame Generated 

Smoke.” Fire and Materials, 24:227–230, 2000. 

6. UL 217. Underwriters Laboratories, Inc., Single Station Fire Alarm Device. 

7. U.O. Köylu and G.M. Faeth, Carbon Monoxide and Soot Emissions from Liquid-Fueled 

Buoyant Turbulent Diffusion Flames. Combustion and Flame, 87:61–76, 1991. 
Cabinet Fire in Switchgear Room 

B-18 

8. Jones, W., R. Peacock, G. Forney, and P. Reneke, “CFAST: An Engineering Tool for 

Estimating Fire Growth and Smoke Transport, Version 5 - Technical Reference Guide,” SP 

1030, National Institute of Standards and Technology, Gaithersburg, MD, 2004. 

9. Gay, L., C. Epiard, and B. Gautier, “MAGIC Software Version 4.1.1: Mathematical Model,” 

EdF HI82/04/024/B, Electricité de France, France, November 2005. 

10. NIST SP 1018-5, Fire Dynamics Simulator (Version 5), Technical Reference Guide, Vol. 3, 

Experimental Validation. 

Attachments 

1. FDS input file: Switchgear_Room_Cabinet.fds 

2. CFAST input files: 

a. Initial Fire Only.in 

b. Cabinet Fire in Switchgear.in 

c. MCC Cable Tray Secondary Fire.o 

d. Thermal.csv 
C-1 

C 

LUBRICATING OIL FIRE IN PUMP COMPARTMENT 

C.1 Modeling Objective 

The purpose of the calculations described in this appendix is to predict the effects of a large fire 

in a small compartment. Specifically, the purpose of the calculation is to determine whether 

important safe-shutdown cables within the compartment will fail, and, if so, at what time failure 

occurs. These cables are protected by an electrical raceway fire barrier system (ERFBS), but 

there is a concern that the existing barrier system will not provide the required protection. 

C.2 Description of the Fire Scenario 

General Description: The compartment is built of fire-resistive construction and contains a 

Train A Emergency Core Cooling System pump and a cable tray containing safe-shutdown 

cables and protected by an ERFBS. The pump is surrounded by a dike to contain any lube oil 

that may leak or spill and has a maximum capacity of 190 L of lube oil. The compartment 

contains one smoke detector and one sprinkler. The fire occurs when pump oil leaks into the 

dike area and ignites. 

Geometry: The pump room comprises one rectangular room with a smaller rectangular entry 

area and door. Figure C-1 is a drawing of the pump compartment. 

Construction: As shown in Figure C-1, the walls are 0.1 m (0.328 ft). The floor and ceiling are 

0.9 m (3 ft) thick. The ASTM E-119 criteria for the temperature rise of the unexposed surface is 

121 °C (250 °F); this is to guard against ignition of combustibles on the non-fire side of the wall 

(NUREG-1805, Section 17.4.2). 

Materials: The walls, ceiling, and floor are all constructed of concrete. Nominal values for the 

thermal properties of various materials in the compartment are listed in Table 3-1 (NUREG1805, Table 2-3). 

Cables: The single cable tray in this compartment is filled with PVC-insulated, PE-jacketed 

cables. These cables have a diameter of approximately 1.5 cm (0.6 in), a jacket thickness of 

approximately 2 mm (0.079 in), and 7 conductors. See Figure C-1 for the location of the cable 

tray. Nominal values for the cable insulation thermal properties are as follows: the density is 

1380 kg/m3

, the thermal conductivity is 0.192 W/m/K, and the specific heat is 1.289 kJ/kg-K. 

The damage criterion is taken to be when the cable temperature reaches 200°C (392°F). These 

values are taken from NUREG-1805, Appendix A. 

ERFBS: This cable tray is protected by an ERFBS, which is two layers of 2.54 cm (1 in) thick, 

128 kg/m3

 Kaowool insulation blankets, covered by 1 mil foil. The density of this material is 128 

kg/m3

, the thermal conductivity is 0.06 W/m/K, the specific heat is 1.07 kJ/kg-K, and the 

emissivity is approximately 0.9. These values are taken from product literature. 

Fire Protection Systems: As shown in Figure C-1, a smoke detector and sprinkler are located 

in the pump room. However, to determine if the barrier system alone will provide the required 

protection, the fire detection and suppression systems are not credited in the fire scenario under 

consideration. 
Lubricating Oil Fire in Pump Compartment 

C-2 

Ventilation: There is one supply and one return register, each with an area of 0.5 m2 (5.4 ft3), 

providing a volume flow rate of 0.25 m3

/s. The locations are shown in Figure C-1. The 

ventilation system continues to operate during the fire with no changes brought about by firerelated pressure effects. This does not imply that the fire does not impact the ventilation 

system, but rather that there is typically limited information about the ventilation network that 

connects to a given compartment. The pump compartment has one door; it is 1.1 m (3.6 ft) 

wide and 2.1 m (6.9 ft) tall. The door is normally closed, but it is opened 10 min after ignition by 

the fire brigade. Before the door opens, leakage due to the doorway occurs via a 2.5 cm (1 in) 

gap under the door. 

Fire: The fire starts following an accidental release of lube oil. The spill is contained by the 

dike. Using the values for transformer oil from NUREG-1805, the density is 760 kg/m3

, the heat 

of combustion is 46,400 kJ/kg, and the infinite-area mass loss rate of the burning oil is 

0.039 kg/m2

/s. The empirical HRR reduction constant is 0.7 m-1, but it is not used for this 

scenario because the compartment heating is expected to enhance the burning rate. Lube oil is 

a mixture of hydrocarbons, mostly alkanes, which have a chemical formula of the form CnH2n+2

(with n ranging from 12 to 15). The radiative fraction of the fire’s HRR is taken to be 35%, a 

typical value for sooty fires (SFPE Handbook). 
Lubricating Oil Fire in Pump Compartment

C-3 

Figure C-1. Geometry of the Pump Room. 
Lubricating Oil Fire in Pump Compartment 

C-4 

C.3 Selection and Evaluation of Models 

This section describes the applicability of the models to this scenario. 

Algebraic Models: Neither FIVE nor the FDTs

 contain correlations to estimate the HGL 

temperatures within a flashed-over, underventilated compartment. Also, the point source 

radiation heat flux calculation included within FIVE and the FDTs

 cannot account for the 

attenuation of thermal radiation by the smoke that fills the compartment. Consequently, neither 

model is used for this scenario. 

Zone Models: This fire scenario is not a typical application of a zone model because it involves 

post-flashover conditions where the two layers essentially become one. Nevertheless, zone 

models can transition to this state when the HGL essentially descends all the way to the floor 

and the room becomes a well-stirred reactor. Conservation laws of mass and energy still apply 

within the single layer. In addition, the rules governing the heating of a target immersed in the 

HGL still apply, even when the HGL is the entire compartment. The zone model MAGIC has 

been selected for this application to demonstrate its use. There is no compelling advantage to 

either MAGIC or CFAST for this scenario. 

CFD Models: This fire scenario is a challenging application, even for a CFD model. It involves 

relatively high temperatures, underventilated conditions, and flashover. The primary advantage 

of a CFD model for this fire scenario is that CFD models typically include combustion algorithms 

that estimate near- and post-flashover conditions. 

Validation: This scenario falls outside the range of applicability of the NRC/EPRI V&V study 

documented in NUREG-1824 (EPRI 1011999) primarily because the equivalence ratio indicates 

that this is an underventilated fire whether the door to the compartment is open or closed (see 

Table C-1). The only experiment in NUREG-1824 (EPRI 1011999) that comes close to 

addressing the open-door phase of this scenario is Benchmark Exercise (BE) #4, a relatively 

large hydrocarbon fire within a relatively small compartment, with an Equivalence Ratio of 0.6. 

However, two experiments were performed by EDF at CNPP in 1997 and were compared to the 

predictions of the zone model MAGIC. One test featured a fully-developed 1,000 kg cable fire in 

a two-room configuration. The size and construction of the fire room was similar to the pump 

room. There was good agreement between recorded and predicted Hot Gas Layer 

temperatures which exceeded those typically associated with flashover condition, as well as 

oxygen depletion. Thermal fluxes to cable targets were also recorded, but these targets were 

not protected. Although the fire room had an open vent, oxygen deletion within the Hot Gas 

Layer suggests that natural ventilation was insufficient for the large HRR of the fire. These 

experiments and the MAGIC simulations are described in EdF HI-82/04/022/A. 

As part of the work performed at NIST for the investigation of the World Trade Center disaster, 

FDS has been validated against large-scale fire experiments. The experiments involved fairly 

large fires in a relatively small compartment, limited ventilation, a liquid fuel spray fire, and the 

measurement of the heat flux to and temperatures of insulated steel (similar to the cables 

protected by Kaowool blankets). These experiments and the FDS simulations are described in 

NIST NCSTAR 1-5F. 
Lubricating Oil Fire in Pump Compartment

C-5 

Table C-1. Normalized parameter calculations for the Pump Room fire scenario.

Quantity Normalized Parameter Calculation Validation Range In Range? 

Fire Froude 

כܳ Number

ሶ

ൌ

ܳ

ሶ

ܦ݃ଶඥܦஶܶ௣ܿஶߩ

ൌ

4980

1.2 ൈ 1.012 ൈ 293 ൈ 1.87ଶ ൈ √9.8 ൈ 1.87 ؆ 0.93 0.4 – 2.4 Yes 

Flame Length, L୤, 

relative to the 

Ceiling Height, H

௙ܮ

ܪ

ൌ

4.84.9 ؆ 0.99

ܮ ௙ൌ ܦ ቀ3.7 ܳכሶ ଶ/ହ െ 1.02ቁ ൌ 1.87 ሺ3.7 ൈ 0. 93଴.ସ െ 1.02ሻ ؆ 4.8

0.2 – 1.0 Yes 

Ceiling Jet Radial 

Distance,rcj, 

relative to the 

Ceiling Height, H

N/A 1.2 – 1.7 N/A 

Equivalence Ratio, 

φ, as an indicator 

of the Ventilation 

Rate 

߮ ൌ

݉ሶ F/݉ሶ Oమ

ݎ

ؠ

ܳ

ሶ

Oమ ሶ݉ ܪ∆ ݎ

ൌ

4980

13,100 ൈ 0.07 ؆ 5.5

݉ሶ Oమ ൌ 0.23 ߩஶܸ

ሶ

ൌ 0.23 ൈ 1.2 ൈ 0.25 ؆ 0.07

0.04 – 0.6 No 

Equivalence Ratio, 

φ, as an indicator 

of the Opening 

Ventilation 

߮ ൌ

݉ሶ F/݉ሶ Oమ

ݎ

ؠ

ܳ

ሶ

Oమ ሶ݉ ܪ∆ ݎ

ൌ

4980

13,100 ൈ 0.38 ؆ 0.99

݉ሶ Oమ ൌ 0.23 · 0.5ܣ௢ඥ݄௢ ൌ 0.23 ൈ 0.5 ൈ 2.31√2.1 ؆ 0.38

0.04 – 0.6 No 

Compartment 

Aspect Ratios 

ܮ

ܪ

ൌ

9.39

4.9 ؆ 1.9

ܹ

ܪ

ൌ

2.81

4.9 ؆ 0.6

0.6 – 5.7 Yes 

Target Distance, r, 

relative to the Fire 

Diameter, D

N/A 2.2 – 5.7 N/A 
Lubricating Oil Fire in Pump Compartment 

C-6 

C.4 Estimation of Fire-Generated Conditions 

This scenario was modeled using the zone model MAGIC and the CFD model FDS. 

C.4.1 Zone Model (MAGIC) 

The following paragraphs outline the data utilized to model the scenario using MAGIC. Figure 

C-2 provides an illustration of the scenario as rendered by MAGIC. 

Geometry: For modeling this scenario with MAGIC, the pump compartment was initially 

modeled as two compartments connected by a large opening (i.e., the geometry in Figure C-1 

was recreated in MAGIC). However, there were difficulties in running the simulation the full time 

with this configuration. Therefore, the two compartments were combined into a single 

compartment of the same total volume and surface area. This allows the volume in which the 

HGL develops, and the surface area through which energy is transferred from the compartment, 

to be maintained. Maintaining the total volume and surface area while leaving the ceiling height 

unchanged at 4.9 m (16 ft) yields an effective compartment size of 9.39 m (30.8 ft) by 2.81 m 

(9.2 ft). The modification to the geometry can be seen by comparing Figures C-1 and C-2. All 

other aspects of the geometry are relatively unchanged. 

Materials: All material properties are as specified above. 

Fire: The fire size is based on the surface area of the dike around the pump. For 

flammable/combustible liquid spills or pools, fires are typically based on surface area and a unitarea mass loss rate (see the pool fire methods in the SFPE Handbook chapter on Heat Release 

Rates for details). Although the dike can be thought of as four connected rectangles, the areas 

were reduced to a single equivalent area and the fire was modeled as a single circular area of 

equivalent diameter; this was found to be 1.87 m (6.1 ft). The fire immediately involves the 

entire surface area of the dike. Based on this area and the data in section C-2 above, an HRR 

of 4980 kW and a total burn time of approximately 22 minutes were calculated. The HRR is 

simply the mass loss rate multiplied by the heat of combustion, and the burn time is simply the 

total mass of the fuel divided by the mass loss rate). As noted previously, a radiant heat fraction 

of 35% was selected. A stoichiometric ratio of 3.48 and an average specific area of 319.2 m2

/kg 

were taken from the MAGIC database for kerosene. 

Ventilation: Mechanical ventilation is maintained constantly during the simulation, using the 

values provided above. MAGIC uses circular ducts, so the rectangular ducts seen in Figure C-1 

were changed to their equivalent circular area. As noted above, the door is normally closed, but 

it is opened 10 minutes after ignition by the arriving fire brigade. Before the door opens, 

leakage due to the doorway occurs via a 2.5-cm gap under the door. 
Lubricating Oil Fire in Pump Compartment

C-7 

Figure C-2. MAGIC View of the Pump Room 

C.4.2 CFD Model (FDS) 

The following paragraphs outline the data utilized to model the scenario using FDS. Figure C-3 

provides an illustration of the scenario as rendered by Smokeview. 

Geometry: The compartment is modeled as shown in Figure C-1, except the pump itself is 

modeled as two rectangular boxes. A single uniform, rectangular mesh spans the entire 

compartment, plus the hallway outside the door. It is important to capture the flow in and out of 

the compartment following the opening of the door. 

The numerical mesh employed consists of 0.2-m (0.7 ft) grid cells. A finer calculation with 0.1-m 

(0.3 ft) cells was performed with similar results. The latter calculation requires roughly a week 

of computing time on a single processor computer (2008 vintage), whereas the more coarsely 

gridded calculation requires about 10 hours. 

Materials: All material properties are as specified above. The protected cable tray is modeled 

as two layers, 5 cm (2 in) of Kaowool surrounding a 2.5 cm (1 in) thick “slab” consisting of 67% 

copper and 33% plastic (by mass). 

Fire: Due to the limited amount of validation data available for scenarios of this type and the 

considerable uncertainties involved, the approach taken is to specify, rather than attempt to 

predict, the burning rate of the fuel, even though the FDS model does provide the physical 
Lubricating Oil Fire in Pump Compartment 

C-8 

mechanisms to estimate burning rates. The fire is specified in the diked area surrounding the 

pump. Although FDS has a liquid fuel burning model, it is not used here because there is not 

enough information about the fuel, and, more importantly, it lacks the exact geometry of the 

pump and diked area. FDS would assume that the oil has formed a relatively deep pool with 

relatively little influence by the surrounding solids. This is not the case here. Instead, the 

specified burning rate, 0.039 kg/m2

/s, is applied directly in the model over an area of 2.75 m2

(29.6 ft2

) yielding a burning rate of 0.107 kg/s. The density of the oil is 0.76 kg/L, which means 

that the oil burns at a rate of 0.141 L/s. At this rate, 190 L will require 1,348 s to burn out. The 

vaporized fuel is a mixture of various hydrocarbons, but FDS uses only one fuel molecule in the 

combustion sub-model. For this calculation the fuel molecule is modeled as C14H30. 

Ventilation: The volume flow rates are applied as specified. 

Figure C-3. FDS/Smokeview rendering of the Pump Room scenario at the early stage of the 

fire, before the compartment becomes underventilated. 
Lubricating Oil Fire in Pump Compartment

C-9 

C.5 Evaluation of Results 

The primary purpose of the calculations is to assess whether critical cables within the pump 

room would be damaged in the event of a lube oil fire. In order to make this assessment, the 

gas temperatures and heat flux to the target tray, and the heating of the target cables under the 

protective Kaowool, need to be predicted. The results of the zone model MAGIC and the CFD 

model FDS are consistent, particularly the HRR. This is not surprising because the models use 

the same specified burning rate, the same fuel stoichiometry, and the same basic rules of gas 

phase flame extinction based on oxygen and temperature levels in the vicinity of the fire. The 

ERFBS is expected to protect the cables from reaching temperatures that would limit their 

functionality in the event of a fire of burning spilled lube oil. The following sections describe the 

results in greater detail. 

C.5.1 The Fire 

Although the burning rate of the lube oil spilled within a dike has been specified as input, it is 

clear from the results of the calculations that there would not be a sufficient amount of air (i.e., 

oxygen) within the compartment to sustain a large fire with the door closed for an extended 

period of time. The HRR curve predicted by the MAGIC and FDS models given the input heat 

release rate are shown in Figure C-4. The pronounced drop in the HRR immediately after the 

start of the fire and the subsequent low fire size lasting until the door opens at 10 minutes is 

evident in this figure. The sudden jump in the HRR predicted by FDS at 600 seconds is due to 

unburned fuel igniting as the door is opened. Note that none of the models has an algorithm 

capable of determining whether or not the fire would be sustained at this reduced burning rate 

until the door’s opening time. 

Figure C-4. Heat Release Rate Predicted by MAGIC and FDS for the Pump Room Fire 

Scenario. 

C.5.2 Hot Gas Layer Temperature 

MAGIC and FDS estimate the temperature of the Hot Gas Layer as a function of time, as shown 

in Figure C-5. As expected, the Hot Gas Layer temperature changes in accordance with the 

altered (oxygen-starved) heat release rate. Once the door opens at 600 seconds, the increased 

0

1000

2000

3000

4000

5000

6000

7000

8000

0 600 1200 1800 2400 3000 3600

HRR (kW)

Time (s)

Heat Release Rate

MAGIC

FDS
Lubricating Oil Fire in Pump Compartment 

C-10 

heat release causes the HGL temperature to rapidly increase until the fire dies out. After the fire 

burns out, the HGL temperature slowly drops as heat leaves the HGL through the bounding 

surfaces and open door. 

Figure C-5. Hot Gas Layer Temperature Predicted by MAGIC and FDS for the Pump Room 

Fire Scenario. 

C.5.3 Cable Temperature 

MAGIC and FDS have heat conduction algorithms to account for the multiple layers of insulation 

and cable materials. The surface temperature predictions of the cables protected by the 

ERFBS (Kaowool in this case) are shown in Figure C-6. MAGIC predicts a maximum cable 

surface temperature of about 55 °C (131 °F). FDS predicts a maximum cable surface 

temperature of about 40 °C (104 °F). These are both substantially below the 200°C (392 °F) 

damage threshold cited above. Note that although the HRR drops and then rises dramatically 

depending on ventilation, the cable temperature slowly rises. This is due to the thermal lag 

caused by the insulation (i.e., Kaowool). 

 

0

100

200

300

400

500

600

700

0 600 1200 1800 2400 3000 3600

Temperature (C)

Time (s)

HGL Temperature

MAGIC

FDS
Lubricating Oil Fire in Pump Compartment

C-11 

Figure C-6. Cable Surface Temperature Predicted by MAGIC and FDS for the Pump Room 

Fire Scenario. 

C.5.4 Uncertainty 

Chapter 4, Model Uncertainty, provides guidance on how to express the uncertainty of the 

MAGIC predictions. In the NRC/EPRI V&V study (NUREG-1824 (EPRI 1011989)), it was found 

that MAGIC predictions of target temperatures are, on average, 27% greater than 

corresponding measurements, and the relative standard deviation of its predictions about this 

average value is 19%. However, these values are for the surface temperature of an exposed 

target, not a protected (i.e., insulated) target. Since the conduction models (i.e., heat transfer 

equations) from the surface in are well known, the surface temperature uncertainties provide a 

reasonable approximation of the overall uncertainty of the protected target. This suggests that 

the true value of the protected cable temperature in this scenario can be approximated as being 

normally distributed with a mean of 46.2 °C and a standard deviation of 12.5 °C. Therefore, the 

probability that the protected cable temperature would exceed 200°C is: 

ܲሺܶ ൐ 200ሻ ൌ 1

2 erfc ൬

200 െ 46.2

12.5√2 ൰ ؆ 0 (C-1)

In other words, there is a near-zero chance of exceeding the temperature threshold for cable 

damage, according to the MAGIC prediction. The same type of calculation can be performed 

for FDS, with similar results (i.e., a near-zero likelihood of target failure). 

C.5.5 Sensitivity 

There can be considerable uncertainty in the heat release rates of real fires. As a result, it is 

prudent to consider the sensitivity of the results of simulations to the selected heat release 

rates. Table 4.2 indicates that both the Hot Gas Layer temperature and target surface 

temperature predictions are each related to the heat release rate by a two-thirds power 

dependence. 

0

10

20

30

40

50

60

70

80

90

100

0 600 1200 1800 2400 3000 3600

Temperature (C)

Time (s)

ERFBS-Protected Cable Surface Temperature

MAGIC

FDS
Lubricating Oil Fire in Pump Compartment 

C-12 

Equation 16 in Chapter 4 is a simple formula that can be used to estimate the relative change in 

the model Hot Gas Layer temperature and target surface temperature output quantity, ∆ܶ/ሺܶ െ

ܶ଴ሻ, due to the relative change in the model heat release rate input parameter, ∆ܳሶ

/ܳሶ: 

∆ܶ

ܶെܶ଴

ൎ 2

3

∆ܳሶ

ܳሶ (C-2) 

The predicted cable surface temperature is only 46.2 °C (115 °F), far less than the 200 °C 

(392 °F) damage temperature. Based on this equation, a six-fold increase in the heat release 

rate of the fire would be required to cause the cable temperature to increase to the damage 

temperature. 

C.6 Conclusion 

Based on the calculations above, the ERFBS is expected to protect the cables from reaching 

temperatures that would limit their functionality in the event of a fire involving burning spilled 

lube oil. This conclusion is based on the predictions of the zone model MAGIC and the CFD 

model FDS, while accounting for the uncertainty in the temperature predictions of the models 

and the sensitivity of the predictions to variations in the heat release rate. 

C.7 References 

1. NUREG-1805. Fire Dynamics Tools.

2. NUREG/CR-6850 (EPRI 1011989), Fire PRA Methodology for Nuclear Power Facilities. 

3. NUREG-1824 (EPRI 1011999), Verification and Validation of Selected Fire Models for 

Nuclear Power Plant Applications, 2007. 

4. SFPE Handbook of Fire Protection Engineering, 4th edition, 2008. 

5. ASTM E 119, “Standard Test Method for Fire Tests of Building Construction and Materials.” 

6. UL 217, Underwriters Laboratories, Inc., Single Station Fire Alarm Device. 

7. NIST SP 1086, CFAST – Consolidated Model of Fire Growth and Smoke Transport (Version 

6), Software Development and Model Evaluation Guide.

