S771tM

NBSIR 79-1713

Final Report on the "BFIRES/Version 1”

Computer Simulation of Emergency

Egress Behavior During Fires: Calibration

and Analysis

Fred I. Stahl

Environmental Design Research Division

Center for Building Technology

National Engineering Laboratory

U.S. Department of Commerce

National Bureau of Standards

Washington, DC 20234

October 1 5, 1 978

Issued March 1979

-QC

100

,U56

79-1713

Prepared for the Center for Fire Research, in support of the

HEW-NBS Fire/Life Safety Program, Sponsored by:

U.S. Public Health Service

Department of Health, Education and Welfare

Washington, DC 20203

?!sfional Bureaa of Sfaniard*^ may 1 4 ’0’^

NBSIR 79-1713

,o FINAL REPORT ON THE “BFIRES/VERSION 1”

COMPUTER SIMULATION OF EMERGENCY

EGRESS BEHAVIOR DURING FIRES: CALIBRATION

AND ANALYSIS

Fred I. Stahl

Environmental Design Research Division

Center for Building Technology

National Engineering Laboratory

U.S. Department of Commerce

National Bureau of Standards

Washington, DC 20234

October 1 5, 1 978

Issued March 1979

Prepared for the Center for Fire Research, in support of the

HEW-NBS Fire/Life Safety Program, Sponsored by:

U.S. Public Health Service

Department of Health, Education and Welfare

Washington, DC 20203

U.S. DEPARTMENT OF COMMERCE, Juanita M. Kreps, Secretary

Jordan J. Baruch, Assistant Secretary for Science and Technology

NATIONAL BUREAU OF STANDARDS, Ernest Ambler, Director

TABLE OF CONTENTS

PAGE

LIST OF FIGURES iv

LIST OF TABLES vl

PREFACE vii

ABSTRACT viii

1.0 INTRODUCTION 1 1.1 Long Range Goals 1 1.2 Objectives of the Project 1 1.3 Purpose and Scope of this Report 1 1.4 Overview of the Technical Approach 2 1.5 Summary of Key Findings 9

1.6 Directions for Future Research 10

2.0 CALIBRATION OF BFIRES/VERSION 1, AND LIMITATIONS

TO THE PROGRAM'S APPLICABILITY 11

2.1 Introduction 11

2.2 Internal Constants 12

2.3 Internal Dynamic Processes 13

2.4 User Supplied Variable Values 13

2.5 Summary 20

3.0 PROGRAM SENSITIVITY ANALYSIS 22

3.1 Introduction 22

3.2 Analysis "A" 24

3.3 Analysis "B” 42

3.4 Sensitivity to Environmental Versus

Occupant Parameters 70

3.5 Summary of Sensitivity Results 70

4.0 CONCLUSIONS 72

4.1 Key Findings 72

4.2 Applicability of Available Data to the

Model-Bulldlng Process 72

4.3 General Summary 74

REFERENCES 75

APPENDIX A 76

111
LIST OF FIGURES

PAGE

Figure 1.1 Orthogonal Grid Laid Over Floor Plan 3

Figure 1.2 Time Dependent Relocation Probability Matrices 4

Figure 1.3 Individual Occupant Loop 6

Figure 1.4 Time Loop 7 Figure 1.5 Replication Loop; BFIRES Executive 8

Figure 2.1 Calibration of Penalty Thresholds in Subroutine

EVAL20 14

Figure 2.2 Translating Orthogonal, Curvelinear, and Angular Wall

Elements into BFIRES-readable Form 17

Figure 2.3 Time Frames to Seconds Conversion Chart 21

Figure 3.1 Un-subdivided Spatial Zone (One-Space Plan) 25

Figure 3.2 One-Space Plan in BFIRES Grid Form 26

Figure 3.3 Spatial Zone Subdivided Into Three Units

(Three-Space Plan) 27

Figure 3.4 Three-Space Plan in BFIRES Grid Form 28

Figure 3.5 Spatial Zone Subdivided Into Five Units

(Five-Space Plan) 29

Figure 3.6 Five-Space Plan in BFIRES Grid Form 30

Figure 3.7 Spatial Zone Subdivided into Seven Units

( Seven-Space Plan) 31

Figure 3.8 Seven-Space Plan in BFIRES Grid Form 32

Figure 3.9 4x3 Factorial Design for Analysis "A" 34

Figure 3.10 Graphic Summary of Hypothesis (1) - (5) 37

Figure 3.11 Effects of Spatial Subdivision and Occupant

Density on Escape Score 43

Figure 3.12 Effects of Spatial Subdivision and Occupant

Density on Route Length 44

Figure 3.13 Non Dead-End Floor Plan 46

Figure 3.14 Non Dead-End Floor Plan in BFIRES Grid Form 47

Figure 3.15 Dead-End Spatial Configuration 48

Figure 3.16 Dead-End Floor Plan in BFIRES Grid Form 49

Figure 3.17 Four-Dimensional Factorial Design for Analysis "B" ... 51

Figure 3.18 Effects of Knowledge of Best Exit Location, Floor

Plan Configuration, and Occupant Density on the

Mean Number of Occupants Escaping the Floor 60

Figure 3.19 Effects of Occupant Mobility, Floor Plan Configuration, and Occupant Density on the Mean Number of

Occupants Escaping the Floor 61

Figure 3.20 Effects of Knowledge of Safe Exit, Floor Plan

Configuration, and Occupant Density on Mean Spatial

Displacement 62

Iv
LIST OF FIGURES (Continued)

PAGE

Figure 3.21 Effects of Occupant Mobility, Floor Plan Configuration, and Occupant Density on Mean Spatial

Displacement 63

Figure 3.22 Effects of Knowledge of Safe Exit, Floor Plan

Configuration, and Occupant Density on Mean Escape

Score 64

Figure 3.23 Effects of Occupant Mobility, Floor Plan

Configuration, and Occupant Density on Mean

Escape Score 65

Figure 3.24 Effects of Knowledge of Safe Exit, Floor Plan

Configuration, and Occupant Density on Mean

Difference Values 66

Figure 3.25 Effects of Occupant Mobility, Floor Plan

Configuration, and Occupant Density of Mean

Difference Values 67

Figure A.l Subroutine Network and Flow of Control 77

Figure A, 2 Possible vs. Impossible Spatial Movements 101

V
LIST OF TABLES

PAGE

Table 2.1 Time Frame/Real Time Conversions, for Three Values

of Walking Speed 19

Table 3.1 Mean Outcomes From Simulations Based on a Density

Threshold of 1 39

Table 3.2 Mean Outcomes From Simulations Based on a Density

Threshold of 3 40

Table 3.3 Mean Outcomes From Simulations Based on a Density

Threshold of 5 41

Table 3.4 Analysis of Variance for Escape Score 45

Table 3.5 Analysis of Variance for Total Number of

Steps Taken 45

Table 3.6 Mean Data from Simulated Five Events 55

Table 3.7 Analysis of Variance for the Total Number of

Occupants who Escape 56

Table 3.8 Analysis of Variance for the Total Number of

Spatial Displacements 57

Table 3.9 Analysis of Variance for Escape Score 58

Table 3.10 Analysis of Variance for Occupants’ Final Positions

Relative to their Initial Positions 59

Table A.l Summary of BFIRES/Version 1 Subroutines...... 78
PREFACE

The Environmental Design Research Division, Center for Building Technology, National Bureau of Standards, is developing a more comprehensive

understanding of pedestrian movement within buildings. The responses of

building occupants during fire emergencies is an important part of this

overall effort.

This report is the final product of a specific effort to develop and

analyze a computer simulation of human egress behavior during fires.

This project was one component of a research program undertaken jointly

by the Department of Health, Education and Welfare, and the Center for

Fire Research of the National Bureau of Standards. In addition to the

behavior of institutionalized populations during fire situations, this

program considered the problems of design analysis, fire and smoke detection, smoke movement and control, and automatic extinguishment.

The author gratefully acknowledges Drs. Edward Arens, Francis Ventre,

Robert Glass, and Messrs. George Turner and James Harris, of the Center

for Building Technology, and Dr. Bernard Levin and Mssrs. Harold Nelson

and Jeffery Shibe, of the Center for Fire Research, for their critical

reviews of this report. The author is especially grateful to Dr. Stephen

Margulis of the Center for Building Technology, for his assistance in

interpreting data obtained during this study. A special debt of gratitude

is owed the Center for Building Technology Word Processing Center, whose

staff prepared the final manuscript.

vii
ABSTRACT

This report documents computer simulation experiments designed to calibrate and analyze BFIRES/VERSION 1, a computer program which simulates

building occupants' egress behavior during fires. This report demonstrates that emergency egress behavior under certain specified conditions

can be systematically conceptualized, and simulated through the use of a digital computer. Important findings concerning the calibration and

sensitivity of BFIRES are also discussed. In particular, it is shown

that: (a) a variety of general egress situations may be simulated

through the application of BFIRES; (b) every such event is unique, and

is defined by the set of user-supplied input parameter values which

describe the building, the threat, and the occupants; (c) BFIRES may be

used in simulated environments of known (or desired) spatial dimension,

and events of known (or desired) temporal duration; and (d) BFIRES

simulation outcomes are sensitive to variations in a number of parameters

of immediate interest to the building design and regulatory communities.

viii
FINAL REPORT ON THE "BFIRES/VERSION 1" COMPUTER SIMULATION OF

EMERGENCY EGRESS BEHAVIOR DURING FIRES; CALIBRATION AND ANALYSIS

1.0 INTRODUCTION

1.1 LONG RANGE GOALS

The research reported here was guided by two main goals. The first was

to provide a framework for identifying parameters for and testing relationships deemed important in defining building fire events, and thereby

to increase our overall understanding of occupants ' emergency egress

behavior. The second goal was to develop a basis from which predictive

design and regulatory tools may eventually be refined,

1.2 OBJECTIVES OF THE PROJECT

This project consisted of four tasks. These were to; (1) develop a theoretical model of occupants' egress behavior during fire events;

(2) simulate such behavior by means of a computer program derived from

the theoretical model; (3) calibrate the computer program to enable the

simulation of "real-world" conditions; and (4) examine the internal

validity of the program, particularly the sensitivity of simulation outcomes to variations in input parameters.

The first two of these tasks were conducted during the project's initial

phase, and have been documented elsewhere (Stahl, 1978). The final

phase of the project dealt primarily with the later two tasks, although

it also included an effort to refine certain aspects of the computer

program written during task (2),

1,3

PURPOSE AND SCOPE OF THIS REPORT

The primary objective of this report is to document computer simulation

experiments which lead to the calibration and analysis of BFIRES/VERSION

1 (or simply, BFIRES), the computer program specially written to simulate

occupants' egress behavior during fires*. In addition, this report

includes complete documentation of the BFIRES program. Finally, since

it may not always be convenient for readers to first peruse the project's

Interim Report (Stahl, 1978), a brief overview of the approach is presented below in Section 1.4,

Determining whether BFIRES can replicate actual historial fire events,

or whether it can predict the outcomes of future ones, was outside the

scope of this project. Consequently, this report includes no case studies in which comparisons are drawn between simulated versus realworld events.

* Research continually results in modifications to BFIRES. The computer

program presented in this report was current at the time of printing.

Prospective users may wish to contact the author regarding the program's currency at some future date, A "user manual" is expected to

be available for BFIRES/VERSION 2, in progress.

1
Similarly, simulating flame and smoke migration, and actually applying

computer simulations to design and regulatory practice, posed special

problems which were outside the scope of the project. As a result,

detailed consideration of these issues was excluded from the report.

1.4 OVERVIEW OF THE TECHNICAL APPROACH

1.4.1 Model of Egress Behavior

In its most basic form, BFIRES is derived from an "information processing" model of human behavior. Accordingly, a building occupant moves

about through an architectural environment as a result of movement

decisions he makes during some period of time. A particular path of

travel results from a "chain" of movement decisions. Each incremental

decision is derived through a process in which the individual Interprets

information he has gathered from the environment in light of his unique

movement objectives.

The environmental information field consists of elements external to the

individual. For present purposes, we may limit the discussion to such

items as other occupants, building elements (e.g., walls, doors), and

fire-based stimuli. These elements are not static. Rather, contents of

the Information field change over time. For example: the spatial location of other occupants is constantly changing; the location or severity

of life-threatening stimuli may change; and physical features of the

architectural environment may change as a result of human interference

(opening and closing of doors) or pyrological destruction.

As an illustration of these processes, consider a planar surface

which has been overlaid with an orthogonal ("x, y") grid. Further consider that spatial boundaries (i.e., a floor plan) have been laid out on this grid, and that persons in this field are permitted only to occupy

grid points (i.e., the intersection of two orthogonal grid lines). Refer

to Figure 1.1. As time advances incrementally, persons move from one grid point to another. Their decisions to move to specific points are based on interpretations of information they have obtained concerning

the degree to which a given move alternative will help achieve some predetermined spatial objective.

The model described here does not assume that movement decisions are entirely determined by some information processing procedure. Rather,

the process leading to a "decision" is construed as one in which various

move alternatives are weighed, and from which the probability that each

alternative will be selected is derived. Accordingly, information

processing biases movement behavior; it does not determine it. Since

the information field changes over time, the magnitude and direction of

the biasing phenomenon changes over time as well.

Figure 1.2 Illustrates the movement probability concept by means of a matrix of spatial locations. The cells contain values of denoting

the probability that an occupant at location i will, during the current

2
X

A: Walls defining floor plan

B: Person-occupiable spatial locations

Figure 1.1 Orthogonal Grid Laid Over Floor Plan

3
Person-occupiable

Spatial

Locations

Time Frame = k

Time Frame = 3

Time Frame = 2

Time Frame = 1

I 1 .20 .20 oo • • • « —; .00 .00

2 .25 .15 .20 • • • • .00 .00

3 .10 .05 .50

• • • • .00 .00

•

•

22 .00 .00 .00 • • • • .20 .35

23 .00 • o o .00 • • ft • .18 .64

1 2 3

Q • 22 23

Person-occupiable

Spatial Locations

Probability values in cells are generated by BFIRES, and are updated

each time frame to reflect changing conditions.

Figure 1.2 Time Dependent Relocation Probability Matrices

4
time increment, relocate to point j. For any given time increment, each

occupant generates his own P

j^j

matrix, M . Since factors which influence

values of P.^ vary over time , the occupant regenerates such a matrix at

the onset or each succeeding time increment. This process may be con- sidered a nonstationary Markov model (Stahl, 1978).

1.4.2 Dynamic Simulation of the Model by Comptuer: BFIRES

The BFIRES computer program was developed specifically for the purpose

of simulating the model described above. BFIRES was written in FORTAN-V

for the UNIVAC 1108 computer located at the National Bureau of Standards*.

The central feature of BFIRES is the "individual occupant loop". This

loop enables occupants of a floor plan to individually exercise their

decisionmaking procedures, during a single time Increment. The occupant loop consists of three main components: (1) an information gather- ing component which scans the information field; (2) an information

interpretation/processing component which compares available information

with predetermined objectives, biases spatial behavior, and establishes

values of and (3) an action component which probabilistically

selects the actual move to be undertaken, and relocates the occupant.

Figure 1.3 illustrates the individual occupant loop.

Figure 1.4 locates the occupant loop within the next higher level of

BFIRES: the "time loop". The time loop enables the iteration of

individual occupant decision procedures over the span of a fire event, on the assumption that the event may be subdivided into a finite number

of discrete units of equal duration.

All occupants in the simulation are "processed" during each successive

iteration of the time loop. Each time loop iteration is referred to

as a "time frame". In Chapter 2.0 of this report, the conversion of

time frames to real time units (i.e., seconds) is discussed.

Finally, the time loop is nested with the "replication loop". This

loop enables the experimenter to run any number of replications of a simulated fire event, under a single set of input parameter values.

As the highest level of the program, the replication loop is also the

BFIRES executive routine. Refer to Figure 1.5.

1.4.3 Facility-Specific Characteristics of BFIRES

In general, BFIRES can be run on any digital computer of adequate capacity. In its current form, the program requires approximately 29,000

36-bit words of memory. On a 32-bit word machine, approximately 32,300

words are required.

* Because BFIRES/VERSION 1 has not been fully validated, its description here does not imply endorsement as a design tool by either NBS

or the Department of Health, Education and Welfare (the sponsor).

5
Figure 1.3 Individual Occupant Loop

6
Figure 1,4 Time Loop
YES

Figure 1.5 Replication Loop; BFIRES Executive

8
Stochastic functions are executed by comparing BFIRES-generated probability values (such as discussed above) against random numbers.

Uniform distributions of random numbers are produced by special subroutines (random number generators). Most "canned" generators are of the

so-called power-residue type, and are specifically written on the basis

of computer word size. Accordingly, a random number generator written

for a 32-bit processor will not function on a 36-bit machine.

To cope with this problem and thereby make BFIRES more universally

applicable, two versions were prepared. BFIRES/32 uses a random number

generator operable on 32-bit computers (e.g.. Interdata 7/32 or 8/32

minicomputers; IBM 360/370 systems). This subroutine is contained withip

the BFIRES source code. Users of 36-bit machines, such as the UNIVAC

1108, will run the BFIRES/36 version. This version contains no random

number subroutine, but rather calls an external subroutine from the

facility library. At the National Bureau of Standards, for example,

this subroutine is known as RANDNU. Within BFIRES/36, the statement

X=RANDNU(0) causes a random number to be generated by the external subroutine, and then assigns the value of this number (between 0 and 1.00)

to the variable labeled X. A user of BFIRES/36 may have to modify the

program’s source code to reflect the requirements of a specific computer

facility.

1.5 SUMMARY OF KEY FINDINGS

Results from this research effort demonstrate that emergency egress

behavior under certain specified conditions can be systematically

conceptualized, and simulated through the use of a digital computer.

Although the intent of this project was not to test the simulation’s

ability to predict real-world fire outcomes, results have suggested its

applicability to problems of immediate interest to building designers

and regulators (e.g. , what is the life safety impact of variations in

floor plan configuration or exit arrangement?). Thus, the way has been

paved for future validation research, and for applications exercises.

In addition to demonstrating both the "simulability" of occupants’

egress behavior and the value of such a facility, important technical

findings concerning the simulation program’s calibration and sensitivity

were also realized. In particular, this report shows that:

(1) A variety of general egress situations may be simulated through

the use of BFIRES.

(2) Every such event is unique, and is defined by the set of usersupplied input parameter values which describe the building, the threat,

and the occupants.

(3) Although BFIRES was not designed to operate in real time, and

while it deals with imaginary spatial units, it is easily calibrated to

standard measures of time and space (i.e, seconds and feet or meters.)

9
Thus, BFIRES may be readily used to simulate environments of known (or

desired) spatial dimension, and events of known (or desired) duration.

(4) BFIRES simulation outcomes are sensitive to variations in

parameters of immediate interest to designers and regulators. These

Include: (a) floor plan configuration, (b) occupants' spatial locations

at the onset of the emergency event, (c) the existence of any impairments to occupants' mobility, (d) occupants' familiarity with the building layout, and (e) permissible levels of occupant density.

1.6 DIRECTIONS FOR FUTURE RESEARCH

1.6.1 Program Enhancements

In the current version of BFIRES, direct effects of flame and smoke

migration are assumed to be felt only outside the area under study. For

example, when the user wishes to examine occupants' egress responses

from a particular floor of a multistory building, he must assume that

the actual fire is occurring on some other floor, and that the occupants

he is studying have some degree of information about the existence and

location of that event. An obvious enhancement of immediate interest,

then, is the Inclusion of subroutines enabling BFIRES to simulate occupants' behavioral patterns in spaces actually infiltrated by fire products.

Another problem is that BFIRES presently makes no provision for rescue activities, important during many emergencies. An additional enhancement of BFIRES will be necessary, enabling the program to simulate

such behavior. Enhancements such as these are presently under development at the National Bureau of Standards.

Other less critical enhancements may be desired, as well. For example,

the interfacing of BFIRES with a validated simulation of fire and smoke

migration should ultimately yield more authentic egress simulations.

Also, the interacting of BFIBffiS with a real-time graphics facility

should enable users to apply the simulation more creatively, and to

apply its results to design problems more directly and efficiently.

1.6.2 Program Streamlining

As BFIRES undergoes more Intensive use, it will be applied to an increasingly wider array of conditions and contexts. As this process continues,

more will be learned about the senstivity of simulation outcomes to

variations in parameter values. Eventually, variation in some parameters may be found to have no significant impact on simulation results.

At some point, therefore, it will be possible (and desirable) to streamline BFIRES by deleting such parameters.

10
1.6.3 External Validation

This problem may be viewed on two levels: face validity , and predictive

validity . In the case of face validity, we are content with the conclusion that behaviors generated by the computer program "feel right"; they

seem, according to conventional wisdom or common sense, to concur with

our general knowledge of the actual phenomenon. Ascertaining predictive

validity, however, requires a more rigorous exercise, since we want to

know the degree to which simulated outcomes are indicative of what might

happen in a real fire under a very specific set of conditions.

To a great extent, the reader can review the experiments in Chapter 3.0

of this report, and make judgements about the face validity of BFIRES

output. To some degree, of course, these judgments will vary according

to the reader's own experience and professional background. In the

future, investigators may wish to examine the program's predictive

validity. This will be extremely difficult to assess directly, however,

since the actual conditions leading up to an surrounding real fire

events are not often easy to forecast. Accordingly, it will be necessary to conduct an indirect analysis, in which the convergence of

results from several techniques is sought. Among the possible techniques

are Turing's Test (Turing, 1950), in which experienced experts attempt

to distinguish simulated scenarios from real ones, and replicative tests,

in which the investigator attempts to replicate actual historical fire

outcomes with the simulation program.

2.0 CALIBRATION OF BFIRES/VERSION 1, AND LIMITATIONS TO THE PROGRAM'S

APPLICABILITY

2.1 INTRODUCTION

The BFIRES simulation program produces tabular output in various forms.

By analyzing this output, the user can draw Inferences about building

fire events. The actual output itself, of course, possesses none of the

physical characteristics of a fire event; it is merely a symbolic representation. The degree to which the computer output represents a realworld event is an important and complex problem, and generally refers to

the external validity of the simulation (a problem outside the current

scope). Here, however, we are concerned with factors which influence

this degree of representation. In particular, there are two factors

which largely determine the similarity between simulated events and

their real-world referents: (1) the correctness of the simulation model,

and (2) the deployment and application of the model to a given case.

Recall that BFIRES constructs a complex network of interrelated variables, or parameters. Some of these are computed, varied, or fixed

internally, and are thus outside the user's immediate control. As such,

these parameters relate directly to the "correctness" of the simulation

model; incorrect parameter values detract from the model's correctness.

The values of others, however, are chosen and input by the user, in his

11
attempt to match simulated conditions to those expected during hypothetical real-world events (or to those actually known to have occured, as in the case of historical simulations). This process of aligning

program parameters with those describing the actual event is what we will refer to here as calibration .

Calibration and external validity are closely related. When the user compares simulated with real-event data and finds some degree of variance between the two sets, he will attempt to adjust input parameters

until a minimum variance is achieved. If the variance is still

unacceptably high, or if low variance could only be achieved at the

expense of using obviously unrealistic parameter values, then the user

may justifiably conclude that the model underlying BFIRES is inappropriate to the case under study .

In this report, we are not concerned with techniques for fine-tuning a simulation in the presence of comparison data from a real fire event

(part of the event validation process, beyond the present scope).

Rather, our objective is to Introduce the user to parameters handled

within BFIRES, so that he will understand the program's range of application, and so that he will be able to conduct a tuning exercise once

the program is in fact applied to an actual case. There are three

classes of parameters with which the user must become familiar:

(1) internal constants; (2) internal dynamic processes; and (3) usersupplied variable values.

2.2 INTERNAL CONSTANTS

2.2.1 Consensus Exit of Choice

Subroutines GROUP, OTHERS, and AGREE establish for a given occupant the

social environment through which he gathers certain Information necessary for making egress movement decisions. An important example

involves the situation in which several occupants inhabiting a space

have different opinions about the best exit from that space. The model

underlying this small package of routines suggests that: (1) whenever

all such occupants hold the same opinion, the choice of exit is clearcut; but (2) where a difference of opinion exists, a consensus will

have the effect of winning all occupants over to the majority view.

But just how should "consensus" be defined: 51% of all occupants in

the space? 67%? The literature on human behavior in fires (or fire

drills) provides no guidance. For practicality, however, the cut-off

line was drawn at 60%: if 60% (or more) of the occupants inhabiting

a space favor a particular exit from the space, they will "convince"

the remaining occupants of the quality of their opinion, and all the

occupants will seek that exit. When occupants have differing opinions

and ^

consensus exists, BFIRES simulates a state of confusion in which

occupants "lose faith" in their originally-held beliefs. Confusion

reigns until a consensus is eventually achieved.

