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Laboratory for Chemical Technology, Ghent University

http://www.lct.UGent.be

3D simulation of turbulent reactive flows with detailed chemistry

Kevin M. Van Geem, Carl M. Schietekat, David J. Van Cauwenberge, Guy B. Marin

1

Methusalem Advisory Board meeting 2014, Gent, Belgium, 19/6/2014

Computational

Product Design

Lengthscale, m

Computational

Chemistry

Computational

Chemistry

10-12 10-810-10 10-410-6 10010-2 102

Computational

Thermodynamics

Computational

Thermodynamics

Reactor, DevicesMaterial Structure

Surface/Solid-Ph. Transport

Elementary Kinetics

Fluid dynamics

Turbulent Transport

Models to relate phenomena at smaller length scales

to properties and behavior at larger scale

Models to relate phenomena at smaller length scales

to properties and behavior at larger scale

Diffusion

Material Properties

Computational

Process Engineering

Computational

Fluid Dynamics

Computational

Fluid Dynamics

Process System

Modeling

Process System

Modeling

P1 Single-Event MicroKinetics in complex reaction mi xtures 1. Dijkmans, T., Van Geem, K.M., Djokic, M., Marin, G.B., (2014)

Combined comprehensive two dimensional gas chromatographic analysis of PAH/PASH compounds in complex matrices, Industrial & Engineering Chemistry Research

2. Dijkmans, T.; Schietekat, C.M.; Van Geem, K.M.; Marin, G.B.(2014) GPU based simulation of reactive mixtures with detailed chemistry in combination with tabulation and an analytical Jacobian, Computers & Chemical Engineering, Submitted

3. Dijkmans, T.; Djokic, M.; Van Geem, K.M.; Marin, G.B. Comprehensive compositional analysis of sulfur and nitrogen containing compounds in shale oil using GC × GC -FID/SCD/NCD/TOF-MS, Fuel, Submitted

4. M. R. Djokic, Frassoldati, A.; Pyl, S.P.; Ranzi, E.; Marin, G.B. K.M. Van Geem, G. B. Marin, (2014) An experimental and kinetic modeling study of cyclopentadiene pyrolysis: first growth of polycyclic aromatic hydrocarbons, Combustion & Flame, accepted

A1 Publications 2013-2014

P5 Reactor design from first principles 5. Schietekat, C.M.; Van Cauwenberge, D.J.; Van Geem, K.M.; Marin,

G.B.,(2014a), Computational Fluid Dynamics based design of finned steam cracking reactors. .AIChE Journal, 60, 794-808

6. Schietekat, C.M.; Van Goethem, M.; Van Geem, K.M.; Marin, G.B.,(2014b) Swirl flow tube reactor technology: an experimental and computational fluid dynamics study, Chemical Engineering Journal, 238, 56-65

P6 From fossil to renewable feedstocks1. De Bruycker, R.; Carstensen, H.-H.; Simmie, J.; Van Geem, K.M.;

Marin, G.B. (2014) Experimental and computational study of the initial decomposition of gamma-valerolactone, Proceedings of the Combustion Institute, Accepted

2. Muñoz, A.E., Van Geem, K.M., Reyniers, M.-F., Marin, G.B., (2014), Influence of the reactor material composition on coke formation during ethane steam cracking, Industrial & Engineering Chemistry Research, accepted 4



9. Muñoz, A.E., Van Geem, K.M., Reyniers, M.-F., Marin, G.B., (2014), Influence of the reactor material composition on coke formation during naphtha steam cracking, Industrial & Engineering Chemistry Research, submitted

10. Djokic, M.; Carstensen, H.-H.; Van Geem, K.M.; Marin, G.B. (2013), The thermal decomposition of 2,5-dimethylfuran, Proceedings of the Combustion Institute 34 (1), 251-258, 2013

11. Yildiz, G.; Lathouwers, T.; Toraman, H.E.; Van Geem, K.M.; Marin, G.B.; Ronsse, F.; Van Duren, R.; Kersten, S.R.A.; Prins, W. (2014) Catalytic fast pyrolysis of pine wood: effect of successive catalyst regeneration, Energy & Fuels, accepted

