-
Minerals Engineering 74 (2015) 4150Contents lists available at
ScienceDirect
Minerals Engineering
journal homepage: www.elsevier .com/locate /minengOptimization
of a fully air-swept dry grinding cement raw meal ball millclosed
circuit capacity with the aid of
simulationhttp://dx.doi.org/10.1016/j.mineng.2015.01.0060892-6875/
2015 Elsevier Ltd. All rights reserved.
Tel.: +90 252 2111938; fax: +90 252 2111912.E-mail addresses:
[email protected], [email protected]. Gen Mugla Stk Koman
University, Faculty of Engineering, Dept. of Mining Engineering,
Ktekli, Mugla 48000, Turkey
a r t i c l e i n f oArticle history:Received 19 August
2014Accepted 9 January 2015
Keywords:GrindingClassificationModellingSimulationOptimizationa
b s t r a c t
Production capacity of a fully air-swept industrial scale
two-compartment KHD Humboldt Wedag
cement ball mill was optimized with the aid of simulation. It
was proposed to operate the mill as a singlecompartment by
eliminating the pre-drying compartment. In this respect, grinding
performance of theair-swept ball mill was evaluated and modelled as
a perfectly mixed single tank using the perfect mixingball mill
modelling approach (Whiten, 1974). Static separator was modelled by
efficiency curve model(Whiten, 1966). The empirical breakage
function required in the estimation of average specific
breakagerates was measured by drop-weight technique. The full scale
model parameters were used to simulatethe raw meal mill grinding
circuit with the aid of JKSimMet Steady State Mineral Processing
Simulator.Simulation results indicated 23% production capacity
increase in cement throughput in case the pre-drying compartment
was used in grinding.
2015 Elsevier Ltd. All rights reserved.1. Introduction
Air-swept raw meal ball mills introduced by the cement
millmanufacturers F.L.Smidth
(Smidth, 2002), Polysius
(Polysius,
2002) and KHD Humboldt Wedag are the most commonly usedones. KHD
Humboldt Wedag manufactured fully air-swept rawmeal mills which
have two compartments used for drying andgrinding processes. In
these mills drying and grinding are per-formed in a single mill as
similar to the Polysius
fully air-swept
mill (Polysius, 2002). First compartment is used as a
pre-dryingcompartment where it is equipped with lifters and
operated with-out grinding media in order to increase the drying
efficiency. Insuch systems, kiln discharge gases are used as a
drying air. Dryingcompartment consumes more energy as compared to
the othersystems due to the high level of moisture in the feed. In
air-sweptmills circulating load is carried pneumatically. Thus, the
energyconsumption for a fully air-swept grinding circuit is higher
byapproximately 1012% as compared to the grinding circuit
withbucket elevator (Duda, 1985). Modelling of fully air-swept
ballmills used in the cement industry were studied with
differentapproaches in the literature (Austin et al., 1975,
1984;Viswanathan, 1986; Viswanathan and Narang, 1988;Viswanathan
and Reddy, 1992; Zhang et al., 1988; Zhang, 1992;Ergin, 1993;
Apling and Ergin, 1994; Benzer, 2004). Grinding modelparameters are
similar except of the material transport function inthe related
models. The population balance model requires resi-dence time which
is difficult to determine for the full-scale mill.Value of
residence time distribution is determined experimentally.Perfect
mixing model (Whiten, 1974) simplifies the discharge(transport)
function by assuming a particle size dependent dis-charge rate
function. The discharge of any particle fraction fromthe mill can
be calculated on the basis of the mass of size fractionin the mill
hold-up and mass flow rate of that particle fraction outof the mill
as product. Perfect mixing model does not constitutemany grinding
parameters which needs to be scaled up. The modelcould be used
directly to predict the performance of full-scalemills. The
relation between particle size and discharge rate depen-dent
breakage rate parameter which was defined as a ratio ofbreakage
rate to discharge rate function was established to mea-sure the
ball milling performance based on perfect mixing model-ling
approach by Zhang (1992), Benzer (2000) and Hashim (2003).