12
2.2.2 Penalty Thresholds

Subroutine EVAL20 simulates an occupant's evaluation of his current

"safety status" by comparing his egress progress to date against the

total elapsed time he has spent in the danger zone. When evaluating

his status with respect to the egress goal (final exit), he seeks to

ascertain that the distance separating himself from the goal is not so great as to preclude his reaching it before the "critical time" is

reached (point at which life support becomes untenable). Similarly,

when evaluating his status with respect to the location of the fire, he

seeks to ascertain that the distance between himself and the fire is

sufficiently large to permit escape prior to the critical time.

BFIRES establishes thresholds (with respect to both threat evasion and

goal seeking), or criteria against which occupants make these evaluations. For example, if an occupant is farther from the exit than permissible at time t, EVAL20 will return a negative status evaluation.

This will also occur if the occupant is closer to the fire than permissible at time t.

As the simulation progresses, the criteria become more difficult to

satisfy, since the critical time is continually being approached. Accordingly, the "penalty thresholds" may be viewed as equations which relate

distance and time. In the absence of empirical data, these functions

were assumed to be linear. For practical purposes, BFIRES assumes an intercept of 0, and a slope of 1 for the threat penalty threshold, and

an intercept equal to the critical time with a slope of -1 for the exit

goal penalty threshold (see Figure 2.1).

The consensus and threshold constants may not be manipulated at execution time. The user may wish to alter their values, however, to reflect new empirical findings or to suit special conditions. This will require

modifications to the program source code. Should a particular application of BFIRES necessitate frequent variation of these values, the user

may wish to establish them as input variables.

2.3 Internal Dynamic Processes

Certain variables within BFIRES take on a new value at the start of each

time frame. However, these are determined entirely by internal processes, and are outside the user's immediate control. The most critical

example is P(K) , the probability that an occupant will, during a given

time frame, select some move alternative, K. The actual values of P(K) are computed within subroutines EQUALZ, TBIAS, EBIAS, ASSIGN, or DOORSl,

depending upon the biasing mode selected in subroutine ASSIGN and the

door-opening behavior generated by subroutine DOORSl.

To date, it has not been possible to calibrate computed values of P(K)

against data from actual fire situations. This is because no data on human behavior during fires exist to describe emergency decisionmaking

processes at so fine a level of detail. Considerable research will be

13
TIME

FRAME

TIME

FRAME

DISTANCE TO THREAT LOCATION

DISTANCE TO EXIT GOAL

Figure 2.1 Calibration of Penalty Thresholds in Subroutine EVAL20

14
necessary to understand the mechanism by which people under emergency

conditions perceive alternative courses of action, relate such alternatives to broader egress strategies, and then select appropriate actions.

As new data becomes available, however, the user may wish to incorporate

new hypotheses about decision biasing or probability value computation.

This will require modifying the program source code.

2.4 USER SUPPLIED VARIABLE VALUES

Parameters describing most of the Important initial conditions are determined by the user, and are input at program execution time. There

are four broad categories of input parameters: (1) fire descriptors;

(2) occupant descriptors; (3) building descriptors; and (4) system

descriptors.

2.4.1 Fire Descriptors

The current version of BFIRES permits the user to define only the initial spatial location of the fire threat (input variables XT and YT).

As BFIRES does not simulate any form of threat migration, the initial

location specified by the user will remain constant throughout the

simulation run. This factor may, however, be used as the basis for a number of realistic fire cases, e.g.: (1) simulation of egress from

compartment while fire and smoke are confined to another compartment

elsewhere on the same floor; (2) simulation of egress from one floor

while fire and smoke are confined to another floor elsewhere within the

building; and (3) simulation of egress during a fire drill, in which one exit has been blocked-off due to "mock fire" conditions.

When specifying the initial location of the threat, the user in effect

blocks-off one of the available exits from the floor; he must assume

that the fire (occurring elsewhere on the floor or within the building)

has effectively rendered that exit non-useable. When using BFIRES to

test egress time requirements from floor plans, the user may establish

exits wherever desired, and run simulations, for any blocking condition

(threat location) he chooses.

2.4.2 Occupant Descriptors

The model underyling BFIRES suggests that a variety of factors may inter

act to predispose occupants to respond in certain ways to the emergency

environment. Principal factors include: (1) the number of occupants

involved in a given fire event; (2) the initial spatial location of each

(3) the tolerance of each occupant to interruptions to goal-seeking

behavior; (4) each individual’s Initial state of knowledge concerning

the location of the best exit from the floor; (5) each occupant's

initial mobility status (e.g.. Impaired versus non-lmpaired mobility);

and (6) each occupant's predisposition toward opening and closing doors

encountered along the egress route.

15
When preparing a given BFIRES simulation run, the user must determine

values for each of these parameters. If the user wishes to simulate a hypothetical fire in an actual facility , he must be careful to estimate

the likely spatial positions of occupants, as well as calibrate each on

the various parameters enumerated above. Spatial locations may usually

be estimated on the basis of information known about the building (or

building type) under study, e.g., work stations, relative locations of

beds, etc. A nighttime fire at a nursing home, for example, would be

simulated with all patients at bed locations, one or two staff members

at their station, and perhaps a single staff member in a corridor. A

daytime event in an office wing might find all occupants initially at

their predefined work stations.

It should also be possible to "guesstimate" values for other occupant

parameters. Consider predispositions toward opening and closing doors.

These are input in the form of probabilities: i.e. , the variable POPEN

is the probability that an occupant opens a closed door he confronts;

the variable PCLOSE is the probability that an occupant closes a (manualtype) door he has just passed through. In the nursing home example, the

user could preset POPEN and PCLOSE for staff members to reflect a particular training program; and preset these variables for patients to

reflect a lack of knowledge; cognitive impairment due to sedation, etc,

(perhaps using the value of 0.50 for each variable). The user might

wish to evaluate variations in door-manipulation behavior exhibited by

staff members which result from different training philosophies. Several

BFIRES runs may be conducted for each of several values of PCLOSE and

POPEN, and the varying effects (if any) of door-manipulation upon egress

time or number of persons evacuated can be studied.

Similarly, the mobility status of occupants, and the exit knowledge of

each, should be estimable from prior knowledge of the facility under

study. Other paramters, however, such as interruption tolerance, are presently not estimable on the basis of existing data from building fire

cases. Here again, data will be required which describe occupants

decisionmaking procedures during emergency conditions,

2.4.3 Building Descriptors

BFIRES constructs building floor plans on a two-dimensional plane by

laying walls out as orthogonal vectors on an x, y grid. Doorways are represented as breaks in wall lines. Such openings may or may not have

doors Installed within them. When doors are present, they may be either

manually- or automatically-closing. The user is free (within certain

limitations) to enter into the computer a floor plan of almost any configuration, This is accomplished by reading in the x, y coordinates of

points defining walls and doors. The principal limitation is that all

walls must lie along orthogonal vectors (i.e,, they must be parallel

to either the x or the y axis). Accordingly, angular or curvelinear

walls must be entered as "steps" (refer to Figure 2,2),

16
Curvelinear element

X

Figure 2.2 Translating Orthogonal, Curvelinear, and Angular Wall

Elements Into BFIRES-readable Form

17
The severity of this "stepping" condition is reduced as the size of the

X, y grid units decrease. But this additional sensitivity comes at the

cost of increased computer memory requirements. For example, a floor

plan laid out on a 10 x 10 grid requires storage for no more than 100

points (wall, door, and person-occupiable locations). A much more

sensitive simulation will result if this plan is laid out on, say, a 50 X 50 grid (e.g., much finer changes in occupants' incremental movement will be generated with each passing time frame). However this

arrangement will require storage for 2,500 points... a 25-fold increase.

Note the examples in Part 3.0 of this report. In Case Study A, a floor

plan is laid out on a 5.0 foot grid. In Case Study B, a more sensitive

2.5 foot grid is used.

The user is free to use almost any size grid he feels is appropriate,

(provided be does not exceed program array limits), considering the

degree of sensitivity desired, and the amount of computer memory available. Once a grid has been laid over the floor plan (which may be

"idealized" to meet the orthogonal vector criterion), wall designator

points are entered through input variable IBAR (IS, I, J). Information

concerning door location, operating type, and initial position position

(i.e., open or closed) is entered via input variable IDOOR (I, J). Of

course, the user can vary the location of walls and doors (i.e., alter

the floor plan) between simulation runs, and study the study variations

in egress phenomena.

2.4.4 System Descriptors

Several input parameters are available which permit the user to establish system-wide rules. The number of replications of a given simulation is specified by NUMREP. If NUMREP is preset to "5", for example,

the computer will generate five completely Independent events which are identical in all respects - except for the outcome of stochastic

processes

.

The user must also preset the desired length of the simulation run. TOTIME specifies the number of interactions within each replication, in

time frames. When comparing simulation outcomes with real-world events,

it is necessary to convert time frames to real time units (i.e.,

seconds). Table 2.1 illustrates such conversions for several typical

situations. When using this table, the user must: (1) make an assumption about the mean^walking speed of all occupants in the event, and

(2) use a mean grid step which conforms to the grid size he has superimposed over his floor plan. For example, if we assume a mean walking

speed of 4.5 ft/s (1.37 m/s), and a mean grid step of 3.02 ft. (0.92m),

then a single time frame will equal about 0.67 seconds, and it will

require about 90 time frames to simulate one minute real time.

* mean grid step = (length of orthogonal step) + (length of diagonal step)

18
TABLE 2.x TIME FEIAME/REAL TIME CONVERSIONS, FOR THREE

VALUES OF WALKING SPEED

MEAN WALKING SPEED (V) = Mean Step Leng^th

Unit Time (second)

4 ft/s 4.5 ft/s 5 ft/s

(1.22 m/s) (1.37 m/s) (1.53 m/s)

o

3.02 ft TF = 0.76 s TF = 0.67 s TF = 0.60

&0

nt •Ho

(0.92 m) TF/min =79* TF/min = 90 TF/min = 100

+

O

XJUuO

II a

6.4 ft

(1.84 m)

TF = I.5I s

TF/min = 40

TF = 1.34 s

TF/min = 45

TF = I.2I s

TF/min = 50

W

QM

i

12.07 ft TF = 3.02 s TF = 2.68 s TF = 2.41 s

(3.68 m) TF/min = 20 TF/min = 23 TF/min = 25

* time frames per minute, rounded to the next higher frame

Where;

TF = Time Frame in "real time" seconds = —

V

Orth D = length of orthogonal step

Diag D = length of Diagonal step

19
Figure 2,3 provides a convient graphic conversion chart, which permits

conversion either from time frames to seconds, (how many seconds are simulated by a run of predetermined length?), or from seconds to time

frames (how long must a simulation run in order to represent a desired

period of real time?).

Note that "grid step" is not meant to imply walking stride . It merely

refers to the mean distance between person-occupiable grid locations.

The user can , however, select his x, y grid to assure that "grid step"

is quite similar to mean walking stride. But again, this may require a large expenditure of computer memory.

Another system-wide parameter preset for a given simulation run is the

crowding factor, input via variable lALLOW. lALLOW specifies that maximum number of occupants permited to Inhabit any person-occupiable grid

location during a single time frame. The value of lALLOW can easily be

converted to a measure of maximum allowable density (persons per unit

area) as follows;

Maximum Allowable Density = area of a grid square

Finally, the user must predetermine the likelihood that occupants will,

during the simulated event, experience a "backtrack" interruption, a "remaln-in-place" interruption, or no interruption at all (these are detailed within Appendix A, under discussions of Subroutines INTRPT and

BACKUP). The probability of a backtrack Interruption is input via

variable PI2, and the probability of experiencing no interruption at all

is input through variable PIO, The probability of experiencing a remainin-place interruption is computed internally as the difference between

PI2 and PIO.

2.5 SUMMARY

Part 2,0 dealt with the calibration of the BFIRES simulation program. A

variety of parameters were considered, and particular attention was paid

to the problem of aligning these with parameters which describe realworld fire events. Three broad categories of parameters were discussed.

Values of internal constants and internal dynamic processes are written

into, or are determined by the BFIRES source code, and are therefore outside the user's direct control. Important parameters which describe the

fire, the occupants, the building, and other aspects of the simulation

event are user supplied at execution time.

20
OF

SIMl

25

Q

AJ

20

15

10

50

45

40

35

30

25

20

15

10

4J +1 6 a E

CD 'd* (N OJ o CD o CD O cr>

• • t • « • 12 CO VO iH ro o

ESTIMATED LENGTH OF REAL EVENT

(seconds)

Figure 2.3 Time Frames to Seconds Conversion Chart

21
3.0

PROGRAM SENSITIVITY ANALYSIS

3.1 INTRODUCTION

3.1.1 Rationale

Sensitivity analysis is an important step in the overall validation of

computer simulation programs such as BFIRES. Generally speaking, sensitivity analysis helps the simulation program writer to determine whether

the "cause-and-ef feet" relationships (often expressed as "if . . . then. . .

statements) which comprise the underlying process model are in fact

demonstrated when the computer simulation is run. Another way of

expressing this problem is by asking how variation in simulation parameter values impacts the results of computer runs, and whether these

results conform with hypotheses derived from the program underlying

model.

Remember that sensitivity analysis yields no Information about whether

the underlying model (i.e., the set of "if . . . then. .

. " statements)

correctly reflects "reality". Similarly, it does not tell us whether

the most important or useful parameters (from an applications point of

view) have been selected for study. However, sensitivity analyses

provide a considerable amount of information about the Interal consistency of the modeling and simulation design processes. This is accom- plished through the examination of specific hypotheses (derived from the

model) about causal relationships, making use of data from computer

simulation exercises.

3.1.2 Overview of the Technical Approach

BFIRES enables the user’ to simulate any number of situations. This

is accomplished by adjusting the BFIRES input parameters to reflect a particular set of initial occupant and environmental conditions. The

complete set of parameters defines the initial state of a given event,

and they may be altered by changing the values assigned to input parameters .

Computer simulations are useful because they help us to make causal predictions (of the "if . . .then. . ." variety), and to evaluate differences

among outcomes from initially dissimilar events. Accordingly, we would

expect differences in initial occupant and environmental conditions to

yield variations in simulated emergency egress outcomes. For example,

we would expect occupants initially located near a safe exit (and at the same time located far from the threatened zone) to leave the building or floor before occupants located at a greater distance from the exit.

Similarly, we would anticipate that occupants who are familiar with the

building, and who knew the location of exits, to escape faster (and use

a more direct path) than occupants who have no such familiarity. In a final example, we might expect that mobility-impaired occupants will

22
recjuire more time to leave the building or floor than will occupants

with no such impairments.

The principal questions for sensitivity analysis is, then, whether varia"

tions in event-defining input parameters produce the expected variations

in BFIRES egress behavior? This question was studied by establishing

base fire scenarios, manipulating input parameters, and then measuring

differences between simulated egress outcomes (e.g., egress time and

path length). According to this rationale, we may conclude that BFIREJS

is sensitive to variation in a particular parameter if, while holding

all other parameter values constant, we find a significant difference

between outcomes from simulations run under two or more different value?

of t!est parameters. For example, if occupants of a floor with dead end

corridors require significantly more time to escape than do occupants

00 a floor without dead ends, then we may conclude that BFIRES is

sensitive to variation in one aspect of "floor plan configuration".

Similarly, if we find that occupants with no familiarity with exit

locations traverse significantly longer paths than do occupants who do

possess exit knowledge, then we will have determined that BFIRES is

sensitive to variation in "exit knowledge" or "building familiarity".

The following list contains input parameters manipulable by the BFIRES

user* To reiterate, , the user presets the initial state of a fire event

jay assigning values to these variables. He differentiates between

events by varying the values of one or more parameters. Parameters

merked with an asterisk (*) were the subjects of specific sensitivity

analyses reported later in this chapter:

*(1) initial threat location;

*(2) placement of interior doors and floor (or building) exits;

*(3) spatial configuration (involving: layout, corridor arrange-^

ment, access to exits, shape of spaces);

*(4) number of spatial subdivisions contained within a floor plan;

(5) number and location of occupants on the floor;

(6) occupants' knowledge of initial threat location;

*(7) occupants' familiarity with the floor or building (i.e.,

their knowledge of a "best exit");

*(8) occupants' mobility status;

*(9) permissible occupant density (or crowding factor);

(10) door type (i.e., manually versus automatically closing);

(11) initial door position (i.e., open versus closed);

23
(12) probability that an occupant will open a closed door he

encounters;

(13) probability that an occupant will close a door he has

passed through;

(14) probability that an occupant will encounter either a remain-in-place or a backtrack interruption.

These parameters were specially selected for user manipulation because

of their practical appeal to building designers, regulators, and managers, and to professionals interested in evaluating the effects of

training programs. We now turn to analyses of two hypothetical cases.

3.2 ANALYSIS ”A"

3.2.1 Description and Objectives

Description ; Fire events were simulated on a rectangular zone measuring

20 feet by 35 feet (6.10 m by 10.68 m). Two exits from the zone were provided, one at the center of each long wall. One exit provided a direct escape to a place of refuge; the other connected the zone under

study with another section of the floor. During all simulations in

Analysis "A”, this later exit was assumed to lead directly to lifethreatening agents (fire and smoke). Accordingly, although the zone under investigation had two potential exits, one was assumed to have

been rendered impassible prior to the onset of the simulation .

Simulations were conducted under various values of the spatial configuration, and interior door placement parameters (refer to Figures 3.1, 3,3,

3.5, and 3.7). These conditions simulated different ways of subdividing

the original zone into smaller functional units. These may represent

variations in bedroom or service space configurations in, say, an addi~

tion to a small nursing unit or group home.

Each simulation run Involved 12 occupants. These were Initially located

at points shown in Figures 3.2, 3.4, 3,6, and 3.8. At the start of each

run, all occupants were assumed to have been alerted to the existence of

the fire, and to the fact that a particular exit was already blocked and

should therefore not be used. In all cases, occupants were assumed to

be "ordinary residents"; no staff persons or other individuals with

specialized training or knowledge (e.g., to affect rescue activities)

were assumed to be present. All occupants were assumed to be fully

mobile with external assistance.

Objectives ; The primary objective of this analysis was to detemlne

whether BFIRES is sensitive to differences in floor plan configuration

(more specifically, degree of spatial subdivision). Secondary objectives

of the analysis were to determine whether program is sensitive to variations in permissible occupant density , and whether it produces an inter - action effort between spatial organization and permissible density.

24
Shaded portion denotes area infiltrated by fire or smoke

Figure 3.1 Un-sub divided Spatial Zone (One-Space Plan)

25
Y

0 2 4 6 8 10 12 14

Figure 3.2 One-Space Plan In BFIRES Grid Form

26
Fjlgure 3.3

Shaded portion denotes area infiltrated by fire or smoke

Spatial Zone Subdivided Into Three Units (Three-Space Plan)

27
r

0 2 4II6 8 10 12 14 16

! — 1 I

1

1

r

1 5 en f*3 r 1 3 C

i

L 3 3 a Cj 3 a L

r

J

-1

i

1

I

1

1

1

1

1 1 1 B 1

r

J (1.53t

1 1 1

1

r

1 1

n p

1 M

T r

L

r

J 1

P

1 1

n p

1 ^

1 p

1

,

Lr^ J L J L J L J c P

1

1

THREAEXrENED

rr

1 one occupa

time^frame

rat at

01

,

t location

Figure 3.4 Three-Space Plan in BFIBES Grid Form

28
Shaded portion denotes area infiltrated by fire or smoke

Figure 3.5 Spatial Zone Subdivided Into Five Units (Five-Space Plan)

29
Y

0 2 4 6 8 10 12 14 16

Figure 3.6 Five-Space Plan in BFIRES Grid Form

30
shaded portion denotes area infiltrated by fire or smoke

I’^.gure 3.7 Spatial Zone Subdivided Into Seven Units (Seven-Space Plan)

31
Y

0 2 4 6 8 10 12 14 16

Figure 3.8 Seven-Space Plan In BFIRES Grid Form

32
3,?, 2 Experimental Design

Independent variables ; A two-way factorial design was constructed to

test the effects of spatial subdivision (the actual number and size of

spaces, or "rooms", constructed within the basic rectangular zone) and

permissible occupant density (the maximum number of occupants permitted

to inhabit a single person-occupiable location at any point in time).

The 4x3 design is shown in Figure 3.9.

The spudy of these variables was warranted for certain practical reasons

Fqr example, fire safety regulations address the design of access to

exitways, and the "directness" of egress paths, without actually evaluat

il^g the cpsts and benefits of alternative designs. A simulation program

sep^iplve to various aspects of spatial configuration could help fill

phis regulatory gap.

Dependent variables ; The two variables measured were occupants' escape

scpres, and their total numbers of spatial displacements ("steps").

Eecepe score is the ratio of time required for escape versus the total

length of the simulated event, and is computed by BFIRES as follows:

E = ~

t where,

occupant's escape score

t = total length of the simulated event in time frames

f =» total number of frames the occupant actually spent on the

floor of study, prior to escape,

Accordingly, if a simulation was run for a total of 100 time frames, and

occqpant escaped during the 50th frame, then his escape score is computed to be 0.50. If the occupant never escapes during the run, his

sepre will be 0.00. The higher the escape score, the earlier during the

simulated event did escape occur.

total number of spatial displacements made by an occupant during a simulated fire event, and the extent of deviation from the minimum

number of steps actually required, may be used as Indicators of egress

path directness and complexity.

Hypotheses i The following hypotheses were examined:

(1) Escape score varies as a function of the extent of spatial subdivision, and in general, for a zone of given gross area, as the number

of subdivisions increases, the mean escape score increases.

(2) Total spatial displacement varies as a function of the extent

of spatial subdivision, and in general, as the number of subdivisions

inerpAses, the number of steps taken decreases.

33
CONFIGURATION

CDCO

N

fQ •H

•U

(C

CO0

CO

(0

rC CMO

qO

•M

CO2

•M

'O

Ml

'=51

CO

to

(13

(Dq

CM

CD 'a

PERMISSIBLE OCCUPANT DENSITY

Figure 3.9 4x3 Factorial Design for Analysis **A"

34
These expectations are deduced from the model underlying BFIRES, which

suggests that before selecting a particular move, occupants first scan

the available alternatives, and weigh the relative costs and benefits of

each. Further, the model implies that as the number of alternatives

available to an occupant at time t increases, the likelihood that he

will in fact select the biased move decreases. As a result, we should

expect more frequent goal-directed movement decisions, and hence a more

direct egress route (l.e. , higher escape score and fewer displacements),

in cases providing the fewest movement alternatives.

(3) Escape score varies as a function of permissible occupant density, and in general, the higher the permissible density, the higher the

escape score.

(4) Total spatial displacement varies as a function of permissible

occupant density, and in general, the higher the density, the fewer displacements will be made.

The notion that occupant density (or, "crowding") impacts egress time

and escape route is also deduced from the model underlying BFIRES.

Similarly, the idea that the effects of density vary as a function of

spatial configuration also stems from the model. While scanning alternative target locations, occupants are thought to assess the viability

of each with respect to certain criteria. The first criterion an alternative target location must pass is its possibility of being reached.

Accordingly, theoretical targets which are blocked by walls cannot be

reached in a single step, and are thus deleted from the occupants' array

of alternatives during time t. Similarly, targets perceived by the

occupant as "crowded" will also be ruled out.

Although the reduction of alternatives has the effect of increasing the

likelihood of selecting a goal-directed alternative, it also has the

effect of reducing the actual number of alternatives leading toward a specified goal. This may influence egress behavior. For example, when

occupying a large open space, an individual .will often have nine movement alternatives available to him (the maximum possible) at a given

point in time. Consider a situation in which the occupant perceives

three of these alternatives as adaptive (i.e., as being highly goaldirected). If he notes that one of these will lead to a crowded location, he will drop it from his list of alternatives. However, there is

still a high probability that the occupant will select one of the

remaining two goal-directed moves.

But consider an individual occupying a more confined space, and that at

time t there are only four movement alternatives available. Consider

further that the occupant perceives that only one of these alternatives

will satisfy his objective. If the target location of this move is

perceived to be crowded, then less adaptive movement behavior will

result (e.g., remaining in place, or meandoring), and valuable time will

be wasted.

35
(5) The effect of occupant density is dependent upon the extent of

spatial subdivision, such that density has the greatest impact where

spatial zones are more highly subdivided into smaller areas.

The meaning of the interaction between spatial subdivision and occupant

density can now be discussed. In larger spaces, an occupant will often

have large numbers of move alternatives (up to nine) to choose from.

More than one of these will usually be perceived as goal-directed, and

so the overcrowding of any single key location need not result in nonadaptive movement behavior. Therefore, the likelihood of successful

escape from larger spaces should depend very little upon the crowding

threshold (permissible number of occupants) for individual spatial locations.

In floor plans subdivided into many smaller spaces, however, the occupant

will usually have relatively few move alternatives to choose from at any

point in time. Often, only one of these will be perceived as goaldirected, and hence the crowding of key locations will lead to nonadaptive movement behavior. Therefore, the likelihood of successful escape

from highly subdivided zones should depend directly upon the crowding

threshold for Individual spatial locations. In such cases, higher thres-^

holds should "forestall” the perception of crowding, by simply endowing

occupants with a greater tolerance for being crowded. The five hypotheses discussed above are summarized in Figure 3.10.

