modélisation multiéchellede la pyrolyse de biomasse...

Modélisationmultiéchelle delapyrolysedebiomasse:modèleDEAMetenthalpiesderéaction

identifiésgrâceàdesexpériencesmenéesàdifférenteséchelles

Prof. PatrickPerré

Auprogramme

• Contexte• Mesures à l’échelle micro-particule• Identificationdemodèles cinétiques• Laquestiondesenthalpiesderéaction• Expériences à l’échelle macro-particule• Lamodélisation comme lienentreéchelles• Conclusionetperspectives

1/06/2017 PatrickPerré,CentraleSupélec 2

• Heat treatment (or torrefaction) is a mildpyrolysis (up to 300°C) suitable for material orenergy end use.

• Material: gain of physico-chemical properties,durability.

• Energy: homogenization of physico-chemical andmechanical properties, energy concentration,reduced hygroscopicity, loss of mechanicalproperties (more brittle).


Context

Reversible/irreversiblechanges

Bergman, 2005

Irreversible

Reversible



4000

4500

5000

5500

6000

6500

7000

7500

8000

0 20 40 60 80

GC

V (k

cl k

g-1)

Mass loss (%)

E. grandis

E. saligna

C. citriodora

untreated

220°C*

250°C

280°C

charcoal

GCV=37.20WL+4654R2 =0.99

180°C

Grosscalorificvalue´Massloss(eucalyptus,5hours).

Almeida, G., Brito, J.O., Perré, P., 2010. Bioresource Technology, 101: 9778-84.

Previousworks

• Themassloss (ML)was proved tobe asyntheticindicator abletopredict thealterations ofseveralphysical properties.Thismeans that MLrepresentsthecumulativeeffects oftemperature anddurationorany morecomplex pathway T =f(t)

6

Ourmodelling strategy is therefore focusedonits prediction

Almeida, G., Brito, J.O., Perré, P., 2010, Bioresource Technology, 101: 9778-84Almeida G., Santos D., Perré P., 2014, Biomass and Bioenergy , 70: 407-415.

1/06/2017 PatrickPerré,CentraleSupélec

Previousworks

OverviewofthemodellingstrategySpatial scale

Applied configurationsBasic knowledge

Micro-particulePore/cell/

inclusion

Set of particles

Particle

Industry/structure Macroscopic scale:

coupled mechanisms

Macro-particule

Process

Multiscale approach


Microscopic scale : kinetics model

Micro-particle

Basicinformation:ATGfordifferentheating pathwaysPerte de masse (%) de la masse anhydre

50%

55%

60%

65%

70%

75%

80%

85%

90%

95%

100%

0 5000 10000 15000 20000 25000

Temps (s)

Per

te d

e m

ass

e (%

)

210 °C

195°C

175 °C

215°C

235°C

245°C

250°C

255°C

265°C

Rousset et al., Annals Forest Sci. 2006


Classicalkineticmodelsfromliterature


Cavagnol et al. 2013, Thermochemica Acta, 574:1-9.

Principleoftheinverseprocedure



Exampleoffittingquality(Locust,modelB)



ResiduesformodelsA,BandC



TheDistributedActivationEnergyModel(DAEM)


RobustnessoftheDAEMmodel


Cavagnol et al. 2015, Can. J. Chemical Engineering, 93:331–339.

Experiment

Multi-stepmodel

DAEMmodel

Temperature

CalibrationofMLusingelementaryanalysis



PredictionofMLusingtheDAEMmodel



Validationondynamictests


ü Stillopenquestionsregardingvalidation(additionaltestsunderprogress)

ü Heatfluxtoosmalltobemeasureddirectly(pb ofbaseline):theheatsofreactioncannotbedertermined atthisscale.

ü AvalidatedDAEMmodelcouldoffernewpossibilities…

Macro-particle

Heat and mass transfer within

particles

Thermal degradation of

wood componentsBiomassà solid residues

+volatiles

Localscale

Modellingstrategyatthemacro-particule level


21

Water

Enthalpy

Air&gas

• Formulationofheatandmasstransfer

( ) ( ) ( )vv v Deffb bbw g w g v

w g w g gw v w v gt

re e r wr r r r r¶+ + + Ñ× + + = Ñ× Ñ

¶

( ) i i

S SS S S G S

itu m mer r

• •¶+ Ñ× = -

¶

æ ö× +ç ÷

è øå

( ) ( ) ( )* *

1,2,4,5v D i

i

effg g a

g g g a Ga a g

i Gt

M mM

e wr r r

•

=

¶+ Ñ× = Ñ× Ñ

¶+ å

( )( )

