Comparison of CFAST and FDS

for Fire Simulation with the

HDR T51 and T52 Tests

Jason E. Floyd

NISTIR 6866
NISTIR 6866

Comparison of CFAST and FDS

for Fire Simulation with the

HDR T51 and T52 Tests

Jason E. Floyd

Fire Research Division

Building and Fire Research Laboratory

March 2002

U.S. Department of Commerce

Donald L. Evans, Secretary

Technology Administration

Phillip J. Bond, Under Secretary for Technology

National Institute of Standards and Technology

Arden L. Bement, Jr., Director
COMPARISON OF CFAST AND FDS FOR FIRE SIMULATION WITH

THE HDR T51 AND T52 TESTS

ABSTRACT

This work uses three methods: hand calculations, a zone model code (CFAST), and a

computational fluid dynamics code (FDS), to examine two fire tests from the HDR facility, a

decommissioned reactor containment building in Germany. The two tests, T51.23 and T52.14,

used different fuels, propane gas and a hydrocarbon solvent, and occurred in two quite different

locations, low in the containment and just below the containment operating deck, respectively.

The two tests pose different challenges for analysis. The T51.23 test contains a simple fuel,

propane gas premixed with air, but a fairly complex geometry for the fire compartment with

restricted ventilation. The T52.14 test uses a more complex fuel, a hydrocarbon solvent that

burned in an underventilated manner, with a somewhat simpler geometry for the fire

compartment. However, the T52.14 test contained a large atria-like space in close proximity to

the fire room which poses an additional challenge. Together these two tests examine the

suitability of computational methods for calculating fires in structures containing multiple levels

with complex compartment interconnections.
TABLE OF CONTENTS

3.3.1.4 Code Output ........................................ ............... 23

3.3.1.3 Input Files .......................................... ............... 23

3.3.1.2 CFAST Heat Transfer ................................. ............... 22

3.3.1.1 CFAST Mass Transfer ................................ ............... 21

3.3.1 Code Description .................................... ............... 20

3.3 CFAST ............................................ ............... 20

3.2.2.6 Warehouse Fire ...................................... ............... 20

3.2.2.5 Tank Farm Fire ...................................... ............... 20

3.2.2.4 Flashover .......................................... ............... 19

3.2.2.3 Hangar Fire ......................................... ............... 19

3.2.2.2 Backdraft .......................................... ............... 18

3.2.2.1 Open Plumes ....................................... ............... 18

3.2.2 Summary of NIST Validation Efforts ..................... ............... 18

3.2.1.7 Output Options ...................................... ............... 17

3.2.1.6 Input Files .......................................... ............... 17

3.2.1.5 Boundary Conditions ................................. ............... 17

3.2.1.4 Heat Transfer Submodels .............................. ............... 16

3.2.1.3 Combustion ........................................ ............... 16

3.2.1.2 Turbulence ......................................... ............... 15

3.2.1.1 Solution Algorithm ................................... ............... 15

3.2.1 Code Description and History ........................... ............... 14

3.2 Fire Dynamics Simulator .............................. ............... 14

3.1.2.2 Integral Analysis ..................................... ............... 12

3.1.2.1 Chen-Rodi Correlations ............................... ............... 12

3.1.2 Buoyant Axisymmetric Plume Analysis ................... ............... 10

3.1.1.2 Single Layer Compartment Fire ......................... ................ 9

3.1.1.1 Two Layer Compartment Fire ........................... ................ 7

3.1.1 Fire Room Computations .............................. ................ 7

3.1 Hand Calculations ................................... ................ 7

3.0 OVERVIEW OF CALCULATIONAL METHODS .......... ................ 7

2.4 Regulatory Issues .................................... ................ 5

2.3 Issues Regarding Human Factors in Computer Code Applications ................ 4

2.2 Mass Flow and Heat Transfer Issues ...................... ................ 2

2.1 Combustion-Related Issues ............................. ................ 2

2.0 OPEN ISSUES IN FIRE MODELING .................... ................ 2

1.0 INTRODUCTION ................................... ................ 1

LIST OF FIGURES ........................................ ............... vii

LIST OF TABLES ......................................... ................ vi

ii
5.2.3 Hand Calculations ................................... ............... 164

5.2.2.3 Compartment Definitions .............................. ............... 43

5.2.2.2 Combustion Related Input Cards ......................... ............... 43

5.2.2.1 Overview .......................................... ............... 43

5.2.2 CFAST Models ...................................... ............... 43

5.2.1.4 Wall Boundary Conditions ............................. ............... 43

5.2.1.3 Output Options ...................................... ............... 41

5.2.1.2 Flow Boundary Conditions ............................. ............... 41

5.2.1.1 Geometry .......................................... ............... 40

5.2.1 FDS Model ......................................... ............... 40

5.2 T52.14 SIMULATION ................................ ............... 40

5.1.3 Hand Calculations ................................... ............... 34

5.1.2.2 Compartment Specifications and Compartment Interconnections ............... 39

5.1.2.1 Overview .......................................... ............... 37

5.1.2 CFAST Models ...................................... ............... 37

5.1.1.4 Wall Boundary Conditions ............................. ............... 37

5.1.1.3 Output Options ...................................... ............... 35

5.1.1.2 Flow Boundary Conditions ............................ ............... 35

5.1.1.1 Geometry .......................................... ............... 34

5.1.1 FDS Model ......................................... ............... 34

5.1 T51.23 SIMULATION ................................ ............... 34

5.0 TEST SIMULATIONS ................................ ............... 34

4.3.3 Subtest Selected for Modeling .......................... ............... 33

4.3.2 T52 Fire Source ..................................... ............... 33

4.3.1 Layout of T52 Fire Rooms ............................. ............... 31

4.3 T52 TEST DESCRIPTION ............................. ............... 30

4.2.3 Subtest Selected for Modeling .......................... ............... 30

4.2.2 T51 Fire Source ..................................... ............... 30

4.2.1 Layout of T51 Fire Rooms ............................. ............... 28

4.2 T51 GAS FIRE TEST DESCRIPTION .................... ............... 28

4.1 SUMMARY OF Facility AND FIRE TEST SERIES ......... ............... 27

4.0 HDR FACILITY ..................................... ............... 27

3.3.2.4 Smoke Layer Development ............................. ............... 26

3.3.2.3 Hangar Fire ......................................... ............... 26

3.3.2.2 Wall Heat Transfer Validation .......................... ............... 25

3.3.2.1 Original Validation Study .............................. ............... 24

3.3.2 Summary of NIST Validation Efforts ..................... ............... 23

iii
8.3 FDS .............................................. ............... 92

8.2 CFAST ............................................ ............... 90

8.1 Hand Calculations ................................... ............... 90

8.0 CONCLUSIONS .................................... ............... 90

7.3.3 FDS Calculations .................................... ............... 88

7.3.2 CFAST Calculations .................................. ............... 87

7.3.1 Hand Calculations ................................... ............... 87

7.3 METHOD USABILITY ............................... ............... 87

7.2.3 FDS Calculations .................................... ............... 87

7.2.2 CFAST Calculations .................................. ............... 86

7.2.1 Hand Calculations ................................... ............... 86

7.2 SUMMARY OF T52.14 RESULTS ...................... ............... 86

7.1.3 FDS .............................................. ............... 86

7.1.2 CFAST Calculations .................................. ............... 85

7.1.1 Hand Calculations ................................... ............... 85

7.1 SUMMARY OF T51.23 RESULTS ...................... ............... 85

7.0 SUMMARY OF PERFORMANCES AND USABILITY ...... ............... 85

6.2.4 Intercomparison of All Analysis Methods .................. ............... 83

6.2.3.5 Dome ............................................. ............... 83

6.2.3.4 Lower Hatch ........................................ ............... 82

6.2.3.3 Upper Hatch ........................................ ............... 81

6.2.3.2 Doorway ........................................... ............... 79

6.2.3.1 Fire Room ......................................... ............... 78

6.2.3 T52.14 FDS Results .................................. ............... 78

6.2.2.3 T52.14 CFAST Gas Concentration Results ................. ............... 74

6.2.2.2 T52.14 CFAST Velocity Results ......................... ............... 73

6.2.2.1 T52.14 CFAST Temperature Results ..................... ............... 68

6.2.2 T52.14 CFAST Results ................................ ............... 68

6.2.1 T52.14 Hand Calculations Results ....................... ............... 61

6.2 T52.14 RESULTS ................................... ............... 61

6.1.4 Intercomparison of All Analysis Methods .................. ............... 61

6.1.3.3 Hallway ........................................... ............... 60

6.1.3.2 Doorway ........................................... ............... 57

6.1.3.1 Fire Room ......................................... ............... 56

6.1.3 T51.23 FDS Results .................................. ............... 56

6.1.2.3 T51.23 CFAST Gas Concentration Predictions .............. ............... 54

6.1.2.2 T51.23 CFAST Velocity Predictions ...................... ............... 51

6.1.2.1 T51.23 CFAST Temperature Predictions .................. ............... 47

6.1.2 T51.23 CFAST Results ................................ ............... 47

6.1.1 T51.23 Hand Calculations Results ....................... ............... 46

6.1 T51.23 SIMULATION RESULTS ....................... ............... 46

6.0 RESULTS OF SIMULATIONS ......................... ............... 46

iv
98

10.0 ADDITIONAL REFERENCES

........................................

9.0 WORKS CITED .................................................... 93

v
LIST OF TABLES

Table 6.14: Steady State Fire Room Predictions for All T52.14 Analyses vs. Data ...... ... 84

Table 6.13: T52.14 FDS Results for the Upper Sensor Grid During Fire Peak ......... ... 84

Table 6.12: T52.14 FDS Results for the Lower Hatch During Fire Peak .............. ... 82

Table 6.11: T52.14 FDS Results for the Upper Hatch During Fire Peak .............. ... 82

Table 6.10: T52.14 FDS Results for the Doorway During Fire Peak ................. ... 81

Table 6.9: T52.14 FDS Results for the Fire Room During Fire Peak ................. ... 79

Table 6.8: T52.14 Velocities in Circulation Loop ............................... ... 68

Table 6.7: T52.14 Mass Flow Rates at Key Locations ............................ ... 67

Table 6.6: T52.14 Plume Hand Calculation Results ............................. ... 64

Table 6.5: T52.14 Measure Fire Room Doorway Average Velocities ................ ... 63

Table 6.4: T52.14 Measure Fire Room Doorway Average Temperatures ............. ... 63

Table 6.3: T51.23 Hand Calculation Results vs. Measured Data .................... ... 62

Table 6.2: Steady State Fire Room Predictions for All T51.23 Analyses Compared to Data ... 61

Table 6.1: T51.23 Hand Calculation Results vs. Measured Data .................... ... 46

Table 4.3: Shellsol T Material Properties ..................................... ... 33

Table 4.2: T52 Fire Compartment Dimensions ................................. ... 31

Table 4.1: T51 Fire Compartment Dimensions ................................. ... 29

Table 3.3: CFAST Validation Results for Mass Flow Rates. ....................... ... 25

Table 3.2: CFAST Validation Results for O2 and CO2 Concentrations ............... ... 25

Table 3.1: CFAST Validation Results for Upper Layer Peak Temperature ............ ... 24

Table 2.1: Fire Simulation Accuracy Criteria .................................. .... 6

vi
LIST OF FIGURES

Figure 6.26: T52.14 T52.14 +39 m Sensor Grid Average Velocities ................. ... 66

Figure 6.25: T52.14 +31 m Sensor Grid Average Velocities ....................... ... 65

Figure 6.24: T52.14 +39 m Sensor Grid Average Temperatures .................... ... 65

Figure 6.23: T52.14 +31 m Sensor Grid Average Temperatures .................... ... 64

Figure 6.22: T51.23 FDS Hallway Temperature Profiles .......................... ... 60

Figure 6.21: T51.23 FDS Results for CG4642 ................................. ... 60

Figure 6.20: T51.23 Doorway Time Averaged Velocity Contours for FDS v2.0α ....... ... 59

Figure 6.19: T51.23 Doorway Time Averaged Velocity Contours for FDS v1.0 ........ ... 59

Figure 6.18: T51.23 FDS Doorway Temperature Profile .......................... ... 58

Figure 6.17: T51.23 FDS Results for CT4543 .................................. ... 58

Figure 6.16: T51.23 FDS Results for CT4523 .................................. ... 57

Figure 6.15 T51.23 FDS Results for CT4511 .................................. ... 56

Figure 6.14: T51.23 Carbon Dioxide Concentration in the Hallway, Measured vs. CFAST ... 55

Figure 6.13: T51.23 Carbon Dioxide Concentration in the Doorway, Measured vs. 55

CFAST .................................................... ...

Figure 6.12: T51.23 Oxygen Concentration in the Upper Doorway, Measured vs. CFAST ... 54

Figure 6.11: T51.23 Velocity in Main Staircase 1.600/1.700 Hatch, Measured vs. CFAST ... 53

Figure 6.10: T51.23 Lower Hallway Velocity, Measured vs. CFAST ................ ... 53

Figure 6.9: T51.23 Upper Hallway Velocity, Measured vs. CFAST ................. ... 52

Figure 6.8: T51.23 Doorway Velocities, Measured vs. CFAST ..................... ... 52

Figure 6.7: T51.23 Level 1.600 Spiral Staircase Temperatures, Measured vs. CFAST ... ... 51

Figure 6.6: T51.23 Dome Temperatures, Measured vs. CFAST .................... ... 50

Figure 6.5: T51.23 Level 1.600 Main Staircase Temperatures, Measured vs. CFAST .... ... 50

Figure 6.4: T51.23 Hallway Lower Layer Temperatures, Measured vs. CFAST ........ ... 49

Figure 6.3: T51.23 Hallway Upper Layer Temperatures, Measured vs. CFAST ........ ... 49

Figure 6.2: T51.23 Fire Room Lower Layer Temperatures, Measured vs. CFAST ...... ... 48

Figure 6.1: T51.23 Fire Room Upper Layer Temperatures, Measured vs. CFAST ....... ... 48

Figure 5.4: CFAST Compartment Layout for T52.14 Model C ..................... ... 44

42

Figure 5.3: T52.14 FDS Nodalization for Fire Level+Dome Input Geometry with

Cutaway to Show Hatch Connection to Dome ........................ ...

Figure 5.2: CFAST Model D Compartment Layout ............................. ... 39

Figure 5.1: T51.23 FDS Nodalization ........................................ ... 36

Figure 4.7: T52.14 Burning Rate and Test Phase Definitions ...................... ... 33

Figure 4.6: T52 Vertical CX ............................................... ... 32

Figure 4.5: T52 Horizontal CX ............................................. ... 32

Figure 4.4: T52 Fire Floor (1.900 Level) ..................................... ... 31

Figure 4.3: T51 Fire Room + Doorway ....................................... ... 29

Figure 4.2: T51 Fire Floor (1.400 Level) ..................................... ... 28

Figure 4.1: HDR Facility and Fire Test Locations ............................... ... 27

Figure 3.3: Buoyant, Axisymmetric Plume .................................... ... 11

Figure 3.2: Compartment Fire with a Single Layers (No Distinct Thermocline) ........ ... 10

Figure 3.1: Compartment Fire with Two Layers (Distinct Thermocline) .............. .... 8

vii
Figure 6.40: T52.14 FDS Results for Doorway Velocity Profile .................... ... 80

Figure 6.39: T52.14 FDS Results for Doorway Temperature Profile ................. ... 80

Figure 6.38: T52.14 FDS Results for CT9606 .................................. ... 78

Figure 6.37: T52.14 CO2, in Upward Flow Path 1.700 Level, Measured vs. CFAST ..... ... 77

77

Figure 6.36: T52.14 CO2 Concentration at the Dome Hemispherical Head Over the Fire

Room, Measured vs. CFAST .................................... ...

Figure 6.35: T52.14 Doorway Upper Layer O2, CO2, and CO, Measured vs. CFAST .... ... 75

75

Figure 6.34: T52.14 Dome to Level 1.900 by Main Staircase Velocities, Measured vs.

CFAST .................................................... ...

Figure 6.33: T52.14 Fire Level to Dome Velocities, Measured vs. CFAST ............ ... 74

Figure 6.32: T52.14 Doorway Layer Velocities, Measured vs. CFAST ............... ... 73

Figure 6.31: T52.14 Level 1.600 Temps Near Spiral Staircase, Measured vs. CFAST .... ... 72

Figure 6.30: T52.14 Upper Sensor Grid Temperatures, Measured vs. CFAST .......... ... 72

Figure 6.29: T52.14 Fire Level Hatch Upper Layer Temperatures, Measured vs. CFAST . ... 71

Figure 6.28: T52.14 CFAST Predicted Layer Heights ............................ ... 70

Figure 6.27: T52.14 Fire Room Temperatures, Measured vs. CFAST ................ ... 69

viii
1.0 INTRODUCTION

This work examines the predictive capabilities of three methods*: hand calculations1,2; CFAST,

the Consolidated model of Fire growth And Smoke Transport3; and FDS, the Fire Dynamics

Simulator4 . A brief description of each of the methods will be given. Then the simulation

results will be compared against test data from two fire experiments performed in the HDR test

facility5(Nowlen, 1995), the containment building from a decommissioned German nuclear

reactor. The first experiment is the T51.23 gas fire experiment which involved a 1 MW propane

gas fire low in the containment building. The second experiment is the T52.14 oil pool fire

experiment which was a 3 MW oil fire high in the containment building.

The following is a brief discussion of the contents of the remainder this report:

Chapter 2 provides background information on some of the open issues with regards to fire

modeling. 

Chapter 3 gives a brief overview of the three methods used in this report.

Chapter 4 gives a brief description of the HDR facility and the fire experiments followed by an

overview of the T51.23 and T52.14 tests.

Chapter 5 presents the development of the input files for the two HDR tests for the CFAST and

FDS simulations as well as the approach taken for of the hand calculations.

Chapter 6 compares the results of the hand calculations and the CFAST and FDS simulations

with the HDR measured data.

Chapter 7 summarizes the performance of the calculational results and the author’s perception of

the usability of the different methods.

Chapter 8 draws conclusions of the observed performance of each of the three computational

methods with recommendations for future work.

*Certain commercial products are mentioned in this report in order to specify adequately the

equipment used. Such identification does not imply recommendation or endorsement by the

National Institute of Standards and Technology, nor does it imply that the equipment or products

are necessarily the best available for the purpose.

1
2.0 OPEN ISSUES IN FIRE MODELING

Current fire simulation tools have a number of open issues involving modeling assumptions and

approximations that should be considered before they are accepted for risk prediction. Some of

these open issues are identified in this subsection.

2.1 Combustion-Related Issues

When simulating the effects of a fire on a structure and/or its inhabitants, it should be obvious

that the success of such a simulation is highly dependent on the successful specification of the

fire source. Fires are a very complex phenomena. For many real-life fire sources, such as

furniture or spilled organic fluids, the evolution of a fire is a result of a complex feedback

interaction between the condensed phase and the gas phase of the fuel.

Fire codes are currently unable to perform more than simple, correlation-based computations for

fire growth6. Rather than actually calculate the growth of the fire, it is typically left to the user to

specify the time-dependent fire source explicitly in an input file. For many common items of

furniture and for some common organic liquid fuels researchers have performed experiments to

measure the burning rate of these items. However, given that the feedback between a fire and its

fuel source is greatly dependent on the compartment in which the fire is located, these

predetermined fire growth curves are not always applicable.

Another aspect of defining the fire source, is defining how the source combusts. Depending on

available oxygen, fuel composition, fuel type, and temperatures reached, the resulting

combustion products can differ widely from one fire to another both in terms of the numbers of

chemical species produced and in the relative amounts. Unfortunately, for those who wish to

calculate combustion product formation, the chemical reactions that take place during a fire are

very complex and numerous. For example, to completely model methane combustion requires a

score of reaction equations7. Solving such a large system of equations is not feasible to do for

large structures, so simplifications must be made. Again, many fire codes make very simplistic

assumptions regarding combustion products that tend to fail during highly underventilated

combustion. This is especially unfortunate as it is during underventilated combustion that large

quantities of lethal carbon monoxide are produced and transported throughout a structure. It is

these products that are responsible for most, 76 %, of the deaths due to fire8.

2.2 Mass Flow and Heat Transfer Issues

There are essentially two classes of software tools used to model fires: control volume codes and

field models. Control volume codes create a control volume for each room or subset of rooms in

a structure. Field models create many nodes to explicitly represent a structure or subset of a

structure with a finite-differenced computational grid. In this work, one computer code of each

class has been used. CFAST and hand computations are the first type, and FDS is the second

type. Both classes of models have a number of generic open issues, some of which are discussed

herein.

2
In a control volume code, the flow field is not explicitly solved for. Rather, correlations and

basic fluid dynamics principles, such as Bernoilli’s Equation, are used to generate the mass flow

between compartments. Correlations are developed by a combination of experimental results and

analysis of a particular type of mass transfer from first principles. As such, very complex flow

fields tend not to be covered by correlations.

One such subset of flow geometries is large, area aspect ratio compartments which include

hallways, vertical shafts, and atria. In a hallway, the long transport times for species to move

from one end to another result in large changes in conditions along the length of a hall which is

contrary to a control volume approach which assumes uniform conditions throughout a

compartment. Vertical flows in control volume codes are mostly handled by some form of

plume correlation which attempts to calculate the entrainment caused by the flow. However,

these plume correlations are developed from either free plumes or wall/corner plumes. In a long

vertical shaft a plume can assume a variety of flow conditions which are not handled by

traditional correlations9

. A plume can either act like a free plume, hug one wall of the shaft with

a descending plume on the other side, rotate around the shaft in a random manner along with a

descending plume, or completely fill the shaft. Furthermore, if the plume continues to support

combustion a buoyancy enhancement effect will arise. While integral models have been

developed to handle free plumes with combustion10, this author has been unable to locate any

such models for confined plumes.

A second generic problem area for control volume codes is underventilated combustion. The

very nature of a control volume approach homogenizes the spatially dependent gas

concentrations in a compartment. As such only simplistic models of combustion are possible

which will not accurately capture the true behavior which depends on local concentrations and

temperatures. In a control volume code, the effects of a burning gas layer will be averaged over

its control volume when in fact some of the effects would be localized. This affects combustion

product formation, convective heat transfer due to high local temperatures in the prototype versus

lower average temperatures in the model, and radiation heat transfer due to an intense local

source in the prototype versus a more diffuse, global source of radiation in the model.

Lastly, heat transfer to surfaces is often difficult for a control volume code to properly account

for. Since the flow field in a compartment is not being calculated, convective heat transfer to the

walls can only be determined by the use of simple correlations using heat transfer coefficients.

These correlations tend to be based on natural convention correlations for flat horizontal plates

and flat vertical plates, e.g. ceilings/floors and walls. As such, significant errors can exist due to

surface orientations and the actual compartment flow field so that either too much or too little

heat transfer occurs to surfaces. Radiation heat transfer in control volume codes can only be

handled by simple calculations as a control volume approach removes geometric information

about the relative orientations of a compartment's surfaces. Since most rooms tend to be

rectangular parallelepipeds, this can typically be accounted for. However, in oddly shaped rooms

or for the radiant heat flux on a particular object or objects in a room, simple correlations based

on rectangular rooms will not accurately calculate the heat transfer. 