8. NIST SP 1018-5, Fire Dynamics Simulator (Version 5), Technical Reference Guide, Vol. 3, 

Experimental Validation. 

9. NIST NCSTAR 1-5F, Federal Building and Fire Safety Investigation of the World Trade 

Center Disaster: Computer Simulation o the Fires in the World Trade Center Towers, 2005. 

10. Gay, L., C. Epiard, and B. Gautier, “MAGIC Software Version 4.1.1: Mathematical Model,” 

EdF HI82/04/024/B, Electricité de France, France, November 2005. 

11. Gay, L., Frezabeu, J., “Qualification File of Fire Code MAGIC version 4.1.1” EdF HI82/04/022/A, Electricité de France, France, December 2004. 

C.8 Attachments 

1. FDS input file: Pump_Room.fds 

2. MAGIC input file: Pump_Room.cas 
D-1 

D 

MOTOR CONTROL CENTER FIRE IN SWITCHGEAR 

ROOM 

D.1 Modeling Objective 

The calculations described in this example estimate the effects of a fire in a Motor Control 

Cabinet (MCC) in a Switchgear Room on nearby cable and cabinet targets. The purpose of the 

calculation is to determine whether these targets will fail, and, if so, at what time failure occurs. 

D.2 Description of the Fire Scenario 

General Description: The Switchgear Room is located in the reactor building. The 

compartment contains multiple motor control centers and some other switchgear cabinets. 

Geometry: The layout of the compartment is shown in Figure D-1. Figure D-2 shows the 

equipment typically contained in the compartment, and Figure D-3 shows the significant 

elevation change between the “high” and “low” ceilings. 

Materials: Property values for the relevant materials are listed in Table 3-1. The cabinet 

housing is 1.5 mm thick steel. 

Cables: The cable trays are filled with cross-linked polyethylene (XPE or XLPE) insulated 

cables with a Neoprene jacket. These cables have a diameter of approximately 1.5 cm (0.6 in), 

a jacket thickness of approximately 2 mm (0.79 in), 7 conductors, and a mass per unit length of 

0.4 kg/m. Tray locations are shown in the compartment drawing. XLPE cables fail when the 

internal temperature just underneath the jacket reaches approximately 400°C (750 °F) 

(NUREG/CR-6931, Vol. 2, Table 5.10) or the exposure heat flux exceeds 11 kW/m2

 (NUREG1805, Appendix A). Damage criteria for the adjacent cabinets are equivalent to that for the 

cable trays because the cables within the cabinet are subjected to a similar thermal exposure as 

the steel cabinet housing. 

Fire: A fire starts within a motor control center cabinet. The cabinet is closed and contains 

more than one bundle of qualified cable. The fire grows following a “t-squared” curve to a 

maximum value of 702 kW in 12 min and remains steady for 8 additional minutes, consistent 

with NUREG/CR-6850 (EPRI 1011989), Appendix G, for a cabinet with more than one cable 

bundle of qualified cable. After 20 min, the HRR decays linearly to zero in 19 min. A peak fire 

intensity of 702 kW represents the 98th percentile of the probability distribution for HRR in 

cabinets of this general description. 

The top of the cabinet contains a louvered air vent, 0.6 m (2 ft) wide and 0.3 m (1 ft) long. The 

cabinet is 2.4 m (8 ft) tall. The fire burns within the interior of the cabinet, and the smoke, heat, 

and possibly flames exhaust from the air vent at the top of the cabinet. 

Ventilation: The compartment is normally supplied with three air changes per hour. The 

supply and return vents are indicated on the drawing. The two doors are normally closed. 

Normal HVAC operations continue during the fire, and the doors remain closed. The volume of 
Motor Control Center Fire in Switchgear Room 

D-2 

the compartment is 882 m3 (31,150 ft3), meaning that three air changes per hour requires a 

volume flow rate of 0.735 m3

/s. 

Figure D-1. Geometry of the MCC/Switchgear Room. 
Motor Control Center Fire in Switchgear Room

D-3 

Figure D-2. Typical electrical cabinet in the lower part of the Switchgear Room. 

Figure D-3. View of the high ceiling space. 
Motor Control Center Fire in Switchgear Room 

D-4 

D.3 Selection and Evaluation of Fire Models 

The fire scenario described above is challenging primarily because it involves a single large 

compartment with two very different ceiling heights, and the empirical and zone models are 

based on the assumption that the compartment is fairly uniform in height. 

Algebraic Models: The correlations used in the FDTs

 and FIVE to estimate HGL temperature 

are based on compartment fire experiments with relatively uniform ceiling height. However, 

these calculation methods can be used to estimate the flame height and the radiation heat flux 

to various targets. For this scenario, the FDTs

 are selected, but FIVE would be appropriate as 

well for these calculations. 

Zone Models: This scenario is challenging for a zone model because of the non-uniform 

ceiling height. Typically, the geometry is modeled as two connected compartments. 

Alternatively, CFAST can model the space as a single compartment with a variable crosssectional area to account for the extra volume of the high-ceiling space. For this reason, 

CFAST is used in the analysis. 

CFD Models: This scenario is a fairly typical application of a CFD fire model. The fact that 

there are two ceiling heights is not an issue, as the compartment geometry is input as is, with no 

need for further assumptions. In fact, it is very convenient in a case like this to use two 

rectangular meshes instead of one. Not only does it conform nicely to the actual geometry, but 

it also enables the calculation to be run in parallel on two processors instead of one. Figure D-5 

is an FDS/Smokeview depiction of the scenario.

Validation: The principal source of validation data justifying the use of the above-listed fire 

models for this scenario is the NRC/EPRI V&V study documented in NUREG-1824 (EPRI 

1011999). NIST has expanded the NRC/EPRI V&V to include the latest versions of CFAST 

(6.1.1) (Peacock, 2008) and FDS (5.5.3) (McGrattan, 2010). Table D-1 lists various important 

model parameters and the ranges for which the validation study is applicable. All but one 

parameter, the Fire Froude Number, fall within the ranges. This parameter is essentially a 

measure of the fire’s heat output relative to its base area. In this example, the fire is assumed 

to “sit” atop the cabinet with the vent opening serving as its “base.” This assumption leads to a 

higher value of ܳሶ

כ than would be calculated if it were not assumed that the fire burns completely 

outside of the cabinet. Thus, the high value of ܳሶ

כ is the result of an assumption that will lead to 

more severe fire conditions than would be expected if the fire were assumed to burn partially 

within the cabinet 

The second important issue in regard to model validation is the two-tiered ceiling. None of the 

experiments used in the NRC/EPRI validation study have a similar ceiling configuration. For 

this reason, the algebraic models are limited only to “open” fire predictions, such as flame height 

and radiation heat flux, for which the compartment geometry is irrelevant. CFAST is to be used 

in a way that was not validated in NUREG-1824 (EPRI 1011999), but still conforms with the 

basic physical assumptions of the model. A CFD model makes no particular assumptions 

based on ceiling geometry; in fact, the set of experiments used in the NRC/EPRI study referred 

to as Benchmark Exercise #2 provides validation data to evaluate the models’ ability to estimate 

the plume and HGL temperature/depth of smoke and hot gases filling a fairly large, open hall 

with an angled roof. 
Motor Control Center Fire in Switchgear Room

D-5 

Table D-1. Normalized parameter calculations for the MCC fire scenario. 

Quantity Normalized Parameter Calculation Validation Range In Range? 

Fire Froude 

כܳ Number

ሶ

ൌ

ܳ

ሶ

ܦ݃ଶඥܦஶܶ௣ܿஶߩ

ൌ

702

1.2 ൈ 1.012 ൈ 293 ൈ 0.5ଶ ൈ √9.8 ൈ 0.5 ؆ 3.6 0.4 – 2.4 No 

Flame Length, L୤, 

relative to the 

Ceiling Height, H

௙ܮ

ܪ

ൌ

2.65.2 ൌ 0.5

ܮ ௙ൌ ܦ ቀ3.7 ܳכሶ ଶ/ହ െ 1.02ቁ ൌ 0.5 ሺ3.7 ൈ 3.6଴.ସ െ 1.02ሻ ؆ 2.6

0.2 – 1.0 Yes 

Ceiling Jet Radial 

Distance,rcj, 

relative to the 

Ceiling Height, H

N/A – There are no targets like sprinklers or smoke detectors under 

consideration in this example. 1.2 – 1.7 N/A 

Equivalence Ratio, 

φ, as an indicator 

of the Ventilation 

Rate 

߮ ൌ

݉ሶ F/݉ሶ Oమ

ݎ

ؠ

ܳ

ሶ

Oమ ሶ݉ ܪ∆ ݎ

ൌ

702

13,100 ൈ 0.2 ؆ 0.27

݉ሶ Oమ ൌ 0.23 ߩஶܸ

ሶ

ൌ 0.23 ൈ 1.2 ൈ 0.735 ؆ 0.2 kg/s

0.04 – 0.6 Yes 

Compartment 

Aspect Ratio 

(Lower | Upper) 

ܮ

ܪ

ൌ

8.53.0 ؆ 2.8

ܹ

ܪ

ൌ

8.53.0 ؆ 2.8

ܮ

ܪ

ൌ

8.69.1 ؆ 0.9

ܹ

ܪ

ൌ

8.59.1 ؆ 0.9

0.6 – 5.7 Yes 

Target Distance, r, 

relative to the Fire 

Diameter, D

ݎ

ܦ

ൌ

1.40.5 ؆ 2.8 2.2 – 5.7 Yes 
Motor Control Center Fire in Switchgear Room 

D-6 

D.4 Estimation of Fire-Generated Conditions 

This section describes how each of the models is used in the analysis, including specific 

assumptions unique to the particular model. 

D.4.1 Algebraic Models (FDTs) 

Fire: The FDTs use a steady-state HRR in both the flame height and radiation heat flux 

calculation. A constant HRR of 702 kW is used for both. A fire diameter is calculated from the 

vent area atop the cabinet, 0.5 m (1.6 ft). The Heskestad correlation yields a flame height of 

2.7 m (8.9 ft). The cables just above the cabinet would be engulfed in flame and fail. 

The point source radiation model predicts the heat flux to the cabinet an estimated 1.4 m (4.6 ft) 

from the fire. The result indicates a peak heat flux of 9.8 kW/m2

. Note that this estimate does 

not include the contribution from the HGL, and that the FDTs do not include a means to estimate 

the temperature of the cabinet. 

D.4.2 Zone Models (CFAST) 

Geometry: Zone fire models subdivide the space of interest into one or more compartments 

connected by vents. With CFAST, the single, large compartment is modeled as two smaller 

compartments stacked one atop the other, connected by a horizontal vent. The reason for this 

is that the fire is located completely underneath the ceiling of the lower compartment. The 

smoke plume does not rise directly into the upper compartment; rather, the smoke pours from 

beneath the lower ceiling like smoke flowing into a horizontal vent. Figure D-4 shows the 

geometry of the CFAST calculation. Note that two additional dummy compartments have been 

included in the calculation, not connected to any other compartment in the simulation, to visually 

represent the MCC cabinets within the Switchgear Room. These are included for visualization 

purposes only and have no impact on the calculation. 

Fire: Following guidance in NUREG/CR-6850 (EPRI 1011989), the fire is placed near the top of 

the cabinet. It is positioned directly below the exposed cable tray to maximize exposure of the 

cable for the simulation. The specified fire area and HRR are input directly into the model. 

Cables: One of the objectives of the calculation is to estimate the potential damage to the 

cables within three trays. CFAST uses the Thermally-Induced Electrical Failure (THIEF) 

methodology developed as part of the CAROLFIRE program (NUREG/CR-6931, Vol. 3). Each 

of the three target cables is specified directly in the model. Electrical functionality is lost when 

the temperature just inside of the 2 mm (0.08 in) jacket reaches 400 °C (752 °F). 

Ventilation: The two compartments used to model the space are connected by a single large 

vent. Although the largeness of this vent relative to the compartment size is not typical of a 

zone model application, the simple two-compartment geometry of the space and the more 

dominant mechanical ventilation flow from one side of the Switchgear Room to the other should 

minimize any uncertainty in the calculation resulting from the large connecting vent. Mechanical 

ventilation is included at the specified height and with the specified volume flow applied to the 

single supply (in the low-ceiling space) and return (in the high-ceiling space). Additionally, since 

zone fire models assume that compartments are completely sealed unless otherwise specified, 

a typical leakage vent, 25 mm (1 in) in height, is included at the bottom of each closed doorway 

to reflect the fact that the doorways are not totally airtight. 
Motor Control Center Fire in Switchgear Room

D-7 

Figure D-4. Geometry of two-height ceiling Switchgear Room as modeled in CFAST. 

D.4.3 CFD Model (FDS) 

Geometry: The entire compartment is included in the computational domain. To avoid 

including a large portion of area outside the compartment, two separate meshes are used, one 

for the low-ceiling section and one for the high-ceiling section. The FDS User’s Guide contains 

detailed instructions for running the simulation on multiple computers. The concrete walls are 

essentially the boundaries of these two meshes. The electrical cabinets and cables are 

included in the simulation as simple rectangular solids, and their dimensions have been 

approximated to the nearest 15 cm (5.9 in). There is no attempt to model the details of either 

the cable trays or cabinets because the grid resolution is not fine enough. This is an 

appropriate assumption because the cables and cabinets are merely “targets” for which it is 

sufficient to know their bulk thermal properties. An FDS/Smokeview rendering of the scenario is 

shown in Figure D-5. 

The numerical mesh consists of uniform grid cells, roughly 15 cm (5.9 in) on a side. This is a 

relatively coarse mesh for a scenario of this type, but finer meshes do not produce significantly 

different results in this case. It should be noted, however, that there is considerable uncertainty 

in the exact nature of the fire relative to the cabinet and the cables just above. This uncertainty 

mainly has to do with the assumption that the fire originates directly atop the cabinet rather than 

deep within. With a model like FDS, it is possible to compare the results of different fire 

configurations, but it is not done here for the sake of brevity. 

Fire: The fire burns over an area of 0.6 m (2 ft) by 0.3 m (1 ft) on top of the cabinet with a 

maximum HRR per unit area of 3,900 kW/m2

, yielding a total HRR of 702 kW. 
Motor Control Center Fire in Switchgear Room 

D-8 

Cables: FDS is limited to only 1-D heat transfer into either a rectangular or cylindrical 

obstruction. In this simulation, the cables are modeled as 1.5 cm (0.6 in) cylinders with uniform 

thermal properties. Following the Thermally-Induced Electrical Failure (THIEF) methodology in 

NUREG/CR-6931, Vol. 3, electrical functionality is lost when the temperature just inside of the 

2 mm (0.08 in) jacket reaches 400 °C (752 °F). Note that no attempt is made in the simulation 

to predict ignition and spread of the fire over the cables, which is why the in-depth heat 

penetration calculation is focused on a single cable. At least one cable per tray is relatively free 

of its neighbors and would heat up more rapidly than those buried deeper within the pile. 

Ventilation: Three air changes per hour are achieved with a volume flow of 0.735 m3

/s applied 

to the single supply and return vents. No other penetrations are included in the model. 

Figure D-5. FDS/Smokeview representation of the MCC/Switchgear Room scenario. 
Motor Control Center Fire in Switchgear Room

D-9 

D.5 Evaluation of Results 

The purpose of the calculations described above is to predict if and when various components 

within the compartment become damaged due to a fire in the MCC. XPE cables are expected 

to be damaged when their internal temperature surpasses 400 °C (750 °F) or the exposing heat 

flux surpasses 11 kW/m2

. Damage criteria for the adjacent cabinet are equivalent to that for the 

cables because the cables within the cabinet come in contact with the heated metal housing 

and, therefore, are exposed to similar thermal conditions. The targets of interest are three cable 

trays, labeled A, B and C, and a single electrical cabinet adjacent to the burning MCC. The 

following sections describe the results in detail. 

D.5.1 Damage to Cabinet 

The cabinet adjacent to the MCC is located approximately 1.4 m (4.5 ft) from the center of the 

fire. The point source radiation calculation included in the FDTs

 predicts a heat flux of 

9.8 kW/m2

. However, this is expected to be an overprediction because there is no direct line of 

sight between the cabinet and the fire. In other words, the adjacent cabinet does not “see” the 

entire fire. The point source radiation model used by the FDTs

 was also shown to overestimate 

radiation heat flux by roughly a factor of two in the NRC/EPRI V&V study, NUREG-1824 (EPRI 

1011999). 

CFAST and FDS estimate the peak cabinet temperature to be approximately 160 °C (320 °F), 

with peak sustained heat fluxes in the range of 4 kW/m2

 to 6 kW/m2. These predictions of heat 

flux and temperature are considerably lower than the damage criteria. The predicted heat flux 

to and temperatures of the exposed cabinets are shown in Figure D-6. 

Figure D-6. Heat flux and temperature predictions for the adjacent cabinet. 

D.5.2 Cable Damage Based on Temperature 

The predicted heat flux to and temperatures of the cables in the three trays are shown in Figure 

D-7. CFAST and FDS estimate cable temperatures using the THIEF methodology 

(NUREG/CR-6931, Vol. 3). Both models predict that the cables in Tray A are likely to fail, but 

FDS predicts a failure time of approximately 8 minutes, while CFAST predicts 12 minutes. 

Neither model predicts that the cables in Tray B will reach the failure temperature of 400 °C 

0

2

4

6

8

10

12

0 600 1200 1800 2400 3000 3600

Heat Flux (kW/m2)

Time (s)

Cabinet Heat Flux

CFAST

FDS

FDTs

0

40

80

120

160

200

0 600 1200 1800 2400 3000 3600

Temperature (C)

Time (s)

Cabinet Temperature

CFAST

FDS
Motor Control Center Fire in Switchgear Room 

D-10 

(750 °F), but both predict that these cables could reach temperatures in the neighborhood of 

200 °C (392 °F). Note that these predictions are sensitive to the exact location of the target 

cable within the tray and its “view” of the fire. In this case, the cables in tray B are heated 

primarily by convection and radiation of the HGL. 

The predicted cable temperatures of the cables in tray C by both FDS and CFAST indicate that 

they are unlikely to fail. 

D.5.3 Cable Damage Based on Incident Heat Flux 

The cable damage predictions discussed above require information about the thermal properties 

of the cables themselves. However, the cables in any given tray within a plant may have a 

range of sizes and thermal properties, making it impractical to estimate the temperature within 

each and every one. For this reason, an alternative predictor for cable damage is simply the 

incident heat flux to the cable surface, which does not require more detailed information about 

the cables themselves. In this scenario, the damage threshold has been defined to be when the 

heat flux exceeds 11 kW/m2

 at some point during the fire. 

 
Motor Control Center Fire in Switchgear Room

D-11 

Figure D-7. Summary of cable results for the MCC/Switchgear Room. 

 

0

10

20

30

40

50

0 600 1200 1800 2400 3000 3600

Heat Flux (kW/m2)

Time (s)

Cable A Heat Flux

CFAST

FDS

0

200

400

600

800

0 600 1200 1800 2400 3000 3600

Temperature (C)

Time (s)

Cable A Temperature

CFAST

FDS

0

2

4

6

8

10

0 600 1200 1800 2400 3000 3600

Heat Flux (kW/m2)

Time (s)

Cable B Heat Flux

CFAST

FDS

0

100

200

300

400

0 600 1200 1800 2400 3000 3600

Temperature (C)

Time (s)

Cable B Temperature

CFAST

FDS

0.0

0.5

1.0

1.5

2.0

2.5

0 600 1200 1800 2400 3000 3600

Heat Flux (kW/m2)

Time (s)

Cable C Heat Flux

CFAST

FDS

0

20

40

60

80

100

0 600 1200 1800 2400 3000 3600

Temperature (C)

Time (s)

Cable C Temperature

CFAST

FDS
Motor Control Center Fire in Switchgear Room 

D-12 

D.5.4 Uncertainty 

Chapter 4, Model Uncertainty, provides guidance on how to express the uncertainty of the 

model predictions. For example, consider tray B, where CFAST predicts a peak heat flux of 

approximately 6 kW/m2

. This value is less than the damage criterion of 11 kW/m2, but in the 

NRC/EPRI V&V study (NUREG-1824 (EPRI 1011989)), it was found that CFAST predictions of 

total heat flux are, on average, 19 % less than corresponding measurements, and the relative 

standard deviation of its predictions about this average value is 47 %. This suggests that the 

true value of the heat flux to the cable in this scenario is normally distributed with a mean of 

6/0.81=7.4 kW/m2

 and a standard deviation of 0.47×7.4=3.5 kW/m2. Therefore, the probability 

that the actual heat flux to the cable would exceed 11 kW/m2

 is: 

ܲሺݍሶᇱᇱ ൐ 11ሻ ൌ 1

2 erfc ൬

11 െ 7.4

3.5√2 ൰ ؆ 0.151 (D-1)

In other words, there is a 15% chance of exceeding the heat flux damage criterion for cable 

tray B, according to the CFAST prediction. 

Table D-2 lists the model uncertainty of the temperature and heat flux predictions for CFAST 

and FDS. For tray A, the probabilities that the heat flux and temperature would surpass the 

critical value are close to 1, meaning that there is a high level of confidence that a fire would 

cause these cables to fail. For tray B, the probability of surpassing the critical heat flux value is 

much higher for the CFAST prediction than for that of FDS, even though both models estimate 

the same heat flux. This is because the validation data indicates that there is more uncertainty 

in the CFAST prediction of heat flux than FDS. 

D.5.5 Sensitivity 

Referring again to Table D-2, it is clear that the cables in tray A would most likely be damaged 

by a fire in the MCC. However, there is a chance that the cables in tray B could be damaged as 

well. In addition to examining the accuracy of the models, as is done in the previous section, it 

is also possible to consider the key input parameter and estimate the increased HRR necessary 

to damage the cables in tray B. Table 4-3 indicates that the heat flux is proportional to the HRR 

to the 4/3 power. Following the methodology in Section 4.4.1, in order to increase the predicted 

heat flux by 5 kW/m2

 to reach 11 kW/m2, the peak HRR,ܳሶ, must increase by approximately: 

∆ܳሶ ൎ 3

4ܳሶ

ሶݍ∆

ᇱᇱ

ሶᇱᇱݍ

ሶ ൌ 3

4 702

5

6 ൎ 438 kW (D-2) 

In other words, the peak HRR of the fire would have to be approximately 702+438=1140 kW to 

cause the cables in tray B to fail. 
Motor Control Center Fire in Switchgear Room

D-13 

Table D-2. Uncertainty analysis of the model predictions of the MCR scenario. 

