bhel final paper nov

8/4/2019 BHEL Final Paper Nov

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Modeling Coal Combustion : Effect of Combustion

Kinetic Parameters

V.Saravanan*+

, S.Jayanti+

, R.K.Kumar* & S.Seetharamu*

*Central Power Research Institute, Bangalore+Department of Chemical Engineering, IIT Madras, Chennai

Abstract

The use of computational fluid dynamics (CFD) models to describe the combustion of coal in utility combustion

chambers has become an important aid in the design process, but increasing demands are being placed on the

technique to give quantitative results rather than qualitative trends. In order to make reliable quantitative

predictions about combustion behaviour of coal particles, it is imperative that the underlying processes of coal

devolatilisation and char oxidation are accurately described. The coal combustion models used in the

commercial CFD codes are based on the empirical relations involving the combustion kinetic parameters viz.

activation energy (E), frequency factor (A), total volatile (V), diffusion coefficient (D), etc., experimentally

obtained from bench/ pilot scale studies for typical coal. Thermogravimetric analysis (TGA) of Indian coals

shows that the combustion behaviour of Indian coals are significantly different. This paper presents thesensitivity analysis of combustion kinetic parameters viz. E, A, Vand diffusion coefficient, on the combustion

behaviour of coal particles in IFRF No.1 furnace. The efforts underway to obtain these parameters

experimentally using TGA and Drop Tube Furnace (DTF) are also described

1.0 Introduction

The increased demand for fossil fuels in recent years has resulted in a greater interest to improve

energy utilization and reduce pollutant emissions from fossil fuel combustion systems. Computer

simulations of combustion systems can give insights into the phenomena occurring inside combustion

and flow systems and can be used as design and analysis tools to improve efficiency and reduce

pollutant emissions. However, these simulations are very complex, not only due to the numericalissues associated with solving the necessary equations but also because of the problems associated

with mathematically describing the important chemical and physical processes occurring in these

systems. Coal combustion models use four well-defined steps: heating up, devolatilisation, volatile

combustion and the combustion of the char; as well as sub models to describe pollutant formation,

slagging and the physical steps such as fluid flow and heat transfer. In order to make reliablequantitative predictions about combustion behavior of coal particles, it is imperative that the coal

devolatilisation and char oxidation parameters are needed to be accurately described in the model

input. A brief description about the processes governing coal combustion and the widely applied

models used to define them are given under.

1.1 Devolatilisation of coals

Moisture present in the coal will evolve early as the temperature rises. As the temperature continues

to increase, gases and heavy tarry substances are emitted. The extent of this pyrolysis can vary from afew percent up to 70-80% of the total particle weight and can take place in a few milliseconds or

several minutes depending on coal size and type, and on temperature conditions [1]. The heating rate

of the particle is one of the important factor, which decides the extent of pyrolysis. The rapid heating

rates (104-105oC) give rise to the maximum yield of volatiles than under slow heating conditions or in

proximate analysis.


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Among the many proposed models for devolatilisation, the most used models in the commercial CFDcodes are single-step devolatilisation model proposed by Badzioch and Hawksley [2] and the two

competing reactions model proposed by Kobayashi et.al. [3]

In single-step devolatilisation model, the devolatilisation is assumed to be a first-order reaction

process, with the reaction rate being proportional to the amount of volatile matter still remaining in

the coal. The correlation used is;

( )VVkdt

dVV = --------------------(1)

Where, dV/dtis the rate of devolatilisation, kv is rate constant, Vis the maximum volatile yield and V

is the lost volatile matter at any instant t. The dependence of kv on the temperature is given by the

Arrhenius relationship;

=

P

V

VVT

EAk exp -------------------------(2)

Where,Av is the frequency factor,Ev, the activation temperature and Tp is the particle temperature in

absolute scale. The change of volatile fraction with respect to time is obtained from

=

t

VdtkVV

0

exp1 ------------------------------(3)

In this case, the parameters viz.Av,Ev and Vfare the input for the model and they have to be evaluated

for the specific coal dust under consideration.

