simulation de la pyrolyse de polymères non-charbonneux...
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Simulation de la pyrolyse de polymères non-charbonneuxavec le code ISIS
GDR Feux — Verneuil en Halatte
G. Boyer
IRSN/PSN-RES/SA2I/LIE
09/03/2017
Introduction
Purposes of the present work Perform coupled pyrolysis/CFD simulations to simulate reference cone calorimeter
experiments
Perform simulations as predictive as possible
Evaluate the relevance of state-of-the-art models
Identify the main lacks
Considered test cases:I PMMA, HIPS, HDPE tested under cone calorimeter (Stoliarov et al., 2009: non-charring
polymers)I Several imposed heat fluxes and sample thicknesses consideredI Gasification experiments also considered to validate the pyrolysis model separatelyI Thermal and thermokinetic input parameters provided by microscale characterization
Available experimental data for comparisonI Heat release rate, mass loss rate per unit areaI . . . and almost nothing else
Introduction - p.2
Outline
1 Introduction
2 Models used for coupled simulations
3 Pyrolysis simulations
4 Conclusion and future enhancements
Introduction - p.3
Outline
1 Introduction
2 Models used for coupled simulations
3 Pyrolysis simulations
4 Conclusion and future enhancements
Models used for coupled simulations - p.4
Pyrolysis modelling
Hypotheses
One-step degradation of a non-charring poymer P , intrinsic density ρ0σ
Pyrolysis volatiles G1, . . . GNγ , mass yield νmassγ,j
′′
Account for the surface regression and the solid deformation (velocity ue,σ)
1D heat transfer: conduction, radiation. Porosity neglected
Semi-transparent material, gray surface
Mass conservation: local reaction rate ωσ = Aσ exp(−Ea/RT )ρ0σ such as
(1) ∂tρ0σ + ∇ ·
(ρ0σue,σ
)= −ωσ,
∫ΓSF
m′′γdΣ =
∫ΩS
Nγ∑j=1
νmassγ,j
′′ωidΩ
Total enthalpy conservation
(2) ∂t(ρ0σhσ) + ∇·
(ρ0σhσue,σ
)+ ∇·
Nγ∑j=1
ργ,jhγ,jue,γ,j
= ∇·(λS∇TS − qrad,S) ,
1D integration of the RTE (non-spectral S2 model)Models used for coupled simulations - p.5
Non-coupled applications
Test cases: gasification experiments No flame flux
Relevance of the 1D modelling: uniform surface heat fluxes
Convective flux : Holman correlation for cooled flate plate
Radiative flux: account for the surface emissivity and absorption
S2 model: qrad,S decomposed into upstream and downstreamfluxes q+
rad,S and q−rad,S Interface boundary condition:
(3) − λσ∇T · n = −hexchSF (TF − TSF ) +
πεσ(1 + n2σ)I0(TSF ) − εσ(qimp − q+
rad,S)
hexchSF ' 8.5 W/m2/K for usual interface temperatures andTF = 300 K
ΩKS
TKS•••••
K• ΓMF
TSF
•
q+rad,S
q−rad,S
Models used for coupled simulations - p.6
Coupled applications
Test cases: cone calorimeter experiments CFD modelling of the flame
Turbulence: pre-calibrated k − ω-BSL RANS model (Menter, 1994), EDC modelling ofthe reaction rate
Soot production: soot yield included in the combustion reaction, no soot combustion
Absorption properties : WSGG model for the gas phase; constant soot absorption
FVM integration of the Radiative Transfer Equation
Interface boundary condition
(4) − λS∇TS · n + ργDTγ∇TF · n =
− πεσ(1 + n2σ)I0(TSF ) + εσ(q+
rad,F + q−rad,S)
with ργDTγ = λγ + µtcp,γ/σT,γ,t
ΩF
ΩS
ΓMF
Γa
n
ΩKS
TKS•••••
K•
TSF
•
Models used for coupled simulations - p.7
Outline
1 Introduction
2 Models used for coupled simulations
3 Pyrolysis simulations
4 Conclusion and future enhancements
Pyrolysis simulations - p.8
Pyrolysis model validation
Test case: gasification experiments, (Stoliarov et al., 2009)
0.01 m2 non-charring materials samples — PMMA, HIPS, HDPE,
Arrhenius laws, heat of pyrolysis, specific heat, conductivity, etc. provided by microscalecharacterisations
Measured surface emissivity, approximate absorption coefficient
Gasification experiments: no flame, no flame flux to assess
Predictive pyrolysis simulations
t (s)
m′′ γ(kg/m
2/s)
PMMA
t (s)
m′′ γ(kg/m
2/s)
HIPS
t (s)
m′′ γ(kg/m
2/s)
HDPE
Figure: Comparison between gasification experiments and numerical simulation results. ():measured mass loss rate per unit area (m′′γ); (—): simulated mass loss rate per unit area.
