simulation de la pyrolyse de polymères non-charbonneux...

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