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Coupling between human behaviour and combustion: multi – agent and CFD simulations for road tunnel fires. Msc- Thesis by Giordana Gai School of Engineering, University of Rome La Sapienza
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Coupling between human behaviour and combustion:
multi – agent and CFD simulations
for road tunnel fires
Candidata:
Giordana Gai
Relatore:
Prof. Ing. Franco Bontempi
Correlatore:
Ing. Filippo Gentili
Facoltà di Ingegneria Civile e IndustrialeCorso di laurea magistrale in Ingegneria Civile
Coupling between human behaviour and combustion: multi – agent and CFD simulations for road tunnel fires
Giordana Gai
STRUCTURAL
SYSTEM
SAFETY
NON –
STRUCTURAL
COMPONENT
STRUCTURAL
COMPONENT
PEOPLE
1 / 18
INTRODUCTION
Coupling between human behaviour and combustion: multi – agent and CFD simulations for road tunnel fires
Giordana Gai
NON –
STRUCTURAL
COMPONENT
Tunnel
INTRODUCTION
Human behaviour
2 / 18
STRUCTURAL
SYSTEM
SAFETY
STRUCTURAL
COMPONENT
PEOPLE
ACTION : Fire
Coupling between human behaviour and combustion: multi – agent and CFD simulations for road tunnel fires
Giordana Gai
INTRODUCTION
Mont Blanc Tunnel fire (1999): 39 people died
(11.6 km long single – bore bi – directional tunnel)
3 / 18
Tunnel system
complexity
FireTraffic
conditionsGeometry
Safety
measuresOccupant
-1 dimension longer
than the other two
- Confined and closed
environment
- Cross section type (n°
of tubes)
- Longitudinal slope
- Daily traffic volume
- % HGV
- Detection system
- Alarm system
- Sprinklers
- SOS stations
- Emergency exits
- Lay – by
- Illumination system
- Vertical signage
- Horizontal signage
- Number of users
- Composition (gender
and age)
- Psycological
characteristics
- Habitual users
(familiarity)
- Human behaviour
- Disabled people
- Fire load
- HRR
- Number of vehicles
involved in the
accident
- Type of fuel
- Position of the
accident
Multidisciplinary and multiphisics problem
Coupling between human behaviour and combustion: multi – agent and CFD simulations for road tunnel fires
Giordana Gai
Spatial aspects 1D - aspects Temporal aspectsCode and
computational cost
RANSReynolds
Average
Navier
Stokes
ANSYS
FLUENT
20 cm – mesh
8 hours of
simulation
LESLarge
Eddy
Simulation
FDS
20 cm – mesh
1 hour of
simulation
0
1
2
3
4
5
6
7
8
9
10
0 200 400
Y [
m]
Temperature [°C]
0
1
2
3
4
5
6
7
8
9
10
0 200 400
Y [
m]
Temperature [°C]
0
50
100
150
200
250
300
0 5 10 15 20
Tem
per
atu
re [°C
]
Time [s]
0
50
100
150
200
250
300
0 5 10 15 20
Tem
per
atu
re [°C
]
Time [s] + Evac
COMPUTATIONAL FLUID DYNAMICS
4 / 18
Classical ApproachLPHC Actions
Low Probability High ConsequencesNormative
• Structural and unstructural
permanent load
•Antropic load
• Snow, wind, seismic action
Combination (ULS)
G1G1+ G2G2+ PP+ Q1Qk1+
+ Q2 02Qk2+…
Combination (SLS)
G1+G2+P+ 11Qk1+ 22Qk2+…
A – Fire characteristics and safety measures
• Position of the accident
• Fire load (HRR)
• Ventilation conditions
• Presence and position of safety measures (by
– passes, signage, illumination, sprinklers,
detection systems, etc)
B – Traffic characteristics
• Traffic flow conditions
• Presence of HGV
C – People
• Number of people
• People composition (physics and
psycological characteristics)
• Human behaviour
• Panic and familiarity with the structure
• Presence of disabled people
ANAS Circular 2009
(based on D.Lgs
264/2006 and Directive
2004/54/EC)
Coupling between human behaviour and combustion: multi – agent and CFD simulations for road tunnel fires
Giordana Gai
SCENARIO – BASED APPROACH
5 / 18
Fixed data
Variables data
Scenario analysis is a process of analyzing possible future events by considering
alternative possible outcomes, including the development paths leading to them.