xL = 8.55 mm, qimp = 52 kW/m2.Pyrolysis simulations - p.9
Coupled simulations: quantitative comparison with experiments
Pre-calibration of the turbulent combustion model constants Comparison to the Mc Caffrey flame (Mc Caffrey, 1979), Qγ = 22 KW/m2.
Inputs: Cµ (plume structure), Rf (buoyancy), CEBU (combustion)
Best results in terms of temperature and axial velocity: Cµ = 0.07, Rf = 0.1 andCEBU = 2
Test cases: cone calorimeter experiments, Stoliarov et al.
Still PMMA, HIPS, HDPE, 0.01 m2 samples
Sample thickness : 3.2, 8.5 and 26.5 mm; imposed heat flux: 25, 50 and 75 kW/m2
Comparison:I experimental HRR vs. numerical m′′γ∆hcI radiative fraction (Tewarson, SFPE Handbook)
Additional analysis criteriaI heat flux at the sample surfaceI flame structure
Pyrolysis simulations - p.10
Coupled simulations: quantitative comparison with experiments
Pre-calibration of the turbulent combustion model constants Comparison to the Mc Caffrey flame (Mc Caffrey, 1979), Qγ = 22 KW/m2.
Inputs: Cµ (plume structure), Rf (buoyancy), CEBU (combustion)
Best results in terms of temperature and axial velocity: Cµ = 0.07, Rf = 0.1 andCEBU = 2
Test cases: cone calorimeter experiments, Stoliarov et al.
Still PMMA, HIPS, HDPE, 0.01 m2 samples
Sample thickness : 3.2, 8.5 and 26.5 mm; imposed heat flux: 25, 50 and 75 kW/m2
Comparison:I experimental HRR vs. numerical m′′γ∆hcI radiative fraction (Tewarson, SFPE Handbook)
Additional analysis criteriaI heat flux at the sample surfaceI flame structure
Pyrolysis simulations - p.10
Coupled simulations: comparison with experiments
0 100 200 300 400 500 6000
500
1000
1500
2000
t (s)
q′′ γ(kW/m
2)
PMMAxL = 3.2 mmqimp = 25 KW/m2
0 100 200 3000
500
1000
1500
2000
t (s)
q′′ γ(kW/m
2)
PMMAxL = 3.2 mmqimp = 50 KW/m2
0 50 100 150 200 2500
500
1000
1500
2000
t (s)
q′′ γ(kW/m
2)
PMMAxL = 3.2 mmqimp = 75 KW/m2
0 500 1000 15000
500
1000
1500
2000
t (s)
q′′ γ(kW/m
2)
PMMAxL = 8.55 mmqimp = 25 KW/m2
0 200 400 6000
200
400
600
800
1000
t (s)
q′′ γ(kW/m
2)
PMMAxL = 8.55 mmqimp = 50 KW/m2
0 100 200 300 400 5000
500
1000
1500
2000
t (s)
q′′ γ(kW/m
2)
PMMAxL = 8.55 mmqimp = 75 KW/m2
0 1000 2000 30000
500
1000
1500
2000
t (s)
q′′ γ(kW/m
2)
PMMAxL = 26.5 mmqimp = 25 KW/m2
0 500 1000 15000
500
1000
1500
2000
t (s)
q′′ γ(kW/m
2)
PMMAxL = 26.5 mmqimp = 50 KW/m2
0 500 10000
500
1000
1500
2000
t (s)q′′ γ(kW/m
2)
PMMAxL = 26.5 mmqimp = 75 KW/m2
Figure: PMMA. (): measured MLRPUA; (—): simulated MLRPUA.
