Turbulent ﬂow and combustion in real-life syngas burner

Kamil Kwiatkowski

1;2

,Konrad Bajer

1;2

,Karol We¸dołowski

1;2

1

Institute of Geophysics,Faculty of Physics,University of Warsaw

2

Interdisciplinary Centre for Mathematical and Computational Modelling,University of Warsaw

kamil@igf.fuw.edu.pl

Abstract

When multi-species,non-premixed ﬂows combine with chemical reactions,a common situation in industrial devices,the mixing or

diffusive phenomena become the key factors of understanding the whole process.Turbulence is conducive to mixing of species and

consequently may increase the reaction efﬁciency [1].That motivates us to study in details the mixing of fuel with air,in an industrial

burner of complex geometry (see ﬁg.1a).The fuel is syngas (gas obtained fromthe process of biomass gasiﬁcation).In order to isolate

the effects of turbulent mixing in a complex-geometry ﬂow,we ﬁrst neglect ignition and possible re-ignition and employ a relatively

simple parametrisation of chemical reactions.

We create a 3Dmodel of a real industrial syngas burner of complex geometry involving an axial co-ﬂowjet and six additional air inlets.

These extra inlets enhance the swirl and promote the generation of vortices,thus making the ﬂow more turbulent,and consequently

accelerate mixing [1,2].The exploratory simulations of non-reactive gas ﬂows are prepared using the commercial CFD Fluent solver

as well as the open source CFD package OpenFOAM[3].Both simulations are based on the RANS turbulence closure.

We also design and run a series of non-premixed combustion simulations.To reconstruct the ﬂowﬁeld correctly we use Steady Flamelet

[4] approach for measured syngas composition.Despite the fact,that several simpliﬁcations are made,the results agree qualitatively

with the observations.

1.Introduction

Gasiﬁcation appears to be the most economically promising

way of thermal treatment of solid biomass waste [5,6,7].

An in-house industrial installation enables clean waste disposal,

which would otherwise require costly outside contracting,and,

in the simplest version,generates heat used in the plant’s tech-

nological process.The combination of the two beneﬁts makes

even the simplest gasiﬁer-combustor-boiler systems commer-

cially viable provided the process is carefully designed to be

clean enough,so that the composition of the ﬂue gases meets

the environmental norms ([8,9]) and the cost of their additional

puriﬁcation is limited.Electric power co-generation can con-

siderably improve the economy of the whole process but any

efﬁcient co-generation,whether with a gas turbine or internal

combustion engine,requires much bigger initial investment in a

systemof syngas puriﬁcation.

All three components of the gasiﬁer-combustor-boiler sys-

tem must be individually designed for different types of solid

biomass waste.Off those three it is the combustor which has

the main effect on the composition of the ﬂue gases.It has to

be individually designed for the target ﬂow rate and for the par-

ticular syngas composition determined by the kind of biomass

fed into the gasiﬁer [10].Some of the pollutants present in the

ﬂue gases are robust.Their content is determined by the chemi-

cal composition of waste biomass and they have to be removed

from the ﬂue gases by speciﬁc chemical treatment.This is the

case,for example,with sulphur for which stable and reliable re-

moval processes are known and ready desulphurisation instal-

lations are available.Other pollutants are highly sensitive to

the details of the combustion process and their concentration in

the ﬂue gases may vary by more than one order of magnitude

depending on the apparently small change in the design of the

combustion chamber,burner,oxidant supply conﬁguration,etc.

This is the case with the NO

x

which are extremely sensitive to

the details of the reacting ﬂow inside the combustion chamber

[11,12].Their concentration measured in the ﬂue gases may

vary wildly without any noticeable change in the control pa-

rameters of the industrial process.

