Multiscale Modelling of Tunnel Fires (Plenary, Valencia, 2011)
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Transcript of Multiscale Modelling of Tunnel Fires (Plenary, Valencia, 2011)
![Page 1: Multiscale Modelling of Tunnel Fires (Plenary, Valencia, 2011)](https://reader033.fdocuments.net/reader033/viewer/2022051816/5477bcfd5806b50b198b4660/html5/thumbnails/1.jpg)
Multiscale Modelling
of Tunnel Fires
Dr Guillermo Rein
School of Engineering
University of Edinburgh
Contributions from F Colella, R Borchiellini,
V Verda, R Carvel and J Torero
Valencia, June 1, 2011
www.sp.se
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�This work is based on the PhD Thesis of
Francesco Colella (2010)
�It is a joint effort between Politecnico di
Torino and University of Edinburgh
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“A case can be made for fire being, next to the life processes,
the most complex of phenomena to understand”
Prof. Hoyt C. Hottel, MIT, 1984
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1050650450110010005003302420TOTAL
200202002705501560Underground
10037030180701402101160Roads
7502602206503803601051200Railways
SpainNorwayUKFranceGermanySwissAustriaItaly
Lengths of EU Tunnels (km)
Tunnels are key infrastructure
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Tunnel Fires are rare but costly
Some important examples:
�Great Belt (Denmark, 1994)
�Channel (UK-France, 1996)
�Mont Blanc (Italy-France, 1999)
�Kaprun (Austria, 2000)
�Gotthard (Italy-Swiss, 2001)
�Channel (2006)
�Channel (2008)
�…
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0
20
40
60
80
100
120
1940 - 1969 1970 - 1979 1980 - 1989 1990 - 1999 2000 - 2007
accidents injuredscasualties
> 400
# o
f e
ve
nts
period
Tunnel Fires are rare but costly
Colella, Multiscale Modelling of Tunnel Ventilation Flows and Fires, PhD thesis, Politecnico di Torino, 2010. http://hdl.handle.net/1842/3528
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� Avoid any harm to occupants and rescue teams
�Minimize disruption of transport and economic
costs (=minimize damage to infrastructure)
Tunnel fire emergencies must be managed by a
global safety system and strategies capable of
integrating:
1. Detection
2. Evacuation
3. Ventilation - Smoke management
4. Suppression and Fire fighting
Tunnel Safety Strategy
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Ventilation System
�Objective: maintaining tenable conditions to
allow safe evacuation and rescue procedures
as well as fire fighting
� Plays a crucial role within the safety strategy
� Most widespread safety system in tunnels
� Normal operating conditions: small part of the system
use for maintaining visibility and pollutants at
acceptable levels
Wu and Bakar 2000, FSJ
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Tunnel Safety Strategy
Vehicle Traffic
Smoke evacuation
Forced ventilation
Safe evacuation and rescue path
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Back-layering
� Back-layering: reverse flow
of smoke against the
longitudinal ventilation
� Critical velocity: minimum
longitudinal air flow
preventing back-layering
Oka and Atkinson, 1995, FSJ
Grant et al, Phil. Trans R Soc Lond A 1998
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Ventilations Systems
�Longitudinal: forced airflow pushes smoke
along the main tunnel gallery to end
shaft/portal
�Transversal: forced airflows push/pull smoke
out of gallery at distributed location to
auxiliary duct system
�Hybrid: some combination of the two
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Generating Ventilation Flows
�The response of the ventilation system during a fire is a complex problem
�Calculation of airflows is a must designers, owners, operators and manufacturers
�Resulting airflow depends on combination of:
�Active ventilation devices (jet fans, axial fans)
�Tunnel layout (long domain, section, shafts)
�Fire-induced flows
�Portal atmospheric conditions (wind, rain)
�Large obstacles (stopped vehicles, wreck)
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Generating Ventilation Flows
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� Domain split in branches and nodes
� Mass conservation in each node
� Momentum conservation in each branch (Bernoulli)
� Fans are source of momentum (pv curves by
manufacturer?)