Pyrolysis simulations - p.11
Coupled simulations: comparison with experiments
0 100 200 300 400 500 6000
500
1000
1500
2000
t (s)
q′′ γ(kW/m
2)
HIPSxL = 3.2 mmqimp = 25 KW/m2
0 100 200 3000
500
1000
1500
2000
t (s)
q′′ γ(kW/m
2)
HIPSxL = 3.2 mmqimp = 50 KW/m2
0 50 100 150 200 2500
500
1000
1500
2000
t (s)
q′′ γ(kW/m
2)
HIPSxL = 3.2 mmqimp = 75 KW/m2
0 500 1000 15000
500
1000
1500
2000
t (s)
q′′ γ(kW/m
2)
HIPSxL = 8.55 mmqimp = 25 KW/m2
0 200 400 6000
500
1000
1500
2000
t (s)
q′′ γ(kW/m
2)
HIPSxL = 8.55 mmqimp = 50 KW/m2
0 100 200 300 400 5000
500
1000
1500
2000
t (s)
q′′ γ(kW/m
2)
HIPSxL = 8.55 mmqimp = 75 KW/m2
0 1000 2000 30000
500
1000
1500
2000
t (s)
q′′ γ(kW/m
2)
HIPSxL = 26.5 mmqimp = 25 KW/m2
0 500 1000 15000
500
1000
1500
2000
t (s)
q′′ γ(kW/m
2)
HIPSxL = 26.5 mmqimp = 50 KW/m2
0 500 10000
500
1000
1500
2000
t (s)q′′ γ(kW/m
2)
HIPSxL = 26.5 mmqimp = 75 KW/m2
Figure: HIPS. (): measured MLRPUA; (—): simulated MLRPUA.
Pyrolysis simulations - p.11
Coupled simulations: comparison with experiments
0 100 200 300 400 500 600 7000
500
1000
1500
2000
2500
t (s)
q′′ γ(kW/m
2)
HDPExL = 3.2 mmqimp = 25 KW/m2
0 100 200 300 4000
500
1000
1500
2000
2500
t (s)
q′′ γ(kW/m
2)
HDPExL = 3.2 mmqimp = 50 KW/m2
0 50 100 150 200 250 3000
500
1000
1500
2000
2500
t (s)
q′′ γ(kW/m
2)
HDPExL = 3.2 mmqimp = 75 KW/m2
0 500 1000 15000
500
1000
1500
2000
2500
t (s)
q′′ γ(kW/m
2)
HDPExL = 8.55 mmqimp = 25 KW/m2
0 200 400 6000
500
1000
1500
2000
2500
t (s)
q′′ γ(kW/m
2)
HDPExL = 8.55 mmqimp = 50 KW/m2
0 100 200 300 400 5000
500
1000
1500
2000
2500
t (s)
q′′ γ(kW/m
2)
HDPExL = 8.55 mmqimp = 75 KW/m2
0 1000 2000 3000 40000
500
1000
1500
2000
2500
t (s)
q′′ γ(kW/m
2)
HDPExL = 26.5 mmqimp = 25 KW/m2
0 500 1000 1500 20000
500
1000
1500
2000
2500
t (s)
q′′ γ(kW/m
2)
HDPExL = 26.5 mmqimp = 50 KW/m2
0 500 10000
500
1000
1500
2000
2500
t (s)q′′ γ(kW/m
2)
HDPExL = 26.5 mmqimp = 75 KW/m2
Figure: HDPE. (): measured MLRPUA; (—): simulated MLRPUA.