To somewhat lesser extent this is also the case with carbon

monoxide (CO).Its chemistry is more robust and predictable

than that of the NO

x

but its emission may be affected by possi-

ble irregular dynamics of the ﬂowcausing puffs of unburned CO

to exit the combustion chamber from time to time.A straight-

forward counter measure would be to raise the temperature of

the combustion process but this is antagonistic to the reduc-

tion of the NO

x

.Another limit on lowering temperature is the

requirement imposed on the combustion of syngas originating

from waste material.Such syngas must be subject to tempera-

ture no less than 850

C for at least 2 seconds ([8,9]).

Since changing temperature in the combustor is restricted

by such opposing environmental constraints it is most important

to optimise the combined CO and NOx emissions by means of

careful design of the reacting ﬂow in the combustion chamber

and that requires numerical simulations which are the subject of

this paper.

In order to have as accurate and reliable numerical simu-

lations as possible we develop two independent codes that are

run in parallel enabling quantitative intercomparison and cross-

checking of the results.One set of simulations is done with

FLUENT and another,under the same conditions,with Open-

Foam [13,3].With these two numerical codes we solve a se-

quence of problems of increasing physical complexity building

up to the ultimate goal of time-dependent simulations of the

combustion chamber of a real industrial installation with true

chemistry of the syngas actually produced froma particular type

of waste biomass.

All simulations are run in the true geometry of the com-

bustion chamber with an axial co-ﬂow jet burner at the top,ad-

ditional air inlets introducing swirl,and asymmetric outlet near

the bottom(see ﬁg.1).The ﬂowis driven by suction,i.e.,by the

pressure drop imposed at the outlet.In practise this is realised

by electric fans at the exit of the ﬂue gases from the boiler far

away fromthe combustion chamber.

All results reported in this paper are for steady-state simu-

lations.First runs for unsteady ﬂow are now under way.With

unsteady simulations we hope to capture the slowmodes of tem-

poral evolution of the ﬂow that we have actually observed in

the combustion chamber.Yet,even the steady state simulations

are quite revealing and indicated hitherto unknown characteris-

tics of the temperature distribution and velocity ﬁeld inside the

chamber.

The ﬁrst stage is the simulation of ‘cold’ ﬂow,i.e.,the ﬂow

without chemical reactions,through the combustion chamber.

Somewhat remote from the ultimate goal of pollutant emission

modelling,yet these simulations serve two important purposes.

The ﬁrst is to compare FLUENTand OpenFoamperformance in

the simulations where the momentum transport dominates and

heat transport does not play a role.The second is to compare

such ‘cold’ simulations with measurements,not yet available,

that will be taken in the industrial installation during the next

maintenance break.We will then test the ﬂow with syngas be-

ing replaced by air.Simple comparison of the relation between

the pressure drop and mass ﬂow rate through this complex ge-

ometry will provide valuable means of validation of the code

and will be a test for different sub-grid scale turbulence models.

The second stage is the simulation of ‘hot’ ﬂow.Then we

include those chemical reactions which strongly affect the en-

ergy balance and therefore inﬂuence the ﬂow.These are pri-

marily the combustion of CO and of H

2

.Large energy re-

lease causes qualitative changes in the ﬂowpattern due to buoy-

ancy of the hot gas.Strong counterﬂow (updraft) appears in

prominent recirculation zones and temperature distribution is

changed.

2.Turbulent cold ﬂow

2.1.Flow conditions

In large-scale industrial syngas devices turbulence occurs natu-

rally.Estimated values of Reynolds number which cover the

range of ﬂows in our simulations of non-reactive case,i.e.

‘cold’ ﬂow,is of the order 10

5

,hence the ﬂow is clearly turbu-

lent and turbulence modelling must be used.The highest value

of Reynolds number,based on the diameter of the fuel inlet and

on the fuel inlet velocity,is equal 1:87 10

5

.

