CFD Fire modelling
at EDF
Inaugural UK Fire & Smoke Modelling Forum
London Fire Brigade
London, 03 November 2017
Fatiha Nmira
Abdenour Amokrane
Bertrand Sapa
Fire project
Martin Ferrand
Nicolas Tonello
Code_Saturne team
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Outline
1. CONTEXT
2. CODE_SATURNE
3. FIRE APPLICATIONS
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EDF COVERS ALL
ELECTRICITY-RELATED
ACTIVITIES
• Generation
• Transmission, distribution
• Trading, supply
• Energy services
LEADER IN LOW-CARBON
POWER GENERATION
• N°1 in the world for nuclear power generation
• N°1 in Europe for renewable energy generation
• N°3 in Europe for energy services
WORLD’S n° 1
ELECTRICITY
COMPANY
37.6 million customers
worldwide
159,112 employees
€75 billion sales
619.3TWh electricity
generation
134.2GWe
6%Other
renewables
16%Hydropower
9%Combined-cycle gas
and cogeneration
15%Fossil-fired excl. gas
54%Nuclear
CAP2030: Double
EDF capacity in
renewable energy
EDF Group emissions95 g CO2 /kWh
EDF France emissions15 g CO2 /kWh
EDF GROUP AT A GLANCE
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Renuda
• CFD Specialists
• Consulting, Software development, Training
• Fully independent
• UK, France, Germany
• Blue Chip Clients
• Applications from single phase pipe flow to
turbomachinery, multiphase flow, coupled heat transfer,
mechanical calculations
• Industries: transport, automotive, processing, nuclear,
power generation, civil engineering
• Compete on
• Skills
• Difficult problems
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Code_Saturne
� Code_Saturne is an open source, 3D general CFD solver in continuous development by
EDF R&D
� Based on a co-located finite volume scheme for unstructured meshes and mostly focused
on incompressible flows, it has been developed since 1997 and distributed under a free
software GPLV2 license since 2007
� It features several turbulence models, from RANS to LES
� A number of specific physical models are also available as “modules”, including
combustion, semi-transparent radiative transfer, Lagrangian particle-based modelling,
electrics arcs, atmospheric flows and turbomachines
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Multi-physics
Open source GUI
HPC
Advanced pre/post
processing Salome_CFD platform
CFD - Finite
Volume with
polyhedral
meshes
Verification &
Validation
EDF R&D: development of Code_Saturne
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Fire risk at EDF
� Fire: internal hazard with the highest frequency
� Risk of damaging important safety components
� Risk of containment break and radioactive emissions outside
� Combustibles � Fire sources
� Electric cables
� Electric equipment (cabinets, …)
� Oil (turbines, pumps, transformers)
� Diesel (support generator)
� Hydrogen (alternator)
� Electrical (short-circuit, overvoltage, arcing
fault,…)
� Mechanical (friction,…)
� Thermal (spark, hot spot, welding, heating, …)
� Chemical (solvents,…)
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Fire risk at EDF
� EDF, as an operator, is responsible for the safety of its Nuclear Power
Plants
� Safety issue: staff, civilians, environment, plants
� Economics issue due to maintenance cost and reactor shutdown
� Fire risk prevention
� EDF has defined a doctrine to prevent the fire risk and guaranee the safety of
its Nuclear Power Plants
� R&D position in EDF: engineering support
� Fire doctrine defence for the current NPPs
� Development of rules for the next reactors
� Development of modelling tools and experimental apparatus
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Fire risk assessment
� Proof of Fire risk control
� Fire risk analysis: functional analysis and common modes
� Hazard study using numerical modelling
� MAGIC: reference code for fire modelling at EDF
� Zonal code which deals with main physical phenomenon in
fire (stratification, pool, plume, mass and energy transfer,
concentrations, …)
� Manage 95 % of the studies
� Limits dues to modelling hypothesis
� CFD codes: go beyond the zonal codes’ limitations
� Complex geometries, large volumes
� Local approach that can manage more physical phenomena:
extinction /reignition, soot production / transport / deposit, …
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Physical phenomena in a flame
Thermal plume
Flame
Convection to environment
Radiation to
environment
Air
entrainment
Convective transfer
Pyrolysis
Combustible
Radiative feedback
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Physical phenomena in a fire compartment
4. Stratification with hot
smoke and fresh air layer6. flame, smoke and walls radiation �
fire propagation
1. Combustion with
diffusion flame5. Pyrolysis increase due
to radiative feedback
2. Plume =
pump
3. Air
entrainment
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Physical phenomena in a fire compartment
Fire outside
Well ventilated compartment fire
Under ventilated compartment fire
Time
Stratification/walls
Limitation by
oxygen
Extinction by
lack of oxygen
Extinction by lack of
combustible
Time
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EDF’s chosen approach
� Development of Code_Saturne for fire modelling since 2008
� Thermo-hydraulic model, used for industrial combustion
� Work on physical modelling and numerical methods
� Process of Verification & Validation
� Now at the state of the art of industrial fire codes
� Good results for well ventilated fire compartment with a prescribed heat
