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NEW DEVELOPMENTS IN CONE CRUSHERPERFORMANCE OPTIMIZATION

Jens Lichter, King Lim, Alex Potapov and Dean Kaja

Metso Minerals Inc., USA

ABSTRACT

This paper shall review Metso Minerals current 3D Discrete Element Method (DEM)

modeling techniques, developed to allow a detailed study of the interactions of crushing

design variables with actual rock mechanics.

A standard DEM approach cannot be applied to systems where size reduction is

an important element in the flow of particles, such as industrial crushers. In these

systems, it is necessary to physically decrease the particle sizes in a realistic way,

as they are transported through the device. Metso Minerals has therefore developed

a breakage model that incorporates elements of Population Balance Modeling (PBM)

techniques to describe breakage as a function of the loads on the individual rocks. The

combination of this breakage model with DEM has therefore allowed the development of

a multi physics based comminution model that can be applied to crusher development.

This model is sensitive to all aspects of crusher design including crusher machine

parameters and the ore characteristics.

This physics based virtual comminution model will enable engineers to optimize the

design development of future crushers by allowing a wider range of values for the crusher

variables to be investigated in a rapid, yet more detailed manner, without the need for the

traditional expensive and lengthy prototype testing.

Key Words: Comminution, Crushing, Discrete Element Modeling, Process Optimization.

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CHAPTER 02

Crusher Design Evolution

Compression cone crusher designs today have evolved from the simple cone crusher

first developed in the mid-1920s by Edgar B. Symons, to the modern high perform-

ance crushers. Early crushers used springs for tramp iron protection and were manually

adjusted. The newer crushers utilize a safer more reliable hydraulic tramp release and

clearing system in addition to hydraulic setting adjustment systems. The hydraulic set-

ting adjustment systems allow remote setting changes and connection to automation

systems that can automatically adjust the crusher setting as needed to optimize the

crusher performance.

Due to the higher power and force levels designed into the newer crushers, they are

able to operate in a mode referred to as interparticle comminution, whereby a bed of feed

particles are interacting not only with the mantle and bowl liner crushing surfaces, but

also with the surrounding particles. This produces a much finer particle distribution for

any given crusher setting. The presence of interparticle crushing places additional de-

mands on the integrity of a physics based virtual comminution model.

With todays technology, crusher design development is still somewhat restrictive. The

ability to investigate crusher variables such as cavity profile, throw, setting, and speed,and its affects on crushing performance cannot be easily achieved without expensive and

lengthy prototype testing programs. Often times, prototype testing still requires several

iterations before realizing positive results. As an example, the time it takes to validate the

result of a cavity profile change requires a minimum of eight to ten months in order to be

able to obtain results from a change (the process being the design change or modification,

then supply and installation, then testing).

There are computer simulation programs based on zone fall-of-material flow calcula-

tions that use crushing breakage models linked to lab material test determined proper-

ties. But the simulations are not able to easily predict performance outside of the field

tested database, and are limited in their ability to handle complex shapes in the crushercavity. These models can be used to predict existing crusher performance quite accurately,

but cannot be used with confidence to design outside of the experience base.

The physics based virtual comminution model described is a breakthrough in com-

minution modeling, whereby crusher variables can be investigated in a rapid, yet more

detailed manner without the need for the traditional expensive and lengthy prototype

testing. The virtual comminution model provides the necessary tool to predict results

and ensure first time success.

The new method treats each significant particle of feed as a separate entity, following

the motion and calculating the forces and energy applied to each particle as it travels

through the crusher. When the required breakage energy threshold has been reached, the

particle breaks and daughter particles are generated.

The virtual crusher comminution model represents a true microscale model, that can pro-

vide details of the crushing environment, and that can be examined in three dimensional

space. This makes it possible to investigate a wider range of crushing conditions in a relative-

ly short period of time and to decide what combination provides the best application results.