Environmental regulation require that the combusting gases

spend no less than 2 seconds in the region of high temperature

(minimum...).For a given gas volume ﬂux at the inlet,de-

termined by the production rate of the gasiﬁer,this imposes a

lower bound on the volume of the combustion chamber which,

in the installation we are modelling is 36m

3

.A sketch of the

simulated combustion chamber is presented in ﬁgure 1.It con-

sists of a vertical cylinder with the system of fuel and air in-

lets installed in the top surface and an outlet located near the

bottom of the cylindrical surface.The position of the outlet in

the wall is a major departure from axial symmetry.The axial

(vertical) cross-section which includes the centre of the outlet

pipe is denoted (x-z) plane.Another asymmetry is due to the

additional swirl-enhancing air inlets in the top surface.Sym-

metrically placed on a circle concentric with the main axial jet

those alone would make only small,possibly negligible,depar-

ture from axial symmetry.However,due to the combination of

discrete auxiliary inlets at the top and the ﬁxed position of the

outlet the systemhas neither planar,nor axial symmetry.

Figure 1:The 3D model of the syngas burner.Six additional

inclined inlet pipes are mounted in the top wall induce swirl.

Details of inlets are presented in the lower picture.

Table 1:Boundary conditions for non-reactive ﬂows.

Boundary

V

axial

[

m

s

]

V

radial

[

m

s

]

V

swirl

[

m

s

]

Fuel inlet

8

0

0

Main air inlet

2.5

0

-2.5

Swirl air inlets

0.5

0

0.5

In our simulations the values of gas and air inlet veloci-

ties correspond to the typical values measured in industrial de-

vices (particularly in the industrial installation for thermal waste

conversion working in Olsztyn).The boundary conditions are-

clearly explained in ﬁg.1.Numerical values of the boundary

conditions are listed in table 1.Since the cold ﬂow simulations

include no chemical reactions,and density of the syngases is

comparable with density of air,we use air as the ﬂuid for both

the oxidiser inlets and for the fuel inlet.

The simulations are run using two alternative Computa-

tional Fluid Dynamics codes,commercial code Fluent and

open-source package OpenFoam.For both CFD packages we

use the same setup,steady-state,incompressible solvers with

RANS k turbulence modelling.These requirements are

fulﬁlled by the pre-deﬁned OpenFoam solver called simple-

Foam.Having the experience of two previous long series of

two-dimensional RANS simulations closed by several turbu-

lence closure models,we decided to choose the k closure

of RANS equations for the present series of simulations.Since

three-dimensional ﬂows are naturally more complex we are go-

ing to make a comparative study of other closures as well.

2.2.Comparison of Fluent and OpenFoamresults

First,we present contours of the axial velocity on the slice in

x-z plane (ﬁg.2).The jet is composed of the streams of co-

ﬂowing ﬂuid issuing from the fuel and oxidiser inlets.Addi-

tional swirls,which supply air mainly for cooling the chamber

walls,does not show in this section.Their inﬂuence on the jet

is negligible.Qualitative observations show that in the Open-

Foamsimulations the jest is slightly wider and has weaker core.

Quantitative analysis,the results of which are presented in ﬁg-

ure 3,conﬁrmed systematically lower values of axial velocity in

the jet centre.

Interesting problemwhich we try to answer in this paper is

the inﬂuence of the geometrical asymmetry on the direction of

the main jet.In ﬁgure 3 the left panel shows the proﬁles of axial

velocities in the plane x-z plane and the right panel in the plane

y-z.

We can notice that Fluent simulations slightly break axial

symmetry (see ﬁg.3,left panel),this effect does not occur in

the OpenFoam simulations.We repeated the calculations with

OpenFoamfor three different meshes,all of themunstructured,

with 0:5 10

6

(called C-Course),0:75 10

6

(M-Moderate) and

1:0 10

6

(F-Fine) nodes.All results,plotted in ﬁgure 4 (plane

x z in the left panel,plane y z in the right panel),are al-

most symmetrical.In our later simulations,with combustion

processes enabled,additional turbulence kinetic energy is pro-

duced and departures fromaxial symmetry are prominent all the

time.

3.Turbulent,non-premixed combustion

Table 2:Notation.