Breakage function and breakage rate parameters are deter-mined
by laboratory experiments in Austins approach (Austinet al., 1984)
and the resulting mathematical equations relatingthe breakage
function and breakage rate to particle size constitutemany
parameters. Thus, more than one parameter set could beproduced in
the solution of these equations each of which definedifferent
breakage rate-particle size relationships. For this reason,it is
difficult to relate the effects of operating variables of ball
millson specific breakage rates. Design and operational
parameterswere studied on laboratory scale mills which need to
be
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Nomenclature
i particle size fraction ij particle size fraction jfi mass
flowrate of mill feed (ton/hour)pi mass flowrate of mill discharge
(ton/hour)ri specific breakage rate of size fraction i (h1)di
specific discharge rate of size fraction i (h1)di normalized
discharge rate of size fraction ia single column step triangular
breakage function matrixsi mass of size fraction i (ton)Q
volumetric feed rate (m3/h)D mill diameter (m)L mill length (m)
r/d ratio of breakage rate to normalized discharge rateEoa
fraction of feed reporting to overflowC fraction undergoing real
classification (1-bypass frac-
tion)B reduced efficiency curve fish hook parameterd50c size of
a particle in feed which has equal probability of
going to underflow or overflow (cut size)b model parameter to
preserve the definition of d50cd particle sizex ratio of di to
d50ca reduced efficiency curve sharpness parameter
42 . Gen /Minerals Engineering 74 (2015) 4150scaled-up. There
had been a few attempts to relate their modelwith air flow through
the mill, feed rate, feed size distribution,material filling and
ball filling (Viswanathan, 1986; Zhang, 1992).Air swept ball mill
model proposed by Austin et al. (1975) was val-idated by Apling and
Ergin (1994) using the industrial scale datafrom a cement grinding
circuit.
In this study, production capacity of a fully air-swept dry
grind-ing raw meal ball mill circuit was evaluated by modelling the
millusing the perfect mixing modelling approach (Whiten, 1972).
Sta-tic separator in the circuit was modelled by efficiency curve
model(Whiten, 1966). JKSimMet Steady State Mineral Processing
Simula-tor was used in the simulation stage. Simulation results
indicated23% capacity increase in cement throughput at the steady
statecondition. However, the static separator is expected to
operatewith the maximum tonnage that can be handled.
2. Methods
2.1. Sampling survey
The simplified process flowsheet of the sampled circuit with
thesampling points is given in Fig. 1. Air-swept ball mill is
operating inclosed circuit with a static separator. The static
fines are collectedin product cyclones where the separation of
particles from the airis performed. Product of electrofilter is
combined with the cycloneproducts to form final cement. Design
specifications of the fullyair-swept ball mill and static separator
are given in Table 1. Designball size distribution applied in the
ball mill is given in Table 2.
Steady state condition of the circuit was verified by
examiningthe variations in the values of operational variables of
the ball milland the static separator in the process control room
system. Sam-pling was started when the steady state condition was
achieved.Representative amount of samples were collected from the
shownsampling points in Fig. 1. Samples from the raw meal feed
werecollected for the determination of moisture content of the mill
feedmaterials. Values of the operational variables were recorded
inevery 5 min from the process control system to be used in the
cir-cuit performance assessment during sampling Control
roomrecordings and related standard deviation values at the
steadystate condition are tabulated in Table 3.
2.2. Experimental
Samples were prepared by using a riffler for dry sieving fromthe
top size down to 150 lm. Sub-sieve sample (150 lm) wassized in wet
mode in a SYMPATHEC laser diffractometer. Drysized material (+150
lm) and wet sized sub-sieve sample(150 lm) were combined to define
the full size distribution fromthe top size down to 1.8 lm. Raw
meal materials were dried atapproximately 100 C before sizing in
order to carry out an efficientscreening operation. Calculated
moisture contents and dry flow-rates of mill feed materials are
given in Table 4.
3. Results and discussions
3.1. Mass balancing
Measured particle size distributions and operational
tonnageflowrates were used to perform mass balance calculations
aroundthe circuit with the aid of mass balance module of the
JKSimMetsimulator to calculate the best fit estimates of the size
distributionsand tonnage flowrates. Mass balanced flowrates and
calculatedfineness as 0.045 mm passing % are given in Table 5.
Circulatingload ratio was defined as the ratio of static separator
reject tonnageto static separator fine tonnage and calculated as
75.34%. Theresults of mass balance calculations were checked out by
plottingthe experimental and calculated particle size
distributions(Fig. 2). Experimental versus mass balanced particle
size distribu-tions were found to be fitted satisfactorily which
indicated that,sampling was successful and the data could be used
for modellingpurpose. Experimental size distributions of final
cement cyclonecollectors were presented in Fig. 3. Particle size
distributions indi-cated no segregation in the cyclones verifying
the sufficient level ofair flow and balanced air distribution
within the cyclones.
3.2. Mill inside sampling and granulometry
The circuit was crash-stopped to collect samples from inside
ofthe mill after completing sampling of the circuit streams. A view
ofmill inside at the crash-stop condition is given in Fig. 4.