3
Field models have their own generic issues. As with control volume models, the complex

chemistry of a fire means that combustion models tend to be simple and in underventilated

conditions may not function correctly. Since field models actually calculate the flow field,

simulations of smoke propagation in hallways and vertical shafts, in theory, should not pose a

problem. However, depending on the codes ability to resolve the eddy structures in fire driven

flow, the entrainment into a hallway or shaft flow may not be correctly calculated. Furthermore,

depending on the resolution of the noding, correlations for wall heat transfer may still be

required. Lastly, since field models preserve geometric information, radiation heat transfer can

be calculated from first principles using methods such as ray tracing. However, these methods

are computationally expensive and tend to be simplified to avoid lengthy calculation times. As

such, interactions such as absorption/radiation by soot or wall-to-wall and wall-to-gas

interactions may be simplified or omitted altogether. Radiation calculations are also hindered by

the ability to correctly determine the local soot concentrations due to simplifications in the

combustion model. For small fires this may not be an issue, but for large fires that reach

flashover, radiation heat transfer becomes a critical phenomena.

2.3 Issues Regarding Human Factors in Computer Code Applications

From the author's experience, a software program will only become a useful tool to the typical

user if the user comprehends the software, its inputs, and its outputs. If a potential user does not

understand the software it will not be used at all, or worse, it will be used in an incorrect manner

giving false or misleading results.

The first step to using a computational tool for safety analysis is to understand the tool itself.

The user must obtain an understanding of the underlying assumptions used in developing the

tool. The user must also gain an understanding of the tool's limitations. Without this

understanding, a user may unknowingly apply the tool to a scenario beyond its capabilities. A

well-written user's manual that discusses the theories, assumptions, and algorithms related to the

code's development and execution as well as a discussion of known limitations of the code can

alleviate the problem of misapplying the tool (Bukowski, 1995). However, a well documented

discussion of the tool’s theory and limitations will only be useful if the user has the educational

background and/or practical experience with which to comprehend the theory.

Once the user understands the tool and has determined its suitability for the problem at hand, the

user must then apply the tool to the problem. Fires in structures are complex. There are many

things that must be defined by the user such as the fuel source, the geometric layout, and heat

transfer surfaces. This process can be aided by well written documentation. A well written input

manual containing detailed examples for a variety of fires and structures is an immense aid to a

user. These examples should describe in detail what is being modeled and how the real-life

prototype is transformed into a computer model. An input preprocessor, preferably a graphical

one, is also a valuable tool, especially if it is capable of flagging potential errors in the user's

input. Finally, the user must be able to easily use the results given by the model. This may seem

to be a simple matter, but again, the software's authors can make this easy or very difficult. In

general, the more portable the output format, the easier it will be to make comparisons to

measured data or to predictions made by other methods of analysis. This can be done by either

4
having a user friendly post-processor that can extract data from an output file and convert it to a

portable form, or to have the output file in a common data format such as comma-delimited

ASCII text, PLOT3D © format , or Microsoft Excel © format.

Both CFAST and FDS have postprocessors for viewing output data. However, in their current

incarnations extracting specific subsets of the output data for use with other data analysis tools

can be a difficult task. 

2.4 Validation Issues

The purpose of using a computational fire model is to make some determination about the effect

a fire will have on a structure and its inhabitants. In the structure design process one wishes to

make this determination in order to assess aspects of the fire safety of the structure. If the

analysis is to be used to demonstrate to a regulator or to the public that the structure has some

level of safety, then the tool used will require some form of approval for use11

. That is, by some

method it must be accepted by the users of the tool, the regulators, and the general public that the

particular analysis method is well suited to the problem for its results to be meaningful in terms

of a risk analysis.

To gain approval, some form of benchmarking will be needed. The analysis method will need to

be evaluated through a series of blind predictions6. That is, a set of standard problems will need

to be defined by either a regulatory organization or a standards setting body such as ISO or

ASTM. These standard problems should cover both a variety of fire types and structures as well

as contain features known to be difficult to solve for such as long, vertical shafts or atria. In

addition to defining the standard problems, what constitutes acceptable performance by a method

will need to be defined and what constitutes acceptable uncertainty by a method will also need to

be specified.

To date, neither acceptance criteria nor a standard set of problems has been defined. As a result,

it is difficult to assess the performance of a code when compared to measured data. What these

criteria should be is not an easy thing to define. For example, a criteria could be to predict gas

concentrations within 10 %. However, for toxic gasses it is the net exposure, an integration of

time and concentration, which determines harmful effects. Therefore a more appropriate criteria

might be the net amount of a toxic gas exposure to a reference person at the location of interest.

In a similar manner a simple error band for temperature is not necessarily sufficient since when

including a suppression system in a simulation, it is the time that a location reaches an activation

temperature that is important. With a simple temperature error band, a model could be within the

band but predict either far too early or far too late an activation of a suppression system.

During the fire test series in the HDR facility, contemporary computer codes were used to

simulate some of the fire experiments. In order to evaluate the performance of those codes a

panel of nuclear safety and fire protection experts developed a set of guidelines to be used during

the evaluation12. Table 2.1 gives these guidelines. The ± 20 °C guideline for far-field

temperatures was added to account for regions which see little temperature increase from a fire.

In this case, it makes little sense to place an accuracy of 20 % on a room whose temperature

5
never exceeds 50 °C. In the absence of other guidelines, this table will be used to judge the

performance of the calculations performed in this work. The guidelines in Table 2.1 were

developed with the following three issues in mind:

1. Maintaining structural integrity of safety-related structures and components

2. Maintaining functionality of safety-related electrical and mechanical facilities

3. Maintain usability of ventilation systems and keep emergency/intervention routes

smoke free (maintain their availability for use).

Table 2.1: Fire Simulation Accuracy Criteria

±20 % or ±20 °C

±10-15 %

±20 %

±15-20 %

±20 %

±30-50 %

±30-50 %

±30-50 %

±5 minutes

Temperature of gasses

Temperature of structures

Pressure difference

Gas concentrations

Aerosols

Energy and mass flows

Velocities

Layer Heights

Event timing

Far-Field

±15 %

±10-15 %

±20 %

±30-50 %

±30-50 %

±5 minutes

Temperature of hot gasses, plume, etc.

Temperature of hot structures

Pressure

Fire Properties

Layer height

Event timing

Near-Field

Location Parameter Desired Accuracy

The above table divides a fire simulation into two regions: the near-field and the far-field. The

near-field is considered to be the compartment in which the fire occurs and any adjoining

compartments in the structure being modeled. In this region the high temperatures and heat

fluxes must be known in order to evaluate the potential for damage to the structure and to any

equipment located in the near-field. The far-field is considered to be the remainder of the

structure. Temperatures in the far field are not as likely to reach very high levels, therefore, the

concern in the far-field is not temperature. The concern in the far-field is human survivability

which is determined by the concentration of toxic gasses and the damage caused by the clogging

of building ventilation systems and equipment cooling systems with soot. It is important,

therefore, that an analysis method be capable of making sufficiently accurate predictions in both

of these regions.

The above table is used in Chapter 6 to discuss the results of the models presented in Chapter 5.

The table is also used to draw conclusions in Chapters 7 and 8. While this table does not

necessarily represent the needed performance-based criteria, in lieu of such criteria it is used as a

basis for rational judgment of predictive outcomes.

6
3.0 OVERVIEW OF CALCULATIONAL METHODS

This chapter briefly discuss the three calculation methods used for this work. More extensive

discussions of these methods can be found in the references noted for each of the methods. For

example, both the CFAST and FDS user manuals are available through the National Technical

Information Service. This chapter will not, therefore, go into great detail about the inner

workings of the methods

3.1 Hand Calculations

In this section, methods for 'hand calculating' basic quantities related to compartment fires are

discussed. These methods are computationally simple, and can be performed with either a hand

calculator, spreadsheet, or a math toolkit such as MatLab ® or Mathematica ®. Hand

calculations typically have the advantage of being transparent to the underlying physics being

modeled and fast to execute. In this manner hand calculations can be used to quickly generate

results that are easily understood and easily presented to others, i.e. the results do not require

sophisticated plotting software like the results of a field model calculation might require.

Since the governing equations for heat and mass transfer in a series of connected compartments

with multiple heat transfer surfaces are complex, numerous simplifications must be made in

order to perform a hand calculation. As a result of these simplifications, hand calculations

should not be expected to yield the same quality of results as would be anticipated from a more

rigorous computational method. However, one would desire that the results from hand

calculations be good enough to at a minimum determine whether or not a detailed analysis is

warranted for a given fire. With this in mind, in this author's opinion, if a hand computation was

accurate to within twice the deviation desired for zone or field model calculations, then it would

be useful as tool for allocating computational resources for fire analysis. That is, fast hand

computations could be used to quickly determine which of many possible fire scenarios warrant

the expense and time of a more rigorous analysis.

3.1.1 Fire Room Computations

Two different methods for computing basic parameters of a compartment fire are described in

this subsection1. The first method applies to fires in which a distinct thermocline exists in the

fire compartment. The second method is for post-flashover compartments in which no distinct

thermocline exists.

3.1.1.1 Two Layer Compartment Fire

Karlsson and Quintiere

1

 also discuss a method with which one can calculate the mass and energy

flux at a doorway to a compartment with two distinct layers. The method assumes that the flow

in the doorway can be divided into three regions. The first region is outward flow, the second

region is inward flow above the layer interface, and the final region is inward flow below the

layer interface. Mass flow equations for each region are generated by applying Bernoulli's

equation across the doorway along with a simple loss coefficient for the doorway. The mass flow

7
equations in combination with conservation of mass at the doorway, conservation of energy for

the upper layer, and an equation of state can be used to find the fire compartment temperature

and doorway mass flux. Figure 3.1 shows a diagram of such a compartment.

Upper Layer

Lower Layer

, ρ T a

a

, ρ T g

g

m

.

g

m

.

a1

m

.

a2

H0

HD

HN

Figure 3.1: Compartment Fire with Two Layers (Distinct Thermocline)

The equations to be solved are:

Region 1 Mass Flow:

*

mg =

2

3 CdWqg

2 qa−qg g

qg

(H0 − HN)

3

2

(1)

Region 2 Mass Flow:

*

ma1 =

2

3CdWqa

2 qa−qg g

qa

(HN − HD)

3

2

(2)

Region 3 Mass Flow:

*

ma2 = C dWH D q a

2 H N−H D

qa −qg g

qa

(3)

Continuity, Equation of State, and Upper Layer Energy Balance:

*

mg =

*

ma1 +

*

ma2

(4)

q =

MP

RT

(5)

*

Q= DT(

*

mg cp + hkAT)

(6)

8
Where the variables have the following definitions:

Upper layer inward mass flow (kg/s) *

ma1 =

Upper layer outward mass flow W = Doorway width (m)

(kg/s)

*

mg =

M = Gas molar mass (kg/mol) T = Temperature (K)

Upper layer temperature - ambient

temperature (K)

Wall heat transfer coefficient DT =

(W/m2⋅K)

hk =

HN = Neutral plane (m) R = Real gas constant (J/mol⋅K)

Upper layer gas density (kg/m3 HD = Layer height (m) qg = )

Ambient gas density (kg/m3 H0 = Doorway height (m) qa = )

cp = Specific heat (kJ/kg⋅K) P = Pressure (Pa)

Fire power (W) *

Cd = Doorway loss coefficient Q=

Lower layer inward mass flow

(kg/s)

*

Upper layer wall surface area (m ma2 =

2 AT = )

The continuity equation merely states that the mass flow into the fire room equals the mass flow

out of the fire room. The equation of state is the Real Gas Law. The energy balance states that

the heat input into the upper layer from the fire is equal to the heat losses through the walls of the

fire room plus the energy used to heat the incoming air up to the fire room temperature. By

solving these equations simultaneously, values for the mass flow out of the doorway and the

upper layer temperature can be found.

3.1.1.2 Single Layer Compartment Fire

Karlsson and Quintiere

1

 discuss a method with which one can calculate the mass and energy flux

at a doorway to a well-mixed compartment. The method assumes that the flow in the doorway

can be divided into two regions: an outward flow region and an inward flow region. The first

region is outward flow, and the second region is inward flow which occurs beneath the neutral

plane. Mass flow equations for each region are created by applying Bernoulli's equation across

the doorway along with a simple loss coefficient for the doorway. The mass flow equations in

combination with conservation of mass at the doorway, conservation of energy for the fire room,

and an equation of state can be used to find the fire compartment temperature and doorway mass

flux. Figure 3.2 shows a diagram of such a compartment.

9
, ρ Tg g

m

.

g

m

.

a

H0

HN

, ρ Ta a

Figure 3.2: Compartment Fire with a Single Layer (No Distinct Thermocline)

The equations to be solved are:

Outward Mass Flow:

*

mg =

2

3 CdWqg

2 qa−qg g

qg

(H0 − HN )

3

2

(7)

Inward Mass Flow:

*

ma =

2

3 CdWqa

2 qa−qg g

qa HN

3

2

(8)

Continuity:

*

mg =

*

ma

(9)

The continuity equation merely states that the mass flow into the fire room equals the mass flow

out of the fire room. The equation of state and the heat balance equation are the same as for the

two layer analysis. Variable nomenclature is also the same. By solving these equations

simultaneously, values for the mass flow out of the doorway, the fire room temperature, and the

location of the neutral plane can be found.

3.1.2 Buoyant, Axisymmetric Plume Analysis

This subsection discusses two hand-calculation methods for modeling buoyant, axisymmetric

plumes. The first method uses the Chen-Rodi correlations13. The second method is an integral

plume model developed by the author using Mathematica ®

14. Figure 3.3 shows a diagram of an

axisymmetric plume.

10
ρ , 0 U0

R0

x

r

R

Rρ

U(r)

Ue

x+dx

x

dx

ρ(r)

ρ

a

Virtual Origin

Figure 3.3: Buoyant, Axisymmetric Plume

Where the variables have the following definitions:

Plume density (kg/m d0 = Initial plume diameter (m) 3q = )

Upper layer gas density (kg/m3 R = Plume radius (m) qg = )

Ambient gas density (kg/m3 U = Plume velocity (m/s) qa = )

Initial plume density (kg/m3 Ue = Entrainment Velocity (m/s) q0 = )

U Initial plume velocity (m/s) r = Distance from plume centerline (m) 0 =

Axial distance from virtual origin R0 = Initial plume radius (m)

(m)

x =

11
3.1.2.1 Chen-Rodi Correlations

The Chen-Rodi correlations13 are repeated here for completeness. These correlations predict the

centerline values of axial velocity and density for a buoyant jet as a function of the distance from

the virtual origin of the plume. These correlations are broken into three regimes: a momentum

driven regime, a buoyancy driven regime, and a transition regime between the momentum driven

and the buoyancy driven regimes. In these correlations x is the distance from the virtual origin of

the jet, 0 represents the value at the jet origin, m represents a value along the jet axis, 'a'

represents the ambient condition, and Fr is the jet Froude number given as:

Fr =

U0

2

g2d0

qa−q0

q0

(10)

Momentum Driven for Fr

−

1

2

q o

q a

−

1

4 x

d 0

< 0.5

U m

U 0

= 6 .2

q 0

q a

1

2 x

d 0

−1 (11)

q a −qm

q a −q 0

= 5.0

q 0

q a

−

1

2 x

d 0

−1 (12)

Transition for 0.5 [ Fr

−

1

2

q o

q a

−

1

4 x

d 0

[ 5

U m

U 0

= 7.26Fr

−

1

10

q 0

q a

9

20 x

d 0

−

4

5

(13)

qa −qm

q a−q 0

= 0.44Fr

q0

qa

−

7

16 x

d 0

−

5

4

(14)

Buoyancy Driven for 5 < Fr

−

1

2

q o

q a

−

1

4 x

d 0

U m

U 0

= 3 .50Fr

−

1

3

q0

qa

1

3 x

d 0

−

1

3

(15)

qa −qm

q a−q0

= 9.35Fr

−

1

2

q0

qa

−

1

3 x

d0

−

5

3

(16)

The virtual origin of a jet is obtained by extrapolating the radius of the jet backwards from the jet

source to obtain a zero radius. The virtual origin is given by Papanicolaou15 as 2.56 diameters

based on velocity and 2.51 diameters based on concentration width. For the comparisons made

in this report a value of 2.5 diameters was used.

3.1.2.2 Integral Analysis

A set of equations was derived to yield an integral analysis of jet behavior. This derivation was

based on the derivation performed by Badre10 for computing the rise of radioactive jets. This

derivation assumes axisymmetric, fully turbulent, Boussinesq flow with a hydrostatic pressure

12
distribution. The conservation equations for mass, momentum, and energy are given below16

with being the body forces and being the internal energy:

→F e

Mass: °

S

q

→

U $ n dA = 0

(17)

Momentum: S

→

F = °

S

q

→

U

→

U $ n dA

(18)

Energy:

$

Q −

$

W= °

V

qe dV

(19)

Beginning with Equation 17 a number of simplifications are made. Since the jet is axially

symmetric, there is no tangential velocity component. Equation 17, therefore, simplifies to

d

dx

° qjUj dA = 2oRjqaUe

(20)

where j represents a quantity in the jet, x is the axial direction, and 'a' represents a quantity in the

ambient. The entrainment velocity, Ue, can be represented by an entrainment coefficient, α,

times the centerline velocity of the plume. This coefficient differs depending on whether or not

the jet is momentum or buoyancy dominated. A correlation for α is given by Sneck17 as:

a = a1 +

a2

Fr

= 0.044 +

0.25

Fr

(21)

where Fr is given in Equation 10. Froude numbers were on the order of 100 for the development

of the above correlation.

In Equation 18, there is only an axial component of momentum as the net radial momentum must

be zero due to the axial symmetry. The body force in the case of buoyant flow is the buoyancy

force. 

d

dx

°

S

qjUj

2 dA + °

V

qj − qa g dV = 0

(22)

Lastly, the energy equation, Equation 19, is simplified. The work and heat addition terms are 0.

The energy term consists of enthalpy, kinetic energy, and heat transfer. Since velocities in the

flows of concern are low, kinetic energy is small compared to the enthalpy of the gas in the

plume and can be ignored. Furthermore, the transfer of energy by conduction is ignored by

assuming that density, which is equivalent to temperature, changes are caused solely by

entrainment.

d

dx

°

S

qjhjUj dA = 2oRjqahaUe

(23)

With the assumption that the working fluid is a real gas, the following simplification is made

h = CpT = Cp

P

qRg

=

P

q

c

c−1

(24)

13
As the pressure is assumed to be hydrostatic and the gas in the plume is assumed to be the same

as the product of enthalpy and density cancels in Equation 23 as the ambient gas’s γ is the same

as the plume’s γ.

d

dx

°

S

Uj dA = 2oRjUe

(25)

Lastly, it is assumed that both the velocity and density profiles are Gaussian with the density

profile width increased by a parameter λ which comes from experimental data.

Henderson-Sellers18 gives a value of 1.16 for λ. 

U j

(r) = U j(0 ) e

−

r

R j

2

, q j

(r) = q j(0 )e

−

r

kR j

2

(26)

Equations 20, 22, and 25 along with Equations 21 and 26 constitute a set of integro-differential

equations which can be solved using a variety of simple iterative methods. For this work the

equations were input into Mathematica ® and numerically solved to yield predictions for Uj, Rj,

and rj.

3.2 Fire Dynamics Simulator

3.2.1 Code Description and History

Fire Dynamics Simulator (FDS) is a computational fluid dynamics code written by staff members

of the Building & Fire Research Laboratory at the National Institutes of Standards and

Technology in Gaithersburg, MD. The code has been developed to calculate fire-driven flows

both in enclosures and in the ambient4,19. FDS v1.0 is written in standard Fortran 90, and, thus,

can be run on any platform for which a Fortran 90 compiler exists.

Version 1.0 of FDS was released in 2000, and contained a relatively simple combustion and

radiation model. Version 2.0 is currently under development20,21 and will contain a

mixture-fraction based combustion model22 and a more sophisticated radiation solver23. The FDS

simulations in this work were calculated by a pre-release Version 2.0 and are designated hereafter

as FDS v2.0α. FDS solves a modified form of the Navier-Stokes equations referred to as the

"low Mach number" equations23. The mathematical nature of this modified form allows the use

of a high-speed solver capable of solving transient flows for a large number of nodes in a

relatively short time as opposed to other CFD codes. The Navier-Stokes equations are reduced

from their full form to a thermally-expandable, multi-component perfect gas form that eliminates

acoustic waves (i.e. Mach number << 1). This results in a set of equations with a Poisson

equation for the pressure term. The end result of all this is that a fast Fourier transform method

(FFT) can be used for a direct solution of the pressure equation which typically must be solved in

an iterative fashion in most CFD schemes.

14
3.2.1.1 Solution Algorithm and Restrictions

The governing equations are discretized in space and time. Time differencing takes the form of a

second order, explicit predictor-corrector method. Spatial differences, taken on a uniform

computational grid, are either second order, central differences or upwind differences depending

on the parameter and the local CFL number. The CFL number, Courant-Friedrichs-Lewy, is used

to judge stability of a time-dependent numerical scheme by comparing the transport distance of a

parameter to the grid size25. Scalar parameters are defined at grid cell centers and vector

parameters are defined at cell surfaces in order to create a staggered grid and reduce numerical

diffusion.

The solution algorithm places a number of restrictions on the type of problems that FDS can

solve. Use of the FFT pressure solver requires that the number of grid cells along an axis be of

the form 2

k

3

m

5

n

 where k,m, and n are positive integers4, thus there could be 15 grid cells along an

axis (31

5

1

) but not 14 (217

1

). The low Mach-number assumption requires that flow speeds be less

than a Mach number of 0.3. Only coordinate transforms that are continuous and monotonic can

be used to convert the problem domain to the computational domain. Furthermore the magnitude

of stretching and shrinking in a grid transformation should be limited to avoid computational

instabilities.

3.2.1.2 Turbulence

FDS has two different methods for determining τ, the viscous stress tensor: Direct Numerical

Solution (DNS) and Large Eddy Simulation (LES). DNS requires the use of very small nodes as

it directly calculates the dissipative terms from first principles during the solution process. As

such, DNS is not practical for the large-scale domains seen in compartment fires due to the

impractical number of nodes that would be required. Thus, the DNS method will not be

discussed further.

In a LES calculation, the method of Smagorinski26 is used. In the Smagorinski method, the

viscosity used in the calculation of the stress tensor in the momentum equation is assumed to be

proportional to the magnitude of the local deformation tensor27. That is, LES calculates only the

large-scale eddies and makes assumptions for modeling eddies smaller than the computational

grid. 

Since fire driven flows are driven by the fire plume which is a large-scale eddy structure, this

method works well. Second, since the desired accuracy in flow resolution is not high, use of a

more complex and perhaps more accurate method is not warranted as it would reduce the

computational speed of FDS.

Use of the LES model for turbulence does place limitations on the grid resolution for an input

file. The Smagorinski method assumes that one is resolving adequately the dominant eddies in

the flow field. For a fire-driven flow, this is accomplished if one resolves the plume structure

scale. Thus, for an FDS computation using the LES submodel, the code user must span the

plume length scale with approximately ten nodes, or the maximum node size must approximate

28:

15
L l 0.1

Q

qcpT g

2

5 (27)

Where Q is the heat release rate of the fire and ρ, cp, and T are the ambient gas properties taken at

the ambient conditions.

3.2.1.3 Combustion

FDS v2.0α uses a mixture-fraction concept in modeling combustion. The mixture fraction is a

dimensionless quantity ranging from 0 to 1. It represents the amount of gas at a location that

originally was fuel. Thus, a mixture fraction of 0 would represent pure ambient air and a mixture

fraction of 1 would represent pure fuel. The mixture fraction obeys the same conservation laws

as a gas species, and it can be correlated through state relationships to the local concentrations of

combustion product species as well as the local heat release rate. Thus, the mixture fraction

model incorporates some combustion chemistry as opposed to the original “thermal element

method” used in v1.0. It also uses more physics since both convective and diffusive transport is

being accounted for with the mixture fraction approach as opposed to the solely convective

transport with the prior model.