The Multi-Physics Comminution Model

The Discrete Element Method (DEM) [1] is a numerical technique in which the equa-

tions of motion of every particle in a system are integrated numerically at every

time step. Thus the motion of every particle in a system is calculated in great detail.Advances in computer hardware, and DEM algorithms, have allowed great strides to be

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73PROCEMIN 2008. Santiago, Chile

New Developments in Cone Crusher Performance Optimization

made in the detail and scope of a problem that can be simulated in a reasonable time

frame. DEM techniques have always been highly suitable for the simulation of the flow

of unbreakable particles in systems where size reduction was not required as part of a

simulation. Early applications of DEM, such as charge trajectory analysis in mills, are now

routine within the mining industry. The application of DEM to crushers is however faced

with an additional challenge. Rock cannot pass through the crusher without being bro-

ken. It is therefore necessary to develop realistic breakage models. These models have

to take as inputs the ore properties, as well as the detailed loading information from the

DEM simulations, and calculate the resultant size reduction. In addition to generating

size reduction data, these models are also required to provide accurate data on the forces

that the rock applies to the crusher components.

Early techniques to develop a breakage model used rocks constructed of sub particles

gluedtogether by contacts that are able to withstand specific tensile stresses before being

broken. This technique is known as Discrete Grain Breakage (DGB) [2, 4, 5]. This technique

can provide good data, but it is restricted in its application due to the very significant

computational expense associated with its use. Problems that can be addressed using thistechnique are therefore largely limited to coarse crushing applications, or two dimensional

crusher studies, where particle counts can be kept to a reasonable level. Two dimensional

DEM (2D-DEM) can provide useful relative performance data but is not suitable for

providing absolute performance data of any kind.

The current development of a virtual comminution model has largely overcome the

limitations imposed by DGB modeling. The approach, currently referred to as Fast Break-

age (FB) modeling [Potapov et al., 2007], combines elements of DEM with elements of

Population Balance Modeling (PBM).

Description of the Fast Breakage Model

An inherent requirement for a realistic and robust breakage model is the use of polyhedral

particles. Gluedspheres, or non spherical particles generated with the use of super quad-

ratics, have the implicit non ideality that they cannot conserve both mass and volume

when broken. The virtual comminution model described here therefore uses randomly

shaped convex polyhedral particles.

The breakage component of the model uses a Population Balance Model (PBM) ap-

proach [2, 3]. The DEM simulation provides the energy applied to every particle in a sys-

tem, either by collision with other particles, or with the crusher bowl liner or mantle. If the

energy of a contact is determined to be sufficient to break a particle, the particle is brokeninstantaneously into the sizes calculated from the solution of a set of ordinary differential

equations, constituting the energy specific PBM. Each resultant fragment now behaves as

a single particle and can be broken again provided that the applied energy is sufficient, and

that the particle size is larger than the minimum particle size defined for the system. (A

minimum particle size has to be defined to control the time step of the DEM calculations,

and the maximum number of particles defined for the system).

The equations describing the primary ore breakage properties are referred to as the

selection function (a n x 1 matrix) and the breakage function (a lower triangular n x n

matrix). The first describes the fracture rate (a probability function) and the second the

size distribution of daughter fragments. These functions are simplified into a functional

form that contains 3 parameters to describe the selection function (Equation 1), andthree parameters to describe the breakage function (Equation 2).

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CHAPTER 02

The form of the selection and breakage functions used for this analysis are given in

Equations (1) and (2) below.

(1)

(2)

Where is the normalized selection function and is primarily an ore characteristic, is

the geometric mean of size fraction i, and the breakage function is the fraction passing

size from the breakage of particles in the size fraction [ , ]. The second order term

in the selection function is typically not required for crusher applications.

The ore breakage characteristics are determined by means of a single particle drop

weight test. The impact energy as well as the resultant fragmentation are measured, andused to develop the parameter estimates for the energy specific PBM model. These break-

age parameters together with the feed ore size distributions, ore specific gravity, and a

shape description constitute the full data set for the feed.

The full crusher geometry including the cavity profile, and the equations of motion

for the mantle, are included into the simulation. The results from the DEM simulation

provide the applied energy data specific to each particle and each contact event. No scal-

ing is therefore required when applying the breakage parameters determined from the

drop weight tests.

Fast Breakage Model Validation and Examples

Model development and validation is an ongoing process. Parameters included in the

validation exercises include crusher throughput, crusher power draw, crushing force and

product size distributions. Two examples of validation exercises are provided below.