release rate ( ~ MW, X00 m3, O2 > 12 %)
� Collaborations
� CNRS Marseille (IUSTI) radiation and soot
� INERIS combustion and pyrolysis
� CNRS Poitiers fire and combustion
� Phenomena to be considered
� Natural convection
� Combustion
� Turbulence
� Radiation (gas and soot)
� Fluid/solid thermal exchanges (convective and radiative)
� Pressure and ventilation interaction
� Soot formation, transport and deposit
� Pyrolysis for solid and liquid combustibles
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Reference modelling
� Combustion infinitely fast chemistry with a presumed PDF (rectangle + 2 Dirac)
� Turbulence : k-ε model taking into account the buoyancy
� Radiative transfer
� Grey gases hypothesis (CO2, H2O and soot)
� Solved with the Discrete Ordinate Model (DOM)
� Soot models available
� Soot yield
� Moss semi-empirical model (precursor number and soot volume fraction)
� Smoke Point model
� Fluid/solid thermal exchange: 1D conduction model
� Next objectives :
� Extend Code_Saturne with more physical models to deal with extinction / reignition, soot production /
transport / deposit, pyrolysis, …)
� Deployment to EDF engineering in 2021
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Validation examples with Code_Saturne
Propane flame (40 kW, 30 cm)
Gengembre, Comb. Sci. Th. (1984)
Methane flame (2 MW, 1 m)
Tieszen, Comb. Flame (2004)
Methane burner (150 kW, 20 m3)
Steckler et al., NBSIR Report (1982)
Dodecane fire (500 kW, 120 m3, 5 h-1)
OECD PRISME fire tests
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Validation examples with Code_Saturne
� Axisymmetric turbulent jets with variable density (helium, air, CO2)
� Amielh et al. et Djeridane et al., Phys. Fluids (1996)
� Panchapakesan et Lumley, J. Fluid. Mech., (1993) Part 1 et 2
� Thermal plume
� Shabbir et George, J. Fluid Mech., (1994)
� Helium plume
� O’Hern et al., J. Fluid Mech., (2005)
� Laminar diffusion flames (CH4, C2H4, C3H8)
� Smyth, http://www.fire.nist.gov/fire/flamedata/
� Pool fires
� Flames of CH4 (D=30 cm, 14-58 kW) McCaffrey, NBSIR Report (1979)
� Flames of C3H8 (D=30 cm, 22-38 kW) Gengembre, Comb. Sci. Th. (1984)
� Flame of CH4 (D=1 m, 2.07 MW) Tieszen, Comb. Flame (2004)
� Flame of C7H16 (D=1.17 m, 2.34 MW) Gutiérrez-Montes et al. Buil. Env. (2009)
� Compartment fires
� Steckler et al., NBSIR Report (1982), (CH4, D=30 cm, 31-158 kW)
� NIST/NRC fire tests
� OECD PRISME fire tests
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Numerical methods extension
� Velocity/Pressure coupling at free boundary
� 10 ∅ domain expensive
� What velocity and pressure at 4 ∅ of a flame ?
� Bernoulli between upstream and the free
boundary
� Dilatation of gas mixture
� Algorithms to manage the temporal variation of
density
� Controls the flame dynamics
� Second order modelling in time and space
Uncoupled Coupled
Plane helium plume
Axisymmetric helium plume
Without With
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Physical modelling extensions
� Radiative transfer modelling
� Spectral method development (FSCK)
� Validation on laminar flames
� Validation on turbulent flames in progress
� Radiation/soot/turbulence interactions (TRI)
� Important for the emission term and radiative fluxes, impact
on flame structure
� Transported Probability Density Function method for fire
modelling (PhD thesis D. Burot – IUSTI Marseille, January 2017)
� Proper turbulent closure of the emission turbulence radiation
� Combustion/radiation/soot/turbulence interactions
� Extending the method to finite detailed chemistry
� Objectiv : to model unburnt gases production and combustion
in under-ventilated fires
z /dn( - )
f v,s(ppm)
f v,s,rms(ppm)
0 5 0 1 0 0 1 5 0 2 0 00
0 .5
1
1 .5
2
2 .5
3
3 .5
4
0
1
2
3
4
5
6
7
N u m . ; fv , s
P re su m e d P D F : fv , s
N um . ; fv , s , rm s
E x p . ; fv , s
E x p . ; fv , s , rm s
b )
z (m )
qrad,w(W
/m2)
f S,EQ(-)
0 0 .25 0 .5 0 .7 5 10
5000
10000
15000
20000
0
1E -05
2E -05
3E -05
4E -05
5E -05F u l l
N o C orr.
Ex p .
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Example of industrial studies
� GMPP fire modelling in the EPR BR
� 50 L oil pool fire at GMPP at the bottom of the GMPP
� 250 targets studied: cables, captors, electrical cabinets, valves, doors, …
� 20 cm cells � 10 M cells
� 1 day of calculation on 392 cores
Fire location
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Target: Under ventilated compartment fires
� Under ventilated compartment fires
� Mechanically ventilated compartment fires
� Naturally ventilated compartment fires
� Large scale flames (~ MW)
� Small scale flames (~ 40 kW)
� Laminar flames
� Unsteady turbulent helium plume
� Steady turbulent thermal plume
VA
LID
ATIO
N
Weakly compressible algorithm
Free boundary conditions
o
o
o
o
Mean room pressure
Mechanical ventilation
Soot production o
Wall thermal exchanges o
Developments Validation test cases
Radiative transfer o
o
o
Pyrolysis
Soot/unburned gases
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Ongoing work
� Next year:
� Under ventilated combustion: combustion/radiation/soot/turbulence
interactions
� LES : development, validation, …
� Next decade:
� Pyrolysis
� Sprinkles
� Soot deposit
�…
Thank you for your
attention
Feel free to contact us
Bertrand SAPA (EDF R&D): [email protected]
Martin FERRAND (EDF R&D): [email protected]
Nicolas TONELLO (RENUDA): [email protected]
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