3.2.1.4 Heat Transfer Submodels

FDS contains three heat transfer submodels: a radiation heat transfer model, a wall heat transfer

model, and a sprinkler model. 

In v2.0α, the radiation heat transfer model uses the finite volume method. In this method the

radiation field is updated at each time step by calculating the local production and absorption of

radiation in each grid cell and propagating that radiation along a number of directional angles

throughout the computational domain. The actual form of the radiation transport equation used

for this solver is analogous to an advection equation. Thus, the radiative solution evolves over

time. With this method, the surface and gas interactions neglected in v1.0 are now included for a

greatly improved prediction in cases where the fire is not the sole significant source of radiation,

such as large fires in small compartments.

The convective heat transfer model for an LES calculation makes use of a mixed convection heat

transfer correlation. For each conducting surface a forced convection heat transfer coefficient

and a natural convection heat transfer coefficient are calculated using flat plate correlations. The

larger of the two is utilized for calculating the heat transfer. In FDS v1.0 only the natural

convection correlation was used which could result in low heat transfer in regions of higher

velocity. 

In the sprinkler submodel, the user specifies surface locations which contain a sprinkler nozzle

along with the activation characteristics of the nozzle. If a nozzle reaches its activation threshold

it inputs droplets of water in a user defined spray pattern into the flow. These droplets are

assigned a size distribution and droplet heat transfer is calculated using evaporative and

convective heat transfer correlations.

16
3.2.1.5 Boundary Conditions

FDS users have access to four flow and five surface boundary conditions. The four flow

conditions are forced vent, passive or open vent, symmetry, and blocked cell. The five surface

conditions are adiabatic, combusting, isothermal, thermally thin wall, and thermally thick wall.

The four flow conditions are defined by the user in the input file as part of the geometry

description. As a default, the problem domain is defined to be closed. The user can create

further blockages by defining rectangular parallelepiped regions to be blocked. At domain

boundaries, the user can define a plane to be a symmetry plane, in which case no flow or heat

transfer is allowed across the surface but flow parallel to the surface is not impeded. A user can

also define a rectangular portion of a domain boundary to be an open boundary. In this case it is

assumed that a vent exists to an infinite reservoir of ambient fluid; outgoing fluid has its pressure

term, H, set to be the stagnation pressure and incoming fluid to 0. For any surface, either a

blocked one or part of the domain boundary, the user can define a rectangular region for which a

fixed velocity or mass flow in or out of the domain is specified.

The first three surface types are self explanatory. The temperature of a thermally thick surface

cell is governed by the 1D heat conduction equation. A thermally thin surface’s temperature is

assumed to be uniform and calculated from the material density, thickness, and specific heat. In

v2.0α a combusting surface can be defined additionally as thermally thick or thin. In this

manner, the influence of surface heat transfer on the pyrolysis rate can be accounted for.

3.2.1.6 Input Files

An FDS input file is an ASCII, card-type, FORTRAN 90 readable file. Each line of the input file

consists of a card declaration, for example OBST to define a blockage, and a comma-delimited

series of variable names and values. FDS currently lacks an input preprocessor; however, any

utility which creates an ASCII file can be used.

3.2.1.7 Output Options

There are six types of output in FDS v2.0α. These are particle files, sensor files, slice files,

dump files, boundary files, and iso-surface files. Each of these can be toggled on or off by the

user along with limited control of the rate of output. The particle file stores particle positions

and temperatures or other user specified parameters at fixed time intervals. This file can be used

to create movies of the flow field and the particles can be used to represent water droplets from

sprinkler systems. Sensor files are created by the user defining a sensor type, such as a

thermocouple or heat flux gauge, and location. The sensor parameters are then dumped to a file

at fixed intervals in time. In this manner the user can simulate test instrumentation or examine in

detail key parameters for a number of fixed points. The slice file stores a single parameter for a

rectangular region of the computational space at fixed time intervals. The dump file is a

complete dump of velocity, temperature, and heat release or other user specified parameters for

the entire computational domain at fixed time intervals. Boundary files dump a surface

parameter such as wall temperature at fixed time intervals. Lastly, iso-surface files dump a set of

17
triangles at fixed time intervals that represents a user defined constant value surface within the

domain, such as the surface of velocity equal to 0 m/s.

An output postprocessor visualization program, called Smokeview29, is available for FDS. This

program is written in OpenGL and, thus, is portable to any platform that can use OpenGL. This

program is mouse driven and allows the user to walk through a 3D geometry, rotate the

geometry, view movies of output files, view contours from dump files, and plot sensors.

3.2.2 Summary of NIST Validation Efforts

FDS was tested against both experiments and correlations. A discussion of these efforts is

presented in this section.

3.2.2.1 Open Plumes

One correlation test was simulating an open fire plume, perhaps the most basic computation. This

was compared to McCaffrey's plume correlations30 with the results of velocity predicted within 5

% in the near field and within 11 % in the far field and temperature predictions within 5 % in the

far field. Temperature predictions in the near field, i.e. at the plume source, are over 100 % in

error, but this is due to the primitive heat source model in FDS v1.0 which does not yield

accurate temperatures immediately at a source. The “thermal element” method is a purely

convective process and since normal velocities at a burning surface are near zero, a particle

spends much of its lifetime near the surface before it is advected upwards into the flow field. As

a result heat releases are biased towards burning surfaces resulting in over predictions of the local

temperature. In the far field temperature predictions are predicted extremely well. Since the total

heat release rate is being achieved with FDS, in the far field the temperature prediction is

essentially a function of the entrainment prediction, that is how much cooler ambient air is being

mixed into the plume. Success in the far field indicates that FDS is correctly solving the

governing equations. FDS v2.0α calculations of the same plume show similar behavior in the

far-field, but a much improved near-field temperature predictions with a 36 % error.

3.2.2.2 Backdraft

Backdraft occurs when an oxygen depleted, fuel rich environment, such as a sealed compartment

with a smoldering fire, is suddenly exposed to a sudden inrush of oxygen rich air. If this inrush is

the result of fire fighters penetrating a structure, the resulting violent increase in the heat release

rate is liable to cause injury or death. An effort to improve the understanding of backdraft used

the mixing of salt and fresh water to simulate the mixing of cold, dense, oxygen rich air and hot,

oxygen depleted gas31. FDS v1.0 was used to simulate these experiments.

The experiments consisted of a smaller compartment filled with fresh water containing

phenolphthalein and a larger, elevated compartment filled with salt water containing sodium

hydroxide. A partition separating the two compartments was removed and a resulting flow was

videotaped. As the two fluids mix a reaction between the phenolphthalein and the sodium

hydroxide changes the fluid color from clear to red and allows visualization of the mixing

18
process. The parameter of importance in these experiments is the total transport time to the wall

opposite the partition.

The results of the FDS v1.0 simulations were as follows. Transport times were well predicted,

within 20 %, however, FDS v1.0 consistently ovepredicted the transport times. Velocity profile

predictions in the compartment opening were within 10 % near the center of the opening and

within 25 % near the edges of the opening. Since this particular simulation does not have any

combustion, FDS v2.0α results will be similar as only hydrodynamic solver is unchanged from

v1.0.

3.2.2.3 Hangar Fire

A third effort was the simulation of two JP-5 pool fires conducted in an Navy hangar in Hawaii32.

The two tests consisted of a round pool centered beneath 24.4 m x 18.3 m x 3.7 m draft curtain in

a hangar with a ceiling height of 15 m. The two fires were a 500 kW, 0.6 m diameter fire and a

2.7 MW, 1.5 m diameter fire. A summary of the comparisons were made between the FDS

predictions and the measured data are given below:

ü There was approximately a 35 % error in the plume centerline prediction over the height of

the plume.

ü Errors in the ceiling jet temperature and velocity predictions were 60 % and 40 %

respectively.

ü Errors in the draft curtain filling and spilling times were 45 % and 60 % respectively.

ü There was an 8% error in the temperature jump from inside to outside of the draft curtain.

ü In general the FDS v1.0 performance for these cases was poor; however, a coarse grid was

used which may have had a negative impact on the results.

3.2.2.4 Flashover

This simulation was part of a broader effort to evaluate computational methods for fire

simulation33 . The experiment being simulated consisted of a 5.2 m x 4.6 m x 2.4 m room with a

standard residential doorway in one corner. The room was fully furnished with sofas, chairs, and

tables, carpet, etc. A cushion on a loveseat was ignited by tipping over a halogen torchiere lamp

and the room was allowed to progress towards flashover. The compartment was instrumented

with three thermocouple trees and a heat flux gauge. 

FDS v1.0 predictions for this scenario were poor. FDS predicted the time to flashover at six

minutes whereas the data indicates flashover near nine minutes. FDS also over predicted the

upper layer temperatures by 40 %. This failure was attributed to three factors. The first was errors

in the material properties for the combustible materials required for field model simulation. The

second was the primitive combustion model in FDS v1.0 which used a very simple oxygen

consumption model. The last factor was the Monte-Carlo radiation method in v1.0 which did not

properly account for radiation heat transfer from hot gasses or hot surfaces.

19
FDS v2.0α shows a number of improvements for this diffucult scenario. Its predicterd time to

flashover was 7.2 minutes. Peak temperature predictions were 16 % below the measured values,

which is just outside the desired 15 % error. The same error sources for v1.0 still exist for v2.0α,

however, the contributions to the error by the radiation model and combustion model have been

greatly reduced.

3.2.2.5 Tank Farm Fire

This study was a purely numerical study to explore the use of FDS in predicting the smoke

transport and radiative heat transfer resulting from large, outdoor pool fires34. FDS v1.0 was used

to simulate two fire scenarios at an oil tank farm. The first was a fire burning at the top of the

tank. The second was a fire burning in the spill containment trench surrounding the tank. The

tanks were 84 m in diameter. FDS v1.0 predicted that 6 % of the heat release from the tank fires

was occurring as thermal radiation, and FDS v2.0α predicted 11 %. This compares well with data

which indicates the radiative fractions from very large pool fires is on the order of 8 %35

.

3.2.2.6 Warehouse Fire

FDS was also tested against a series of 22 heptane burner fires in the Underwriters Laboratories'

(UL) Large Scale Test Facility36. This test involved a heptane burner located beneath an array of

sprinklers bounded by a draft curtain. Up until the sprinkler activations, FDS calculates

temperatures near the sprinklers within 10 % of the measured values. FDS correctly predicted all

but one of the sprinkler activations; it predicted an activation where it did not occur. After the

sprinkler activations, FDS results continue to be within 10 % for those sprinklers which did not

activate; however, FDS greatly over predicts temperatures near sprinklers that do activate

indicating that more work is needed on the FDS droplet model which is relatively primitive at

this stage. For FDS v2.0α, a more sophisticated droplet model is being developed which should

result in lower temperatures near activated sprinklers. The new droplet model will make use of

the local vapor pressure of water to determine the droplet evaporation rate rather than only

evaporating the droplet once it reach the boiling temperature of water as in v1.0. This change

will result in some evaporation occuring near the sprinkler head.

3.3 CFAST

3.3.1 Code Description

CFAST, the Consolidated model of Fire Growth And Smoke Transport, was developed by the

Building and Fire Research Laboratory at the National Institute of Standards and Technology to

give both fire researchers and fire protection specialists a relatively easy to use computer code

with low computational requirements to predict the effects of a fire on a building's interior3,37.

CFAST was first released by the BFRL in 1990, and the latest release is version 4.0.1. 

CFAST belongs to a group of fire codes known as zone model codes. A zone model code is a

lumped-parameter code in which each room is divided into two lumped-parameter volumes, an

upper layer and a lower layer. Fires originating in the lower layer entrain air into a smoke plume

20
and transport heat and mass into the upper layer, see Figure 3.1. This entrainment is calculated

from McCaffery's correlation. As time progresses the upper layer will grow downward as more

mass is transported into it. If the upper layer grows down below the soffit of a doorway or

window, heat and mass from the upper layer can be transported to neighboring compartments.

Early versions of zone models were only capable of computing one level of a structure. That is,

heat and mass transfer between floors was not computed. CFAST currently has provisions for

handling multilevel structures. 

CFAST can model a fire as either a source of heat or with a simple combustion model. In the

former case, CFAST calculates heat and mass transfer but does not track the concentration of gas

species such as O2 and CO2. In the latter case, the user specifies the rate of pyrolysis, the rate at

which gaseous fuel is released by a burning object, the basic chemical composition of the fuel,

how much hydrogen, oxygen, nitrogen, and chlorine are present, and the combustion products

emitted by the fuel. CFAST will then combust the fuel on the basis of the oxygen available.

Unburned fuel is transported where it can continue burning if both oxygen is available and the

layer temperature is above a user defined ignition temperature. Transport of combustion

products is accomplished simply by calculating the mass transfer between compartments and

layers and allocating the mass transferred by means of the species concentration from the

originating compartment and layer.

Upper Layer

Lower Layer

Q m

.

Figure 3.1: Zone Model Overview

3.3.1.1 CFAST Mass Transfer

There are three methods in CFAST by which a user can connect compartments. Doors and

windows may be specified by specifying their heights, widths, and positions above the floor.

Doorway connections may be specified in a time-dependent fashion. A connection between

adjacent floors can be specified by providing a flow area and a connection shape, square or

circular cross section. Connections between floors may not change state during code execution.

The final method of connecting compartments is to use a ventilation system. A ventilation

system is constructed by creating nodes within compartments and attaching ducts to those nodes.

Ducts, which are given flow loss coefficients, can be connected to other compartment nodes or to

user defined fans for which the user defines the fan curve, mass flow rate, based on the pressure

difference across the fan.

21
Horizontal flow through vertical openings, e.g. doors and windows, is solved for by the use of

Bernoulli's equation. The assumption is made that the flow stagnates in the destination

compartment and the velocity being solved for is from the originating compartment. Flow is

calculated from upper layer to upper layer and from lower layer to lower layer in both directions.

Depending on the relative layer heights between the two compartments, a mixing flow may occur

which allows flow from the upper layer to the lower layer or vice versa.

Vertical flow through the floor between compartments is a function of two phenomena. The first

is the pressure difference between the compartments which acts to cause flow in the direction of

the gradient. The second is the density differences between the compartments which in the case

of cooler air over warmer air causes a buoyancy driven flow upwards. A correlation by Cooper38

is used that accounts for these two phenomena along with a correction for the shape of the

opening, square or circle. The layer into which the mass is placed is determined by calculating

the enthalpy of the incoming flow and comparing it to the layer enthalpies for the compartment.

The mass is placed in the lower layer if its enthalpy is less than that of the lower layer.

If the user defines a ventilation system, that system is expressed in CFAST as a nodal network.

Flow through the system is solved by a joint application of Bernoulli's equation along with

Kirchoff's Law for electrical networks. The Kirchoff's Law implementation sets the condition

that flow into a node must equal flow out of a node. In the present version of CFAST,

ventilation systems can only posses one state during a code execution; that is, a ventilation

system is either always on or always off.

In addition to the above modes of mass transfer, CFAST contains to primary submodels. These

submodels modify the horizontal mass transfer routine. One submodel attempts to correct zone

model physics for high ceilinged spaces such as an atrium. The other submodel delays mass and

energy transfer through a compartment to simulate the effect of a long hallway through which

flow disturbances take time to propagate.

3.3.1.2 CFAST Heat Transfer

CFAST has separate models for each of the three heat transfer modes: convection, conduction,

and radiation. To implement heat transfer calculations the user must define one or more of the

room surfaces to be a conducting material. A separate multilayer slab definition can be specified

for the walls, floor, and ceiling of each room. Objects within a room can also be specified, and

CFAST will combust those objects if user defined heat flux and temperature limits for the object

are reached.

Convective heat transfer within CFAST is implemented as a Grashof number correlation. The

correlation is evaluated in one of three manners depending on whether the surface is vertical, the

surface is horizontal with the wall temperature greater than the gas temperature, or the surface is

horizontal with the wall temperature less than the gas temperature. Therefore, for each room two

sets of four convection calculations are made, one each for the ceiling, the floor, the upper layer

portion of the walls, and the lower layer portion of the walls. The two sets are one set for the

22
room interior and one set for the room exterior in order to set the boundary conditions for the

wall conduction. The room exterior calculation uses the user-defined ambient conditions.

Radiative heat transfer within CFAST is calculated using a modified version of an N-surface

radiation equation developed by Siegel and Howell39. For rooms with no fires the radiation heat

transfer is solved as a two-wall problem. The two walls are the ceiling and upper layer portion of

the room walls and the floor and lower layer portion of the room walls. View factors are

calculated assuming the two walls are hemispheres. If there is a fire in the room a four-wall

computation is made. In this case the four walls are the ceiling, the floor, the upper layer portion

of the walls, and the lower layer portion of the walls.

Conduction heat transfer is computed by solving a transient, 1D, heat conduction problem for

each of the four wall types, the same types as in the convection calculation. The 1D heat

conduction solver divides the multilayer walls into a non-uniform mesh. The mesh is denser at

the wall boundaries and the mesh distribution is skewed towards the wall interior. A backwards

or implicit Euler method is used to perform the time stepping25. The wall boundaries can either

be compartment and ambient or compartment and compartment. That is heat can be transferred

through the walls to another compartment

3.3.1.3 Input Files

Input files for CFAST are card style , free format, ASCII input files. Since the input files are

ASCII files, any text editor can be used to create them

3.3.1.4 Code Output

There are two manners in which output from the code can be obtained. The user can specify a

few parameters to plotted during the code execution or the user can allow the code to display a

summary table to the screen at fixed time intervals. The user can also specify a time interval for

which complete dumps of the variable space will be written to a binary file.

The binary output file can be viewed with a primitive DOS based postprocessor or by running a

second program to extract data from the binary file into a comma-delimited ASCII file suitable

for importing into a spreadsheet. Unfortunately, the ability to specify which data to extract by the

second method is limited, and for multi-compartment problems with constrained fires the number

of columns can quickly exceed the import capability of common spreadsheet programs.

3.3.2 Summary of NIST Validation Efforts

As CFAST has been in existence for almost a decade, there is a large body of work documenting

its use. A few examples of this work are presented herein.

23
3.3.2.1 Original Validation Study

NIST performed a validation of CFAST using posttest predictions of five different fire

experiments. These computations were used to demonstrate the validity of the CFAST code3 and

were included as part of the original program documentation. The five experiments included two

single room tests with and without wall burning, two multiroom and single level tests with three

and four compartments, and one multiroom and multilevel test. A summary of these results are

presented to indicate the level of accuracy seen by CFAST at that time, 1993. The overall results

shown below are mixed indicating that at the time still CFAST needed improvements to its

algorithms.

Table 3.1 below summarizes the errors in predicting the peak upper layer temperature of the five

experiments. From Table 2.1 we obtain the criteria of ±15 % for the fire room and ±20 % for

other rooms. This table indicates that CFAST only meets the fire room criteria for one of the tests

and only meets the far field criteria for half of the far-field compartments. This is not a favorable

assessment of predictive capability.

Table 3.1: CFAST Validation Results for Upper Layer Peak Temperature

40 %

13 %

Fire room

#1 Multiple level test

22 %

35 %

6 %

23 %

Fire room

#2

#3

#4

Four room test

30 %

19 %

29 %

Fire room

#2

#3

Three room test

Single room wall burning Fire room 5 %

Single room w/ furniture Fire room 18 %

Test Compartment Error

The recommended accuracy criteria for gas concentrations is given in Table 2.1 as ±15-20 %.

Table 3.2 below presents a summary of the minimum O2 concentrations and the maximum CO2

concentrations for three of the five experiments. Only in the four room test did CFAST have

success predicting gas concentrations.

24
Table 3.2: CFAST Validation Results for O2 and CO2 Concentrations

59 %

75 %

O2

CO2

Fire Room

Fire Room

Multiple level test

15 %

8 %

39 %

8 %

4 %

O2

O2

CO2

CO2

CO2

Fire Room

#2

Fire Room

#2

#3

Four room test

6 v/o*

80 %

O2

CO2

Single room w/ furniture Fire Room

Test Compartment Gas Error

*O2 concentration in test was 0 v/o.

Table 3.3 shows the peak mass flow rates predicted by CFAST versus the experimental data.

These should be compared to the criteria of ±30-50 %. Data are shown for two of the tests for

the flow exiting the fire room. In both cases CFAST makes excellent predictions of the mass

flow, falling well within the acceptable error band.

Table 3.3: CFAST Validation Results for Mass Flow Rates.

Three room test 19 %

Single room w/ furniture 20 %

Test Error

3.3.2.2 Wall Heat Transfer Validation

The United States Navy has a great interest in being able to predict heat transfer through walls.

Since a typical naval vessel has metal walls, a fire in one compartment could conceivably ignite

materials in a neighboring compartment due to the high conductivity of the wall materials. As

part of its ongoing effort to improve fire safety on naval vessels the U.S. Navy conducted a series

of experiments aboard the ex-USS Shadwell to measure temperature changes in compartments

adjacent to compartments with fires. After development of new heat transfer algorithms for

CFAST v3.1, the data from the ex-USS Shadwell tests was used to validate the code40.

The particular test examined involved a diesel spray fire in an interior compartment two levels

below the deck. CFAST was used to predict the temperatures in that compartment and the two

compartments above it during the fire. In the fire compartment CFAST temperature predictions

during the early phase of the test were poor; however, the fire was started as a pool fire into

which diesel fuel was sprayed and the pool mass loss rate was not measured. During the latter

portions of the test when the diesel spray was activated, CFAST predictions in the fire

compartment are within 5 % of the measured data. In the compartment directly above the fire

compartment, CFAST predicted a slightly faster temperature rise than measured by the data;

however, the near equilibrium temperatures towards the end of the test were within 5 %. The

final compartment, two decks above the fire room, saw only a slight increase in temperature.

25
CFAST matched well both the rate of temperature increase and the final temperature. CFAST

predictions were slightly higher than indicated by the data.

3.3.2.3 Hangar Fire

A third effort was the simulation of two JP-5 pool fires conducted in an Navy hangar in Hawaii32.

The two tests consisted of a round pool centered beneath 24.4 m x 18.3 m x 3.7 m draft curtain in

a hangar with a ceiling height of 15 m. The two fires were a 500 kW, 0.6 m diameter fire and a

2.7 MW, 1.5 m diameter fire. A summary of the comparisons were made between the CFAST

predictions and the measured data are given below:

ü For the 2.7 MW fire predictions were made of the temperature decrease along the ceiling jet

created by the fire plume impingement on the ceiling of the hanger. From 75 s to 225 s after

ignition the fire measured temperature decrease changed from 14 °C to 9 °C. CFAST

predictions decreased from 1 °C to -2 °C. Thus, CFAST was in error for both the magnitude

of the temperature change and the sign of the temperature change as 225 s into the fire

CFAST predicted that the temperature would increase along the length of the ceiling jet.

ü Measured velocities in the ceiling jet 6 m from the 500 kW fire ranged from 0.5 to 0.8 m/s

over the 75 s to 225 s time period. CFAST predicted velocities ranged from 1.6 to 1.1 m/s,

close to a 100% error. Similar errors existed for the 2.7 MW fire.

