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): bertrand.sapa@edf.fr

Martin FERRAND (EDF R&D): martin.ferrand@edf.fr

Nicolas TONELLO (RENUDA): nicolas.tonello@renuda.com