Model Quantity Target Predicted 

Value 

Critical 

Value 

Probability 

of Exceeding 

CFAST Heat Flux Cabinet 4.4 kW/m2 11 kW/m2 0.015 

CFAST Heat Flux Cable A 26 kW/m2 11 kW/m2 0.919 

CFAST Heat Flux Cable B 6 kW/m2 11 kW/m2 0.151 

CFAST Heat Flux Cable C 0.75 kW/m2 11 kW/m2 0.000 

FDS Heat Flux Cabinet 6 kW/m2 11 kW/m2 0.006 

FDS Heat Flux Cable A 35 kW/m2 11 kW/m2 0.999 

FDS Heat Flux Cable B 6 kW/m2 11 kW/m2 0.006 

FDS Heat Flux Cable C 1.5 kW/m2 11 kW/m2 0.000 

CFAST Temperature Cabinet 160 °C 400 °C 0.000 

CFAST Temperature Cable A 550 °C 400 °C 0.852 

CFAST Temperature Cable B 220 °C 400 °C 0.000 

CFAST Temperature Cable C 55 °C 400 °C 0.000 

FDS Temperature Cabinet 160 °C 400 °C 0.000 

FDS Temperature Cable A 550 °C 400 °C 0.980 

FDS Temperature Cable B 165 °C 400 °C 0.000 

FDS Temperature Cable C 60 °C 400 °C 0.000 

D.6 Conclusion 

The purpose of the calculations described above is to predict if and when various components 

within the compartment become damaged due to a fire in the MCC. The fire model analyses 

performed for this scenario indicate that the fire would damage the cables in tray A because all 

the models (FDTs

, CFAST, FDS) predict that the flames would directly impinge on the cables 

themselves. 

 CFAST and FDS predict that the cables in tray B are unlikely to be damaged based on the 

heat flux criterion. However, both models predict that the cables could reach temperatures 

as high as 200 °C (392 °F), a temperature that could damage thermoplastic cables. 

 Neither FDS nor CFAST predicts that the cables in tray C would be damaged. 

 None of the analyses indicate that the adjacent cabinet housing would be exposed to a heat 

flux that would cause damage. 

D.7 References 

1. NUREG/CR-6850 (EPRI 1011989), Fire PRA Methodology for Nuclear Power Facilities, 

2005.

2. NUREG-1805, Fire Dynamics Tools, 2004.
Motor Control Center Fire in Switchgear Room 

D-14 

3. NUREG-1824 (EPRI 1011989), Verification and Validation of Selected Fire Models for 

Nuclear Power Plant Applications, 2007.

4. NUREG/CR-6931, Cable Response to Live Fire (CAROLFIRE), Volume 2: Cable Fire 

Response Data for Fire Model Improvement, 2007. 

5. NUREG/CR-6931, Cable Response to Live Fire (CAROLFIRE), Volume 3: ThermallyInduced Electrical Failure (THIEF) Model, 2007.

6. NIST SP 1086, CFAST – Consolidated Model of Fire Growth and Smoke Transport 

(Version 6), Software Development and Model Evaluation Guide.

7. NIST SP 1019, Fire Dynamics Simulator User’s Guide. 

8. NIST SP 1018, Fire Dynamics Simulator, Technical Reference Guide, Vol. 3, Experimental 

Validation. 

9. SFPE Handbook of Fire Protection Engineering, 4th edition, 2008. 

D.8 Attachments 

1. FDS input file: Switchgear_Room_MCC.fds 

2. CFAST input files: 

a. MCC in Switchgear.in 

b. MCC 702 kW.o 

c. thermal.csv 
E-1 

E 

TRANSIENT FIRE IN CABLE SPREADING ROOM 

E.1 Modeling Objective 

The calculations in this appendix estimate the impact on safe-shutdown cables due to a fire in a 

trash bin inside a Cable Spreading Room (CSR). These calculations are part of a larger fire 

analysis described in Chapter 11 of NUREG/CR-6850 (EPRI 1011989), Volume 2, “Detailed 

Fire Modeling (Task 11).” The CSR contains a large quantity of redundant instrumentation and 

control cables needed for plant operation. Transient combustibles have been identified as a 

possible source of fire that may impact the cables. The purpose of the calculation is to analyze 

this condition and determine whether the cable targets will fail, and, if so, at what time failure 

occurs. The time to smoke detector activation is also estimated. The calculation will provide 

information for a decision on the hazard and risk for this scenario. 

E.2 Description of the Fire Scenario 

General Description: The CSR contains a large quantity of redundant instrumentation and 

control cables needed for plant operation. The cables are installed in either ladder-back trays or 

conduits. 

Geometry: Figure E-1 illustrates the geometry of the CSR, and Figure E-2 shows a photograph 

of the CSR. In addition to cables, the CSR contains a fully enclosed computer compartment, 

ductwork, and large structural beams. There is no high- or medium-voltage equipment 

(switchgears or transformers) in the compartment. As indicated in Figure E-3, the top 2 m 

(6.6 ft) of the compartment is filled with cable trays containing cables, or ductwork, or large 

structural beams. 

Construction: The walls, floor, and ceiling of the CSR are constructed of normal-weight 

concrete. 

Materials: Nominal values for the thermal properties of various materials in the compartment 

have been taken from NUREG-1805 (Table 2-3) and are listed in Table 3-1. The important 

cables for this calculation are located in the third and sixth trays above the fire source, which are 

filled with PE-insulated, PVC-jacketed control cables important to safe shutdown. These cables 

have a diameter of approximately 1.5 cm (0.6 in), a jacket thickness of approximately 1.5 mm 

(0.06 in), and 7 AWG 12 conductors. These cables are damaged when the internal cable 

temperature reaches 205 °C (400 °F) or the exposure heat flux reaches 6 kW/m2

 (NUREG1805, Appendix A). 

The lowest cable tray contains cross-linked polyethylene (XLPE) cables. Although not important 

to safe shutdown of the plant, the cables in the lowest tray may ignite and provide an additional 

fire source to the trays above. For this reason, the bottom cable tray is protected on the lower 

surface by a solid metal barrier. The cables in the tray have a diameter of approximately 1.5 cm 

(0.6 in), a jacket thickness of approximately 1.5 mm (0.06 in), and 7 AWG 12 conductors. 

These cables are damaged when the temperature reaches 330°C (625°F) or the exposure heat 

flux reaches 11 kW/m2

 (NUREG-1805, Appendix A). 
Transient Fire in Cable Spreading Room 

E-2 

The bottom and side surfaces of all cable trays in the CSR are of solid metal construction; top 

surfaces are open. 

Detection System: Smoke detectors are located on the ceiling at locations shown in Figure 

E-1. The detectors are UL-listed with a nominal sensitivity of 4.9%/m. 

Suppression System: An automatic CO2 system is initiated by cross-zone smoke detection in 

the compartment or operated manually. A CO2 discharge causes fire dampers to close and 

mechanical ventilation fans to stop to maintain a proper concentration of suppression agents. 

Activation of the CO2 system is not modeled in this example. 

Ventilation: The CSR has two doors on the east wall that are normally closed. Each door is 

2 m (6.6 ft) wide by 2 m (6.6 ft) tall, with a 1 cm (0.4 in) gap along the floor. Standard procedure 

calls for an operator to investigate the fire within 600 s (10 min) of an alarm condition. For this 

reason, one of the doors is opened for this investigation. 

There are two supply and two return vents for mechanical ventilation, each with an area of 

0.25 m2

 (2.7 ft2). The total air supply rate is 1.4 m3/s. All vents are 2.4 m (8 ft) above the floor. 

Upon smoke detector activation, the mechanical ventilation fans stop and the dampers close. 

Fire: A trash fire ignites within a cylindrical steel waste bin 0.8 m (2.6 ft) high and 0.6 m (2.0 ft) 

in diameter, containing 5 kg of trash. The HRR of the transient fire is estimated using 

NUREG/CR-4680. The heat of combustion of the trash is 20 kJ/g (SFPE Handbook; based on 

an average for various items that could be encountered in a trash can). The fire grows following 

a “t-squared” curve to a maximum value of 317 kW (the 98th percentile value from Table G-1 in 

NUREG/CR-6850 (EPRI 1011989)) in 480 s (consistent with NUREG/CR-6850 (EPRI 1011989) 

Supplement 1 for a transient fire growth rate contained within a trash can). The fire burns at its 

maximum value until the trash is consumed. The radiative fraction16 of the fire is taken to be 

35%, consistent with typical sooty fires. The soot yield of the fire is taken to be 1.5%, typical for 

wood and other cellulosic materials (Tewarson chapter, SFPE Handbook).

 

16 The fraction of the fire’s total energy emitted as thermal radiation. 
Transient Fire in Cable Spreading Room

E-3 

Figure E-1. Geometry of Cable Spreading Room
Transient Fire in Cable Spreading Room 

E-4 

Figure E-2. Photograph of typical Cable Spreading Room 

Figure E-3. Geometric detail of the Cable Spreading Room. 
Transient Fire in Cable Spreading Room

E-5 

E.3 Selection and Evaluation of Fire Models 

The fire scenario described above is a typical application of both zone models and CFD models. 

With a single fire contained within a rectangular compartment, the application is straightforward. 

Following is a discussion of further strengths and weaknesses of the available models. 

Algebraic Models: FIVE and the FDTs

 both contain correlations to estimate the HGL 

temperatures within a closed, ventilated compartment; however, the FDTs

 do not allow the HRR 

to be input as a function of time. Since using the maximum HRR as a constant value will 

produce the highest HGL temperatures, these tools could be appropriate for screening 

scenarios. If necessary, additional analyses with a zone or CFD model may be appropriate. 

Both algebraic models contain calculations to estimate smoke detector activation time. 

FIVE and the FDTs

 also contain methods to estimate the heat flux from a fire to a target. The 

FIVE analysis uses Alpert’s plume temperature correlations and Heskestad’s flame height 

correlation, whereas the FDTs analysis uses only those of Heskestad to estimate the 

temperature to which the cables are exposed. Neither analysis included the effects of blockage 

due to the trays, nor the effect of thermal radiation from the Hot Gas Layer on the targets; thus, 

it is possible that the use of either of these models could lead to an underprediction of the heat 

flux. 

Zone Models: The fire scenario outlined in the previous section falls within the range of 

applicability for a zone model. The simple compartment geometry of this scenario lends itself 

well to the application of zone models. Both CFAST and MAGIC include algorithms to estimate 

the temperature of cable targets. 

In CFAST, target temperatures are calculated based on a one-dimensional heat transfer 

calculation that includes radiation from the fire, upper and lower gas layers, and bounding 

surfaces; convection from nearby gases; and conduction into the target. Radiation from the fire 

is modeled using a point source radiation calculation from the fire to the target. 

In MAGIC, cable target temperatures are also calculated based on a one-dimensional heat 

transfer calculation that includes radiation exchanges between compartment surfaces, the upper 

and lower gas layers, and the nearby compartment fires; and convective heat transfer that 

involves targets heating up in the HGL, fire plume, and ceiling jet sub-layers. Each cable is 

divided into 20 cm (8 in.)-long segments, and the maximum surface temperature calculated on 

all the segments is the criterion to cable ignition (once the ignition temperature is reached, the 

reported surface temperature remains constant). Thus, the relative location of the cables to the 

flame, plume, ceiling jet or layers will affect the temperature calculation and the time to failure. 

The relative position of the cabinet fire and cable trays may provide a challenge because the 

algorithms used by the zone models to assess target damage are based on a fire radiation point 

source. 

For this analysis, the zone model CFAST is used. 

CFD Models: This scenario is a fairly typical application of FDS. The model is applied here in 

much the same way that the zone models approach it, with the fire within the waste bin. The 

primary advantage of a CFD model for this fire scenario is that the CFD model can estimate 
Transient Fire in Cable Spreading Room 

E-6 

conditions at the specific location of the target cables, taking into account surrounding cable 

trays which may block radiation from the fire source. For this analysis, FDS results are included 

as a comparison to the zone model calculations. 

Validation: NUREG-1824 (EPRI 1011999) contains experimental validation results for CFAST 

and FDS that are appropriate for this scenario. These experiments include ventilation effects 

and heat fluxes to and temperatures of various targets, particularly cables. Fire sizes in these 

experiments bound those used in this scenario. For CFAST, the Software Development and 

Model Evaluation Guide, NIST SP 1086 includes updated validation results for the newest 

version of the model used for this calculation. This includes all of the validation comparisons 

from NUREG-1824 (EPRI 1011999), plus additional comparisons for experiments not included 

in the NRC guide. Plume temperature calculations have been validated for a broad range of fire 

sizes and distances above the fire source in NIST SP 1086. 

Table 2-5 of Volume 1 of NUREG-1824 (EPRI 1011999) lists various important model 

parameters and the ranges for which the validation study is applicable. Table E-1 below lists 

the values of these parameters for this fire scenario, along with their ranges of applicability. 

Of these parameters, only the compartment aspect ratio is outside the range of tests included in 

NUREG 1824 (EPRI 1011999). In this scenario, the compartment width to height ratio is well 

within limits, but the length to height ratio is higher than those included in NUREG 1824 (EPRI 

1011999). For a zone model, this “longer than typical” compartment is mainly a concern early in 

the fire development before a reasonably uniform layer has formed. Thus, prediction of events 

that occur early in the fire (such as smoke detection) may be expected to have a higher 

uncertainty if they are located distant from the fire source than those that occur later in the fire 

(such as ignition of cables above the initiating fire source) once the fire is more fully developed. 

For this scenario, smoke detectors are included throughout the compartment, but the primary 

ones of concern are those which would naturally respond faster, i.e., those nearest the fire. 

.
Transient Fire in Cable Spreading Room

E-7 

Table E-1. Key parameters and their ranges of applicability to NUREG-1824. 

Quantity Normalized Parameter Calculation Validation Range In Range? 

Fire Froude Number ܳכ

ሶ

ൌ

ܳ

ሶ

ܦ݃ଶඥܦஶܶ௣ܿஶߩ

ൌ

130

1.2 ൈ 1.012 ൈ 293 ൈ 0.82ଶ ൈ √9.8 ൈ 0.82 ൌ 0.5 0.4 – 2.4 Yes 

Flame Length, Lf, 

relative to the Ceiling 

Height, H

௙ܮ

ܪ

ൌ

2.64.0 ൌ 0.7 0.2 – 1.0 Yes 

Ceiling Jet Radial 

Distance,rcj, relative 

to the Ceiling Height, 

H

N/A – Ceiling jet targets are not included in simulation. 1.2 – 1.7 N/A 

Equivalence Ratio, φ, 

as an indicator of the 

Ventilation Rate 

߮ ൌ

݉ሶ F/݉ሶ Oమ

ݎ

ؠ

ܳ

ሶ

Oమ ሶ݉ ܪ∆ ݎ

ൌ

317

13,100 ൈ 0.4 ൌ 0.06

݉ሶ Oమ ൌ 0.23 ߩஶܸ

ሶ

ൌ 0.23 ൈ 1.2 ൈ 1.42 ൌ 0.4

0.04 – 0.6 Yes 

Compartment Aspect 

Ratio 

ܮ

ܪ

ൌ

40

4.0 ൌ 10

ܹ

ܪ

ൌ

18.5

4.0 ൌ 4.6

0.6 – 5.7 No 

Target Distance, r, 

relative to the Fire 

Diameter, D

ݎ

ܦ

ൌ

2.3

0.82 ൌ 2.8 2.2 – 5.7 Yes 
Transient Fire in Cable Spreading Room 

E-8 

E.4 Estimation of Fire-Generated Conditions 

This section provides details specific to each model. 

E.4.1 Zone Model (CFAST) 

General: In CFAST, the cable spreading room is modeled as a single compartment with 

obstructions accounted for by modifying the cross-sectional area of the compartment as a 

function of height, as described in the geometry section below. Figure E-4 shows the scenario 

as modeled by CFAST. 

Figure E-4. CFAST rendering of the Cable Spreading Room scenario. 

Geometry: Since zone models are concerned with volumes and not physical length and width, 

the volume of the computer compartment, as well as the numerous cable trays, ductwork, and 

beams, was modeled in CFAST with a cross-sectional area that varies with height. Table E-2 

shows the cross-sectional area as a function of height calculated from the compartment 

geometry shown in Figure E-1. 

Table E-2. Cross-sectional area as a function of height used for CFAST calculation 

Height 

(m) 

Area 

(m2) 

Floor Level 0 700.04 

Bottom of Cable Trays 1.8 571.44 

Bottom of Obstructions 2.2 411.44 

HVAC Ductwork 2.4 410.44 

Top of Obstructions 2.8 570.44 

Top of Cable Trays 3.2 699.04 

Ceiling Level Obstructions 3.6 267.04 

Ceiling Level 4 267.04 
Transient Fire in Cable Spreading Room

E-9 

Fire: The specified fire was input directly into CFAST. To determine the duration of the fire, the 

total energy of the fuel is calculated: (5 kg)×(20,000 kJ/kg) = 100,000 kJ. Conversely, the total 

heat release can be determined by integrating the HRR curve over time as: 

  480 2 3

0 480

1 317 480 317 480

3

f t

Q t dt dt f       t   (E-1)

where 2   317 480 for a t-squared fire that grows to 317 kW in 480 s, as specified in the 

scenario definition. Solving for tf yields a total burning time of 635 s. The combustibles are 

estimated to fill about half the volume of the waste bin (roughly consistent with the test data in 

Appendix G of NUREG-6850 (EPRI 1011989)). 

Materials: The material properties listed above were used for the zone models.

Cables: In CFAST, target temperatures are calculated based on a one-dimensional cylindrical 

heat transfer calculation based on the material properties and cable diameter, as specified in 

the scenario description. To account for the shielding of the cables on the lower surface of the 

cable tray, the CFAST input for the normal vector from the cable surface is directed upwards. 

This effectively shields the cables from the fire below while exposing them to the surrounding 

gas temperature for convection and to the hot upper gas layer for radiation. 

Ventilation: The supply and return air flow rates are input directly into CFAST. Upon smoke 

detector activation, mechanical ventilation fans stop and dampers are closed. Therefore, before 

a stop time for the fans could be specified, the time to smoke detector activation was needed. 

This requires that CFAST be run with the fans on for the entire time to find the first smoke 

detector activation. The model is then re-run using the smoke detector activation time as the 

fan-stop time. 

Fire Detection: Although there are multiple smoke detectors in the space, it was assumed that 

the closest detector is the only one that needs to be modeled to determine time to detection. 

The basis for this assumption is that the nearest detector will be exposed to the greatest 

concentration of smoke products and the highest gas temperatures leading to the earliest 

response. There are no geometric or ventilation features that would prevent this from being the 

case in the example consider. In CFAST, there is no direct way of calculating smoke density for 

smoke detector activation; instead the smoke detector is modeled as a sprinkler with a low 

activation temperature and RTI. An activation temperature of 30 o

C (86 oF) and an RTI of 

5 (m/s)1/2 were used for this scenario. 

E.4.2 CFD Model (FDS) 

General: This scenario is notable because it includes a considerable amount of “clutter,” that 

is, the space has a relatively large number of obstructions. Figure E-5 illustrates the FDS 

simulation with all the blockages. Because the cable trays are regularly spaced in both the 

horizontal and vertical directions, it is easy in FDS to simply replicate a single tray as many 

times as necessary. Another interesting feature of the scenario is the automatic shutdown of 

the ventilation system at the time of any smoke detector activation. FDS models this by 

associating the creation or removal of obstructions or the activation/deactivation of a vent with 

actions taken by any number of fire protection devices. 
Transient Fire in Cable Spreading Room 

E-10 

Figure E-5. FDS/Smokeview rendering of the Cable Spreading Room scenario. 

Geometry: The interior of the compartment is modeled, and all obstructions have been 

included. To get increased resolution in the area of interest, multiple meshes are used. The 

finest mesh has a 10 cm (4 in) resolution and spans a volume surrounding the trash can, which 

is 6 m (20 ft) long, 3 m wide (10 ft), and 4 m (13 ft) high. Coarse meshes cover the remainder of 

the compartment and adjacent hallway with cells of 20 cm (8 in). Because the objective of the 

calculation is to estimate time to failure for cables within stacked trays, it is important to have at 

least 10 cm (4 in) resolution, the typical dimension of the rails of conventional cable trays. 

Fire: The trash can is modeled with a square, rather than round, cross-section with an 

equivalent area to the round cross-section and a height equal to the height of the trash can. 

The local flow features about the fire are not a significant aspect capable of affecting the 

outcome of this example calculation; thus the transformed square geometry is appropriate for 

this application. The specified HRR is applied to the top of trash can. The duration of the fire is 

635 s, as was computed for the zone model input. There is no need to model the interior of the 

can. 

Materials: The thermal properties of the walls are applied directly as specified. 

Cables: The primary objective of the calculation is to estimate the potential damage to the 

cables within the trays. FDS is limited to only 1-D heat transfer into either a rectangular or 

cylindrical obstruction. In this simulation, the cables are modeled as 1.5 cm (0.6 in) cylinders 

with uniform thermal properties, given above. Following the Thermally-Induced Electrical 

Failure (THIEF) methodology in NUREG/CR-6931, Vol. 3, electrical functionality is lost when the 

temperature just inside the jacket of a thermoplastic cable reaches 205°C (400°F). Note that no 

attempt is made in the simulation to estimate ignition and spread of the fire over the cables. 

The THIEF methodology does not account for the effects of bundled cables, which may reduce 

the overall heat-up of a single cable. 

Detection: FDS has a smoke detection algorithm that predicts the smoke obscuration within 

the detection chamber based on the smoke concentration and air velocity in the grid cell in 

which the detector is located. The detector itself is not modeled, as it is merely a point within 

the computational domain. The two parameters needed for the model are the obscuration at 

alarm, which is given by the manufacturer, and an empirically determined length scale from 

which a smoke entry time lag is estimated from the outside air velocity. The SFPE Handbook, 

4th Edition, provides a nominal value of 1.8 m (5.9 ft) for this length scale. The obscuration at 

alarm is 4.9%/m, a typical sensitivity for smoke detectors. 
Transient Fire in Cable Spreading Room

E-11 

Ventilation: The supply and return air flow rates are input directly into FDS. The ducts are 

represented by rectangular obstructions with thin plates just below (one grid cell) the vent itself 

to represent the diffusing effect of the grill. The resolution of the grid is not fine enough to 

capture this effect directly. FDS is capable of stopping the ventilation system upon the 

activation of any smoke detector. 

E.5 Evaluation of Results 

The purpose of the calculations described above is to estimate smoke detector activation times 

and potential cable damage from a trash can fire in the Cable Spreading Room. The 

compartment itself is relatively large, and the relatively small fire (317 kW) does not substantially 

heat it up. Figure E-6 shows the heat release rate and estimated HGL temperature. Differences 

between the two models likely result from FDS’s ability to locally account for all the blockages in 

the room. HGL temperature in CFAST is a spatially average value intended to represent the 

bulk conditions throughout the compartment, while the FDS values are a calculation based on a 

single vertical profile of temperature at a fixed location within the room (in this scenario placed 

several meters away from the fire location to eliminate local effects of the fire plume on the 

temperature profile). 

Figure E-6. Heat release rate and estimated HGL temperature for Cable Spreading Room scenario 

The analysis below shows that a 317 kW waste bin fire beneath a vertical array of cable trays is 

unlikely to damage cables in the trays three and six levels above the fire. Both CFAST and FDS 

estimate peak temperatures well below 100 °C (212 °F) for cables in the third tray from the 

bottom. Estimated temperatures on the lowest cable tray peak at 125 °C (257 °F), still well 

below the ignition temperature of the cables. This is discussed in more detail below. 

Because of the uncertainty in the smoke detector activation prediction of all the models and the 

uncertainty associated with the possible ignition of cables in the trays just above the fire, it is 

difficult to predict whether or not the CO2 suppression system would be activated in time to 

prevent possible cable ignition. No validation results are available that address time to detector 

activation. Thus, the analysis makes the conservative assumption that the suppression system 

does not activate. 