Coupling between human behaviour and combustion: multi – agent and CFD simulations for road tunnel fires
Giordana Gai
HUMAN BEHAVIOURAL MODEL
6 / 18
PEOPLE INSIDE THE TUNNEL
Situation Ideal (theoretical) Real
Tunnel environment
and its infrastructuresComplete knowledge Partial knowledge
Psycological feelings No fear Panic
Behaviour Perfectly rational Imperfectly rational
For example, failure in
using the safety
equipment
For example, uncorrect
exit door selection
FDS + EvacPartially behavioural model
• Movement algorithm
• Social force
• Panic model
• Reduced visibility for smoke and obstacles
• Reduced velocity for smoke, incapacitation and death
• Fractional Effective Dose concept
•Tendency to act independently or to form group
• 5 categories of humans with different physical characteristics
• 3 behavioural type (rational, conservative, herding)
Coupling between human behaviour and combustion: multi – agent and CFD simulations for road tunnel fires
Giordana Gai
Sicily, Catania – Syracuse Motorway E45
THE ST. DEMETRIO TUNNEL
7 / 18
Syracuse – Catania tube, L = 2948 m
Infrastructures and devices respecting the European standards
for tunnel longer than 3 km (Directive 2004/54/EC)
Catania
Cortesy of Eng. Luigi
Carrarini, ANAS
Catania – Syracuse tube, L = 2895 m
705 m
Coupling between human behaviour and combustion: multi – agent and CFD simulations for road tunnel fires
Giordana Gai
40 m165 m 175 m 245 m80 m
MESH 1
25x25x25 cm
MESH 2
50x50x50 cm
MESH 2
50x50x50 cm
MESH 3
100x100x100 cm
Jet fanJet fan Jet fanJet fan Jet fan
Emergency
exitPortalFire
source
TRAFFIC FLOW DIRECTION
MESH 3
100x100x100 cm
Catania – Syracuse tube
THE ST. DEMETRIO TUNNEL: FDS+Evac MODEL
8 / 18
Emergency
exit
Portal
140 m 300 m
Bus Vehicle (1 passenger) Vehicle (2 passengers) Vehicle (3 passengers) Vehicle (4 passengers)
Fire source
705 m
Coupling between human behaviour and combustion: multi – agent and CFD simulations for road tunnel fires
Giordana Gai
12%
63%
25%
Agents composition
Rational Conservative Herding
N° tot = 100 AGENTS
• Rational : Adult
• Conservative : Male, Female
• Herding : Child, Elderly
each category has a
different exit selection
preference order
THE ST. DEMETRIO TUNNEL: EVAC MODEL
9 / 18
FAMILIARITY
CONCEPT
Known door
probability
1
Portal
0.5
Emergency exit
Emergency
exit
Portal
140 m 300 m
Fire source TRAFFIC FLOW DIRECTION
Coupling between human behaviour and combustion: multi – agent and CFD simulations for road tunnel fires
Giordana Gai
ASET
Available Safety Egress Time
From ignition to unsustainable
conditions for the egress of
humans:
Required Safety Egress Time
From ignition until the time
the last occupant reaches a
safe place.
It depends on: detection time,
alarm time, pre – movement
time, travel time.
THE PERFORMANCE – BASED APPROACH FOR EGRESS
• Visibility < 10 m
• T > 60°C
• FED > 1
Pre – evacuation
timeDetection time Reaction time
Alarm timeRecognition
timeResponse time
Decision – making process
Movement time
RSET>>
10 / 18
Coupling between human behaviour and combustion: multi – agent and CFD simulations for road tunnel fires
Giordana Gai
0
20
40
CA
R 2
LL
- C
AR
1 R
L
CA
R 4
LL
- C
AR
3 R
L
CA
R 6
LL
- C
AR
5 R
L
CA
R 8
LL
- B
US
RL
CA
R 1
0 L
L -
CA
R 7
RL
CA
R 1
3 L
L -
CA
R 9
RL
CA
R 1
5 L
L -
CA
R 1
1 R
L
CA
R 1
6 L
L -
CA
R 1
2 R
L
CA
R 1
8 L
L -
CA
R 1
4 R
L
CA
R 2
2 L
L -
CA
R 1
9 R
L
CA
R 2
0 R
L
CA
R 2
1 R
L
Time [s]
Formation of the queue inside the tunnel
Left lane (LL)
Right lane (RL)
THE ST. DEMETRIO TUNNEL: EVAC MODEL
0
0.005
0.01
0.015
0.02
0.025
0.03
0.035
0.04
0.045
250 275 300 325 350
Probability
distribution
Time [s]
Pre - evacuation time distribution
Normal distribution
Truncated normal
distribution
ANAS Reference
Time
Probabilistic Approach
Deterministic Approach
11 / 18
Coupling between human behaviour and combustion: multi – agent and CFD simulations for road tunnel fires
Giordana Gai
Fire source
HRR = 6, 30 MW
Jet fans
Volume flow = 15 m3/s
Flow velocity = 15 m/s
EMERGENCY
EXIT
PORTAL
THE ST. DEMETRIO TUNNEL: RESULTING MODEL
12 / 18
HUMAN
CATEGORYCOLOR
Adult Blue
Male Green
Female Red
Child Yellow
Elderly Black
140
300150
Coupling between human behaviour and combustion: multi – agent and CFD simulations for road tunnel fires
Giordana Gai
0
5
10
15
20
25
30
35
0 1000 2000 3000
Time [s]
HRR [MW]
SCENARIOS
13 / 18
Jet fans 1 Jet fan
Emergency exit Emergency exit
BUS FIRE