ü The time to fill the draft curtain with smoke for the 500 kW and 2.7 MW fires was 100 s and

50 s respectively. CFAST predictions were 50 s and 30 s respectively. While the error is

large, the prediction is conservative.

ü Smoke detector activiations for the 500 kW at 3.0 m, 6.1 m, 8.5 m, 9.1 m , and 11.6 m from

the fire were recorded as 30 s, 50 s, 45 s, 75 s, and 90 s respectively. The corresponding

CFAST predictions were 105 s, 110 s, 125 s, 130 s, and 150 s. In all cases CFAST was a

minute or more late in its predictions, though the error percentage decreased with distance

from the fire.

3.3.2.4 Smoke Layer Development

A series of experiments were performed in the Building Research Institute at the University of

Tokyo to generate t2 fire data with which to validate zone model performance in calculating the

properties of smoke layers41. The tests consited of burning a polyurethane mattress in a

compartment connected to a hallway. Load cell measurements of the fire showed a t2 fire with a

peak power of 200 kW.

CFAST calculations for two of the tests showed the same behavior. CFAST calculates too quick

of a drop in the corridor layer height. For both cases CFAST predicted that the equilibrium layer

height was reached about one minute earlier than the data indicated. The layer height

predictions, however, were quite good with the predictions being within 20 to 30 cm of the data. 

 CFAST also had a mixed performance in predicting the layer temperature. For both cases

CFAST correctly predicted the time of the maximum temperature; predictions were within 30 s.

However, CFAST predicted twice the temperature increase, a 40 °C change as opposed to a

20 °C change.

26
4.0 HDR FACILITY

4.1 SUMMARY OF FACILITY AND FIRE TEST SERIES

The HDR (Heiss-Dampf Reaktor) facility,

shown in Figure 4.1, was the containment

building for a decommissioned,

experimental nuclear power reactor in

Germany. The building was a cylinder 20

m in diameter by 50 m in height topped by a

10 m radius hemispherical dome for a total

facility height of 60 m. Internally the

building was divided into eight levels with

each level further subdivided into smaller

compartments. The total number of

compartments was between 60 to 70

depending on the configuration of

removable partitions. The facility

contained two fixed, staircases, and three

adjustable vertical flow paths, an elevator

shaft, and two sets of equipment hatches

running the axial length of the building.

The total free air volume of the facility was

11,000 m3 of with 4,800 m3 above the

operating deck, the topmost floor of the

facilty. The HDR containment, its

compartments, internal structural materials,

vent flow openings and other pertinent data

are documented by Schall42.

From 1984 to 1991 a total of four fire test

series divided into seven fire test groups

were performed inside the HDR facility5.

The fire tests consisted of the T51 series consisting of eleven propane gas tests and three wood

crib tests, the T52 series consisting of four hydrocarbon oil pool tests, the E41 series with ten

hydrocarbon oil pool tests, and the E42 series consitisting of three cable fire tests. Figure 4.1

shows the location of the various test series inside the HDR facility.

The two sections that follow will give a brief overview of the two test series that were simulated

in this work. These were the T51 gas fire test series and the T52 oil pool fire test series. Further

details about the test series including instrumentation maps, protocols, and measurement

uncertainties can be found in a number of prior reports by this author2,43,44,45.

27

Figure 4.1: HDR Facility and Fire Test Locations
4.2 T51 GAS FIRE TEST DESCRIPTION

The T51 test series consisted of a total of fourteen subtests. Test execution for the gas fire tests

consisted of three separate testing periods. Approximately one half-hour before the scheduled

start of a fire, the data acquisition system would be activated, its operation verified, and a pretest

baseline data set taken. After the taking of baseline data, the burners would be ignited and fed at

a constant flow rate for approximately one hour. After the gas supply was terminated, data

collection continued for another forty minutes to collect cool down data.

4.2.1 Layout of T51 Fire Rooms

To avoid damaging the structure of

the HDR facility, as the building

was still considered a nuclear

facility under German law, a

special set of fire test rooms was

prepared at the 1.400 level of the

containment building, see Figure

4.1 for the location of the 1.400

level. These rooms also served to

control the flow of gases in and

out of the fire room. Figure 4.2

shows a cross section view of the

1.400 level and indicates the

location of these rooms which

consisted of the fire room with a

narrow doorway, a long hallway

wrapping around the reactor vessel

shield wall, and a curtained area

centered beneath the maintenance

hatch next to the main staircase.

For the remainder of the facility no

special precautions were

undertaken with respect to

insulation as gas temperatures outside the fire floor were anticipated to be below damage causing

levels. Table 4.1 below gives the geometric data of the prepared compartments46.

The fire room, vertical cross section through the 0-180° line and horizontal cross section at the

+0.0 m elevation, is shown in Figure 4.3, was constructed inside of room 1.405. The floor, walls,

and ceiling of the fire room were lined with 25 cm of Ytong fire brick. The ceiling, which would

be exposed directly to the fire plume, had additional protection in the form of a 3 cm thick layer

of Alsiflex matting, a fire resistant, ceramic fabric. The floor of room 1.405 below the Ytong fire

bricks consisted of a 1 m thick layer of concrete coated with a 1.5 mm thick coating of paint.

Along the wall of the fire room opposite the doorway were the six gas burners used for the gas

28

360o 0o

90o

180o

270o

1.401

1.402

1.403

1.404

1.405

1.406

1.410

1.408

1.409

±0.0 m

-1.6 m

Fire Room

Doorway

Hallway

Curtain

Hatch

1.307

1.407

Figure 4.2: T51 Fire Floor (1.400 Level)
fire tests. The gas burners were

mounted 0.675 m above the floor

of room 1.405 or 0.425 m above

the brick lining of the fire room.

The doorway to the fire room had

the same construction as the fire

room itself. The doorway’s height

was less than both that of the fire

room and the hallway. Unlike

most test chambers created for fire

experiments, the doorway had a

significant depth of 1.5 m. This

will cause a reduction in flow rate

through the doorway compared to

a standard door due to friction

losses along the walls in addition

to the typical orifice losses of a

standard door.

The hallway was constructed

inside of room 1.406. This

compartment wrapped around the

reactor vessel shield wall, thus, the

walls along the length are not

parallel planes, but instead the wall

around the vessel is an arc. The

doorway from the fire room enters the hallway slightly off set from the end of the hall. The walls

and ceiling of the hallway were constructed of a 10 cm thick layer of Ytong fire brick. The floor

of the hallway was not insulated and was of the same concrete and paint as in the remainder of

the HDR. This results in the floor of the hallway being 25 cm below the floor of the fire room

and doorway. The hallway had a constant ceiling height, and its width varied from 1.14 m at the

door to the fire room to 1.8 m at the entrance to the curtained area. This curvature of the hallway

and the general layout of neighboring compartments create a fairly complex flowpath for the

exhaust gasses from the fire.

Table 4.1: T51 Fire Compartment Dimensions

Curtained 5.350 12 63 7.40x0.50 2.3x2.0

Hallway 2.485 11 22 1.80x2.485 n/a

Doorway 1.975 2 3 1.01x1.975 n/a

Fire room 2.750 10 27 1.01x1.975 n/a

Hatch

(m x m)

Doorway

(m wide x m tall)

Volume

(m)

Area

(m)

Height

(m)

Compartment

29

0.875 m

0.10 m

2.485 m

1.975 m

2.75 m

-1.1 m

0.25 m

1 2

3 4 5 6

1.000 m

0.250 m

5.000 m

3.010 m

2.150 m

1.010 m

1.650 m

Gas Burners

0.575 m

0.600 m

Figure 4.3: T51 Fire Room + Doorway
The curtained area was constructed next to the main staircase under an open maintenance hatch

and was created primarily to force flue gasses from the fire away from the inside steel shell and

up through the vertical shaft of the open maintenance hatches. This area was created by draping

Alsiflex mats from the ceiling down to 0.5 m above the floor. This 0.5 m gap allowed for a cold

air return flow to the fire room and attempted to force a better separation of the hot and cold gas

streams. It is important to note that the gap below the curtain opened up towards both the main

staircase and towards compartment 1.403 which had a floor elevation that was 1.1 m above the

floor of the fire hallway or 0.6 m above the top edge of the gap beneath the curtain.

4.2.2 T51 Fire Source

The gas fires for the T51 tests used propane gas fed at a constant rate through one or more of the

six burners located along the wall of the fire room opposite the fire room doorway. Each burner

was located 0.625 m above the floor of the fire room. Before being injected into the burners the

propane gas was premixed with 10 % excess air, i.e. 10% more air than required by

stoichiometry, to insure complete combustion of the propane.

4.2.3 Subtest Selected for Modeling

The particular T51 subtest which was modeled was the T51.23 test. This test had a fire power of 

1.011 MW and was a repeat of the T51.14 test. The T51 gas subtests in general make for superb

tests for fire modeling due to the simplicity of specifying the test boundary conditions. This

simplicity is due to a couple of factors. First, the fire source is very well defined. Since the

propane gas is being fed to the burners with 10% excess air, nearly complete combustion is

occurring at the burners. Second, the geometry for these tests is very well defined. The simple

fire source makes this test well suited for examining the performance of a computational

method’s heat and mass transfer algorithms without the added uncertainty usually associated with

a liquid pool fire or solid fuel.

4.3 T52 TEST DESCRIPTION

The second test series of fire experiments was the T52 oil fire test series which consisted of four

oil pool fire tests performed in 198647,48,49. The tests ranged in power from two to four megawatts

with the fire lasting approximately 30 minutes. Whereas the previous test series, the gas and

wood fires, were performed at a level low in the containment building, it was decided to position

this test series high up in the containment building as shown in Figure 4.1. Thus, the fires were

positioned in a special fire compartment constructed on the 1.900 level, the level just below the

operating deck. It was anticipated that this would confine smoke and soot to the dome region.

The fire compartment, see Figure 4.4, was located such that it vented directly into the dome

through the maintenance hatch next to the spiral staircase. 

Fuel for the fires consisted of an initial volume of oil in a pool with a surface area ranging from 1

m

2

 to 3 m2 in size. A nozzle augmented the initial amount of fuel by feeding a continuous

supply of oil once the initial pool was nearly consumed. The nozzle mass flow rate varied with

each test. Each fire lasted approximately 30 minutes.

30
For this test series special attention was paid to the buoyant fire plume entering the upper dome.

Three two-dimensional grids of instrumentation were placed in the vertical flow path of the

plume exiting the fire room. These grids contained thermocouples, velocity probes, and CO2

sensors. The grids were located at the exit of the maintenance hatch leading from the 1.800 level

to the 1.900 level, at the exit of the maintenance hatch leading to the dome from the 1.900 level,

and centered over the maintenance hatch at near the elevation of the polar crane mounted in the

dome.

4.3.1 Layout of T52 Fire Rooms

The T52 test series took

place in a set of specially

constructed compartments

inside of rooms 1.902 and

1.906, see Figures 4.5 and

4.6 for horizontal and

vertical cross-sections of the

compartments. As with the

T51 test series, there was

concern about the intense

heat in the immediate

vicinity of the fire damaging

the HDR structure. In

particular there were

concerns about the steel

shell of the containment

being damaged by high

temperatures. These

compartments consisted of a

fire room, a doorway

region, and a region below

the auxiliary maintenance

hatch located near the spiral

staircase. Table 4.2 gives

some geometric details of

the compartments.

Table 4.2: T52 Fire Compartment Dimensions

Maintenance Hatch Area 5.0 3.6x3.05=10.98 52 1.85x2.6=4.81

Doorway 3.0 0.95x0.78=0.74 2 3.0x0.95=2.85

Fire Room 2.8 4.58x1.75=7.88 24 n/a

Flow Area

(m2)

Volume

(m3)

Floor Area

(m2)

Height

(m)

Compartment

31

360o 0o

90o

180o

270o

1.410

1.802

1.801

+21.05 m 1.307

1.903

1.901

1.905

+25.30 m

1.803

+20.60 m

1.704

+17.55 m

Fire Room

Hatch

1.906

1.904

1.902

Figure 4.4: T52 Fire Floor (1.900 Level)
The fire itself was located

in a compartment

constructed in room 1.906.

This compartment was

constructed out of Ytong

firebrick. The floor, the

ceiling, and the shorter

length walls were

constructed of a 25

cm-thick layer of firebrick.

The other two walls had a

10 cm-thick layer. The

ceiling was given an

additional insulative layer

consisting of a 3 cm

thickness of Alsiflex

matting. In the center of

the fire room a 25 cm high

platform was constructed

to suspend the oil pans in

which the fire would occur

above three digital scales

used to measure the

burning.

The fire room was

connected to the area

beneath the maintenance

hatch by a doorway similar

in size to the doorway in

the T51 tests. To avoid

creating too narrow of a

doorway, it was lined on

the side walls with only a 3

cm thickness of Alsiflex

matting. The floor and

ceiling of the doorway

were lined with a 25

cm-thick layer of Ytong

firebrick.

Since the steel shell had no

protective concrete layer in

the region below the maintenance hatch in room 1.902, a compartment was also constructed in

this room. This compartment was created by building a wall to isolate the spiral staircase and the

32

Figure 4.5: T52 Horizontal CX

0.175 m

2.600 m

1.850 m

3.050 m

3.600 m

1.000 m

0.950

0.250 m

4.580 m

Hatch

Doorway

Fire Room

Fire Platform

3.000 m

R 1.902

R 1.802

R 1.906

R 1.905

1.750 m

0.100 m

Figure 4.6: T52 Vertical CX

3.80 m

4.25 m

1.78 m

2.80 m

38° 18°

Hatch

Hatch

Fire Room

Doorway

R 1.902

R 1.906

1.00 m

0.25 m

5.00 m
steel shell. The wall was created with a 17.5 cm layer of Ytong firebrick. The other walls were

lined with a 10 cm layer of Ytong firebrick. To enhance the flow of the combustion products

into the dome, the ceiling of room 1.902 was modified to create a tapered chimney like structure.

This was created using 2 cm thick Promatec plates.

4.3.2 T52 Fire Source

The fire source for the T52 test series was Shellsol T. Shellsol T is a hydrocarbon solvent

manufactured by Shell Chemicals of Norway. Shellsol T is a liquid isoparaffin consisting of 11

to 13 carbon atoms with 80 % of the molecules having 12 atoms. It is a clear liquid that

generates less soot than common fuel oils such as kerosene. Shellsol T materials properties at

standard temperature and pressure conditions are shown below in Table 4.347,50.

Table 4.3: Shellsol T Material Properties

761 181-213 60 42,500

Heat of Combustion

(kJ/kg)

Flashpoint

(°C)

Boiling Temperature

(°C)

Density

(kg/m3)

4.3.3 Subtest Selected for Modeling

The T52.14 test was selected for modeling with CFAST and FDS. The primary reason for

selecting this test was that it was used in a prior international effort of computer modeling of

containment fires12,51. In

order for that effort to have

occurred, more care was

given to generating the

burning rate function for

this test than for the other

tests in the series. Since a

fire model is highly

dependent on the accuracy

of the input burning

function, the T52.14 test

was the clear choice for

modeling. Figure 4.7

shows the burning rate

function for the T52.14

test. The various stages of

the test, burning of the

initial oil volume, constant

fuel addition, and post-fire

cooldown are labeled on

the plot.

33

Time (min)

Burning

R

ate (kg/s)

0 10 20 30 40

0.00

0.01

0.02

0.03

0.04

0.05

0.06

0.07

0.08

0.09

0.10

0.11

0.12

Cooldown

Burning of

Initial Oil

Constant Oil

Addition

Figure 4.7: T52.14 Burning Rate and Test Phase Definitions
5.0 TEST SIMULATIONS

This chapter briefly discusses the CFAST and FDS input files for the T51.23 and T52.14 fire

tests and the hand calculations performed for each test. For both fire tests, only one input file for

each computer code was executed for this report. The input files utilized resulted from a number

of years of prior effort in using both FDS and CFAST for simulating the HDR fire tests. Lessons

learned from the successes and failures of the prior modeling efforts were used to develop the

final input files discussed in this Chapter. For a more detailed discussion of the input files for

CFAST and FDS and a discussion of prior modeling efforts by this author for the T51 and T52

fire tests, the reader is referred to references 2, 44, 45, 52, 53, and 54. For more details on the

hand calculations performed, including copies of the Mathematica files used, the reader is

directed to reference 2.

5.1 T51.23 SIMULATION

The T51.23 fire test was selected mainly because it represented the best combination of known

boundary conditions and instrumentation map of all the HDR fire experiments46. Since the

T51.23 fire test used propane gas burners fed with a gas-air mixture, the heat release rate and the

combustion chemistry can be specified with little error. Furthermore, the T51.23 test did not

involve the use of any of the HDR facility’s ventilation systems which eliminates a source of

added complexity. If a computer model cannot reasonable simulate a test with such a simple fire

source, one would be forced to question if the model’s results could be applied to any test

simulation.

The following three sections describe the inputs for the FDS and CFAST simulations of the HDR

T51.23 gas fire test and the methodology used for the hand calculations. The FDS simulation of

the test encompassed the fire room, the hallway, and the curtain area for a period of 10 minutes

from the start of the fire. The CFAST simulation encompassed the entire HDR facility at or

above the elevation of the fire room and covered the duration of the fire, 60 minutes, plus 30

minutes of the cool down period after the fire. Hand calculations were performed for the fire

room only. Results of the model simulations are compared with data in Chapter 6.

5.1.1 FDS Model

5.1.1.1 Geometry

As FDS is very memory intensive, it was decided, therefore, to only include the fire room, the

hallway, and the curtained region beneath the hatch in the T51.23 FDS input file. Modeling

these regions of the T51.23 test presented an interesting challenge for FDS modeling. The

current version of FDS nodalizes a geometry in purely rectilinear coordinates. The T51.23 test,

however, contains a mix of orthogonal surfaces, non-orthogonal surfaces, and cylindrical

surfaces on the fire floor. This mix of surfaces results from the hallway leading from the fire

room to the curtained area. The hallway wraps around the cylindrical reactor vessel shield wall

at the center of the containment building. One wall of the hallway is approximately a 60° arc.

The opposite wall of the hallway is a plane perpendicular to the 135° radius drawn from the

34
center of the HDR. This plane is non-orthogonal to the fire room surfaces. Lastly, the ceiling at

the end of the hallway rises up slightly as it reaches the curtained area creating an inclined plane.

Creating the geometry described above in FDS requires specifying a complex series of blockages

to approximate the aforementioned surfaces. The side walls of the hallway were modeled by a

series of stair steps that approximated each of the two surfaces. Twenty stair steps were used for

each wall which results in steps representing about 20 cm of arc length.. There is conflicting

documentation regarding the rise in the hallway ceiling near the curtained area with some figures

showing a gradual rise and other figures indicating a sharp rise. Since there is almost no

instrumentation in the curtained area, it was decided to not model a form of inclined plane as the

inclusion or lack thereof would not have much effect upstream in the hallway at the available

sensor locations.

The resulting geometry yielded a computational domain 11.195 m x 9.645 m x 4.600 m in

dimension. This region was mapped to a finite differenced volume of 100 nodes x 90 nodes x 50

nodes for a total of 450,000 nodes. The resulting geometry is shown in Figure 5.1. This figure

shows a top down view (XY plane), a view from the right side (YZ plane), and an oblique view.

5.1.1.2 Flow Boundary Conditions 

Experiment T51.23 used 5 of the 6 available gas burners, numbers 1 through 5. Since the T51

tests series injected a mix of propane gas and air through the burners at a constant flow rate, the

five gas burners were defined in FDS as separate vents with a constant inlet velocity. These

vents were defined in FDS according to their physical location as shown in Figure 4.3. For FDS

v2.0α, two sets of burners were created. The first set at the physical location of the burners was

defined as a source of fuel. The second set directly located above the first set was defined as a

source of ambient air. This was required as the mixture fraction formulation in FDS v2.0α

precludes the use of premixed fuels.

In addition to the gas burners, two additional vent specifications were needed. They were the

flow area under the curtain and the flow area through the maintenance hatch. Both of these were

defined as passive vents, i.e. flow of either direction through the vent is allowed (see 3.1.1.5 for

more details).

5.1.1.3 Output Options

A number of HDR instrumentation locations were specified in the input file to be output during

the code execution. In all, 81 sensors in the T51.23 fire compartments were specified. 

35
0

2

4

6

8

10

024

0 2 4 6 8 10

X

Y

Z

0 2 4 6 8 10

Y

0510

0

2

4

X Y

Z

0

2

4

Z

0

5

10

X

0

2

4

6

8

10

Y

Y

Z

X

Figure 5.1: T51.23 FDS Nodalization

36
5.1.1.4 Wall Boundary Conditions

There were two surface types which required defining in the input file. The first surface type was

the Ytong firebrick that lined the fire room and the walls and ceiling of the hallway. The second

surface type was the exposed concrete on the floor of the hallway and the floor and ceiling of the

maintenance hatch. All surfaces of the fire room and doorway were set to be firebrick as were

the walls and ceiling of the hallway. The wall of the hatch area near the HDR centerline was also

defined as firebrick as was the wall of the hatch area where the hallway entered. The remaining

surfaces were defined as concrete.

5.1.2 CFAST Models

5.1.2.1 Overview

The CFAST input file created for this work was a ten compartment model that included the HDR

faciltiy from the fire level to the dome. The case presented here is a subset of the larger body of

work by the author discussed at the beginning of this. Results of the CFAST computation are

documented in Chapter 6.

For the CFAST input file, the simulation began with a 100 s null transient, the reason for which

will be described in the next subsection which discusses the compartments and compartment

interconnections. The heat release rate was ramped up at the start of the fire and down at the end

using a 1 s linear ramp. The fire is followed by a 1/2 hour cooldown period.

5.1.2.2 Compartment Specifications and Compartment Interconnections

This subsection will discuss the compartment layouts and the specifications for compartment

interconnections for the T51.23 CFAST model. A total of seven material definitions were

required for the T51.23 CFAST model. 

The first subsection of the model encompassed the specially built compartments on the 1.400

level including the fire room and the fire room doorway, the hallway, and the curtained area.

Connections are defined from the fire room to the doorway, from the doorway to the hallway,

from the hallway to the curtained area, from the curtained area to the 1.500 level and from the

curtained area to the remainder of the 1.400 level. The latter two connections are to the ambient.

In addition to these flow connections a simple ventilation system representing the air flow

through the gas burners was defined consisting of an inlet duct from Room 1.603, a blower, and

an outlet duct to the fire room.

Using the data in Table 4.1, the models of the four compartments were created. Since only the

doorway and the curtained area were rectangular spaces, length and width dimensions had to be

created for the other two compartments. For the fire room it was decided to preserve the distance

from the back wall of the fire room, 2.51 m, to the doorway entrance plane. For the hallway and

the curtained area, it was important to maintain a room dimension equivalent to the dimension of

the largest flow connection. For the hallway, this meant maintaining the hallway width of 1.8 m

37
were it connected to the curtained area. Heights for the fire room, the doorway, and the hallway

were given as the actual compartment heights. The height for the compartment was given as the

total height from the floor of the curtained area to floor of the 1.500 level. The floor level for the

fire room and the doorway were set to an elevation of 0.25 m to account for the raised floor due

to the layer of Ytong firebrick placed in those areas. The floor level for the hallway and

curtained area was set to an elevation of 0 m.

Compartment interconnections were defined according to the data in Table 4.1 with the

exception of the under-the-curtain connection in the curtained area. An examination of curtained

area reveals that although the length of the curtain is 7.3 m, only a portion of the length is

available for flow. Those portions of the curtain near the reactor vessel shield wall and the

elevator, room 1.410, are not contributing to the return flow under the curtain due to flow

obstructions present at those locations. Therefore, it was only the length of the curtain

neighboring the stairs, 4.3 m, that was specified for a flow connection.