0

100

200

300

400

0 600 1200 1800 2400 3000 3600

HRR (kW)

Time (s)

Heat Release Rate

CFAST

FDS

10

20

30

40

50

0 600 1200 1800 2400 3000 3600

Temperature (C)

Time (s)

HGL Temperature

CFAST

FDS
Transient Fire in Cable Spreading Room 

E-12 

E.5.1 Smoke Detection 

Table E-3 shows the results for smoke detection activation for the models. CFAST models 

smoke detector actuation as a heat detector with a relatively low thermal inertia and activation 

temperature. However, there is no consensus in the fire literature for the appropriate RTI 

(Response Time Index) value and activation temperature. Given the presence of beam pockets 

and obstructions, even a CFD model like FDS, which uses actual smoke concentration rather 

than temperature in its detector algorithm, is subject to significant uncertainty. 

Table E-3. Smoke detector activation times, Cable Spreading Room. 

Model Time (s) 

CFAST 170 s 

FDS 120 s 

E.5.2 Cable Damage 

Figure E-7 shows the estimated impact of the fire on the cable trays above the fire. The bottom 

cable is located at least 1 m (3.3 ft) above the base of the waste bin fire. With an estimated 

flame height of 1.7 m (5.7 ft), ignition may occur from flame impingement; however, since the 

bottom tray is protected by a solid metal lower surface and the heat flux to the bottom cable tray 

is estimated to be about 4.1 kW/m2

 (well below the critical value of 11 kW/m2), this is unlikely. 

E.5.3 Uncertainty 

In this scenario, the objective of the calculations is to predict the impact of a waste bin fire on 

safe-shutdown cables located in cable trays directly above the fire by comparing calculated 

values of temperature and heat flux near the cables with critical values. In addition, calculations 

of smoke detector activation and flame height of the fire are also estimated. While it is 

estimated that none of the predicted values exceed established critical values, the uncertainty of 

the model calculations needs to be examined to better understand how close the predictions are 

to critical values. 

For example, in the NRC/EPRI V&V study (NUREG-1824 (EPRI 1011999)), it was found that 

predictions of target heat flux are, on average, 18% lower for CFAST than corresponding 

measurements, and the relative standard deviation of its predictions of this average value is 

47%. This suggests that the true value of the peak cable heat flux in this scenario is normally 

distributed with a mean of 5.1 kW/m2

 and a standard deviation of 2.4 kW/m2. Therefore, the 

probability that the cable temperature would exceed 11 kW/m2

 is: 

ܲሺܳ ൐ 11ሻ ൌ 1

2 erfc ൬

11 െ 5.1

2.4√2 ൰ ؆ 0.008 (E-2)

In other words, there is a less than 1% chance of exceeding the flux threshold for the lowest 

cable tray according to the CFAST prediction. The FDS predictions estimate temperatures even 

lower than CFAST. 

For the upper cables, the predicted temperature and heat flux by CFAST are somewhat higher 

than FDS because CFAST does not account for the fact that the cable trays of interest are 

shielded by trays below or that the burning spreads outward from the ignition point. In any 
Transient Fire in Cable Spreading Room

E-13 

event, neither model predicts that the upper cables will come anywhere close to the damage 

criteria. 

 
Transient Fire in Cable Spreading Room 

E-14 

Figure E-7. Estimated cable conditions for the Cable Spreading Room. 

 

0.0

0.5

1.0

1.5

2.0

0 600 1200 1800 2400 3000 3600

Heat Flux (kW)

Time (s)

Cable B Heat Flux

CFAST

FDS

0

1

2

3

4

5

0 600 1200 1800 2400 3000 3600

Heat Flux (kW)

Time (s)

Cable A Heat Flux

CFAST

FDS

0

20

40

60

80

100

0 600 1200 1800 2400 3000 3600

Temperature (C)

Time (s)

Cable B Temperature

CFAST

FDS

0

20

40

60

80

100

0 600 1200 1800 2400 3000 3600

Temperature (C)

Time (s)

Cable A Temperature

CFAST

FDS

0.0

0.2

0.4

0.6

0.8

1.0

1.2

1.4

1.6

1.8

2.0

0 600 1200 1800 2400 3000 3600

Flame Height (m)

Time (s)

Flame Height

CFAST

0

20

40

60

80

100

120

140

0 600 1200 1800 2400 3000 3600

Temperature (C)

Time (s)

Bottom CableTemperature

CFAST

FDS
Transient Fire in Cable Spreading Room

E-15 

It should also be noted that these damage criteria are intended to indicate electrical failure, but 

are routinely assumed to also apply as ignition criteria. In newer studies in NUREG/CR-7010, 

cable ignition was not observed at fluxes below 25 kW/m2

, and most often only with direct flame 

impingement. Handbook values for minimum ignition flux for power and communication cables 

are reported in the range of 15 kW/m2

 to 35 kW/m2 (SFPE Handbook, Table 3-4.2). 

Table E-4 lists the probability of exceeding the critical temperature and heat flux for all the 

model calculations. 

Table E-4. Uncertainty analysis of the model predictions of the CSR scenario 

Quantity Location Model Predicted 

Value 

Critical 

Value 

Probability of 

Exceeding 

Temperature 

Bottom 

Cable 

CFAST 125 °C 330 °C 0.000 

FDS 45 °C 330 °C 0.000 

Cable A CFAST 92 °C 330 °C 0.000 

FDS 35 °C 330 °C 0.000 

Cable B CFAST 62 °C 330 °C 0.000 

FDS 53 °C 330 °C 0.000 

Heat Flux 

Bottom 

Cable 

CFAST 4.17 kW/m2

 11 kW/m2 0.008 

FDS -- 11 kW/m2 

Cable A CFAST 2.97 kW/m2

 11 kW/m2 0.000 

FDS 0.33 kW/m2 11 kW/m2 0.000 

Cable B CFAST 1.98 kW/m2

 11 kW/m2 0.000 

FDS 0.90 kW/m2 11 kW/m2 0.000 

E.5.4 Sensitivity 

Referring again to Table E-4, it is clear that the cables directly above the waste bin fire would 

not be damaged by a 317 kW fire. In addition to examining the accuracy of the models as is 

done in the previous section, it is also possible to estimate how large a fire would be required to 

damage the cables. Table 4-3 indicates that the heat flux is proportional to the HRR to the 4/3 

power. Following the methodology in Section 4.4.1, in order to increase the predicted heat flux 

by 6 kW/m2

 to reach 11 kW/m2, the peak HRR, ܳሶ, must increase by approximately: 

∆ܳሶ ൎ 3

4ܳሶ

ሶݍ∆

ᇱᇱ

ሶᇱᇱݍ

ሶ ൌ 3

4 317

6

5 ൎ 285 kW (E-3) 

In other words, the peak HRR of the fire would have to be approximately 317+285=602 kW to 

cause the cables in the bottom cable tray B to fail. 

E.6 Conclusion 

The analysis shows that a 330 kW waste bin fire beneath a vertical array of cable trays is 

unlikely to damage cables in the trays three and six levels above the fire. Both CFAST and FDS 

estimate peak temperatures well below 100 °C (212 °F) for cables in the third tray from the 

bottom. Estimated temperatures on the lowest cable tray peak at 125 °C (257 °F), still well 

below the ignition temperature of the cables. 
Transient Fire in Cable Spreading Room 

E-16 

E.7 References 

1. NUREG-1805, Fire Dynamics Tools.

2. NUREG/CR-6850 (EPRI 1011989), Fire PRA Methodology for Nuclear Power Facilities. 

3. NUREG-1824 (EPRI 1011999), Verification and Validation of Selected Fire Models for 

Nuclear Power Plant Applications, 2007. 

4. SFPE Handbook of Fire Protection Engineering, 4th edition, 2008. 

5. NUREG/CR-4680, Heat and Mass Release Rate for Some Transient Fuel Source Fires: A 

Test Report

6. NUREG/CR-6931, Cable Response to Live Fire (CAROLFIRE) Volume 3: ThermallyInduced Electrical Failure (THIEF) Model. 

7. UL 217, Underwriters Laboratories, Inc., Single Station Fire Alarm Device. 

8. SFPE Engineering Guide to the Evaluation of the Computer Model DETACT-QS 

9. NIST SP 1086, Consolidated Model of Fire Growth and Smoke Transport, CFAST (Version 

6), Software Development and Model Evaluation Guide 

10. NIST SP 1018-5, Fire Dynamics Simulator (Version 5), Technical Reference Guide, Vol. 3, 

Experimental Validation. 

11. Gay, L., C. Epiard, and B. Gautier, “MAGIC Software Version 4.1.1: Mathematical Model,” 

EdF HI82/04/024/B, Electricité de France, France, November 2005. 

E.8 Attachments 

1. FDS input files: Cable_Spreading_Room.fds 

2. CFAST input files: 

a. Trash Fire In Cable Spreading Room.in 

b. Transient Combustibles.o 

c. Trash Fire.o 

d. Thermal.csv 
F-1 

F 

LUBRICATING OIL FIRE IN A TURBINE BUILDING 

F.1 Modeling Objective 

The calculations described in this appendix estimate the effects of a large lubricating oil fire in a 

Turbine Building on unprotected structural steel. This type of analysis may arise when 

addressing ASME/ANS RA-Sa-2009 supporting requirement FSS-F01 in a Fire Probabilistic 

Risk Assessment (FPRA), which requires the consideration of fire scenarios that expose 

structural steel. The typical scenario considered for this requirement is a catastrophic failure of 

the turbine itself, which would result in a large lubricating oil spill fire. The purpose of this 

hypothetical example is to evaluate the Turbine Building structural steel response for two 

potential curb locations in the Turbine Building. The calculation will provide information for a 

decision on the hazard posed to the structural steel for each potential fire location, thus serving 

as part of the basis for a plant modification. 

F.2 Description of the Fire Scenario 

General Description: The Turbine Building is a large structure that is approximately 100.3 m 

(329 ft) by 99.5 m (326 ft) by 21 m (69 ft) tall, as shown in Figure F-1. The ambient temperature 

in the Turbine Building is 36 °C (95 °F), which is the same temperature as the surrounding 

external areas. The Turbine Building often contains multiple levels; however, for this example 

the structure will be evaluated using two primary levels, the lower levels (collectively) and the 

main turbine deck. The lowest portion of the lower level floor is about 1.2 m (4 ft) below grade 

in the area near the fire, but most of the lower level floor elevation is at the 0 m (0 ft) elevation. 

The ceiling height is about 4.6 m (15 ft) above grade. The floor of the turbine deck is at the 

5.6 m (18 ft) elevation, and the ceiling is at the 19.8 m elevation. The turbine deck has a 

somewhat smaller plan than the lower level, approximately 90 m (295 ft) by 70 m (230 ft). The 

building contains the turbine generators (See Figure F-1) and a Heating, Ventilation, and Air 

Conditioning (HVAC) room. Each turbine generator contains about 3,000 L (800 gal) in a single 

reservoir volume. The lubricant oil is dominated by alkanes, which have a chemical formula of 

CnH2n+2 with n ranging from twelve to fifteen (centered about fourteen) and a soot yield of 0.1 kg 

soot/kg fuel consumed. The proposed curbed area is 6.1 m (20 ft) by 4.6 m (15 ft). Based on 

the current use of the area, the plant has identified two locations on the lower level where the 

curbing could be installed. The position of Curb Location 1 is as shown in Figure F-1. The 

south edge of Curb Location 2 is 26 m (85.3 ft) north of the south wall, and the east edge of 

Curb Location 2 is 21.1 m (69.2 ft) east of the west Turbine Building wall. The curbed areas will 

be designed to contain the entire lubricant volume from a turbine generator, or 3,000 L of 

lubricant. 

There are forty unprotected steel support columns in a rectangular configuration (four rows of 

ten each) around the lube oil tank. Figure F-3 shows a typical unprotected steel column. The 

columns are all W14ۭ145 standard wide flange members, as shown in Detail A of Figure F-1 

(American Institute of Steel Construction [AISC], 2006). Six columns in particular are evaluated 

in detail and are denoted in Figure F-1 as A, B, C, D, E, and F. A plant structural analysis has 

revealed that the loss of any of these six columns could lead to partial collapse of the Turbine 

Building, which is considered an unacceptable consequence by the plant. 
Lubricating Oil Fire in a Turbine Building 

F-2 

Figure F-1. Geometry of the Turbine Building. 

Curb Location 1 

Curb Location 2 

Plant

north

Plant

north
Lubricating Oil Fire in a Turbine Building

F-3 

Figure F-2. Structural Steel Column in the Turbine Building.

Figure F-3. Main Turbine Lubricating Oil Tanks in the Turbine Building. 
Lubricating Oil Fire in a Turbine Building 

F-4 

Geometry: A plan and side view of the Turbine Building are shown in Figure F-1. The area of 

interest involves the two levels shown in Figure F-1, which are separated by a concrete slab. 

There are several stairwell, hatch, and exhaust vent penetrations throughout the slab. These 

penetrations are identified in Figure F-1 with the “H” symbol for a hatch and the “S” symbol for a 

stairwell. 

Construction: The turbine deck is made of 1 m (3.3 ft) thick normal weight concrete having a 

density of 2,400 kg/m 3). The floor and walls of the lower level are constructed of 0.3 m (1 ft) 

thick normal weight concrete. Numerous areas and landings in the Turbine Building are made 

of metal grating. The floor in the area of the lube oil tank is 1 m thick normal weight concrete. 

The walls and ceiling of the upper level of the Turbine Building are made of 3 mm (0.12 in) thick 

corrugated steel. The structural columns, steel grating, and corrugated steel are fabricated from 

steel containing 0.5 percent carbon. 

Materials: Nominal values for the thermal properties of the normal weight concrete and steel 

are listed in Table F-1 (NUREG-1805, Table 2-3). The damage criteria for the structural steel 

are based on the acceptance criteria for an ASTM E119 (ASTM E119-10a, 2010) test and are 

listed in Table F-2. 

Table F-1. Material Properties of Concrete and Steel in the Turbine Building 

Material Thermal Conductivity, 

k (W/m-K) Density,  (kg/m3) Specific Heat, cp(kJ/kg-K) 

Normal weight 

concrete 1.6 2,400 0.75 

Steel (0.5% carbon) 54 7,850 0.465 

Table F-2. Structural Steel Failure Criteria (ASTM E119-10a) 

Member Maximum Cross-Section 

Temperature (°C) 

Maximum Cross-Section 

Average Temperature 

(°C) 

Beam 704 593 

Column 649 538 

Detection System: There is no safety-related equipment in this Turbine Building, and, as such, 

there are no detection systems or sprinklers in the Turbine Building that are credited for this 

analysis. If Turbine Building underdeck sprinklers were installed, such features may be ignored 

when considering the potential for worst-case structural failure and the possible need for 

passive structural fire protection. In addition, demonstrating the suppression effectiveness for 

large hydrocarbon spill fires would be a significant aspect of the evaluation, but is not treated 

analytically with the fire modeling tools considered in this guide. 

Ventilation: The Turbine Building is an open area configuration with all forced ventilation 

intentionally shut down at the start of the fire for reasons unrelated to the fire. There are 
Lubricating Oil Fire in a Turbine Building

F-5 

eighteen exhaust vents to the outside around the perimeter of the turbine deck level. There are 

no other internal or external openings beyond than those already noted and shown in Figure 

F-1. 

Fire: A large, confined lubricant spill fire involving 3,000 L is postulated on the lower level. The 

lubricant has been preheated prior to the spill such that the growth rate of the fire would be short 

compared to the total time required to burn the spill volume. The total spill area is equal to 27.9 

m2 (300 ft2), as shown in Figure F-1, and the spill depth is thus 0.1 m (0.33 ft). 

The key fuel properties for the lubricant oil are summarized in Table F-3 (NUREG-1805, Tables 

3-2 and 3-4). The properties listed in NUREG-1805 actually correspond to transformer oil, but it 

is asserted in Table 2-6 of NUREG-1805 (2005) that the fuels are similar, and it is reasonable to 

use the fuel properties for transformer oil when dealing with lubricant oil. 

Table F-3. Lubricant Fuel Properties (NUREG 1805, 2005) 

Density,  (kg/m3 ) Heat of combustion, 

ΔHc (kJ/kg) 

Burning rate, 

݉"ሶ (kg/s-m2) 

Empirical constant, 

kβ (m-1) 

760 46,400 0.039 0.7 

The peak heat release rate is computed from the plan area, the heat of combustion, and the 

burning rate: 

ܳሶ

௣ ൌ ݉"ሶ  HୡA (F–1)

which results in a peak heat release rate of 50.3 MW. The fire duration is determined using the 

volume, density, and burning rate: 

t ൌ ܯ

݉ሶ "ܣ ൌ V

ܣ" ሶ݉

(F–2)

which results in a fire duration of about 35 minutes. 

Initial and Ambient Conditions: The ambient temperature both inside and outside the Turbine 

Building is 36 °C (95 °F), as noted in the General Description. The corresponding ambient 

density is density is 1.2 kg/m3 and the corresponding ambient air heat capacity is 1.0 kJ/kg-K, 

per Table B.2 in the SFPE Fire Protection Handbook (2008). 

F.3 Selection and Evaluation of Fire Models 

Following is a discussion of further strengths and weaknesses of the available models. 

Algebraic Models: FIVE (EPRI 1002981, 2002) and the FDTs

 (NUREG 1805, 2005) both 

contain correlations for estimating the Hot Gas Layer temperatures within a closed, ventilated 

compartment, the heat flux at fixed distance from the exposure fire, and the flame height, all of 
Lubricating Oil Fire in a Turbine Building 

F-6 

which play a role to some extent in this scenario. FDTs also contains algebraic models for 

predicting the fire resistance of unprotected structural steel; however, the exposure profile is 

limited to the ASTM E119 Standard Time-Temperature curve and is thus not applicable to this 

scenario. 

A simple calculation of the flame height using FDTs

 spreadsheet 

03_HRR_Flame_Height_Burning_Duration_Calculations.xls 

indicates that the predicted flame height is about 11.7 m (38 ft), which is significantly greater 

than the maximum ceiling height of 5.8 m (19 ft) in the area of the fuel spill. This suggests that 

the radiant heat flux models (point source and solid flame) would not be representative of the 

actual exposure conditions. The heat flux predictions using these models could be in significant 

error and consequently are not recommended for this application. 

The geometry is also not readily modeled using the empirical Hot Gas Layer model because of 

the large number of horizontal vents and the large volume and boundary surface area. These 

models are thus not recommended for this configuration. 

Zone Models: This is a particularly challenging simulation for a zone fire model, with very large 

compartments and numerous connections between the compartments and to the outside. With 

such large compartment sizes, local variations in temperatures can be expected within the lower 

compartment that contains the fire source. In addition, because the flame height is predicted to 

be greater than the ceiling height, the radiant heat flux calculations may not be representative of 

the conditions that would arise from the postulated fire. Results of calculations that depend on 

the uniform gas layer assumption inherent in all zone fire models should be evaluated with care. 

In CFAST, target temperatures are calculated based on a one-dimensional heat transfer 

calculation that includes radiation from the fire, upper and lower gas layers, and bounding 

surfaces; convection from nearby gases; and conduction into the target. Radiation from the fire 

is calculated using a point source radiation calculation from the fire to the target. 

For this analysis, the zone model CFAST is used (NIST SP 1086, 2009). 

CFD Models: This scenario is challenging because it involves a very large fire in a very large 

space; however, the fact that the objective of the calculation is to estimate the temperature 

increase of steel columns that are not located within the fire itself makes it less subject to error. 

Predicting the heat flux to a column engulfed in fire is more difficult because it requires details of 

the fuel and exhaust products, including soot, within the flame region. 

For this analysis, the CFD model FDS is used (NIST SP 1018-5, 2010). 

Validation: The principal source of validation data justifying the use of the above-listed fire 

models for this scenario is the NRC/EPRI V&V study documented in NUREG-1824 (EPRI 

1011999). Table 2 in Volume 1 of NUREG-1824 (EPRI 1011999) and Section 2 of this guide 

lists the various important model parameters and the ranges for which the validation study is 

applicable. Table F-4 provides a summary of the normalized parameter calculations for the 

Turbine Building fire scenario. In some cases, the one- and two-compartment representations 

yield different values, and are shown accordingly in Table F-4. Additionally, the normalized 

target distance to fire diameter is provided for each of the six columns. 
Lubricating Oil Fire in a Turbine Building

F-7 

The calculation of the equivalence ratio is not straightforward with the equations provided 

because of the vertical flow paths. The value listed in Table F-4 was determined from the single 

compartment geometry in which the horizontal vents are represented as vertical vents of equal 

area; as such, this value is only indicative. Nonetheless, it falls well within the validation range, 

and it is expected that there is adequate ventilation available, such that the equivalence ratio will 

be less than one.
Lubricating Oil Fire in a Turbine Building 

F-8 

Table F-4. Normalized Parameter Calculations for the Turbine Building Fire Scenario.

Quantity Normalized Parameter Calculation Validation Range In Range? 

Fire Froude 

כܳ Number

ሶ

ൌ

ܳ

ሶ

ܦ݃ଶඥܦஶܶ௣ܿஶߩ

ൌ

50300

1.2 ൈ 1.012 ൈ 293 ൈ 5.98ଶ ൈ √9.8 ൈ 5.98 ؆ 0.51 0.4 – 2.4 Yes 

Flame length 

to ceiling 

height ratio 

(single 

enclosure 

model) 

௙ܮ

ܪ

ൌ

10.918.8 ؆ 0.58

ܮ ௙ൌ ܦ ቀ3.7 ܳכሶ ଶ/ହ െ 1.02ቁ ൌ 1.87 ሺ3.7 ൈ 0. 51଴.ସ െ 1.02ሻ ؆ 10.9

0.2 – 1.0 Yes 

Flame length 

to ceiling 

height ratio 

(two 

enclosure 

model) 

௙ܮ

ܪ

ൌ

10.9

4.6 ؆ 2.4

ܮ ௙ൌ ܦ ቀ3.7 ܳכሶ ଶ/ହ െ 1.02ቁ ൌ 1.87 ሺ3.7 ൈ 0. 51଴.ସ െ 1.02ሻ ؆ 10.9

0.2 – 1.0 No 

Ceiling jet 

radial 

distance,rcj, 

relative to the 

ceiling height, 

H

N/A 1.2 – 1.7 N/A 

Equivalence 

ratio as an 

indicator of 

the ventilation 

rate 

N/A 0.04 – 0.6 N/A 

Equivalence 

ratio as an 

indicator of 

the opening 

ventilation 

߮ ൌ

݉ሶ F/݉ሶ Oమ

ݎ

ؠ

ܳ

ሶ

Oమ ሶ݉ ܪ∆ ݎ

ൌ

50300

13,100 ൈ 14.9 ؆ 0.99

݉ሶ Oమ ൌ 0.23 · 0.5ܣ௢ඥ݄௢ ൌ 0.23 ൈ 0.5 ൈ 113√1.3 ؆ 14.9

0.04 – 0.6 Yes 
Lubricating Oil Fire in a Turbine Building

F-9 

Quantity Normalized Parameter Calculation Validation Range In Range? 