(30 MW)
2 – CARS FIRE
(6 MW)
• Ideal behaviour
• Real behaviour
0
5
10
15
20
25
30
35
0 1000 2000 3000
Time [s]
HRR [MW]
Emergency exit Emergency exit
• Real behaviour
Coupling between human behaviour and combustion: multi – agent and CFD simulations for road tunnel fires
Giordana Gai
RESULTS (6 MW – fire)
14 / 18
0
20
40
60
80
100
0 500 1000
N°
agen
ts
Time [s]
Ideal egress
Emergency exit
Portal
Total evacuated agents
0
20
40
60
80
100
0 500 1000
N°
agen
ts
Time [s]
Real Egress
Emergency exit
Portal
Total evacuated agents
RATIONAL
BEHAVIOURPANIC
Ideal egress
Real egress
0
20
40
60
80
100
Emergency exitPortal
90
10
5149
Number of
agents
Ideal egress
Real egress
0
20
40
60
80
100
0 200 400 600 800 1000
Number of
evacuated
agents
Time [s]
Ideal Real
Coupling between human behaviour and combustion: multi – agent and CFD simulations for road tunnel fires
Giordana Gai
RESULTS (6 MW – fire)
0
10
20
30
40
50
60
70
80
90
100
0 200 400 600 800 1000 1200
Number of
evacuated agents
Time [s]
15 / 18
0
200
400
600
800
1000
1200 1,011.0939.0
1,120.0 1,125.0
RSET[s]
Yes Jet Fan - Yes Em. Exit No Jet Fan - Yes Em. Exit
Yes Jet Fan - No Em. Exit No Jet Fan - No Em. Exit
Jet Fans 1 Jet Fan
Emergency Exit Emergency Exit
2 – CARS FIRE
(6 MW)
Jet Fans
Em. Exit
1 Jet Fan
Em. Exit
Jet Fans
Em. Exit
1 Jet Fan
Em. Exit
Emergency Exit Emergency Exit
Coupling between human behaviour and combustion: multi – agent and CFD simulations for road tunnel fires
Giordana Gai
Human _ speed
[m/s]*10-4
STREAKS
t = 593 st = 390 s
Portal
Emergency
exit
RESULTS (6 MW – fire)
16 / 18
This is not a general result:
FDS+Evac should be run
using Monte Carlo method
(repeated sampling to
determine the properties of
the phenomenon).
This is only one sampling of
the Monte Carlo simulation.
Coupling between human behaviour and combustion: multi – agent and CFD simulations for road tunnel fires
Giordana Gai
RESULTS (6 MW – fire)
17 / 18
• Visibility _ soot [m] at z = 1.6 m
high visibility upstream the fire source
during the egress time
ASET >> RSET considered scenario
• Humans FED 10-5
very low value, even for those scenarios with 1 jet fan off (emergency ventilation is so strong that there
are no problems of intoxication)
• Temperature slice [°C]
low value (< 60°C) next to
the emergency exit
Coupling between human behaviour and combustion: multi – agent and CFD simulations for road tunnel fires
Giordana Gai
CONCLUSIONS
18 / 18
• The FDS+Evac code is a good tool for the assessment of the emergency egress for road tunnel
fires: fire and smoke influence human motion and their effects imply different choices of the
escape route, intoxication (until the death) and reduction of the walking velocity.
• The possibility of using numerical simulations for egress scenarios is fundamental for the Safety
Engineering, because it is possible to verify the efficiency of the escape routes of many different
types of building (civil building, stadium, tunnel, etc) by controlling the maximum contact force
developed between humans and the most problematic streaks next to the exits.
• For what concerns the S. Demetrio tunnel, the results of the analysis are satisfactory: for the
scenarios examined the emergency egress is complete in 15–20 minutes, without problems of
visibility or intoxication. The backlayering phenomenon occurs only for the bus fire with 1 jet fan
off, but it happens when humans have already gone out.
THE END
V – velocity field
0
20
40
60
80
100
0 200 400 600 800 1000 1200
Number of
evacuated agents
Time [s]
Egress _ 6 MW fire
Ideal and Rational Yes Jet Fan - Yes Em. Exit
No Jet Fan - Yes Em. Exit Yes Jen Fan - No Em. Exit
No Jet Fan - No Em. Exit
12%
63%
25%
Agents composition
Rational
Conservative
Herding
Coupling between human behaviour and combustion: multi – agent and CFD simulations for road tunnel fires
Giordana Gai
Coupling between human behaviour and combustion: multi – agent and CFD simulations for road tunnel fires
Giordana Gai
BACKLAYERING PHENOMENON
Bus fire – 1 jet fan offt = 418 s
t = 594 s
t = 720 s
Coupling between human behaviour and combustion: multi – agent and CFD simulations for road tunnel fires
Giordana Gai
Human _ force
total [N/m]
t = 300 s
t = 360 s
t = 327 s
Coupling between human behaviour and combustion: multi – agent and CFD simulations for road tunnel fires
Giordana Gai
RESULTS (6 MW – fire)
Human _ force
total [N/m]
Block in the bus