Coupling between human behaviour and combustion

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


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NON –

STRUCTURAL

COMPONENT

Tunnel

INTRODUCTION

Human behaviour

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STRUCTURAL

SYSTEM

SAFETY

STRUCTURAL

COMPONENT

PEOPLE

ACTION : Fire


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INTRODUCTION

Mont Blanc Tunnel fire (1999): 39 people died

(11.6 km long single – bore bi – directional tunnel)

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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


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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

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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)


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SCENARIO – BASED APPROACH

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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.


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HUMAN BEHAVIOURAL MODEL

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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)


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Sicily, Catania – Syracuse Motorway E45

THE ST. DEMETRIO TUNNEL

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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


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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

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Emergency

exit

Portal

140 m 300 m

Bus Vehicle (1 passenger) Vehicle (2 passengers) Vehicle (3 passengers) Vehicle (4 passengers)

Fire source

705 m


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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

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FAMILIARITY

CONCEPT

Known door

probability

1

Portal

0.5

Emergency exit

Emergency

exit

Portal

140 m 300 m

Fire source TRAFFIC FLOW DIRECTION


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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>>

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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

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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

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HUMAN

CATEGORYCOLOR

Adult Blue

Male Green

Female Red

Child Yellow

Elderly Black

140

300150


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0

5

10

15

20

25

30

35

0 1000 2000 3000

Time [s]

HRR [MW]

SCENARIOS

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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


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RESULTS (6 MW – fire)

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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


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0

10

20

30

40

50

60

70

80

90

100

0 200 400 600 800 1000 1200

Number of

evacuated agents

Time [s]

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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


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Human _ speed

[m/s]*10-4

STREAKS

t = 593 st = 390 s

Portal

Emergency

exit


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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.


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• 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


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CONCLUSIONS

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• 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


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BACKLAYERING PHENOMENON

Bus fire – 1 jet fan offt = 418 s

t = 594 s

t = 720 s


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Human _ force

total [N/m]

t = 300 s

t = 360 s

t = 327 s


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Human _ force

total [N/m]

Block in the bus

Education

Coupling between human behaviour and combustion