Compartment 

aspect ratios 

(single 

enclosure 

model) 

ܮ

ܪ

ൌ

86.618.8 ؆ 4.64

ܹ

ܪ

ൌ

87.318.8 ؆ 4.64

0.6 – 5.7 Yes 

Compartment 

aspect ratios 

(twoenclosure 

model) 

ܮ

ܪ

ൌ

100.3

4.6 ؆ 21.8

ܹ

ܪ

ൌ

99.5

4.6 ؆ 21.6

0.6 – 5.7 No 

CURB LOCATION 1 

Target 

distance to 

fire diameter 

ratio 

(Column A) 

ݎ

ܦ

ൌ

8.5

5.98 ؆ 1.42 2.2 – 5.7 No 

Target 

distance to 

fire diameter 

ratio 

(Column B) 

ݎ

ܦ

ൌ

7.225.98 ؆ 1.21 2.2 – 5.7 No 

Target 

distance to 

fire diameter 

ratio 

(Column C) 

ݎ

ܦ

ൌ

18.85.98 ؆ 3.15 2.2 – 5.7 Yes 

Target 

distance to 

fire diameter 

ratio 

(Column D) 

ݎ

ܦ

ൌ

18.35.98 ؆ 3.06 2.2 – 5.7 Yes 
Lubricating Oil Fire in a Turbine Building 

F-10 

Quantity Normalized Parameter Calculation Validation Range In Range? 

Target 

distance to 

fire diameter 

ratio 

(Column E) 

ݎ

ܦ

ൌ

36.55.98 ؆ 6.1 2.2 – 5.7 No 

Target 

distance to 

fire diameter 

ratio 

(Column F) 

ݎ

ܦ

ൌ

78.45.98 ؆ 13.1 2.2 – 5.7 No 

CURB LOCATION 2 

Target 

distance to 

fire diameter 

ratio 

(Column A) 

ݎ

ܦ

ൌ

28.03

5.98 ؆ 4.67 2.2 – 5.7 Yes 

Target 

distance to 

fire diameter 

ratio 

(Column B) 

ݎ

ܦ

ൌ

26.90

5.98 ؆ 4.5 2.2 – 5.7 Yes 

Target 

distance to 

fire diameter 

ratio 

(Column C) 

ݎ

ܦ

ൌ

8.8

5.98 ؆ 1.47 2.2 – 5.7 No 

Target 

distance to 

fire diameter 

ratio 

(Column D) 

ݎ

ܦ

ൌ

3.945.98 ؆ 0.66 2.2 – 5.7 No 

Target 

distance to 

fire diameter 

ݎ

ܦ

ൌ

43.35.98 ؆ 7.24 2.2 – 5.7 No 
Lubricating Oil Fire in a Turbine Building

F-11 

Quantity Normalized Parameter Calculation Validation Range In Range? 

ratio 

(Column E) 

Target 

distance to 

fire diameter 

ratio 

(Column F) 

ݎ

ܦ

ൌ

80.85.98 ؆ 13.5 2.2 – 5.7 No 
Lubricating Oil Fire in a Turbine Building 

F-12 

Table F-4 shows that the Turbine Building fire scenario falls outside of the parameter space of 

the NRC/EPRI V&V study, both for the single- and multiple-enclosure geometric representations 

(NUREG-1824 (EPRI 1011999)). It is interesting that the single compartment representation 

only falls out of range of the parameter space for four of the six column targets, two of them 

being too low (close) and two of them being too high (far). All other parameters are within the 

NUREG-1824 (EPRI 1011999) parameter space (NUREG-1824 (EPRI 1011999)). In the case 

of the multiple compartment representation applicable to both the CFAST and FDS models, the 

aspect ratio, the flame length to ceiling height ratio, and the four target distances fall outside the 

parameter space range. 

A flame length to ceiling height ratio greater than one indicates that the flames would be 

impinging on the ceiling and spreading out under the ceiling. This configuration is beyond the 

model capability of CFAST and could affect the plume entrainment, the Hot Gas Layer 

temperature and depth, and the radiant heat flux to a target. If the Hot Gas Layer temperature 

is not a significant source of heat flux to a target, the significance of this parameter could 

decrease in the case of a target temperature calculation, provided the target distance is within 

the validated parameter space (i.e., not too close). The aspect ratio also plays a role in the Hot 

Gas Layer formation and temperature. In the case of a zone model, a large aspect ratio may 

suggest that there could be localized regions where the gases are significantly hotter than the 

average (i.e., zone temperature). This type of calculation falls within the model capability of 

FDS, and there is no reason to expect that the model is not applicable for these aspect ratios. 

Nonetheless, it is at this point necessary to provide justification either by drawing on additional 

data for comparison or by demonstrating that the Hot Gas Layer temperature is not a significant 

source of heat flux to the targets, which implies that the analysis can tolerate a significant 

relative error in the temperature prediction of the Hot Gas Layer. 

As part of the work performed at NIST for the investigation of the World Trade Center disaster, 

FDS has been validated against large-scale fire experiments. The experiments involved fairly 

large fires in relatively small compartments, limited ventilation, a liquid fuel spray fire, and the 

measurement of the heat flux to and temperatures of insulated steel (similar to the cables 

protected by Kaowool blankets). These experiments and the FDS simulations are described in 

NIST NCSTAR 1-5F. 

Because the target to distance ratios shown in Table F-4 are outside the validation range for 

four of the six column targets, it is possible that the heat flux at the nearest and farthest columns 

could be underpredicted. In the case of the farthest columns, this is not a serious issue 

because the conditions at the columns within the parameter space range are more severe but 

acceptable with respect to the critical steel temperature. In addition, the point source model 

invoked by CFAST (Jones et al., 2009) is within the model validation basis per the Society of 

Fire Protection Engineers’s (SFPE) Engineering Guide, “Assessing Flame Radiation to External 

Targets from Pool Fires” (1999). In the case of the nearer columns, simple models such as 

CFAST are outside their intended application range. It may be prudent to investigate the 

potential error of using the point source model (CFAST) at such distances through the use of 

other radiant heat flux models (i.e., solid flame models [NUREG-1805, 2004]). Although the 

near and far targets are outside the NUREG-1824 parameter space for FDS, there is additional 

validation data for FDS for these exposure conditions. Details can be found in NIST NCSTAR 

1-5F, as previously described. In addition to the temperature measurements, heat fluxes to 

various structural elements were calculated and compared to test data. This data can serve as 

the V&V basis for FDS with respect to these target columns. 
Lubricating Oil Fire in a Turbine Building

F-13 

F.4 Estimation of Fire-Generated Conditions 

This section provides details specific to each model. 

F.4.1 Zone Model (CFAST) 

Geometry: The CFAST analysis defines the compartment as a single rectangular 

parallelepiped with the specified dimensions. Two fire model strategies are considered. First, 

the entire volume of the turbine generator building is represented as a single compartment. 

This is a simple application of the CFAST model, and the implied assumption here is that the 

mass transfer across the hatch and stair openings is rapid relative to the development of a Hot 

Gas Layer in the lower level. The horizontal openings to the exterior of the building at the 4.6 m 

(15 ft) elevation are treated as vertical openings centered at the 4.6 m (15 ft) elevation, which is 

4.6 m (15 ft) above the floor, ignoring the depressed area near the fuel spill. The second 

strategy is to model the Turbine Building using two primary compartments, one for the lower 

deck and one for the upper turbine deck. The two compartments are connected by hatches and 

stairs, which are themselves modeled as sub-compartments. This represents a complex 

application of the CFAST model and is expected to provide a better representation of the plume 

entrainment in the lower level; however, CFAST does not model the entrainment from plumes 

originating from horizontal openings. Instead, the combustion products are directly placed in the 

upper hot gas zone after flowing through the horizontal opening. In addition, the gross area of 

the larger horizontal vents exceeds the recommended size per NIST SP 1086, indicating that 

there is no adequate validation data for the application. Neither geometric representation is 

ideal, although each configuration bounds one or more aspects of the fire scenario development 

and the resulting exposure to the structural steel. 

The dimensions of the primary compartments and the vent characteristics for each configuration 

are summarized in Table F-5. The dimensions for the single compartment representation 

conserve the volume, aspect ratio of the lower compartment, and the total height. Another valid 

strategy would be to conserve the total height, the boundary surface area, and the volume. 

Figures F-4a and F-4b show three-dimensional views of the geometry for the two configurations. 

Note that the entrainment within the intermediate floor is ignored in the single compartment 

model; in this case the total height is 1 m (3.3 ft) lower than the height between the lower level 

floor and the upper level ceiling. Figures F-4a and F-4b also show the locations of the targets 

and the two proposed curb locations. 

Table F-5. Primary Compartment Dimensions 

Model Length (m) Width (m) Height (m) 

Single Compartment 86.6 87.3 18.8 

Multiple Compartments: 

Lower Level 100.3 99.5 4.6 

Multiple Compartments: 

Upper Level 95 71.3 14.2 
Lubricating Oil Fire in a Turbine Building 

F-14 

 

Figure F-4a. CFAST Geometry for the Single-Compartment Representation of the Turbine Building.

Leakage to exterior

Curb 

Location 1

Vents to exterior

Column A Plant

north

Column B

Column C

Column D

Column E

Curb 

Location 2
Lubricating Oil Fire in a Turbine Building

F-15 

 

Figure F-4b. CFAST Geometry for the Two-Compartment Representation of the Turbine Building.

Note that the internal obstructions, such as the turbine generators, the condensers, and the 

HVAC room, as well as variations in the floor elevation, are not accounted for in the geometric 

definition. The total volume of these obstructions is small relative to the total volume of the 

Turbine Building, and ignoring them is not expected to affect the results appreciably, especially 

since the focus is on the heat flux to a target in the lower level. In practice, this assumption 

would be verified by creating another CFAST geometry that has a slightly lower volume that 

does not include the volume of the large obstructions. This step is not performed in this 

example, as it lies outside the primary focus. 

Fire: The fire is specified in the curbed areas, as described in Section F.2. CFAST requires a 

user-specified time-dependent HRR and stoichiometry for the combustion of fuel and oxygen. 

As noted in Section F.2, the fuel oil is dominated by alkanes, which have a chemical formula of 

CnH2n+2 with n ranging from 12 to 15 but centered on 14. The average fuel composition is 

therefore C14H30. In the absence of test results for the specific fuel oil, the gas yields needed for 

input to CFAST can be estimated. The CO yields are available from the work of Köylu and 

Faeth: 

Vents to exterior

Lower level

Upper level

Hatches and stairs 

between levels

Boundary

leakage

Curb 

Location 1

Column A

Plant

north

Column B

Column C

Column D

Column E

Curb 

Location 2

Column F
Lubricating Oil Fire in a Turbine Building 

F-16 

ݔ12 ൌ ை஼ݕ

௙ݒ௙ܯ

0.0014 ൅ 0.37ݕ௦ (F-3)

where x is the number of carbon atoms in a fuel molecule (two in this example), Mf is the 

molecular weight of the fuel (198 g/mol, calculated from the effective chemical formula), yS is the 

soot yield, and vf is the stoichiometric coefficient of the fuel, which is equal to one since all 

species yields are taken as a ratio to the fuel burned. Note that this correlation is applicable to 

well-ventilated fires, which would be appropriate for this fire scenario given the large volumes 

involved and the large number of vents to the external areas. For this example, the CO yield is 

calculated from the above formula to be 0.037 kg CO/kg fuel. The CO2 yield is computed using 

a chemical mass balance: 

aC14H30+bO2→cCO+dC+eCO2 (F–4) 

 

where a, b, c, d, and e are the number of moles of each reactant or product and C is the soot 

(unburned carbon). The number of moles of fuel required to produce 1 kg of fuel is 5.051; thus, 

a is equal to 5.051. The number of moles necessary to produce 0.037 kg of CO is 1.32, and the 

number of moles necessary to produce 0.1 kg of C is 8.33. The coefficients c and d are thus 

equal to 1.32 and 8.33, respectively. A mole balance on the carbon atom requires e to be 

61.06. This results in a CO2 yield of 2.69 kg CO2/kg fuel. This is consistent with data reported 

by Tewarson in Table 3-4.14 of the SFPE Handbook (2008) for typical alkane fuels. The 

number of moles of oxidizer (b) is not an input parameter for CFAST, but may be determined 

from the products. It is thus equal to the number of moles of carbon dioxide plus half the 

number of moles of carbon monoxide, or 61.72. 

Direct inputs for species production rates in CFAST are normalized to this CO2 yield. Thus, 

CFAST input of CO/CO2 is 0.014, and C/CO2 is 0.037. A final CFAST input is the ratio of the 

mass of hydrogen to the mass of carbon in the fuel, or 0.178 kg H/kg C. CFAST uses the fire 

area directly as an input. 

Materials: CFAST defines a wall, ceiling, and floor boundary using a single material, though 

they may be different for each of the three boundaries. In the case where the Turbine Building 

is modeled as two compartments, the material specification for each boundary follows from the 

actual geometry. Specifically, the wall and floor of the lower level are 0.3 m (1 ft) thick normal 

weight concrete and the ceiling is 1 m (3.3 ft) thick normal weight concrete, as is the floor of the 

turbine deck level. The ceiling and walls of the turbine deck level are 3 mm (0.1 in) thick 

corrugated steel. In the case where a single compartment is used to represent the Turbine 

Building, all materials are modeled using the most thermally resistive material among the 

different materials present. As such, the walls, floor, and ceiling are 0.3 m (1 ft) normal weight 

concrete. 

Ventilation: There are eighteen vents from the lower level that are open to the building 

exterior, in addition to two stairs. In addition, there are four hatches and four stair openings 

connecting the lower level to the upper level. Leakage is approximated as two small vents in 

each primary compartment, one near the floor and one that spans the entire compartment 

height. 
Lubricating Oil Fire in a Turbine Building

F-17 

The single compartment model treats the exterior vents as vertical openings centered at the 

height of the vent, or 4.6 m (15 ft) above the floor. Vents between the lower and upper levels 

are by definition ignored (i.e., the flow between the levels is rapid relative to the development of 

the Hot Gas Layer). The two-compartment model approximates each horizontal flow path using 

additional sub-compartments having an area equal to the area of the vent and a depth equal to 

the floor depth, or 1 m (3.3 ft). Horizontal vents are placed at the base and top of each subcompartment. This results in 28 additional sub-compartments and 56 horizontal vent 

connections. 

Fire/Smoke Detection: There are no smoke or fire detector inputs for this scenario. 

Steel Columns: The columns are approximated as steel plates with the given thickness of the 

actual columns. The orientation of the surface normal is directed toward the fire parallel to the 

plane of the floor since the columns’ surfaces are perpendicular to the floor plane. CFAST will 

compute the target temperature given the predicted heat flux at the target surface. The method 

effectively treats the target as having an adiabatic unexposed temperature and would thus be 

expected to overestimate the temperature if the losses on the unexposed boundary are 

significant. Conversely, this model could underestimate the temperature if the surrounding 

temperature on the unexposed side increases significantly. To determine the location of the 

highest temperature, initial simulations with targets from floor to ceiling were conducted. The 

simple point source model for the fire led to the highest temperature on portions of the steel 

columns at floor level. Note that the actual height of the target in the CFAST model is slightly 

above the floor level, or 0.01 m (0.4 in), to ensure that the target position is not coincident with 

the floor position.

F.4.2 CFD Model (FDS) 

Geometry: The entire turbine hall is included in the simulation. One mesh covers the lower 

deck, and one covers the upper turbine deck. The numerical mesh consists of uniform grid cells 

with a resolution of about 1 m. While this mesh appears to be fairly coarse, the fire is so large 

that the ratio of D*

 (the characteristic fire diameter) to the cell size is about five. This is sufficient 

resolution to simulate the fire and its impact on the overall space, based on the range provided 

in Section 2 of this guide. The main focus here is the heat flux to nearby columns, not 

necessarily columns within the fire itself; thus, the resolution is considered adequate. 

The columns cannot be resolved on the relatively coarse grid, and are approximated as steel 

plates with the given thickness of the actual columns. The column obstructions are one cell 

thick, which allows the boundary conduction on the surface opposite the fire to be exposed to 

the room conditions. Even though the column obstruction is one cell thick in the domain mesh, 

the thickness of the steel surface through which heat is transferred is equal to thickness of the 

column web. Note that FDS only performs a one-dimensional heat transfer calculation within 

solid obstructions, which is why there is little to be gained by resolving the column further. The 

neglect of lateral heat conduction within the solid tends to produce a slight overprediction of the 

average column cross-section temperature, but, because the heat flux from the fire is expected 

to be fairly uniform over the width of the column, a more detailed thermal conduction calculation 

is not warranted. 
Lubricating Oil Fire in a Turbine Building 

F-18 

Figure F-5. FDS Geometry for the Turbine Building Fire Scenario. 

Materials: The material properties are applied directly as specified to the walls, floor, ceiling 

and cabinet. 

Fire: The fire is specified in the curbed areas, as described in Section F.2. The heat release 

rate, soot yield, and molecular weight are as described in Section F.2, and are provided directly 

as inputs to FDS. A 10-second growth rate is used to allow the flows to develop over a finite 

time interval. 

Ventilation: The openings to the exterior and between the lower level and the upper level are 

modeled at the locations, as shown in Figures F-1 and F-5. It should be noted that the point of 

including the lower and upper levels of the Turbine Building in the simulation is to check whether 

there would be sufficient make-up air drawn through the various vents to sustain a steady-state 

50.3 MW fire. 

F.5 Evaluation of Results 

The purpose of the calculations described above is to estimate the steel temperature of six large 

columns in the Turbine Building to determine if any would lose the ability to carry their design 

load in the event of a large fire in the curbed area about a tank of lubricant oil. A structural steel 

Upper level Hatches and stairs 

between levels

HVAC room

Vents to exterior

Lower level

Stair opening

Plant

north

Curb 

Location 1

Curb 

Location 2

Column A

Column B

Column C

Column D

Column E
Lubricating Oil Fire in a Turbine Building

F-19 

column is considered to fail if the average cross section temperature of the steel exceeds 

538 °C (1,000 °F), as described in Section F.2. The heat release rate profile for the lubricant oil 

fire in the curbed area, as modeled by CFAST and FDS, is shown in Figure F-6. 

Figure F-6. Heat Release Rates Used by CFAST and FDS for Lubricant Oil Fire Scenario. 

F.5.1 Column Heat Flux and Column Temperature 

The predicted heat fluxes and resulting column temperatures for the six columns shown in 

Figure F-2 are summarized in Figure F-7 for Curb Location 1 and Figure F-8 for Curb Location 

2. Note that Column F was not included in the single-compartment CFAST model because the 

physical dimensions of the column exceed the enclosure dimensions. This is one drawback 

when using specific targets within approximated enclosure geometries. 

The output quantity for FDS is the gauge heat flux relative to a 36 °C (95 °F) ambient 

temperature. Two locations were considered at each column, one point near the floor and 

comparable to the CFAST position and one point near the ceiling of the lower level. The heat 

flux and temperature plots are based on the point with the maximum column temperature 

among the two. This generally corresponds to the upper point, except for columns near the fire, 

where the lower point is predicted to be hotter. The output quantity for the CFAST simulations 

is the total heat flux, which includes the fire, boundary surface reradiation, HGL radiation, and 

net convective flux at the surface of the target. This quantity is comparable to the incident heat 

flux output by FDS. 

0

10000

20000

30000

40000

50000

60000

0 600 1200 1800 2400 3000 3600

HRR (kW)

Time (s)

Heat Release Rate
Lubricating Oil Fire in a Turbine Building 

F-20 

Figure F-7a. Predicted Incident or Total Heat Flux and Column Temperature for Column A – 

Curb Location 1. 

Figure F-7b. Predicted Incident or Total Heat Flux and Column Temperature for Column B 

– Curb Location 1. 

Figure F-7c. Predicted Incident or Total Heat Flux and Column Temperature for Column C – 

Curb Location 1. 

0

50

100

150

200

250

300

350

400

450

500

0 600 1200 1800 2400 3000 3600

Temperature (°C)

Time (s)

Temperature of Column A

CFAST - single 

compartment

CFAST - multiple 

compartment

FDS

0

2

4

6

8

10

12

14

16

18

20

0 600 1200 1800 2400 3000 3600

Heat Flux (kW)

Time (s)

Heat Flux of Column A

CFAST - single 

compartment

CFAST - multiple 

compartment

FDS

0

50

100

150

200

250

300

350

400

450

500

0 600 1200 1800 2400 3000 3600

Temperature (°C)

Time (s)

Temperature of Column B

CFAST - single 

compartment

CFAST - multiple 

compartment

FDS

0

5

10

15

20

25

30

35

40

45

50

0 600 1200 1800 2400 3000 3600

Heat Flux (kW)

Time (s)

Heat Flux of Column B

CFAST - single 

compartment

CFAST - multiple 

compartment

FDS

0

50

100

150

200

250

300

350

400

450

500

0 600 1200 1800 2400 3000 3600

Temperature (°C)

Time (s)

Temperature of Column C

CFAST - single 

compartment

CFAST - multiple 

compartment

FDS

0

1

2

3

4

5

6

7

8

9

10

0 600 1200 1800 2400 3000 3600

Heat Flux (kW)

Time (s)

Heat Flux of Column C

CFAST - single 

compartment

CFAST - multiple 

compartment

FDS
Lubricating Oil Fire in a Turbine Building

F-21 

Figure F-7d. Predicted Incident or Total Heat Flux and Column Temperature for Column D 

– Curb Location 1. 

Figure F-7e. Predicted Incident or Total Heat Flux and Column Temperature for Column E – 

Curb Location 1. 

Figure F-7f. Predicted Incident or Total Heat Flux and Column Temperature for Column F – 

Curb Location 1. 

0

50

100

150

200

250

300

350

400

450

500

0 600 1200 1800 2400 3000 3600

Temperature (°C)

Time (s)

Temperature of Column D

CFAST - single 

compartment

CFAST - multiple 

compartment

FDS

0

1

2

3

4

5

6

7

8

9

10

0 600 1200 1800 2400 3000 3600

Heat Flux (kW)

Time (s)

Heat Flux of Column D

CFAST - single 

compartment

CFAST - multiple 

compartment

FDS

0

50

100

150

200

250

300

350

400

450

500

0 600 1200 1800 2400 3000 3600

Temperature (°C)

Time (s)

Temperature of Column E

CFAST - single 

compartment

CFAST - multiple 

compartment

FDS

0

1

2

3

4

5

0 600 1200 1800 2400 3000 3600

Heat Flux (kW)

Time (s)

Heat Flux of Column E

CFAST - single 

compartment

CFAST - multiple 

compartment

FDS

0

40

80

120

160

200

0 600 1200 1800 2400 3000 3600

Temperature (C)

Time (s)

Temperature of Column F

CFAST - multiple 

compartment

FDS

0

1

2

3

4

5

0 600 1200 1800 2400 3000 3600

Heat Flux (kW)

Time (s)

Heat Flux of Column F

CFAST - multiple 

compartment

FDS
Lubricating Oil Fire in a Turbine Building 

F-22 

Figure F-8a. Predicted Incident or Total Heat Flux and Column Temperature for Column A – 

Curb Location 2. 

Figure F-8b. Predicted Incident or Total Heat Flux and Column Temperature for Column B 

– Curb Location 2. 

Figure F-8c. Predicted Incident or Total Heat Flux and Column Temperature for Column C – 

Curb Location 2. 