C

d

model constant of the order of unity

D molecular diffusion coefﬁcient

~

k Favre-averaged turbulent kinetic energy

N scalar dissipation rate

Sc

t1

,Sc

t1

model constants of the order of unity

u

k

k-component of velocity vector

Y

mass fraction of specie

~ Favre-averaged energy dissipation

turb

turbulent viscosity

mixture fraction

mean value (in sense of Reynolds averaging) of

quantity

~

mean value (in sense of density-weight averag-

ing) of quantity

0

ﬂuctuation of fromReynolds averaged value

00

ﬂuctuation of from density-weight averaged

value

st

value of quantity where mixture fraction is

equal its stoichiometric value

!

production termof specie

3.1.Characteristics of syngas

Process of biomass gasiﬁcation gives unique combustible gas

called biomass syngas.This fuel is fully renewable and con-

tains mainly nitrogen (if gasiﬁcation was made in pure oxygen

and biomass was nitrogen-free,nitrogen would be absent),hy-

drogen and carbon monoxide (detail compositions,measured in

real-life gasiﬁers,are presented as mass fractions in table 4 and

as volume fractions in table 3).Due to its relatively low mean

caloriﬁc value,strongly ﬂuctuating composition and admixture

of soot and other solid components,syngas is most often burnt

in combustion chambers.Due to the fact that produced syngas

contains methane and other hydrocarbons,we have to use the

scheme for chemical reactions that allows for the combustion

of not only hydrogen and CO ([11]) but also of hydrocarbons.

The syngas generally does not contain hydrocarbons higher that

three atoms of carbon (table 3).Hence we can use the GRI3 [14]

detailed mechanism of chemical reactions and thermodynamic

data.We use the GRI3 for laminar ﬂamelet.It is based on

6 elements and 53 species appropriate for syngas and includes

more than 300 reactions.The simulations were performed for

the whole set of 53 species and for a simpliﬁed set of 20 species.

3.2.Conserved scalar approach

All species present in the combustion chamber obey the

advection-diffusion (1) with nonlinear source term describing

the chemical conversions of the species.

@(Y

)

@t

+

@(u

k

Y

)

@x

k

=

@

@x

k

D

@Y

@x

k

+!

(1)

Under the assumption of equal diffusivities of all species,a

reasonable assumption for turbulent ﬂow,we can use the con-

served scalar approach to separate the modelling of ﬂow and

combustion [15].For turbulent,non-premixed combustion it is

convenient to introduce the mixture fraction variable, (some-

times denoted also as f),deﬁned over the whole space and time,

to be the mass fraction of the material that originated from the

fuel stream.The origin of the material is constant during chem-

ical reactions or conversions,so the mixture fraction is con-

served (eqn.2).If combustion does not occur,the mixture

fraction simpliﬁes to fuel mass fraction.

@()

@t

+

@(u

k

)

@x

k

=

@

@x

k

D

@

@x

k

(2)

We usually normalise mixture fraction,so that = 1 in the

fuel stream and = 0 in the oxidiser stream which simpliﬁes

the boundary conditions for fuel and oxidiser inlets (see table

5).Mass fractions of the particular species of fuel are presented

in table 4.The sum over all species,according to deﬁnition of

mixture fraction,should be 1.

For large-scale complex ﬂows with turbulence the set of

conservation equations (eq.2 also) has to be averaged.For

ﬂows with strong variation of density,which occurs naturally

in the combustion processes,the method of choice is density-

weighted average (also called Favre average,[4]) deﬁned as

~

=

:(3)

Here the averaged quantity is split, =

~

+

00

,where

~

is the

Favre-averaged value and

00

is the departure (ﬂuctuation) from

the density-weighted mean.The second

0

is added to distinguish

00

fromthe ﬂuctuations in RANS averaging

0

..