Pyrolysis simulations - p.11
Coupled simulations: comparison with experiments
Experimental HRR vs. numerical m′′γ∆hc
Time-to-ignition and time-to-peak HRR rarely exceeding the relative experimentalrepeatibility discrepancy
Peak and average HRR: gap to experiment lower than the relative experimentalrepeatibility discrepancy, except for HIPS at large heat flux (overestimation of the heatof combustion ?)
Radiative fraction Definition: χrad = Qrad/Qchem with
Qchem =
∫ΩF
(∆h0γ,z −
∑P
∆h0γ,Pµ
′′γ,P )ωγdΩ, Qrad =
∫ΩF
−∇ · qrad,FdΩ
Material χrad (SFPE Handbook) χrad (simulation)
PMMA 0.31 0.13HIPS 0.59 0.18HDPE 0.38 0.13
Pyrolysis simulations - p.12
Coupled simulations: comparison with experiments
Experimental HRR vs. numerical m′′γ∆hc
Time-to-ignition and time-to-peak HRR rarely exceeding the relative experimentalrepeatibility discrepancy
Peak and average HRR: gap to experiment lower than the relative experimentalrepeatibility discrepancy, except for HIPS at large heat flux (overestimation of the heatof combustion ?)
Radiative fraction Definition: χrad = Qrad/Qchem with
Qchem =
∫ΩF
(∆h0γ,z −
∑P
∆h0γ,Pµ
′′γ,P )ωγdΩ, Qrad =
∫ΩF
−∇ · qrad,FdΩ
Material χrad (SFPE Handbook) χrad (simulation)
PMMA 0.31 0.13HIPS 0.59 0.18HDPE 0.38 0.13
Pyrolysis simulations - p.12
Coupled simulations: sample heat flux and flame structure
Heat flux received by the sample surface
Convective part: lower than 2 kW/m2, decreases when qimp increases
Radiative part: 5 kW/m2 (PMMA), 10 kW/m2 (HIPS), 6 kW/m2 (HDPE):underestimated ?
x0 0.01 0.02 0.03 0.04 0.050
5
10
15
20 Flux, t=825.000000
Flux, t=1760.000000
Flux, t=2750.000000
Flux, t=1760.000000
Flux, t=1760.000000
Flux, t=2750.000000
r (m)
q(K
W/m
2)
qimp = 25 KW/m2PMMA, qconvHIPS, qconvHDPE, qconvPMMA, q+rad,MHIPS, q+rad,MHDPE, q+rad,M
x0 0.01 0.02 0.03 0.04 0.050
5
10
15
20 Flux, t=825.000000
Flux, t=990.000000
Flux, t=1210.000000
Flux, t=1760.000000
Flux, t=1760.000000
Flux, t=2750.000000
r (m)
q(K
W/m
2)
qimp = 50 KW/m2PMMA, qconvHIPS, qconvHDPE, qconvPMMA, q+rad,MHIPS, q+rad,MHDPE, q+rad,M
x0 0.01 0.02 0.03 0.04 0.050
5
10
15
20 Flux, t=825.000000
Flux, t=660.000000
Flux, t=825.000000
Flux, t=1760.000000
Flux, t=1760.000000
Flux, t=2750.000000
r (m)
q(K
W/m
2)
qimp = 75 KW/m2PMMA, qconvHIPS, qconvHDPE, qconvPMMA, q+rad,MHIPS, q+rad,MHDPE, q+rad,M
Figure: Convective and radiative flux received by the sample surface for 26.5 mm thick samples ofPMMA, HIPS and HDPE under different imposed heat flux, extracted at half time-to-peak.