Data collection and analysis ; The spatial subdivision and occupant density parameters were examined at the levels indicated in Figure 3.9.

Variation in spatial subdivision was defined as the extent to which the

original 700 square foot (65.15 m^) zone was subdivided into smaller

spaces, as follows:

O Level 1: one space; area equals 700 square feet (65.15 m ).

Level 2: three spaces; mean spatial area equals 200 square feet

(19.36 m^).

Level 3: five spaces; mean spatial area equals 142 square feet

(12.78 m^).

Level 4: seven spaces; mean spatial area equals 108 square feet

(9.72 m2).

Variation in occupant density was defined in terms of the maximum number

of persons permitted to occupy any spatial location at a given point in

time. In Analysis "A", a person-occupiable spatial location represented

an Imaginary envelope of 25 square feet (2.25 m^). Therefore:

Level 1: density threshold equals 1; maximum allowable density

equals 0.04 persons per square foot (0.43 persons per

m2)

,

36
ROUTE

LENGTH

ESCAPE

SCORE

PERMISSIBLE OCCUPANT DENSITY

Figure 3.10 Graphic Summary of Hypotheses (1) - (5)

37

EGRESS

TIME
Level 2: density threshold equals 3; maximum allowable density

equals 0.12 persons per square foot (1.29 persons per

m^)

.

Level 3: density threshold equals 5; maximum allowable density

equals 0.20 persons per square foot (2.15 persons

per m'^)

.

The 4x3 factorial design was replicated 10 times. For each cell,

values of both mean escape score and mean spatial displacement (across

the replications) were recorded. Separate analyses of variance were conducted for each of the two dependent variables, in order to assess

the effects of spatial subdivision and occupant density.

The random effects analysis of variance model was chosen, in which the

interaction mean square is used to compute values for the main effects.

This model was employed since the levels of the independent variables

actually studied could, at least in theory, have been selected randomly

from some larger range. Use of the random effects model permits inferences to be drawn from the particular findings to all levels of the

variables, within such a range.

3.2.3 Findings and Discussion

Mean outcomes from simulation runs assuming density thresholds of one,

three, and five are shown in Tables 3.1, 3.2, and 3.3, respectively.

Each table indicates mean escape scores and route lengths (in number of

"steps") aggregated across all 12 occupants within each replication.

Hence, the grand means were computed by aggregating across occupants and

replications, for each level of the spatial subdivision variable. These

data are shown graphically in Figures 3.11 and 3.12. Analyses of variance for escape score and step totals are summarized in Tables 3.4 and

3.5, respectively.

Escape score ; Hypotheses (1), (3), and (5) presented above were

supported by simulated escape score data. In particular; BFIRES was

found to be sensitive to variation in both spatial subdivision and

occupant density, in the predicted directions. Moreover, the predicted

interaction effect between these variables was also found to be statistically significant.

Route length ; Hypotheses (2) and (4) were supported by simulated data

on route length (total steps taken by occupants). In particular, the

program was found to be sensitive to variation in both spatial configuration and occupant density, in the predicted directions. However, no statistically significant interaction effect between these variables was

found.

Discussion ; Two Important conclusions are suggested by these findings.

First, under the experimental conditions described above, the BFIRES

computer program faithfully replicated theoretical relationships about

38
Table S.l Mean Outcomes From Simulations Based on a Density

Threshold of 1

Replication

1-Space Plan

Mean j Escape! Mean

Score 1 Steps

3-Space

Mean | Escape | Score 1

1

Plan

Mean

Steps

5-Space Plan

Mean | Escape | Mean

Score 1 Steps

L

7-Space Plan

Mean 1 Escape! Mean

Score ! Steps

1 .27

1

1

1 16.50

j

1

1 .18 1

1 16.92 .19

1

1 17.17

1 .38 i 12.58

2 .31 1 14.50

1 .28 i

1 14.58 .36 1 12.42

1 .35 1 11.42

3 .26

1

1 17.08

1

1 .33 1

1 13.83 .26 i 14.83

1 .31 i 12.50

A .33 1 14.58

1

1 ,22 1

i 16.25 .28

1

1 14.33

1 .30 1 13.25

5 .32

J

1 14.67

1 .20 1

1 16.50 .26

1

1 15.00

1 .36 ! 10.58

6 ..22

1

1 16.50

1 .26 11 14.25 .42

1

1 10.25 .36 1 12.92

7 .41

1

j 13.58

1

1 .27 1

1 16.42 .29

1

1 14.50

1 .27, 1 13.67

8 .34

j 14.17 .24 i

1 15.58 .32

j 13.67 .29 1 13.00

9 .35

1

I 13.58

1

1 .17 1

1 17.17 .27

1

1 14.92

1 .36

j 11^83

10 .42 1 12.75

1 .22 1 15.42 .27

1

1 15.08 .27 ! 14.58

1 , 1

1

1

1

1

r

1 ^RAND MEANS .32 1 14.79 .24 1 15.69 .29 1 14.22 .33 1 12.63

39
T ab le 3.2 Mean Outcomes From Simulations Based on a Density

Threshold of 3

Replication

1-Space Plan

Mean j Escape! Mean

Score 1 Steps

3-Space Plan

Mean | Escape! Mean

Score ! Steps

5-Space Plan

Mean | Escape ! Mean

Score ! Steps

1

7-Space Plan

Mean ! Escape! Mean

Score ! Steps

1

1 .18

1

j 19.58

1 .34 13.75 .56

1

1 10.25

1 .49

1

i 10.75

1

2 ,39

1

1 13.83

1 .39 14.75 .53

1

1 10.67

1 .55

1

1 9.17

1

3 .49 \ 11.25

1 .34 13.58 .45

1

i 12.33

1 .51

1

1 9.83

1

4 .38 i 14.17

1 .34 15.17 .35

1

1 15.33 .46

1

1 10.50

5 .43 1 13.33

1 .31 13.67 .47

1

i 11.17 .49

1

j 11.00

6 .32 i 14.17

1 .26 16.58 .38

1

1 13.25 .29

I 15.08

7 .42 1 13.25

1 .24 16.33 .47

1

1 11.83 .58

1

1 8.75

8 .33 1 15.67

1 .27 16.58 .39

i

1 13.83 .56

1 8.67

9 .39

1

1 13.58

1 .41 13.67 .56

1

i 9.08 ./5

1 12.17

10 .39 1 13.58 .32 15.75 .55

1

j 9.33 .54 j 10.25

1 1

1

1

1

1

1 1 1 GRAND MEANS .37 1 14.24 .32 14.98 .47 1 11.71 .49 ! 10.62

40
Table 3, 3 Mean Outcomes From Simulations Based on a Density Threshold of 5

Replication

1-Space Plan

Mean | Escape' Mean

Score I Steps

3-Space Plan

Mean

Escape

Score

Mean

Steps

5-Space Plan

Mean

Escape

Score

Mean

Steps

7-Space

Mean

Escape

Score

1

2

3

A

5

6

7

8

9

10

.46 j 12.17

I .46 j 13.17

.45

.26

.47

.36

.26

.34

.34

.41

13.00

17.08

12.00

14.83

16.83

15.08

14.67

13.75

.32

.20

.38

.40

.21

.27

.35

14.92

17.58

12.92

13.08

17.33

16.33

14.00

.42 i 11.83

I .26 1 16.92

I .29

j 15.50

.34

.50

.59

.52

.53

.56

.41

.49

.64

.37

14 . 33

10.17

8.50

10.50

10.00

9.00

12.33

10.50

7.67

13.33

.44

.52

.51

.50

. 66

.40

.44

.56

.62

.42

GRAND MEANS .38 14.26 .31 I 15.04 49 10.63 .46

Plan

Mean

Steps

12.92

9.50

10.33

10.33

6.25

13.58

11.58

9.58

8.67

12.92

10.57

41
spatial subdivision and occupant density which are contained within the

program’s underlying model. Thus, our confidence in the internal validity and consistency of BFIRES is strengthened. Second, when simulating

certain kinds of fire events, users should expect to find BFIRES capable

of distinguishing among variations in such important environmental and

occupancy factors as spatial subdivision and occupant density.

3.3 ANALYSIS "B"

3.3.1 Description and Objectives

Description ; Fire events were simulated on a single story of a dormitorytype facility. The floor under study consisted of a double-loaded corridor with four rooms on each side. The corridor was divided into two

segments by a wall, and the segments were connected by a doorway. Two

egress stairs were provided. One stairway lead to a place of refuge;

the other was assumed to be smoke-logged, due to a fire already burning

on another floor of the building.

Simulations were conducted under two different floor plan configuration

conditions. In the first condition, stairways were located at the

extreme ends of the corridor (refer to Figure 3.13). In the second,

the stairways were located closer toward the center of the building,

leaving dead ends of 15 feet (4.58 m) at each end of the corridor (see

Figure 3.15).

Each simulation run involved 20 occupants. These were initially located

at points shown in Figures 3.14 and 3.16. At the start of each run, all

occupants were assumed to have been alerted to the existence of a fire

elsewhere within the building. All occupants were assumed to be "ordinary residents", and as in Analysis "A", no staff persons or other

individuals with specialized training were present.

Simulations were conducted under several different occupant conditions.

Comparisons were made between simulations in which occupants knew which

stair was blocked and which was safe, and those in which occupants had

no such direct knowledge. In addition, comparisons were made between

simulations in which occupants were fully mobile, and those in which

they were mobility-impaired.

Objectives ; The objective of Analysis "B" was to determine whether

BFIRES is sensitive to differences in floor plan configuration (specifically, the presence or absence of dead end corridors), and to variation

in such occupant parameters as mobility and knowledge about exit utility.

An additional objective was to study the sensitivity of BFIRES to variation in occupant density.

3.3.2 Experimental Design

Independent variables : A four dimensional factorial design was employed

to test the effects of floor plan configuration, occupant mobility.

42
mm

ESCAPE

SCORE

00

25 -

. 50 --

75

1.00

DENSITY THRESHOLD

2 (Persons / m )

35

30

25

20

15

10

5

Figure 3.11 Effects of Spatial Subdivision and Occupant Density on Escape Score

43

REAL

-

TIME

EQUIVALENT

,

IN

SECONDS
MEAN

NUMBER

OF

SPATIAL

DISPLACEMENTS

,

IN

STEPS

2 (Persons / m )

Figure 3.12 Effects of Spatial Subdivision and Occupant Density on Route Length

44

TOTAL

EQUIVALENT

DISTANCE

TRAVELED,

IN

METERS
Table 3.4 Analysis of Variance for Escape Score (N=120)

SOURCE D.F. S.S. M.S. F

Density (D) 2 .415 .207 12.936^

Number of Spaces (S) 3 .417 .139 8.688^

D K S 6 .097 .016^ 3.027^

Within 108 .577 .005

Total 119 1.506

Table 3.5 Aitalysls of Variance for the Total Number of Steps Taken

(N=120)

SOURCE D.F. S.S. M.S. F

Density (D) 2 69.874 34.937 6.660^

Number of Spaces (S) 3 314.167 104.722 19.962^

D X S 6 31.478 5.246^ 1.619

Within 108 349.912 3.240

Total 119 765.431

Notes: (1) significant at the ,05 level

(2) significant at the ,01 level

(3) In the random effects model, the D x S Interaction mean

square Is ued to compute values of ^ for the main effects

45
46

Figure

3,13

Non

Dead-End

Floor

Plan
47

Figure

3.14

Non

Dead-End

Floor

Plan

In

BFIRES

Grid

Form
48

Figure

3.15

Dead-End

SpaLlal

Coiifig

urafeion
49

Figure

3,16

Dead-End

Floor

Plan

In

BFIRES

Grid

Form
occupants' knowledge of the safe exit location, and occupant density

threshold. The 2x2x2x2 design is shown in Figure 3.17, Examination of

these variables is important for a number of reasons. For example,

Analysis "A" suggested the sensitivity of BFIRES to variation in a particular aspect of building design, spatial subdivision. Floor plan

configuration is another aspect of design which is under the immediate

control of the architect. If BFIRES can assist the architect in evaluating differences between alternative floor plan arrangements, it will be

deemed a valuable design tool. Similarly, the ability of BFIRES to

distinguish among occupants who differ on various characteristics will

strengthen its value as a facility management and occupant (or staff)

training tool.

Dependent variables ; Measures of four dependent variables were recorded:

(a) the total number of occupants who escaped the floor by the end of an

event of arbitrarily selected length; (b) the difference between occupants' initial distances from the safe exit and their final distances;

(c) occupants' escape scores; and (d) occupants' total numbers of spatial

displacements. Variables (c) and (d) have already been described in

detail in Section 3.2,2 above.

Variable (a), the total number of occupants escaping the floor, is self

explanatory. This provides a somewhat gross measure of the overall outcome of a fire event: at the end of a given period of time, how many

people escaped the floor under study? Variable (b), on the other hand,

provides a finer measure of occupant performance during a particular

event. When we curtail a simulated event at some arbitrarily chosen

point, it is quite likely that many occupants who would have eventually

escaped are still found on the floor. It is therefore useful to have

some measure of the progress of the remaining occupants, without having

to actually trace the complete movement paths of each individual

(although BFIRES does permit the user to conduct such tracing exercises)

The "difference” variable accommodates this need. The output is computed

for each occupant, and is defined as the difference in straight-line

distance separating the Individual and the safe exit location between

the initial and terminal time frames.

If the difference output for occupant i is zero, for example, then this

individual was neither nearer to, or farther from, the safe exit at the

terminal time frame as he was at the initial frame. This does not necessarily mean that occupant i remained in place throughout the entire

event. It simply means that all his activity resulted in no net change

in distance relative to the safe exit location. Indeed, an occupant

with a zero difference value may also have experienced a large number of

spatial displacements during the event. This combination would suggest

that movement decisionmaking occurred in an environment virtually devoid

of information (about, say, the location of the safe exit). It would

also suggest that decisionmaking occurred in a confused environment, in

which multiple sources of conflicting information were present.

50
Occupant

Density

Threshold

=1

Occupant

Density

Threshold

0)o

'a ,Qj Q) ‘tH M (TS

§

'43

(s3

tn 43coo

<0

Q.O

O

snrjpr^S* ^‘^TTT<low , s:mednooo

PQ

51

Figure

3.17

Four-Dimensional

Factorial

Design

for

Analysis
Alternatively, difference values may be either positive or negative.

Positive values Indicate that the occupant is nearer to the safe exit at

the terminal time frame; negative values indicate that he is farther.

Consider two examples: An occupant with a high positive difference

value and relatively small displacement output was probably making movement decisions on the basis of "good" information, and is obviously on his way toward reaching the safe exit. Had the simulation been run for

another few time frames, he may very well have attained his exit goal.

On the other hand, an individual with a high negative difference value

is likely to be operating under an erroneous idea of the safe exit's

location, A high negative difference may also result when both the

safe and threatened exits are very close to each other.

Hypotheses : Several hypotheses were evaluated:

(6) Permissible occupant density will have no effect on the dependent variables, nor will it interact with knowledge of safe exit

location, the presence of dead end corridors, or occupant mobility.

We found during Analysis "A" that variation in occupant density produced

changes in event outcomes depending upon the extent to which a spatial

zone was subdivided into smaller and smaller units. In Analysis "B",

occupant density was varied while spatial subdivision and size remained

constant. Under these conditions, the model underlying BFIRES predicts

no variation in event outcomes. Moreover, neither theoretical nor logical links are suggested between occupant density and safe exit knowledge, the presence of dead end corridors, or occupant mobility,

(7) In general, a larger portion of those occupants possessing

knowledge of the safe exit location will escape the floor than those

without exit location knowledge.

Exit-seeking is the most important objective processed within BFIRES.

In order to work toward the exit objective, an occupant must, by definition, possess knowledge of its location. Given a knowledge of the safe

exit's location, the occupant is able to route his way through any network of spatial subdivisions. Without any knowledge of the safe exit's

location, the occupant must resort to satisfying the second-echelon

objective: increasing his distance from the threat. In BFIRES, however,

this may result in "meandoring" , during which the safe exit may be found

only by chance (and not as a result of conscious planning and movement).

On the average, then, we expect most occupants with safe exit knowledge

to escape the floor within the time allowed. Similarly, we expect very

few Individuals possessing no exit knowledge to escape,

(8) Regardless of floor plan configuration, more occupants with

unimpaired mobility will escape the floor than will those with a mobility Impairment,

52
BFIRES defines mobility impairment in terms of a reduction in movement

velocity. This is accomplished by forcing impaired occupants (say,

elderly, arthritic, etc.) to remain in place during every other time

frame. The overall effect is a velocity reduction of about 50% (the

user may wish to adjust the program source code to produce other levels

of reduction). Because of this speed reduction effect, fewer mobilityimpaired occupants are expected to reach the exit objective by the terminal time frame.

(9)

By the terminal time frame, occupants with a knowledge of the

safe exit will have moved closer to the exit objective than will individuals with no exit location knowledge. This will occur irrespective of

floor plan configurations.

Refer to the discussion of hypothesis (7), above. It is assumed here

that many fully able and knowledgable occupants would have escaped the

flopr by the terminal time frame, had the simulation been run for a longer period (say, 150 instead of 100 frames). Accordingly, we expect

such individuals to increase the difference considerably between their

initial and final positions, and that their movement behavior will be

directed toward the exit objective.

(10) The effect predicted by hypothesis (9) will be greater for

unimpaired occupants than for those with mobility impairment.

Refer to the discussion of hypothesis (8).

(11) Occupants with knowledge of the safe exit location will achieve

higher escape scores than will those with no exit knowledge.

Pscape score is an index which indicates not only whether an occupant

has escaped by the terminal time frame (any non-zero value), but also

how quickly (the higher the value, the earlier the escape). Exit knowledge equips the occupant with the highest priority goal, and persons

working toward this goal are expected to es^cape earliest. Refer also

^0 the discussions of hypotheses (7) and (9), above.

(12) Occupants with unimpaired mobility will achieve higher escape

scores than will mobility-impaired individuals.

According to BFIRES, mobility-impaired occupants will require about

twice as much escape time as unimpaired individuals. Since escape score

is a direct measure of escape time*, scores for impaired individuals

* ET = FL [T(l-ES)]

Where: ET = escape time, in seconds

FL = length of a single frame, in seconds

T = total number of frames run ES = occupant's escape score

53
will - by definition - be significantly lower than those achieved by

fully able occupants.

(13) Occupants with knowledge of the safe exit location will traverse

a shorter egress route (i.e., fewer "steps") than will individuals with

no exit knowledge.

Occupants with the exit objective clearly in mind should have relatively

little difficulty in planning their escape routes. These routes will be

as direct and as linear as possible, with deviations resulting only from

random variation and either cognitive or environmental interruptions.

(14) Unimpaired occupants will traverse longer paths during the

simulated event than will those with mobility-impairments.

By definition, unimpaired occupants will take about twice as many "steps"

as impaired individuals. Deviations may result from either random

variation among occupants, or from interruptions, as in the case of

hypothesis (13).

Data collection and analysis ; The floor plan configuration, occupant

mobility, exit knowledge, and occupant density parameters were examined

at the levels Indicated in Figure 3.17, and discussed in Section 3.3.1

( Description ) . Variation in occupant density was defined in terms of

the maximum number of persons permitted to occupy any spatial location

at a given in time. In Analysis "B", a person-occupiable spatial location represented and imaginary envelope of 6.25 square feet (0.56 m^).

Therefore:

Level 1: density threshold equals 1; maximum allowable density

equals 0.16 persons per square foot (1.79 persons

per m^)

.

Level 2: density threshold equals 3; maximum allowable density

equals 0.48 persons per square foot (5.36 persons

per m"^)

.

The 2x2x2x2 factorial design was replicated twice. For each cell,

values of total number of escapees, locational difference, escape score,

and spatial displacement were recorded. Separate fixed-effects analyses

of variance were conducted for each dependent variable.

3.3,3 Findings and Discussion

Mean outcomes from simulation runs are shown in Table 3.6. The values

recorded are aggregations of the original data from the 20 occupants in

each replication. The data were further aggregated across the two

replications. These data are displayed graphically in Figures 3.18

through 3.25. Analyses of variance for the four dependent variables

studied are shown in Tables 3.7 through 3.10.

54
Tablf 3.6 Mean Data From Simulated Fire Events

CASE PLAN® g

o

PQO

X

g

0)CO

M-l&

M

o

00

peS O

CO

X

PhHCO

1' 1 1 0 0 0 1.45 .00 81.38

2 0 1 0 0 0 1.00 .00 80.63

3 0 1 0 1 14.5 15.30 .30 55.68

4 1 3 0 0 0 0.70 .00 82.75

5 0 1 1 0 0 0.10 .00 40.13

6 1 1 1 1 4.0 5.60 .06 37.33

7 0 3 0 0 0 0.60 .00 82.43

8 0 3 0 1 14.5 15.35 .31 55.90

9 0 3 1 1 5.5 11.75 .05 40.63

10 0 3 1 0 0 -0.20 .00 40.98

11 1 3 1 1 5.5 9.85 .07 38.85

12^ 0 1 1 1 4.0 7.60 .05 40.18

13 1 3 0 1 13.0 15.65 .30 59.93

14 1 3 1 0 0 0.20 .00 42.18

15 1 1 0 1 10.5 13.50 .19 63.95

16 1 1 1 0 0 1.05 .00 40.70

(a) floor plan configuration;

0 “ dead-end plan

1 “ non-dead-end plan

(b) occupant density threshold;

value indicates actual number of occupants permitted per person-occupiable

spatial location

(c) occupants' mobility status;

0 » all occupants were uninq)alred

1 > all occupants were Impaired

(d) occupants’ Iqiowledge of the safe exit location;

0 - no occupants possessed knowledge of the safe exit location

1 - all occupants possessed knowledge of the safe exit location

(e) number of occupants who escaped the floor by the 100th time frame

(f) occupants' final locations relative to their initial locations, in grid steps*

(g) occupants' escape scores

(h) total number of actual spatial displacements, in grid steps*

t ipean grid step - 3.5 feet (1,08 m)

55
TABLE 3.7 ANALYSIS OF VARIANCE FOR THE TOTAL

NUMBER OF OCCUPANTS WHO ESCAPE

N = 32

Source df SS MS F

Floor plan configuration (FP) 1 3.781 3.781 3.27

Density threshold (DT) 1 3.781 3.781 3.27

Mobility status (MS) 1 140.281 140.281 121.33*

Exit knowledge (K) 1 639.031 639.031 522.68*

DT X FP 1 .781 .781 .68

DT X MS 1 .031 .031 .03

DT X K 1 3.781 3.781 3.27

FP X MS 1 3.781 3.781 3.27

PF X K 1 3.781 3.781 3.27

MS X K 1 140.281 140.281 121.33*

2nd-order interactions 4

3rd-order interaction 1

Error 16 18.500 1.156

Total 31 963.969

* Significant at the .001 level

56
TABLE 3.8 ANALYSIS OF VARIANCE FOR THE TOTAL NUMBER OF

SPATIAL DISPLACEMENTS ("STEPS" TAKEN)

N=32

'T"

- -

Source df SS MS F

Floor plan configuration (FP) 1 7.078 7.078 .68

Density threshold (DT) 1 .057 .057 .01

Mobility Status (MS) 1 7120.717 7120.717 685.44*

Exit knowledge (K) 1 1293.496 1293.496 124.51*

MS X K 1 961.959 961.959 92.60*

Other Ist-order interactions 5

2nd"order interactions 4

3rd-order interaction 1

Error 16 166.216 10.389

Total 31 9658.441

* Significant at the .001 level

57
TABLE 3.9 ANALYSIS OF VARIANCE FOR ESCAPE SCORE

Source df SS MS F

Floor plan configuration (FP) 1 .001 .001 .76

Density threshold (DT) 1 .002 .002 1.28

Mobility status (MS) 1 .092 .092 55.82*

Exit knowledge (K) 1 .218 .218 131.50*

MS X K 1 .092 .092 55.82*

Other lst“order interactions 5

?nd-order interactions 4

3rd-order interaction 1

Error 16 .026 .002

Total 31 .450

* Significant at the .001 level

58
TABLE 3.10 ANALYSIS OF VARIANCE FOR OCCUPANTS' FINAL POSITIONS

RELATIVE TO THEIR INITIAL POSITIONS

N = 32

Source df SS MS F

Floor plan configuration (FP) 1 2.205 2.205 4.31

Oensity threshold (DT) 1 10.125 10.125 19.78***

Mobility Status (MS) 1 93.161 93.161 182.00***

Exit knowledge (K) 1 1019.261 1019.261 1991.25***

DT X FP 1 .361 .361 .71

DT X MS 1 3.920 3.920 7.66*

DT X K 1 19.845 19.845 38.77***

FP X MS 1 .125 .125 .24

FP X K 1 6.125 6.125 11.97**

MS X K 1 66.701 66.701 130.31***

DT X MS X K 1 5.445 5.445 10.64**

Other 2nd-order interactions 3

3rd-order interaction 1

Error 16 8.190 .512

Total 31 1238.799

* Significant at the .05 level

** Significant at the .01 level

*** Significant at the .001 level

59
DENSITY

THRESHOLD =1

DENSITY

THRESHOLD

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66
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67
Main effect of floor plan configuration ; For all dependent variables

studied, variation In floor plan configuration (l.e., the presence or absence of dead end corridors) produced no significant change In simulation outcomes.