Averagematerial height above the ball surface level (18 cm) and
free heightof the mill (2.27 m) were measured to be used in mill
powder load(hold-up) calculation ahead of collecting the samples
along thelong axis of the mill at the crash-stop condition. Mill
filling was cal-culated to be 32% using the mentioned geometrical
measurements.Photograph of the lifter bar design in the drying
compartment ispresented in Fig. 5. Considerable abrasion and damage
on lifterswere recognized. Whole length of the grinding compartment
waslined with classifying liners. Classifying liner configuration
is pre-sented in Fig. 4.
Sample collection dips were formed by digging out the millcharge
(mill powder + balls) approximately 40 cm below thecharge level.
Samples were collected along the long axis of the milltowards the
end of the discharge grate in order to demonstrate thesize
reduction performance using the inside mill size
distributions(granulometry). Samples were collected by one meter up
to thesixth meter of the grinding length whereas by half meter at
the restof the mill length. Mill inlet and outlet temperatures were
recorded
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Fig. 1. Simplified flowsheet of a raw meal
grinding-classification circuit. Streams/sampled: (1) iron ore
bunker belt; (2) clay bunker belt; (3) limestone bunker belt; (4)
totalfresh feed; (7) static separator reject (coarse); (9a) product
cyclone-1 underflow; (9b) product cyclone-2 underflow; (10) product
cyclone combined; (12) electrofilter return;(13) dust from cooler.
Streams/not sampled: (5) mill feed; (6) mill discharge; (8) static
separator fine; (11) cyclone dust.
Table 1Design specifications for air-swept raw meal ball mill
and static separator.
Raw meal ball millDiameter (m) 3.8Drying compartment length (m)
2.935Grinding compartment length (m) 6.935Mill power (kW) 1600Mill
rotational speed (rev/min) 15Critical speed % 69Ball filling %
27Discharge diaphragm middle grate aperture size (cm) 8 8Static
separatorSeparator diameter (m) 5.2
Table 2Design ball size distribution of the grinding
compartment.
Ball size (mm) Weight (kg) Weight % Cumulative weight %
80 2853 4 100.0070 17,552 22 96.4560 18,594 23 74.5950 17,040 21
51.4440 17,442 22 30.2230 6827 9 8.50
Total 80,308 100
Table 3Control room recordings during the sampling survey.
Operational variables Value Standard deviation
Limestone (t/h) 65 1.38Clay (t/h) 26 1.37Iron ore (t/h) 1.72
0.13Total fresh feed wet flowrate (t/h) 92.72 1.55Static separator
reject (t/h) 64 14.40Ball mill filling % 83 1.44Ball mill inlet
temperature (C) 325 2.96Ball mill discharge temperature (C) 93
3.31Ball mill inlet pressure (mmSS)a 25 4.04Ball mill discharge
pressure (mmSS) 360 22.46Ball mill ventilation pressure (mmSS) 767
27.79Static separator pressure difference (mmSS) 335 19.49Ball mill
(Amper) 120 0.00Ball mill elevator (Amper) 24 0.00Ball mill motor
(kW) 1240 7.90Mill specific energy consumption (kW h/t) 14.57
0.26Kiln capacity (t/h) 71
a Millimeters of water column.
. Gen /Minerals Engineering 74 (2015) 4150 43as 325 C and 93 C
respectively at the crash-stop condition. Themill was cooled down
for 67 h before inside mill sampling byopening the mill inlet. Air
flow through the was not allowed as fineparticles will discharge
from the mill.
It should be mentioned that, it is crucial to collect
representa-tive samples in any sampling operation. The technique
used in thisstudy provided collecting representative inside mill
samples at theregarding sample collection dip. Collection of
material and ballsamples just above the charge surface (which is
common in suchsampling procedures) will not give statistically
representativeresults for the evaluation of ball charge load and
distribution whichaffects the size reduction performance of the
mill. Sample amountcollected at each sample collection dip were
tabulated in Table 6.Mill length given in Table 6 refers to the
measured length at thesampling condition. Particle size
distribution at the mill inlet wasfound to be coarser than that of
the following sampling dipsexcluded of the particle size
distribution of the sample collectedfrom the first meter of the
mill length. This condition could berelated to the difficulty of
digging of the sample collection dip atthe first meter due to the
existing coarse balls such as 90 mmand 80 mmwhich could have
affected the quality of sampling. Par-ticle size distribution of
the mill inlet was found to be finer thanthe first meter sample as
shown in Fig. 6. This condition could bedue to the accumulation of
static separator reject material at themill inlet which affected
the particle size distribution at thecrash-stop condition. Particle
size distributions of the inside millsamples and the mass balanced
mill feed and discharge size distri-butions are presented on loglog
scale in Fig. 6. Particle size distri-bution of the mill hold-up
(mill load) was assumed to be calculatedusing the average size
distribution of the inside mill samples whichis denoted by the
average mill content size distribution in Fig. 6.