12. Yildiz, G.; Lathouwers, T.; Djokic, M.; Van Geem, K.M.; Ronsse, F.; Van Duren, R.; Kersten, S.R.A.; Prins, W. (2013) Validation of a new set-up for continuous catalytic fast pyrolysis of biomass coupled with vapour phase upgrading JOURNAL OF ANALYTICAL AND APPLIED PYROLYSIS

13. Toraman, H.E.; Dijkmans, T.; Djokic, M.R.; Van Geem, K.M.; Marin, G.B. (2014) Detailed compositional characterization of plastic waste pyrolysis oil by GC × GC – FID/SCD/NCD/TOF-MS Journal of Chromatography A, 2014, accepted 5



6


P5 Reactor design from first principles

Dis

tilla

tion

Crude oil

10% chemicals: Ethane & Naphtha

80% to fuels

10% asphalt, residue, lubricants

Pro

cess

ing

Natural gas Methane

NGL (Ethane, Propane...)

Gascondensates

Steamcracker Ethene

PropeneButadieneAromatics

Base chemicals

Chemical industry

Consumer goods

Difference in yieldof 0.1 wt% of

ethene, propene or 1,3-butadiene

difference in profitof medium sized

cracker of5 000 000 €

7


It’s all in the details

8


Why CFD with detailed chemistry?

Reactor designReactor design

BendsBends 3D technologies3D technologies

Impact on mixing, heat transfer and pressure drop

Coking and product yields

Detailed mechanism: higher accuracy

9

3D reactor technology

• Standard RANS simulations

• Speeding up the code:– Application QSSA and code optimization– Dynamic multi-zone partitioning

• Turbulence-chemistry interaction

• Periodic Large Eddy Simulations– non-reactive and reactive 10


Outline

11


Industrial reactor simulation

Kellogg Millisecond propane cracker (KBR)• Feedstock 118.54 kg/h propane• Steam dilution 0.326 kg/kg

4 geometries were simulated:• Same reactor volume• Same axial length• Same minimal wall thickness• Same total heat input

Bare Straight Helix SmallFins

OptimizedIndustrial geometry

12


Industrial reactor simulation

4 geometries were simulated:• Same reactor volume• Same axial length• Same minimal wall thickness• Same total heat input

0

2

4

6

8

10

12

0 50000 100000

Axi

alco

ordi

nate

[m]

Heat flux [W/m²]

Total calculation time:100,000 CPU hours

13


Computational method

Turbulence:� RNG/Reynolds Stress Model� Enhanced wall treatment (Wolfstein)

Material properties:� ideal gas mixing laws� cp temperature polynomials� k, Dmol, µmol kinetic theory

Computational Fluid Dynamics: FLUENT 13.0 Gambit 2.4.6

Extrusioncross-section:

> 5 106 cells

Reaction network :� 13 molecules, 13 radicals

metalalloy

processgas

periodicBC

heat flux BC

Flow:� Pressure-based compressible steady-state� Pressure-velocity coupling: SIMPLE

14


Steady-state transport equations

• Conservation of mass

• Navier-Stokes equations

• Conservation of energy

• Species transport equations

� �� = 0

� ∙ �� = −� + � ∙ �̿

� ∙ �� = −� ∙ ��̅ + �� , ∀� = 1, �� − 1

� ∙ �� + = � ∙ �� − ℎ��̅�

+ "#

15


Industrial propane cracker

More uniform gas temperatureLower metal temperature

Bare Straight Helix SmallFins

OptimizedIndustrial geometry

16


Axial mixing-cup profiles

Similar average process gas

temperature profile

Reactor pressure drop up to 66% higher

17


Tube Metal Temperature

TMT Smallfins : 51 K lower

Increased run lengthCoking rate: 49% lower

18


Radial species profile

z = 10.5 mz = 10.5 m

Molecular species:Difference limited to factor 0.8

Radical species:Up to 4 times higher

Ea [kJ/mol]

350

0.09

C3H8C3H8

CH3CH3

19


Product selectivities

Minor effect on totalolefin selectivity!