Main effect of occupant density ; Variation In occupant (l.e., whether

the density threshold was or 3 ) had no significant effect upon simulation outcomes for total number of occupants escaping, total spatial

displacement, and escape score. Variation In density did, however, have

a significant effect upon occupants' final positions relative to their

Ipltlal ones, as follows; On the average, occupants In the case permitting higher density were one "step" closer to the exit goal than were

individuals in the low density case. This distance translates to 3.5

feet (1.08 m)

.

Main effect of occupant mobility : Variation In occupant mobility (l.e.,

whether pccupants could move during every, or every other time frame)

had a significant effect upon simulation outcomes for all dependent

measures recorded. In all cases, the effect was In the predicted

direction.

Main effect of knowledge of the safe exit location ; Variation in safe

exit knowledge (l.e., whether or not an occupant knew the location of

the safe exit at the onset of the event) significantly effected event

outcomp^ for all dependent measures. In each case, the effect was in

fhe predicted direction:

Interaction effects ; For each of the four dependent variables studied,

the occupant moblllty-by-exlt knowledge interaction was signficantly

i^rge. T^e analysis of variance for final relative to initial location

yjlelded a number of other significant interaction effects. These

included the first order interactions between occupant density and

mobility, density and exit knowledge, and floor plan and exit knowledge.

Moreover, the second order effect between density, mobility, and exit

knowledge was significantly large.

Discussion ; We shall first consider the analyses for number escaping,

oscape score, and spatial displacement, since these appear to establish

a consistent pattern of results. The analysis for final relative to

initial location produced results falling far outside this pattern. We

will therefore consider that analysis separately.

In discussing the first three analyses, we note that the mobility and

knowledge main effects, and the mobility-by-knowledge Interactions, were

all statistically significant. The main effects by themselves lend ample

support for the sensitivity hypotheses entimerated in Section 3,3,2 above.

This is, occupants' escape behavior, under the experimental conditions

established in Section 3.3,1, are impacted by variation in levels of

occupant mobility and safe exit location knowledge. Moreover, in com- parison to these "personal trait" variables, variation in both allowable

density and floor plan configuration have negligible effects.

68
However, the Interaction of occupant mobility with safe exit knowledge

must be considered if we are to make a case for the sensitivity of

BFIRES to variation in these two parameters. Clearly, the finding that

HFIRES produces interactions among certain input parameters is of critical importance, and permits us to qualify our statement about the

program's sensitivity. In particular, sensitivity to exit knowledge

is contingent upon the level of occupant mobility considered (the reverse also being true). We note that although occupants require a knowledge of the safe exit location in order to escape the floor:

(1) those who are knowledgeable are more likely to escape if they

are not mobility-impaired; and

(2) those who are knowledgeable will escape more quickly if they

ere not mobility-impaired. Moreover:

(3) mobility-impaired occupants traverse the fewest steps, but for

the case of non-impaired individuals, full exit knowledge results in

fewer steps than does a lack of knowledge.

As discussed earlier in Chapter 3.0, these effects are consistent with

the model underlying BFIRES.

Initial relative to final occupant locations : The analysis of variance

for this variable produced results falling far outside the pattern discussed above. Recall that this "difference value" was defined as the

difference between an occupant's initial linear distance from the exit

goal, and his final distance measured at the terminal time frame. This

variable was expected to tell us whether those occupants whose attainment of the exit goal was terminated prematurely (by the arbitrary

selection of the simulation end point) had otherwise made substantial

progress toward the escape objective. Accordingly, a pattern of results

similar to that produced by the analysis of the total number of occupants

escaping was anticipated. Portions of this pattern were, indeed, found

in the analysis of difference values: occupant mobility and exit knowledge main effects, and the first order interaction between these parameters. However, the occupant density main effect was also found to be

significantly large, as were a number of other first and second order

interactions. These clearly complicate the analysis.

It may be that these effects are indeed predictable from the model

underlying BFIRES, but that they Involve relationships so complex as to

require additional analyses. Such analyses would Involve observing the

variables studied here at other levels, as well as considering additional

variables. This task is clearly beyond the current scope.

But perhaps these effects cannot be traced to the model underlying the

computer program. In that case, the program may not have been consistently deduced from the model, or alternatively, the inconsistent findings may be artifacts of the particular sample of cases studied. Again,

the solution of these problems will be tasks for future research.

69
3.4 SENSITIVITY TO ENVIRONMENTAL VERSUS OCCUPANT PARAMETERS

3.4,1 An Overall Comparison Between Analyses "A” and "B"

In Analysis "A”, all replications involved occupants who were fully knowledgeable of the safe exit location, and who were not mobility-impaired.

Under these conditions, event outcomes for various levels of two environmental parameters (occupant density and spatial subdivision) were examined. The analysis concluded that, under the conditions established

for study, BFIRES may be considered sensitive to variation in both environmental parameters.

In Analysis "B", however, two occupant-based parameters (mobility

impairment and knowledge of safe exit location) were investigated in

conjunction with the environmental variables studied in the former case. Occupants in Analysis "B" varied in level of mobility Impairment and

exit knowledge, as well as on the basis of which environmental system

they inhabited. This analysis concluded that, when individuals vary

on the basis of occupant parameters, BFIRES is sensitive only to variation in these parameters; under these conditions, the effects of varia- tion in environmental parameters disappear .

This finding is critical for two important reasons. First, it helps

define the ranges of conditions under which we should expect BFIRES to

be sensitive to various parameters. Second, it raises an important

theoretical question very worthy of future Investigation: is the likelihood of safe escape dependent upon the extent of occupants' mobility,

emergency preparedness and emergency alert, while not at all dependent

on the physical design of the building?

3.5 SUMMARY OF SENSITIVITY RESULTS

In cases where all occupants knew the safe exit location, and where no occupants were mobility-impaired, experiments using the BFIRES computer

simulation program yield results suggesting that:

(1) Escape score varies as a function of the extent to which a spatial zone is subdivided into smaller segments. For a zone of given

gross area, the mean escape score for all occupants should increase as the number of spatial subdivisions is increased,

(2) Total spatial displacement by occupants varies inversely as a function of the extent of spatial subdivision. As a zone is subdivided

into more spaces, the number of steps taken by occupants should decrease.

(3) Escape score varies as a function of permissible occupant density. With a higher permissible density, a higher mean escape score should be found for all occupants on the floor.

(4) Total spatial displacement varies inversely as a function of

permissible occupant density. At higher densities, fewer spatial

displacements should be found.

70
(5) The effect of permissible occupant density is dependent upon

the extent of spatial subdivision. Density appears to have the greatest

impact where spatial zones are subdivided into a larger number of smaller

areas

.

Under conditions where occupants varied in their knolwedge of safe exit

location, and their levels of mobility impairment, BFIRES experiments

yielded results suggesting that;

(6) Floor plan configuration (specifically, the presence or absence

of dead end corridors) has no effect on emergency egress outcomes.

(7) In general, egress outcomes will not be influenced by variations

in permissible occupant density.

(8) Egress outcomes vary as a function of occupant mobility. Unimpaired occupants are more likely to escape the floor within a given time

period, will escape more quickly, and will traverse shorter routes than

will their mobility-impaired counterparts.

(9) Egress outcomes vary as a function of occupants* knowledge of

the safe exit location. Knowledgeable occupants are more likely to

escape the floor, will escape more quickly, and will traverse shorter

routes than will uninformed individuals.

(10)

The effect of exit knowledge is dependent upon occupants'

mobility. In general, occupants never informed as to the location of

the safe exit may never escape within the time allowed. However,

occupants who ^ know the safe exit's location will escape faster and

along more direct routes if they are not mobility-impaired.

71
4.0

CONCLUSIONS

4.1

KEY FINDINGS

This effort demonstrated the feasibility and utility of systematically

conceptualizing the emergency egress behavior of building occupants

under certain specified conditions, and of simulating this behavior

on a digital computer. Although the ability of the simulation model to

predict or replicate real-world fire events has not yet been tested,

results to date do suggest that the computer program is applicable

to problems of immediate interest to building designers and regulators.

At the very least, this project has paved the way for future validation

research, and for applications exercises.

In addition to demonstrating both the "simulability" of occupants*

egress behaviors and the value of this capability, important technical

findings were also noted. In particular, this report showed that:

(1) A variety of general egress situations could be simulated by means of the BFIRES computer program.

(2) Every such situation is unique, and is defined by the set of

user-supplied input parameter values which describe the building, the

threat, and the occupants.

(3) BFIRES output is readily interpretable in terms of familiar

units of space and time. Thus, the program is capable of simulating

environments of known (or desired) spatial dimensions, and events of

known (or desired) temporal duration.

(4) BFIRJIS was shown to be sensitive to variations in parameters

of immediate interest to building designers and regulators. These

included: (a) several aspects of floor plan configuration, (b) the existence of impairments to occupants' mobility, (c) occupants* familiarity

with the building layout, and (d) levels of occupant density.

4.2

APPLICABILITY OF AVAILABLE DATA TO THE MODEL-BUILDING PROCESS

As discussed in Chapter 1.0, BFIRES resulted from a deductive exercise,

in which a particular model of emergency egress was derived from a much

more general and basic system: an information-processing theory of

human behavior. The deductive approach was favored over empirical modelbuilding chiefly because of unresolved difficulties which characterize

the available data on emergency egress. Several of these are summarized

below.

First, available data shed virtually no light on the cognitive

processes at work during building fire emergencies. For example, while

Wood (1972) and Bryan (1977) attempted to identify action sequences,

neither described specific processes through which such sequences were

72
detemlned. Accordingly, there remains no direct knowledge of:

(a) occupants’ perception of the building-scale emergency environment;

(b) mechanisms for gathering and interpreting information about the

emergency situation; (c) mechanisms for evaluating alternative action

patterns; and (d) strategies for making decisions about action in or upon the emergency environment. Since BFIRES deals specifically with

these factors, use of this data to formulate or test systemic relationships was not possible.

Second, the literature is characterized by several Important methodological shortcomings. Taken as a whole, for example, the body of research

on egress behavior and human responses during fires was not guided by

any single set of objectives. Consequently, individual efforts were neither cumulative nor purposefully directed toward theory development.

What we do have is a collection of discrete studies in which it is often

difficult to even compare results for ostensibly similar variables.

Moreover, many of the studies discussed above suffer problems or reliability and validity. Included are the following:

(1) Often, such complex constructs as "egress behavior" were operationalized in terms of pedestrian flow measures (e.g., velocity, flow

rate, density). Variance due to social and cognitive factors could not

be assessed, and- variance attributed to physical design features may

therefore have been overrated.

(2) With few exceptions (experiments by Peschl (1971) and Henderson

(1971), field investigations of the carrying capacity of egress ways

were characterized by a lack of experimental controls. In fact, most

studies involved no tests of explicit hypotheses, and may consequently

be viewed as exercises in data collection technique,

(3) Even where meaningful trends might have been found in the carrying capacity data, investigators rarely attempted to quantify these in a statistically rigorous fashion.

(4) Surveys of fire survivors consisteci of scalar, structured, and

open ended items. The reliability and validity of the various protocols

employed has not, to date, been examined.

(5) Survey researchers never systematically controlled for effects

arising from the temporal proximity of the interview and the actual

experience. Where too long a period lapsed, respondents’ impressions of

the event may have changed due to media reports and interactions with

other victims. Moreover, the emotional Impact of the event may, over

time, have altered the Individual’s memory of the fire experience.

Conversely, if the event was traumatic, too short a time lapse could

have resulted in distorted reports. For the available data base, the

extent of such effects - and hence the validity of findings - are largely indeterminate.

73
(6) Finally, when properly conducted an interview may yield much

insight into behavioral processes which result in safe escape during a building fire. Since those who do not survive can never be interviewed,

our knowledge of processes leading to failure can only be based on indirect inference.

For a more detailed treatment of the literature on human behavior in

building fires, refer to the review by Stahl and Archea (1977).

4.3 GENERAL SUMMARY

This report documented computer simulation experiments designed to calibrate and analyze BFIRES, a computer program which simulates building

occupants’ egress behavior during certain fire conditions. The investigation demonstrated that emergency egress behavior can be systematically

conceptualized, and that the computer simulation of this phenomenon

would be useful. In general, experimental results suggested that BFIRES

is sensitive to variation in a number of parameters of immediate concern

to building designers and regulators. Finally, the applicability of

available research data on human behavior in fires to the simulationmodeling process was briefly discussed.

74
REFERENCES

Bryan, J. L., Smoke as a Determinant of Human Behavior in Fire Situations; Project People. Washington, D.C.: U.S. Dept, of Commerce,

National Bureau of Standards, NBS GCR 77-94, 1977.

Henderson, L. F., The Statistics of Crow Fluids. Nature , 1971, 229 , 381-383.

Peschl, I., Passage Capacity of Door Openings in Panic Situations.

Bowen (Construction), January 9, 1971, 62-67.

Stahl, F. I., A Computer Simulation of Human Behavior in Fires: Interim

Report. Washington, D.C.: U.S. Dept, of Commerce, National Bureau of

Standards, NBSIR 78-1514, 1978.

Stahl, F. I. and Archea, J. , An Assessment of the Technical Literature

on Emergency Egress from Buildings. Washington, D.C.: U.S. Dept, of

Commerce, National Bureau of Standards, NBSIR 77-1313, 1977.

Turing, A. M. , Computing Machinery and Intelligence. Mind , 1950, 59 , 236, 433-460.

Wood, P. G. , The Behavior of People in Fires. London, U.K.: Dept, of

the Environment and Fire Officers' Committee, Joint Fire Research Organization, November, 1972.

75
APPENDIX A: "BFIRES" PROGRAM DOCUMENTATION

INTRODUCTION

This appendix provides documentary material which describes the BFIJIES

computer program. The program is presented as a "package" composed of

a network of interrelated subroutines. These are linked through the

EXECUTIVE program, as shown in Figure A.l. For each unit, the following

information is provided:

(1) program or subroutine name;

(2) loop within which the program functions;

(3) description of the program's purpose of function;

(4) description of computational formulas, if any;

A (5) description of program logic by means of flow diagrams ;

(6) FORTRAN listing.

Subroutines comprising BFIRES/VERSION 1 are outlined in Table A.l.

Not Included with I/O and non-behavioral subroutines.

76
OlHERS

GROUPEXECUTIVE

KTOXY

SUMMRY

Figure A.l Subroutine Network and Flow of Control

77
Table A,1 Summary of BFIRES/VERSION 1 Subroutines

Subroutine Functional Category User Options

EXECUTIVE Central calling program no KPOSS Perceptual process simulator no GROUP Perceptual process simulator no

OTHERS Perceptual process simulator no AGREE Perceptual process simulator no

KTOXY Perceptual process simulator

utility program

no

JAMMED Perceptual process simulator no EQUALZ Information processing and

decisionmaking simulator no TBIAS Information processing and

decisionmaking simulator no EBIAS Information processing and

decisionmaking simulator no DOORSl Decisionmaking simulator no DOORS2 Decisionmaking simulator no EVAL8 Information processing simulator yes

EVAL20 Information processing simulator yes

INTRPT Information processing and

decisionmaking simulator no BACKUP Information processing and

decisionmaking simulator no ASSIGN Movement behavior simulator no UPDATE Utility program no NEWXY Utility program no

XSCORH Utility program no

STEPS Utility program no PASSG Utility program no SUMMARY Input/output (I/O) program yes

REPORT I/O Program yes

TRACE I/O Program yes

TOTALS I/O Program yes

78
Routine EXECUTIVE

Loop Replication

Purpose (1) Reads-in input data files;

(2) processes complete replications of

events

building fire

(3) accumulates event outcome data;

(4) summarizes outcome data in tabular form.

Formulas nia.

79
80
o

81
2

82
83
84 5
o

85
86
c

ccCmw

Cmcm

THIS VEBSlOH IS FOR THE INTERMTR 7/32 W4D OT>CR 32-«IT UNITS

C* BFIRES — HUMAN EGRESS BEHAVIOR DURING BUILDING FIRES C*

cm

cm

cm UFITTEN BY FRED I. STAHL. RESEARCH PSYCHOLOGIST Cm ARCHITECTURAL RESEARCH PROGRAM

c» ENVIROKTENTAL DESIGN RESEARCH DIVISION CP CENTER FOR BUILDING TECHNOLOGY, NEL CP NATIONAL BUREAU OF STANDARDS c« UASHINCTON. DC 2B234 CP

CP FOR PROGRAM FOR DESIGN CONCEPTS CP CENTER FOR FIRE RESEARCH. NEL CP NATIONAL BUREAU OF STANDARDS c«

CP IN SUPPORT OF THE CP

CP NBS/HEU FIRE-LIFE SAFETY PROGRAM CP

C«naoMi C«

C*

C*

REVISED AUGUST 30.1978

THE BFIRES PROGRAM SIMULATES HUMAN EGRESS BEHAVIOR DURING BUILDING

FIRES. BFIRES IS A DISCRETE TIME STOCHASTIC SIMULATION BASED ON A NON- STATIONARY MARKOV MODEL OF THE BUILDING FIRE PROCESS. ACCORDING TO THIS

MODEL. FIRES MAY EE UNDERSTOOD IN TERre OF THREE INTERACTING COTPONENTS.

THESE ARE (I) THE FIRE AND ITS BI-PRODUCTS. (2) THE BUILDING ENCLOSURE.

AND (3) THE HUMAN OCCUPANTS. EACH POSSESSES UNIQUE CHARACTERISTICS.

AND THE BEHAVIOR OF EACH CONTRIBUTES TO THE OVERALL OUTCOME OF ANY FIRE

EVENT (I.E.. HOU MANY PEOPLE ESCAPED. HOU MUCH TIfE DAS REQUIRED FOR ESCAPE.

ETC.).

E><EC2 IS THE SECOND VERSION OF THE BFIRES EXECUTIVE ROUTINE. THE PURPOSE OF EVSC2 IS TO READ-IN ALL USER-SUPPLIED DATA. AND THEN TO RUN A FIRE EVENT FDR A GIVEN PERIOD OF TItt. IN ADDITION. EXEC2 PERMITS THE USER

C

cc

c

c

cc

c

c

c

cc

c

c

c

c

cc

c

cc

c

c

cc

c

c

c

c

c

c

cc

c

c

c

cc

c

c

cc

c

TO cc;:rucT a number <UP to 2B> of replications of a given fire event, in a SINGLE COMPUTER RUN.

THE FOLLOUING DATA MUST BE PROVIDED BY THE USER. THESE DESCRIBE THE

FIRE. THE BUILDING ENCLOSURE. AND THE OCCUPANTS FOR THE COIVUTER.

XT.YT NUHEXT

rt<Tire NSPACE

EVLOPT

rtC ClALLOU

NDRREPRT

RREPT2

XE.YE

NENPOINT

IBAR(lS.l.J)

IBAR(IS.2.J)

IGOALX

IGOALY XLO.>«I

VLO.YHI

IDOOP.U.J) ID00R(2.J) IDOORO.J)

IDOOR(4.J) NUMOCC

TOTIHE

IRAND

X.Y COORDINATES OF INITIAL THREAT LOCATION

NUMBER OF EXITS FROM THE FLOOR (NOT MORE THAN 2) OCCUPANTS' PERCEIVED TIME FOR EGRESS (LESS THAN TOTIlt) NUMBER OF SPATIAL SUBDIVISIONS ON THE FLOOR (NOT MORE THAN

20) STATUS EVALUATION OPTION SELECTOR PRESET TO ZERO PRESET TO ZERO SPATIAL CRO'JDING FACTOR

NUMBER OF DOORS ON THE FLOOR (NOT MORE THAN 30) SUMMARY TABLE OPTION SELECTOR SUMMARY table OPTION SELECTOR X.Y COORDINATES OF EXITS FROM THE FLOOR NUrSER OF EXITS FROM A SPATIAL SUBDIVISION

NUMBER OF POINTS COMPRISING UALLS UHICH ENCLOSE A SPATIAL SUBDIVISION (NOT MORE THAN 75) X COORDINATE OF THE JTH POINT OF A LJALL UHICH ENCLOSES SUBDIVISION IS Y COORDINATE OF THE JTH POINT OF A UALL UHICH ENCLOSES

SUBDIVISION IS X COORDINATE OF AN EXIT FROM A SUBDIVISION Y COORDINATE OF AH EXIT FROM A SUBDIVISION

RANGE OF X COORDINATES OF POINTS COMPIRISING UALLS UHICH

ENCLOSE A SUBDIVISION

RANGE OF Y COORDINATES OF POINTS COrPRISING UALLS IHICH

ENCLOSE A SUBDIVISION X COORDINATE OF LOCATION OF JTH DOOR Y COORDINATE OF LOCATION OF JTH DOOR DOOR-TVPE IDENTIFIER FOR JTH DOOR

DOOR POSITION IDENTIFIER FOR JTH DOOR HUMBER OF OCCUPANTS IN THE EVENT (NOT MORE THAN 20) TOTAL HUMBER OF SIMULATED TIME FRAMES TO BE RUN (I.E., LENGTH Or THE FIRE EVENT — NOT MORE THAN 100 FRAfCS) RANDOM HUMBER SEED (NECESSARY FOR 32 BIT COtPUTER ONLY), ANY

S DIGIT ODD NUrPER. FOR UNIVAC-II0B VERSION. INSERT ANY

5 DIGIT DUMMY NUMBER; 87
UUUUUUUUUUUUUUUUUUUUUUUUUUUUUUUUUUUUUUUCIUUUUUUUU

C KUrREP

C PI2

c Pie

c INUItl

C LBVSTS

C IHANCI C KNOUPY

C MD.YQ

C POPEN

C PCLOSE

C

TOTOL NUrSER OF REPLICflTIOHS 6ESIRE® PROBABILITY OF R TYPE-2 INTERRUPTION PROBABILITY OF NO INTERRUPTION

OCCUPANTS' INTERRUPTION LIMIT

OCCUPANTS' INTERVENTION LIMIT

OCCUPANTS' MOBILITY STATUS

OCCUPANTS' INITIAL KNOULEDCE OF BEST EXIT X,Y COORDIATES OF OCCUPANTS' INITIAL SPATIAL LOCATIONS PROABILITY TNAT OCCUPANT UILL OPEN A CLOSED DOOR PROBABILITY THAT OCCUPANT UILL CLOSE AN OPEN DOOR

THESE DATA ARE ENTERED IN THE FOLLOUINC KOUENCE...

TITLE (ANY 80 CHARACTER COf«NT)

(20A4) IFMT (USER SUPPLIED FORMAT STATE^EHT>

(20A4) JFMT (USER SUPPLIED FORMAT STATEMENT)

(20A4) KFMT (USER SUPPLIED FORMAT STATEFENT)

(20A4)

XT, YT. NUMEXT. K<T I ME . N3PACE , EVLOPT . tt( , C , I ALLOU. ND , RREPRT. RREPT2

(5(12. IX). 2(1 1, IX), F 1.0. lX.2(tX. I2).2(tX. ID)

>«.YE ALL XC OORDINATES FOLLOUED BY ALL YC OORDINATES

(IFTIT) REPEAT THE FOLLOUINC SEQUENCE FOR EACH SPATIAL SUBDIVISION

HE.NPOIHT

(IFMT) IBARdS. l.J) COORDIATES I-NPOINT IN ADJACENT FIELDS

(JFMT) IBARdS. 2. J) C OORDINATES 1-NPOINT IN ADJACENT FIELDS

(JFMT) IGOALX. ICOALY ALL X COORDINATES. FOLLOUED BY ALL Y COORDINATES

(IFMT) >0.0.>«I.YL0.YHI

(IFMT) IDOORd.J) (COORDINATES I-ND IN ADJACENT FIELDS)

(JFMT) ID00R(2.J) (COORDINATES 1-ND IN ADJACENT FIELDS)

(JFMT) IDDORO.J) (IDENTIFIERS I-ND IN ADJACENT FIELDS)

(JFMT) ID00R(4.J) (IDENTIFIERS I-ND IN ADJACENT FIELDS)

(JFMT) NUMOCC.TDTirC. IRAND.NUMREP.PI2.PIB

(2( 12. IX). IS, IX. 12.2( 1X.F4.2))

REPEAT THE FOLLOUINC LINE FOR EACH OCCUPANT IN THE RIW...