The last portion of this model subsection addressed the ventilation system for supplying air to the

propane gas burners. This system took its suction from room 1.603 next to the spiral staircase

and the discharge node was placed in the fire room 0.625 m above the floor. A constant speed

fan was placed in between the suction and discharge locations to create a constant flow of air into

the fire room. 

The next subsection contains compartments for the maintenance hatch region of the 1.500 level

and three compartments to represent the 1.600 level (one for the main staircase hatch, one for the

spiral staircase hatch and R1.603 where the air supply intake was located, and one for R1.606

which connected the two sides of the building). These additional compartments were added with

two issues in mind. The first is that the total height of the HDR facility should be preserved as

well as the height of the individual levels. The second was that only the volume of the facility

which communicated with the fire room be included in the model.

The first item fixed the height of the additional compartments. These heights were determined

from Schall42 which gave elevations for selected locations in the facility. This fixed the 1.500

level compartment to a height of 5.5 m, the 1.600 level hatch compartments to 5.05 m, R1.606 to

4.6 m, the upper region compartment to 34.395 m, and the 1.600 level to 1.400 level connecting

compartment to 6.6 m.

The second item was not as obvious. On the 1.500 level, which lacked a single large return

connection from higher levels, it was decided to only model that portion of the level adjacent to

the maintenance hatch. Thus, the 1.500 level compartment dimensions were set to be the same

as the curtained area dimensions on the 1.400 level. The 1.600 level included a number of

features which needed to be accounted for in the compartment definitions. These included the

main staircase hatch, the large return connection from the dome region (the spiral staircase

hatch), the air supply intake, and the hallway connecting the two halves of the facility.

Therefore, the main staircase hatch area was given the net volumes of R1.604 and R1.337 (main

staircase), the connecting hall was given the volume of R1.606, and the spiral staircase side was

given the volumes of R1.611 (spiral staircase) and R1.603 (air supply location). The flow

38
connection was given the

dimensions of the net flow area

between the 1.600 level and the

1.400 level not including the

hatches. 

Flow connections between the new

compartments were given the areas

of the maintenance hatches for the

vertical connections and the

smallest cross-sectional area of

R.1606 for the horizontal

connections on the 1.600 level. In

addition to these connections,

another flow connection was

required. CFAST would not

initialize the ventilation system

without a connection to the

ambient. Therefore, a null

transient of 100 s was added to the

input file during which a small

connection to the outside was

opened in the 1.600 level to 1.400

level connecting compartment. At the start of the fire this connection was closed at which point

CFAST continued to execute.

The remaining compartments were two compartments for the spiral and main staircase side of the

1.700 level, two compartments to represent the 1.800 level and 1.900 level spiral and main

staircase side, and a final compartment for the dome. The 1.800 and 1.900 levels were combined

into one level since CFAST had difficulties running with the two levels defined separately. For

the remainder of the facility only those compartments directly adjacent to the maintenance

hatches were included in the active volume. The non-adjacent compartments did not possess

significant flow connections to the ones included above, and were thus ignored. The remainder

of the facility included (given up the main staircase side and down the spiral staircase side:

R1.707 and R1.347, R1.805 and R.1357, R.1903 and R1.367, the dome, R1.902 and R.1906,

1.802 and R.1804, and R1.703 and R1.708. Figure 5.2 below shows the layout for the model.

5.1.3 Hand Calculations

A simple hand calculation was performed for the fire room of the T51.23 test using Mathematica

v3.0 ®. Hand calculations are a valuable tool in performing safety analyses. Their simplicity

and speed enable them to be used for scoping basic details of a problem. While they may not be

as accurate as a complex simulation, their results can nonetheless serve as a sanity check for a

more detailed method. Therefore, to demonstrate their potential usefulness the methods

39

Burner Air

Supply

Fire Room

and Doorway Hallway CurtainedArea

1.400

Level

1.500 Main

Staircase

Hatch

1.600 Main

Staircase

Hatch

Dome

R 1.606

1.600 Spiral

Staircase

Hatch+R1.603

1.600 Level

to 1.400 Level

Connection

Temperorary

Connection

to Ambient

1.700 Main

Staircase

Hatch

1.700 Spiral

Staircase

Hatch

1.8/1.9 Main

 Staircase

Hatch

1.8/1.9 Spiral

Staircase

Hatch

Figure 5.2: T51.23 CFAST Model Compartment Layout
described in 3.1 were applied to the T51.23 experiment. The hand calculation used for the

T51.23 test made the following assumptions:

1. The fire has reached steady-state conditions with respect to the wall heat transfer.

The measured data show this assumption is valid for the end of the hour long gas

fire as all temperatures have ceased rising significantly by the end of the fire.

2. The fire room possesses two distinct layers. Again this assumption is born out by

the measured data which shows low temperature near the floor of the fire room,

even in the corner furthest from the doorway.

3. The smoke layer height in the fire equals the burner height off the floor. There

was not enough instrumentation in the fire room to accurately determine the layer

height, however, given the burner arrangement it is unlikely that the layer

interface was far from this location.

4. The mass addition of the fuel/air mixture is negligible compared to the mass flow

rate into the room at the doorway. Mass addition to the fire room from the fuel

and air mixture was approximately 0.1 kg/s. An average lower layer velocity into

the fire room of 1 m/s would result in over 1 kg/s of mass input.

As a result of the above assumptions, most notably the second assumption, the method described

in 3.1.1.1 was used to analyze the T51.23 fire room. Results are presented in Chapter 6 and the

Mathematica ® notebooks are documented in Appendix C.

5.2 T52.14 SIMULATION

The following two sections describe the inputs for the FDS simulations and the CFAST

simulations of the HDR T52.14 oil pool fire test. The FDS model encompassed the fire room,

the fire room doorway, the region beneath the maintenance hatch from the ceiling of the 1.800

level to the top of the operating deck, and a portion of the dome region from the operating deck

to the measurement grid located beneath the start of the hemispherical portion of the dome

region. The CFAST simulation encompassed the entire HDR facility from the 1.600 level to the

dome and covered the duration of the fire plus 15 minutes of the cooldown period after the fire.

This encompassing modeling effort resulted from a prior assessment of the data for all the T52

tests3,45.

5.2.1 FDS Model

5.2.1.1 Geometry

For the FDS model it was desired to simulate enough of the HDR facility in order to make use of

the two sensor arrays located in the dome. Thus, the FDS model included the fire room, the

hatch area adjacent to the fire room, and a portion of the dome up to the level of the second

40
measurement grid. An area around the grid was included to account for the effect of containment

steel shell which would serve to restrict entrainment into the plume along one side.

Unlike the T51.23 test, there were few non-orthogonal surfaces to model. The fire room, the

doorway, and the lower portion of the hatch region were all composed of surfaces orthogonal to

the Cartesian grid. The upper portion of the hatch region, however, had the shape of a truncated

pyramid. As with the T51.23 model, this was done by defining a staircase-stepped region to

approximate the non-orthogonal surfaces. The combined computational domain was 9.00 m x

8.31 m x 14.2 m and encompassed the fire room, doorway, hatch, and a portion of the dome

surrounding the upper sensor grid. The domain was discretized with 72 nodes x 64 nodes x 120

nodes for a node total of 552,960 nodes. Figure 5.3 shows the noding for this geometry. This

figure shows a top down view (XY plane), a view from the right side (YZ plane), and an oblique

view with part of the dome blanked to show the connection to the lower rooms.

5.2.1.2 Flow Boundary Conditions

Test T52.14 was used for code comparisons during the execution of the T52 test series51.

Because of this, HDR staff made efforts to define a burnup curve on the basis of the available

weight sensor data. A copy of this curve can be found in Travis’s report on using the

GASFLOW computer code to model the T52.14 test51. A piecewise linear curve was fit to the

burnup curve and used to define a time-dependent fire source for FDS. A 2 m2 vent was defined

at the center of the oil platform nodes and assigned the time-dependent function.

In addition to the oil pan, further vent specifications were needed. The maintenance hatch below

the fire room was defined as a passive vent, i.e. flow of either direction through the vent is

allowed. Also the following surfaces in the dome region were defined as open vents: y=0.00 m,

y=8.31 m, x=9.00 m, z=14.2 m. The x=0.00 m surface was the steel shell of the dome, and as

such was not open for flow.

5.2.1.3 Output Options

Since FDS will output user selected variables at user specified locations during its computation, a

number of HDR instrumentation locations were specified in the input file to be output during the

code execution. In all, 86 sensors were specified. 

41
0

1

2

3

4

5

6

7

8

Y

010 Z

0 1 2 3 4 5 6 7 8 9

X

X

Y

Z

0

2

4

6

8

10

12

14

Z

0

2

4

6

8

X

0

2

4

6

8

Y

Y

Z

X

0 1 2 3 4 5 6 7 8

05 X

0

2

4

6

8

10

12

14

Z X Y

Z

Figure 5.3: T52.14 FDS Nodalization for Fire Level and Dome Input Geometry

with Cut-away to Show Hatch Connection to Dome

42
5.2.1.4 Wall Boundary Conditions

Three surface definitions were used for the T52.14 input files. These surfaces were the 0.25 m

thick Ytong firebrick walls in the fire room, the 0.10 m thick Ytong firebrick walls below the

maintenance hatch, and the HDR concrete. All surfaces of the fire room and the ceiling and floor

of the doorway were set to be the thick firebrick material. The remainder of the doorway and the

side walls of the hatch area were defined as the thin firebrick material. All remaining surfaces

were defined as the HDR concrete.

5.2.2 CFAST Models

5.2.2.1 Overview

The CFAST input file was a 12 compartment model that encompassed the HDR facility from the

1.600 level through the dome and included three nodes in the dome. This model resulted from a

series of prior model development efforts3,45,53,54 (Floyd, et al., 2000a-c and Floyd, 2000d). 

5.2.2.2 Combustion Related Input Cards

The combustion product values were based on information in Karlsson and Quintiere1. Chapter 9

of their book contains information on combustion product formation in various fuels. Table 9.2

in the book gives combustion product yields for a variety of fuels in well-ventilated fires and

Figure 9.7 gives ratios of well-ventilated to under-ventilated yields for a variety of fuels for a

spectrum of equivalence ratios. Hydrocarbon oils were not among the fuel types listed in either

table. Of the fuels available in both locations, polystyrene appeared a good match as it is a

nongaseous hydrocarbon. From Table 9.2 in the book the yields of CO2, CO, and soot were used

to calculate the percent of the carbon atoms in the fuel that went into the various products for a

well-ventilated fire. These fractions were scaled to the chemical formula for Shellsol-T. Figure

9.7 was then used to calculate the product yields for an equivalence ratio of 3, which was

selected due to the large CO concentrations measured during the test. These product yields were

then used for the CFAST input.

5.2.2.3 Compartment Specifications and Compartment Interconnections

This subsection will discuss the compartment definitions and the definitions for compartment

interconnections for the CFAST model for T52.14. A total of seven material definitions were

required for the T52.14 CFAST model. The CFAST models encompassed the HDR facility

from the 1.600 level to the dome. Maintenance hatches to the lower levels were sealed as were

the doors to the elevator shaft. Therefore, no significant flow path existed to the 1.200 through

the 1.500 levels. The model contained the following compartments: fire room and fire room

doorway, fire level hatch region, three node dome, one compartment for each level on the main

staircase side from 1.900 to 1.600, and one compartment for each level on the spiral staircase

side from 1.600 to 1.800. The three node dome portion of the model resulted from a series of

prior model building efforts undertaking by the author as part of an earlier study of the T52 test

series45. The resulting compartments are shown in Figure 5.5 below.

43
50.00 HDR Elevation

10.00

15.05

30.85

25.55

25.30

20.60

28.55

Dome

Fire Room + Doorway

Level 1.900

Level 1.800

Level 1.700

Level 1.600

Fire Room Hatch

1

2

3

4

5

6

7

8

10

11

12

40.00

9

Figure 5.4: CFAST Compartment Layout for T52.14

5.2.3 Hand Calculations

The significant driving force of the T52 test series was the large thermal plume leaving the fire

room and rising into the dome. One could take basic parameters of the T52.14 test and use hand

computations or simple integral models to predict the behavior of the plume and some of the

basic impacts on the HDR facility. This approach could be an alternative to a rigorous modeling

effort when one only wishes to examine the overall magnitude of a postulated fire's impact in

order to determine if further investigation is warranted.

To illustrate this approach, the constant oil addition portion of the T52.14 test was examined

with some simple hand calculations. These calculations were performed in two parts. The first

part analyzed the fire room itself. The second part used the results from the first and predicted

properties of the plume entering the dome.

The analysis of the fire room made the following assumptions:

1. The fire has reached steady state conditions with regards to wall heat transfer in

the fire room. As with this assumption in the T51.23 analysis, data for the fire

room shows that temperatures in the fire room were stable over this time period.

Furthermore, the higher temperatures earlier in the test would have acted to heat

44
the fire room walls faster and allow the later portion of the test to reach

equilibrium sooner.

2. The atmosphere of the fire room is well mixed. That is no distinct layer exists.

The thermocouples in the fire room plus the doorway indicate that the entire fire

room reached elevated temperatures during the test.

3. The heat addition by the fire is equal to the total heat of combustion available in

the fuel being added to the oil pool.

4. The mass addition rate for the fuel is negligible compared to the mass exchange in

the doorway. As with T51.23 the fuel addition rate is less than 0.1 kg/s. Little

flow speed at the doorway would be required to make this a small fraction of the

mass flux.

As with the T51.23 hand calculations, the second assumption determines the method from

Chapter 3 to be used. In this case it is the method described in 3.1.1.2.

Once the flow from the doorway and the fire room temperature is known, these values can be

used to calculate parameters of the plume entering the dome. The fire room temperature, the

velocity, and the flow area from the fire room can be used as initial conditions with either the

Chen-Rodi correlation or the integral analysis as described in 3.1.2. From these methods we can

determine the plume temperature and radius at various elevations in the dome. These are key

parameters as the plume mass flow defines the overall mixing throughout the facility. With the

fire room mass flow rate calculated as well as the mass flow through the hatch into the dome,

application of the conservation of mass would yield the overall flow through the maintenance

shafts as well as recirculation within the dome.

Results of using Mathematica ® to apply the methods from 3.1.1.2 and 3.1.2 to the T52.14 test

are discussed in Chapter 6 along with the CFAST and FDS results and the Mathematica ® used

are documented in Appendix C.

45
6.0 RESULTS OF SIMULATIONS

This chapter presents the FDS simulations and the CFAST simulations of the T51.23 and T52.14

tests. The results are presented along with a discussion of the performance of each method of

analysis. The discussion is presented in terms of the desired predictive quality, see Table 2.1 in

Section 2.5.4, for a performance-based code regime.

6.1 T51.23 SIMULATION RESULTS

The results of the T51.23 gas fire test simulations are discussed in the following four sections.

The sections individually describe the results of the three calculation methods applied to the

T51.23 test as well as gives an intercomparison of the results of the three methods.

6.1.1 T51.23 Hand Calculations Results

The two-layer compartment equations from Chapter 3 were entered into Mathematica v3.0 ®.

Before solving these equations a number of variables needed to be defined. The doorway loss

coefficient Cd was defined as 0.71. The ambient temperature was defined as 300 K. The upper

layer wall surface area was calculated from the room geometry as 39.82 m2. The gas molar mass

was taken to be that of air, 0.0288 kg/mol. The ambient pressure was assumed to be 101 kPa.

Lastly, the wall heat transfer coefficient was calculated from the wall heat conduction assuming

steady-state heat transfer. For simplicity all the fire room walls were assumed to be 0.25 m of the

Ytong firebrick. This results in hk=0.96 W/m2⋅K. Other variables have already been specified in

Section 5.2 documenting the test layout. The following solutions were obtained by

Mathematica v3.0 ®:

Table 6.1: T51.23 Hand Calculation Results vs. Measured Data

HN (m) 0.90

Lower Vel (m/s) 1.15 2.7

Upper Vel (m/s) 3.52 4.9

1.21 *

mg (kg/s)

ρg (kg/m3) 0.32

Tg (°C) 834 769-905

Variable Value Data

The hand calculation results performed well for this scenario. The predicted gas temperature lies

with in the range of the measured data and is within 4 % of the actual average measured

temperature in the upper layer. Since for this test only two velocity probes were used, it is

difficult to compare an averaged quantity with a point quantity. However, since the probe

placements were near the door centerline a short distance away form the ceiling and floor, they

should represent a velocity condition near the maximum velocity. Thus, one would expect the

hand calculation quantity to be lower than the measured, and in fact they are. 

 

46
The hand calculation method discussed in this section is a fairly simplistic one. Due to this

simplicity, it took little time, on the order of an hour, to create the calculational notebook in

Mathematica ® and obtain results. Once created, the calculational notebook could be run for

many different permutations in a very short period of time as the actual calculation took only a

few seconds. The results obtained by this method are quite good. The upper layer temperature

and the mass flow out of the fire room were very well predicted. These quantities were predicted

well enough that such hand calculations clearly have a role to play in a performance-based code

system. The ability to quickly generate basic results about the effects of a fire could allow one to

focus computational resources towards only those scenarios that warrant more in-depth

computations.

6.1.2 T51.23 CFAST Results

The T51.23 CFAST results in this section are organized according to the predicted parameter,

e.g. temperature, velocity, gas concentrations.

6.1.2.1 T51.23 CFAST Temperature Predictions

The first two figures of this section, Figures 6.1 and 6.2, show the predicted temperatures in the

upper and lower layers of the fire room. The upper layer is overpredicted consistently by 150 °C.

 However, this is within 17 % of the measured value and is thus close to the fire room

temperature criteria of within 15 %, see Table 2.1. The model does show a sudden increase in

rate of temperature rise during the last five minutes of the fire which results in an overprediction

of 30 % or twice the 15 % criterion. During this period, the layer height shifted 0.75 m toward

the ceiling, This drop in the volume of the upper layer results in the increase in the rate of

temperature rise; however, there is no phyiscal cause for the layer height to have shifted in this

manner. The model matches well the cooling trend shown after the fire.

In the lower layer, temperature predictions lie within the range of the measured data. However,

as these measurement locations were subject to a high radiative flux, and the measured data have

not been corrected for this flux, in actuality CFAST is most likely overpredicting the lower layer

temperature by some amount. The post fire coolddown is not matched as well in the lower layer

as it was for the upper layer. The model shows an oscillatory behavior during the first 12

minutes and a change in trend during the last five minutes of the fire. The oscillatory behavior,

which shows 400 °C shifts in temperature and the trend change result from shift in the layer

height trend in the fire room. As with the upper layer results, the fire is at a steady state power,

and thus one would not expect the layer height to move towards the ceiling. 

Figures 6.3 and 6.4 show upper and lower layer temperatures in the hallway. The temperatures

shown are taken from near the center of the hallway's length. This location represents the closest

spot from which one could measure the average hallway properties.

From Figure 6.3 it is observed that the predictions are poor for this location. At the onset, the

predictions lie on top of the data; however, at 1-2 minutes into the fire, the temperatures sharply

decrease. Further oscillations are also seen at the end of the fire. At 50 minutes into the fire the

 

47
model is underpredicting the temperatures by 30 % which is below the 20 % from Table 2.1. As

with the fire room, this behavior is caused by shifts in the layer height.

0

100

200

300

400

500

600

700

800

900

1000

1100

1200

1300

0 10 20 30 40 50 60 70 80 90

Time (min)

Temperature (C)

CT4522

CT4523

CT4532

CT4533

CT4542

CT4543

CFAST

CFAST

Figure 6.1: T51.23 Fire Room Upper Layer Temperatures, Measured vs. CFAST

0

100

200

300

400

500

600

700

800

900

1000

0 10 20 30 40 50 60 70 80 90

Time (min)

Temperature (C)

CT4511

CT4512

CT4513

CT4514

CFAST CFAST

Figure 6.2: T51.23 Fire Room Lower Layer Temperatures, Measured vs. CFAST

Lower layer predictions, Figure 6.4, for the hallway continue the unpredictableness of CFAST

results. The model , while at first matching the data, shows a sharp increase starting at 35

minutes into the fire. In fact, the end temperature prediction of this model exceeds the hallway

upper layer predictions by 350 °C, a nonsensical result. Examination of other parameters reveals

that at 35 minutes CFAST reverses the direction of mass flow in the lower layer of the doorway,

resulting in the addition of hot fire room gasses to the hallway lower layer. It would seem

though, that the partitioning of the energy from the fire room to the two hallway layers could be

improved.

 

48
0

50

100

150

200

250

300

350

400

450

500

550

600

0 10 20 30 40 50 60 70 80 90

Time (min)

Temperature (C)

CT4631

CT4632

CT4633

CT4634

CFAST CFAST

Figure 6.3: T51.23 Hallway Upper Layer Temperatures, Measured vs. CFAST

0

100

200

300

400

500

600

700

800

0 10 20 30 40 50 60 70 80 90

Time (min)

Temperature (C)

CT4628

CT4629

CT4630

CT4662

CFAST

CFAST

Figure 6.4: T51.23 Hallway Lower Layer Temperatures, Measured vs. CFAST

Temperatures on the 1.600 level near the main staircase are shown in Figure 6.5. The lower layer

predictions lie well below the measured data. However, since the layer height in the

compartments comprising the vertical flowpaths were nearly zero, this underprediction is not

meaningful. The upper layer predictions exceed the measured data a maximum deviation of 23

°C. This is close to the 20 °C criteria. Even though the model shows reasonable deviations, the

trends shown are not entirely reasonable. The model reaches its peak temperatures at 50 minutes

into the fire whereas the data does not peak until 60 minutes. The model also shows a spike in

 

49
temperature in the first two minutes of the fire followed by a decrease in temperature for the

second two minutes of the fire.

10

20

30

40

50

60

70

80

90

0 10 20 30 40 50 60 70 80 90

Time (min)

Temperature (C)

CT6609

CFAST Up

CFAST Low

CFAST Upper

CFAST Lower

Figure 6.5: T51.23 Level 1.600 Main Staircase Temperatures, Measured vs. CFAST

The following figure, Figure 6.6, shows temperatures measured in the dome along with the

corresponding CFAST predictions. The lower layer prediction is shown for informative purposes

only, as with the prior plot the layer height is near zero. The CFAST prediction for the upper

layer lies within the measured data and is therefore acceptable.

15

20

25

30

35

40

45

50

55

0 10 20 30 40 50 60 70 80 90

Time (min)

Temperature (C)

CT 411

CT 423

CFAST Up

CFAST Low

CFAST Upper

CFAST Lower

Figure 6.6: T51.23 Dome Temperatures, Measured vs. CFAST

 

50
The last temperature plot, Figure 6.7, shown for the T51.23 CFAST simulation is for the spiral

staircase region on level 1.600. This location is at the end of the circulation loop created by the

fire and is also the source for the air that feeds the fire room. In general the CFAST predictions

are excellent during the fire. The model overpredicts temperatures, but the deviation maximum

is 12 °C. Unlike positions earlier in the circulation loop, CFAST does not predict the cooldown

well at this location. The data shows a temperature maximum almost 7 minutes after the fire

whereas CFAST shows the maximum 5 minutes before the end of the fire. These are time

deviations of 12 minutes and 7 minutes respectively; both of which are greater than the 5 minute

deviation given in Table 2.1.