The two competing reaction model suggests that the pyrolysis could be modeled with the following

pair of parallel, first order, irreversible reactions

2222

2

1111

1

)1(

)1(

VYSYC

VYSYC

k

k

+

+--------------------(4)

With the rate equations

ckkdt

dc)( 21 += ----------------(5)

And

ckYkYdt

dvdv

dt

dv)( 2211

21 +=+

= --------------------(6)

Here, k1 and k2 are Arrhenius-type rate coefficients and the important feature of this model is that, it is

assumed that E1


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oxygen is given by kd (Pg-Ps), where Pg is the partial pressure of oxygen in the furnace gases far fromthe particle boundary layer and Ps is the oxygen pressure at the particle surface. The value of Kd is

given by:

P

PTT

Rk A

gP

P

d

75.07

2

1053.2

+=

-------------(7)

Where, Rp is the particle radius, TP is the particle temperature and Tg is the far-field gas temperature.Further P is the local pressure and PA is atmospheric pressure. The char oxidation rate per unit area of

particle surface is given by kc;

=

P

C

PCCT

TTAk exp ---------------(8)

Where, the parameters Ac and Tc depend on the type of coal, and are specified as input parameters.

For this model, kd and kc are in units of kg/m2 /atm/s, and recommended values for Ac and Tc

are 497 s-1

and 8540oK. The overall char reaction rate of a particle is given by:

( )A

PgCd

P

PRPkk

2114+

------------------(9)

And is controlled by the smaller of the rates kd and kc.

The alternative char oxidation model, the Gibb model, takes into account the diffusion of oxygen

within the pores of the char particle. The oxidation mechanism of carbon can be characterized by the

parameter so that oxides are produced according to the equation

( ) ( ) 22 212 COCOOC ++ ----------(10)The value of is assumed to depend on the particle temperature TP

A number of commercial CFD codes have been developed and those widely used for modeling coal

combustion are CFX, FLUENT, PHOENICS and STAR CD. The CFD codes are dependent on the

accuracy of the sub-models contained within them and most have common characteristics such as the

mathematical methods of solution, the fluid flow and heat transfer sub-models that are of greatimportance. These codes provide generalized values for the combustion kinetic parameters (Ev, Av,

V, Ac, etc) and other empirical constants derived for certain coals. These default values may not be

suitable for all the coal types viz. Lignite, sub-bituminous coals, low and high volatile bituminous

coals and anthracite. These parameters are to be evaluated for a specific coal under consideration. The

estimation of these parameters needs comprehensive experimental methodologies closely simulating

the actual process.

This paper presents the numerical analysis of the sensitivity of the combustion kinetic parameters viz.

E, A, Vand diffusion coefficient, on the combustion behaviour of pulverized coal particles which is

modeled in IFRF No.1 furnace. The application of various experimental methodologies viz.

Thermogravimetric analysis (TGA) and Drop Tube Furnace (DTF) in determining these parameters

has also been brought out in this paper

2.0 Results and Discussion

The present simulation is carried out using the commercial code CFX-10 on the geometry of IFRF

No.1 furnace with the geometrical details given by Visser et al [5]. A high ash Indian coal has been

taken for assessing the effect of devolatilisation kinetic parameters. The coal properties are given in

Table -1. The effect of diffusion coefficient on the char oxidation process presented in this paper was


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obtained from the studies made by S.Jayanti et al [6]. Single-step devolatilisation model proposed byBadzioch and Hawksely and Field char oxidation model have been used in the present study.

The coal combustion model considered here suggests that the particle, at any time in the reaction

process, is composed of moisture, raw coal, char and ash [1]. The raw coal is the maximum volatile

matter content of the coal particles (assumed to be in solid form). The raw coal is released out of the

particle as fuel (gaseous combustible matter) when devolatilisation is taking place. The fuel willfurther undergo combustion in the gaseous phase to form gaseous products. The left out solid residue

after devolatilisation contains char and ash. The char will further get oxidized to form gaseous

products and ash. The final constituent of the solid particle is only ash if the combustion is complete.