I NTL IM. LBYSTD. IHAND I , KNOUAY. XO . YD . POPEN , PCLOSE

(KFMT)

DIMENSION ITYPE1(20).ITYPE2(20).IDPASS(20),IPS(2O) DIMENSION IXTRCE(20.100).IYTRCE(20.IO0) DIMENSION IBACK(23),JTirE(20).INITYO(20).INITXO(2O) DIMENSION INTR(20).INTNUM(20).TITLE(20) DIMENSION IFMT(20).JFMT(20).KFMT(23), lENTERO)

DIFENSION IBAR(20.75.2).LBYSTD(20).IHANDI(20).KNOUAY(20)

DIMENSION INTLIM (20) . IBY3TD(20) ,NE(20) ,NPOINT(20) DIMENSION PTDIST(20).PEDIST(20).P(9) DIMENSION IGOALX(20. 10) . IGOALY(20. 10) .KXO(20) ,KYO(20) DIMENSION POPEN(20).PCLOSE(20),IDOOR(30.4).IDOPEN(30.100) DIMENSION IFLAGC20). ISCORE(20).NUMSTP(20)

INTEGER »>RIOR(20).YFRIOR(20),SCORE(20)

INTEGER XT.YT.>O(20),YO(20),XE(10).YE(I0).TOTBAR.TOTIME

INTEGER XLO(20) .XHI (20) . YLO(20) . YHI (20) .EVLOPT

INTEGER XO9(20. I00).YOB(20. 100) .RREPRT, RREPT2

C

C READ RUN INPUT AND INITIALIZE RUN VARIABLES READ (S.iei) TITLE c

READ (5.101) IFMT READ (5.103) JFMT

’ READ (5.104) KFMT

C

Cs INITIALIZE THE SIMULATION...

C: (1) ENVIRONMENTAL PARAMETERS; READ (5.100) XT.YT.NUMEXT.ltairE.NSPACE.EVLOPT.ttC.C.

1 lALLOU.ND.RREPRT.RREPTZ

READ (5.1FMT) (XEd), 1-l.NUMEXT). (YEd), I-l.NUrEXT) DO 10 IS-l.NSPACE READ (5. IFMT) NE(IS) .NPOINTdS)

NEXIT*NE(IS) TOTEAR'NPOINTdS)

READ (5.JFMT)(!EAR(IS.I.1).I-1, TOTBAR) READ (5.JFMT)( IBARdS, 1,2), I«l. TOTBAR) READ (5.IFMT)(1G0ALX(1S.JEXIT).JEXIT-1.HUMCXT).

1 (IGORLY(IS.JEXIT).JEXIT-l.NUMEXT)

88
le REM (S. IFnT) X>.0(IS).»II(lS).VtO(IS).YHI(IS) REM <5.JFMT) ( IDOOR( I. U. 1-l.ND) READ (S.JFtIT) (ID00Rn,2),I>l.ND)

READ (5,JFrm (ID00Ra,3).I»l,ND)

READ (S.JFtIT) nD00R(I.4>,l-l,HD)

Cl (2) SYSTEM PARAMETERS: READ (3,102) NUM3CC.T0TIMC.lRAND.NUn;EP.PI2.Pie

DO 40 1‘l.NUMOCC

IBYSTD(I)-8 40 CONTINUE

Cl (3) OCCUPANT PARAtCTERSt

DO 45 N>l,NUroCC

READ (5.KFMT) INTLIMCN) .LBYSTD(N) . IHANDI (N).KNOUAY(N) ,XD(H),YO(N)

1 ,POPEN(N).PCLOSE(N)

K)CO(N)«XD(N) KYO(N)«YO(N)

1NITX0(N)>X0(N) IN1TY0(N)»V0(H)

45 CONTINUE

C

C •• E>CCUTE THE SIMULATION E>PERirtNT »*

C

C ITERATE FOR DESIRED NUMBER OF REPLICATIONS

DO 90 lII-l,NUt«EP

C INITIALIZE REPLICATION VARIABLES

DO 91 N*1,NUM0CC

NO(N)>KNO(N)

91 YO(N)>KYD(N)

C DO 92 NTNIS'l.NUMOCC

IFLAGCNTNISl'O NUMSTP(NTHIS)«0

lSCORE(NTHIS)«e

IBACK(NTHIS)>0 JTirt(NTHIS)-0

INTR(NTHIS)"0 INTNUMCNTWISl-O

ITYPE1(NTHIS)«0

ITYP£2(NTHIS)-0

92 IDPASS(NTHIS)«e

C

C ITERATE FOR DESIRED NU«ER OF TIFE FRAfCS

C DO 50 ITIfE-l.TOTIMt

C. DO 501 I>1.ND

501 ID0PEN(l,ITirC)>lD00R(I.4)

C

C ITERATE FOR DESIRED NUrCER OF OCCUPANTS

DO 60 tiTHIS-l.NUMDCC

IF (IFLAG(NTHIS).EO.l) GO TO 60

C INITALIZE OCCUPANT LOCATORS

XPRIOR(NTHIS)-XD(NTHIS) YPR10R(NTH1S)-YD(NTHIS)

I>ORCE(NTHIS,lTirE)*XO(NTHIS)

lYTRCECNTHIS. ITirE)-YO(NTNIS)

^(OB(NTHIS. IT1ME)*«KNTHIS)

YCBtNTHIS. ITlrt)-YO(NTHIS)

C DETERMINE UHICH SPACE THE OCCUPANT IS CURRENTLY OCCUPYING

H«e

15 N-N+1

IF (((>a.O(N).LT.XOCNTHIS)).AND.

1 (YLO(N).LT.YO(NTHIS))).AND.

2 ((>HI(N).GT.XO(NTHIS)).AND.

3 (YHI(N).GT.YO(NTHIS)))) GO TO 25

GO TO 20

25 IS-N

- GO TO 26 * 20 IF (N.LT.NSPACE) GO TO 15 IS-NSPACE

26 TOTEAR-NPOINT(IS)

C DETERMINE UHETHER THE OCCUPANT IS INTERRUPTED

CALL INTRPT ( ITIME.NTHIS. IHANDI. INT. IBYSTD. lEVAL.

1 XO.YO. IBAR.TOTBAR.>a.YT.NRGREE.>E.YE, lAGREE. 2 IRRND.P.MOV'E.XK.YK.K.L. IS. IGOALX. IGOALY. lENTER.

3 X, INTLIM,1NTR.INTNUM.PI2.PI0)

IF (INT.EO.l) GO TO 27

IF (INT.E0.2) GO TO 30

GO TO 31 C REMAIN-IN-PLACE INTERRUPTION

27 1TYPE1(NTHIS)-ITYPE1(NTHIS)+I

GO TO 70

C BACK-TRACK INTERRUPTION

30 CALL BACKUP ( IBACK. XO.YO. INITXO. INITYO.XDB. YOB,

1 ITIME.NTHIS.NEUXO.HEUYO. INTR.JTlttE)

I TYPE2 (NTH IS) • 1 7YPE2 (NTH IS) -M IF(INTR(NTH1S).E0.0) GO TO 31 GO TO 71

31 CONTINUE

IF (:3YSTD(HTHIS).E0.1) GO TO 70

C DETERMINE SOCIAL CONDITIONS SURROUNDING THE OCCUPANT

CALL GROUP (NTHIS.NUMOCC. IHANDI. KNOUAY.KOOCC.NHANDI.NKNOU.NAGREE.

1 lAGREE)

89
IF (NHRNDI.GT.O) CO TO 65

GO TO 6T

65 CALL BYSTNl) ( IBY5T5.HTM1S)

IF (IBYSTD(NTHIS).EO.I) CO TO 78

C DETERMINE MODE Or STATUS EVALUATION

67 IF (EVLOPT-I) 69,68,69

68 CALL EVAL8CX0.Y0,XT.YT.XE,YE.NTHIS.IACREE,ITir€,IEVAL.

I PTDIST.TDIST.PEDIST.EDIST, IS. IGOALX. ICOALY) GO TO 78

69 CALL EVAL20 (r«rTirC,r»;.X0.YD,XE.YE.NTNI8. lAGREE.

I IT1ME,C,IEVAL.T0TIME)

C DETERMINE LOCAL CROIJDING CONDITIONS SURROUNDING TNE OCCUPANT

70 CALL JAITED ( ITlrZ,NTHlS, IHANDI, INT. IBYSTD, lEVAL.

1 XD,YO, IBAR.TOTBAR,XT,YT,NAGREE,>E,VE, lAGREE, IRAHD. 2 P.MOVE,>OC,VX,K,IALLOU,NUMOCC,IENTER)

C GENERATE MO'/E PROBABILITIES

CALL ASSIGN ( ITirE,NTHIS, IHANDI, INT, IBYSTD, lEVAL.

1 XO,YO, IBAR,TOTBAR,XT,YT,NAGREE,XE,YE, lAGREE, 2 IRAND,P.MOVE,>«,VK,K,L, IS, IGOALX, IGOALY, lENTER.

3 X, IDOOR. POPEN, ND, MDOOR, PCLOSE)

CALL NELKY ( ITIME,NTHIS, IHANDI, INT. IBYSTD, lEVAL.

1 XO,YO, IBAR.TOTBAR,XT,YT,NAGREE,XE,YE, lAGREE. 2 IRAHD. P. MOVE. >«.YK.K.NEUXO,NEUYO>

C RECORD DOOR-PASSAGE. IF ONE OCCURRED

CALL PASSG (IDPASS, IDOOR. XO.VO.NTHIS.ND.NEUXO.NEUYO)

71 IF CRREPRT.EO.l) GO TO 72

GO TO 61 C PRINT MOVE PROBABILITY MATRIX. IF THIS OPTION IS SELECTED

72 CALL REPORT ( ITIME.NTHIS. IHANDI. INT. IBYSTD. lEVAL.

1 XO.YO. IBAR.TtiTBAR.XT.YT.NAGREE.XE.YE. lAGREE. 2 IRAND.P.MOVE.W.YK.K.NUMEXT.NUMOCC.TOTIME, INTLIM. 3 LBYSTD. KNOUAY. PTD 1ST, TD I ST. PED 1ST. ED 1ST, NEUXO. NEUVO. 4 EVLOPT. IDOOR, IDOPEN.ND.INTR)

C UPDATE OCCUPANT LOCATORS

61 CALL UPDATE (XO.YP.NTHIS.NELIXO.NEUYO) ISCORE(NTHIS)-ISCORE(NTHIS)+I

IF ((XO(NTHIS).EO.XE(KNOUAY)).AND.

I (YD(NTHIS).EQ.VE(KNOUAY))) CO TO 62

60 TO 66

62 1FLAG(NTHIS)>I IPS(NTHIS)»IDPASS(NTHIS)

GO TO 60 C UPDATE NUMBER OF STEPS TRAVERSED BY THE OCCUPANT

66 CALL STEPS (WRIOR.YPRIOR.XO.YO.NUMSTP.NTHIS)

66 CONTINUE

50 CONTINUE

C PRINT SUmARY TABLE. IF THIS OPTION IS SELECTED

IF (RREPRT.E0.2) CO TO 63

GO T0 64

C COrPUTE ESCAPE SCORES FOR ALL OCCUPANTS IN THE RUN

63 CALL XSCORE (TDTIfE. ISCORE.NUMOCC. SCORE) CALL SUmSY (INITXO.INITYO, INTLIM.LBYSTD. IHANDI, KNOUAY.POPEN.

1 PCLOSE. SCORE, NUMSTP, IPS. 1 1 l.NUrREP.NUMOCC.TOTirt.XO. YO.)C.YE.

2 TITLE)

IF (RREPT2.E0.1) GO TO 64

CO TO 90 64 CONTINUE

C PRINT OCCUPANT ftlVErENT RACES. IF THIS OPTION IS SELECTED

CALL TRACE UXTRCE. lYTRCE.NTHIS, ITIME.NUMOCC.TOTIfE)

C PRINT INTERRUPTION SUrtlARY TABLE. IF THIS OPTION IS SELECTED

CALL TOTALS ( IDPASS. ITYPEl. ITYPE2.NTHIS.NUM0CC)

90 CONTINUE

C

Cj INPUT FORimiNG

C100 FORMAT (5(I2.1X).2(M.1X).FI.0,IX,I2.1X.I2.2(IX.II))

101 FORMAT (20A4)

102 FORrpiT (2(I2.1X).I5.IX,I2.2(IX.F4.2))

103 FORMAT (20A4)

104 FORMAT (20A4) END

90
Hojatines GROUP, OTHERS, and AGREE

l-oop Occupant

Purpose This is a collection of subprograms which establishes the

social environment of occupants as they progress through

the simulated fire event. By calling upon the routines

OTHERS and AGREE, the GROUP package informs a given

occupant:

(1) whether any other occupants co-occupy the space with

him;

(2) whether any of the others in the space possess informa

tion currently unknown to him;

(3) whether any of the others in the space is Injured or otherwise in need of assistance; and

(4) whether all the occupants in the space are able to

agree upon an effective exit route.

Formulas (1) PSUM = 0.60 * SUM

where: PSUM = the minimum number of occupants who

must agree upon a single exit;

SUM = the total number of occupants impact"

ing the consensus process.

91
.W"'

Dctenlne whether

OCC. eharcs epace with othera

;

what Inforaatlpn

- la poaaesaed by the others, and whether all agree

on the best

exit

Subroutine GROUP

92
cC

C

c

c

C SUBROUTINE CROUP

C

C THE PURPOSE OF CROUP IS TO ESTABLISH AND UPDATE TNE SOCIAL ENVIRONTENT OF

C OCCUPANTS AS THEY PROGRESS THROUGH THE SIftILATED FIRE EVENT. C SUBROUTINE CROUP (NTHIS.NUMDCC. IHANDI.KNOUAY.tCOOCC.HHANDI.

-1 NKNOU.NAGREE.IACREE)

DIMENSION KNOUAY(20) C DETERMINE UHETHER THE OCCUPANT SHARES THE SPATIAL SUBDIVISION UITH OTHER

C OCCUPANTS. UHAT INFORMATION IS POSSESSED BY THE OTHERS, AND UHETHER ALL

C SUBDIVISION AGREE ON THE BEST EXIT

CALL OTHERS (NTHIS.NL'MOCC. IHANDI.KNOUAY.KOOCC.NHANDI.NKNOU)

IF (KNOL»AY(NTHIS).GT.0) CO TO 1 IF (KOOCC.EO.B) GO TO 993 CO TO 2

1 IF (KOOCC.EO.B) GO TO 999

IF (KXNOU.EO.B) CO TO 999

2 CALL AGREE (NTHIS.NUMOCC. IHANDI.KNOUAY.KOOCC.NHANDI,

1 HKNO'J.NAGREE.IAGREE) 999 RETURN END

93
Subroutine OTHERS

94
o

iMcord

niapber of

.othora wtio know beat way out

Subroutine OTHERS

95
cc

cc

c

C SUBROUTINE OTHERS

C

C THE PURPOSE OF OTHERS IS TO RECORD THE NUfBER OF OTHER OCCUPANTS IN THE

C SUBDIVISION. OTHERS ESTABLISHES SEPARATE RECORDS FOR THE NUMBER OF MOBILITY

C -IMPAIRED (HANDICAPPED) OTHERS. AND FOR THOSE KNOUING THE DAY OUT. c

* SUBROUTINE OTHERS (NTHIS.NUMOCC, IHANDI.KNOUAY.KOOCC.NHAHDI.

1 NKNOU) DIMENSION IHANDI(20).KNOUAY(20) C INITIALIZE COUNTERS

NKNOU’B

NHANDI-0

C SET FLAG

IF (NUMOCC.CT.l) CO TO J KOOCC-0

GO TO 999

1 KOOCC-I

C RECORD NUMBER OF MOBILITY- IMPAIRED OTHERS IN THE SUBDIVISION

DO 50 I*l.NUMOCC

IF (I.EQ.NTHIS) CO TO 50

IF (IHANDI(I).EQ.l) GO TO 51 GO TO 50

51 NKAMDI-NHAHDI+1

50 CONTINUE

C RECORD THE NUMBER OF OTHERS UHO KNOU THE BEST EXIT

DO 60 I-t.NUMIQCC

IF (I.EO.NTHIS) GO TO 60

IF (KNOUAYCD.GT.B) GO TO 61 GO TO 60

61 NKHOU'NKNOU+1

60 CONTINUE

999 RETURN

END

96
Subroutine AGREE

97
Dateraine

consensus

axle of choice

Subroutine AGREE

98
SUBROUTUC MREE

THE PURPOSE OF RCTEE IS TO BETERMIHE P CONSENSUS-EXIT-OF-CHOICE PMONC MJ.

OCCUPANTS OF A Sl\^ SPATIAL SUBDIVISION

SUBROUTINE AGREE (NTHIS.NUMOCC, IHANDI.KNOUAY.KOOCC.

1 NHANDI.NKNOU.NAGREE.IAGREE)

DirENSlON KN0UAY(28> C INITIALIZE EXIT COUNTERS KONE«e

KTUD-e

KZERO’B

C RECORD HUPBERS OF OCCUPANTS WHO ADVOCATE EACH EXIT

DO SB i>i,Nuncc

IF (KNOUAY(I).EO.l) 60 TO SI

IF (KN0UAY(I).E0.2) 60 TO S2

IF (FNOMYCD.EO.B) 60 TO S3

60 TO 50

51 KONE'KONE'fl 60 TO 56 52 KTUO'KTUCHl GO TO 50 53 KZERO'KZERtKI

56 CONTINUE

C CONVERT COUNTS TO FLOATING POINT NUTBERS

ONE'KONE

TUO'KTUO ZERO-KZERO C DETERMINE CONSENSUS EXIT OF CHOICE SUM-ONE+TUO+ZERO

PSUM*.GC>KSUM

IF ((0NE.GE.PSUM>.0R.nU0.6E.PSUM)> 60 TO 1 NAGREE'B

lAGREE>a

60 TO 2

1 NRGREE'l

IF (ONE.GE.PSUM) GO TO 3

IAGRE£«2

' GO TO 2 3 IAGREE-1 2 RETURN END

99
Routine KPOSS

Lpop Occupant

Purpose As an occupant moves through a bounded environment, motion in

certain directions may be possible, while in others it may be

constrained. When he arrives at a particular point in space,

the individual begins looking ahead and scanning possibilities for the next move decision. He requires a perceptual

apparatus which permits him to distinguish open paths from

those constrained by walls or other physical barriers. As

Subroutine GROUP provides the occupant with means of perceiving the social environment. Subroutine KPOSS provides "eyes"

fhtough which to discern his immediate physical environment.

Namely, as the occupant scans each potential move alternative,

k, he determines which are physically possible to attain, and

which are blocked. Blocking by architectural features (e.g.,

walls) is Illustrated in Figure A. 2. KPOSS also responds to

inputs from Subroutine JAMMED. A spatial location which is

crowded beyond an occupant's level of acceptance will be

tteated as though it was blocked off by an inanimate physical

bar^rler; the individual will eliminate that alternative, k,

from the array of possibilities available at time frame t.

Formulas n/f

100
6 person-occupiable location

possible move

itrpossible move (i.e., blocked)

FIGURi A. 2

currently occupied location

Possible vs. Impossible Spatial Movements

101
4a Subroutine KPOSS

102
Subroutine KPOSS

103
SUBROUTINE KPOSS

C

cz

c

c

cc

C THE PURPOSE OF KPOSS IS TO SMN THE OCCUPANT'S irPEDIATE PHYSICAL

C ENVIRONrtNT. AND TO DETERMINE UWETHER A MOVE ALONG ANY DIRECTION IS C RENDERED IMPOSSIBLE BECAUSE OF EITNER A PHYSICAL CONSTRAINT (UALL) OR

C OVERCROUDING BY OTHER OCCUPANTS

C SUBROUTINE KPOSS < ITirE.NTHlS. IHANDI. IHT. IBYSTD, lEVAL.

1 XO. YO. IBAR,TOTBAR.XT.YT,NAGREE.>C, YE, lAGREE. IRAND. 2 P.MOVE.MC.YK.K.L. IS. IGOALX. IGOALY. lENTER) DIMENSION IBAR (20,75,2) . lENTERO)

INTEGER XO(20).YOt20),)fl(.YK.TOTOAR C CONVERT SPATIAL POINT FROM K VALUE TO X.Y COORDINATES

CALL KTOXY ( ITIME.NTHIS. IHANDI. INT, IBYSTD. lEVAL.

1 XO.YO. IBAR,TOTBAR.XT,YT.NAGREE.>E.YE. lAGREE. IRAND.

. 2 P.MOVE,>«,-YK.K) C DETERMINE UHETHER THE MOVE ALTERNATIVE UNDER REVIEU IS POSSIBLE.

C I.E.. IS NOT BLOCKED BY A UALL. OR DUE TO OVERCROUDING

I CROSS • ( XO (NTH I S ) +»0 /2

JCROSS ( YO ( NTH I S ) +YK) /2

i>a j«i

1 i-i+i

IF (I.GT.TOTBAR) CO TO 5

IF (IBAR(IS,I,J).EO.ICROSS) GO TO 2 GO TO I

2 J*J+l

IF (IBAR(IS.l.J).EQ.JCROSS) GO TO 4

J-J-I GO TO I 4 CONTINUE

C THE MOVE ALTERNATIVE UNDER REVIEU IS NOT POSSIBLE. .. IT IS BLOCKED BY A UALL

C CR BECAUSE OF OVERCROUDING L-0 GO TO 6

5 L-I

IF (lENTER(K).EO.B) GO TO 4

6 RETURN END

104
Routine KTOXY

Lyop Occupant

Purpose Two spatial notations systems are employed by BFIRES:

The orthogonal x,y coordinate system keeps track of the

spatial locations of wall and door elements, and occupants.

The k-grid system is used in connection with the move

alternative selection process. The k-grid may be thought of

in terms of a compass dial, with eight vectors radiating

outward from a central point (note Figure A. 2), This point

denotes the current location of occupant n, while the vectors

represent potential movement paths, A ninth vector also

exists to denote the condition of remaining-in-place. Each

vector on the k-grid is designated by a number (1 through 9).

As an occupant moves about through space, he "carries” his

personal k-grid along with him, such that the central point

(k=5) always coincides with his current location. Execution

of the various subroutines often requires transformations

between the x,y and k-grids. This is accomplished by

Subroutine KTOXY ( "k to x,y").

Formulas

*~i— (1> general form for computing an x,y coordinate when

k-number is known;

XK = XO + c YK = YO + c

Where;

XK; YK = X and y coordinates of a new point which

would be reached if vector k is selected;

XO, YO = current x and y coordinates describing

occupant^' s location;

c = constant required, to produce locational shift.

105
<

106
Subroutine KT03CY
SUBROUTINE KTOW

C

c

c

c

c

C TME PURPOSE OF KTOXY (*K TO X,Y*) IS TO CONVERT SPflTIftL LOCfiTIONS FROM

C K-GRID DESIGNATIONS TO X.Y COORDINATES

C SUBROUTINE tOOXYC ITIME.NTHIS. IHANDI. INT. IBYSTD. lEVAL.

1 XO.YO. IBAR.TOTEAR.XT.YT.NAGREE.XE.YE. lAGREE. IRAND. 2 P.M0VE,«<.YK,K)

INTEGER XO(20).TO(20).>«.Y)(

C FOR THE VALUE OF K UNDER REVIEU, COMPUTE NEU X.Y COORDINATES OOC.VK)

C AS A FUNCTION OF THE EXISTING ONES (XO.YO) GO TO (1.2. 3. 4.5. 6. 7.6.9).

K

1 )0C«X0(NTHIS)-2 YK-Y0(NTHIS)-2

GO TO 10 2 XK-X0(NTHIS)-2

YK-YO(NTHIS) GO TO 10 3 XK-XD(NTHIS)-2

YK-Y0(NTHIS)+2

CO TO 10 4 )«-XO(NTHlS) YK-Y0(NTHIS)-2

GO TO 10 5 >«*XO(NTHIS)

YK-YO(NTHIS) GO TO 10 6 )«-XO(NTHlS) YK»Y0(NTHIS)+2

CO TO 10 7 >«-X0(NTHIS)+2

YK-Y0(NTHIS)-2

GO TO 10 6 >»:-X0(NTHlS)+2 YK-YO(NTHIS) CO TO to

9 >S(-XD(NTHIS)+2 YK*Y0(NTHIS)+2

le RETURN

END

108
Routine JAMMED

Loop Occupant

Purpose As occupants move about during a simulated fire, the

population density of the different spatial locations varies.

Some mechanism is necessary to enable an occupant to gather

information about the density, or degree of physical crowding,

of locations he may wish to enter. JAMMED satisfies this

need. As an occupant looks ahead and scans the alternative

target locations available to him, he counts the number of

other individuals already occupying each. If, for any given

alternative location, this number is greater than the preset

crowding tolerance, he rejects that alternative from his array

of movement choices.

Formulas n/a

109
Subroutine JAMMED

no
0

Subroutine JAMMED

111
SUBROUTINE JAfTED

C

c

cc

c

cc

C THE PURPOSE OF JAMMED IS TO ENABLE THE OCCUPANT TO GATHER INFORMATION ABOUT

C THE DEGREE OF 'CRO'JDING* OF LOCATIONS HE MAY UISH TO ENTER... AS THE

C OCCUPANT SCANS THE ALTERNATIVE TARGET LOCATIONS AVAILABLE TO HIM. HE

C DETERMINES UHETHER EACH IS NON-ENTERABLE DUE TO OVERCROUD INC C SUBROUTINE JATtED (ITlrE.NTHIS. IHANDI, INT. IBYSTD. lEVAL.