-0.01 %

+0.21 %

+0.34 %

Effect on olefin selectivity

20


Product selectivities

Minor effect on totalolefin selectivity!

-0.01 %

+0.21 %

+0.34 %

-0.26 % +0.02 % +0.04 %

21


Coke formation

z = 10.5 mz = 10.5 m

�$ = % &$'() , &$*(+ , �,

Reduced average coking rate BUT greater internal surface

Fin valleys will fill up with cokes even faster than a bare tube!

Top

Top

Valley






Outline

reduce computational cost:

1. µ-radical hypothesis

2. QSSA on β-radicals

3. automatic code optimization

23


Reaction network extension

Feedstock Product

reduce computational cost:

1. µ-radical hypothesis

2. QSSA on β-radicals

3. automatic code optimization

24


Reaction network extension in OpenFOAM

Feedstock Product

25


µ sub-networks

* Pyl, PhD thesis (2012)

� reaction sequence is reduced to 1 ‘lumped’ reaction by µ-hypothesis and

QSSA:

... 321 +⋅+⋅→ •CHaetheneahexane refk

1.

µ-radicals eliminated from reaction networkless reactions explicitly in reaction network

26


Single Event Micro Kinetic model

unimolecular reactions predominateuni- and bimolecularreactions included

µ NETWORK β NETWORKC6+ molecules

C5- moleculesβ radicals

R addition H abstraction

isomerizationcyclizationβ scission

µ radicals

bond scission

bond scissionrecombinationH abstractionisomerization

cyclizationβ scission

radical addition

1.

27


QSSA on β-radicals

( )( )

==

00

cc

cfR( )

( )

===

=

0

)2()1()2(

)2()1()1(

0

),(0

,

cc

cchR

ccgR

FLUENTeach cell, flow

iteration i

Retrieve molecular

concentrations

Update radicalconcentration

Calculatemolecularrates of

formation

Store radicalconcentrations

and rate of formation in

UDM

UDF

c(1)i-1,T c(2)

i-1c(2)

i

only continuity equations of molecules are solved

��-./ = ��- ��

��0Solver update formula:

2.

28


Automatic code optimization3.

β networkµ sub-

networks

Sort reactions

Code Generation & Optimization

Symbolical expressions

for rates of production

generateefficient C code

avoid time-consuming general do-loops

29


Methodology validation

Feedstock N ° molecules N ° radicals Speedup factor

Ethane 6 3 7.4

Butane 8 6 51.8

Propane 13 11 54.2

0.015 m873.15 K0.01 kg/s

Incoloy 800H

2D axisymmetric280.000 cells

Process gas

30


Centerline profiles: butane case

31


Propane cracker revisited

Reaction network� 44 molecules, 41 radicals

Selectivities[kg/kg]

Bare SmallFins*

Methane 19.96 20.05

Ethene 36.27 35.98

Propene 25.45 25.86

1,3-Butadiene 1.89 1.90

Benzene 3.24 3.23

Naphthalene 1.13 1.08

Light olefins 63.61 63.75

Pygas [C 5+] 8.63 8.59

** Light olefins = ethene + propene +1,3-butadiene* scaled to same conversion

z = 7 mz = 7 m

Conversion 75.15 75.15






Outline

Dynamic multi-zone partitioning

33


� ∙ �1 � = −� ∙ 23 + �� , � = 1, �� − 1

�� = f �, � , "# = ��∆6�,�

computationally expensive

Dynamic multi-zone scheme:

1. Group cells into zones

2. Solve chemical kinetics based on zone averages

3. Map zonal solution back to individual cells

1

2

3

� ∙ �� + = � ∙ �� − ℎ��̅�

+ "#

* Liang et al. (2009), Combustion Science and Technology, 181:11, 1345-1371

Zoning of cells

34


Single value for �� for given cell conversion and temperature� zoning based on conversion and temperature

�$'()for all cells in butane cracking reactor

1

Uniform zoning of cells

35


� user-specified ∆T and ∆Yfeed� tresholds can be changed during simulation� every iteration new zones �78-� = ∑�:

�&�;;�78-�<78-� = ∑<=

�&�;;�78-��78-� = ∑�:

�&�;;�78-�

>?@AB = f �78-� , <?@AB, 78-�

>= = >?@AB,=

2

3� implemented in

[K]

[wtfr]

[kg/m³]

36


Butane cracking reactor

Reaction network: 8 molecules, 7 radicals

n-C4H10δ = 0.3893 K

30.2 mm

Butane cracking reactor: CPU time

- Mesh size: 740804 cells- ∆T = 5 K and ∆Yn-butane = 5 wt%- 16 CPU’s

37


about 20 times faster

significant zoning overhead

Maximum 1400 zonesfor 740 kCells

Butane cracking reactor: zones

38


Mixing-cup averages (1)

39


�&C6/D

&E6C &F6G

Mixing-cup averages (2)

40


&6C &E6G

&F6H 6E



• Turbulence -chemistry interaction



Outline

Turbulence-chemistry interaction

42


� ∙ �1 � = −� ∙ 23 + �� , � = 1, �� − 1�� , � ≠ �� , �̅

��J = K �� L � M�NOPQNORS

effect of turbulent temperature fluctuationsnormally not accounted for in RANS

concentration fluctuationsassumed negligible

use temperature distribution L �for evaluation rates

T� �, � = ��:UVR,W = X��UYP,RZN �:UVR,W

Temperature PDF

43


L � = 12\]NE

/Eexp − � − ��

E2]NE

Gaussian distribution assumed

Solve extra transport equation for temperature variance

a �̅�:b ]NEac: = aac: �̅ d + de

a]NEac: + 2�̅de

a�ac:

E− �̅fN

unclosed variancedissipation

Temperature variance dissipation modeling

44


fN = &gb f̃�i ]NE

Algebraic dissipation model:

Transport equation for temperature variance dissipation :

a �̅�:b fNac: = aac: �̅

j"� +je"�e afNac: − &/�̅

fN]NE − &E�̅

E &k�ije fN

+&F �̅&k�i"�ea�ac:

E+ &Cje ��i "l

E

production byT gradient

mechanicaldestruction

production byu gradient

scalardestruction

&� many models proposed

Integration rate coefficients

45


�:J = 2\]E U//EK X: exp −�n,:�� exp −� − �� E2]E M�

o

Uo

c = � − ��2]E //E

�:J = \U//EK X: exp − �n,:� 2]E //Ec + �� exp −c

E Mco

Uo

p qr q

�:J = K s c % c Mc ≈u

n v=% q=w

:x/

Gaussian quadratureabscissaweightsquadrature order

normalizedtemperature

�:J = K �: � L � M�o

Uo

Validation vs. DNS data

46


Re = 5500Pr = 0.71

periodicperiodic

isoflux

* Redjem-Saad et al. / Int. J. Heat and Fluid Flow 28 (2007) 847–861

47


Reactive simulation

Reaction network: 8 molecules, 7 radicals

n-C4H10δ = 0.3 800 K

30.2 mm

Reactive simulation: yields

48


�&C6/D

&E6C &F6G

Reactive simulation: yields

49


Yield[wt% dry]

No interaction

Withinteraction

Difference

H2 1.39 1.40 0.00CH4 11.10 11.18 0.08C2H6 8.74 8.69 0.05C2H4 62.28 62.51 0.24C3H6 14.26 14.12 0.14C3H8 1.38 1.35 0.03N-C4H10 0.85 0.75 0.10

&6F6

� Direct Numerical Solution (DNS)Fully resolve all time and length scales

� Reynolds-Averaged Navier-Stokes (RANS)One model for all scales, solve additional equations to

provide closures

� Large Eddy Simulation (LES)Resolve relevant energy containing scales, model the smaller energy

dissipating eddies

Resolving turbulence


50LESRANS

Axialvelocity[m/s]