The turbulence and radiation were treated by the k- and discrete transfer sub-models respectively.

The particle heat transfer was treated by the Rans-Marshal model and the gaseous combustion was by

mixed is burnt probability density function approach.

The default values given for the activation temperature (Ev), frequency factor (Av) and the total

volatile yield (V) in CFX-10 are 8850oK, 134000s-1 and 1.25 (Q-factor) times that of the proximate

volatile matter respectively. These are close to the values obtained by Badzioch and Hawksley [2],

from the devolatilisation kinetics of coal samples studied in a drop tube furnace. In the present work,values of these parameters were varied systematically, and the sensitivity of this variation on the

combustion behaviour of coal was studied.

2.1 Effect of devolatilisation activation temperature:

The activation temperature is given by the ratio between the activation energy and the universal gas

constant in the Arrhenius relation. The activation temperature value reported by Badzioch and

Hawksley is 8800oK [2] for the coal samples with proximate volatile matter content 11.5 to 42.0%

(dry ash free basis). The calculated activation energy in this case was 73.163kJ/kg (75kJ/kg).

In order to assess the sensitivity of this parameter towards the combustion behaviour, three different

values viz. the default value (73.163kJ/kg), a lower value of activation energy (50kJ/kg) and a highervalue of activation energy (100kJ/kg) than the default value were considered. The respective

activation temperatures would be 8850oK, 6014oK and 12027oK. The pre-exponential value was

assumed to be constant and assigned the default value, 134000s-1

as given in the CFX-10 code. The

results obtained for the simulations are given in Fig.1-1-Fig1-12.

The profiles obtained in the IFRF No.1 geometry show significant difference in respect of the volatile

evolution and gaseous volatile combustion for different activation temperature values. The increase of

the magnitude of activation temperature significantly delayed the volatile evolution (Fig1.1-1.3) and

made the gaseous volatile combustion more and more diffusive (Fig 1.4-1.6). This lead to the dilution

of heat energy released from volatile combustion. The delay in char oxidation (Fig1.7-1.9) was due to

the diffusive profile of volatile combustion, as the char ignition needs minimum threshold energy that

is normally derived from volatile combustion. The XY plots of the variation of volatile evolution,volatile combustion and char oxidation with the axial distance of the furnace are given in Fig. 1.10-

1.12 respectively.

It is apparent from the XY plots that, the volatile evolution (Fig. 1.10) was completed at themaximum axial distance of 0.45m from the burner inlet for 6014oK activation temperature and this

was delayed to the distance of 0.55m and 0.80m for 8850oK and 12027

oK activation temperatures

respectively. Similarly the volatile combustion (Fig.1.11) profiles show the increase of diffusivities

when the activation temperature is increased from 6014oK to 12027

oK. The increase of delay in char


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oxidation with the increase in activation temperature is shown in Fig.1.12. The delay of the completeoxidation of char particles is about 5m to 7m for the increase of activation temperature from 6014 oK

to 12027oK respectively.

2.2 Effect of devolatilisation pre-exponential/frequency factor:

The frequency factor value reported by Badzioch and Hawksley was 115000s -1 [2] for the coalsamples with proximate volatile matter content 11.5 to 42.0% (dry ash free basis). This has been

approximately taken as the default value (134000s-1

) in CFX-10. The effect of frequency factor in the

single step devolatilisation model towards the combustion behaviour of coal particles is assessed by

increasing the default value (134000s-1

), by two fold (268000s-1

) and decreasing by two fold(67000 s-1). The default activation temperature 8850 oK value in the CFX-10 code is assumed to be

the same for all these cases. The results are given in Fig.1.13-1.24.