The Favre-averaged version of the equation of mixture frac-

tion conservation takes the following form:

@(

~

)

@t

+

@( ~u

k

~

)

@x

k

=

@

@x

k

D

@

@x

k

@(

^

u

00

k

00

)

@x

k

:(4)

For non-reacting scalar the gradient assumption can be used

for the last term on the right hand side (see [4]),so

]

u

00

k

00

=

Figure 2:Comparison of the OpenFoam(left) and Fluent (right) results,fro the simulations on the ﬁne grid (1:010

6

nodes).Qualitative

observation is that the OpenFoam jet spreads slightly wider and slower than that in Fluent.Quantitative comparisons are presented

below.

Figure 3:Comparison of the simulations with Fluent (FL solid lines) and OpenFoam (OF dashed lines),for the ﬁne grid (1:0 10

6

).

Four radial proﬁles of axial velocity V

axial

at different z stations (distance measured from the top surface) are plotted:0:5m (red),

1:5m(navy),2:5 (brown) and 3:5m(green).Left panel shows the cross-section along x-axis and right panel - along the y-axis.

Figure 4:Dependence of the OpenFoamresults on the mesh size.Shown are the resulta for three meshes:0:5 10

6

(called C-Course),

0:75 10

6

(M-Moderate) and 1:0 10

6

(F-Fine).Four radial proﬁles of axial velocity V

axial

at different z stations (distance measured

fromthe top surface) are plotted:0:5m(green),2m(black),3:5 (violet) and 5m(red).Left panel shows the cross-section along x-axis

and right panel - along the y-axis.

Table 3:Composition of syngases (volume fraction) produced in the process of biomass gasiﬁcation.Syngas composition depends on

the type and parameters of the biomass and on the conditions of the gasiﬁcation process.

Volume fraction

syngas 0

syngas 1

syngas 2

syngas 3

syngas 4

syngas 5

syngas 6

syngas 7

Nitrogen (N2)

0.486

0.538

0.531

0.493

0.543

0.562

0.518

0.550

Carbon Mono.(CO)

0.240

0.264

0.302

0.310

0.257

0.270

0.285

0.200

Hydrogen (H2)

0.180

0.081

0.074

0.089

0.079

0.065

0.061

0.080

Carbon Di.(CO2)

0.060

0.073

0.051

0.058

0.059

0.044

0.054

0.040

Oxygen (O2)

0.004

0.019

0.021

0.019

0.0500

Water (H2O)

0.024

0.026

0.033

0.021

0.021

0.039

Methane (CH4)

0.03

0.019

0.017

0.019

0.017

0.014

0.018

CH2

0.040

Ethyne (C2H2)

0.040

Ethane (C2H6)

0.001

0.001

0.002

Propane (C3H8)

0.003

0.003

0.003

0:Biomass syngas,source:www.treepower.org.

1-6:Syngases produced fromwood wastes.Composition measured in industrial gasiﬁers.Courtesy of Modern Technologies and Filtration Sp.z o.o.

7:Syngases produced fromturkey feathers.Courtesy of Modern Technologies and Filtration Sp.z o.o.

Table 4:Composition of the same biomass syngases given as mass fractions.

Mass fraction

syngas 0

syngas 1

syngas 2

syngas 3

syngas 4

syngas 5

syngas 6

syngas 7

Nitrogen (N2)

0.568

0.567

0.562

0.529

0.567

0.583

0.536

0.590

Carbon Mono.(CO)

0.281

0.277

0.319

0.333

0.268

0.280

0.295

0.214

Hydrogen (H2)

0.015

0.006

0.006

0.007

0.006

0.005

0.005

0.006

Carbon Di.(CO2)

0.110

0.121

0.085

0.097

0.096

0.071

0.088

0.067

Oxygen (O2)

0.005

0.023

0.025

0.023

0.061

Water (H2O)

0.016

0.018

0.023

0.014

0.014

0.027

Methane (CH4)

0.020

0.012

0.010

0.012

0.019

0.015

0.020

CH2

0.021

Ethyne (C2H2)

0.040

Ethane (C2H2)

0.001

0.001

0.001

Propane (C3H8)

0.005

0.005

0.005

Table 5:Boundary conditions for turbulent non-premixed combustion.