1 XO.YO. IBAR.TOTBAR.XT.YT.NAGREE.XE.YE. lAGREE. IRAND. 2 P.MOVE.XK.YK.K, lALLOU.NUMOCC. lENTER) INTEGER XO(2O).YO(20).XK.YK,XE,YE DIMENSION JAMOI.IENTERO)

C SCAN EACH MOVE ALTERNATIVE. AND RECORD UHETHER EACH NEU LOCATION IS FILLED

C TO CAPACITY

DO 100 K*1.9

CALL KTOXY ( ITIME.NTHIS, IHANDI . INT. IBYSTD, lEVAL.

1 XO.YO. IBAR.TOTBAR.XT.YT.NAGREE.XE.YE. lAGREE, IRAND. 2 P.MOVE.W.YK.K)

JAMCIO-0

DO 200 N-l.NUMOCC

IF (N.EQ.NTHIS) GO TO 200

IF ((XO(N).EO.XK).AND.(YO(N).EQ.YK)) GO TO I GO TO 200

1 JAM(K)-JAM(K)+I

200 CONTINUE

IF <(XK.EO.XE) .AND.(YK.EQ.YE)) GO TO 2

IF (JAM(K).LT.IALLOU) GO TO 2 GO TO 3 2 1ENTER(K)«1 GO TO 100

3 IENTER(K)-0

100 CONTINUE RETURN

END

112
Routine

Purpose

Potinulas

EQUALZ

Occupant

EQUALZ is one of the biasing routines available to ASSIGN.

The function of EQUALZ is to satisfy the condition of no bias , that is, the situation in which the probability

values of available move alternatives are equalized.

An occupant enters a state of confusion whenever he is

mobile and uninterrupted, makes a negative safety status

evaluation, and is unable to discern an effective egress route.

He will remain in this condition until he;

(1) makes a positive safety status evaluation;

(2) learns of an effective route; or

(3) decides to enter the backtracking interruption mode.

(1) P(K) = l.O/NUMPOS

Where;

P(K) = the probability of selecting the kth move

alternative;

NUMPOS = the total number of possible alternatives

available.

113
START

Separate

possible moves _ from those which are not possible

Subroutine EQUALZ

114
Subroutine EQUALZ

115
c

c

c

c

c

C SUBROUTINE EOUM.Z

C

C THE PURPOSE OF EOUflLZ IS TO SftTISFY THE CONDITION OF MO DECISION BIAS

C (INDECISION), THAT IS. THE CONDITION UNDER UHICH THE PROBABILITY VALUES OF

C AVAILABLE HOVE ALTERNATIVES ARE ALL EQUALIZED

C SUBROUTINE EOUALZ( ITITE.NTHIS. IHANDI. INT. IBYSTD. lEVAL,

1 XD, YD. IBAR.TOTBAR.XT.YT.NAGREE.XE.YE. lAGREE. 2 IRAND.P.ItIVE.)*. YK.K.L. IS, IGOALX, ICOALY, lENTER) INTEGER XO(2O).YlI(20).»<,YK DIMENSION irfOSS (9). P (9) Nurpos-0

C IDENTIFY ALL POSSIBLE MOVE ALTERNATIVES

DO 1 K«1.9

CALL KPOSS (ITIME.NTHIS. IHANDI, INT. IBYSTD. lEVAL,

1 XO, YO, IBAR.TOTBAR,XT.YT,NAGREE.>€,VE, lAGREE. 2 IR^ND.P.MOVE.XK.YK.K.L. IS, IGOALX. IGOALY. lENTER)

IF (L.EQ.l) GO TO 2 GO TO 3 2 NUMPOS-NUTPOS+1

irPOSS(K)-B

GO TO I 3 irPOSSOO-l

1 CONTINUE

C ESTABLISH MOVE PROBABILITY VALUES FOR ALL POSSIBLE MOVE ALTERNATIVES.

C SUCH THAT ALL VALUES ARE EQUAL

DO 4 K*1.9

IF (irPOSS(IO.EO.l) GO TO 5 P(K)-1.0/FLOAT(NUrPOS)

GO TO 4

5 P(K)-3.0 4 CONTINUE RETURN

END

116
Routine

I

Purpose

Formules

T'-T

TEXAS

Occupant

Subroutine TEXAS effectuates "threat evasion" movement

behavior. Whenever this biasing routine is assigned, it

estabXishes move seXection probabiXity vaXues which "favor"

moves that maximize the occupant's distance from the fire

threat (threatened exit). TEXAS is assigned if the

occupant

(1) is mobile and uninterrupted during the current time frame;

(2) is operating under a positive perception of his current

safety status;

(3) has no exit route in mind; and

(4) knows the location of the threat.

(1) DXSTj^ * SQRT ((XT-XK)^ + (YT-YK)^)

(2) P(K) = DXST (K)/TOTDST

where:

DXST^ = linear distance between an alternative

location and the threat location;

XYjYT = x,y coordinates of the threat location;

XKjYK * x,y coordinates of the kth alternative

location;

P(K) = probability of selecting the kth alternative;

TOTDST = 9

E DXSTj^

117
Subroutine TBIAS

118
Subroutine TBIAS
c

c

cc

c

c

c

c

c

cc

S'-CROUTINE TBlftS

THE PL'SPOSE OF TBlflS IS TO EFFECTUP7E ‘THREAT EVASION* MOVEMENT BEHAVIOR. UHENEVER TBIAS IS ASSIGNED, MOVE PROBABILITY VALUES ARE ESTABLISHED IN SUCH

A L'AY AS TO ‘FAVOR* MOVES UHICH MAXIMIZE THE OCCUPANT'S DISTANCE FROM

THREATENING STItULI

C SUBROUTINE TBIAS (ITIFE.NTHIS. IHANDI, INT. IBYSTD, lEVAL.

1 XO.YO, IBAR,TOTBAR.XT.YT,NAGREE.XE,YE. lAGREE.

1 IRS!!D.P,MOVE,«<.YK,K.L. IS. IGOALX, IGOALY, lENTER) INTEGER XO(20).YO(20).XT.YT,»<,YK

DIMENSION M(9).DISTO).P(9)

TOTD3T*0.

C IDENTIFY ALL POSSIBLE MOVE ALTERNATIVES

DO 10 K-1.9

Cr.LL KP0S3 (ITIME.NTHIS.IHANDI.IMT.IBYSTD.IEVAL,

1 MO, YC, lEAR.TOTEAR.XT.YT.NAGREE.XE.'iE. lAGREE.

2 IRAND.P.MJ'vE.XK.YK.K.L, IS. IGOALX, IGOALY, lENTER)

C FOR EACH POSSIBLE MOVE, COMPUTE THE DISTANCE FROM THE NEU LOCATION TO THE

C THREAT

IF (L.EQ.n GO TO I • MClO-l

GO TO 10

1 M(K)-0

D IST(K) SORT(FLOAT( (XT-MO not<2+( YT-YIO HOC) ) TOTDST*TOTDST+DIST(K)

10 CONTINUE

c

C: FpR EACH POSSIBLE MOVE. COMPUTE THE MOVE-PROB.. P(K):

C

C FOR EACH POSSIBLE MOVE. COMPUTE THE PROBABILITY OF SELECTION. POO

DO 15 K-1,9

IF CM(K),EO.0) GO TO 2 P(K)-0,

CO TO 15 2 PCK)-DIST(K)/TOTDST

15 CONTINUE RETURN

END

120
Rpyitlne

Loop

Purpose

PormuLas mii^l 1,1 li n

i» .p

EBIAS

Occupant

For all move alternatives available to an occupant at a^ given

point in time, Subroutine EBIAS weights move selection

probabilities to favor moves which minimize the occupant's

distance from an exit goal point. An occupant’s decision

making strategy is routed through Subroutine EBIAS if he:

(1) is mobile and uninterrupted during the current time frame;

(2) is operating under a positive perception of his current

safety status; and

(3)

has a specific egress route in mind,

(1) DIST(K) = SQRT((IGOALX - XK)^ + (IGOALY - YK)^)

(2) P(K) » A(K)/SUMA

(3) A(K) = TOTDST/DIST(K)

(4) P(K)* = l.O/ZERO

-Where;

DIST(K) * linear distance from new location designated

by k, to the agreed-upon exit from space^;

IGOALX , IGOALY = x,y coordinates of the agreed-upon

exit from space^;

XKjYK = x,y coordinates of the spatial location

denoted by k;

P(K) = the probability of selecting the kth move

alternative, under the condition that not

more than one alternative leads directly

through an exit from space^, during t;

TOTDST = 9

Z DIST(K)

k=l

SUMA =* 9

Z A(K)

k=l

121
P(K)* = the probability of selecting an alternative

which leads directly through an exit from

space^^, only under one condition that more

than one alternative leads through such an

exit;

ZERO = the total number of alternatives leading

directly through an exit from space^

during t.

122
Subroutine EBIAS

123
For each possible move K, ccmpute the probability of selection, P(K)

SUMA>SaMA-tA(K)

Subroutine EBIAS

124
Subroutine EBIAS

Nl/

ZERO - 0.0

125
o
SL'3R0UTINE EBIftS

C

CC

cc

cc

C THE PURPOSE OF EBlflS IS TO EFFECTUATE GOAL SEEKING nOVEMENT BEHAVIOR.

C EBIAS IIEIGHTS nO'i'E SELECTION PROBABILITIES TO ’FAVOR' MOVES UHICH

C MINIMIZE THE OCCUPANT'S DISTANCE TO AN EXIT GOAL

C SUBROUTINE EBIASCITIME.NTHIS. IHANDI. INT. IBYSTD. lEVftL.

1 XO.YO. IBAR.TOTBAR.XT.YT.NAGREE.JC.YE. lAGREE.

2 IRAND.P.MOVE.XK, YK.K.L. IS. IGOALX. IGOALY. lEHTER) INTEGER XO(20).YO<20).>E(10).YE(10).>«.YIC DIMENSION M(9),DIST(9).A(9).P(9)

DIMENSION I GOALX (20 . I 0 ) . I GOALY (20.10) TDTDST-0.

SUMA-0. C IDENTIFY ALL POSSIBLE MOVE ALTERNATIVES

DO 10 K-1.9

CALL KPOSS (ITIME.NTHIS. IHANDI. INT.IBYSTD.IEVAL.

1 XO.YO. IBAR.TDTBAR.XT.YT.NAGREE.>€.YE. lAGREE.

2 IRAND.P.MOVE.XK. YK.K.L. IS. IGOALX. IGOALY. lENTER) C FOR EACH POSSIBLE rOVE. COMPUTE TNE DISTANCE FROM THE NEU LOCATION TO THE

C AGREED-UPON-EXIT

IF (L.EQ.l) GO TO I M(K)-1 GO TO 10

1 M(K)>0

DIST(K) -SORT(FLOAT( ( IGOALX( IS. IAGREE)-MO*»2-*-

I (IGOALYdS. IAGREE)-YK)»a2)) TOTDST-TOTDST+DIST(K)

10 CONTINUE

C FOR EACH POSSIBLE MOVE. COMPUTE THE PROBABILITY OF SELECTION. P(K) DO 15 K*1.9

IF (M(K).EQ.l) SO TO IS

IF (D1ST(K).EQ.0.) GO TO IS A(K)*T0TDSTXDIST(K)

SUMA*SUMA-KI(K>

IS CONTINUE C

K«0 2 K*K+I

IF (M(K).EQ.I) GO TO 3

IF (D1ST(K).EQ.0.) CO TO 5

P(K)-A(K)y'SUMA GO TO 4

3 P(K)-0. 4 IF (K.LT.9) GO TO 2 RETURN

5 ZERO-0.

DO 20 K-1.9

1F(M(K).EQ.1) GO TO 20

IF (DIST (K}.EQ.0.) GO TO 6 GO TO 20

6 ZERO-ZERO+l.

20 eONTINUE

DO 25 K-1.9

IF (M(K).EQ.l) GO TO 707

IF (DIST(K).EO.B.) GO TO 7 707 P(K)-0.0

GO TO 25

7 P(K)-1./ZER0

25 CONTINUE

RETURN

END

127
Routines DOORS 1 and D00RS2

Loop Occupant

Purpose As a part of its move selection function, subroutine ASSIGN

controls the manipulation of doors by occupants. For example,

when an individual encounters a closed door, there is some probability he will open it, and some chance that he will

not. If he chooses not to open the door, the through-door

move alternative is deleted, and the probility values of

remaining alternatives are adjusted so as to maintain a sum

of unity. This function is controlled by Subroutine DOORSl.

Moreover, if the occupant indeed passes through an open door,

he may or may not close it behind him. Subroutine D00RS2

controls this behavior.

Formulas (1) SUM = SUM + P(K)

(2) DIFF =» 1.0 - SUM

(3) SHARE » DIFF/NPOSS

(4) P(K)* * P(K) + SHARE

Where;

SUM cvunulative sum of probability values for

all k. vectors;

P(K) = likelihood of selecting move k;

Share = proportion of cumulative probility which

must be redistributed under the condition

that the through-door alternative has been

deleted;

NPOSS ® total number of possible moves available

during t;

P(K)* = new value of P(K), after cumulative

probability has been redistributed.

128
129
Record door

at appropriate move alternative
YES

NO

CALL KPOSS

NO

(

YES

If

DIFF « 1.0 - SUM /

N

SHAKE - D]CFF/NPOSS

Subroutine DOORS 1

NPOSS « NPOSS 1

SUM • SUM + P'(K)

131
K - 1,1

i ^

. aOL KPOSS

Subroutine DOORS

1
ononnnono SUBROUTINE DOORS

1

TWE PURPOSE OF DOORSl IS TO DETERMINE UHETWER THE OCCUPANT UILL OPEN R aOSED DOOR WHICH IS RLONO AN ALTERNATIVE MOVEFENT PATH AVAILABLE TO HIM...

C OPENING THE DOOR DOES NOT GUARANTEE THAT THE OCCUPANT UILL PASS THROUGH IT

C ...IF HE DECIDES TO LEAVE THE DOOR CLOSED. HO'JEVER. THE THRU-DOOR MOVE

C ALTERNATIVE UILL BE CANCELED, AND THE rOVE PROBABILITIES UILL BE

C RECOrPUTED

C SUBROUTINE DOORSl (ITirt.NTHIS. IHANDI. INT. IBYSTD. lEVAL.

1 )CO,yO. IBAR.TOTBAR.XT.YT.NPGREE.JS.TE. lAGREE.

2 IRAND.P,MOVE.>«,YK,K,L, IS. IGDALX. ICOALY, lENTER. 3 X, IDOOR.POPEN.ND.MDOOR.PCLOSE. IX) DirENSION PCS). IDOOR<30,4),POPENC20)

INTEGER >O(20).YOC20).)«,'tX,TOTBAR

C DETERMINE LHETHER ANY MOVE ALTERNATIVE REQUIRES PASSING THROUGH A DOOR

K*0

5 K«K+1

6 CALL KTDXY (ITirE.NTHIS. IHANDI. INT. IBYSTD. lEVAL. . 1 X0.Y0.I8AR.T0TBAR,>a.YT.NRGREE.XE,YE. lAGREE.

2 IRAND.P.MOVE.)«.YK.K)

I CROSS •( XD ( NTH 1 S) *•>«) /2 JCROSS • ( YO (NTH IS) +YK) /2

I«0 J-0

J-I

3 I-I+!

IF (I.GT.ND) GO TO I IF (IDOOR(I.J).EQ.ICROSS) GO TO 2

GO TO 3 2 J-J+1

IF (IDOOR(l.J).EQ. JCROSS) GO TO 4

J-J-1

GO TO 3

1 MDOOR-0

IF (K.EQ.9) GO TO 999

GO TO 5

C RECORD DOOR AT APPROPRIATE MOVE ALTERNATIVE 4 IX1

MDOOS-K

C IF DOOR IS IN THE OPEN POSITION (IDOOR(I.4)-l)). RETURN. . .OTHERUISE.

C DETERMINE UHETHER THE OCCUPANT OPENS THE DOOR

IF (lDOOR(1.4).EQ.l) GO TO 999 CALL RANDOM (ITIFE.NTHIS. IHANDI. INT. IBYSTD. lEVAL.

1 XO.YO. IBAR.TDTBAR.XT.YT.NAGREE.XE.YE, lAGREE. 2 IRAND.P.ftDVE,)*. YK.K.L. IS, IGOALX. IGOALY. lENTER.X)

IF (X) 55.5S.5S

55 X-X*(-I)

5S IF (X.LT.POPEN(HTHIS)) GO TO S

C THE OCCUPANT OPENS THE DOOR

IDOOR(I.4)-l RETURN

GO TO 999

C THE OCCUPANT LEAVES THE DOOR CLOSED

5 P(MDOOR)-0.0

C THE DOOR HAS BEEN LEFT CLOSED. . .THIS MOVE ALTERNATIVE IS NO LONGER

C APPLICASLE...RECOrPUTE MOVE PROBABILITIES FOR THE REMAINING MOVE

C ALTERNATIVES

K-0 SUM-0.0

NPOSS-0 7 K-K+1

IF (K.GT.9) GO TO 9 CALL KPOSS (ITirS.NTHIS. IHANDI. INT.IBYSTD.IEVAL.

1 XO.YO. IBAR.TOTBAR.XT.YT.NAGREE.XE.YE. lAGREE.

2 IRAND.P.MOVE.XK.YK.K.L, IS. IGOALX. IGOALY, lENTER)

IF (L.EO.I) GO TO B GO TO 7 8 NPOSS-N“OSS+l

SUI1-SUM+P(K) GO TO 7 9 DIFF-I. 0-SUM

SHA°E'DIFF/FLOAT(NPOSS)

. DO 25 (C-I.9 CALL KPOSS (ITIME.NTHIS. IHANDI, INT, IBYSTD. lEVAL.

1 -XO.YO. IBAR,TOTBAR.)a,YT,NAGREE.XE.YE, lAGREE, 2 lF,AND.P,MOVE,>a<,YK.K,L. IS, IGOALX, IGOALY. lENTER)

IF (L.EO.I) GO TO 10 GO TO 25

10 P(K)-P(K)+SHARE

25 CONTINUE

999 RETURN

END

133
134 I
SU2S0UT1NE D00RS2

C

c

cc

c

cc

C TKc PU.’^POSE OF D00PS2 IS TO CETERniNS WHETHER THE OCCUPPNT CLOSES ft 800R

C BEHIND HIM. ONCE HE HftS PftSSED THROUGH (ONLY ftPPLlCfiBLE FOR THE CftSE OF

C MftNUALLY-OPERflTED POORS)

C SUBROUTINE D00RS2 ( ITIME.NTHIS. IHftNDI. INT, IBYSTD. lEVftL,

1 XO.YO. ISflR.TOTBftR.XT.YT,NfiGREE,XE,YE. IftGREE. 2 IRftND,P,MOVE.)«.YK,K,L. IS, IGOflLX. IGOftLY. lENTER.

3 X, IDOOR.POPEN.ND.tlDOOR.PCLOSE.IX) DIMENSION I DOOR (30 . 4) , PCLOSE (20)

IF (MDOOS.EQ.0) GO TO 999

IF (MOVE.EO.MDOOR) GO TO I TO 999

C PET 'MINE LWETHER THE DOOR IS OF THE MftNUftLLY-OPERftTINC TYPE. I.E.,

C 1OOUR(IX.3)«0

1 IF (IDOOR(IX.3).Ea.0) GO TO 2

CO TO 999

C DETERMINE UHETHER THE OCCUPANT CLOSES THE DOOR AFTER PASSING THROUGH.

C IN WHICH CftSE. IDOOR(IX,4) IS RESET TO 0. DENOTING THE CLOSED POSITION

2 CALL RANDOM ( ITIME.NTHIS. IHANDI. INT. IBYSTD, lEVAL.

1 XO.YO. IBftR.TDTBAR.XT.YT.NAGREE.>€.YE. lAGREE. 2 IRAND.P.MDVE.)*. YK.K.L. IS. IGOALX. IGOALY.

3 lENTER.X)

IF (X) S5.S6.S6

55 X-X»(-l)

56 IF (X.LT.PCLDSE(NTHIS)) GO TO 999

I DOOR (IX. 4) *0 999 RETURN

END

135
Routines EVAL8 and EVAL 20

Loop Occupant

Purpose The direction of move probability biasing frequently

depends upon an occupant's current evaluation of his own safety status (his spatial location with respect to the

locations of the exit goal and the threat, if these are known to him). Evaluations may be positive or negative: A

positive evaluation results whenever an occupant perceives

his status to have improved between time t-1 and t. BFIRES

provides two user-called options for the evaluation of

safety status; EVAL8 and EVAL20.

EVAL8 constructs evaluation outcomes purely on the bases

of straight-line distance measurements between an occupant's

current location and the locations of threats and exits.

A positive evaluation results whenever the occupant's perceive status at t time is better than that at time t-1

(i.e. , he is nearer to an exit goal, and/or farther from

the threat).

EVAL20 on the other hand, evaluates egress progress relative to the total elapsed time an occupant has spent in the

threatening environment. A move in a seemingly threatening

direction may not be perceived as negative, if the occupant

thinks (on the whole) he still has an ample amount of time

left to escape safely.

136
Formulas EVAL8

(1) TDIST =« SQRT ((XO-XT)^ + (YO-YT)^)

(2) PTDIST = TDIST

(3) TCHANG = TDIST - PTDIST

(4) EDIST = EDIST

(5) PEDIST = EDIST

(6) ECHANG = EDIST - PEDIST

Where:

TDIST ® distance between occupant^ and the threat;

XOjYO = x,y coordinates of occupant^ *s current

location;

XT,YT = x,y coordinates of the threat location;

PTDIST = distance between occupant^^ and the threat

at time frame t-1;

TCHANG = change in distance between occupant^ and

the threat, between time frames t-1

and t;

EDIST =* distance between occupant^^^ and the agreedupon exit from space^^;

IGOALX,IGOALY =» x,y coordinates of the agreed-upon

exit from space^;

PEDIST - the distance between occupant^ at the

agreed-upon exit from space^, at time

frame t-1;

EXCHANG = change in distance between occupant^ and

the agreed-upon exit from space^, between

time frames t-1 and t.

137
Formulas EVAL20:

(1) TEST = SQRT((XOXE)^ + (YO-YE)^)

(2) TDIST = TTIME - TIME

(3) TDIST* = TTIME » MXTIME

(4) QDIST = SQRT ((XO-XT)^ + (YO-YT)^)

(5) TDIST**=TIME

Where:

TEST = distance between occupant^ 's current

location and the agreed”upon exit

from floor;

XOjYO = x,y coordinates of occupant^ 's current location;

XEjYE ® x,y coordinates of agreed-upon exit

from the floor;

TDIST = time distance factor with respect to

the exit location, under the condition that the elapsed time is greater

than the critical time;

TTIME = total number of time frames in the

event;

Time = current time frame (i.e., elapsed

time )

;

TDIST* = time distance factor with respect

to the exit location under the con dition that the elapsed time is

less than the critical time;

MXTIME = critical time;

QDIST distance between occupant^ 's current

location and threat location;

XTsYT = x,y coordinates of the threat location;

TDIST** = time distance factor with respect

to the threat location, under the

condition that the elapsed time is

less than the critical times

138
^

START

TDIST - SQRT( (}(D(NTOIS)-

XT) ( YO (UraiS ) -YT) ^

)

)

Determine Occ. 's present distance

from the threat

(if kncwn to him)

,

and compute change

since last move

Subroutine EVAL8

139
140
PTDIST(MTHIS) - TDISZ

PEDIST(NTHIS) “ EDISl

Subroutine EVAL8
SUBROUTINE EVRL8

t.C

c

c

c

cc

C THE PURPOSE OF EVBLB IS TO ENRBLE THE OCCUPPNT TO PROCESS DISTANCE

C INFORr«TION. AND THEREBY DETERMINE HIS CURRENT 'SAFETY STATUS EVAL8

C CONDUCTS STATUS EVALUATIONS PURELY ON THE BASIS OF STRAIGHT-LINE DISTANCE

C rtASUREFENTS BETIEEN THE OCCUPANT'S CURRENT LOCATION. AND THE LOCATIONS OF

C THREATS AND EXITS... A POSITIVE STATUS EVALUATION RESULTS LHENEVER THE

C OCCUPANT'S PERCEIVED STATUS AT TirE T IS 'BETTER' THAN IT UAS AT TIME T-1.. C OTHERUISE. HIS EVALUATION IS NEGATIVE

C SUBROUTINE EVAL8 (XD. YO.XT.YT.XE.YE.NTHIS.

I lAGREE. ITKE. lEVAL.PTDIST.TDIST.PEDIST.