As the frequency factor is only the multiplication factor in the Arrhenius relationship, the change in

the values, has not significantly affected the combustion profiles though there is a slight systematic

variation is observed. As the frequency factor is increased the rate of the kinetics is also increased.

The diffusivity in volatile combustion (Fig 1.16-1.18 & Fig.1.23) and delay in char oxidation (Fig

1.19-1.21 & Fig 1.24) due to the variation of frequency factor are found subtle.

2.3 Effect of maximum volatile yield

In the present study, the total volatile yield is assumed to vary between 1.25 (default value) to 2.25

times that of the proximate volatile matter. All other default values (activation temperature - 8852oK

and frequency factor-134000s-1

) were assumed to be constant. Badzioch and Hawksley [2],

established that the Q-factor (The factor of increase in volatile at high heating rates with respect to

proximate volatile matter) is ranging from 1.30 to 1.51 for weakly swelling coals and 1.43 to 1.83 for

highly swelling coals.

The increase in maximum volatile yield decreases the char mass fraction by the same amount since

the coal is assumed to be composed of raw coal, char and ash on dry basis. The increase of rawcoal mass fraction due to the increase of Q-factor is explicit in the Fig. 1.34. This profile does not

show significant variation in the rate of volatile release. But, surprisingly, the volatile combustion

(Fig 1.35) and the char oxidation (Fig.1.36) profiles in the case of where the Q-factor is 2.25, are

quite diffusive and some of the particles escape the domain with partial combustion.

2.4 Effect of char oxidation diffusion coefficient

In the classical shrinking core model of char combustion, the effect of ash is taken into account by

considering a thin ash layer surrounding the char particle through which oxygen has to diffuse.

Accordingly, the diffusion rate of oxygen is reduced in the presence of ash [7]. If the ash content

increases significantly, it is possible that the thickness of the hypothetical ash layer surrounding the

char particle may also increase. This would have the effect of further decreasing the rate of diffusionof oxygen to the surface of the combusting char particle. Thus, kd will be reduced as the ash content

of the coal increases.

In order to see if this would have a significant effect on the overall furnace parameters, calculations

would have to be made with reduced values of kd. This can be done for example by reducing the

coefficient 2.53 10-7 in equation (10). The effect of reducing kd by a factor of 2.5 are shown inFig.3, where, for the sake of comparison, the reference case and the case for a 2.5 times increase in

the value ofkdare also shown. The variation of the particle temperature and the particle mass (due to


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devolatilization and char burnout) are shown along the length of the furnace. The particle massvariation with length has four distinct phases: (i) the initial heating up stage where the mass does not

change, (ii) the rapid devolatilization stage its mass decreases rapidly, (iii) the slower char burnout

stage and (iv) the heating or cooling stage of the particle containing only ash. The effect of changing

the oxygen diffusion rate for char burnout has a significant effect only on the third stage. Reducing

the oxygen diffusion rate slows down the char burnout rate while increasing it marginally increases it.

Examination of the particle temperature variation (Fig. 3a) shows that this has a strong effect on thepeak particle temperature. In all the cases, the peak temperature occurs in the char burnout stage (see

Fig. 3b). When the oxygen diffusion rate is increased, the faster burnout rate increases the maximum

temperature to nearly 3000K while with the decreased diffusion rate, the peak particle temperature is

about 1000oK less. The peak gas temperatures also occur later in the furnace in the latter case

although the peak value is nearly unchanged. The gas outlet temperatures are nearly the same.

These results show once again that the overall furnace parameters are dependent on the heat transfer

characteristics rather than on the combustion characteristics. The presence of excess ash and the

consequent decrease in oxygen diffusion rate may lead to substantial reduction in char combustion

without significantly affecting the overall combustion parameters. Similar insensitivity of the peak

and outlet temperatures to the increase in ash content has been reported by Kurose et al (2001), [8]when investigating combustion of coals with ash content in the range of 36% to 53%.