The mill modelling approach was to use average mill
hold-upparticle size distribution when calibrating the model
parametersof perfect mixing model proposed by Whiten (1974). Inside
millparticle size distributions (Fig. 6) indicated a consistent
size reduc-tion towards the mill discharge end such that, particle
size distri-bution of the samples became finer towards the
discharge grate.
Mill inside fineness curve established using the 0.045
mmcumulative passing % size is given in Fig. 7. Amount of fine
materialproduction in the first meter decreased. However, fine
materialproduction increased in the following two meters. No
more
-
Table 4Moisture contents of mill feed and calculated dry
flowrates.
Raw meals Moisture % Measured wetflowrate (t/h)
Dry flowrate(t/h)
Limestone 2.08 65 63.65Clay 22.64 26 20.11Iron ore 4.12 1.72
1.65Total raw meal 6.64 92.72 85.41
44 . Gen /Minerals Engineering 74 (2015) 4150considerable size
reduction was achieved at the rest of the milllength which could be
due to a series of operational factors asgiven below:
probable increase in amount of fine material due to the low
airflow rate, such that, less fines extracted from the mill,
increase in mill inside temperature which could lead to
cush-ioning effect as explained by Austin et al. (1984). Coating of
ballsurface with material is expected to have an adverse effect
ongrinding performance of the grinding media thus will result
inlower specific breakage rate,
probable agglomeration of fine particles inside the mill
whichcould have decreased the transportation (discharge) rate
ofparticles through the mill. This claim could be supported byTable
5Mass balanced flowrates and fineness as 0.045 mm passing %.
Stream No Stream identification Sample am
1 Iron ore bunker belt 64.862 Clay bunker belt 47.363 Limestone
bunker belt 55.774 Total fresh feed 5 Mill feed 6 Mill discharge
(static separator feed) 7 Static separator reject (coarse) 5.368
Static separator fine 9a Product cyclone-1 underflow 2.569b Product
cyclone-2 underflow 2.6010 Product cyclone combined 2.6511 Cyclone
dust 12 Electrofilter return 3.2413 Dust from cooler 4.5514 Final
cement 2.42
Fig. 2. Agreement between experimental and mass bthe work of
(Kolacz, 1999). Effect of air flowrate on the dis-charge rate of
material in an air swept ball mill was studiedby Kolacz (1999). It
was concluded that, transportation of mate-rial through the mill by
air sweeping becomes more difficult ifthe mill content is finer
which is due to the agglomeration ofvery fine particles falling
back into the mill bed,
material coating observed at the discharge grate couldhave
affected the fine material accumulation amount in themill and
decreased the grinding performance of the grindingmedia.
Particle size distribution of the mill discharge estimated
bymass balance calculations was found to be finer than that of
thesample collected at the mill discharge end which correspondedto
the sample at the seven point fourth meter of the grindinglength.
This condition is expected under sufficient screening effectof the
discharge diaphragm (Fig. 6). Screening effect wasexplained as the
rejection of coarse particles to the last meter ofthe compartment
length after screening at the diaphragm and dis-cussed in the
literature (Benzer, 2000; Gen, 2008; Gen andBenzer, 2009) for
intermediate and discharge diaphragms of over-flow (gravity
discharge) type multi-compartment cement grindingball mills.ount
(kg) Calculated flowrate (t/h) 0.045 mm passing %
1.65 3.5720.07 2.7963.41 1.5885.13 1.91
149.26 8.00149.26 52.3264.14 16.2985.13 79.58 80.00 78.80
82.73 78.102.40 100.004.97 100.002.57 100.00
87.70 80.71
alanced size distributions of the circuit streams.
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Fig. 3. Experimental size distributions of final cement cyclone
collector productsand dust from cooler upstream.
Classifying liners
Grinding compartment
Fig. 4. Photographs of mill inside and classifying liners in the
grindingcompartment.
Fig. 5. A view of lifter bar liners in the drying
compartment.
Table 6Mill inside sample amounts.
Length (m) Sample (kg)
Mill inlet 10.421 6.602 7.963 5.794 3.915 3.436 3.836.7 3.727.4
6.30
Fig. 6. Axial mill inside particle size distributions towards
the mill discharge end.
0
20
40
60
80
100
0 1 2 3 4 5 6 7 8
0.04
5mm
cum
ulat
ive
pass
ing
%
Grinding compartment length (m)
Fig. 7. Fineness variation along the grinding compartment
length.