15

18

21

24

27

30

33

36

39

42

45

0 10 20 30 40 50 60 70 80 90

Time (min)

Temperature (C)

CT 6309

CT6610

CFAST Up

CFAST Low

CFAST Upper

CFAST Lower

Figure 6.7: T51.23 Level 1.600 Spiral Staircase Temperatures, Measured vs. CFAST

6.1.2.2 T51.23 CFAST Velocity Predictions

CFAST outputs the mass flow rate for connections between compartments. The HDR data set

contains velocity measurements. To allow for direct comparison, the CFAST mass flow rates

were converted to velocities. This was done by converting the mass flow rate to a volume flow

rate using the real gas law, and then using the flow area to convert volume flow rate to velocity.

In this manner an average velocity can be derived to compare with the measured data.

The velocity predictions versus measurements for the upper and lower layer of the doorway are

shown in Figures 6.8. Since instrumentation in the doorway consisted of two velocity probes,

one in the upper layer and one in the lower layer, direct comparisons of CFAST to measured data

is not easy to do as CFAST represents the average layer velocity, and the location of the probe in

the profile is unknown.

Velocity predictions are difficult to evaluate for this test. With only the two velocity probes and

with CFAST given layer averaged velocities, intercomparisons cannot be made easily. However,

it is clear the CFAST predicted lower layer velocity of near zero is a very poor prediction. The

upper layer velocity shown is 25 % of the measured velocity. However, since the measurement

 

51
location was near the top of the doorway, where the maximum velocity is expected, the only

conclusion that can be drawn is that the prediction is plausible. What is not plausible, however,

is the sudden spike of upper layer velocity to 10 m/s at 2 minutes into the fire.

-1

0

1

2

3

4

5

6

7

8

9

10

11

0 10 20 30 40 50 60 70 80 90

Time (min)

Velocity (m/s)

CV4640 Up

CV4641 Low

CFAST Up

CFAST Low

CFAST Upper

CFAST Lower

 Figure 6.8: T51.23 Doorway Velocities, Measured vs. CFAST

The upper and lower layer velocities for the hallway are shown in Figures 6.9 and 6.10. For the

first two minutes of the fire the model makes predictions that lie near the data. However, after

the first two minutes the flow through the hallway nearly ceases. Discontinuities are seen again

in both layers at the start and end of the test. CFAST is not performing well for this parameter.

-1

0

1

2

3

4

5

6

0 10 20 30 40 50 60 70 80 90

Time (min)

Velocity (m/s)

CV4657

CV4661

CV4662

CFAST

CFAST

Figure 6.9: T51.23 Upper Hallway Velocity, Measured vs. CFAST

 

52
-1.50

-1.00

-0.50

0.00

0.50

1.00

0 10 20 30 40 50 60 70 80 90

Time (min)

Velocity (m/s)

CV4655

CV4656

CV4657

CFAST

CFAST

Figure 6.10: T51.23 Lower Hallway Velocity, Measured vs. CFAST

0.0

0.5

1.0

1.5

2.0

2.5

3.0

3.5

0 10 20 30 40 50 60 70 80 90

Time (min)

Velocity (m/s)

CF7701

CFAST

CFAST

Figure 6.11: T51.23 Velocity in Main Staircase 1.600/1.700 Hatch Measured vs. CFAST

Figure 6.11 shows the upward velocity leaving the level 1.600 on the main staircase side of the

HDR. Unfortunately, the velocity sensors at lower elevations in this vertical flowpath were

non-functional during this test so comparisons closer to the fire room cannot be made. Strangely,

the temperature discontinuities seen in vertical flowpath is not seen in the velocity profiles. The

CFAST results, while underpredicted, do show the same trend as the measured data. One would

 

53
expect that some form of velocity discontinuity would exist to go along with the temperature one.

Errors in the prediction are in excess of the 30-50 % error band.

6.1.2.3 T51.23 CFAST Gas Concentration Predictions

The first figure of this section, Figure 6.12, shows the oxygen concentration at the interface

between the upper layer of the fire room and the doorway. The predictions for track quite well

with the data for the first 50 minutes of the fire, within 10 %. In the last ten minutes of the fire

the predicted concentration drops rapidly until it is almost 6 v/o (volume percent or mole

fraction) below the data. Since the temperature shows a large spike during this time frame, the

error is at least consistent with the other predicted quantities. Although the model predicts a

partial recovery in the post-fire oxygen concentration, it does not come close to predicting the

near complete recovery in oxygen concentration shown by the data.

0.0

2.0

4.0

6.0

8.0

10.0

12.0

14.0

16.0

18.0

20.0

22.0

0 10 20 30 40 50 60 70 80 90

Time (min)

Oxygen Mole Fraction (v/o)

CG4642

CFAST

CFAST

Figure 6.12: T51.23 Oxygen Concentration in the Upper Doorway, Measured vs. CFAST

The carbon dioxide concentration in the doorway is shown in Figure 6.13 below. Since the fuel

was propane gas premixed with air, input file specification of the combustion products for

CFSAT was trivial. As opposed to a pool fire where the user would have to make assumptions

regarding the combustion product formation. As such, one would expect the CO2 concentrations

to be well predicted and this is the case with this model. The model makes good predictions for

both the upper and lower layer (CG4667 upper layer, CG4666 near interface, CG4665 lower

layer). In the upper layer they are within 16 to 30 % of the measured data, except for the sharp

increase in concentration seen during the last ten minutes of the fire. For the peak concentrations

at the end of the fire this is within the Table 2.1 criteria. In the lower layer the model is within

0.5 v/o for the CO2 concentration.

The final gas concentration figure, Figure 6.14, shows the data from a rake of gas sensors in the

center of the hallway compared to the CFAST predictions for the upper and lower CO2

concentrations in the hallway. In the upper layer the models' predictions lie within the span of

 

54
measured data (CG4654 and CG4663). At this location the jump in the last ten minutes seen in

prior plots is not seen here. In the lower layer, the model doe not show a rise in CO2

concentration until 45 minutes into the fire. At this point the predictions all rise quickly to match

the trend of the measured data only offset by 0.5 v/o.

0

1

2

3

4

5

6

7

8

9

10

0 10 20 30 40 50 60 70 80 90

Time (min)

Carbon Dioxide Mole Fraction (v/o)

CG4665

CG4666

CG4667

CFAST Up

CFAST Low

CFAST Upper

CFAST Lower

Figure 6.13: T51.23 Carbon Dioxide Concentration in the Doorway, Measured vs. CFAST

0.0

0.5

1.0

1.5

2.0

2.5

3.0

3.5

4.0

4.5

5.0

0 10 20 30 40 50 60 70 80 90

Time (min)

Carbon Dioxide Mole Fraction (v/o)

CG4654

CG4663

CG4662

CFAST Up

CFAST Low

CFAST Upper

CFAST Lower

Figure 6.14: T51.23 Carbon Dioxide Concentration in the Hallway, Measured vs. CFAST

 

55
6.1.3 T51.23 FDS Results

The FDS results of this subsection are presented in groups based on the geometric divisions of

the FDS v2.0α model. The results are presented in terms of the fire room, the doorway, and the

hallway

6.1.3.1 Fire Room

The compartment containing the fire is an especially important one for any fire computer model.

For a field model such as FDS, it is critical that both the temperature magnitude and its spatial

variance be accurately predicted. This is due to field models having the greatest potential to

predict the damaging effects of a fire on a local basis within the fire room and adjoining

compartments. That is, the effects that the location of objects within a room and the room's

geometry have on the spatial temperature, radiant heat flux, and mass flux can only be predicted

by a field model.

0

10

20

30

40

50

60

70

0 50 100 150 200 250 300 350 400 450 500

Time (s)

Temperature Change (C)

CT4511

FDS 2.0a

Figure 6.15: T51.23 FDS Results for CT4511

The first figure, Figure 6.15 plots FDS predictions and the measured temperatures at -0.7 m in

absolute HDR elevation, or 15 cm above the floor. Thermocouple CT4511 was located in the

doorway and, thus, was partially shielded from the radiative flux from burners 1 through 3. This

location of CT4511 represents the temperature of the air entering the fire room from the hallway.

The measured data for CT4511 shows a slow temperature rise of 60 °C over the first ten minutes

of the fire. FDS v2.0α shows an increase of 20 °C which is 40 °C lower than the measured

data. However, some of the measured increase is due to radiative heating of the thermocouple

from burners 4 and 5. Thus FDS v2.0α is performing better than the comparison seems to

indicate, but how much so is uncertain due to the errors in the thermocouple measurement. It is

likely that if radiation could be corrected for that FDS v2.0α would be within the 20 °C criteria

in Table 2.1.

 

56
The next figure, Figures 6.16, depicts the FDS results for CT4523 which is near burner #1 at the

+0.2 m HDR elevation, 1.05 m above the floor of the fire room. CT4523 shows a temperature

increase of 550 °C over the first ten minutes. FDS v2.0α makes excellent temperature

predictions with the predictions lying on top of the measured data. Since there is likely to be a

small error in the measured data from radiation the FDS v2.0α predictions for this location falls

within the Table 2.1 criteria.

0

100

200

300

400

500

600

700

0 50 100 150 200 250 300 350 400 450 500

Time (s)

Temperature Change (C)

CT4523

FDS 2.0a

Figure 6.16: T51.23 FDS Results for CT4523

The next figure, Figure 6.17, shows predicted vs. measured data for CT4543 located just beneath

the ceiling of the fire room near the center of the room. FDS v2.0α differs from the measured

data by less than 16 % after the initial transient, which meets the 15 % criteria. Fire room

temperatures are well predicted by FDS v2.0α.

6.1.3.2 Doorway

The following figure, Figure 6.18, shows the FDS predicted temperature profile in the doorway

at the location of two thermocouple rakes in the doorway. FDS v2.0α matches the profile in both

shape and magnitude over the entire doorway.. FDS v2.0α predicts values within 15 % over the

entire height of the doorway.

Figure 6.19 shows a time averaged velocity contour plot in the doorway exit plane for the FDS

simulation. Time averaged values of the two velocity probes in the doorway are shown in text

boxes at the probe locations. FDS shows a typical doorway profile of a counterflow with an

outward flowing hot layer and an inward flowing cold layer. In v2.0α, the measured velocities in

the upper and lower regions of the doorway are close to the measured values.

 

57
0

100

200

300

400

500

600

700

800

0 50 100 150 200 250 300 350 400 450 500

Time (s)

Temperature Change (C)

CT4543

FDS 2.0a

Figure 6.17: T51.23 FDS Results for CT4543

0

100

200

300

400

500

600

700

800

900

1000

-0.6 -0.4 -0.2 0.0 0.2 0.4 0.6 0.8 1.0 1.2

Elevation (m)

Temperature Change (C)

HDR L

HDR R

FDS 1.0 L

FDS 1.0 R

FDS 2.0a L

FDS 2.0 a R

Figure 6.18: T51.23 FDS Doorway Temperature Profile

The final gas concentration figure, Figure 6.20, shown for the doorway is the FDS prediction for

the O2 concentration versus the value measured by O2 sensor CG4642. Two observations are

made from this figure. The first is that FDS predicts a much faster drop in the O2 concentration

than indicated by the data. The data shows a delay of approximately 30 seconds from the start of

the fire before the O2 concentration in the doorway starts to drop whereas FDS shows no delay.

This is most likely due to numerical diffusion due to the relatively coarse noding. The second

observation is that the drop in concentration predicted by FDS is approximately 25 % lower for

v2.0α. FDS v2.0 does not give, therefore, oxygen concentration predictions close enough to the

measured data. This result probably arises from yet to be resolved numerical integration errors in

 

58
the mixture fraction combustion model. It may also result in part from the lower predictions of

velocities in the lower doorway which would result in less air mixing in the fire room and, hence,

lower concentrations in the upper doorway.

3.94 4.15 4.35 4.56 4.77 4.98

0.17

0.26

0.34

0.43

0.51

0.60

0.68

0.77

0.85

0.94

1.02

1.11

1.19

1.28

1.36

1.45

1.53

1.62

1.70

1.79

1.87

1.96

2.04

2.13

2.21

2.30

x (m)

y (m)

5.60-6.00

5.20-5.60

4.80-5.20

4.40-4.80

4.00-4.40

3.60-4.00

3.20-3.60

2.80-3.20

2.40-2.80

2.00-2.40

1.60-2.00

1.20-1.60

0.80-1.20

0.40-0.80

0.00-0.40

3.76

2.19

Figure 6.19: T51.23 Doorway Time Averaged Velocity Contours for FDS v2.0α

-80

-70

-60

-50

-40

-30

-20

-10

0

0 50 100 150 200 250 300 350 400 450 500

Time (s)

Oxygen Mole Fraction (% Change)

CG4642

FDS 2.0a

Figure 6.20: T51.23 FDS Results for CG4642

 

59
6.1.3.3 Hallway

The next two figures, Figure 6.21 and Figure 6.22, show the hallway temperature profile for two

thermocouple rakes and the velocity profile at a location halfway down the hallway. FDS v2.0α

predicts temperatures within 15 % over the entire height of the hallway and also predicts the

same overall temperature gradient as seen in the data. FDS velocity predictions are with 30 % of

the data and have the same overall profile.

0

50

100

150

200

250

300

350

400

450

500

-0.6 -0.4 -0.2 0.0 0.2 0.4 0.6 0.8 1.0 1.2

Elevation (m)

Temperature Change (C)

HDR L

HDR R

FDS 2.0a L

FDS 2.0 a R

Figure 6.21: T51.23 FDS Hallway Temperature Profiles

0.9

1.0

1.1

1.2

1.3

1.4

1.5

1.6

1.7

-1.0 -0.8 -0.6 -0.4 -0.2 0.0 0.2 0.4 0.6 0.8 1.0 1.2

Elevation (m)

Velocity (m/s)

HDR

FDS 2.0a

Figure 6.22: T51.23 FDS Hallway Velocity Profile

 

60
6.1.4 Intercomparison of All Analysis Methods

This section compares the fire room results of the three analysis methods with the data. These

comparisons are made at 15 minutes into the fire, the length of the FDS simulation. Table 6.2

summarizes the results for key parameters of the fire room using the best results of each analysis

method. The velocities shown in the table for the three analysis methods represent the layer

averaged velocities.

Table 6.2: Steady State Fire Room Predictions for All T51.23 Analyses

Compared to Data

O2 Concentration (v/o) 11.6 N/A 10.0 7.6

Layer Height (m) 1.0 0.7 0.7 0.9

Lower Velocity (m/s) 2.3 0.4 0.0 1.1

Upper Velocity (m/s) 4.5 3.3 1.2 2.8

Upper Temperature (°C) 730 834 870 808

Quantity Data Hand Calc. CFAST FDS

The results shown in this table are somewhat surprising. The hand-calculation performs nearly

as well as the other two methods. CFAST has the poorest temperature prediction while FDS has

the poorest oxygen prediction. FDS does quite well though in predicting the layer height and the

upper layer temperature. Velocity predictions cannot be directly compared to the data as the data

consists of only two points from which a layer average cannot be determined. However, it is

clear the CFAST’s predictions are relatively poor considering the 0 m/s prediction for the lower

layer velocity.

6.2 T52.14 SIMULATION RESULTS

The results of the T52.14 oil pool fire test simulations are discussed in the following four

sections. The sections individually describe the results of the three calculation methods applied

to the T52.14 oil pool fire test as well as given an intercomparison of the three methods.

6.2.1 T52.14 Hand Calculation Results

Equations 7-9 were entered into Mathematica v3.0 ®. Before solving these equations a number

of variables needed to be defined. The doorway loss coefficient Cd was defined as 0.71. The

ambient temperature was defined as 300 K. The upper layer wall surface area was calculated

from the room geometry as 31.49 m2. The gas molar mass was taken to be that of air, 0.0288

kg/mol. The ambient pressure was assumed to be 101 kPa (1 atm.) Lastly, the wall heat transfer

coefficient was calculated from the wall heat conduction assuming steady-state heat transfer. For

simplicity all the fire room walls were assumed to be 0.25 m of the Ytong firebrick. This results

in hk=0.96 W/m2

⋅K. The following solutions were obtained by Mathematica ®:

 

61
Table 6.3: T52.14 Hand Calculation Results

HN (m) 1.0332

2.1577 *

mg (kg/s)

ρg (kg/m 0.2340 3)

Tg (°C) 1227

Variable Hand Calc

Measured fire room temperatures for this test occurred in two planes located above the oil pool.

These planes were at the +27 m elevation, the middle of the fire room, and the +28 m elevation,

0.55 m below the ceiling. If the data is averaged over the time period from 20 to 30 minutes,

approximately the last ten minutes of the fire when the data indicates steady-state conditions

exist, the measured temperatures range from 577 °C to 1166 °C with an average of 872 °C. The

hand calculation value of 1227 °C lies 350 °C above the average, 41 % difference in

temperature, and 100 °C above the upper bound of the measured values, a difference of 11 % in

absolute temperature. The average temperature for this prediction exceeds the recommended 15

% threshhold given in Table 2.1.

The hand calculation in this case is not making as good a prediction as it did for T51.23.

However, unlike T51.23, the boundary conditions outside the fire room are significantly

different. The presence of the tremendous vertical flow through the maintenance shaft just

outside the fire room is not a boundary condition typically encountered in fire experiments and,

thus, is not one for which the hand calculation methods account and have been developed for.

Thus, this presents a challenging test for such methods.

Table 6.4 gives the temperature profile in the fire room doorway averaged over the time period

from 20 minutes to 30 minutes. Both the absolute sensor positions and the positions relative to

the fire room floor are listed. This table indicates that the layer in the doorway is positioned

about 1.5 m above the floor. Table 6.5 shows the doorway velocity profile. From this table the

neutral plane is shown to be between 1.1 m and 1.6 m above the fire floor with the actual

number closer to 1.6 m. The hand calculation predicts a neutral plane location of 1.03 m or

about 0.5 m below the measured value; this is an error of 30 % which is acceptable according to

Table 2.1.

Using the neutral plane location, mass flow rate, and the layer densities the average layer

velocities can be calculated. This calculation yields an average upper layer velocity of 5.5 m/s

and an average lower layer velocity of 1.9 m/s. From this we see that the upper layer velocity is

well predicted by the hand calculation. However, since the temperature is greatly overpredicted

the mass flow rate is actually being underpredicted by 25 %. In essence, the hand calculation can

not account for the jet pump like effect created by the upward flow in the maintenance shaft.

This underprediction is acceptable, however.

 

62
Table 6.4: T52.14 Measured Fire Room Doorway Average Temperatures

(Average from 20 min to 30 min)

CT9651 25.60 0.05 80

CT9653 25.90 0.35 117

CT9657 26.90 1.35 455

CT9658 27.15 1.60 758

CT9642 27.35 1.80 1147

CT9641 27.45 1.90 1107

CT9640 27.55 2.00 1156

CT9639 27.65 2.10 1147

CT9637 27.85 2.30 1170

CT9633 28.25 2.70 1128

CT9632 28.35 2.80 1154

CT9631 28.45 2.90 1180

Temperature

(°C)

Relative Elevation

(m)

Absolute Elevation

(m) Sensor

Table 6.5: T52.14 Measured Fire Room Doorway Average Velocities 

(Average from 20 min to 30 min)

CV9606 25.65 0.10 -1.28

CV9605 26.15 0.60 -1.72

CV9604 26.65 1.10 -1.64

CV9603 27.15 1.60 0.81

CV9602 27.55 2.00 4.86

CV9601 27.95 2.40 2.55

CV9600 28.25 2.70 7.89

Velocity

(m/s)

Relative Elevation

(m)

Absolute Elevation

(m) Sensor

The following table, Table 6.6, shows the results of the Chen-Rodi and the Integral Analysis for

the plume rising into the dome. The results are tabulated for the elevations of the two

measurement grids in the dome at +31 m and +39 m. The predicted neutral layer position, fire

room temperature, and the mass flow rate were used as the initial plume conditions for both

methods. It was assumed that a plume with the fire room temperature, doorway out-flowing

velocity, and hydraulic diameter based on the neutral plane originated below the maintenance

hatch at the elevation of the top of the doorway.

 

63
Table 6.6: T52.14 Plume Hand Calculation Results

Radius (m) N/A 1 N/A 1

Temperature (°C) 959 229 55 66

Velocity (m/s) 9 7 5 6

Chen-Rodi Integral Chen-Rodi Integral

Method Method

+31 m grid + 39 m grid

Location

Parameter at

Centerline

 

Figures 6.23 and 6.24 show the measured temperatures for both grids averaged over the time

period from 20 to 30 minutes, while figures 6.33 and 6.44 depict the velocities for the same time

period. Due to the inability to resolve upward velocities at the +31 m grid due to cross flow at

the hatch affecting the velocity sensors, a contour plot for the velocity is not possible.

x (m)

y (m)

-7.5 -7.0 -6.5 -6.0 -5.5

0.00

0.25

0.50

0.75

1.00

1.25

1.50

1.75

Temperature (C)

438.8

420.0

401.1

382.3

363.4

344.6

325.7

306.9

288.0

269.2

250.3

231.4

212.6

193.7

174.9

156.0

137.2

118.3

99.5

80.6

HDR DATA +31 m

Figure 6.23: T52.14 +31 m Sensor Grid Average Temperatures (Average from 20 min to 30 min)

 

64
x (m)

y (m)

-8.5 -8.0 -7.5 -7.0 -6.5 -6.0 -5.5 -5.0 -4.5

-1.0

-0.5

0.0

0.5

1.0

1.5

2.0

2.5

Temperature (C)

149.1

146.4

143.8

141.1

138.4

135.8

133.1

130.4

127.7

125.1

122.4

119.7

117.1

114.4

111.7

109.0

106.4

103.7

101.0

98.4

HDR DATA +39 m

Figure 6.24: T52.14 +39 m Sensor Grid Average Temperatures (Average from 20 min to 30 min)

3.808

3.292

3.270

3.429

2.422

x (m)

y (m)

-7.5 -7.0 -6.5 -6.0 -5.5

0.00

0.25

0.50

0.75

1.00

1.25

1.50

1.75 Velocity (m/s)

HDR DATA +31 m

Figure 6.25: T52.14 +31 m Sensor Grid Average Velocities (Average from 20 min to 30 min)

 

65
x (m)

y (m)

-8.5 -8.0 -7.5 -7.0 -6.5 -6.0 -5.5 -5.0 -4.5

-1.0

-0.5

0.0

0.5

1.0

1.5

2.0

2.5

Velocity (m/s)

4.0

3.8

3.5

3.3

3.0

2.7

2.5

2.2

2.0

1.7

1.5

1.2

1.0

0.7

0.4

0.2

-0.1

-0.3

-0.6

-0.8

HDR DATA +39 m

Figure 6.26: T52.14 +39 m Sensor Grid Average Velocities (Average from 20 min to 30 min)

The first pair of figures, Figures 6.23 and 6.24, indicate centerline temperatures of 440 °C and

150 °C respectively. At the +31 m grid the Chen-Rodi correlation overpredicts the temperature

by 520 °C and the integral method by 210 °C, 118 % and 48 % errors respectively. Both

methods do not predict within the Table 2.1 guidelines. At the +39 m grid the Chen-Rodi

correlation underpredicts the temperature by 95 °C, a 63 % error. The integral method

underpredicts the temperature by 84 °C, a 56 % temperature difference.