Boundary

V

axial

[

m

s

]

V

radial

[

m

s

]

V

swirl

[

m

s

]

[]

0

2

[]

T

emp

[K]

Fuel inlet

10

0

0

1

0

800

Main air inlet

2

0

3

0

0

300

Swirl air inlets

6

0

6

0

0

300

Walls

0

0

0

0

0

1000 (300)

So far we have done simulations for hot and cold walls with uniform temperature distribution.Simulations with a more accurate temperature proﬁle

measured in a working industrial combustion chamber are currently under way.

D

t

@

@x

k

.In a turbulent ﬂow the turbulent diffusion coefﬁcient

D

t

is much larger than molecular diffusivity,so the latter is usu-

ally neglected.

As we shall see later,the second moment of mixture frac-

tion,

g

00

2

,is a parameter in the assumed probability density

function (PDF,see eq.8),so we must solve an additional equa-

tion for its temporal evolution (eq.6,ref.[16,17]).

@(

g

00

2

)

@t

+

@( ~u

k

g

00

2

)

@x

k

=

@

@x

k

turb

Sc

t1

@

g

00

2

@x

k

!

(5)

+2

turb

Sc

t2

@

~

@x

k

C

d

~

~

k

g

00

2

;

The mean values of the reacting scalars (mass fractions of

all species) can be calculated fromthe equation 6 using the pre-

sumed shape of the PDF of the mixture fraction,P(),and in-

tegrating over the whole mixture fraction space,

f

Y

=

Z

1

0

Y

()

~

P()d:(6)

The shapes of this PDF is an empirical result of many exper-

iments (cf.[18]).In numerical simulations of turbulent com-

bustion mainly two kinds of PDFs are used:the clipped Gaus-

sian function or a beta function,both parametrised by the mean

value of mixture fraction (obtained by solving equation 4 with

a CFDcode) and by root mean square of the ﬂuctuation of mix-

ture fraction (obtained by solving equation 6).Alternatively,

the whole set of equations for the reacting species should be

solve directly,which is a lot slower and less convenient.The

beta-function PDF of the mixture fraction is deﬁned by the the

formulae 8 and plotted in ﬁgure 5 for several values of the mean

mixture fraction and of the variations of mixture fraction.

P() =

1

(1 )

1

R

1

(1 )

1

d

(7)

=

~

~

(1

~

g

00

2

1

!

=

1

~

~

(1

~

g

00

2

1

!

Due to large density ﬂuctuations in the combustion process

we use the Farve-averaged version of the beta-function PDF

~

P() =

()

P() (8)

Figure 6:Typical mixture fraction distribution neat to inlets.

3.3.Laminar ﬂamelet

Combustion takes place when two conditions are fulﬁlled.

Firstly,the value of the mixture fraction should be close to sto-

ichiometric which ensures appropriate proportion of fuel and

oxidiser.Secondly,there should be a large gradient of the mix-

ture fraction,which distinguishes the case when fresh fuel is

mixings with oxidiser fromthe case when fuel and oxidiser are

already burnt [15].Often such zones (ﬂamelets) are consid-

erably thinner than the smallest characteristic length scale of

turbulence (Kolmogorov scale) and can be treated as a wrin-

kled sheet of constant,stoichiometric,value of mixture fraction

[19].Locally it is possible to introduce the coordinate system

with two coordinates parallel to the isosurfaces of the mixture

fraction (see ﬁg.6) and with mixture fraction as transversal co-

ordinate.Peters [4] reviewed the formal introduction of this co-

ordinate transformation and derived the equations for the mass

fractions of all species (eq.9) and for temperature (10).The

main processes in the such ‘mixture fraction space’ are diffu-

sion and chemical reactions.The inﬂuence of the ﬂuid ﬂow

on mixing is accounted for by considering the quantity called

scalar dissipation rate,N = 2Dr r,which may be inter-

preted as the inverse of the characteristic time scale of diffusion

[20].

@Y

@t

=

1

2

N()

@

2

Y

@

2

+!