. Gen /Minerals Engineering 74 (2015) 4150 45Mill powder was
expected to discharge through the middlegrate of the discharge
diaphragm as the grate opening was wideenough (8 8 cm) to allow
transportation of finely ground rawmeal powder by only air sweeping
in the studied mill. Mill insidesize distributions demonstrated
consistent size reduction. Particlesize distributions of the sample
at the seventh meter of the grind-ing compartment length was found
to be considerably coarser thanthat of the mill discharge (Fig. 6).
Both size distributions should beclosely similar under the
effective air flowrate operationalconditions.
Another observation was the existence of coarse particle
accu-mulation in the mill. Certain amount of coarse particle
accumula-tion within the size range of 25 + 19 mm, 19 + 13.2
mm,13.2 + 9.5 mm was observed at the fourth meter of the
milllength. Such operational inefficiencies were attributed to the
hard-ness of these particles, material coating at the discharge
diaphragmand low air flowrate condition as the operational air
flowrate at themill outlet was recorded to be 25.9 m/s. Typical
range for the airflowrate at the mill outlet is 24.435.1 m/s for
air swept ball mills(Duda, 1985). Recorded low air flowrate at the
mill outlet couldhave decreased the grinding capacity due to the
transportation offine material through the mill. On the otherhand,
air flowratethrough the mill was calculated as 5.02 m/s using the
measuredmill filling (32%) at the sampling condition. This figure
was foundto be higher than the typical air flowrate range suggested
for air-swept mills which is 34 m/s inside the mill as given by
Duda(1985).
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Fig. 8. Weighted measured ball size along the mill length.
46 . Gen /Minerals Engineering 74 (2015) 41503.3. Ball size
classification
In order to assess the classifying performance of the mill
liners,ball samples were collected during the inside mill powder
sam-pling by screening out the balls over a screen with 25 25
mmaperture size in order to separate the raw meal powder and
thegrinding media at the sampling dips. Ball samples were
collectedevery meter, up to the fourth meter of the mill. The
sampling pro-cedure was to collect some amount of mixture of raw
meal powderand balls and then screening. Balls were retained on the
screen andcollected in a sampling bag to be weighted and sized to
determinethe ball size distribution along the mill length. On the
otherhand,raw meal powder which was the screen undersize was
collectedin another sampling bag. Collected ball sample mass along
the milllength was tabulated in Table 7. It should be mentioned
that, thepresented values are not representative of the whole ball
load atthe sampling dip. However, the results clearly indicated the
ballsize classification along the long axis of the mill. Ball size
distribu-tion was found to get finer towards the mill discharge
end, exceptfor the sample collected at the second meter of the
compartmentwhich indicated true ball size classification. The
concept of trueball size classification was discussed for cement
grinding multi-compartment ball mills by Gen et al. (2008). This
condition showsthe affect of classifying liners. Weighted average
ball size was cal-culated using the collected ball samples at each
sampling locationwhich demonstrated the true ball size
classification along the con-sidered mill length and given in Fig.
8.Fig. 9. Normalized single particle breakage functions (replotted
after Gen et al.,2008).3.4. Material characterization
Drop weight technique was used to characterize breakage
dis-tribution function of the mill feed material so as to reflect
breakagecharacteristics to the model parameters of the mill.
Breakage testwas conducted on single particles in the size fraction
of9.5 + 8 mm at an energy level of 1 kW h/ton. A modified
manualversion of a JK Tech drop weight test device (Napier Munn et
al.;Brown and Grimes, 2005) was used in the characterization
tests.Specifications of the drop weight tester which was used was
givenby Gen (2002) and Gen et al. (2004). It was proposed to use
acombined breakage function that was determined by combiningthe
single particle impact breakage functions of individual compo-nents
of the mill feed using the weight percentages of the mill
feedcomponents (Gen and Benzer, 2008) in modelling of
cementgrinding mills. The combined breakage function determined
onthe basis of the mentioned assumption and is shown in Fig. 9
astotal feed combined. Mill feed is composed of 60% clinker,
24%trass, 11% limestone and 5% gypsum by weight and used to
deter-mine the combined breakage function. Combined breakage
distri-bution was found to be shifted towards the breakage function
ofthe dominant component of the mill feed which was clinker.
Investigated raw meal mill feed constitutes 74% limestone,
24%clay and 2% iron ore by weight. According to the recorded
findings(Gen and Benzer, 2008), the approach was to use single
particlebreakage distribution function of limestone which is the
majorcomponent of the raw meal mill feed to estimate the
averagebreakage function and presented in Fig. 9.Table 7Ball sample
amounts along the mill length.