0

20

40

60

80

100

120

140

160

180

200

0 600 1200 1800 2400 3000 3600

Temperature (°C)

Time (s)

Temperature of Column A

CFAST - single 

compartment

CFAST - multiple 

compartment

FDS

0

1

1

2

2

3

3

4

0 600 1200 1800 2400 3000 3600

Heat Flux (kW)

Time (s)

Heat Flux of Column A

CFAST - single 

compartment

CFAST - multiple 

compartment

FDS

0

20

40

60

80

100

120

140

160

180

200

0 600 1200 1800 2400 3000 3600

Temperature (°C)

Time (s)

Temperature of Column B

CFAST - single 

compartment

CFAST - multiple 

compartment

FDS

0

1

2

3

4

5

6

7

8

9

10

0 600 1200 1800 2400 3000 3600

Heat Flux (kW)

Time (s)

Heat Flux of Column B

CFAST - single 

compartment

CFAST - multiple 

compartment

FDS

0

50

100

150

200

250

300

350

400

450

500

0 600 1200 1800 2400 3000 3600

Temperature (°C)

Time (s)

Temperature of Column C

CFAST - single 

compartment

CFAST - multiple 

compartment

FDS

0

5

10

15

20

25

0 600 1200 1800 2400 3000 3600

Heat Flux (kW)

Time (s)

Heat Flux of Column C

CFAST - single 

compartment

CFAST - multiple 

compartment

FDS
Lubricating Oil Fire in a Turbine Building

F-23 

Figure F-8d. Predicted Incident or Total Heat Flux and Column Temperature for Column D 

– Curb Location 2. 

Figure F-8e. Predicted Incident or Total Heat Flux and Column Temperature for Column E – 

Curb Location 2. 

Figure F-8f. Predicted Incident or Total Heat Flux and Column Temperature for Column F – 

Curb Location 2. 

0

100

200

300

400

500

600

700

0 600 1200 1800 2400 3000 3600

Temperature (°C)

Time (s)

Temperature of Column D

CFAST - single 

compartment

CFAST - multiple 

compartment

FDS

0

10

20

30

40

50

60

70

80

90

100

0 600 1200 1800 2400 3000 3600

Heat Flux (kW)

Time (s)

Heat Flux of Column D

CFAST - single 

compartment

CFAST - multiple 

compartment

FDS

0

20

40

60

80

100

120

140

160

180

200

0 600 1200 1800 2400 3000 3600

Temperature (°C)

Time (s)

Temperature of Column E

CFAST - single 

compartment

CFAST - multiple 

compartment

FDS

0

1

2

3

4

5

0 600 1200 1800 2400 3000 3600

Heat Flux (kW)

Time (s)

Heat Flux of Column E

CFAST - single 

compartment

CFAST - multiple 

compartment

FDS

0

40

80

120

160

200

0 600 1200 1800 2400 3000 3600

Temperature (°C)

Time (s)

Temperature of Column F

CFAST - multiple 

compartment

FDS

0

1

2

3

4

5

0 600 1200 1800 2400 3000 3600

Heat Flux (kW)

Time (s)

Heat Flux of Column F

CFAST - multiple 

compartment

FDS
Lubricating Oil Fire in a Turbine Building 

F-24 

The temperature and heat flux plots reveal several interesting aspects of the curb fire exposures 

to the target columns. First, the CFAST single- and multiple-compartment representations of 

the Turbine Building produce nearly the same result. This suggests that the exposure boundary 

conditions at the columns are either dominated by the flame heat flux or that the HGL 

temperature predictions are not strongly dependent on the presence of the intervening floor. 

The fraction of the boundary heat flux at the columns that comes directly from the flame actually 

is a function of the column position. Columns close to the fire receive about 95% of the heat 

flux from the flames; columns that are located far from the fire receive about 30% of their heat 

flux directly from the flames. This is shown in Figure F-9 for two columns in the single 

compartment representation of the Turbine Building. The surface heat flux in Figure F-9 refers 

to the heat flux radiated from the heated boundaries of the enclosure; the HGL heat flux is the 

heat flux radiated from the gases in the enclosure; the target convection flux is the net 

convective heat flux at the target surface. Both Figures F-9a and F-9b show the fractions during 

the time the fire is burning. 

Figure F-9a. Column A Boundary Heat 

Flux Fractions Predicted by CFAST – 

Curb Location 1 in One Compartment 

Geometry 

Figure F-9b. Column E Boundary Heat 

Flux Fractions Predicted by CFAST – 

Curb Location 1 in One Compartment 

Geometry 

The Hot Gas Layer temperatures and the Hot Gas Layer heights are shown in Figures F-10a 

and F-10b for the single- and multiple-compartment representations. The temperatures apply to 

either curb location since the spatial location of the fire does not affect the HGL unless it is near 

a wall or in a corner. Figure F-10 indicates that the Hot Gas Layer temperatures are nearly the 

same for each configuration, though the layer elevation is somewhat higher in the single 

compartment representation. Figures F-9 and F-10 suggest that the similarity between the 

temperature results for the two CFAST configurations is an expected result for this application. 

In effect, the results do not rely on the assumptions regarding the mass flow through the 

horizontal vents between the lower level and the turbine deck and effectively confirm the 

assumption that a single-volume enclosure approximation is applicable to this application. 

-0.25

-0.05

0.15

0.35

0.55

0.75

0.95

0 500 1000 1500 2000

Heat Flux Fraction

Time (seconds)

Heat Flux Fractions at Column A

Flame

Enclosure Surfaces

HGL

Convection at Target Surface

-0.1

0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

0 500 1000 1500 2000

Heat Flux fraction

Time (seconds)

Heat Flux Fractions at Column E

Flame

Enclosure Surfaces

HGL

Convection at Target Surface
Lubricating Oil Fire in a Turbine Building

F-25 

Figure F-10a. Hot Gas Layer Temperature 

Predicted by CFAST in the Turbine 

Building. 

Figure F-10b. HGL Elevation Predicted 

by CFAST in the Turbine Building. 

The CFAST and FDS predictions are generally similar with regard to the overall magnitude and 

trend for the target heat flux. In all cases, CFAST predicts a higher and more conservative heat 

flux than FDS by 50% to 100%. This is partially a result of the flame height exceeding the 

ceiling height by a considerable margin. In addition, the CFD model, FDS, simulates the fire 

with a more realistic flow field and the inclusion of blocking obstructions. The FDS predictions 

of heat flux are based on the solution of a three-dimensional radiation transport equation with 

100 angular directions. This model accounts for both the fire and the hot smoke as sources of 

heat flux at the columns. FDS predicts a maximum heat flux and temperature for Column A 

because the simulated fire leans in the direction of this column because the large hatch nearby 

draws the hot gases and fire, upward. 

The predicted steel temperatures for Curb Location 1 are lower than the threshold value of 

538 °C (1,000 °F) at all locations by a significant margin. The maximum predicted temperature 

in the columns nearest the proposed curb location remains lower than 380 °C (716 °F) for the 

CFAST simulations and 265 °C (509 °F) for the FDS simulations. Note that the application of 

CFAST for predicting the temperatures at the nearest columns does not have a V&V basis; 

thus, more weight is assigned to the FDS results. 

The predicted steel temperatures for Curb Location 2 are lower than the threshold value of 

538 °C (1,000 °F) at all locations, except for Column D. CFAST predicts a steel temperature of 

about 620 °C (1,148 °F), while FDS predicts a steel temperature of about 508 °C (946 °F) by a 

significant margin. As was the case with Curb Location 1, the CFAST predictions for the 

nearest columns are outside the V&V basis, and more weight is assigned to the FDS results. 

However, in this case the FDS predictions are marginally lower than the threshold value, and, 

as will be seen in Section F.5.2, there is a considerable probability, based on model uncertainty 

alone, that the actual result would exceed the threshold margin. It is therefore concluded that 

Curb Location 2 is not suitable despite the plant’s preference to locate it there. Curb Location 1 

is preferable based on the fire modeling results. 

0

40

80

120

160

200

0 600 1200 1800 2400 3000 3600

Temperature (°C)

Time (s)

HGL Temperature

CFAST - One 

Compartment

CFAST -

multiple 

compartments

0

2

4

6

8

10

12

14

16

18

0 600 1200 1800 2400 3000 3600

Height (m)

Time (s)

HGL Height

CFAST - one 

compartment

CFAST - multiple 

compartments
Lubricating Oil Fire in a Turbine Building 

F-26 

F.5.2 Uncertainty 

The results indicate that the single- and multiple-compartment representation of the Turbine 

Building produce nearly the same temperature, consistent with the total heat flux results. The 

CFAST and FDS predictions are generally similar with regard to the overall magnitude and trend 

for targets. The predicted steel temperature is fairly similar for Columns C and D despite the 

moderate differences in the total and incident heat fluxes (See Figures F-7 and F-8). This is 

likely due to the differences in the boundary conditions on both the exposed and unexposed 

faces of the steel plate. In all cases except for Column C, CFAST predicts a steel temperature 

greater than that of FDS. This is not surprising, since the total heat flux is greater in all cases 

and an adiabatic boundary condition is applied to the unexposed face. 

Chapter 4, Model Uncertainty, provides guidance on how to express the uncertainty of model 

predictions. The uncertainty of the model predictions is considered for the columns that are 

predicted to have the hottest temperature, which in practice would serve as the basis for any 

conclusions drawn from the fire modeling results. Table F-6 summarizes the columns and 

hottest column temperatures for the two-zone model configurations and the FDS results. 

Table F-6. Maximum Column Temperatures among the Six Columns Considered Predicted 

by CFAST and FDS. 

Fire Model Configuration Curb Location 

Column with 

Maximum 

Temperature 

Maximum Column 

Temperature (°C) 

CFAST Single 

Compartment 1 B 377 

CFAST Two 

Compartment 1 B 378 

FDS Two 

Compartment 1 A 265 

CFAST Single 

Compartment 2 D 623 

CFAST Two 

Compartment 2 D 623 

FDS Two 

Compartment 2 D 508 

In the NRC/EPRI V&V study (NUREG-1824 (EPRI 1011999)), it was found that CFAST 

predictions of target temperature increases are, on average, equal to the corresponding 

measurements, and the relative standard deviation of its predictions about this average value is 

27%. Similarly, it was found that FDS predictions of target temperatures are, on average, 2% 

higher than the corresponding measurements, and the relative standard deviation of its 

predictions about this average value is 13%. 

This suggests that the true value of the maximum steel temperature in the column for this 

scenario is normally distributed with a mean value and standard deviation, as summarized in 

Table F-7. 
Lubricating Oil Fire in a Turbine Building

F-27 

Table F-7. Mean Maximum Column Temperatures and Standard Deviations among the Six 

Columns Considered Based on Model Uncertainty for CFAST and FDS. 

Fire Model Configuration Curb 

Location 

Mean Maximum 

Column Temperature 

Increase (°C) 

Maximum Standard 

Deviation (°C) 

CFAST Single 

Compartment 1 341 92 

CFAST Two 

Compartment 1 342 92 

FDS Two 

Compartment 1 225 29 

CFAST Single 

Compartment 2 587 158 

CFAST Two 

Compartment 2 587 158 

FDS Two 

Compartment 2 463 60 

Therefore, the probability that the steel temperature increase would exceed 518°C (932°F) at 

Curb Location 1 (i.e., 538 °C [1,000 °F] critical value minus the initial ambient temperature of 

36 °C [95 °F]) is: 

ܲሺ߂ܶ ൐ 518ሻ ൌ 1

2 erfc ൬

518 െ 341

92√2 ൰ ؆ 0.03 (F-5)

for the single-compartment configuration in CFAST; 

ܲሺ߂ܶ ൐ 518ሻ ൌ 1

2 erfc ൬

518 െ 342

92√2 ൰ ؆ 0.03 (F-6)

for the two-compartment configuration in CFAST; and 

ܲሺ߂ܶ ൐ 518ሻ ൌ 1

2 erfc ൬

518 െ 225

29√2 ൰ ؆ 0 (F-7)

for the two-compartment configuration in FDS. In other words, there is a three or less percent 

chance of exceeding the temperature threshold for structural damage based only on model 

uncertainty, according to both CFAST predictions and the FDS prediction. 

The probability that the steel temperature increase would be less than 518°C (932°F) at Curb 

Location 2, as predicted by CFAST, is: 

ܲሺ߂ܶ ൐ 518ሻ ൌ 1

2 erfc ൬

587 െ 518

158√2 ൰ ؆ 0.33 (F-8)

for the single-compartment configuration in CFAST and 
Lubricating Oil Fire in a Turbine Building 

F-28 

ܲሺ߂ܶ ൐ 518ሻ ൌ 1

2 erfc ൬

587 െ 518

158√2 ൰ ؆ 0.33 (F-9)

for the two-compartment configuration in CFAST. Similarly, the probability that the steel 

temperature increase would be greater than 518 °C (932 °F) at Curb Location 2, as predicted by 

FDS, is: 

ܲሺ߂ܶ ൐ 518ሻ ൌ 1

2 erfc ൬

518 െ 462

60√2 ൰ ؆ 0.2 (F-10)

for the two-compartment configuration in FDS. In other words, there is a three or less percent 

chance of exceeding the temperature threshold for structural damage based only on model 

uncertainty, according to both CFAST predictions and the FDS prediction. 

Thus, there is at least a 20% chance that the one of the columns would exceed the temperature 

threshold for structural damage based only on model uncertainty, according to both CFAST 

predictions and the FDS prediction; however, since the FDS cases have a firmer V&V basis, 

they are more reliant on these results. Although FDS predicts a maximum temperature in the 

steel that is about 30°C (86°F) below the critical value, the model uncertainty indicates that 

there is a non-trivial probability that the true temperature would be greater than the threshold 

value. Given this insight, it is concluded that Curb Location 1 is a better option based only on 

fire modeling considerations. 

F.5.3 Sensitivity 

Heat Flux

Table 4.2 indicates that the target heat flux output parameter is primarily a function of the heat 

release rate. A variation in the heat release rate corresponds to a variation in the heat flux that 

is proportional to the heat release rate raised to the 4/3 power. Consequently, a given 

uncertainty in the heat flux results in a greater uncertainty in its quantity. Fortunately, the heat 

release rate for pool fires is fairly well defined for particular fuels. Data for the burning rate of 

liquid fuels provided by Babrauskas (2008) indicates that there is generally a 5% to 10% 

uncertainty in this input parameter, which itself is proportional to the heat release rate, though 

no particular uncertainty is reported for the actual fuel involved in the Turbine Building fire 

scenario. Conservatively assuming a 10% uncertainty in the burning rate results in a 14% 

variation in the predicted heat flux. To assess whether or not this could influence the 

conclusions, reference is made to Figures F-7a, F-7b, and F-8d. Figures F-7a and F-7b depict 

the most adverse exposure fluxes to the columns, as predicted by FDS and CFAST, 

respectively. The maximum heat flux, as shown in Figure F-7b, is about 22.5 kW/m2, and the 

resulting peak steel temperature is about 375 °C (707 °F). Based on the uncertainty in the fuel 

burning rate, one could expect the predicted heat flux to fall between 19.6 and 25.5 kW/m2, 

based on the sensitivity of this parameter to the heat release rate alone. Figure 8d depicts a 

heat flux exposure condition that causes the steel to reach 500 °C (932°F) to 600 °C (1,112). In 

this case, the peak exposure heat flux is on the order of 50 kW/m2 to 60 kW/m2. This provides a 

strong indication that a peak heat flux of 25.5 kW/m2 would not result in the steel reaching a 

temperature of 538 °C (1,000 °F), the failure condition for the steel in this example. 

Consequently, it is concluded from the parameter sensitivity information for the heat flux that the 

uncertainty in the heat release rate could not result in a different conclusion. 
Lubricating Oil Fire in a Turbine Building

F-29 

Target Temperature

Table 4.2 indicates that the target temperature output parameter is also primarily a function of 

the heat release rate. A variation in the heat release rate corresponds to a variation in the heat 

flux that is proportional to the heat release rate raised to the 2/3 power. Consequently, a given 

uncertainty in the heat flux results in a lower uncertainty in the target temperature quantity. As 

previously described, a conservative uncertainty in the heat release rate for a burning liquid fuel 

is about 10%, which corresponds to a variation in the predicted target temperature of 7%. To 

assess whether or not this could influence the conclusions, reference is made again to Figures 

F-7a and F-7b, which depict the most adverse steel temperatures for Curb Location 1. The 

maximum temperature predicted among all of the models is about 375 °C (707 °F), such that 

the maximum temperature increase is about 339 °C (610 °F) for an initial ambient temperature 

of 36 °C (95 °F). A 7% variation in this output parameter indicates that the predicted target 

temperature is between 351°C (664 °F) and 399°C (750 °F), which is considerably less than the 

failure condition of 538°C (1,000°F) for the steel in this example. Consequently, it is concluded 

from the parameter sensitivity information that the uncertainty in the heat release rate could not 

result in a different conclusion. 

F.6 Conclusion 

Based on the analysis above, a 50.3 MW lubricant fire in the curbed area located between 

Columns A, B, C, and D (Curb Location 1) is not predicted to cause the structural steel to 

exceed a temperature of 538 °C (1,000 °F). This is not the case for the proposed location near 

Column D (Curb Location 2). Consequently, the recommendation for the design package is to 

install the curbed area at Curb Location 1. 

Overall, given the large volume of lubricant involved, it is significant that structural failure is not 

predicted for either the zone or the CFD fire models for Curb Location 1. Although it may seem 

counterintuitive, this is a direct result of the relatively small area in which the lubricant is 

confined. The curbing restricts the surface area of the lubricant spill, and, correspondingly, the 

heat release rate of the fire. 

F.7 References 

1. NUREG-1805, Fire Dynamics Tool, 2004.

2. NUREG-1824 (EPRI 1011999), Verification and Validation of Selected Fire Models for 

Nuclear Power Plant Applications, 2007. 

3. SFPE Handbook of Fire Protection Engineering, 4th edition, 2008. 

4. NIST SP 1018-5, Fire Dynamics Simulator (Version 5), Technical Reference Guide, Vol. 3, 

Experimental Validation, 2010.

5. NIST NCSTAR 1-5F, Federal Building and Fire Safety Investigation of the World Trade 

Center Disaster: Computer Simulation o the Fires in the World Trade Center Towers, 2005. 

6. NIST SP 1086, Consolidated Model of Fire Growth and Smoke Transport, CFAST 

(Version 6), Software Development and Model Evaluation Guide, 2009. 

7. U.O. Köylu and G.M. Faeth, Carbon Monoxide and Soot Emissions from Liquid-Fueled 

Buoyant Turbulent Diffusion Flames. Combustion and Flame, 87:61–76, 1991. 

8. ASTM E119-10a. Standard Test Methods for Fire Tests of Building Construction Materials,” 

American Society for Testing and Materials, West Conshohocken, PA, 2010. 

9. American Institute of Steel Construction, Steel Construction Manual, 13th Edition, New York, 

New York, 2006. 
Lubricating Oil Fire in a Turbine Building 

F-30 

10. EPRI 1002981, Fire Modeling Guide for Nuclear Power Plant Applications, EPRI 

1002981Electric Power Research Institute, Palo Alto, CA, August 2002. 

11. SFPE, “Assessing Flame Radiation to External Targets from Pool Fires,” SFPE Engineering 

Guide, Society of Fire Protection Engineers (SFPE), Bethesda, MD (1999). 

F.8 Attachments 

1. FDS input files: 

a. Lube_oil_fire_in_TB_Location_1.fds 

b. Lube_oil_fire_in_TB_Location_2.fds 

2. CFAST input files: 

a. Lube oil fire in TB – Location 1 One compartment.in 

b. Lube oil fire in TB – Location 1 Two compartments.in 

c. Lube oil fire in TB – Location 2 One compartment.in 

d. Lube oil fire in TB – Location 2 Two compartments.in 

e. LubeOil.o 

f. thermal.csv 
G-1 

G 

TRANSIENT FIRE IN A MULTI-COMPARTMENT 

CORRIDOR 

G.1 Modeling Objective 

The calculations described in this example predict the transport of smoke and heat from a stack 

of burning pallets through multiple compartments with different door heights and soffits. The 

purpose of the calculation is to determine whether important safe-shutdown equipment will fail, 

and, if so, at what time failure occurs. The time to smoke detector activation is also estimated. 

G.2 Description of the Fire Scenario 

General Description: The corridor provides access to a variety of spaces and contains support 

equipment. Various important cables are routed through these connecting spaces. 

Geometry: This multi-compartment area consists of interconnected compartments and 

corridors on the same level. Figure G-1 illustrates the geometry. 

Materials:

Construction: The walls, ceiling, and floor are made of concrete. The cabinets and cable trays 

are made of steel. All boundary surfaces are 0.5 meters thick, as shown in Figure G-1. 

Nominal values for the thermal properties of various materials in the compartment are listed in 

Table 3-1 (NUREG-1805, Table 2-3). 

Cables: The cable trays contain cross-linked polyethylene (XPE or XLPE)-insulated cables with 

a Neoprene jacket. These cables have a diameter of approximately 1.5 cm (0.6 in), a jacket 

thickness of approximately 2 mm (0.079 in), and 7 conductors. The cables have a density of 

1,375 kg/m3

, a specific heat of 1.39 kJ/kg/K, a thermal conductivity of 0.235 W/m/K, and an 

emissivity of 0.95 (NUREG/CR-6850 (EPRI 1011989)). They are considered damaged when 

the internal temperature just underneath the jacket reaches 330 °C (626 °F) or the exposure 

heat flux reaches 11 kW/m2

 (NUREG-6850 (EPRI 1011989), Table H-1). The tray locations are 

shown in Figure G-2. 

Fire Protection Systems: There are nine smoke detectors, located as shown in Figure G-1. 

The detectors are UL-listed, with a nominal sensitivity of 4.9%/m. There is no automatic fire 

suppression. 

Ventilation: The ventilation system supplies the combined space at a rate of 1.67 m3

/s 

(3,540 ft3

/min). The supply and return vents are shown in the drawing. There are three doors 

leading into the space, all of which are closed during normal operation. 

Fire: The fire source, a stack of four wood pallets with two trash bags, is located in the corner, 

as shown in Figures G-1 and G-2. 
Transient Fire in a Multi-Compartment Corridor 

G-2 

G.3 Selection and Evaluation of Models 

This section describes the applicability of each of the five fire models to this scenario. Note that 

a typical NPP fire modeling analysis would not require the use of all five models. 

Algebraic Models: FIVE and the FDTs

 are not capable of modeling fire conditions in multicompartment scenarios, but do contain correlations that can be used for smoke detector 

activation estimates. 

Zone Models: The fire scenario outlined in the previous section falls within the range of 

applicability for a zone model. Zone models can calculate the time-dependent Hot Gas Layer 

properties in multi-compartment scenarios, as well as the activation times of smoke detectors. 

Although the geometry in this scenario is somewhat complex, it can be handled by zone 

modeling since it is largely a group of interconnected compartments. 

CFD Models: The primary advantage of a CFD model for this fire scenario is that CFD models 

can predict the fire more realistically. The CFD models can also provide greater accuracy when 

modeling smoke detector activation. The geometry of this scenario is somewhat complex due 

to the multiple compartments, and varying connections and these aspects can be modeled with 

greater accuracy using CFD models. If initial evaluations using zone modeling suggest that 

more detailed modeling is required, particularly in areas remote from the fire, the added input 

data development and model run times required for CFD models may be justified. 

Validation: A source of validation data justifying the use of the fire models discussed above for 

this scenario is the NRC/EPRI V&V study documented in NUREG-1824 (EPRI 1011999). The 

National Institute of Standards and Technology (NIST) Multi-Compartment Test Series 

comprised 45 fire tests in a three-room suite, which consisted of two relatively small rooms 

connected via a relatively long corridor. The fire source, a gas burner, was located against the 

rear wall of one of the small compartments, and fire tests of 100 kW, 300 kW, and 500 kW were 

conducted. The present scenario has a larger fire in a larger, longer compartment. 