1 EDIST. IS.IGOALX. IGOALY) INTEGER XO(20).YO(2B),>E(10).YEn0).XT.YT

DirENSION PTDIST<20) . IGOALXC20. 10) . IGOALY(20. IB) DirENSION PEDISTC20)

C DETERMINE THE OCCUPANT'S PRESENT DISTANCE FROM THE THREAT (IF KNOUN TO HIM) C AND COrPUTE CHANGE SINCE LAST MOVE

IF ((XT.GT.0).AND.(YT.GT.0)) GO TO I IF (IAGREE.CT.0) GO TO 2

GO TO 6

1 TDIST-SQRT(FLOAT((XO(NTHIS)-XT)«»2'«-

1 ('rO(NTHIS)-YT)»=«2))

IF (ITIIE.GT.l) GO TO SB PTDIST(NTHIS)-TDIST

SB TCHAMG*TDIST-PTDIST(NTHIS)

IF (lAGREE.GT.B) GO TO 2

IF (TCHRNG.GE.0.) GO TO S

GO TO 6

C DETERMINE THE XCUPANT'S PRESENT DISTANCE FROM THE BEST EXIT. AND COrPUTE

C CHANGE SINCE LAST MOVE

2 EDIST-SQRT(FLORT((XO<NTHIS)-IGOALX(IS. IAGREE))**2

I -KYOCNTHISI-IGOALYCIS.IAGREEIIWC))

IF (ITirE.GT. I) GO TO 5S FEDIST(NTHIS) -EDIST

55 ECHANG-EDIST-PEDIST(NTHIS)

C RECORD CURRENT STATUS EVALUATION, lEVAL-I (POSITIVE). IEVAL-0 (NEGATIVE)

IE ((XT.GT.B).AND.(YT.GT.a)) GO TO 3

IF (ECHANG.LE.0.) GO TO S

GO TO 6 3 IF ((TCHANG.GE.0.). AND. (ECHANG.LE.0.)) GO TO 5

GO TO 6

5 IEVAL-1 GO TO 7 e IEVAL-0 C UPDATE VALUES OF PTDIST AND PEDIST FOR THE NE)a CYCLE

7 PTDIST(NTHIS)-TDIST

PEDIST(NTHIS)-EDIST

RETURN

END

142
•TMCT 3

143
Test for threat- penalty

QTEST » SCBT ( (»D (NTHIS ) -XT) ‘

+yO(JITHIS)-YT)^)

Record Occ . '

status ev

evaluation:

lEVAL-l: Positive

IEVALbO: Negative

Subroutine EVAL20

144
SUBPOLiTlNs EVnL20

C

C

C

c

cc

c

C THE PURPOSE OF EVRL20 !S TO ENRBLE THE OCCUPfiNT TO EVOLUflTE HIS

C 'SfiFETY STfiTOS' BY COrPRRING EGRESS PROGRESS RGRINST TOTAL ELAPSED Tift

C SPENT IN THE DANGER ZONE

C SUBROUTINE EVAL20 (rKTIME.IIC.XO. YO.>t. YE.NTHIS. lAGREE,

1 ITIME.C.IEVRL.TOTIftJ

INTEGER XD(20).YO(20).XE(10).YE(10).XT.YT.TOTirE

IF (lAGREE.EQ.B) GO TO 5

C COMPUTE TEST DISTANCE BETUEEN THE OCCUPANT’S CURRENT LOCATION AND THE

C AGREED-UPON EXIT

TEST*SQRT(FLOAT( (XO (NTH IS) -XE ( lAGREE) )»»2+

1 CY0(NTHIS)-YE(IAGREE))*»2))

5 CONTINUE

C CHECK THE OCCUPANT'S KNOULEDGE OF BEST EXIT AND THREAT LOCATIONS

* IF ((XT.GT.0).AND.(YT.GT.0)) GO TO 10

IF (IAGREE.GT.0) GO TO 20

GO TO 50

10 IF (IAGREE.GT.0) GO TO 20

GO TO 30

C TEST FOR ESCAPE PENALTY

20 IF (ITIME.LE.tDO-IPE) GO TO 21 TIME-ITIft TTlME-TOTIft TDIST-TTlft-Tirt

GO TO 22

21 TDIST-TTinE-(FLOAT(rD(TirE)) 22 IF (TEST.LE.TDIST) GO TO 51

GO TO 50

C TEST FOR THREAT PENALTY

30 QTEST-SORT(FLOAT((XO(NTH:S)-Xn*»2+

1 (Y0(N7HIS)-YT)»*2))

IF (ITIft.LE.rtXTirE) GO TO 31 Tlft-lTirt

TDIST-TIft

GO TO 32

31 TDIST-0.0

C RECORD THE OCCUPANT’S STATUS EVALUATION. IEVAL-1 (POSITIVE). IEVAL-0

C (NEGATIVE) 32 IF (OTEST.GE.TDIST) GO TO 51 50 IEVAL<0 RETURN

51 lEVAL-1 RETURN

END

145
Routine

Formulas

INTRPT

Occupant

This subroutine probabilistically determines whether an occupant's goal“directed behavior will be interrupted

during time frame t. The two modes of interruption are remaining-in-place and backtracking. Occupants are assigned probabilities of encountering such interruptions

Each occupant is also assigned an interruption limit. If

during the course of the simulated event, an occupant has

experienced a number of interruptions equal to his limit,

he will not "tolerate” any more, and hence ignore future

interruptions

.

n/a

146
START

Decetnine whether

OCCj^ experiences

a remain- in-place

Interruption (INT-l), _ a back-track inter- ruption (INT“2), or no Interruption

at all (INT-0)

Subroutine INTRPT
SUBROUTINE IHTT?PT

C

c

cc

c

cc

C THE PURPOSE OF INTRPT IS TO PR0BR91LISTICPLLY DETERMINE UHE'mER THE

C OCCUPfiMT'S GOAL-DIRECTED BEHAVIOR UILL BE INTERRUPTED DURING TirE FRATC T. C TIJO rjDES OF INTERRUPTION ARE AVAILABLE, REMA IN ING- IN-PLACE AND

C backtracking. INTEPT DETERMINES UHETHER AN INTERRUPTION UILL OCCUR. AND

C UHICH MODE UILL CONTROL.

C SUBROUTINE INTRPT ( ITirE.NTHIS. IHANOI , INT, IBYSTD, lEVAL,

1 XO.VO, IBAR.TOTBAR.XT.YT.NAGREE.XE.YE, lAGREE.

2 IRAND.P,MO'VE,>«,YK,K,L, IS. IGOALX, IGOALY, lENTER. 3 X, INTUM. INTR.INTHUM.PI2.PI0) DIMEYSION INTN'JM(20).iNTLIMC20) DIMENSION INTRC20)

C DETERMINE UHETHER THE OCCUPANT EXPERIENCES A REMAIN- IN-PLACE INTERRUPTION

C (INT-1). A BACKTRACK INTERRUPTION UNT-2). OR NO INTERRUPTION AT ALL (INT-0)

IF CINTRCNTHISI.EQ.l) GO TO 1 IF CINTHUM(NTHIS).LE.INTLIMCNTHIS)) GO TO 2 IMT-0 RETURN

1 INT-2 RETURN

2 CALL RANDOM (ITIfS.NTHIS. IKANDI. INT. IBYSTD, lEVAL.

1 XO. YO. IBAR.TOTEAR.XT.YT.NAGREE.XE.YE. lAGREE. 2 IRANO.P.MOVE.XK.YtC.K.L, IS, IGOALX, IGOALY. lENTER. 3 X)

IF (XI 5,6.6

5 X-X*C-1)

6 CONTINUE

. IF CX.LT.PI2) GO TO 3

IF CX.LT.PI0) GO TO 4

INT1

INTHUMCNTHISI-INTHUMCNTHIS)-*.! RETURN

3 intnum(nthis)-:ntnum(nthis)+i

INTRCNTHISI-l

INT-2 RETURN 4 INT-0 RETURN

END

148
Routine BACKUP

Loop Occupant

Purpose If a backtracking interruption is evoked by Subroutine

INTRPT, then BACKUP is called. BACKUP processes occupants

who have entered into this mode by retracing their steps

back toward their initial starting location. Once the

occupant has returned to this point, he is removed from the

backtracking mode, and he resumes the normal decisionmaking

and goal seeking processes.

Formulas n/a

149

o Dcteraine

x,7 coordinaces ._| of OCCj^'e new

location

HEWZ»>X(ffi (HTHIS . rriME)

NEHTO>TOB(irrHIS .XTIHE) 0

c

RETDBN 3

Subroutine BACKUP

151
SUBROUTINE BACKUP

C

c

c

cc

cc

C TWE PURPOSE OF BACKUP IS TO PROCESS OCCUPANTS THRUST INTO THE BACKTRACK

C INTERRUPTION NODE. BACKUP RETRACES THEIR STEPS BACK TOUARD THEIR INITIAL

C STARTING LOCATIONS. ONCE AT THIS LOCATION. OCCUPANTS REENTER THE NORMAL

C GOAL-SEEKING MODE.

C SUBROUTINE BACKUP ( IBACK.XO, YO, INITVO, INITYO.XOB.YDB.

1

ITirE.NTHIS.NELKO.NEUTO.INTR.JTirE) DIMENSION IBACK(2O).INIT>O(20).

I INITYOC20).JTINEC20),INTR(20)

INTEGER XOB(20,I00).VOB(20.1BB),XD(20).T1ja<J)

C DETERMINE BACKTRACK STEP COUNT

IF (IBACK(NTHIS).EQ.0) GO TO I C DETERMINE LHETHER THE OCCUPANT HAS ATTAINED HIS BACKTRACK COAL

IF ((XDCNTHIS) .EO. IN ITHOCNTH IS5 ) . AND.

1 (YOCNTHIS).EO.INirrO(NTHIS))) CO TO 3

S IBACK(NTHIS)»IBACK(NTHIS)+l

C DETERMINE THE NE>CT BACKTRACK LOCATION

IF (IBRCK(NTHIS).EQ.l) GO TO 2 JTITE(NTHIS) -JTII^INTHIS)-!

GO TO 4

2 IF (ITirE.CT.l) CO TO 21 JTirECNTHISl-l

GO TO 4

21 JTir€(NTHlS)-ITIKE-l 4 KTirE»JTIME(NTHIS)

C DETERMINE X.Y COORDINATES OF THE OCCUPANT'S NEU LOCATION

NEUXO -XOB ( NTH I S . KT IKE) NEUYO «YOB ( NTH I S . KT I rt) RETURN

3 INTR(NTH!S)-0 IBACKCNTHIS)»0 RETURN

END

152
Routine

Loop

Purpose

Formulas

ASSIGN

Occupant

BFIRES assumes that an individual's decisionmaking behavior

will be biased, and that the direction of bias will be

determined by his immediate perception of the fire

situation. The primary function of ASSIGN is to "recall"

for each occupant all those factors which comprise his

current perception (e.g., current evaluation of success,

knowledge of exit locations, interruption status, etc.). It

then assigns his decisionmaking task to an appropriate

biasing subroutine. The following directions are accommodated within the current version of BFIRES:

(1) threat evasion (Subroutine TBIAS);

(2) exit goal seeking (Subroutine EBIAS);

(3) interruption mode fulfillment (Subroutines INTRPT and/or

BACKUP);

(4) confusion, or no specific bias (Subroutine EQUALZ).

(1) CUM(K) = P(K)

(2) CUM(K) » P(K) + CUM(K-l)

(3) RAND = CUM(K) - X

Where:

CUM(K) “ cumulative probability of selecting

the kth move;

P(K) = the computed probability fo selecting

the kth move;

K = move identifier;

X = a uniformly distributed random number

between 0 and 1;

RAND = Test number for stochastic selection

process.

153
mxT

c )

ik

TIME - ITIME ATIME - TIME/ 2. JTIME - ATIME

B « JTIME TEST - ATIME-BTIME

YES

Determine whether

ITIME Is odd/even: mobility-impaired

occupants only move during ODD time- frames

Determine move probability

biasing mode:

Is OCC^ In an Interruption

mode?

Is Occ. currently in

a helping mode?

Assess Occ^'s

current status evaluation

Is the threat location known

to Occ^l

Does a best-exit

consensus exit? _ (If so, HAGREE ^ 0)

Subroutine ASSIGN

154
CALL HBIAS

Rema In- In-p lace option

enforced

Bias move

probabilities

to favor approaching or remaining with

another (helping)

:nagree-o

NO

YES

CALL EQUALZ

Equalize all move probabilities

Subroutine ASSIGN

155
K - X - RA

0NDNU(O)

\ /

K - K + 1

( 0 ).(+)

Determine whether

OCC. will open

a closed door he has confronted

Occ selects a movi from among

those available

Prepare alternative move probability

values for testing

against random no.

Generate a random number ,X, and test move alternatives

156 3 Subroutine ASSIGN
MOVE - K

N

b

CALL DOORS2

h C ^

RETURN ^

Decermlne whether

OCC. closes a he has just passed

through (If In fact he has just done so

Subroutine ASSIGN
c

cc

c

c

C SUSROUTINE ASSIGN

c

C TNE PURPOSE OF ASSIGN IS TO CONSIDER ALL FACTORS COrPRISING THE OCCUPANT'S

C CURRENT PERCEPTION OF HIS SITUATION. AND THEN TO SUITCH CONTROL FOR

C DECISIOH-riAKING TO TVIE APPROPRIATE BIASING ROUTINE.

C SUSROUTINE ASSIGN ( ITirE.NTHIS. IHANDI . INT. IBYSTD, lEVRL.

I XO.YO, IBAR.TOTBAR.XT.YT.NAGREE.XE.YE. lAGREE.

Z IRAND.P.MOVE.XK, YK.K.L. IS. IGOALX, IGOALY. lENTER.

3

X. IDOOR.POPEN.ND.fIDOOR.PCLOSE) DirEMSION IHANDI (20) . IBYSTD(20) .P(9) .CUM(9>

INTEGER MH20),YOC20).>E(10),YE(10).XT.YT

C DETERniNE UHETHER ITIFIE. THE CURRENT TIME-FRAME. IS ODD OR EVEN...

C MOSILITY-irPAIRED OCCUPANTS ONLY MO'VE DURING ODD TIFE-FRArES

Tirc-iTirt

ATIME-Tire/2. JTIME-ATITE BTIME-JTirt

TEST-ATire-BTI“E

C DETERMINE MOVE PROBABILITY BIASING MODE

IF ( IHANDI (NTHIS).EQ.l) GO TO 1 GO TO II

1 IF (TES7.NE.0.) GO TO 2

C IS THE OCCUPANT IN AN INTERRUPTION MODE

II IF (INT.EQ.l) GO TO 2

C IS THE OCCUPANT CURRENTLY IN A HELPING MODE

IF (lEYSTD(NTH’S).EQ.I) GO TO 3

C ASSESS THE OCCUPANT’S CURRENT STATUS EVALUATION

IF (lE'/AL.EQ.I) GO TO 4

C IS THE THREAT LOCATION KNOUN TO THE OCCUPANT

IF ((XT.EQ.0).AND.(YT.EQ.0)) GO TO 5

C DOES A EEST-E;JIT consensus EXIST (IF SO. NAGREE.NE.0)

IF (NAGREE.EQ.0) GO TO 404

GO TO 504

C BIAS MOVE PROBABILITIES TO FAVOR THREAT-EVASION

404 CALL TBIAS ( ITIME.NTHIS. IHANDI. INT. IBYSTD. lEVAL.

1 XO.YO. IBAR.TOTBAR.XT.YT.NAGREE.XE.YE. lAGREE.

2 IRAND.P.roVE.)«. YK.K.L. IS. IGOALX. IGOALY. lENTER) GO TO 6 4 IF (NAGREE.EQ.0) GO TO 404

C BIAS MO'vE PROBABILITIES TO FAVOR EXIT-SEEKING

504 CALL EBinS ( ITIME.NTHIS. IHANDI. INT. IBYSTD. lEVAL.

1 XO.YO. IBAR.TOTBAR.XT.YT.NAGREE.XE.YE. lAGREE.

2 IRAND.P. MO'VE. >«.YK.K.L. IS. IGOALX. IGOALY. lENTER) GO TO 6

C REMAIN- IN-PLACE OPTION ENFORCED

2 P(5)-I.0

DO 53 K-1.4

SB P(K)-0.0

DO 51 K*6.9

51 P(K)«0.0

GO TO 60!

C Bins MU'VE PROBABILITIES TO FAVOR APPROACHING OR REMAINING UlTH A MOBILITYC IMPAIRED OTHER

3 CALL HBIA3 ( ITIME.NTHIS. IHANDI. INT. IBYSTD. lEVAL.

1 XO.YO. ISAR.TOTEAR.XT.YT.NAGREE.XE.YE. lAGREE.

2 IRAND.P) GO TO 6

5 IF (NAGREE.NE.0) GO TO 504

C EQUALIZE ALL raVE PROBABILITIES

CALL E0UAL2 ( ITIME.NTHIS. IHANDI . INT. IBYSTD, lEVAL.

1 XO.YO, IBAR.TOTEAR.XT.'iT.NAGREE.XE.YE, lAGREE.

2 IRAND.P. MOVE. »(.YK.K.L. IS, IGOALX. IGOALY. lENTER)

C DETERMINE UHETHER THE OCCUPANT UILL OPEN A CLOSED DOOR HE HRS CONTRONTED

6 CALL DOORSl ( ITIME.NTHIS. IHANDI , INT, IBYSTD, lEVAL.

1 XO.YO, IBRR.TOTBAR,>a.YT. NAGREE.XE.YE. IRGREE.

2 IRAND.P, MOVE. >«.YK,K.L. IS. IGOALX. IGOALY. lENTER.

3 X. IDOOR.POPEN.ND.MDOOR.PCLOSE, IX) 601 CONTINUE

C THE OCCUPANT SELECTS A MO'VE FROM AMONG THE ALTERNATIVES AVAILABLE

DO 100 K-1.9

C PREPARE ALTERNATIVE MOVE PROBABILITY VALUES FOR TESTING AGAINST A RANDUH

C NUrEER

IF (K.EO.l) GO TO 200 CUM(K)-P(K)+CUM(K-1)

GO TO 100

158
200 cuncK)-p«c)

100 CONTINUE

C GENERATE A RANBOM NUTBE X. AND TWEST TWE rOVE ALTERNATIVES

K*0 CALL RANDOM tlTlrE.NTHIS. IHANDI. INT, IBYSTD. lEVAL.

1 XO, YO, 1BAR.T0TBAR.XT,TT.NAGREE.>E.YE. lAGREE. IRAHD, 2 P,mVE.>«,VK.K.L, IS. IGOALX. IGOALY. lENTER.X) 7 r-K-M

IF (X) 71.72.72

71 X«X»(-I)

72 RAND*CUM(I«-X

IF (RAND) S2.S3.S3

S3 mVE-K

GO TO B

52 IF (K.LT.9) GO TO 7

C DETERMINE UHETHER THE OCCUPANT CLOSES A DOOR JUST PASSED THROUGH (IF IN C FACT HE HAS JUST DONE SO) 8 CALL D00RS2( ITIft.NTHIS. IHANDI. INT. IBYSTD. lEVAL.

1 XO.YO. IBAR,TOTBAR.XT.YT.NAGREE.>E.YE. lAGREE. 2 IRAND,P.MOVE.)«.YK.K.L. IS. IGOALX. IGOALY. lENTER.

3 X. IDOOR.POPEN.ND.MDOOR.PCLOSE. DO

12 RETURN END

159
Routines UPDATE, NEWXY, XSCORE, STEPS, PASSG (Utility Programs)

Loops Occupant and Replication

Purposes UPDATE

:

This subroutine changes the x,y coordinates denoting occupant

locations to reflect movement actions of each during the

just-completed time frame.

NEWXY:

This program converts spatial locations from k-grid

designators to x,y coordinates, using Subroutine KTOXY,

in those cases where KTOXY is not called directly.

XSCORE;

This subroutine computes each occupant's escape score for

the entire event.

STEPS;

The purpose of STEPS is to keep track of the total number of

spatial displacements ("steps") actually made by each

occupant during the fire event. Remaining-in-place is not

recorded as a step.

PASSG;

PASSG keeps track of door-passage behavior exhibited by

occupants.

160
Formulas XSCORE:

(1) SCORE = (SUMTIM-E)/SUMTIM)

Where

SCOEIE = occupantj^'s overall escape score;

SUMTIM = total number of time frames available

E = time frame at which escape occured^.

If the occupant never escapes, E SUMTIM

161
c

c

c

c

cC SUBROUTIHE UPDATC

C

C THE PURPOSE OF UPDATE IS TO CHANGE THE . .V UUKDIN'^ES OF OCCUPANT LOCATIONS

C TO REFLECT rtJVErZNT ACTIONS OF EACH DURING ’HE JUS"-COrPLETED TIME FRArE

C SUBROUTINE UPDATE OC.YO.NTHIS.NELKO.NEUTO)

INTEGER XO(20).YO(2B) MICNTHISI'NELMI

YOCNTHISJ-NEUTO

RETURN

END

C

c

c

cc

C SUBROUTINE NElB<y c

C THE PURPOSE OF NEIKY IS TO CONVERT SPATIAL LOCATIONS FROM K-GRID

C DESIGNATORS TO X.Y COORDINATES. USING SUBROUTINE KTOXY. IN THOSE

C CASES UHERE KTOXY IS NOT CALLED DIRECTLY

C SUBROUTINE NEUXY ( ITirE.NTHIS. IHANDI. INT, IBYSTO. lEVAL.

1 XD.YO. IBAR,TOTBAR.XT.YT.NAGREE.>€.YE. lACREE. 2. 1RAND.P.M0VE.>3(.YK.K,NEIM].NEUY0) INTEGER >«.YK CALL KTOXY UTirt.NTHIS.IHANDI.INT. IBYSTD. lEVAL.

1 XO.YO. IBAR.TOTBAR.XT.YT.NAGREE.>€.YE. lACREE. 2 IRAND.P.rOVE.XC.YK.K)

NELDCO'MC NEUYO«YK

RETURN

- END

C

c

cc

cC SUBROUTINE >SCORE

t

C THE PURPOSE OF XSCORE IS TO COIPUTE EACH OCCUPANT'S ESCAPE SCORE FOR THE

C ENTIRE EVENT. I.E.. SCORE*(TOTAL TirE AVAILABLE - CURRENT TirE FRATE)

C DIVIDED BY THE TOTAL TirE AVAILABLE

C SUBROUTINE XSCORE (TOTirE. ISCORE.NUItJCC.SCORE) DirENSION ISC0REC2B). SCORE (2B)

INTEGER TUTIfE SUMTIM-TOTIfE

DO le NTHIS'l.NUrOCC

EoISCORE(NTHIS)

C COtPUTE the OCCUPANT'S ESCAPE SCORE FOR THE ENTIRE EVENT

IB scoRE(NTHis)-(SunTiM-E)/surrrin RETURN

END

C

c

ccc

C SUBROUTINE STEPS

C

C THE PURPOSE OF STEPS IS TO KEEP TRACK OF THE TOTAL NUrSER OF SPATIAL

C RELOCATIONS ('STEPS') ACTUALLY MADE BY EACH OCCUPANT DURING THE FIRE EVENT

C ...A STEP IS defined as A SPATIAL RELOCATION. AND THEREFORE. REMAINING- IN>

C PLACE IS NOT RECORDED AS A STEP

C SUBROUTINE STEPS (JPRIOR. YPRIOR.XO, YO.NUMSTP.NTHIS)

INTEGER )PRIOR(2e).YPRIOR(2B>.XO(2e).YO(2B>

DIMENSION NUMSTP<20) C RECORD l>t£THER THE OCCUPANT MOVED DURING THE TIME FRAFE JUST ENDED. THAT IS. C LPETHER <>PRIOR.HE.XO).AND.{YPRIOR.HE.YO>

IF (OPRIOR(NTHIS).EQ.)C(NTHIS)).AND.(YPRIOR(NTHIS).EO.YO(NTHIS))>

I GO TO 999

C UPDATE THE TOTAL NUMBER OF STEPS TAKEN BY THE OCCUPANT DURING THE EVENT

NUnSTP (NTH IS) •NUMSTPCNTH IS)+I 999 RETURN

END

162
nononooono SUBROUTINE PflSSC

INE PURPOSE CF PRSSG IS TO KEEP TRACK OP DOOR-PASSAGE BEHAVIOR EM4IBITED BY

OCCUPANTS

SUBROUTINE PASSG ( IDPASS. IDOOR.«5. YO.HTHIS.

1 NS.NELiXO.NEUlO) DirCNSION ISPASS(2e).IDOOR(3e.4)

INTEGER >O(20).YO(20)

C DETERMINE UMETHER THE OCCUPANT PASSED THROUGH A DOORUAY DURING THE Tir€-

C FRArE JUST ENDED

I»>ASS-<N£LDJ)+>3D(NTHIS))/2 lYPASS- (NE^JYO•^•^D (NTHIS) )/2 DO 10 I'l.ND

IF ((1D00R(I.1).EQ.IXPASS).AND.

1 (ID00R(I.2).E0.1YPASS)) 60 TO 5 GO TO 10 C UPDATE THE TOTAL NUMBER OF DOOR PASSAGES MADE BY THE OCCUPANT DURING THE

C FIRE EVENT

5 lDPRiS(NTHlS)-IDPASS(NTHIS)+I

IB CONTINUE RETURN

END

163

I
Routines SUMMARY, REPORT, TRACE, TOTALS (Input/Output Programs)

Occupant and Replication

SUMMARY;

This program prints a summary table for each replication.