51


Transient transport equations

• Conservation of mass

• Navier-Stokes equations

• Conservation of energy

• Species transport equations

a�ay + � �� = 0

a ��ay + � ∙ �� = −� + � ∙ �̿

a � �ay + � ∙ �� = −� ∙ ��̅ + �� , ∀� = 1, �� − 1

a ��ay + � ∙ �� + = � ∙ �� − ℎ��̅�

+ "#

Grid requirements for the near-wall region: Nx Ny Nz ∝ Re1.8

Computational cost ∝ Re2.4

Wall-resolved LES


52* Piomelli, 2014


Periodic LES of enhanced tubes

53

Straight fins

Rifledfins

Intermittent ribs

Lemniscate

Focus on the fully-developed region, i.e. mean velocity profile is

constant and temperature is fully developed

=

+

Fully developed flow

54


Temperature: reality

Non-periodic linear rise

Periodic radial profile

Computational domain limited to a length of 5-10 diameters

Pressure and temperature made periodic by adding the

appropriate source terms

Streamwise periodicity

55


Comparison with DNS data of Redjem-Saad (2007) (Reτ=186, Pr=0.71) and

Tiselj (2001) – Tτ = 3.73K

Validation study – Bare tube

56


Relative error: 1-2%

Comparison with experimental data of M. Cakan (2000) and L. Casarsa (2005)

PIV measurements positioned after 4 fins -> not yet fully developed periodic

Heat transfer studied by means of liquid crystals on the channel surface


Validation study – Ribbed Channel (VKI)

PIV

57

Similar periodic simulation domain as used by Rémy Fransen (CERFACS) in his

PhD thesis using the AVBP code †


Validation study – Ribbed Channel (VKI)

58

AVBP

OpenFOAM

† Fransen R., Simulation aux grandes échelles pour la modélisation aérothermique des aubages de turbines refroidies, 2013


Ribbed Channel – Mean Velocity

59

AVBP †

OpenFOAM

−1 0 1 2 3 4 50

1

2

3

4

U/ Ub+x/ h

y/

h

PIV

x/ h=0

x/ h=1

x/ h=2

x/ h=3

† Fransen R., Simulation aux grandes échelles pour la modélisation aérothermique des aubages de turbines refroidies, 2013

Tube ID: 50mm, element height: 2mm, helix angle: 65°

Simulations performed at Reynolds numbers 5.5k – 11k – 25k –

38k

Grid sizes ranging from 4 to 16 million cells


Helicoidally ribbed tube (MERT)

60

Velocity

Temperature


MERT – Velocity Profiles

Flow separation near the fin top, reattachment after 12.85mm

Swirling flow motion

61


MERT – LES vs RANS

62

0

50

100

150

0 1 2 3 4 5

Nu

sse

lt n

um

be

r [-

]

Reynolds number [-] x 10000

Bare_cor

Vicente (2004)

Ravigururajan (1996)

Zhang (1991)

MERT_LES

Bare_LES

MERT_kOmegaSST

0

0,005

0,01

0,015

0,02

0,025

0 1 2 3 4 5

Fa

nn

ing

fri

ctio

n f

act

or

[-]

Reynolds number [-]

x 10000

Bare_cor

Saha (2010)

Vicente (2004)

Ravigururajan (1996)

Zhang (1991)

MERT_LES

Bare_LES

MERT_kOmegaSST

The periodic LES is not the fastest simulation tool but is

extremely robust and can handle pretty much any kind of flow

phenomena and geometries -> excellent design tool

In anticipation of detailed experimental data, it can be used as a

validation/tweaking tool for geometry-specific Reynolds stress

models

Summary

63


Re = 11,000

Bare MERT Slit-MERT Swirl Flow Straight fins

ΔP [Pa] 5.16 8.97 8.22 6.68 6.88

Relative ΔP 1.00 1.74 1.59 1.29 1.33

Nu 32.4 46.1 41.9 42.9 30.3

Relative U 1.00 1.42 1.29 1.33 1.20

Tmetal [°C] 1060 1046 1050 1049 1053

Can the concept of periodicity be extended beyond just cold flow

simulations?