3. Experimental methodologies for determining combustion kinetic parameters

There are many experimental methodologies established for assessing the combustion kinetic

parameters which include, Thermogravimetric Analysis (TGA) / Derivative Thermo Gravimetric

Analysis, Heated Wire Grid (HWG), Drop Tube Furnace (DTF), etc. The details of TGA/DTG and

DTF are discussed in brief.

3.1 TGA/DTG

In TGA, a small quantity of the powdered sample is heated on a highly sensitive microbalance in a

given atmosphere, either in an isothermal mode or non isothermal mode with a pre-set rate oftemperature rise. The change in weight of the sample is measured and plotted as a function of furnace

temperature (non-isothermal) or time (isothermal). TGA is mainly used for compositional analysis of

coal, to determine the temperature ranges of weight changes and to investigate the char burnout [9].

DTG is similar to TGA except that a continuous plot of the rate of weight loss with time as a function

of furnace temperature produced. When the coal is heated in an atmosphere of flowing air, the

graphical plot produced is generally known as the burning profile curve. If an inert gas such as

nitrogen is used instead, the profile obtained is known as the volatile release profile. DTG analysis

provides a finger print of the complete combustion process of coal, giving an assessment of its

relative combustion characteristics including ignition, flame stability, burnout and reactivity. The

standard interpretation of the burning profile curve of a coal produced is given in Fig.4. The point

where the curve crosses the base line is termed as the initiation temperature (ITvm), from where thevolatile loss commences . The balance of the burning profile represents devolatilisation and oxidation

of the coal, with a small effect due to the decomposition of minerals. The order of reactivity of coalis assessed primarily on the peak temperature (PT, the temperature of the maximum rate of weight

loss); the higher this temperature the less reactive the coal. Coals with greater weight profiles, which

extend into very high temperature ranges indicate slow burning coals for which longer combustion

times or higher temperatures are require for complete combustion. The coals with higher weight loss

rates at lower temperatures are easier to ignite and burn. The burnout temperature (BT) is thetemperature at which combustion ceases.


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Assuming the combustion process in the TG/DTG tests follow first order kinetics, the following

equations are emploued for calculating the rate constant;

=

dt

dW

Wk

1

Where, k is the reaction rate coefficient, W is the weight of unburned combustible and dW/dt is theinstantaneous rate of weight loss. The reaction rate coefficient (k) can be related to temperature by the

Arrhenius equation:

=

RT

EAk exp

Where A is the frequency factor, E the activation energy, R the universal gas constant and T is the

temperature in absolute scale. The value of rate constant k for various temperatures T can be obtainedfrom the burning profile of the DTG plot. The plot of log k vs. 1/T yields the value of A (intercept)

and E (slope). If the burning profile contains multiple peaks, that leads to different activation energy

values, in which case weighted mean activation energy can be taken for calculations. It is derived

from

Em = F1.E1+F2.E2+.Fn.EnWhere, F1 to Fn are the combustible content of the samples burned during each region of Arrhenius

linearity, and E1 to En are the individual values of apparent activation energy obtained over each

corresponding period of Arrhenius linearity.

These results are dependent on the test conditions and apparatus (as well as coal characteristics). Themaximum heating rate achieved in TGA/DTG is 102K/s. This cannot simulate the conditions as

prevailing in the utility boilers where the heating rate is about 10 5-106K/s. As the devolatilisation

process is sensitive to heating rate, the maximum volatile yield (V) obtained in this technique will be

lesser than the actual volatile yield at high heating rates. However, TGA/DTG methodology is highly

useful in determining the relative reactivity of different coals and which can give preliminary ideasabout the comparative reactivities of different coals.

3.2 Drop Tube Furnace ( DTF )

These are the reactors that closely simulate the combustion conditions in industrial PF combustors.

The essential characteristics of these types of reactors are: high heating rates (104

to 105

K/s), hightemperature (up to 1800oC), dynamic dilute particle phase and atmosphere simulating conditions.