The upper grid predictions appear to show that both models are under-predicting the upper grid

temperature. However, given that both methods underpredicted the +31 m grid temperatures, it

is expected that they would both underpredict the upper grid. A better test is the drop in

temperature which is a function of the entrainment prediction. The relative drops in temperature

for the T52.14 test, the Chen-Rodi, and the integral method are 66 %, 94 %, and 71 %

respectively. With this comparison it is clear that in this case the Chen-Rodi correlation is

overpredicting the entrainment whereas the integral method appears to have captured the

entrainment quite well. 

The second pair of figures, Figures 6.25 and 6.26, show plume centerline velocities of greater

than 3.3 m/s and 4.27 m/s respectively. Due to the sparse information at the +31 m grid,

quantitative conclusions are not possible. Qualitatively, it is clear that the Chen-Rodi correlation

at this location is greatly overpredicting the centerline velocity. The integral method is also

over-predicting the velocity at this elevation. At the upper grid both methods overpredict the

velocity by 26 % and 35 % respectively.

 

66
The poor predictions made for the lower grid result from the fact that the plume at this location

is a wall plume and, hence, lacks the total entrainment of the free plume assumed in the two

models. Furthermore, the temperature profile in the data indicates a likelihood that some

counter-current flow is occurring in the hatch. This would also act to reduce the entrainment of

the plume. This reduction in entrainment results in a higher measured temperature than the

model predicts. Neither plume analysis method is well suited to this particular location. In this

far field location with a correlation method such as these, predictions closer to 30 % should be

possible.

In addition to temperature and velocity predictions, the integral method also calculates the plume

radius. The integral method assumes a Gaussian plume shape. For the derivation used for this

work, the radius referred to that location where the velocity was 1 % of the centerline velocity.

With a centerline velocity of 4.27 m/s, occurring at HDR (x,y) coordinates of (-7.61 m, 1.58 m), 

the radius of the plume at the +39 m grid would be at the location of an upward velocity of 0.04

m/s which occurs at HDR (x,y) coordinates of (-5.82 m, 0.23 m). This is a radius of 2.25 m,

almost twice the predicted value.

The Gaussian functions for velocity, density, and radius function used in the integral plume

method can also be used to determine the mass flow at a given elevation in the plume. This is

done be integrating Equation 20 using the solutions obtained from the integral model. This

integration was performed at the positions of the operating deck and at the plume's impingement

point on the dome's hemispherical head. Knowledge of these values plus conservation of mass

allows the calculation of the mass flows shown in the following table, Table 6.7.

Table 6.7: T52.14 Mass Flow Rates at Key Locations

6 Circulation loop 7 #2

4 Dome Recirculation 28 #3 - #2

Integrate at steel

shell

3 Flow at plume top 34

Integrate at

operating deck

2 Flow into dome 7

1 Upper doorway 2 Hand-calc output

How Obtained Mass Flow Rate

(kg/s) # Location

Assuming temperatures near the ambient in the main staircase maintenance hatch on the opposite

side, the circulation loop mass flow rate can be used to calculate an average velocity through the

circulation loop. A mass flow of 6.62 kg/s at ambient temperature through the 4.54 m2

maintenance hatch yields an average velocity of 1.25 m/s through the hatches. Table 6.8 below

gives the measured velocities in the flow loop. For all locations the hand calculation has greatly

overestimated the velocities through the flow loop. Three factors may account for a portion of

this. First, it is already known that the mass flow rate at the measurement grid at the operating

deck is overestimated since the hatch restricts flow and the analysis assumed a free plume.

Second, soot deposition on the paddlewheel flow sensors does degrade performance for low flow

rates. Thirdly, a fraction of the mass flow seen at the hatch results from countercurrent flow of

 

67
the containment atmosphere recirculating in the dome and descending the hatch near the fire

room alongside the rising plume. Combined these effects, probably account for much of the

error.

Table 6.8: T52.14 Velocities in Circulation Loop

CF9205 Spiral staircase 1.900 level 0.662

CF7802 Spiral staircase 1.700 level 0.096

CF6602 Main staircase 1.600 level 0.043

CF7703 Main staircase 1.700 level 0.004

CF9301 Main staircase 1.900 level 0.005

Velocity

(m/s) Sensor Location

In the dome, if the ambient conditions outside the plume are considered to be near room

temperature, the recirculation flow in the dome can be calculated. If 27.84 kg/s of mass is being

recirculated in the dome due to the plume entrainment, this corresponds to a turnover time of 200

seconds, i.e. 3.4 minutes. This implies that over the thirty minutes of the fire that the upper dome

atmosphere was recirculated in the dome nine times. This is a tremendous air exchange given

the 5000 m3 size of the dome and is most likely an overestimation by the model. However, since

the model assumes a free plume and the dome is not an infinite volume, it is not surprising that

this would be overpredicted. This does give insight, however, that a tremendous recirculation is

occurring inside the dome.

6.2.2 T52.14 CFAST Results

The T52.14 CFAST results in this section are organized according to the predicted quantities ,

e.g. temperature, velocity, and gas concentrations

6.2.2.1 T52.14 CFAST Temperature Results

The first figures, Figure 6.27 shows the CFAST predicted upper and lower layer temperatures

versus measured data in the fire room. The thermocouple locations for this test were all in the

upper layer, so no direct comparisons can be made for the lower layer. Predictions are somewhat

overpredicted during the peak of the fire but lie within the measured data for the steady-state

portion of the fire. In the lower layer the model lies below the spectrum of data in the fire room.

Given the absence of thermocouples at lower elevations in the fire room, the only conclusion that

can be drawn is that for the model, CFAST is making a physically realistic computation.

However, for both layers the model results do not show as rapid a cooldown as indicated by the

data, although it is fairly close . CFAST temperature predictions also follow the burning rate

trend to a much larger degree than shown in the data. This indicates that CFAST is not fully

capturing heat storage and release phenomena from the room surfaces.

 

68
0

200

400

600

800

1000

1200

1400

1600

0 5 10 15 20 25 30 35 40 45 50 55 60

Time (min)

Temperature Change (C)

CFAST Up

CFAST Low

CT9606

CT9608

CT9611

CT9616

CFAST Lower

CFAST Upper

Figure 6.27: T52.14 Fire Room Temperatures, Measured vs. CFAST

The observations above have a number of factors that could be contributing to them. Since

CFAST overpredicts the peak of the fire, it is possible that the pyrolysis curve supplied by the

HDR facility overspecifies the peak of the fire leading to elevated temperature predictions. The

cooldown errors seen also most likely result from mass flow prediction errors, with CFAST

predicting too quick of a stop in the HDR model circulation after the fire.

The CFAST calculated layer heights for the fire room area and the hatch area are shown in Figure

6.28. The only location for which enough instrumentation is present to determine the layer

height is in the doorway. Test data indicates that the layer interface is positioned near +26.9 m in

elevation or 1.35 m above the floor of the doorway. Since the fire room layer height calculated

by CFAST is the average height over that entire region including the doorway, one would expect

the CFAST prediction to be slightly lower than that measured in the doorway. Also, the layer in

the hatch area is expected to by predicted higher than the fire room. This is indeed the case. The

fire room layer height is predicted to be 0.5 m below that measured in the doorway, and the hatch

area has a larger layer height than the fire room. CFAST predictions are excellent for this

parameter.

 

69
25.0

25.5

26.0

26.5

27.0

27.5

28.0

28.5

29.0

29.5

30.0

30.5

31.0

0 5 10 15 20 25 30 35 40 45 50 55 60

Time (min)

Layer Position (Abolsute Elevationm)

Fire Room

Hatch

Dome Operating Deck

Doorway Ceiling

Fire Room Ceiling

Fire Room Floor

Level 1.900 Floor

Figure 6.28: T52.14 CFAST Predicted Layer Heights

Figure 6.29 below shows the CFAST predicted temperatures in the compartment constructed

below the maintenance hatch to the dome. The region within the compartment was not

instrumented, however the inlet and exit hatches to this region were heavily instrumented.

Therefore, the CFAST results for the upper layer are shown in comparison to the instrumentation

grids located in the upper hatch. For the upper layer, it is important to realize that the flow field

in this location consisted of a wall plume rising through the hatch corner nearest the fire room

doorway. That is, the plume did not rise through the center of the hatch. For this situation it is

difficult to define an upper layer temperature based on test data, as in this case an upper layer did

not exist in a traditional sense. At best, for the upper layer CFAST can be expected to predict

temperatures that lie within the range of temperatures seen in the plume, and indeed this is what

occurs with CFAST results lying in the middle of the data’s span. Except for during the

cooldown, the model predicts the same temperature profiles seen in the data. 

 

70
0

100

200

300

400

500

600

700

0 5 10 15 20 25 30 35 40 45 50 55 60

Time (min)

Temperature Change (C)

CT 456

CT 457

CT 458

CT 462

CT 467

CFAST Up

CFAST Low

Figure 6.29: T52.14 Fire Level Hatch Upper Layer Temperatures, Measured vs. CFAST

Figure 6.30 shows CFAST predictions along with the corresponding measurements for the upper

sensor grid. This locations represents the conditions of the atmosphere entering the upper region

of the dome. Since the layer height in this regions quickly dropped to near zero, the lower layer

is not meaningful for comparisons. The data shown represent the spread of temperatures seen in

the plume entering the upper dome. Since CFAST results represent a volume averaged

temperature for this region, one would anticipate CFAST to be predicting well below the highest

measured temperatures as the plume only occupied a fraction of this region. The model predicts

temperatures that lie near the highest measured temperatures at the upper sensor grid. CFAST is,

therefore, over predicting the volume average temperature substantially in this region. The post

fire cooldown is well predicted.

CFAST predictions compared with measured temperatures at the bottom of the global circulation

loop are depicted in Figure 6.31. The temperatures shown are from a vertical rake located in the

level 1.600 hallway connecting the main staircase side of the HDR with spiral staircase side. The

data from the rake indicates that this region of the containment only saw a small temperature

increase of a few degrees and that only during the early growth of the fire. During the fuel

addition portion of the test, conditions were back to ambient. The CFAST model predicts both

too large of a temperature increase during the test and do not cool back to ambient conditions

during the fuel addition portion of the test. Furthermore, during the first five minutes of the fire

the lower layer predictions exceed the upper layer predictions. After this point the predicted

layer height decreases rapidly and the lower layer predictions lie nearly on top of the measured

data; however, the layer height at this point lies below the measured data locations. It is clear

that CFAST is not correctly predicting the flow circulating through the HDR. It is possible that

further experimentation with flow connections between the two sides of the facility could

 

71
improve predictions lower in the facility. However, there is little guidance to the code user on

such issues.

0

15

30

45

60

75

90

105

120

135

150

0 5 10 15 20 25 30 35 40 45 50 55 60

Time (min)

Temperature Change (C)

CT 440

CT 441

CT 442

CT 443

CT 444

CFAST Up

CFAST Low

Figure 6.30: T52.14 Upper Sensor Grid Temperatures, Measured vs. CFAST

0

2

4

6

8

10

12

14

16

0 5 10 15 20 25 30 35 40 45 50 55 60

Time (min)

Temperature Change (C)

CT6614

CT6617

CT6620

CFAST Up

CFAST Low

Figure 6.31: T52.14 Level 1.600 Temps Near Spiral Staircase, Measured vs. CFAST

 

72
6.2.2.2 T52.14 CFAST Velocity Results

The first figure in this section, Figure 6.32, compares the CFAST predicted velocities to

measured values for the upper layer and lower layer of the doorway. The measured values shown

for the doorway are not the actual sensor readings, for all but the uppermost sensor, CV9600, the

measured fluctuating data from the facility were smoothed greatly before being added to the

electronic dataset.

In the upper layer, CFAST predictions lie near the average of the data during the fire. One

cannot expect a better prediction from a zone model code. After the fire, however, the model

shows a instantaneous drop to zero where the data clearly indicates that a small region of the

upper doorway still has a substantial outward flow of 1 m/s at 60 minutes.

In the lower layer, the model overpredicts the velocity by greater than 75 %. Also, during the

post-fire cooldown the model predicts a small outward flow whereas the data indicates a small

inward flow still exists in the lower layer. These results are somewhat puzzling. Since CFAST

appears to be overpredicting the amount of cool air entering the fire room, one would expect the

CFAST predicted temperatures in the fire room to tend towards underprediction. This was not

the case as seen in Figure 6.27 which shows an overpredictiion of the fire room temperature.

This would indicate that some aspect of the room heat transfer calculation is being

underpredicted leading to the overprediction of temperature.

-4

-2

0

2

4

6

8

10

0 5 10 15 20 25 30 35 40 45 50 55 60

Time (min)

Velocity (m/s)

CV9600

CV9601

CV9602

CV9603

CV9604

CV9605

CV9606

CFAST Up

CFAST Low

Figure 6.32: T52.14 Doorway Velocities, Measured vs. CFAST

The following figure, Figure 6.33, shows velocities leaving the fire room level and entering the

dome through the maintenance hatch. The CFAST model results in velocity predictions which

are about 50 % below the measured velocities. However, since the upward flow did not actually

 

73
occupy the whole hatch but rather 1/3 to 1/2 of the hatch, the CFAST predictions are correct in

terms of mass flow. Unlike the T51.23 CFAST model, the first region of vertical flow after the

fire room is very well predicted for T52.14. This is a tremendous accomplishment for a zone

model code and after the results from the T51.23 simulations, a completely unexpected result.

-0.5

0.0

0.5

1.0

1.5

2.0

2.5

3.0

3.5

4.0

4.5

5.0

5.5

0 5 10 15 20 25 30 35 40 45 50 55 60

Time (min)

Velocity (m/s)

CV 480

CV 484

CV 486

CFAST

Figure 6.33: T52.14 Fire Level to Dome Velocities, Measured vs. CFAST

The last velocity figure, Figure 6.34, shows the velocity entering the downward flowpath on the

main staircase side of the HDR. It is clear that CFAST models is greatly overpredicting the flow

down the main staircase maintenance hatches. In all fairness, some of this is do to the model

itself which does not contain a flowpath connecting the sides of the lower dome and, thus, forces

more air down the main staircase. However, in prior work performed by the author45 in which a

connection in the dome was made, the results were lower temperatures in the upper dome, higher

temperatures in the main staircase side of the building, and the same magnitude of velocity

prediction at this location. These results would indicate that CFAST may not be capable of

calculating flows inside of large volumes. This is in contrast to work done by Chow55 which had

success in using CFAST to model a large volume by subdividing that volume into smaller

compartments. However, that work only subdivided the volume horizontally, not horizontally

and vertically as was done by this author. CFAST's performance here is not surprising as

CFAST was never designed with such flows in mind; however, this does question the ability to

use CFAST for large atrium style spaces. Further work is warranted in examining the use of such

subdivisions for modeling large volumes with CFAST.

6.2.2.3 T52.14 CFAST Gas Concentration Results

Figures 6.35, compares measured values for the oxygen, carbon dioxide, and carbon monoxide

concentrations in the upper layer of the doorway with CFAST predictions. As discussed in the

introductory sections, one of the greatest challenges for modeling a fire is the description of the

combustion process, especially for underventilated fires. Unless an experiment exists for the

exact geometry and test conditions being modeled, a CFAST user must make assumptions

 

74
regarding the combustion product outcomes for a fire. These assumptions greatly impact its

predictive capabilities. The following figures will illustrate aspects of this difficulty.

0.0

0.3

0.6

0.9

1.2

1.5

0 5 10 15 20 25 30 35 40 45 50 55 60

Time (min)

Velocity (m/s)

CFAST

CV 434

CV 9301

Figure 6.34: T52.14 Dome to Level 1.900 by Main Staircase Velocities, Measured vs. CFAST

0

2

4

6

8

10

12

14

16

18

20

22

0 5 10 15 20 25 30 35 40 45 50 55 60

Time (min)

O2, CO2 Mole Fraction (v/o)

0.0

0.5

1.0

1.5

2.0

2.5

3.0

3.5

4.0

4.5

5.0

5.5

CO Mole Fraction (v.o)

CG9602-O2

CG9603-CO2

CFAST O2

CFAST CO2

CG9601-CO

CFAST CO

Figure 6.35: T52.14 Doorway Upper Layer O2, CO2, and CO, Measured vs. CFAST

The CFAST prediction for oxygen, up until the peak of the fire near four minutes, lies ontop of

the measured oxygen concentration. At this point in time the predictions and the data diverge.

The CFAST prediction undergo an oscillation between 6 v/o and 10 v/o and then 6 v/o and 12

v/o as the fire's intensity dwindles before the fuel addition begins. After the fuel addition starts

the CFAST prediction slowly decreases to 8 v/o. The measured concentration shows a markedly

 

75
different behavior. After the peak of the fire, the data continues to decrease until the upper layer

is completely depleted of oxygen. This condition remains until the end of the fire. CFAST does

not successfully predict the oxygen concentration in the fire room during the fire. At the end of

the fire the CFAST predicted concentrations do not fully recover to near ambient conditions.

The data, however, show a quick recovery to the original concentration after the fire ends,

followed by a slow decrease of 2 v/o as the global circulation loop continues to mix the

oxygen-depleted atmosphere deposited in the dome throughout the facility.

Similar observations can be made for the CO2 concentration prediction. Again CFAST

performance is excellent during the first two minutes of the fire, but afterwards the predictive

quality worsens considerably. During the steady-state portion of the fire, the model

underpredicts the CO2 concentration by 8 v/o, 4 v/o predicted versus 12 v/o measured, an error of

66 % which is well outside acceptable limits. A portion of this may be due to combustion

product specification in the input file, however, if the mass of CO and soot specified in the input

file were zeroed out this would only increase the amount of CO2 by 2.5 times or from 4 v/o to 10

v/o. This would be a 16 % error; however, since soot and CO are being produced, much of the

error is not due to the input but rather the code computations. The code is not predicting the CO2

concentration well.

The CO predictions by CFAST do not ameliorate the situation. The beginning of the fire is

rather well predicted, but the peak CO concentration is greatly underpredicted by at least 2 v/o.

The real extent of the underprediction is unknown due to a range selection error for the CO

sensor (the sensor maxed out at 4.5 v/o). During the steady-state portion of the fire, the CO

predictions range from 1 v/o to 2 v/o above the measured values lying between 1 v/o and 1.5 v/o.

Since CO production is primarily specified by the user, the underprediction of the peak and the

overprediction of the steady-state portion most likely result from a poor input specification. The

failure of the CO2 prediction is further bolstered by the CO prediction. If all the CO that was

overpredicted was CO2, the CO2 prediction would still be 6 v/o too low.

Figure 6.36 shows the CFAST predicted concentration of CO2 entering the upper dome. The

measured values shown in the figure are from the uppermost measurement grid at +39 m, 1 m

below the start of the containment dome’s hemispherical head. At this location CFAST matches

the overall trend shown in the date, but is overpredicting the measured concentrations by 25 %.

Since the measurement locations lie inside the plume and CFAST is predicting for the volume of

the entire region beneath the measurement grid, one would expect CFASR predictions to be

slightly less than the measured data. Thus, the 25 % error is actually a lower bound on the error.

The final T52.14 CFAST figure, Figure 6.37, shows the measured versus predicted CO2

concentrations in the upward flow maintenance shaft. As with the dome CFAST predicts a

similar transient behavior as seen in the data. However, CFAST predicts a drop in maximum

concentration of 0.3 v/o from the dome whereas the data shows a drop of 0.7 v/o. The end result

is that CFAST is overpredicting the maximum concentration by 100 %. CFAST does correctly

predict the fact that there is no concentration decrease at this location after the fire. This correct

prediction of the end of the fire is not strictly a success for CFAST, however, given that for most

 

76
other parameters and locations CFAST did not make good predictions for the cooldown phase of

the fire.

0.0

0.4

0.8

1.2

1.6

2.0

2.4

2.8

3.2

3.6

4.0

0 5 10 15 20 25 30 35 40 45 50 55 60

Time (min)

CO2 Mole Fraction (v/o)

CG 414

CG 415

CG 416

CFAST

Figure 6.36: T52.14 CO2 Concentration at the Dome Hemispherical Head Over the Fire Room,

Measured vs. CFAST

0.0

0.3

0.6

0.9

1.2

1.5

1.8

2.1

2.4

0 5 10 15 20 25 30 35 40 45 50 55 60

Time (min)

CO2 Mole Fraction (v/o)

CG7802

CFAST

Figure 6.37: T52.14 CO2, in Upward Flow Path 1.700 Level, Measured vs. CFAST

 

77
6.2.3 T52.14 FDS Results

The FDS results of this subsection are presented in groups based on the geometric divisions of

the FDS model. The results are presented in terms of the fire room, the doorway, the hatch

region, and the dome.

6.2.3.1 Fire Room

The first comparison, Figure 6.38, compares FDS predictions with the temperatures from a

sensor is located in the corner of the fire room diagonally opposite the doorway. FDS v2.0α

again performs well in the fire room. At the peak of the fire, which occurred near 190 s, FDS

v2.0α is predicting a temperature change 27 % higher than measured as this location. There are a

number of possiblities as to why the temperature is being overpredicted. A few are: not a high

enough noding resolution, predictive errors in the radiation heat transfer, and the assumption of

perfect combustion (e.g. not account for soot and CO production) which results in a higher

effective heat of combustion inside the fire room.

0

300

600

900

1200

1500

0 30 60 90 120 150 180 210

Time (s)

Temperature Change (C)

CT 9602

FDS 2.0a

Figure 6.38: T52.14 FDS Results for CT9606

The table below, Table 6.9, shows the measured vs. predicted temperatures in the fire room

during the peak of the fire. These were obtained by averaging the data and the predictions over

the time span from 188 seconds to 211 seconds after the start of the fire. FDS v2.0α averages a

19 % overprediction inside the fire room, which is within the Table 2.1 criteria..

 

78
Table 6.9: T52.14 FDS Results for the Fire Room During Fire Peak

CT9622 °C 1,267 1,312 4 %

CT9621 °C 888 1,441 62 %

CT9620 °C 1,244 1,269 2 %

CT9169 °C 905 1,354 50 %

CT9618 °C 1,222 1,255 3 %

CT9617 °C 917 1,144 25 %

CT9616 °C 1,194 1,099 8 %

CT9615 °C 955 1,237 30 %

CT9613 °C 728 1,178 62 %

CT9612 °C 974 996 2 %

CT9611 °C 910 1,121 23 %

CT9610 °C 892 1,034 15 %

CT9609 °C 1,165 1,192 9 %

CT9608 °C 1,339 1,331 2 %

CT9606 °C 1,052 1,319 24 %

CT9604 °C 1,209 1,381 13 %

CT9603 °C 1,199 1,313 7 %

CT9602 °C 989 1,249 23 %

Sensor Type HDR FDS 2.0α Error

6.2.3.2 Doorway

The first two figures of this section, Figures 6.39 and 6.40 show the doorway temperature and

velocity profiles during the peak of the fire. The measured data comes from a rake of

thermocouples and pitot tubes at the centerline of the doorway. In Figure 6.39 it is observed that

FDS v2.0α is correctly predicting the temperature profile in the top of the doorway. FDS also

predicts a velocity profile prediction for the lower region of the doorway which matches the

profile seen in the data. In the upper portion of the doorway; however, FDS predicts a profile

that decreases in velocity at the highest measurement location where the data shows a high

velocity measurement. This discrepancy most likely results from a combination of the noding

resolution in the upper doorway being too coarse and errors in the sensor due to the high

temperatures and soot concentrations that occurred during the test.