Output are values for various dependent measures computed

by BFIRES. These values are "grand means” taken across occupants and time frames, and report aggregated scores and

final status at the end of the last time frame for each

replication. Initial conditions are also printed, for

comparison against final states.

REPORT:

This subroutine prints a summary table for each time frame

within a given replication. Each table reports results of

the decision process for each occupant in the run. Data

include move probability values, and x,y coordinates for

occupants* locations at times t-1 and t.

TRACE:

TRACE prints a summary table for each occupant in a given

replication. Each table traces the spatial displacement of

the occupant across the entire simulated event (in terms of

changes in x,y coordinates).

TOTALS:

This routine prints summary tables reporting total numbers

of door passages and interruptions for each occupant in the

event. Door passages are also reported by Subroutine SUMMARY.

164
SUBROUTINE SUfTRY

C

c

c

cc

cc

C THE PURPOSE OF SUrtHY IS TO PRINT-OUT A SUmBRY TfiBLE FOR EACH REPLICATION

C RUN... OUTPUT VALUES ARE 'GRAND rEANS' TAKEN ACROSS OCCUPANTS AND TlttC FRAMES. AND REPORT AGGREGATED SCORES AND FINAL STATUS AT THE END OF THE

C LAST Tire FRArt FOR EACH REPLICATION

C SUBROUTINE SUtTRY flNITTO. INITYO, INTLIM.LBYSTD. IHANDI.KNOUAY,

1 POPEN.PCLOSE.SCORE.NUMSTP.IPS.III.NUtREP.NUMOCC.TOTirE.

2 XD.YO.>€. YE, TITLE) DIMENSION INIT>0(20) , INITY0C28) , INTLIM(20) ,LBYSTD(20) , IHANDI (20)

.

1 KNOUAY( 20 ) , POPEN (2O).PCLOSEC20),SCORE(20). NUMSTP ( 20 ) . IPS (20) DirSNSION NUMBER(20),SMEAN(20),DMEAN(20).DIST(20).DEINIT(20).

1 DIFF(20).DFr€AN(20).TITLE(20)

REAL NrEAN(20) . irEAN(20) INTEGER TOTir€.XD(20).YO(20).)«(10),YE(10) DlFTOT-0.0

DTOTAL-0.0

STOTAL-0.0 N7OTAL-0

ITOTAL-0 N3UM-NUrOCC*NUM?EP SUM-NSUM

ftN-NUMOCC LRITE (6,100) LRITE (6.134) TITLE

LRITE (6.119) URITE (6.102) URITE (6.103) LRITE (6.119) LRITE (6.104) III.NUrREP.TOTirE LRITE (6.102) LRITE (6.119) LRITE (6.105) LRITE (6,119) LRITE (6,106) DO 200 N>1.20

NUMBER (H)-H 200 CONTINUE

LRITE (6.107) (NUMBER (N).N- 1.20) LRITE (6.101)

to 55 K-l.HUMCCC

55 DEINIT(K)-SQRT(((INIT)C0(K)->€(l))«t»2)+((INITY0(K)-YE(l))»*2)) LRITE (6.131) (DEINIT(K).K-l.NUMOCC)

(INIT>II(K).K-l.NUMOCC) (INlTYO(K).K-l.NUMOCC)

(INTLIM(K),K-l,NUMOCC)

(LBYSTD(K),K*1,NUMDCC) (IHANDl(K).K-l.NUMOCC)

(KNOL'AY(K).K-l,NUMOCC) (POPcN(K).K-l.NUMOCC) (PCLOSE(K).K-I.NUMOCC)

LRITE (6.100) LRITE (6,109) LRITE (6.110) LRITE (6.111) LRITE (6.112) LRITE (6.113) LRITE (6.114) LRITE (6.115) LRITE (6.102) LRITE (6,119) LRITE (6.116) LRITE (6.119)

. LRITE (6,106) LRITE (6.107) (NUPEER(N),N-1.20) LRITE (6,101) C..COrRUTE REPLICATION MEANS...

DO 20 K-I.NUMOCC

DIST(K)-SQRT(((XE(1)-XD(K)) *»2)+((YE(1)-Y0(K))ko«2)) DTOTAL-DTOTAL+PIST(K) STOTAL-STOTAL+SCORE(K)

NTOTAL-NTOTAL-HIUMSTP(K) 20 ITOTAL-ITOTAL+IPS(K) SMSAN(1I1)-S7DTAL/PN

NMEAN (III) 'FLOAT (NTOTAL) /AN

IMEAN (HI) -FLOAT( ITOTAD/AN

DMEAN(III)-DTOTAL/AN

DO 201 K-l.NUMOCC

DIFF(K)-DEINIT(K)-DIST(K)

DIFTOT-DIFTOT+DIFF(tC)

201 NUMSTP(K)-NUMSTP(K)+1

LRITE (6.127) (XO(K) .K-l.NUMOCC) LRITE (6.12S) (YO(K),K-I,HUMOCC) LRITE (6.129) (DIST(K) .K- I .NUMOCC) LRITE (6. 132) (DIFF (K) ,K- 1 .NUMOCC) LRITE (6,117) (SCORE(K). K-l.NUMOCC) LRITE (6,1 IB) (NUMSTP(K). K-l.NUMOCC) LRITE (6.120) ( IPS (K). K-l.NUMOCC)

C. COMPUTE NESCBP... NESCAP-NUMDCC

DO 300 L-l. NUMOCC

IF (SCORE(L).LE. 0.001) GO TO 301 GO TO 300

301 NESCAP-NESCAP-1

300 CONTINUE

LRITE (6,126) NE5CAP LRITE (6.102) LRITE (6.122) NUMOCC

LRITE (6.130) DMEAN(III) OFMEAN (111) -D IFTOT/HN LRITE (6.133) DFMEAN(III)

165
LRITH (6.123) SrCANdll)

LRITE (6.124) NrCAH(III) j;iTc (S. 125) irCAN(IIl) URITE (6,102) URITE (6.121) URITE (6.102)

100 FORrWT ('!')

101 FORflRT (130('»*))

102 F0RP1ST (130('»*)./'. 130C*'))

103 FORmT (S7X.'SIMLn.RTI0N SUmiRY*)

104 FORmT (3X.'REPLlCfiT10N'.15.* OF' . 15.70X, 'RUN FOR'. 14.

1

' Tim FRftrES') 105 FORmT (S7X.' INITIAL CONDITIONS')

106 FORmT (63X, 'OCCUPANT NU78ER')

107 FOPmT (11X,20(I2.3X))

10S FORmT (3X,'IN1TX0'.1X.29(I3.2X).I3)

109 FORmT (3X, 'INITY0',1X,29(I3,2X).I3)

110 FORmT (3X,'INTLIir.lX.29n3.2X).I3)

111 FORmT {3X.'LBYSTD',1X,29(I3.2X).I3)

112 FORmT (3X,'1HANDI'.1X.29(I3.2X).I3)

113 FORmT (3X,'KN0UflY'.lX,29(I3.2X).I3)

114 FORmT (3X,'P0PEN ' . 1X.29(F3.2,2X) .F3.2)

115 FORmT (3X,'PCL0SE',1X.29(F3.2.2X).F3.2)

116 FORmT (SSX.'OUTCOmS*)

117 FCr.mT (3X,'SC0RE '.1X.20(F4.2.1X))

lie FORmT (3X.'STEPS '.1X.20U3.2X))

120 FORmT (3X.'PfiSSES'.lX.20U3.2Xl)

119 FORmT t' ') 121 FCR.mT (S7X.'EHD OF REPLICATION')

122 FORmT (9X.'nEANS COmuTED ACROSS'. 13.* OCCUPANTS,..')

123 =CRmT (20X.*nEAN SCORE - '.F4.2)

124 FORmT (20X,'t1EAN STEPS '.F6.2)

125 FORmT (20X.'t1EAN PASSES -'.F6.2)

126 FORmT (SX.'NUrBER ESCAPED' ,5X. 13) 127 FORmT (3X,'FIN X '

. 1X,20( I3.2X)

)

123 FORmT (3X.'F1N Y '

. 1X.20( I3.2X)

)

129 FORMAT (3X.'D1ST ' , 1X.20CF4. 1. IX)

)

133 FORMAT (20X,'MEAN DIST • '.F4.1)

131 FORmT (3X.'1NIT D'.1X.20(F4.1.1X))

132 FORMAT (3X,"DIFF D'. 20<F5.1))

133 FORmT (20X.'MEAN DIFF D -'.F4.1)

134 FORMAT (IX. 'RUN TITLED '.20A4) RETURN

END

166
oonnonoooo SUBROUTINE REPORT

THE PURPOSE OF REPORT IS TO PRINT-OUT ft SUrWRY TRBLE FOR EACH TIFE-FfiftrE OF ft GIVEN REPLICflTION...EftCH TABLE REPORTS RESULTS OF THE DECISION

PROCESS FOR EACH OCCUPANT IN THE TIME FRAME. PARTICULARLY MOVE PROBABILITY

C

cc

c

c

c

C:

C:C

C

C:C

c

C:C

c

Ic

c

C:C

c

value: assigned to each available move alternative at that point in Tire

...X.Y COORDINATES ARE ALSO SHOUN FOR BOTH TireS T AND T+1. FOR EACH OCCUPANT IN THE Tilt FRAFE

SUBROUTINE REPORTCITIME.NTHIS, IHANDI, INT. IBYSTD. lEVAL.

1 XO.YO. IBAR.TOTBAR.XT.YT,NAGREE.>E.YE. lAGREE.

2 IRSND.P.MOVE.MK.YK.K.NUMEXT.NUMOCC.TOTIFE. INTLIM.

3 LB-^TD, KNOUAY. PTD 1ST. TD I ST, PED 1ST, ED 1ST. NEUXO, NEUYO. 4 EVLGPT. IDOOR.IDOPEN.ND.INTR) DIMENSION IBAR (20,75.2) , INTLIMC20) ,LBYSTD(20) . IHANDI

I (23) .KNOLIAYC20) . IBYSTD (20) ,P (9) , INTR(20) DIMENSION IDOOR(S0.4) . ID0PEN(30, 100) INTEGER ME(10),YE(10),XO(20).YO(20).XT.YT,TOTirE.

1 >X,YK.EVLOPT

, IF ((ITIME.GT.l).OR.(NTHIS.GT.l)) GO TO 1

ECHO: CHECK INPUT PARAMETERS*

(1) ENVIRONMENTAL:

LWITE (S.100)

L<;iTE (6.101)

UrRITE (6.102)

LiRlTE (6,104) LRITE (6.105) URITE (6.106)

>a.YT

NUFEXT

(XE(I).I-l.NUrEXT) (YECD.I-l.NUFEXn

(2) SYSTEM:

L>R1TE (6,109) NUMOCC

URITE (6,110) TOTIF€ URITE (6.111) IRAND

(3) OCCUPANT:

URITE (6.112) URITE (6.113) URITE (6,114) URITE (6.115) URITE (6.116) URITE (6.117)

( 1NTLIM( I). I-l. NUMOCC)

(L6Y3TD(I).I-1. NUMOCC) (IHANDI(I).I-I, NUMOCC)

(KNOUAY( I ) . I • 1 . NUMOCC)

CONTINUE

IF (NTHlS.NE.l) GO TO 2

IF NTH IS- 1. PRINT CURRENT Tirt MARKER AND COLUFN HEADINGS:

URITE (6.118) URITE (6.119) ITIFE URITE (6.118) URITE (6.128) URITE (6,118)

C

2 IF (INTR(NTHlS).EQ.l) GO TO 22

C

C: URITE OUTPUT MATRIX:

IF (EVtOPT-1) 20,28,21

28 CONTINUE

URITE (6.121) NTHIS.X0(NTHIS).Y0(NTH1S), INT, IBYSTD(NTHIS). lAGREE.

1 TDIST.EDIST. (P(K).K-1.9).NEUM).NEUY0

GO TO 23

21 URITE (6.123) NTHIS.XO(NTHIS) .YO(NTHIS) . INT. IBYSTD(NTHIS).

1 lAGREE. (P(K).K-l. 9). NEUXD.NEUYO

60 TO 23 22 URITE (6,127) NTHIS.XO(NTHIS) .YO(NTHIS) . INT,

1 NEUXO.NEUYO

23 CONTINUE

IF (NTHIS.EQ. NUMOCC) GO TO 3

GO TO 4

3 URITE (6.118) 4 IF ((ITIFE.EO.TOTirE).AND.(NTHlS.EQ.NUrOCO) GO TO 5 CO TO 6 5 URITE (6.118) URITE (6.124) URITE (6.118) URITE (6.12S) URITE (6.118) DO 30 1-1, ND

URITE (6.126) 1,IDOOR(1.1).1DOOR(I.2).IDOOR(I.3).

1 (IDOPEN(I.ITM).ITM-l.TOTIFE)

167
30 CONTINUE LRITE (£.118) URITE (£.122) URITE (£.118) GO TO £ C

C: OUTPUT FORTOTINCs

C100 FORMST (IX. 120(*»*).-'^.55X. 'ECHO-CHECK INPUT PftRftFETERS 120

I ('»•). z'/'.lX.'d) ENVIRONrENTflL :'./') 101 FORMAT (24X.' THREATENED EXIT; X- ' . I2.4X.'Y«* . 12) 102 FORMAT (24X. 'NUMBER OF EXITS: - '.12)

103 FORMAT (24X. 'NO. OF BARRIER PTS-'. 13.-0 104 FORMAT (24X.* COORDINATES OF EXITS: 123458789 18'.

1

/”) 105 FORMAT (43X;'X: '.10(12. IX))

I0£ FORMAT (43X.'Y: ' . 10( 12. IX) .-O 107 FORMAT ( IX. 'BARR lER-POINT MATRIX;'./')

100 FORMAT (2X.'X:'.33(I2.1X)./.2X.'Y:'.38(I2.1X)./0

109 FORTttT (IX. '(2) SYSTEM"./'.24X. 'NUMBER OF OCCUPANTS IH THE SPACE •'

1 .13) 110 FORI'BT (24X. 'TOTAL NO. OF TI7E INCRErtNTS -'.13)

111 FORMAT (24X. 'RANDOM NUMBER STARTER •'.13./') 112 FORMAT (1X.'(3) OCCUPANT; './. 12X. 'PARAMETER' .5X. "OCC NO 1 2 3 14 5 6 7 8 9 10 11 12 13 1 4 15 1£ 17 18 19 20'. )

113 FORMAT (!2X.'INTLIM".15X.20(I2. IX))

114 FORMAT (12X,'LBYSTD'.15X.20(I2.1X))

115 FORMAT (12X.' IHANDl' . 15X.20( 12. IX)) 11£ FORMAT (12X. 'KNOLJAY'.15X.20(I2.1X)./O

117 FORMAT (2(1X.120('*').^)) MB FORMAT (IX. 120('*')./') 119 FORMAT (IX. 'Tire - '.13.-0

120 FORMAT (£X. 'PR lOR' . I8X. 'EXIT' .89X. 'NEU' ./. IX. 'OCC' .2X. 'LOCAT' . 17X. r AGREED'. 87X.'L0CAT'./'. IX. 'HUM'. 2X.'X0 YO INT IBYSTD UPON

2 PTDIST TDIST PEDIST EDIST P(l) P(2) P(3) P(4) P(5) P(£)

3 P(7) P(8) P(9?'.£X,'X0 YO'./') 121 FORMAT (IX. I2.3X. I2.1X. I2.4X. Il.SX. Il.SX. I2.3X.2(7X.F£.3.2X).

I 9(F5.3. 1X).4X. I2.1X. 12) 122 format (SBX.'EMD OF S1M>JLATI0N'./)

123 FORMAT ( IX. I2.3X. 12. IX. I2.4X. 1 1 .£X. I l.£X.

1 I2.33X.9(F5.3.IX).4X. I2.1X. 12) 124 FORMAT (56X. 'DOOR STATUS SUM1ARY' . /') 125 FORMAT ( IX. ' DOOR' .4X. 'X Y' .5X. 'TYPE' .5X. 'T- 12345 1 £ 7 8 9 10 11 12 13 14 15 1£ 17 18 19 20 21 22 23

2 24 25 2£ 27 28 29 30'.-') 12S FORMAT (2X.I2.5X,I2.1X,12.7X.I1.8X.30(12.1X))

127 FORMAT ( IX. I2.3X. 12. IX. I2.4X. 1 1. 10£X. 12. IX. 12) £ RETURN

END

168
nonnnnoonoori SUBROUTINE TRftCE

THE PURPOSE OF TRfiCE IS TO PRINT-OUT A SU.i-»R: . S'LE FOf EACH OCCUPANT IN A GIVEN REPLICATION...EACH SUCH TABLE TRACES THf SPATIAL DISPLACErENT

(CHANGE IN X.Y COORDINATES) OF EACH OCCUPANT ACROSS THE ENTIRE SIMULATED EVENT

SUBROUTINE TRACE ( DORCE. lYTRCE.NTHIS. ITItE.NUMOCC.

I TOTirC) DIMENSION I)ORCE(20. 100) . IYTRCE(20. 100) INTEGER TOTltE LRITE (6,1) DO 25 I«1,NUM0CC URITE (6,2) I DO 24 J-I,TOTirE

URITE (6,3) J,IXTRCE(I,J),1YTRCE(I,J) 24 CONTINUE

LRITE (6.4) 25 CONTINUE

URITE (6.5)

1 FORMAT (IX.I20('»*).-'/'.48X.

I -OCCUPANT MOVErENT TRACES' IX. I20C»* ) ) 2 FORMAT (lX,120('»').yv’,IX.'OCCUPANT NUrBERi'.M..'.

1 I0X.'TirC'./.10X.'FRAtE-.l0X,'X'.5X.'Y"./'.

2 1X,I20('»*)) 3 FORMAT (12X.12.10X.12.4X.I2)

4 FORMAT (1X.120('»'))

5 FORMAT (IX.120C'*'),>'''.55X.'END OF TRACES', >’'.

1 1X.120('»')) RETURN END

CC

c

c

c

C SUBROUTINE TOTALS

C

C THE PURPOSE OF TOTALS IS TO PRINT-OUT SUTMARY TABLES REPORTING TOTAL

C NUMBERS OF DOOR PASSAGES AND INTERRUPTIONS (OF EACH TYPE) FOR EACH

C OCCUPANT IN THE EVENT C

SUBROUTINE TOTALS (IDPASS, ITYPEl. ITYPE2.NTHIS.NUMDCC) DirENSlON IDPASS(20).ITYPEI(20).ITYPE2(20) DirENSlON IOCC(20)

DO 25 I«t.NUrCCC

25 I0CC(I)>1 URITE (6.1) URITE (6.2) (IOCC(I).I>l.NUIt)CC) URITi (6.3) (1TYPE1(NTHIS).NTHIS»1.NUMDCC) URITE (6.31) (ITYPE2(NTHIS).NTHIS-I.HUrOCC) LUTE (6.4) URITE (6.5) (IOCC(I).I«l.NUrOCC) LRITE (6.6) (lDPASS(NTHlS).NTHIS«t.NUMOCC> LRITE (6.F) URITE (6.0)

1 FORMAT (IX. 120('*').^A45X.

1 'OCCUPANTS INTERRUPTION TOTALS :'./'/.38X. 2 'REPORTS TOTAL NUrOER OF FRArES SPENT IN MODES'.

3 IX. 120 ('»'))

2 FORMAT ( IX. 'INTRPT'.29X, 'OCCUPANT'. /-.2X. 'TYPE'.

1 1BX.20(I3))

3 F’ORMAT (lX.120('»'),/.4X,'r.llX.20(I3))

31 FORMAT (4X.-2'.IlX.20n3)./'.IX.12B('*')) 4 FORMAT (IX. 120 ('»'). /A 5BX.' DOOR PASSAGE TOTALS'.

1 IX. 1 20 ('»')./. 55X. • OCCUPANT'

)

5 FORMAT (30X,20'I3)./.1X.120('«'))

6 FORMAT (3OX,20iI3)./.lX,120('»'))

7 FORMAT (IX. 120('«')./'^.52X.'END OF TOTALS',/’^. IX.

. 1 120('*')7

0 FORMAT (lX.123('»').-'/’.55X.'END OF RUN'.^A 1X.120('*')) RETURN

END

169
FEDERAL INFORMATION PROCESSING STANDARD SOFTWARE SUMMARY

01. Summary datel

Yr. Mo. Day 7 3 ill 018

04. Software date

Yr. Mo. Day 7

00 p 00 3!0,

j 06. Short title

I 08. Software type

02. Summary prepared by (Name and Phone)

Fred I. Stahl (301) 921-2627

05. Software title

03. Summary action New Replacement Deletion

Computer Simulation of Human Behavior in Building

Fires

BFIRES

Previous Internal Software 10

07. Internal Software 10

09. Processing mode 10. GeneralApplication area

Specific Automated Data Q System

ptj Computer Program

I I Subroutine/Module

j~) Interactive (3 Batch

I I Combination

11. Submitting organization and address a

Computer Systems

Support/Utility

Scientific/Engineering

Sibliographic/Textuai

Management/

Business

Process Control Other

Computer simulation of

human behavior

* 12. Technical contact(s) and phone

Architectural Research Program

Environmental Design Research Division

Center for Building Technology

National Bureau of Standards

Washington j DC 202'^

A

Fred I.

13. Narrative

Stahl (301) 921-2627

BFIRES aids the prediction of escape times and escape routes of building

occupants during fires. The program executes a descrete time stochastic

simulation of human movement within bounded physical spaces, in response

to specified fire conditions. The simulation is based on a non—stationary

Markov model of building fire events. Input/output is via punched cards and

line printer, or via terminal.

14. Keywords

Building fires; computer-assisted building design; fire research; fire safety;

human performance simulation. -

15. Computer manufr and model UNIVAC 110816. Computer operating system

EXEC 8

17. Programing language(s)

FORTRAN V

IS. Number of source program state- ments

19. Computer memory requirements

28.62 K 36-bit

20. Tape drives 21. Oisk/Orum units 22. Terminals

words

23. other operational requirements

185-101
NBS>114A (Rev. 9- 79 )

U.S. DEPT. OF COMM.

BIBLIOGRAPHIC DATA

SHEET

1. PUBLICATION OR REPORT NO. NBSIR 79-1713

4. TITLE AND SUBTITLE

Final Report on the "3 FIRES /VERS ION 1" Computer

Simulation of Emergency Egress Behavior During Fires:

Calibration and Analysis

5. Publication Date March 1979

7. AUTHOR(S)

Fred I. Stahl

8. Performing Organ. Report No.

9. PERFORMING ORGANIZATION NAME AND ADDRESS

NATIONAL BUREAU OF STANDARDS

DEPARTMENT OF COMMERCE

WASHINGTON, DC 20234

11. Contract/Grant No.

12. SPONSORING ORGANIZATION NAME AND COMPLETE ADDRESS cstro^t, city, state, ZIP)

National Bureau of Standards

Department of Commerce

Washington, D.C. 20234

U.S. Public Health Service

Depto of H.E.W.

Washington, D.C. 20203

13. Type of Report & Period Covered FINAL

15. SUPPLEMENTARY NOTES

fxl Document describes a computer program; SF-185, FIPS Software Summary, is attached.

IS. ABSTRACT (A SOCMvord or lama tactual aamniary of moat aighiUcant Iniomatian. It document ineludea a aignitieant bibliogrephy or

literature surrey, mention it here.) This report documents computer simulation experiments designed to calibrate and

analyze BFIRES, a computer program which simulates building occupants' egress

behavior during fires. This report demonstrates that emergency egress behavior

under certain specified conditions can be systematically conceptualized, and

simulated through the use of a digital computer. Important findings concerning

the calibration and sensitivity of BFIRES are also discussed. In particular, it

is shown that: (a) a variety of general egress situations may be simulated

through the application of BFIRES; (b) every such event is unique, and is defined

by the set of user-supplied input parameter values which describe the building,

the threat, and the occupants; (c) BFIRES may be used in simulated environments

of known (or desired) spatial dimension, and events of known (or desired) temporal

duration; and (d) BFIRES simulation outcomes are sensitive to variations in a number of parameters of immediate interest to the building design and regulatory

commtinities

.

17. KEY WORDS (aix to twelve entriea; alphabetical order; capitalixe only the lirat letter of the lirat key word unleae a proper name;

aepereted by semieoiona) Architectural Research; building fires; computer-aided design;

environmental psychology; fire research; fire safety; human performance; modeling

technique; programming; sensitivity analysis; simulation.

18. AVAILABILITY Unlimited

I I For Official Distribution. Do Not Release to NTIS

I I Order From Sup. of Doc., U.S. Government Printing Office, Washington, DC

20402, SD Stock No. SN003-003- pn Order From National Technical Information Service (NTIS), Springfield, VA, 22161

19. SECURITY CLASS

(THIS REPORT)

UNCLASSIFIED

20. SECURITY CLASS

(THIS PAGE)

UNCLASSIFIED

21. NO. OF

PRINTED PAGES

178

22. Price

$9.00

1 /

USCOMM-OC
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