Grinding compartment length (m) Total sample weight (kg)
1 26.272 33.143 28.804 15.43Standard Bond work index value of
the mill feed material wasalso experimentally determined as 11.03
kW h/ton according toTS 7700 standard (TS 7700, 1989) using a 90 lm
test sieve.3.5. Ball mill model
Air-swept ball mill was modelled using the perfect mixing
mod-elling approach (Whiten, 1974) which defines the
comminutionprocess in terms of three parameters; breakage rate,
discharge rateand breakage function Eq. (1). On the other hand,
discharge rate(di) of particles were defined to be a function of
mill product (pi)and mill hold-up (si) as given by Eq. (2) (Napier
Munn et al.)
f i piri=di Xij1
aijpiri=di pi 0 1di pi=si 2
In these equations, fi and pi are the mass flowrates (t/h) of
sizefraction i in mill feed and product respectively, aij is the
breakagefunction (in the form of single column step triangular
matrix), riis the specific breakage rate of size fraction i (tonnes
broken perhour per tonne in the mill which is h1), di is the
specific dischargerate of size fraction (i) (tonnes discharged per
hour per tonne in themill which is h1), and si is the mass of size
fraction (i) inside the
-
Fig. 11. Specific breakage rates (ri) in the air-swept raw meal
ball mill. Replottedafter (Gen et al., 2008).
. Gen /Minerals Engineering 74 (2015) 4150 47mill as tons.
Perfect mixing model was used by Benzer (2004) inmodelling of an
air-swept raw meal grinding ball mill by consider-ing the single
compartment mill as three perfectly mixed tankswhereas air-sweeping
through the mill was modelled by a classi-fier at the mill
discharge. In the model, tank-1 corresponded tothe mill length
where lifting liners were applied whereas tank-2and tank-3 lengths
corresponded to the mill length where classify-ing liners were
applied. In the related study, mill performance wasevaluated
through particle size versus r/d combined breakage rateparameter
which normalized the discharge rate effect.
In order to correct the variations in residence time, di is
scaledin terms of the mill volume and volumetric feed rate (Q) to
theterm di using Eq. (3), where D and L are the diameter and
thelength of the mill respectively. Then, r/d model parameter is
calcu-lated. Normalized discharge rate (di ) is a function of
particle sizeEq. (3) (Napier Munn et al.)
di di
4Q=D2L3
Normalized discharge rate function variation established
usingthe estimated mill hold-up (si) was given for the investigated
air-swept raw meal mill in Fig. 10. Experimentally determined
values(measured) are denoted by the scatter plot and compared with
thetypical trend observed in semi-autogenous grinding mills
(SAG)(Napier Munn et al.; Leung, 1987) which is denoted by the
dottedlines in Fig. 10. This function was calculated by eliminating
theclassification effect of the discharge grate. The discharge rate
func-tion (di) was considered to be the product of two
mechanisms;transport and classification by the discharge grate as
explainedfor SAG mills by Leung (1987).
There is a critical particle size in the mill which is denoted
by xcand can be determined using normalized discharge rate (di )
func-tion as shown in Fig. 10. Particles finer than this size (xc)
behavelike a fluid medium in the mill and discharge at a constant
ratethrough the mill. The rate of discharge for particles coarser
thanthis size was found to decrease systematically in wet
grindingconditions (Napier Munn et al.; Morrell and Man, 1997).
Particlescoarser than the grate size (xg) remain in the mill for
further sizereduction where the discharge rate equals to zero. In
the investi-gated air-swept mill, the fluid medium corresponded to
air andthe critical particle size (xc) was expected to be highly
dependedon the airflow rate through the mill (Fig. 10).
In this study, the modelling approach was to consider the millas
a perfectly mixed single tank as the whole length of the millwas
lined with classifying liners. Specific discharge rate
functions(di) were calculated from Eq. (2) using the estimated
millhold-up. Specific breakage rate (ri) function was estimated
usingthe calculated discharge rate functions from Eq. (1). Mill
hold-up(tons in each size fraction) in grinding compartment wasFig.
10. Measured normalized discharge rate function (di ) in a full
scale fully air-swept raw meal mill (xc = 50 lm). Replotted after
(Gen et al., 2008).calculated using the size distribution of
average mill content andmeasured mill filling data at the
crash-stop condition. The specificbreakage rate calculation
procedure was formulated on Excel
spreadsheets.Specific breakage rate function is presented in
Fig. 11. Agree-
ment between experimental and back-calculated mill product
sizedistributions are given in Fig. 12. The experimental data was
foundto be fitted to the model satisfactorily. Specific breakage
rates wereassumed to not change along the mill in the modelling
approach.