The initial validation exercise was based on a pilot laboratory test conducted on a B90

cone crusher. The B90 is a small continuous laboratory scale cone crusher. The feed mate-

rial used in this test was a Sorilla granite, and the tests were conducted at Metso Miner-

als pilot crushing facility in Tampere, Finland. A sample of the feed was provided for the

single particle drop weight tests conducted at Metso Minerals Colorado Springs facility

in the USA. Figure 1 below shows a snapshot of the B90 simulation.

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Figure 1: A sectional view of the B90 DEM simulation

The measured crusher throughput during the validation test was 40.7 kg/min, and the re-

sult from the simulation was 41.5 kg/min. Agreement was therefore good. Figure 2 below

shows the comparison between the measured and simulated product size distributions.

Figure 2: Simulated and experimental product size distributions B90 crusher

The fine fraction of the simulated product size distributions is always truncated due to

the need to restrict minimum particle size and control the total particle count. The parti-

cle count is heavily influenced by the minimum particle size selected. This value therefore

needs to be chosen with care and should consider both computation time required and

the need for resolution at the smaller size fractions.

A second validation point was provided by data available from a pilot crushing test

conducted on limestone at the Metso Minerals Milwaukee test facility in the USA. The

crusher used in this test was an HP100.

Figure 3 below shows a snapshot of the HP100 simulation, with Figure 4 showing the

comparison between the experimental and the simulated product size distributions. Of

interest with this validation exercise is the distinct change in the breakage parameter es-timates as a function of the size fraction in the feed. Two simulations were completed,

one using the breakage parameter estimates from 50mm rock, and the second using the

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parameter estimates from 25mm rock. The measured throughput for the test was 121

tph. The simulated throughput with the two sets of ore properties were 111 tph and 131

tph. Current models allow such differences in the breakage parameters to be included in

a single simulation.

Figure 3: A sectional view of the HP100 DEM simulation

Figure 4: Simulated and experimental product size distributions HP100 crusher

Crusher Selection and Optimization

With current crusher selection procedures, gathering the correct application informa-

tion is the key to the proper selection of cone crushers for a specific application. The in-

formation needed includes the throughput requirements with due consideration for the

expected availability of the overall crushing circuit. Information on expected feed gra-

dation and product size is required along with the characteristics of the material being

crushed. The material characteristics should include the specific gravity or bulk density of

the material, impact work index, moisture content, and abrasion index. Information on

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how the material breaks is helpful as well. Actual data from an existing operation, if avail-

able, is a valuable aid in the selection of the secondary and tertiary crushing equipment.

For Greenfieldprojects, information on the material characteristics should be obtained

from either laboratory tests in small samples, or if larger samples are available, a full scale

pilot crushing test can be performed. Simulations using the virtual comminution model

use data from drop weight tests. These samples are always relatively small. Small sample

sizes of relatively large rocks are prone to sampling errors, and may not be representativeof an ore body. Small sample sizes do however allow multiple samples to be analyzed for

their breakage characteristics. Pilot scale tests can incur similar problems. Experiment

repeatability can also be an issue.

With current crusher selection procedures, application tools including flowsheet simu-

lators and proprietary models are used to assist in the flowsheet development and equip-

ment selection. Crusher selection is typically based on finding a suitably sized crusher to

fit the flowsheet or application. The development of a virtual comminution model has

the possibility to take crusher design and development to a different level. Accurately

predicting results and optimizing the crusher variables before manufacture is now real-

istically feasible. The model will respond to variations in the feed crushability, feed sizedistributions, and feed shape. Material flow calculations using DEM take all aspects of

crusher operation into consideration, including cavity volumes, effect of throw and speed

on particle motion and the resultant rock hold up in the crusher cavity.

Due to the relative ease of obtaining results in a virtual environment, it is possible to

extensively optimize crusher parameters, both in terms of machine design and operation,

specific to an application. It will therefore be possible to evaluate accurately multiples

of parameters such as crusher speed, throw, and cavity design simultaneously, and have

results in weeks. As the feed material in the simulations can be tightly controlled, the

results will show true relative performance, without the difficulties and expense required

to run multiple pilot crushing campaigns.

The models are sensitive to almost all aspects of crusher operation. It is therefore pos-

sible to determine the effect that choke feeding will have on crusher throughput and

product gradation. The virtual comminution model will respond realistically to loads ap-

plied to the bowl liner and mantle by the rocks in the crushing chamber.