� Fire is a source of heat
1D Network model
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Fan Characteristic Curve
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1D Network model
� Fast simulations (within seconds in a desktop PC)
� Predict the global behaviour
� Industry uses it to explore wide design options
BUT
� Need calibration constants (requires full scale testing)
� ballpark figures (does not predict accurate behaviour)
� Assumes flow is 1D (not valid for fire or fans)
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CFD model
� Continuity:
� Momentum:
� Energy:
� + Turbulence
0̀=⋅∇+∂∂
uρρt
( ) ∑+⋅∇+−∇=⋅∇+∂
∂Sτuu
up
tρρ
[ ] ( )( ) ( ) ∑+⋅+∇⋅∇=+⋅∇+∂∂
Eeff STkpEEt
uτu effρρ
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�Fire modelled as rectangular obstruction releasing hot combustion products from the top and extracting cold air from the sides
�Dimensions scale with fire Froude scaling
( )( )∞−
−=TTc
Qm
GpG
λ1&&
CFD Fire Source
305
400
550550
700600
700900
9501000
1000
Longitudinal coordinate [m]
Ver
tical
Ele
vatio
n[m
]4.75 5 5.25 5.5 5.75
0
0.05
0.1
0.15
0.2
0.25
temperature: 300 350 450 550 650 750 850 950
30 kW Fire:Symmetry plane
350
325
350
350
325
450
325
375
600
Longitudinal coordinate [m]
Ver
tical
Ele
vatio
n[m
]
4.75 5 5.25 5.5 5.750
0.05
0.1
0.15
0.2
0.25
temperature: 300 350 400 450 500 550 600 650 700
3 kW Fire:Symmetry plane
Colella, Multiscale Modelling of Tunnel Ventilation Flows and Fires, PhD thesis, Politecnico di Torino, 2010. http://hdl.handle.net/1842/3528
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Grid Independence Study
Colella, Multiscale Modelling of Tunnel Ventilation Flows and Fires, PhD thesis, Politecnico di Torino, 2010. http://hdl.handle.net/1842/3528
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CFD model
� 3D flow field from first principles
� Accurate results
� Industry uses to verify a pre-approved design
BUT
� Slow simulations (~1.5 km takes 1 month to solve)
� Not affordable for long tunnels (solution time for 24 km?)
� Cannot study all ventilation strategies (only time for 1 or 2 cases)
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rough1D
Co
mp
uta
tio
na
l ti
me
Tunnel Length
CFDaccurate
Is there
anything in
between?
CFD vs. 1D computing time
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CFD model
1D model
1D model
Multiscale1D Regions:
� Low velocity/temperature gradients
� 1D models can be used
3D Regions:
� High velocity/temperature
gradients
� CFD models must used
L’
L’’
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Tunnel Portal
CFD 3D jet fan module
1-dimensional network
1-dimensional network
Tunnel Portal
Multiscale – Jet fans
3D region
1D region
1D region
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Multiscale – Fire source
3D region
1D region
1D region
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Multiscale Modelling� Dramatic reduction of the computational time
by 2 orders of magnitude
� Full coupled ventilation/fire simulation of the whole domain takes a few hours
� Hundreds of simulations can be done in a week
� Fast/accurate tool allows to explore multiple scenarios and design question not possible before: � What is the best design for a wide range of conditions?� How many jet fans must be installed?
� What is different fire sizes are considered?
� What is the redundancy of the system?
� What is the impact of the wind conditions?
� Would a fire change the tunnel airflow resistance?
� How fast would the system response to activation?
� How much faster than fire growth?
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L’
L’’
Jet fan pairs
Near fieldCFD model
1D model
1D model
L=?
1D/3D interface location?
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L’
L’’
Correct 1D/3D interface location
Jet-fan discharge
L3D[m]
Mas
sflo
wra
te[k
g/s]
Err
or[%
]
0 100 200 3000
10
20
30
40
50
60
70
80
90
100
110
120
0
10
20
30
40
50
60
70
80
90
100
mass flow rateerror
L≈17 times the diameter L≈12 times the diameter
Fire source
Colella et al., A Novel Multiscale Methodology for Simulating Tunnel Ventilation Flows during Fires, Fire Technology 47, pp. 221-253, 2011. doi:10.1007/s10694-010-0144-2
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Dartford Tunnels, London
� Under Thames river
� 1.5 km long
� Hybrid ventilation system
� Jet fans + supply & extraction shafts
� West Tunnel, built in 1963:
� 28 jet fans
� Diam 9.5 m
133m 1280m 157m
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Cold Flow Validation
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Cold Flow Validation
Colella et al., Calculation and design of tunnel ventilation systems using a two-scalemodelling approach, Building and Environment 44, 2009
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System wide predictions
� Cold flow
� Multiple (x8) ventilation strategies studied
� Redundancy levels can be studied (how many jet fans can be disable while system provides safe conditions?)
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Multiscale vs. CFD
� full CFD
� Multiscale
Scenario: 30 MW fire and 3 Jet fan pairs activated
Colella et al., A Novel Multiscale Methodology for Simulating Tunnel Ventilation Flows during Fires, Fire Technology 47, pp. 221-253, 2011. doi:10.1007/s10694-010-0144-2
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Throttling Effect� Additional flow resistance imposed by the fire size (buoyancy, gas expansion and hot smoke aerodynamics)
� Reported experimentally in 1979 but hardly ever use
� eg, 100 MW fire decrease airflow by 30%
0
1
2
3
4
5
6
0 20 40 60 80 100 120
Fire size [MW]
# j
et
fan
pa
irs� Requires
coupling of fire and ventilation
� Can be significant for large fires and long tunnels
Jet fans needed to reach critical velocity
Colella et al., A Novel Multiscale Methodology for Simulating Tunnel Ventilation Flows during Fires, Fire Technology 47, pp. 221-253, 2011. doi:10.1007/s10694-010-0144-2
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time
Detection/Activation:
Transient Problem
HRR
4 min
De
tect
ion
ra
ng
eVentilation #1?