The r/d combined breakage rate parameters of the perfect mix-ing
model were calculated as ln(r/d) in the model fit module of
theJKSimMet simulator considering the mill as a perfectly mixed
sin-gle tank. The fitted values were of the best values that
defined themill discharge size distribution. The r/d breakage rate
parametersfitted to the perfect mixing model were tabulated in
Table 8 andused in the simulation step which characterized the
specific break-age rates in the mill. It should be mentioned that,
spline functionknot values, which could be defined usually by
maximum of fourdata points, were selected from the whole set of
specific breakagerate values calculated for each particle size
given in Fig. 11.
3.6. Static separator model
Grinding efficiency in ball mills depends on the classifying
per-formance of air separators as explained in the study of
(Klumparand Slavsky, 1989) and (Kolacz, 1999). Their findings
indicatedthat, energy consumption in ball milling can be reduced if
the clas-sification efficiency is sufficiently high. The
classification behaviorof air separators are described using the
efficiency curve concept inthe literature (Austin et al., 1975;
Zhang et al., 1988; Zhang, 1992;Benzer, 2000; Luckie and Austin,
1975; Schneider et al., 1983;Kuhlmann, 1984; Dunn, 1985; Plank,
1985; Kellett and Rock,1986; Benzer et al., 2001; Hashim, 2003;
Gnl, 2006; Altun,2007). The mathematical equation of the efficiency
curve modelis given in Eq. (4) (Napier Munn et al.).
Eoa C1 bbxexpa 1expabx expa 2
4
where,Eoa: fraction of feed reporting to overflow.C: fraction
undergoing real classification (1-bypass fraction).a: reduced
efficiency curve sharpness parameter.b: reduced efficiency curve
fish hook parameter.b: parameter to preserve the definition d50c,
i.e. d = d50c whenE = (1/2)C where E denotes the fraction of
feed.x: ratio of particle size d to corrected size d50c.
-
Fig. 12. Agreement between experimental and calculated (model
fitted) millproduct size distributions.
Table 8ln(r/d) combined model parameters of the ball mill.
Particle size (mm) ln(r/d)
1.18 4.000.425 1.780.15 0.830.045 0.23
Fig. 13. Efficiency curve (tromp) for static separator (d50 =
0.099 mm; by-pass = 11.85%; fish-hook = 2.39%).
Table 9Model fitted efficiency curve parameters used in the
simulation of circuit.
Model parameter Value
d50c 0.1069C (1-by-pass) 85.15a 3.74b 0.3633b 1.16
48 . Gen /Minerals Engineering 74 (2015) 4150d50c: size of a
particle in feed which has equal probability ofgoing to underflow
or overflow (cut size)
The fraction of feed reporting to underflow (EUA) was defined
as1Eoa (Napier Munn et al.). The separator performance can
bemodelled in terms of d50c, C, a and b. It was stated that, b
controlsthe initial rise in the efficiency curve at fine sizes,
while a deter-mines the slope at larger values of d which is around
d50c. b is cal-culated iteratively during the fitting of Eq. (4)
Whiten, 1966. Effectsof operational parameters on efficiency curve
model parameterswere given for air separators used in the cement
industry byGnl (2006), Altun (2007) and Benzer et al. (2001). The
efficiencycurve (tromp curve) for the static separator established
on thebasis of the mass balanced size distributions is presented
inFig. 13. The characteristic efficiency curve parameters which
ared50, by-pass and fish-hook are also given in Fig. 13.
Fish-hook parameter characterizes the difference between
themaximum percentage of fine material amount that appears incoarse
stream (underflow of the separator) and the by-pass per-centage.
Model fitted efficiency curve parameters used in the sim-ulation of
the circuit are given in Table 9. The separatorperformance is not
at maximum as 11.85% of feed reports to sepa-rator coarse product.
However, this value is reasonable and classi-fication performance
of the static separator is sufficiently high.4. Simulation
Simulation model of the circuit was designed in simulationmodule
of the JKSimMet simulator by defining the perfect mixingmodel
parameters of the air-swept ball mill and efficiency curvemodel
parameters of the static separator given in Tables 8 and
9respectively. The ball mill was simulated as a single
compartmentmill by eliminating the mill length of 2.935 m which was
used indrying stage, such that the full length (L = 9.87 m) of the
mill wasused in grinding. Thus, drying of the raw meal outside the
millby an appropriate dryer was assumed. Static separator
perfor-mance was sufficiently high and assumed to not change at the
sim-ulated condition. Cyclones are used to separate static fines
fromgas and store static separator fine product (cement). There is
notany classification. Thus, cyclones were excluded in the
simulationmodel whereas electrofilter return was identified as a
stream.The circuit response to the proposed operational condition
interms of tonnage flow rates and fineness (0.045 mm passing
per-centage) is presented in Table 10. Mass balanced particle size
dis-tributions in comparison to those obtained after
simulation(simulated) at 23% capacity increase case in the cement
through-put are given in Fig. 14. Simulation parameters were kept
constantduring the optimization study.