In most widely used versions of a DTF system, size graded coal/char/mineral matter particles

(typically


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agreement with that of the utility boilers, since the heating rate of this system is almost same as thatof the utility boilers.

Central Power Research Institute, Bangalore has developed an instrumented drop tube furnace

(Fig.5) for the systematic way of assessing the combustion kinetic parameters viz E, A, k, etc. in

respect of devolatilisation and char oxidation for a specific solid fuel. This facility can also be used

for assessing the combustion behaviour of blended coals and biomass fuels. This system closelysimulates the conditions as prevailing in the industrial pulverized fuel combustors.

4.0 Conclusion

It is observed that the combustion kinetic parameters are having significant effect towards the

combustion behaviour of coal particles. As these are the input parameters for the coal combustion

modeling, these values should be precisely described to get a reliable output. As these parameters are

dependent upon a specific coal type, they have to be evaluated through the experimental

methodologies closely simulating the actual process. There are various experimental methodologies

in assessing the combustion reactivity of coal. TGA/DTG gives burning profile of coal samples,

however, the heating rate employed is not comparable with the industrial pulverized fuel combustors.

Considering the modeling of coal combustion, drop tube furnace appears to be a reliablemethodology, which simulates the conditions as near to the conditions in the industrial PF

combustors. This can be used to evaluate the combustion kinetic parameters required for coal

combustion modeling for a specific coal under consideration.

5.0 References

1. Smoot, L.D. & Smith, J.P., Coal Combustion and Gasification, The Plenum ChemicalEngineering Series, Plenum Press New York. (1985),

2. Badzioch,S. & Hawksley, P.G.W., Kinetics of Thermal Decomposition of Pulverised Coalparticles, Ind. Eng. Chem. Process Des. Dev., 9, 521(1970)

3. Kobayashi, H., Howard, J.B., & Sarofim, A.F, Coal Devolatilization at High Temperatures,18

th

Symposium (International) on Combustion, The combustion Institute, Pittsburg, PA, 411(1977)

4. Field D.W., Gill B.B. & Hawksley The Combustion of Pulverized Coal, British CoalUtilization Research Association, Leatherhead, Surrey, UK. (1967)

5. Visser B. M. Mathematical odeling of swirling pulverized coal flames, Dissertation,Technische Universiteit Delft, the Netherlands. (1991)

6. Jayanti,S., Maheswaran, K., & Saravanan, V., Assessment of the effect of high ash contentin pulverized coal combustion Article in press, Applied Mathematical Modeling Journal

(2006).

7. Puri I.K. Environmental Implications of Combustion Processes, edited by I.K. Puri, CRCPress, Boca Raton, Florida, USA.(1993)

8. Kurose R., Ikeda M. & Makino H. Combustion characteristics of high ash coal inpulverized coal combustion,J. Fuel, Vol. 80, pp. 1447-1455. (2001)

9. Carpenter, A.M. & Skorupska, N.M. Coal combustion-analysis and testing, IEA CoalResearch, London, (1993)

10.Sorensen, L.H., Clausen, S., Astrup, P., Jensen, P.A., Porsdal & H., Oslen, A., Fundamentalsin combustion. Pyrolysis and reactivity measurements with a new atmosphereic entrainedflow reactor, and description of a burning particle in a controlled atmosphere EFP-85-project

Em jr.nr. 1323/85-4, Roskilde, Denmark, Riso National Laboratory, 140pp (May 1991)


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Table-1: Coal properties taken for combustion modeling (Effect of Ev, Av andV)

Properties of coal ValuesProximate analysis (As analyzed basis, %)

Moiture 7.20

Volatile matter (%) 27.60

Char (%) 24.80Ash (%) 40.40

Ultimate analysis (As analyzed basis, %)