Procedure of CERFACS (Toulouse)

• Apply full periodicity to all variables

• Temporal instead of spatial simulation -> use the average velocity to track

the simulated “plug” through the reactor and translate it back to a

position: Δx = Δt.Ubulk

• Detailed evaluation of the influence of reactor design on species mixing

and their influence on yields

• Requires time-varying boundary conditions to apply

a realistic heat flux profile and a varying momentum

source to overcome friction

Reactive LES

64


Mass fraction C 2H4

In a periodic setup, all fluxes of mass/momentum/enthalpy/…

through the outlet, are introduced again at the inlet, i.e. we’re

dealing with a closed volume

Closed volume + conservation of mass = constant density!

In steam cracking, density decreases throughout the length of

the reactor due to a variety of contributions

• Temperature rise: 650 °C -> 850 °C (x0.8)

• Pressure drop: 2.5 bar -> 1.7 bar (x0.7)

• Molecular expansion: Naphtha -> ethylene (x0.8, roughly)

Incorrect density -> incorrect concentrations -> incorrect yields

Limitations

65


By introducing a sink term in the continuity equation, a certain

amount of mass is removed from the compuational volume,

based on the solution in the previous timestep

a�ay + � �{ −

|�(e)|y = 0

|�(e) = �,�� (eU/)− �(eU/)

This introduces a continuity error in all other equations -> add

correction terms �08-e�E.g. momentum equation becomes:

a(�{)ay + � �{{ −�08-e{= −| + �� +grad() %;��d�T��y��

Solution: mass dissipation

66


• Pressure expansion according to the calculated required

momentum source (with optional correction factors) or using

a pressure gradient read from an a-priori 1D simulation result

• Heat flux varies over time (~distance) and is interpolated

from a file

• Thermodynamics calculated using NASA polynomials,

transport properties using kinetic theory of gases

• Finite-rate chemistry with quasi-steady state approximation

for the free radicals

• Surprisingly stable methodology, 2nd order accuracy in time

and space

Variable-density LES

67


Computational domain: 0.045m x 9mm, cell count ≈ 1M

Actual dimensions: 12m x 9mm

3.2kg/h pure butane feedstock

Steam dilution of 0.71 [kg/kg]

Full automatically generated reaction network, reduced to a

workable size: 19 components, 149 reactions and validated with

experimental results

Test case: LCT pilot plant

68


U0 = 28.4m/s, Re ≈ 10,000

0 2 4 6 8 10 120

5000

10000

15000

Axial position [m]

Hea

t fl

ux

[W

m−

2]


69



70


Non-reactive

Radial profiles at 9m

71


H•

� 3D simulation with detailed chemistry (<50 species) is possible

� Succesfully switched from Fluent to OpenFOAM

� Evaluation of rates-of-production: Speed-up factor > 50 obtained

� Turbulence-chemistry interaction seems non-negligible

� Periodic reactive LES with variable density highly promissing

72


Conclusions

Plenary speakers: dr. Truhlar, dr. Iglesia, dr. Coote, dr. Seakins & dr. Kraft

Special issue of International Journal of Chemical Kinetics dedicated to ICCK 9

convention center Het Pand Downtown Ghent

Bruges

74


Acknowledgments and questions

� Ruben De Bruycker, Dr. Steven Pyl, Thomas Dijkmans, Dr. Nick Vandewiele, Dr. Alberto Passalacqua, Dr. Bo Kong

� FWO-Vlaanderen

� The Long Term Structural Methusalem Funding

� STEVIN Supercomputer Infrastructure

LongLongLongLong TermTermTermTerm StructuralStructuralStructuralStructural MethusalemMethusalemMethusalemMethusalem

FundingFundingFundingFunding ofofofof thethethethe FlemishFlemishFlemishFlemish GovernmentGovernmentGovernmentGovernment

� CFD = Computational Fluid Dynamics� COT = coil-outlet-temperature, i.e. the mixing-cup averaged

process gas temperature at the reactor outlet� µ-radical = a radical for which bimolecular reactions can be

negelected� µ-radical hypothesis = the hypothesis that radicals with more

than 5 carbon atoms are µ-radicals� β-radical = a radical that undergoes both mono- and bi-

molecular reactions� QSSA = Quasi-Steady-State Assumption = the assumption

that the rate of formation and consumption of a certaincomponent are equal

75


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