As a consequence of the proposed modification in the mill andthe
expected capacity increase, a series of operational modifica-tions
will be required such that, regulation of static separator
oper-ational parameters. For instance, particle size distribution
of thestatic separator feed (mill discharge) is estimated to become
fineras indicated by the simulated particle size distributions
which willrequire the optimization of the static separator.
Parameters thatcan be adjusted in the classification process to
attain the targetfineness were recorded in the literature by
Kohlhaas (1983) as:
varying of the air flow rate; increase in air flow rate
willdecrease the cut size (d50),
adjusting of the deflector over the bottom of the inlet
ductthrough which the powder carrying air enters the
separator;position of the deflector can be adjusted which will
effect thecut size (d50),
adjusting of the top outlet duct; where the cut size can be
var-ied by vertical adjustment of the air outlet duct at the top of
theseparator. For a constant air flow rate, increase in the length
ofthe duct will lead to decrease the cut-size (finer product) or
viceversa.
Air flow rate in the duct of the mill should be increased
beforethe adjustment of the static separator parameters (i.e.,
angle set-ting adjustable vanes, deflector) by controlling the
by-passamount. The cyclone performance will change depending on
thecyclone geometry such that, as the cyclone diameter decreasesand
the length of the conical section increases, centrifugal force
-
Table 10Comparison of crash-stop and simulated cases.
Crash-stop condition (Calc) Simulated condition (Sim)
Stream flows t/h 0.045 mm passing % t/h 0.045 mm passing %
Total fresh feed 85.13 1.91 105.00 1.91Mill discharge 149.26
52.32 165.27 58.21Static separator reject 64.14 16.29 60.27
21.43Electrofilter return 4.97 100.00 4.97 100.00Final cement 90.10
80.71 109.97 82.41
Fig. 14. Agreement between mass balanced and simulated particle
size distribu-tions of streams.
. Gen /Minerals Engineering 74 (2015) 4150 49effect on the
particle flow pattern will increase and will lead toeffective
separation of powder carrying air as explained byKohlhaas (1983).
Separation efficiency of the cyclones willdecrease at very low or
high grain concentrations. Based on thesimulation results, cyclone
and electrofilter capacities are expectedto handle 23% capacity
increase in addition to the increase in thedust concentration in
the product cyclone overflow. However, thecyclone will be operated
at full capacity.
5. Conclusions
Conventional two-compartment fully air-swept KHD HumboldtWedag
raw meal ball mill operating in closed circuit with a
staticseparator was modelled and simulated to evaluate the
probablecapacity increase in the circuit in case the pre-drying
compartmentwas used in the grinding stage. The mill was modelled as
a per-fectly mixed single tank as the material discharge was
providedonly by air-sweeping. Performance of the separator was
assumedto not change in the simulation stage.
Simulation results indicated that, 23% capacity increase in
thecement throughput could be achieved at the steady state
conditionby operating the pre-drying compartment at the same ball
chargelevel and ball size distribution, without any change in the
productcyclone capacity, and by assuming that the process of
pre-drying isperformed in the ball mill upstream. However, air
flowrate throughthe mill should be critically regulated as the
velocity of the air con-trols the particle size distribution of the
mill product in addition tothe operational parameters of the static
separator at the new oper-ational condition for a stable and
optimum production rate. Grind-ing heat generated could increase
which may lead toagglomeration of particles unless reduced. The new
design mayrequire larger dust collectors, larger ventilation fans
which willbring additional cost.Acknowledgements
Authors appreciation goes to SET Italcementi Group BalkesirPlant
for providing the access to the plant and their valuable sup-port
during the sampling survey. Prof. A. Hakan Benzer for his valu-able
discussions and contributions, Assistant Prof. Okay Altun
andAssistant Prof. Hakan Dndar from Hacettepe University are
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Optimization of a fully air-swept dry grinding cement raw meal
ball mill closed circuit capacity with the aid of simulation1
Introduction2 Methods2.1 Sampling survey2.2 Experimental
3 Results and discussions3.1 Mass balancing3.2 Mill inside
sampling and granulometry3.3 Ball size classification3.4 Material
characterization3.5 Ball mill model3.6 Static separator model
4 Simulation5 ConclusionsAcknowledgementsReferences