Pyrolysis simulations - p.13
Coupled simulations: sample heat flux and flame structure
Flame structure Relevant flame height estimation Laminar flame behaviour near the sample surface
I Low turbulent mixingI limited convective exchange
0 0.2 0.4 0.6
600
800
1000
1200
1400
1600
1800
0
0.002
0.004
0.006
0.008
0.01PMMAHIPSHDPE
x (m)
T(K
)
µGt(kg/m/s)
qimp = 25 KW/m2
0 0.2 0.4 0.6
600
800
1000
1200
1400
1600
1800
0
0.002
0.004
0.006
0.008
0.01PMMAHIPSHDPE
x (m)
T(K
)
µGt(kg/m/s)
qimp = 50 KW/m2
0 0.2 0.4 0.6
600
800
1000
1200
1400
1600
1800
0
0.002
0.004
0.006
0.008
0.01PMMAHIPSHDPE
x (m)
T(K
)
µGt(kg/m/s)
qimp = 75 KW/m2
Figure: Axial temperature and turbulent viscosity profiles computed for 26.5 mm samples, under25 kW/m2, 50 kW/m2 and 75 kW/m2 imposed heat flux, and recorded at half the time-to-peak heatrelease rate. The vertical lines denote the flame height evaluation resulting from the Heskestadcorrelation (Heskestad, 1998) on the basis of the mass loss rate recorded at the same instant.
Pyrolysis simulations - p.14
Outline
1 Introduction
2 Models used for coupled simulations
3 Pyrolysis simulations
4 Conclusion and future enhancements
Conclusion and future enhancements - p.15
Conclusion for each modelling domain. . .
PyrolysisI Good ability for one-step chemistry and non-charring polymersI For charring polymers: degradation path ? charring residual thermal properties ?I Study of the apparent conductivity by homogeneisation techniques (IRSN/Pprime PhD.
Thesis, Jianwei SHI)
Turbulent combustionI Ability of simple RANS models to show the main, average, flame features (height,
transition)I Avoiding parameter-fitting, unsteadiness : use of LESI Further modelling and knwoledge required for the interface convective exchanges
Radiative transferI Underestimation of the radiative heat transfer and the radiative flux received by the sampleI Influence of the turbulence-radiation interactions ?
Self-sustained pyrolysis: a better test to discriminate the relevant modelling (Cf. Kacemet al., 2016)
Conclusion and future enhancements - p.16
Conclusion for each modelling domain. . .
PyrolysisI Good ability for one-step chemistry and non-charring polymersI For charring polymers: degradation path ? charring residual thermal properties ?I Study of the apparent conductivity by homogeneisation techniques (IRSN/Pprime PhD.
Thesis, Jianwei SHI) Turbulent combustion
I Ability of simple RANS models to show the main, average, flame features (height,transition)
I Avoiding parameter-fitting, unsteadiness : use of LESI Further modelling and knwoledge required for the interface convective exchanges
Radiative transferI Underestimation of the radiative heat transfer and the radiative flux received by the sampleI Influence of the turbulence-radiation interactions ?
Self-sustained pyrolysis: a better test to discriminate the relevant modelling (Cf. Kacemet al., 2016)
Conclusion and future enhancements - p.16
Conclusion for each modelling domain. . .
PyrolysisI Good ability for one-step chemistry and non-charring polymersI For charring polymers: degradation path ? charring residual thermal properties ?I Study of the apparent conductivity by homogeneisation techniques (IRSN/Pprime PhD.
Thesis, Jianwei SHI) Turbulent combustion
I Ability of simple RANS models to show the main, average, flame features (height,transition)
I Avoiding parameter-fitting, unsteadiness : use of LESI Further modelling and knwoledge required for the interface convective exchanges
Radiative transferI Underestimation of the radiative heat transfer and the radiative flux received by the sampleI Influence of the turbulence-radiation interactions ?
Self-sustained pyrolysis: a better test to discriminate the relevant modelling (Cf. Kacemet al., 2016)
Conclusion and future enhancements - p.16
Conclusion for each modelling domain. . .