( )

* *

* *

( )

v + v ( )v

K D ( )

bw w g v b o s g

b bw w v g b

eff effv v a a

w g g ggw v a a

w g gw v a a

gg R

h h h h ht

h h h h

h h H

P

T

e e r e

r

w w

r r r r

r r r

r

¶+ + + + -

¶

Ñ × + + +

= Ñ × Ñ + Ñ + Ñ - D

Solid

Macroscopic formulation


Turner et al, 2010, Int. J. Heat Mass Transfer, 53: 715-725

Macroscopic formulation



Experimentaldeviceatthemacro-particlescale

• Control(andmeasurement)ofO2

• Temperatureandpressureinsideparticle• Globalmassloss


60cm

Temperatureovershootduetoexothermicreactions(isothermaltestsat280°C)


Pachon et al., SFGP, 2017

Lasimulationprédictive


Formulation (modèle)

Mesure ou prédiction Paramètres

Simulation Validation

Prédiction Contrôle/commande

Identification

Identificationofreaction enthalpies

27



Modelvalidation



Simulation:oven-dryboard

29Rémond, Turner, Perré, 2010, Drying Technology, 28: 1013-1022


Simulation:20%initialMC

301/06/2017 PatrickPerré,CentraleSupélecRémond, Turner, Perré, 2010, Drying Technology, 28: 1013-1022

Effect ofthickness/MC

311/06/2017 PatrickPerré,CentraleSupélecRémond, Turner, Perré, 2010, Drying Technology, 28: 1013-1022

Thedual-scale model

Pre-treatmentbymildpyrolysis

Perré, Rémond, Turner, 2013, Int. J. Heat Mass Transfer, 64: 838-849


34

Airflow Board

RL

T Boardmesh

zColumn i-1

Layer j

Column i Column i+1

Control volume

Layer j+1

x+ dxx

jCjVjLqa

qv

qa

qv

x

PhysicalformulationattheGlobalScale:TheStack

up, j lo, j 1vv v

dqj j

dx+= +Water

Air&gas up, j lo, j 1aa a

dqj j

dx+= +

up, j lo, j 1pa a pv v c c

up, j up, jv pv surf

lo, j 1 lo, j 1v pv surf

lo, j 1 lo, j 1a pa surf

up, j up, ja pa surf

dT(C q C q ) j jdx

j (C (T T)

j (C (T T)

j (C (T T)

j (C (T T)

+

+ +

+ +

+ = +

+ -

+ -

+ -

+ -

Enthalpy



35

2.0mInlet Outlet

1 6 11 35mm20mm

20mm

• 11IDENTICALBeech boards• Vair=2m/s•Mcinit=3%



36

2.0mInlet Outlet

1 6 11 35mm

20mm

20mm

A=35mm,3%MCB=35mm,20%MCC=18mm,3%MC



37

2.0mInlet Outlet

1 6 11 35mm

20mm

20mm

A=35mm,3%MCB=35mm,20%MCC=18mm,3%MC



Effect ofgas velocity

38

220

230

240

250

260

270

ConfA(Reference) velocity=5m/s Velocity=8m/s Velocity=11m/s

Tmaxatcore(°C)

Board1 Board6 Board11



Conclusion• Microparticle kinetics

– Modelparametersdeterminedbyinverseanalysisofseveralexperimentssimultaneously

– GoodpredictionabilityofDAEM– Heatfluxnotaccurateenoughtodeterminetheheatsofreaction

• Macroscopicmodelling– Heat&masstransfercoupledtokineticsreactions(2-way

coupling)– Heatsofreactionsdeterminedbyinverseanalysisusingthecore

temperatureofsample• Dualscalemodel

– Onemacromodelforeachparticle– Amasterstackmodel– comprehensiveandpredictivemodelisabletoaddresspractical

configurations


40

Thank you for your attention


ManythankstocolleaguesandPhDstudents

GianaAlmeida,Joël Casalinho,Sofien Cavagnol,JulienColin,Wieslaw Olek,PinLu,JohnPachon,FloranPierre,FrançoisPuel,Romain Rémond,JohnRosler,PatrickRousset,ElenaSanz,IanTurner…

modélisation multiéchellede la pyrolyse de biomasse...

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