(9)

@T

@t

=

1

2

N()

@

2

T

@

2

+!

T

:(10)

Figure 5:Beta-functions PDFs plotted for values of mixture fraction from0:1 to 0:5 (function is symmetrical with respect to = 0:5).

Each plot shows the PDFs for 6 values of the mixture fraction variance.

Figure 7:Scalar dissipation rate in the laminar ﬂamelet model.

Boundary conditions for these equations are such like for

counter-ﬂowing jets of fuel and oxidiser with a stagnation point

(again see ﬁg.6.In such situation the scalar dissipation rate can

be analytically calculated ( see ﬁg.7),

N() = N

max

e

2(erfc

1

(2))

:(11)

This formula is an approximation valid especially in the regions

of stoichiometric value of mixture fraction (

st

) and it gives the

stoichiometric scalar dissipation rate,

N

st

(

st

) = N

max

e

2(erfc

1

(2

st

))

:(12)

In a turbulent ﬂow to obtain the mean values of the mass

fractions,

f

Y

,one has to integrate over mixture fraction and

over all possible values of the stoichiometric scalar dissipation

rate,

f

Y

=

Z

1

0

Z

1

0

Y

(;N

st

)

~

P(;N

st

)ddN

st

:(13)

Above a certain value of the scalar dissipation rate reactions

are always quenche so,in practice,the integration over in the

formula 13 is limited to a sub-interval of [0;1].

The joint probability density function of

~

P(;N

st

) is gen-

erally unknown.In the literature of the subject ([19,4,21,22])

it is discussed and commonly assumed that and N

st

are sta-

tistically independent,so

~

P(;N

st

)

~

P()P(N

st

):(14)

Under the assumption of weak ﬂuctuations of N

st

,the proba-

bility density function P(N

st

) reduces to

P(N

st

) = (N

st

~

N

st

);(15)

where

~

N

st

is typically modelled in the following way ([23])

~

N

st

=

C

N

g

00

2

k

:(16)

Great advantage of the methods based on tabulated chem-

istry,like laminar ﬂamelet method,is the posibility of doing

all calculations of chemical reactions once,before running the

the ﬂuid-mechanical simulations.The Flamelet Library built in

such way consists of solutions of eqs.9 and 10 depending on

the values of the mixture fraction and of the scalar dissipation

rate.Both these quantities,and also the variations of the mix-

ture fraction that are nessesary for the beta-function PDF,are

computed in the CFD code.In ﬁgure 8 we show so tabulated

functions (temperature and Y

for selected species) from the

Flamelet Library computed with Fluent Selected dependencies

fromFlamelet Library are plotted in ﬁg.8.

Figure 8:Solutions of the Flamelet equations computed by Fluent.The panels show the dependence of temperature and of the selected

species concentrations on mixture fraction.

3.4.Results

The results are obtained using steady-state,pressure-based Flu-

ent solver.Among simulating processes are turbulent ﬂows,en-

ergy transfer,radiation and non-premixed combustion,details

of Fluent setup are listed at the table 6.

Table 6:Summary of Fluent setup for the simulations of turbu-

lent combustion.

Models

Energy

Turbulence

Realizable k

Radiation

P1

Non-premixed combustion

Steady Flamelet

Solver

Steady-state

Pressure based

Even in this early stage the simulations correctly reproduce

major features of the real combustion process which we ob-

serve in the working industrial burner.Firstly,the length of

the jets is consistent with observations.Although their extent

varies somewhat fromsimulation to simulation and depends on

the mesh size and on the wall temperature,they reach down,

roughly,to the middle of the combustion chamber (see ﬁgures

9).Secondly,simulations in all cases predict the presence of the

updraft near the wall of the chamber.The effect of this updraft is

clearly visible in the pattern formed by solid particles deposited

on the wall.Thirdly,none of the computational results show

symmetry,neither axial nor planar.In fact the ﬂow that we ob-

serve in the working combustion chamber always lacks symme-

try.Large departures from axial symmetry are clearly seen and

is currently being documented by the measurements of external

wall temperature.Visual observations as well as the analysis of

the high-speed camera recording show the combustion process

to be unsteady.The time dependence of the ﬂowand the effects

of unsteadiness cannot be captured by our steady-state (RANS)

simulations.In particular we are not able to predict any time-

dependent phenomena,like oscillations of the jet length or jet

precession.