Table G-1 lists various important model parameters and the ranges for which the NRC/EPRI 

validation study is applicable. The calculations in Table G-1 are for the fire room. The room 

width geometry is not within the range of validation; however, this is not a significant measure of 

model accuracy for this scenario, since room volume is more important for this scenario than 

aspect ratios. The natural ventilation parameter is just inside the range due to the large roomto-room connection, while the mechanical ventilation value is significantly out of range due to 

the low CFM; however, the large room-to-room opening provides more than enough ventilation 

for this scenario, so the mechanical ventilation parameter is also not a significant measure of 

model accuracy for this scenario. 
Transient Fire in a Multi-Compartment Corridor

G-3 

Table G-1. Normalized parameter calculations for the Multi-Compartment Corridor fire scenario.

Quantity Normalized Parameter Calculation Validation Range In Range? 

Fire Froude Number ܳכ

ሶ

ൌ

ܳ

ሶ

ܦ݃ଶඥܦஶܶ௣ܿஶߩ

ൌ

2500

1.2 ൈ 1.012 ൈ 293 ൈ 1.28ଶ ൈ √9.8 ൈ 1.28 ൌ 1.21 0.4 – 2.4 Yes 

Flame Length, L୤, 

relative to the Ceiling 

Height, H

௙ܮ

ܪ

ൌ

3.86.1 ൌ 0.62

ܮ ௙ൌ ܦ ቀ3.7 ܳכሶ ଶ/ହ െ 1.02ቁ ൌ 1.28 ሺ3.7 ൈ 1.21଴.ସ െ 1.02ሻ ൌ 3.8

0.2 – 1.0 Yes 

Ceiling Jet Radial 

Distance,rcj, relative to 

the Ceiling Height, H

N/A 1.2 – 1.7 N/A 

Equivalence Ratio, φ, 

as an indicator of the 

Ventilation Rate1

߮ ൌ

݉ሶ F/݉ሶ Oమ

ݎ

ؠ

ܳ

ሶ

Oమ ሶ݉ ܪ∆ ݎ

ൌ

2500

13,100 ൈ 0.03 ൌ 5.8

݉ሶ Oమ ൌ 0.23 ߩஶܸ

ሶ

ൌ 0.23 ൈ 1.2 ൈ 0.12 ൌ 0.03

0.04 – 0.6 NA 

Equivalence Ratio, φ, 

as an indicator of the 

Opening Ventilation 

߮ ൌ

݉ሶ F/݉ሶ Oమ

ݎ

ؠ

ܳ

ሶ

Oమ ሶ݉ ܪ∆ ݎ

ൌ

2500

13,100 ൈ 5.1 ൌ 0.04

݉ሶ Oమ ൌ 0.23 · 0.5ܣ௢ඥ݄௢ ൌ 0.23 ൈ 0.5 ൈ 18√6 ൌ 5.1

0.04 – 0.6 Yes 

Compartment Aspect 

Ratios 

ܮ

ܪ

ൌ

14.2

6.1 ൌ 2.33

ܹ

ܪ

ൌ

3.06.1 ൌ 0.49

0.6 – 5.7 No2

Target Distance, r, 

relative to the Fire 

Diameter, D

N/A 2.2 – 5.7 N/A 

1 The mechanical ventilation of the fire room is prorated based on the volume fraction of the fire room to the total volume served by the 

mechanical ventilation system; however, for this scenario natural ventilation dominates, so mechanical ventilation does not affect the accuracy. 

2 Based on the room width to height ratio. 
Transient Fire in a Multi-Compartment Corridor 

G-4 

Figure G-1. Geometry of the Multi-Compartment Corridor. 
Transient Fire in a Multi-Compartment Corridor

G-5 

Figure G-2. Geometry Details of the Multi-Compartment Corridor. 
Transient Fire in a Multi-Compartment Corridor 

G-6 

G.4 Estimation of Fire-Generated Conditions 

This is a classic application of a zone fire model with a fire in one compartment connected to a 

number of additional compartments with doorway-like vents. Outputs of primary interest in the 

simulation include temperatures in the compartments, activation of smoke detectors in the 

compartments, and the temperature of cable targets in the compartments. This scenario was 

modeled using the zone model MAGIC. 

Geometry: To simplify the process of modeling the multi-compartment geometry, the layout 

was divided into eight areas, as illustrated in Figure G-3. Note that the small indentation in 

compartment 1 was ignored for the MAGIC calculations. Connections between compartments 

was by door (compartments 5 to 6), by soffit (compartments 2 to 3), or left open by using a fullwall opening. Table G-2 summarizes the compartment dimensions used for zone modeling. A 

graphical depiction of the scenario, as modeled in MAGIC, is shown in Figure G-4. 

Figure G-3. Effective corridor layout for implementation in zone models (not to scale). 

Table G-2. Compartment dimensions for Corridor scenario. 

Comp. Length (m) Width (m) Area (m2) 

1 7.6 4.1 31.2 

2 2.0 22.9 45.8 

3 44.1 4.1 180.8 

4 8.1 5 40.5 

5 10.4 6.61 68.7 

6 10.3 6.1 62.8 

7 12.2 8.2 100.0 

8 3 14.2 42.6 

Fire: The fire source, a stack of four wood pallets with two trash bags, is located in the corner, 

as shown in Figures G-1 and G-2. As shown in the figures, the pallet stack measures 0.44 m 

(1.4 ft) high. The fire grows following a “t-squared” curve to a maximum value of 2,500 kW in 

1 

2 

3 

8 

4 

5 

6 

7 
Transient Fire in a Multi-Compartment Corridor

G-7 

7 minutes and remains steady for 8 additional minutes. The HRR is estimated by combining 

separate estimates for a 0.44 m (1.4 ft) stack of wood pallets and 2 trash bags filled with paper 

and using HRR data from the Heat Release Rates chapter of the SFPE Handbook. After that, 

the fire’s HRR decays linearly to zero in 8 minutes. 

The radiative fraction of the fire is taken to be 35%, a value typical of sooty fires (SFPE 

Handbook). The soot yield is 1.5%, typical of cellulosic materials like wood and paper (SFPE 

Handbook). MAGIC uses a mass loss rate to determine the HRR; this is simply the HRR 

divided by the heat of combustion. 

The fire was modeled as a 1.3 m2

 (14 m2) source (equivalent diameter of 1.28 m (4.2 ft)) at an 

elevation of 0.44 m (1.4 ft) (see Figure G-2). For the fire, an oxygen-fuel stoichiometric ratio of 

1.3 and a heat of combustion of 16.4 kJ/g were used (SFPE Handbook). An average specific 

area of 114 was calculated based on an average soot yield value for wood (SFPE Handbook). 

Materials: The materials are as described above. 

Ventilation: The ventilation rate is given above. The vents in Figure G-1 are square, but, 

because MAGIC uses round vents, an equivalent diameter of 1.13 m (3.7 ft) was used as input. 

In room-to-room connections with the same ceiling height, a shallow (0.1 m) soffit was added to 

allow smoother model execution. Finally, the only leakage from the space occurs via a 2.5-cm 

(1 in) crack under each of the three doors. 

Fire Protection Systems: In MAGIC, there is no direct way of calculating smoke density for 

smoke detector activation. Consistent with NUREG-1805, the recommended approach given by 

the developers is to model the smoke detector as a sprinkler with a low activation temperature 

and RTI. An activation temperature of 30 o

C (86 oF) and an RTI of 5 (m/s)1/2 was selected. 
Transient Fire in a Multi-Compartment Corridor 

G-8 

Figure G-4. MAGIC rendering of the Corridor scenario. 
Transient Fire in a Multi-Compartment Corridor

G-9 

G.5 Evaluation of Results 

The purpose of the calculations described above is to determine whether a stack of burning 

pallets in a corridor could generate gas temperatures in adjacent compartments that are 

capable of damaging cables and electrical equipment. Smoke detector activation is also 

estimated. Only the zone model MAGIC was used for this scenario. In general, the results 

demonstrate that the fire is not capable of generating damaging conditions, even in the 

compartment of fire origin; as a result, there is no need for detailed modeling of the targets in 

remote locations. However, an additional simulation was run with the fire’s HRR increased by 

an order of magnitude, which was also found to generate HGL conditions incapable of causing 

damage to the cables in the remote rooms based on the failure criteria cited above. The 

following sections describe the results in greater detail. 

G.5.1 Heat Release Rate 

The heat release rate produced by MAGIC was unmodified from that based on the input (i.e., 

there was no oxygen starvation). The heat release rate increases as a function of t2

, has a 

steady burning phase, and then burns out, as shown in Figure G-5. 

Figure G-5. Heat Release Rate produced by MAGIC for the Corridor Scenario. 

G.5.2 HGL Temperature 

MAGIC predicts peak temperatures of about 205 °C (400 °F) in the corridor where the fire is 

located (see Figure G-6). This is below the cable damage temperature threshold of 330 °C 

(625 °F), cited above. The HGL temperatures for the other corridors are substantially lower; for 

example, the center corridor is also shown in Figure G-6. A comparison of Figures G-6 and G-5 

will show that the change in HGL temperature closely follows the change in the heat release 

rate. 

0

500

1000

1500

2000

2500

3000

0 600 1200 1800 2400 3000 3600

HRR (kW)

Time (s)

Heat Release Rate
Transient Fire in a Multi-Compartment Corridor 

G-10 

Figure G-6. Hot Gas Layer Temperature Predictions by MAGIC for the Corridor Scenario. 

This scenario concerns the prediction of cable damage at a location outside the compartment of 

fire origin. Prior to conducting detailed analyses of cable heating in another compartment, the 

temperature of the Hot Gas Layer in the compartment of fire origin can be modeled as a 

potential screening tool. If the HGL temperature within the compartment of origin is not likely to 

cause damage to cables in that compartment, damage to cables outside the fire compartment is 

even more unlikely. As part of this approach, it is conservatively assumed that the cable 

surface temperature will match the HGL temperature (i.e., heat-up of the cable is assumed to be 

immediate). 

G.5.3 Smoke Detection 

The smoke detector activation time in the corridor containing the burning pallets was predicted 

to be 110 seconds. At this time the fire is only at 172 kW. 

G.5.4 Uncertainty 

Chapter 4, Model Uncertainty, provides guidance on how to express the uncertainty of the 

MAGIC predictions. In the NRC/EPRI V&V study (NUREG-1824 (EPRI 1011999)), it was found 

that MAGIC predictions of Hot Gas Layer temperatures are, on average, 1% greater than 

corresponding measurements, with a relative standard deviation of 7%. This suggests that the 

true value of the peak HGL temperature in this scenario is normally distributed with a mean of 

203 °C and a standard deviation of 14.2 °C. Therefore, the probability that the cable 

temperature would exceed 330 °C (626 °F) is: 

ܲሺܶ ൐ 330ሻ ൌ 1

2 erfc ൬

330 െ 203

14.2√2 ൰ ؆ 0 (G-1)

In other words, there is a near-zero probability of exceeding the damage temperature threshold 

for cables within the compartment of fire origin based on a surrounding HGL temperature, 

according to the MAGIC prediction. This demonstrates that detailed analyses of the cables 

outside the compartment of original are not warranted. 

0

40

80

120

160

200

0 600 1200 1800 2400 3000 3600

Temperature (C)

Time (s)

HGL Temperature Center Corridor 

0

50

100

150

200

250

300

0 600 1200 1800 2400 3000 3600

Temperature (C)

Time (s)

HGL Temperature Fire Room 
Transient Fire in a Multi-Compartment Corridor

G-11 

G.5.5 Sensitivity 

There can be considerable uncertainty in the heat release rates of real fires. As a result, it is 

prudent to consider the sensitivity of simulation results to the selected heat release rates. 

Table 4.2 indicates that the Hot Gas Layer temperature prediction is related to the heat release 

rate by a two-thirds power dependence. 

Equation 16 in Chapter 4 is a simple formula which can be used to estimate the relative change 

in the model Hot Gas Layer temperature output quantity, ∆ܶ/ሺܶ െ ܶ଴ሻ, due to the relative 

change in the model heat release rate input parameter, ∆ܳሶ/ܳሶ: 

∆ܶ

ܶെܶ଴

ൎ 2

3

∆ܳሶ

ܳሶ (G-2)

The predicted Hot Gas Layer temperature is 203°C (397 °F), considerably less than the 330°C 

(625 °F) target damage temperature of interest. Based on this equation, more than twice the 

heat release rate of the fire would be required to cause the Hot Gas Layer temperature to 

increase to the damage temperature of interest. 

G.6 Conclusion 

The zone model MAGIC does not predict HGL temperatures capable of cable damage in any 

compartment or corridor, including the corridor containing the burning pallets, while accounting 

for uncertainty in the temperature predictions of MAGIC and the sensitivity of the predictions to 

variations in the heat release rate. An additional simulation was run with the fire HRR increased 

by an order of magnitude, which was also found to generate HGL conditions incapable of 

causing damage to the cables in the remote rooms. Based on a simplified method for smoke 

detector activation, smoke detector operation occurs at about 110 seconds. 

G.7 References 

1. NUREG-1805, Fire Dynamics Tools.

2. NUREG-1824 (EPRI 1011999), Verification and Validation of Selected Fire Models for 

Nuclear Power Plant Applications, 2007. 

3. NUREG/CR-6850 (EPRI 1011999), Fire PRA Methodology for Nuclear Power Facilities. 

4. SFPE Handbook of Fire Protection Engineering, 4th edition, 2008. 

5. UL 217, Underwriters Laboratories, Inc., Single Station Fire Alarm Device.

6. NIST SP 1018-5, Fire Dynamics Simulator (Version 5), Technical Reference Guide, Vol. 3, 

Experimental Validation. 

7. NIST SP 1086, Consolidated Model of Fire Growth and Smoke Transport, CFAST 

(Version 6), Software Development and Model Evaluation Guide 

8. Gay, L., C. Epiard, and B. Gautier, “MAGIC Software Version 4.1.1: Mathematical Model,” 

EdF HI82/04/024/B, Electricité de France, France, November 2005. 

G.8 Attachments 

1. MAGIC input file: Corridor.cas 

 
Transient Fire in a Multi-Compartment Corridor 

G-12 
H-1 

H 

CABLE TRAY FIRE IN ANNULUS 

H.1 Modeling Objective 

The calculations described in this Appendix examine the potential for damage to redundant 

safe-shutdown cables due to a fire in an adjacent tray in the annulus region of the containment 

building. In addition, the calculations provide information on the effectiveness of some 

protection strategies. 

H.2 Description of the Fire Scenario 

General Description: The annulus is the region between the primary containment structure 

and the secondary containment (shield) building. The primary and secondary containments are 

cylindrical with domes on top. The annulus space contains a variety of penetrations from the 

reactor to the external support systems. One of these penetrations contains two cable trays 

with cables that control systems in both trains of safety equipment. A fire starts in one tray of 

cables and spreads vertically and horizontally along the cables in that tray. 

Geometry: The layout of the annulus is shown in Figure H-1. The exterior wall is made of 

concrete, while the interior wall and cable trays are made of steel. The cable tray locations are 

shown in Figure H-2. 

Materials: Property values for the relevant materials are listed in Table 3-1. The annulus wall 

thicknesses are indicated in the drawing. The cable tray steel is approximately 2 mm (0.079 in) 

thick. 

Cables: The cable trays are filled with PE-insulated, PVC-jacketed control cables. These 

cables have a diameter of approximately 1.5 cm (0.6 in), a jacket thickness of approximately 

1.5 mm (0.06 in), and 7 conductors. There are approximately 120 cables in each tray. The 

mass of each cable is 0.4 kg/m. The mass fraction of copper is 0.67. These cables fail when 

the internal temperature just underneath the jacket reaches approximately 200 °C (390 °F) 

(NUREG/CR-6931, Vol. 2, Table 5.10) or the exposure heat flux exceeds 6 kW/m2

 (NUREG1805, Appendix A). 

Fire: A fire ignites at the base of the lower cable train in the vicinity of the bend at the inner 

wall. From the results of the CHRISTIFIRE project (NUREG/CR-7010, Vol. 1), the burning rate 

of the PVC cable is 250 kW/m2

. The heat of combustion of the cables is 16 MJ/kg, which is 

appropriate for PE/PVC cable. A mixture of PE (C2H4) and PVC (C2H3Cl) would have an 

effective chemical formula of C2H3.5Cl0.5. 

The fire spreads vertically at a rate of 258 mm/s and horizontally at a rate of 0.9 mm/s 

(NUREG/CR-6850 (EPRI 1011989), Appendix R). The peak heat release rate would be 945 kW 

once all of the cables in the first tray are burning. 
Cable Tray Fire in Annulus 

H-2 

For this scenario, the soot yield of the burning cable is 0.1; that is, 10% of the cable mass 

consumed is converted into smoke particulate. The radiative fraction of the fire is 35%, typical 

of sooty fires (Tewarson, SFPE Handbook, Table 3-4.16). 

Detection and Suppression Systems: Smoke detectors are located on the wall of the shield 

building 15 m (50 ft) above-grade. The detectors are UL-listed, with a nominal sensitivity of 

4.9%/m. Standard response sprinklers are located on the inner wall, as shown in the drawing. 

The sprinklers have a response time index (RTI) of 130 (m s)1/2 and activate at a temperature of 

100 °C (212 °F) (NUREG-1805, Chap. 10). Each sprinkler is topped by heat collectors 

designed to trap heat from a fire. 

Ventilation: None. 
Cable Tray Fire in Annulus

H-3 

Figure H-1. Geometry of the Annulus. 
Cable Tray Fire in Annulus 

H-4 

Figure H-2. Geometry details of the Annulus. 
Cable Tray Fire in Annulus

H-5 

H.3 Selection and Evaluation of Fire Models 

The fire scenario described above can be categorized as an “open” rather than a “compartment” 

fire. Because of this, compartment fire models are generally inapplicable, although certain 

algorithms contained within these models may still apply. 

Algebraic Models: The heat flux calculations in the FDTs

 and FIVE can provide useful 

screening information for this scenario. For comparison purposes, both the point source and 

solid flame calculations from the FDTs

 were used for this scenario. Given the proximity of the 

two cable trays, the solid flame model is expected to provide a more accurate estimate of the 

heat flux to the adjacent cable tray. 

Zone Models: The geometry of this scenario is quite unique for the application of a zone model 

that is typically used with mostly rectangular compartments where an HGL forms from a fire 

source. Still, since the containment building is so large that the curvature of the walls will have 

little effect, a smaller compartment can be defined with a tall ceiling height and large vents so 

that any layer that forms will flow out into the rest of the annulus without impacting the region 

directly around the fire source and redundant cable tray target. 

CFD Models: Although the geometry of this scenario is unlike the mostly rectangular 

compartments found in a nuclear power plant, it is not particularly difficult to model in FDS. In 

fact, the containment building is so large that the curvature of the walls has little effect on the 

results of the calculation. Figure H-3 is an FDS/Smokeview depiction of the scenario. 

Validation: According to NUREG-1824 (EPRI 1011999), the applicability of the validation 

results can be determined using normalized parameters traditionally used in fire science. 

Normalized parameters allow users to compare results from scenarios of different scales by 

normalizing physical characteristics of the scenario. Table H-1 lists the parameters, and, where 

applicable, the values calculated for this scenario. For this scenario, only two of the parameters 

are applicable because the others address phenomena unique to compartment fires. The 

parameter that falls outside of the validation range of NUREG-1824 (EPRI 1011999), ݎ/ܦ, 

indicates that in this scenario the fire is relatively close to the target. 

Only FDS was used to predict the smoke detector and sprinkler activation. The sprinkler and 

smoke detector activation algorithms in CFAST were developed under the assumption that the 

device is located in the fire plume or Hot Gas Layer. The plume would have limited impact on 

the devices located in the annulus, and the size of the annulus makes the accumulation of a Hot 

Gas Layer unlikely. In addition, smoke detector activation in CFAST is predicted based on a 

temperature rise above ambient rather than actual smoke obscuration. This approximation has 

been shown to have significant uncertainties (Schiffiliti, 1996). 
Cable Tray Fire in Annulus 

H-6 

Table H-1. Normalized parameter calculations for the Annulus fire scenario.

Quantity Normalized Parameter Calculation Validation Range In Range? 

Fire Froude 

כܳ Number

ሶ

ൌ

ܳ

ሶ

ܦ݃ଶඥܦஶܶ௣ܿஶߩ

ൌ

945

1.2 ൈ 1.012 ൈ 293 ൈ 1.1ଶ ൈ √9.8 ൈ 1.1 ؆ 0.7 0.4 – 2.4 Yes 

Flame Length, L୤, 

relative to the 

Ceiling Height, H

N/A 0.2 – 1.0 N/A 

Ceiling Jet Radial 

Distance,rcj, 

relative to the 

Ceiling Height, H

N/A 1.2 – 1.7 N/A 

Equivalence Ratio, 

φ, as an indicator 

of the Ventilation 

Rate 

N/A 0.04 – 0.6 N/A 

Compartment 

Aspect Ratio N/A 0.6 – 5.7 N/A 

Target Distance, r, 

relative to the Fire 

Diameter, D

ݎ

ܦ

ൌ

1.71.1 ؆ 1.5 2.2 – 5.7 No 
Cable Tray Fire in Annulus

H-7 

Figure H-3. FDS/Smokeview rendering of the Annulus scenario. 
Cable Tray Fire in Annulus 

H-8 

H.4 Estimation of Fire-Generated Conditions 

This section provides specific details on how each model is set up and run. 

H.4.1 Algebraic Models (FDTs) 

The FDTs (NUREG 1805, 2005) contain several correlations for estimating the heat flux at a 

fixed distance from the exposure fire. The FDTs

 spreadsheets 

05.1_Heat_Flux_Calculations_Wind_Free.xls (Point Source) and 

05.1_Heat_Flux_Calculations_Wind_Free.xls (Solid Flame 1) 

were used in this analysis. In addition, the solid flame 1 spreadsheet calculates the equivalent 

diameter of the fire and the flame height to determine the size of the exposure fire. 

Using the estimated peak heat release rate of 945 kW and a fire-to-target distance of 1.7 m 

(5.6 ft), the heat flux based on the point source model is estimated as 4.3 kW/m2

. Using the 

solid flame model, the heat flux is estimated as 7.1 kW/m2

 with an effective area of 1.02 m2

(11 ft2

)and a flame height of 2.48 m (8.1 ft). As expected, the solid flame model estimate of the 

heat flux is significantly higher than the point source value. The spreadsheet for the solid flame 

calculations is shown in Figure H-4. 