Another area of considerable potential for virtual crusher comminution models is the

inclusion of wear modeling. Metso Minerals DEM model for mill applications includes

a highly developed wear model that allows the accurate prediction of wear life as a func-

tion of shell liner design and mill operation. The current crusher comminution model

collects data on the shear work expended on the wear surfaces, but metal removal and

wear life predictions are not available at this time. These model additions will be the

focus of future developments.

CONCLUSIONS

The ongoing emphasis by operations on process optimization and efficiency improve-

ments will take advantage of the latest virtual comminution models. These models will

allow the design of a best fit crusherfor any given flowsheet or application. The use of the

virtual comminution model is not limited to new crusher development alone. Upgrades

of existing crushing facilities will present considerable opportunities. Existing operations

have an advantage in that most of the physical parameters associated with the feed are

known and can be measured. This is often not the case for Greenfield applications. Thiswill allow considerably more fine tuning of existing applications than might be possible

for Greenfield operations.

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Areas of ongoing activity will include developing a more thorough understanding of some

hard to measure variables such as friction coefficients, ore stiffness parameter estimates,

etc. All evidence to date indicates that provided that the estimates used for these param-

eters fall within a reasonable range, the models are largely insensitive to variations and

therefore intrinsically robust. Validation is an ongoing activity, and faces its own spe-

cific challenges. The values provided by any virtual model are fundamentally different

to what is measurable in the field. As an example, product size distributions are typicallymeasured on screens, meaning the measurement will include the influences of shape and

orientation. The results from DEM simulations need to reflect that. Similarly, calculated

power is based on work done on the mantle. The measured value is almost always at the

motor, so drive train and bearing losses all need to be factored in. Motor shaft power is

typically measurable with the correct motor data and equipment, but bearing losses need

to be based on theoretical calculations.

Current absolute results for variables such as throughput, power draw and product size

gradations are within the range of the measured values where experimental procedures

need to be analyzed, so as to determine whether the differences between experimental and

simulated results are due to experimental error or due to the model itself. The current er-ror bar appears to be within 10% for the accuracy of Greenfield predictions, but a greater

volume of data is required before a reasonable confidence interval can be established.

These challenges aside, the relative values for all measurable parameters provided by

the virtual crusher model have been shown to track well with plant data over large opera-

tional ranges. Relative performance predictions are useful in that they are more forgiving

of field measurement inaccuracies. They also provide a good indication that the form of

the comminution model is fundamentally sound and robust. The error associated with

relative performance predictions (determining the effect of a change in crusher operating

parameters) has been shown to be less than 5%.

The true value of a physics based virtual crusher model is that it is a micro model and

sensitive to all aspects of a crusher design and operation. The ore crushability can be

measured relatively easily and parameter estimates for the ore crushability do not require

fittingas is necessary in the current generation of macro PBM models.

The data provided by a virtual model can also be highly localized, e.g. the shear and

normal work on a liner in a specific location. This opens up the possibility of fundamental

wear modeling that will be sensitive to ore and crusher parameters.

Virtual crusher model are computationally intensive, and are unlikely to replace current

crusher selection practice in the near or medium future as a fast analysis method will con-

tinue to be required. These models will however open up numerous opportunities to aid

in fundamental crusher design, and to trouble shoot or optimize existing installations. For

these opportunities, the computational effort is very reasonable and easily justified.

ACKNOWLEDGEMENT

This paper was first presented at the Comminution 08 Symposium in Cornwall, UK. It

has been made available for re-publishing by kind permission of MEI.

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REFERENCES

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Herbst, J. A. & Potapov, A. V. (2004). Making a Discrete Grain Breakage Model Practical for

Comminution Equipment Performance Simulation. Powder Technology, pp. 144-150. [2]

Herbst, J. A., Lo, Y. C. & Flintoff, B. (2003). Size Reduction and Liberation,In: Principles of Mineral

Processing. Ed., M. C. Fuerstenau and K. N. Han, SME, Littleton, CO, pp. 61-118. [3]

Potapov, A. V., Hopkins, M. A. & Campbell, C. S. (1995). A Two-dimensional Dynamic Simulation

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