 

79
25.5

26.0

26.5

27.0

27.5

28.0

28.5

0 200 400 600 800 1000 1200 1400

Temperature Change (C)

HDR Elevation (m)

HDR

FDS 2.0a

Figure 6.39 T52.14 FDS Results for Doorway Temperature Profile During Fire Peak

25.5

26.0

26.5

27.0

27.5

28.0

28.5

-4 -2 0 2 4 6 8 10

Velocity (m/s)

HDR Elevation (m)

HDR

FDS 2.0a

Figure 6.40 T52.14 FDS Results for Doorway Velocity Profile During Fire Peak

The following table, Table 6.11, shows measured vs. Predicted values for the sensors in the

doorway during the peak of the fire. These values were obtained in the same manner as for Table

6.10. As with the fire room. FDS v2.0α temperature predictions are excellent in the upper

region of the doorway. The doorway lower level predictions are more difficult to assess due to

thermocouple errors. It is also worth noting the FDS v2.0α makes an improved prediction of the

oxygen concentration in the upper doorway as compared to the T51.23 predictions as well as

makes an adequate prediction of the carbon dioxide concentration in the upper doorway.

 

80
 Table 6.10: T5214 FDS Results for the Doorway During Fire Peak

CG9603 v/o CO2 10.8 12.4 14 %

CG9602 v/o O2 0.65 0.13 2 %

CV9606 m/s -1.54 -1.69 9 %

CV9605 m/s -2.11 -2.22 5 %

CV9604 m/s -2.17 0.86 139 %

CV9603 m/s 2.12 4.02 90 %

CV9602 m/s 5.78 5.98 36 %

CV9601 m/s 5.24 7.08 35 %

CV9600 m/s 9.09 5.89 35 %

CT9658 °C 679 1,021 50 %

CT9657 °C 679 795 17 %

CT9653 °C 322 9 97 %

CT9651 °C 323 19 94 %

CT9642 °C 1,262 1,141 10 %

CT9641 °C 1,243 1,184 5 %

CT9640 °C 1,264 1,223 3 %

CT9639 °C 1,258 1,257 0 %

CT9637 °C 1,255 1,308 4 %

CT9633 °C 1,277 1,299 2 %

CT9632 °C 1,267 1,271 0 %

CT9631 °C 1,269 1,247 2 %

Sensor Type HDR FDS 2.0α Error

6.2.3.3 Upper Hatch

Table 6.11 shows the FDS predictions compared with the measured data for sensors located in

the hatch leading to the dome from the fire room during the peak of the fire. Both versions make

similar predictions in terms of predictive quality. The main reason for the large discrepancies in

temperature is that FDS is predicting a somewhat more narrow plume in the hatch than indicated

in the data. This could be the result of not enough grid points in the hatch region. Also this

could result from model itself. In actuality the containment building shaft near the fire room

acted like a jet pump, creating a large circulation loop inside the facility. This along with the

recirculation the occurred in the dome are not being captured by FDS since the model did not

include the entire facility. To have included the entire facility would have been impractical,

however, due to the immense amount of nodes that would have been required. Velocity

predictions are also poor in this location. 

 

81
Table 6.11: T52.14 FDS Results for the Upper Hatch During Fire Peak

CV 490 m/s 2.67 1.44 46 %

CV 488 m/s 3.18 1.82 42 %

CV 486 m/s 3.06 4.69 53 %

CV 484 m/s 3.85 5.82 51 %

CV 480 m/s 4.22 -0.15 113 %

CT 479 °C 31 21 32 %

CT 477 °C 71 51 29 %

CT 475 °C 36 13 64 %

CT 473 °C 75 46 38 %

CT 471 °C 137 24 82 %

CT 469 °C 58 29 50 %

CT 467 °C 153 35 77 %

CT 465 °C 169 17 90 %

CT 463 °C 224 169 24 %

CT 461 °C 391 261 33 %

CT 459 °C 190 259 36 %

CT 457 °C 411 546 33 %

CT 455 °C 264 42 84 %

Sensor Type HDR FDS 2.0α Error

6.2.3.4 Lower Hatch

Table 6.12 shows the FDS predictions compared with the measured data for sensors located in

the hatch leading from the lower levels of the containment building to the fire room during the

peak of the fire. As with the doorway, the thermocouples in this region could “see” flames in the

fire room doorway. Thus, part of the temperature increase seen at these locations in the data

results from radiation heat transfer to the thermocouples. A second factor is that the air entire the

fire level through this hatch did slowly rise in temperature during the test as the heat from the fire

was advected throughout the facility. FDS is not simulating those effects, although, it would be

possible to modify FDS to contain a time dependent boundary condition for temperature at the

lower boundary. FDS overpredicted the measured velocities by 1 m/s; however, it shows the

same basic velocity profile as seen in the data with CF9202 and CF9205 being about equal and

greater than CF9207.

 

82
Table 6.12: T52.14 FDS Results for the Lower Hatch During Fire Peak

CF9207 m/s 0.12 1.31 958 %

CF9205 m/s 1.18 2.16 84 %

CF9202 m/s 1.09 2.11 93 %

CT9217 °C 90 0 100 %

CT9216 °C 68 0 100 %

CT9215 °C 22 0 100 %

CT9214 °C 50 0 100 %

CT9213 °C 62 0 100 %

Sensor Type HDR FDS 2.0α Error

6.2.3.5 Dome

Table 6.13 shows the FDS predictions compared with the measured data for sensors located in

the uppermost sensor grid during the peak of the fire. This grid was located at the transition to

the dome’s hemispherical head. Once again it is observed that FDS is predicting a somewhat

more narrow of a plume than that seen in the data as well as a plume shifted in location from

what is indicated in the data. This again is probably due to two factors, grid resolution, and

including only a piece of the dome in the model

6.2.4 Intercomparison of All Analysis Methods

This section compares the fire room results of the three analysis methods with the data. These

comparisons are made for steady-state portion of the fire test from 20 minutes to 30 minutes.

Table 6.14 summarizes the results for key parameters of the fire room using the best results of

each analysis method. The velocities shown in the table for the three analysis methods as well as

the data represent the layer averaged velocities.

 

83
Table 6.13: T5214 FDS Results for the Upper Sensor Grid During Fire Peak

CV 423 m/s 0.89 -0.13 113 %

CV 422 m/s -0.35 -0.17 50 %

CV 421 m/s 2.44 -0.20 108 %

CV 418 m/s -0.06 0.21 433 %

CV 417 m/s 1.25 2.87 129 %

CV 416 m/s 4.86 3.29 32 %

CV 413 m/s 0.06 0.67 1097 %

CV 412 m/s 0.38 3.76 889 %

CV 411 m/s 1.27 3.12 145 %

CT 454 °C 23 0 100 %

CT 452 °C 70 1 98 %

CT 450 °C 70 1 98 %

CT 448 °C 30 8 75 %

CT 446 °C 69 11 84 %

CT 444 °C 34 6 76 %

CT 442 °C 49 30 40 %

CT 440 °C 99 42 57 %

CT 438 °C 34 30 13 %

CT 436 °C 71 75 6 %

CT 434 °C 24 8 66 %

CT 432 °C 42 38 8 %

CT 430 °C 67 39 41 %

Sensor Type HDR FDS 2.0α Error

Table 6.14: Steady State Fire Room Predictions for All T52.14 Analyses vs. Data

O2 Concentration (v/o) 0 7 1

Layer Height (m) 2 1 1 1

Lower Velocity (m/s) 2 2 3 1

Upper Velocity (m/s) 4 5 4 4

Upper Temperature (°C) 872 1,227 959 931

Quantity Data Hand Calc. CFAST FDS

The same observations that applied to the T51.23 comparisons apply here. The hand calculation

performs quite well in comparison to the other two methods. Only the temperature is

significantly different. As with the T51.23 results, even though FDS is overpredicting

temperatures, it makes the same average layer prediction that CFAST makes. In fact FDS makes

better predictions for lower layer velocity for the steady-state portion of the fire and nearly

matches the data for the oxygen concentration, a parameter for which CFAST has an

unacceptable error.

 

84
7.0 SUMMARY OF PERFORMANCES AND USABILITY

This chapter summarizes the performances of the various computational methods whose results

were presented in Chapter 7. The summary is given in three main sections. The first section will

discuss the performance as related to the T51.23 test simulations. The second section will

discuss the performance as related to the T52.14 test simulations. The final section discusses the

performance of each methods from the perspective of ease of use, which while being subjective

is nonetheless quite important if one or more of these methods is to see widespread use in a

performance-based code system.

7.1 SUMMARY OF T51.23 RESULTS

Three methods were used to simulate the T51.23 test. These methods included a hand

calculation, a CFAST model, and an FDS model. Each method had successes and failures when

used to simulate the test.

7.1.1 Hand Calculation

The hand calculation performed for the T51.23 fire room was very successful. Fire room upper

layer temperature, layer height, and the doorway upper layer mass flow were are all predicted

within the criteria given in Table 2.1. The doorway lower layer mass flow was not predicted as

well, but due to the sparseness of instrumentation in the doorway, it can not be concluded

whether or not the hand calculation was deficient in calculating this quantity. When considering

that hand calculation methods are designed primarily for speed and less so for accuracy, the

performance in this case is outstanding.

7.1.2 CFAST Calculations

The CFAST calculations saw mixed results. The model made good predictions of near-field

temperature and gas concentration. However, the model results showed a number of

non-physical behaviors in the form of discontinuities in temperatures and gas-concentrations near

the start and the end of the fire. As a steady-state combustion process, well supplied with

oxygen, sudden sharp increases and decreases in these quantities are not occurring. The

observed phenomena seems to be related to shifts in the layer height prediction which drives the

temperature and mass flow solver. It may be worth revisiting CFAST’s solution algortihm to

see if jump conditions exist in the logic that could lead to the observed behavior or to see if

relaxation is required in calculating one or more parameters.

In general, CFAST showed a wide variability in its predictive capabilities for the T51.23 test.

Depending on the quantity of concern,, CFAST may or may not be successful. Also no quantity

was predicted with any consistent success.

85
7.1.3 FDS

FDS v2.0α performed well for this test. Temperatures in all regions of the fire level were well

predicted as were the velocities. The only parameter that was poorly predicted was the oxygen

concentration, however, a premixed fuel is not in the traditional domain of a mixture fraction

approach.

7.2 SUMMARY OF T52.14 RESULTS

Three methods were used to simulate the T52.14 test. These methods included a two-part hand

calculation, a CFAST model, and an FDS model. Each method had successes and failures when

used to simulate the test.

7.2.1 Hand Calculations

The T51.24 test posed a much more difficult case for the hand calculation method. Fire room

temperatures were greatly overpredicted by this method, although mass flows and the neutral

plane height were reasonably predicted. A number of factors could be affecting this. The

presence of a large vertical shaft just outside the fire room may be creating flow conditions that

the hand calculation is not capable of resolving. Another, and likely quite important factor, is

that the heat release rate is likely overspecified. While the pyrolysis rate is known reasonably

well in the later stages of the T52.14 test, how much of that burned inside versus outside the fire

room is not well known. This could be impacting the hand calculation results.

In the second part of the hand calculation, mixed results are observed. At the operating deck,

where the plume is highly constrained, neither the Chen-Rodi nor the integral method give good

predictions of velocity and temperature. At the upper grid, where the plume is closer to a free

plume, both methods are again greatly underpredicting the temperatures. However, at this

location the integral method is correctly predicting the drop in temperature and both methods are

correctly predicting the velocity. As with the fire room, the plume analysis has difficulties in

application to the flow conditions present in the HDR. However, the method is capable of yield

basic insight of the fire's effect on the containment.

7.2.2 CFAST Calculations

Given the relatively poor results from the T51.23 simulations both in this work and in other work

by the author45,53, it was anticipated that with an underventilated fire and the presence of the large

dome near the fire room that CFAST would perform even worse for the T52.14 test. This was

not the case, however. In general, gas concentrations, near-field and dome velocities, and dome

temperatures were well predicted by CFAST models. Far-field temperatures and velocities were

not well predicted, however, CFAST predictions in these regions were conservative.

The T52.14 CFAST predictions did show some disturbing attributes. In the far-field,

temperature predictions showed unphysical behavior. For example, upper layer temperatures

showed no increase for 8 minutes while the lower layer saw a 10 °C. At 8 minutes the upper

86
layer jumped instantly to the same temperature as the lower layer followed by a decrease in the

lower layer temperature. Sudden discontinuities and oscillations are all indicative of either

numerical instabilities in a code's algorithm or logic flaws in the algorithm's implementation.

7.2.3 FDS Calculations

Similar statements can be made for the v2.0α T52.14 model as were made for the T51.23 model.

Temperatures and velocity predictions inside the fire room and doorway were excellent as were

the gas concentration predictions with FDS v2.0α correctly predicting both the oxygen and the

carbon dioxide levels. However, these success are tempered by the fact that there were poor

predictions of velocities and temperatures in the hatches and the dome. This would seem to

indicate that the ability to handle complex boundary conditions and choosing proper computation

domains will be crucial to future use of FDS.

7.3 METHOD USABILITY

This section discusses the author's impressions on the ease of use of the three methods. These

discussions include creating an input for the calculation, understanding how the calculation takes

place, and being able to use the results of the calculation.

7.3.1 Hand Calculations

Hand calculations are by far the most transparent of the three methods used in this work. By

their simplistic nature, hand calculations typically only involve a few equations grounded in basic

principles. As these are the methods that tend to be used for problem solving in educational

course work, explanatory material is easy to locate. The calculations themselves are

straightforward requiring at most a spreadsheet and pencil and paper. Results from these

methods are also easy to use as only a few quantities are solved for. While it may take a couple

of hours to construct a template in a spreadsheet or other math toolkit for performing a hand

calculation, the calculation itself takes almost no time.

7.3.2 CFAST Calculations

CFAST has been in existence for a number of years now. As such, one would expect that after

many years of development and use of the code by a broad group of international users that its

usability would be very high. This is not entirely the case, however.

CFAST has both a user's manual describing how to run the code and a theory manual describing

the internal workings and theory behind the code. Both of these documents are well written,

explaining the various code inputs and what the code does with them. What is missing, however,

is guidance on creating an input model for a complex structure. For a simple structure with a few

compartments and simple interconnections, the input descriptions in the manual suffice.

However, for a large structure with many compartments, multiple levels, and complex

interconnections no guidance is given on what should and should not be included in an input

model and how to simplify groups of compartments into a single compartments or how to

87
simplify multiple interconnections into single interconnections. This is a potential impediment to

using CFAST for fires in large structures.

CFAST also possess a preprocessor. This program is a DOS-based program that uses character

graphics to gain the look of a Windows ® application. As a DOS based program with graphics it

must be run in full-screen mode. In this mode a user is unable to cut and paste parameters from a

spreadsheet or other document into the preprocessor. This makes generating an input file prone

to transcription errors when typing in values that could be cut and pasted. Ideally this

preprocessor should be migrated towards a pure Windows ® environment. The preprocessor

also writes input files that are overly difficult to read. For example, room dimensions are written

to the input file with a precision of 10-5 m. This is somewhat absurd since compartment

dimensions in either a model facility or a prototype facility are not known to this level of

precision. Other parameters are also written in a similar manner. This excessive number of

digits degrades the readability of an input file.

The CFAST code output is written into a single, proprietary format, binary output file. As such

one can not directly read the output file into common graphics applications. CFAST is

distributed with a DOS based post-processor that allows a user to extract subsets of the data file

to a spreadsheet compatible, ASCII format. However, for a large model these subsets

(temperatures, mass flows, gas concentrations, etc.) can become unwieldy. Improvements to this

could be had by either providing more control in the post-processor in deciding what data to

extract from the output file, or by perhaps generating separate files for the various quantities in a

standard binary format. It should be noted that conservation of hard disk space is not the issue it

was a decade ago when CFAST was first released.

In addition to the above mentioned deficiencies, the author has observed some problems with

executing CFAST. In the cast of T51.23, CFAST would not initialize the pressure solver without

a small leakage connection to the outside. While this would not impact a user making a

calculation for a residential dwelling, this does impact users modeling facilities such as

containment buildings which have very little leakage. It has also been observed that in some

model configurations CFAST will have time steps on the order of nanoseconds, which of course

makes for a prohibitively long computation. However, by making very small changes to

compartment dimensions and/or compartment connections, the code will progress with

millisecond time steps resulting in a feasible computation time. This fact combined with the

behavior observed in the model results, indicates possible stability problems with CFAST.

7.3.3 FDS Calculations

FDS has only recently been released as version 1.0. For the time period during which this work

was done, FDS was very much a developmental code. As such, one anticipates a certain degree

of user unfriendliness since code user/code developer interactions tend to act quickly to improve

usability in first release.

As with CFAST, FDS is distributed with both a theory manual and a user's manual. The theory

manual is very well written, containing detailed descriptions of the equations used in FDS, how

88
they are discretized, and how the code algorithm proceeds. The user's manual is also well

written. It contains a number of sample input files for a wide variety of fire types and structures.

It also contains a detailed description of each input file and the various input options. However,

as with the CFAST manuals, it could use more guidance on constructing input models such as

recommended node sizes, initial timestep, modeling non-orthogonal surfaces, etc.

FDS currently lacks an input preprocessor. For a very simple fire, this is not a major drawback;

however, for simulations such as the ones performed in this work it becomes somewhat tedious

to generate the geometric descriptions. A GUI preprocessor would greatly improve FDS's ability

to be used widely.

Where FDS really shines is in its post-processing capabilities. A separate, multi-platform,

program called Smokeview has been written that allows the user to visualize all the various

outputs created by FDS. With this program contour plots, (x,y) plots, and transient animations

can be rendered. This program uses a graphical interface and allows the user to rotate and

walkthrough the input geometry while visualizing the data. Furthermore, FDS writes its output

into a number of separate data files written in either an ASCII format or a standard binary format.

This allows easy use of other graphics packages for analyzing code output. Furthermore, the

output file formats are fully specified in the user's manual which allows users to write their own

post-processing routines.

89
8.0 CONCLUSIONS

A performance-based code system must have access to appropriate computational tools in order

for credible statements of performance to be made. These computational tools may take different

forms: hand calculations, lumped parameter methods, computational fluid dynamics, etc.;

however, they must all share certain characteristics. They must possess a certain degree of user

friendliness if they are to see widespread use in a regulatory regime not traditionally associated

with computer modeling, and they must predict the consequences of a fire with a reasonable

degree of accuracy. Since criteria for neither characteristic has been established, this work

examined two potential tools and evaluated their performance in relation to a proposed set of

performance criteria, Table 2.1. The usability of the tools was also discussed. Basic conclusions

of each method will be discussed.

8.1 Hand Calculations

The first tool examined was the application of simple hand calculations to the two fire tests.

Hand calculations, as they omit or greatly simplify the various phenomena related to a fire,

cannot be expected to yield precise information on a fire's consequences. However, one can

expect that a hand calculation yields sufficient information regarding a fire to determine whether

or not a more detailed analysis is warranted.

The results obtained in this work showed that hand calculations are capable of yielding useable

information regarding the basic parameters of a compartment fire. However, as the results for

T52.14 demonstrated, care must be taken when applying hand calculations. Due to their

simplicity, they should not be applied indiscriminately to any given fire, but rather the underlying

assumptions of the method should be compared with the fire to be modeled to ensure

applicability. This was observed in the inability of the two plume models to yield accurate

results at the level of the operating deck, see Section 7.2.1.

8.2 CFAST

Since CFAST is already a familiar tool to many in the fire protection arena, it is important that its

limitations in terms of modeling large structures be understood. This work has clearly shown

that CFAST is in need of significant improvements if it is to be used in a performanced-based

code regime for analyzing entire structures. Far-field mass flows, temperature changes, and

propagation of gas species are not well predicted by CFAST. Even near-field predictions of

temperatures and mass flows can be in substantial error. Furthermore, observed behaviors such

as higher lower layer temperatures in regions with only horizontal flow could could cause

acceptance problems as such results act to degrade confidence in the overall performance.

It is obvious that predicting the near-field accurately is important as this is the region where the

fire is most likely to cause physical damage to equipment and structures. In the far-field, one

may be inclined to discount large errors as the net changes in temperatures and gas

concentrations tend to be smaller and risk of thermal damage becomes small. However, these

parameters must still be predicted accurately. Survival of personnel in the far-field is largely

90
dependent on exposure to small concentrations of toxic gasses. Also, ventilation systems and

equipment cooling fans can become clogged with soot and fail to function leading to other modes

of failure.

Prior work performed by this author with CFAST noted many of these same problems. In

addition it was observed that CFAST had numerous problems associated with fuels containing

oxygen52 and with ventilation system induced flows44.

What is clear, however, is that some model such as CFAST will be required in a

performance-based code system. Hand calculations are not going to have the precision to

analyze an entire structure, and CFD methods are currently computationally too expensive to

model multiple fire scenarios in large structures for long periods of time or to model very large,

complex, structures in their entirety. Because of this, it can be concluded that CFAST should

undergo further development and validation directed toward the goal of using it in a

performance-based code system.

Specifically the following recommendations for CFAST development are given:

1. Migrate the code away from a DOS environment to a pure Windows environment.

This will accrue a number of usability benefits. As a Windows program,

operations such as cut and paste will be available. Furthermore the look and feel

of the program will be identical to other Windows software resulting in an

immediate sense of familiarity. Lastly, as a Windows program, the code can make

use of the Windows built-in, helpfile applets to aid the user when creating an

input file. Lastly, Microsoft has stated that it wishes to remove support for DOS

applications from future versions of Windows. While this may not happen in the

very near future, it should be prepared for.

2. Examine the code's numerics for gas concentration calculations. It is possible that

the calculations need to be relaxed when the solution calls for rapid concentration

changes.

3. Develop an improved combustion model. First, in its current implementation it is

entirely up to the user to specify the combustion products. That is the quality of

output is highly dependent on quantities that the user cannot know ahead of time

for a blind computation. Second, prior work has shown that CFAST is not

capable of correctly tracking combustion products if an oxygen containing fuel is

specified.

4. Create another document to be distributed with CFAST that discusses how to

approach modeling of large structures or odd-sized rooms such as atrium, shafts,

or very long hallways.

5. Further improvements are needed in the determination of mass flows between

compartments, especially far-field vertical flows.

91
6. Further benchmarking of the code for fires in complex structures, especially one's

with operating ventilation systems is needed.

8.3 FDS

FDS, as well as other CFD methods in general, is a relative newcomer to fire protection. CFD

models such as FDS are not easy to use. Furthermore, their computational requirements greatly

limit their applicability. One is not going to use a CFD model to analyze hundreds of possible

scenarios in a large structure. CFD models, rather, are going to be used to analyze very specific

scenarios which require the precision that only CFD can provide. For example, whereas a zone

model can predict the average heat flux seen at some distance from a fire, it cannot predict the

spatial distribution of the heat flux at that distance. A zone model cannot determine that one

object is perhaps shielded by another object from the effects of a fire. A CFD model can be

capable of yielding such information. Although they are computationally expensive and time

consuming, CFD methods are the only available method when one needs highly localized

information of on fires’ effects.

The work herein examined one CFD model, FDS. It has been observed that FDS v1.0 was not

capable of modeling fires which are large with respect to their compartments, or fires which are

greatly underventilated. The results presented in Chapter 6 indicate, however, that the current

sub-models being implemented for release as FDS v2.0 should greatly improve FDS’s predictive

capabilities. In addition to improvements already in the works for v2.0 the following

developments are recommended for FDS to improve its usability and accuracy:

1. Create a GUI front end for generating input files in a manner that ensures

cross-platform consistency, such as using OpenGL (like with Smokeview).

2. Provide further guidance in the user's manual on node sizes and how to specify

compartments with complex internal blockages or non-orthoganal surfaces.

92
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