 
CHAPTER 5

ESTIMATING RADIANT HEAT FLUX FROM FIRE

TO A TARGET FUEL AT GROUND LEVEL

UNDER WIND-FREE CONDITIONS

SOLID FLAME RADIATION MODEL

Version 1805.1

(SI Units)

INPUT PARAMETERS

Mass Burning Rate of Fuel (m") Enter Value kg/m2-sec

Effective Heat of Combustion of Fuel (Hc,eff) TRUE Enter Value kJ/kg

Empirical Constant (k) Enter Value m-1

Heat Release Rate (Q) 945.00 kW

Fuel Area or Dike Area (Adike) 1.02 m2 1.02 m2

Distance between Fire and Target (L) 1.70 m 1.70 m

OPTIONAL CALCULATION FOR GIVEN HEAT RELEASE RATE

Select "User Specified Value" from Fuel Type Menu and Enter Your HRR here → 945 kW

Calculate

THERMAL PROPERTIES DATA

Mass Burning Rate Constant Select Fuel Type m" (kg/m2

-sec) km 



Methanol 0.017 100 Scroll to desired fuel type then 

Ethanol 0.015 100 Click on selection

Butane 0.078 2.7

Benzene 0.085 2.7

Hexane 0.074 1.9

Heptane 0.101 1.1

Fuel

20,000

26,800

45,700

40,100

The following calculations estimate the full-scale cable tray heat release rate.

Parameters in YELLOW CELLS are Entered by the User.

and secure to avoid errors due to a wrong entry in a cell(s). The chapter in the NUREG should be read before an analysis is made.

Parameters in GREEN CELLS are Automatically Selected from the DROP DOWN MENU for the Cable Type Selected.

All subsequent output values are calculated by the spreadsheet and based on values specified in the input parameters. This spreadsheet is protected 

BURNING RATE DATA FOR FUELS

Project / Inspection Title: Fire Model User's Guide Appendix H

Heat of Combustion

Hc,eff (kJ/kg)

44,700

44,600

User Specified Value

Xylene 0.09 1.4

Acetone 0.041 1.9

Dioxane 0.018 5.4

Diethy Ether 0.085 0.7

Benzine 0.048 3.6

Gasoline 0.055 2.1

Kerosine 0.039 3.5

Diesel 0.045 2.1

JP-4 0.051 3.6

JP-5 0.054 1.6

Transformer Oil, Hydrocarbon 0.039 0.7

561 Silicon Transformer Fluid 0.005 28,100 100

Fuel Oil, Heavy 0.035 1.7

Crude Oil 0.0335 2.8

Lube Oil 0.039 0.7

Douglas Fir Plywood 0.01082 10,900 100

User Specified Value Enter Value Enter Value

Reference: SFPE Handbook of Fire Protection Engineering , 3rd Edition, 2002, Page 3-26.

42,600

46,000

Enter Value

43,500

43,000

46,000

39,700

44,700

43,700

43,200

44,400

40,800

25,800

26,200

34,200

User Specified Value

H-9
CHAPTER 5

ESTIMATING RADIANT HEAT FLUX FROM FIRE

TO A TARGET FUEL AT GROUND LEVEL

UNDER WIND-FREE CONDITIONS

SOLID FLAME RADIATION MODEL

Version 1805.1

(SI Units)

ESTIMATING RADIATIVE HEAT FLUX TO A TARGET FUEL Reference: SFPE Handbook of Fire Protection Engineering , 3rd Edition, 2002, Page 3-276.

SOLID FLAME RADIATION MODEL

q" = EF1->2

Where

q" = incident radiative heat flux on the target (kW/m2

)

E = emissive power of the pool fire flame (kW/m2

)

F1->2 = view factor between target and the flame

Pool Fire Diameter Calculation

Adike =D2

/4

D = √(4Adike/)

Where

Adike = surface area of pool fire (m2

) 

D = pool fire diamter (m) 

D = 1.14 m

Emissive Power Calculation

E = 58 (10-0.00823 D)

Where

E = emissive power of the pool fire flame (kW/m2

)

D = diameter of the pool fire (m)

E = 56.76 kW/m2

View Factor Calculation

F1->2,H = (B-1/S)/(B2

-1)1/2 tan-1 ((B+1) (S-1)/(B-1)(S+1))1/2-(A-1/S)/((A2-1)1/2) tan-1 ((A+1)(S-1)/(A-1)(S+1))1/2

F1->2,V = 1/(S) tan-1(h/(S2

-1)1/2)-(h/S) tan-1 ((S-1)/(S+1))1/2 + Ah/S(A2-1)1/2 tan-1 ((A+1)(S-1)/(A-1)(S+1))1/2

A = (h2+S2+1)/2S

B = (1+S2

)/2S

S = 2R/D

h = 2Hf/D

F1->2,max = √(F2

1->2,H + F21->2,V)

Where

F1->2,H = horizontal view factor 

F1->2,V = vertical view factor 

F1->2,max = maximum view factor

R = distance from center of the pool fire to edge of the target (m)

Hf

 = height of the pool fire flame (m)

D = pool fire diameter (m)

H-10
CHAPTER 5

ESTIMATING RADIANT HEAT FLUX FROM FIRE

TO A TARGET FUEL AT GROUND LEVEL

UNDER WIND-FREE CONDITIONS

SOLID FLAME RADIATION MODEL

Version 1805.1

(SI Units)

Distance from Center of the Pool Fire to Edge of the Target Calculation

R = L + D/2 

Where

R = distance from center of the pool fire to edge of the target (m) 

L = distance between pool fire and target (m)

D = pool fire diameter (m)

R = L+D/2 = 2.270 m

Heat Release Rate Calculation

Q = m"Hc,eff (1 - e-kD

) Adike

Where

Q = pool fire heat release rate (kW)

m" = mass burning rate of fuel per unit surface area (kg/m2

-sec)

Hc = effective heat of combustion of fuel (kJ/kg)

Adike = surface area of pool fire (area involved in vaporization) (m2

)

k= empirical constant (m-1)

D = diameter of pool fire (diameter involved in vaporization, circular pool is assumed) (m)

Q = #VALUE! kW

Pool Fire Flame Height Calculation

Hf = 0.235 Q2/5-1.02 D

Where

Hf = flame height (m)

Q = heat release rate of fire (kW)

D = fire diameter (m)

Hf = 2.479 m

S = 2R/D = 3.983

h = 2Hf/D = 4.350

A = (h2

+S2+1)/2S = 4.493

B = (1+S2

)/2S = 2.117

FH1 FH2 FH3 FH4 F1->2,H

F1->2,H = 0.053 0.318 0.912 0.308 0.770 0.053

F1->2,V = 0.113 FV1 FV2 FV3 FV4 F1->2,V

F1->2, max = √(F2

1->2,H + F21->2,V) = 0.125 0.068 0.229 0.357 0.770 0.113

H-11
CHAPTER 5

ESTIMATING RADIANT HEAT FLUX FROM FIRE

TO A TARGET FUEL AT GROUND LEVEL

UNDER WIND-FREE CONDITIONS

SOLID FLAME RADIATION MODEL

Version 1805.1

(SI Units)

RADIATIVE HEAT FLUX CALCULATION

q" = EF1->2

Answer q" = 7.10 kW/m2 0.63 Btu/ft2

-sec

Prepared by: Date:

Checked by: Date:

NOTE:

The above calculations are based on principles developed in the SFPE Handbook of Fire Protection Engineering, 3 rd Edition, 2002. Calculations are based on certain 

assumptions and have inherent limitations. The results of such calculations may or may not have reasonable predictive capabilities for a given situation and should only be 

interpreted by an informed user. Although each calculation in the spreadsheet has been verified with the results of hand calculation, there is no absolute guarantee of the 

accuracy of these calculations. Any questions, comments, concerns and suggestions or to report an error(s) in the spreadsheets, please send an email to 

David.Stroup@nrc.gov or Naeem.Iqbal@nrc.gov.

Organization:

Additional Information:

Organization:

H-12
Cable Tray Fire in Annulus

H-13 

H.4.2 Zone Models (CFAST) 

Geometry: Only the section of the annulus directly enclosing the cables and relevant targets is 

included in a single-compartment simulation. A taller ceiling was included to allow the HGL to 

form well away from the targets, since the much larger volume of the whole annulus would have 

to fill before any HGL would form near the fire source and targets. Horizontal vents on each 

side of the annulus section were included and sized to the full cross-section of the annulus to 

simulate flow from the simulation region to the rest of the annulus. Surfaces of this section of 

the annulus are constructed with concrete of the specified thickness. A screenshot of the 

geometry input for CFAST is shown in Figure H-5. 

Fire: The fire originates near the base of the vertical portion of the cable train and quickly 

spreads to the entire vertical surface (4.6 m (15 ft) high by 0.6 m (2 ft) wide). With the specified 

HRR of 250 kW/m2

 (NUREG/CR-7010, Volume 1), this results in a peak HRR of approximately 

945 kW. To determine the duration of the fire, it is calculated that 120 cables per tray multiplied 

by 0.4 kg/m equals 48 kg/m total mass per unit length of tray. One-third (0.33) of this mass has 

been determined to be combustible plastic, or 15.8 kg/m. Since the tray is 0.6 m (24 in) wide, 

the mass of combustibles per unit area of burning surface is 15.8/0.6=26.3 kg/m2

. The specified 

heat of combustion for PE/PVC is 16,000 kJ/kg (NUREG/CR-7010, Volume 1); thus, the 

combustible “load” is 420,800 kJ/m2

. Using the specified HRR per unit area, the duration of the 

fire at any particular location along the tray is 420,800/250=1,683 s. A screenshot of the fire 

input for CFAST is shown in Figure H-6. 

Cables: One of the objectives of the calculation is to estimate the potential damage to the 

cables within the redundant train. CFAST calculates target temperature using a 1-D heat 

transfer calculation into a rectangular target. In this simulation, the cables are modeled with the 

uniform thermal properties given above. Following the Thermally-Induced Electrical Failure 

(THIEF) methodology in NUREG/CR-6931, Vol. 3, electrical functionality is lost when the 

temperature just inside the 1.5 mm (0.06 in) jacket reaches 200 °C (392 °F). Thus, the target 

thickness is specified to be 3 mm (0.12 in) so that the calculated center temperature of the 

target represents the temperature of the inside surface of the jacket insulation. No attempt was 

made in the simulation to estimate ignition and spread of the fire over the cables, which is why 

the in-depth heat penetration calculation is focused on a single cable. 

 
Cable Tray Fire in Annulus 

H-14 

Figure H-5. Screenshot showing CFAST Geometry Input Screen. 

Figure H-6. Screenshot showing CFAST Fire Input Screen. 

 
Cable Tray Fire in Annulus

H-15 

H.4.3 CFD Model (FDS) 

Geometry: Only the section of the annulus encompassing the cables and relevant targets is 

included in the computational domain. This volume is 9.6 m (31.5 ft) wide, 2.5 m (8.2 ft) deep, 

and 12.8 m (42 ft) high. Extra depth is needed to accommodate the slight curvature of the 

bounding walls. The top, bottom, and sides of the computational domain are specified as 

“open,” that is, open to an infinitely large volume. Since the volume of the annulus is very large, 

neither smoke build-up nor pressure effects would influence the region near the cables. Both 

the internal and external walls of the annulus are included in the model. Since FDS only allows 

rectilinear obstructions, a series of obstructions 20 cm (7.9 in) thick approximate the curved 

walls. The numerical grid conforms to this “stair-stepped” geometry. 

Fire: The fire ignites near the base of the vertical portion of the cable train near the shielding, or 

inner wall. The spread rates of 25 mm/s in the vertical direction and 0.9 mm/s in the horizontal 

are input by using a feature of FDS whereby a surface is designated as having a fire spread 

over it at a designated rate. In this case, a surface is specified along the side of the vertical tray 

and along the top of the horizontal tray with the respective spread rates. The HRR per fire unit 

area is specified directly and not predicted by the model. As was previously discussed, the 

combustible load and duration of the fire are calculated based on the tray dimensions, number 

of cables per tray, cable mass per unit length, estimated combustible mass, heat of combustion 

for PE/PVC, and HRR per unit area. The combustible “load” is calculated as 420,800 kJ/m2

, 

and the duration of the fire at any particular location along the tray is 1,683 s. FDS accepts as 

input the combustible load as a “surface density” and computes the burn-out of fuel 

automatically. A Smokeview rendering of the FDS simulation is shown in Figure H-7. 

Cables: One of the objectives of the calculation is to estimate the potential damage to the 

cables within the redundant train. FDS is limited to only 1-D heat transfer into either a 

rectangular or cylindrical obstruction. In this simulation, the cables are modeled as 1.5-cm 

cylinders. Following the Thermally-Induced Electrical Failure (THIEF) methodology in 

NUREG/CR-6931, Vol. 3, electrical functionality is lost when the temperature just inside the 1.5-

mm (0.06 in) jacket reaches 200 °C (392 °F). Since the objective of this calculation is to 

estimate time to failure of the redundant cables, ignition and spread of the fire over the second 

set of cables is not considered. The in-depth heat penetration calculation is focused on a single 

cable that is relatively free of its neighbors and that would heat up more rapidly than those 

buried deeper within the pile. 

Smoke Detection: FDS has a smoke detection algorithm that predicts the smoke obscuration 

within the detection chamber based on the smoke concentration and air velocity in the grid cell 

within which the detector is located. The detector itself is not modeled, as it is merely a point 

within the computational domain. The two parameters needed for the model are the 

obscuration at alarm, which is given by the manufacturer, and an empirically determined length 

scale from which a smoke entry time lag is estimated from the outside air velocity. The SFPE 

Handbook provides a nominal value of 1.8 m (5.9 ft) for this length scale. The obscuration at 

alarm is 4.9%/m. 

Sprinkler Activation: FDS uses the conventional Response Time Index (RTI) concept to 

predict sprinkler activation. In this scenario, a steel plate has also been added just above the 

location of the sprinkler to simulate the effect of the actual deflector. Note that the sprinkler 

itself is just a point in the model, and its activation is determined by the time history of the 

temperature and velocity of hot gases within the numerical grid cell in which the sprinkler exists. 
Cable Tray Fire in Annulus 

H-16 

Figure H-7. FDS/Smokeview rendering of the Annulus scenario showing burning cable 

tray. 
Cable Tray Fire in Annulus

H-17 

H.5 Evaluation of Results 

The purpose of the calculations described above is to estimate the potential for damaging the 

redundant cables in tray B during a fire in tray A. The heat release rate profiles developed for a 

fire in the tray A cables are shown in Figure H-8. As previously discussed, a steady peak heat 

release rate is used for the FDTs

 calculations while CFAST and FDS use the same heat release 

rate profile. 

Heat Flux and Temperature 

The results of the simulations are shown in Table H-9. The heat flux calculations from the FDTs 

were used as a scoping analysis to determine if additional analysis was required. Using the 

peak heat release rate as a constant input, the solid flame model provides a worst case result 

for the heat flux of 7.1 kW/m2

. This value suggests a potential for damage to the redundant train 

of cables. A growing fire based on the estimated spread of the fire on the cables was used as 

input to the CFAST and FDS models. Although FDS does have an algorithm to predict flame 

spread, it was decided to use the specified burning and spread rates as given above. As a 

result, the HRR increases fairly rapidly to approximately 700 kW following ignition and the 

spread of the fire upwards, and it continues to increase, but not as rapidly, as the fire spreads 

horizontally. The peak HRR is about 945 kW. 

The heat flux from the burning cable to the redundant cable tray is predicted by CFAST to peak 

just above 2 kW/m2

 and for FDS just below 1.75 kW/m2. This makes sense because the point 

source method of radiation heat transfer employed by CFAST would tend to over-estimate the 

heat flux when the target is relatively close to the fire, as in this example. The predicted interior 

cable temperatures predicted by both models are very similar. The temperature rises to 

approximately 95 °C (203 °F) in the CFAST simulation and 87 °C (189 °F) in the FDS 

simulation, well below the damage temperature. 

Figure H-8 Heat Release Rates Used by the FDTs, CFAST and FDS for the Cable Tray 

Fire Scenario. 

0

100

200

300

400

500

600

700

800

900

1000

0 600 1200 1800 2400 3000 3600

HRR (kW)

Time (s)

Heat Release Rate

FDTs

CFAST

FDS
Cable Tray Fire in Annulus 

H-18 

H.5.1 Fire Protection Systems 

FDS does not predict sprinkler activation in this scenario because the link temperature is only 

predicted to increase to approximately 80 °C (176 °F), less than the activation temperature of 

100 °C (212 °F). FDS predicts smoke detection at about 570 s. It should be noted, however, 

that both the sprinkler and smoke detector are located just outside the fire plume. It is expected 

that for a real fire of this type, the natural air movements within such a large space as the 

containment annulus would almost certainly bend the plume from the vertical in a way that 

would be difficult to replicate with a model that is not accounting for the air movements 

throughout the entire facility. 

Figure H-9. Summary of simulation results for the Annulus. 

0

20

40

60

80

100

120

0 600 1200 1800 2400 3000 3600

Temperature (C)

Time (s)

Redundant Cable Temperature

CFAST

FDS

0

1

2

3

4

5

6

7

8

0 600 1200 1800 2400 3000 3600

Heat Flux (kW)

Time (s)

Redundant Cable Heat Flux

FDTs

CFAST

FDS

0

20

40

60

80

100

120

0 600 1200 1800 2400 3000 3600

Temperature (C)

Time (s)

Sprinkler Link Temperature

FDS

0

20

40

60

80

100

0 600 1200 1800 2400 3000 3600

Obscuration (%/m)

Time (s)

Obscuration Inside Smoke Detector

FDS
Cable Tray Fire in Annulus

H-19 

H.5.2 Uncertainty 

For the annulus scenario, the objective is to predict the potential for damage to the redundant 

cables if a fire occurs in the adjacent cable tray. The predicted quantities of interest are the 

heat flux and temperature near the redundant cables. To better quantify whether or not the a 

critical value is exceeded, the uncertainty of the model predictions needs to be calculated 

Chapter 4, Model Uncertainty, provides guidance on how to express the uncertainty of the 

model predictions. For example, consider tray B, where CFAST predicts a peak heat flux of 

approximately 2 kW/m2

. This value is less than the damage criterion of 11 kW/m2, but in the 

NRC/EPRI V&V study (NUREG-1824 (EPRI 1011999)), it was found that CFAST predictions of 

total heat flux are, on average, 19 % less than corresponding measurements, and the relative 

standard deviation of its predictions about this average value is 47 %. This suggests that the 

true value of the heat flux to the cable in this scenario is normally distributed with a mean of 

2/0.81=2.5 kW/m2

 and a standard deviation of 0.47×2.5=1.2 kW/m2. Therefore, the probability 

that the actual heat flux to the cable would exceed 6 kW/m2

 is: 

ܲሺݍሶᇱᇱ ൐ 11ሻ ൌ 1

2 erfc ൬

6 െ 2.5

1.2√2 ൰ ؆ 0.001 (H-1) 

In other words, there is a 0.1 % chance of exceeding the heat flux damage criterion for cable 

tray B, according to the CFAST prediction. Table D-2 lists the model uncertainty of the 

temperature and heat flux predictions for CFAST and FDS. 

The uncertainty analysis can also be applied to the estimate of sprinkler activation. In the 

NRC/EPRI V&V study (NUREG-1824 (EPRI 1011999)), it was found that FDS predictions of 

target temperatures17 are, on average, 2 % higher than the corresponding measurements, and 

that the relative standard deviation of its predictions about this average value is 13 %. This 

suggests that the true value of the link temperature is normally distributed with a mean of 79 °C 

and a standard deviation of 10 °C. Therefore, the probability that the link temperature would 

exceed 100 °C (212 °F) is: 

ܲሺܶ ൐ 100ሻ ൌ 1

2 erfc ൬

100 െ 79

10√2 ൰ ؆ 0.02 (H-2)

H.5.3 Sensitivity 

Referring again to Table D-2, it is unlikely the cables in tray B would be damaged by a fire in 

tray A. In addition to examining the accuracy of the models, as is done in the previous section, 

it is also possible to consider the key input parameter and estimate the increased HRR 

necessary to damage the cables in tray B. Table 4-3 indicates that the heat flux is proportional 

to the HRR to the 4/3 power. Following the methodology in Section 4.4.1, in order to increase 

the predicted heat flux by 4 kW/m2

 to reach 6 kW/m2, the peak HRR, ܳሶ, must increase by 

approximately: 

 

17 A sprinkler link is essentially a “target” with a thermal inertia characterized by the RTI (Response Time 

Index). 
Cable Tray Fire in Annulus 

H-20 

∆ܳሶ ൎ 3

4ܳሶ

ሶݍ∆

ᇱᇱ

ሶᇱᇱݍ

ሶ ൌ 3

4 945

4

2 ൎ 1417 kW (H-3) 

In other words, the peak HRR of the fire would have to be approximately 945+1415=1339 kW to 

cause the cables in tray B to fail. 

Table H-2. Uncertainty analysis of the model predictions for the Annulus scenario. 

Model Quantity Target Predicted 

Value 

Critical 

Value 

Probability 

of Exceeding 

CFAST Heat Flux Cable B 2 kW/m2 6 kW/m2 0.001 

FDS Heat Flux Cable B 1.75 kW/m2 6 kW/m2 0.000 

CFAST Temperature Cable B 95 °C 200 °C 0.000 

FDS Temperature Cable B 95 °C 200 °C 0.000 

H.6 Conclusion 

Using the solid flame model from the FDTs indicates that a fire in one of the cables trays could 

damage the cable in the adjacent tray; however, an additional analysis using CFAST and FDS 

indicates that cable damage is unlikely. While it is not expected that a fire in one cable tray 

within the annulus region of the containment building would damage cables in the adjacent train, 

the models cannot conclusively predict whether a sprinkler would activate above the fire, or at 

what time a smoke detector might activate. These predictions are extremely sensitive to the 

exact locations of the devices relative to a fire plume that may be subject to unpredictable air 

movements throughout the entire facility. Alternative protection strategies, such as shielding 

between trays or other thermal barriers, should be considered to ensure the protection of the 

redundant cables. 

H.7 References 

1. NUREG/CR-6850 (EPRI 1011989), Fire PRA Methodology for Nuclear Power Facilities.

2. NUREG-1805, Fire Dynamics Tools.

3. NUREG-1824 (EPRI 1011999), Verification and Validation of Selected Fire Models for 

Nuclear Power Plant Applications, 2007. 

4. SFPE Handbook, 4th edition, 2008. 

5. NUREG/CR-6931, Cable Response to Live Fire (CAROLFIRE), Volume 2: Cable Fire 

Response Data for Fire Model Improvement. 

6. NUREG/CR-6931, Cable Response to Live Fire (CAROLFIRE), Volume 3: ThermallyInduced Electrical Failure (THIEF) Model. 

7. NFPA 70 (NEC 2008), National Electric Code. 

8. UL 217,. Underwriters Laboratories, Inc., Single Station Fire Alarm Device.

9. NIST SP 1018-5,. Fire Dynamics Simulator (Version 5), Technical Reference Guide, Vol. 3, 

Experimental Validation. 

10. NUREG/CR-7010, Cable Heat Release, Ignition, and Spread In Tray Installations during 

Fire (CHRISTIFIRE), Volume 1: Horizontal Trays. 

11. Schiffiliti, R. and W. Pucci, Fire Modeling, State of the Art, Fire Detection Institute, 1996.
Cable Tray Fire in Annulus

H-21 

12. NIST NCSTAR 1-5B, Experiments and Modeling of Structural Steel Elements Exposed to 

Fire. 

H.8 Attachments 

1. FDS input file: Annulus.fds 

2. CFAST input file: 

a. Cable in Annulus.in 

b. Annulus cable.o 

c. Thermal.csv 

3. FDTs Spreadsheets: 

a. 05.1_Heat_Flux_Calculations_Wind_Free.xls (Point Source) 

b. 05.1_Heat_Flux_Calculations_Wind_Free.xls (Solid Flame 1)