PyrolysisI Good ability for one-step chemistry and non-charring polymersI For charring polymers: degradation path ? charring residual thermal properties ?I Study of the apparent conductivity by homogeneisation techniques (IRSN/Pprime PhD.
Thesis, Jianwei SHI) Turbulent combustion
I Ability of simple RANS models to show the main, average, flame features (height,transition)
I Avoiding parameter-fitting, unsteadiness : use of LESI Further modelling and knwoledge required for the interface convective exchanges
Radiative transferI Underestimation of the radiative heat transfer and the radiative flux received by the sampleI Influence of the turbulence-radiation interactions ?
Self-sustained pyrolysis: a better test to discriminate the relevant modelling (Cf. Kacemet al., 2016)
Conclusion and future enhancements - p.16
Thank you for your attention
Conclusion and future enhancements - p.17
Bibliography
Engineering, Society Of Fire Proctection (2008). The SFPE hnadbook of fireprotection engineering. Fourth. National fire proctection association.
Heskestad, G. (1998). “On Q* and the dynamics of turbulent diffusion flames”.In: Fire Safety Journal 30, pp. 215–227.
Kacem, A. et al. (2016). “A fully coupled fluid/solid model for open air combustionof horizontally-oriented PMMA samples”. In: Combustion and Flame 170, ’135–147’.
Mc Caffrey, B. J. (1979). Purely buoyant diffusion flames: Some experimentalresults. Technical Report NBSIR-79-1910. National Bureau of Standards.
Menter, F. R. (1994). “Two-Equation Eddy-Viscosity Turbulence Models for En-gineering Applications”. In: AIAA Journal 32.8, pp. 1598–1605.
Stoliarov, S. I. et al. (2009). “Prediction of the burning rates of non-charringpolymers”. In: Combustion and Flame 156, pp. 1068–1083.
Conclusion and future enhancements - p.18
Turbulent combustion
A priori turbulence models constants fitting
Comparison to the Mc Caffrey flame (Mc Caffrey, 1979), Qγ = 22 KW/m2.
Inputs: Cµ (plume structure), Rf (buoyancy), CEBU (combustion)
Outputs: temperature, axial velocity
z*
T
103
102
101
200
400
600
80010001200
C =0.07, Rf=0.1, C
EBU=2
C =0.07, Rf=0.1, C
EBU=4
C =0.07, Rf=0.4, C
EBU=2
C =0.09, Rf=0.1, C
EBU=2
Exp.
z*u*
102
101
0.5
1
1.5
2
C =0.07, Rf=0.1, C
EBU=2
C =0.07, Rf=0.1, C
EBU=4
C =0.07, Rf=0.4, C
EBU=2
C =0.09, Rf=0.1, C
EBU=2
Exp.
Figure: Axial temperature (left) and axial velocity (right) profiles of the Mc Caffrey flame.Comparison between measurement points and simulations performed for various values of Cµ, Rf
and CEBU. z∗ = x/Q0.4γ , u∗ = u/Q0.2
γ , ∆T = T − T∞
Conclusion and future enhancements - p.19
Coupled simulations: quantitative comparison with experiments
Table: Comparison between the minimal and maximal relative difference between simulations andexperiments on the peak heat release rate, average heat release rate, time-to-peak andtime-to-ignition, for each considered polymer, and the related experimental repeatibility error
Material q′′γ,max (kW/m2) ¯q′′γ (kW/m2) τHRRmax (s) τig (s)min/max/rep min/max/rep min/max/rep min/max/rep
PMMA 0.3% / 31% / 17% 3.9% / 32% / 7 % 1.5 % / 35% / 12% 5.6 % / 29% / 17%HIPS 1.4% / 44% / 10% 3.2% / 81% / 6 % 7.4 % / 31% / 34% 1.5 % / 16% / 15%HDPE 3.2% / 44% / 36% 1.0% / 57% / 28% 1.2 % / 25% / 35% 0.8 % / 25% / 45%
Conclusion and future enhancements - p.20