2 min
Ventilation #2?
Ventilation #3?
� Only after fire detection, ventilation is activated
� Acceleration of the mass of air in tunnel while fire is growing
� Race between fire growth and ventilation response
30 MW
15 MW/min
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Ventilation Response in time
Colella et al., Time-dependent Multiscale Simulations of Fire Emergencies in Longitudinally Ventilated Tunnels, Proceedings 10th International Symposium on Fire Safety Science, 2011
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1 min 59 s after ignition / 1 s from activation
70 m back –layering
330320 310
Longitudinal coordinate [m]
elev
atio
n[m
]
50 100 150 200 2500
2
4
6
temperature: 300 320 340 360 380 400
-0.6 -0.4 0.6
0
0
0.41
Longitudinal coordinate [m]
elev
atio
n[m
]
50 100 150 200 2500
2
4
6
x-velocity: -1 -0.8-0.6-0.4-0.2 0 0.2 0.4 0.6 0.8 1
Transient Results
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400 500 600 7000
5
100 m back –layering
Scenario 1: 3 Jet fan pairs
Longitudinal coordinate [m]400 500 600 700
0
5
0 m back –layering
≈ 0 m back –layering
Scenario 3: 10 Jet fan pairs
Ventilation scenario 2
400 500 600 7000
5
Scenario 2: 5 Jet fan pairs
70 m back –layering
Transient Results
3 min after ignition / 1 min after activation
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Ventilation scenario 1
400 500 600 700 800 900 1000 1100 12000
5
Transient Results
Scenario 1: 3 Jet fan pairs
400 500 600 700 800 900 1000 11000
5
Scenario 2: 5 Jet fan pairs
1200
400 500 600 700 800 900 1000 11000
5
Scenario 3: 10 Jet fan pairs
1200
5 min after ignition / 2 min after activation
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Detection vs. Ventilation Requirements
� Evaluation of the design options in terms of detection technology
� For a given required time to remove back-layering, options range from low tech detection + many jet fans , to high tech detection + few jet fans
0
50
100
150
200
250
300
350
400
2 3 4 5 6 7 8 9 10 11 12 13 14# active jet fan pairs
ela
pse
d t
ime
fro
m f
ire
ou
tbre
ak
[s] Scenarios 1, 2, 3; TD=2min
Scenarios 4, 5, 6; TD=2.5min
Scenarios 7, 8, 9; TD=1.5minDetection time 1.5 min
Detection time 2.0 min
Detection time 2.5 min
Colella et al., Time-dependent Multiscale Simulations of Fire Emergencies in Longitudinally Ventilated Tunnels, Proceedings 10th International Symposium on Fire Safety Science, 2011
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Conclusions: efficient, accurate & fast
� Multiscale is as accurate as full CFD
� Dramatic reduction of the computational time (by 2
orders of magnitude)
� Hundreds of simulations can be done in a week
� Fast/accurate tool allows to explore multiple
scenarios and design question not possible
before
� Full coupling fire and ventilation
� Throttling effect is significant
� Allows for transient problems and full ventilations
strategies
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Thanks!for more information
Colella et al., A Novel Multiscale Methodology for Simulating Tunnel Ventilation Flows during Fires, Fire Technology 47, pp. 221-253, 2011. doi:10.1007/s10694-010-0144-2
Colella et al., Analysis of the ventilation systems in the Dartford tunnels using a multi-scale modelling approach, Tunneling and Underground Space Technology 25, 2010 doi:10.1016/j.tust.2010.02.007
Colella et al., Calculation and design of tunnel ventilation systems using a two-scalemodelling approach, Building and Environment 44, 2009 doi:10.1016/j.buildenv.2009.03.020
Colella et al., One dimensional and multi-scale modelling of tunnel fires and ventilation flows, Chapter in: The Handbook of Tunnel Fire Safety, ICE Publishing (in press), 2011.
Colella, Multiscale Modelling of Tunnel Ventilation Flows and Fires, PhD thesis, Politecnico di Torino, 2010. http://hdl.handle.net/1842/3528
Colella et al., Time-dependent Multiscale Simulations of Fire Emergencies in Longitudinally Ventilated Tunnels, Proceedings 10th International Symposium on Fire Safety Science (in press), June 2011, Maryland.
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Cold flow – Norfolk Tunnel AU
Prediction vs. Measurements
� Two one-directional tunnels in Sydney (AU)
� 460 m long
� 6 jet fan pairs (34 m/s discharge velocity) 80 m spaced
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Multiscale – coupling procedure
-0.080
-0.070
-0.060
-0.050
-0.040
-0.030
-0.020
-0.010
0.000
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19
0.00
0.50
1.00
1.50
2.00
2.50
3.00
3.50
Total pressure at inlet
Mass flow rate at inlet
[kg/s] [Pa]
Multiscale iterations - K