4.Conclusions

The simulations of non-reacting ﬂows,which we presented in

the ﬁrst part of the paper,were made using both Fluent and

OpenFoam.In both cases the results are in reasonable agree-

ment.Since the OpenFoam CFD package seems reliable for

non-reactive ﬂows we are going to test its reacting ﬂow solvers

in the near future.Only a few OpenFoam solvers are dedicated

to combustion or reacting ﬂows,i.e.reactingFoam,ﬁreFoam.In

addition there are solvers designed specially for Diesel engine

simulations.

The simulations of combustion are highly sensitive to

changes in the process parameters,mainly to the ﬂuctuations

of temperature.

Qualitative observations made in the real-life device work-

ing in an industrial plant provide strong evidence of the ﬂow

being time-dependent.Through a window located opposite the

outlet we observe four main modes:1) ﬂame not visible at all;

2) clockwise ﬂame vortices appear momentarily and then are

transported by the ﬂowto the outlet;3) entire bottompart of the

chamber is ﬁlled with ﬂames;4) anticlockwise ﬂame vortices

ﬂow to the outlet.

From these observations we can infer the following four

distinct possibilities:

i) the dominant mode is oscillatory;

ii) there coexist different steady-state regimes and ﬂuctuations

cause the ﬂow to ‘switch’ between those regimes;

iii) the ﬂow is fully unsteady but on the slow time scale well

separated from the much short time scales of turbulence and

combustion.

High-speed camera recordings,with time resolutions vary-

ing from400 frames per second to 10000 frames per second,al-

lowus to estimate the characteristic times scale of these modes.

The fastest modes are 1) and 3) with time scale of the order

0:01s while modes 2) and 4) are one or even two orders of mag-

nitude slower.

a) b) c)

Figure 9:Colour map of velocity magnitude in the x z plane sections:

a) ﬁne mesh (10

6

nodes),hot wall (1000K);b) coarse mesh (0:5 10

6

nodes),hot wall (1000K);c) coarse mesh (0:5 10

6

nodes),cold

wall (300K).

a) b) c)

Figure 10:Results of the combustion simulations computed with Fluent.Colour maps of temperature the x z plane sections:

a) ﬁne mesh (10

6

nodes),hot wall (1000K);b) coarse mesh (0:5 10

6

nodes),hot wall (1000K);c) coarse mesh (0:5 10

6

nodes),cold

wall (300K).

In order to capture and analyse temporal variations we cur-

rently running the unsteady RANS simulations.We are also

planning to performLES simulations for both reactive and non-

reactive ﬂows.Those require much ﬁner mesh.The LES solvers

are also being developed for OpenFoam and we are going to

compare their results with Fluent.

The main long-termgoal of this work,is to reduce the emis-

sion of nitric oxides.The production of the NO

x

is a highly sen-

sitive process and its modelling requires very accurate simula-

tions of the ﬂowﬁeld as well as the most sophisticated chemical

reaction model.

5.Acknowledgements

This research is sponsored by the Foundation for Polish Science

programme VENTURES (operated within the Innovative Econ-

omy Operational Programme 2007-2013).Numerical computa-

tions were performed in the Interdisciplinary Centre for Com-

putational and Mathematical Modelling (ICM),University of

Warsaw,grant number G34-8.KK’s visitsg to the Univer-

sity of Cambridge are supported by the Young Scientists Pro-

gramme of the British Council and Polish Ministry of Science

and Higher Education.All experimental works were carried in

the gasiﬁcation system designed by Modern Technologies and

Filtration Sp.z o.o.(MTF).

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