Carbon (%) 41.90

Hydrogen (%) 2.78

Nitrogen (%) 0.94

Sulphur (%) 0.26

Oxygen (%) 6.52

Properties of coal

Particle size (m) 60

Density of char (kg/m3) 2000

Density of volatiles (kg/m3) 1560

Density of ash (kg/m3) 1000

LCV of volatiles (MJ/kg) 2.623

LCV of char (MJ/kg) 3.29

Molecular weight of coal 93

Emissivity of coal 1.0

Emissivity of char 0.6

Mass flow rate (kg/s) 0.163

Table 2: Coal properties taken for combustion modeling (Effect of diffusion coeff.)[6]

Properties of coal ValuesProximate analysis

(% w/w dry basis)

Volatile matter (%) 36.3Char (%) 52.9

Ash (%) 10.8

Ultimate analysis

(% w/w dry ash free basis)

Carbon (%) 75.37

Hydrogen (%) 4.47

Nitrogen (%) 1.15

Oxygen (%) 18.94

Properties of coal

Particle size (m) 60

Density of char (kg/m3) 2000

Density of volatiles (kg/m3) 1560

Density of ash (kg/m3) 1000

LCV of volatiles (MJ/kg) 2.623

LCV of char (MJ/kg) 3.29

Molecular weight of coal 93

Emissivity of coal 1.0

Emissivity of char 0.6

Mass flow rate (kg/s) 0.124


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Fig. 1.1 Fig.1.2 Fig.1.3

Volatile evolution for three different values of activation temperatures -, 6014oK , 8850

oK and 12027

oK

Fig. 1.4 Fig.1.5 Fig.1.6

Volatile combustion for three different values of activation energies -, 6014oK , 8850

oK and 12027

oK

Fig. 1.7 Fig.1.8 Fig.1.9

Char combustion for three different values of activation temperatures-, 6014oK , 8850

oK and 12027

oK

Fig. 1.10 Fig.1.11 Fig.1.12

Variation of Volatile evolution, volatile combustion and char combustion along the axial distance for

different activation temperatures, 6014oK , 8850

oK and 12027

oK


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Fig. 1.13 Fig.1.14 Fig.1.15

Volatile evolution for three different values of pre-exponential factor 67000 s-1

, 134000 s-1

& 268000 s-1

Fig. 1.16 Fig.1.17 Fig.1.18

Volatile combustion for three different values of pre-exponential factor 67000 s-1

, 134000 s-1

& 268000 s-1

Fig. 1.19 Fig.1.20 Fig.1.21

Char combustion for three different values of pre-exponential factor 67000 s-1

, 134000 s-1

& 268000 s-1

Fig. 1.22 Fig.1.23 Fig.1.24

Variation of volatile evolution, volatile combustion and Char combustion for three different values of pre-

exponential factor 67000 s-1

, 134000 s-1

& 268000 s-1


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Fig. 1.25 Fig.1.26 Fig.1.27

Volatile evolution for three different values Q- factor -1.25,1.75 & 2.25

Fig. 1.28 Fig.1.29 Fig.1.30

Volatile combustion for three different values Q- factor -1.25,1.75 & 2.25

Fig. 1.31 Fig.1.32 Fig.1.33

Char combustion for three different values Q- factor -1.25,1.75 & 2.25

Fig. 1.34 Fig.1.35 Fig.1.3

Variation of volatile evolution, volatile combustion and char combustion along axial distance form inlet

for different values Q- factor -1.25,1.75 & 2.25


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Fig.3 Computed variation with axial position of (a) particle mass and (b) particle

temperature for the reference case and for a decrease/ increase in the oxygen diffusionrate by a factor of 2.5. Ref-[6]

Temperature of max. rate of weightloss due to moisture evaporation

o ITVM, initial temperature of volatilematter ( weight loss first begins to

fall )

ITFC, initial temperature of fixedcarbon (rate of weight loss

accelerates)

PT, Peak Temperature ( max. rateof weight loss)

BT, burn out temperature(combustion ceases)

Fig.4 Burning profile of Typical coals Fig.5. Instrumented Drop Tube system at

CPRI

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