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EXPLORING THE EFFECT OF ENERGY RECOVERY POTENTIAL

ON COMMINUTION EFFICIENCY: THE GLENCORE RAGLAN MINE CASE

*Peter Radziszewski1 and David Hewitt

2

1 Metso Minerals Canada

795 George V

Lachine, Quebec, CANADA, H8S 2R9

(*Corresponding author: peter.radziszewski@metso.com)

2 Glencore Raglan Mine

120 avenue de l’Aéroport

Rouyn-Noranda, Québec J9Y 0G1 Canada

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EXPLORING THE EFFECT OF ENERGY RECOVERY POTENTIAL

ON COMMINUTION EFFICIENCY: THE GLENCORE RAGLAN MINE CASE

ABSTRACT

Typically, comminution efficiency is cited as being less than 1%. As a result, much effort is going

into increasing that efficiency through the development of new and innovative equipment as well as

through the means to measure and quantify changes in comminution efficiency. However, what about the

other 99%? The focus of this paper is to explore the impact of the other 99% of the energy input into a

given mill on comminution efficiency. Specifically, using, mill and comminution circuit temperature data

from the Raglan Mine SAG and ball mills, this paper will first revisit a thermodynamic model of

comminution processes in order to illustrate the potential and means to energy recovery. This will be

followed by an investigation into the sources of energy loss including conduction/convection and radiation

losses as well as mass transfer. Finally, a discussion will explore the potential impact of energy recovery

on comminution efficiency.

INTRODUCTION

Efficiency, expressed as a percentage, is defined as a dimensionless ratio of the work produced

over the energy consumed or input in order to produce that work. In the case of comminution processes,

the work produced is defined by the new surface energy produced in grinding. Typically, that is cited to be

less than 1% (Lowrinson, 1974) indicating that comminution processes are very inefficient.

As a result, much effort is going into increasing that efficiency through the development of new

and innovative equipment and processes such as blast design (fig. 1a), HPGRs circuits (fig. 1b), flanged

rolls (fig. 1c) and stirred mills (fig. 1d) as well as through the means to measure and quantify changes in

comminution efficiency (Efficiency, 2015; Rowland and McIvor, 2008).

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a) blast design - upto 15% increase in comminution efficiency

(Hart et. al.,2006.)

b) HPGR ball mill circuit - 25% increase in efficiency over a

SABC circuit (Wang et al. 2013)

c) HRC ® - flanged design produces potential 15% increase in

efficiency over non-flanged HPGR (Knorr et al., 2013)

d) VERTIMILL ® - upto 50% increase in efficiency over ball mills

for regrind applications (Merriam et al., 2015)

Figure 1 - Energy Efficiency Processes and Equipment

However, what about the other 99% of the energy input?

Typically, it is accepted that the other 99% of the energy input is transformed into heat

(Radziszewski, 2013) which indicates that comminution processes are actually very efficient in producing

heat. However, the value of heat is negligible unless, as it cannot be currently, it can be converted into a

more value added product or commodity such as electrical energy.

The focus of this paper is to explore the other 99% of the energy input into a given mill.

Specifically, using temperature, mill and circuit data for the Raglan Mine SAG and ball mills, this paper

will first revisit a thermodynamic model of comminution processes in order to illustrate the potential and

means for energy recovery. This will be followed by an investigation into the sources of energy loss

including conduction/convection, radiation and mass transfer as well as exploring avenues into possible

means to maximise energy recovery. Finally, a discussion will explore the potential impact of energy

recovery on comminution efficiency.

THE RAGLAN MINE CONCENTRATOR

Glencore’s Raglan Mine is located along the northern limit of Quebec’s territory, along the 62nd

parallel (see Figure 2). The average annual temperatures are about -10C with lows in winter below -40C

(Isolated, 2013) and average ambient temperatures underground around -15C. Raglan Mine’s property

spans 70 km consisting of 4 operating underground nickel mines, a port facility on Deception Bay,

accommodation and administrative facilities at Katinniq, an airport at Donaldson and the necessary

infrastructure to connect these installations. It is important to note that Raglan Mine is not connected to the

Hydro-Quebec grid due to its remote location. As a result, all electrical energy has been until recently

produced by diesel electric generation. In 2014, a wind energy project including an energy storage system

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was constructed in order to capture the local wind energy potential and off-set diesel fuel costs, this system

now accounts for up to 5% of Raglan Mine’s total energy production requirements. As of June 2015, it has

produced 6.76 GWh of electrical energy, displacing 1.734 million litres of diesel fuel and reducing

greenhouse gas emissions by 4838 Tonnes.

Raglan Mine has been in operation since 1997. Originally designed for 800 000 tonnes of ore

annually, Raglan’s Concentrator now operates at the maximum 1 320 000 M tonnes annually as per The

Raglan Agreement signed with the government and local Inuit communities in 1995.

Figure 2 - Location of Glencore’s Raglan Mine (Raglan Mine, 2015)

THERMODYNAMIC COMMINUTION MODEL REVISITED

Thermodynamic model development (Radziszewski, 2013) starts with the definition of a control

volume around a piece of equipment or circuit followed by establishing all of the input and puts as

illustrated in Figure 3.

a) control volume around a SAG mill circuit b) control volume around a ball mill

Figure 3 - Defining a control volume around a comminution circuit and equipment

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Once the control volume and all input and outputs are determined, an energy balance can be

prepared:

�̇�𝑐.𝑣. − �̇�𝑙𝑜𝑠𝑡 = �̇�𝑠𝑙(ℎ2 − ℎ1) (1)

where:

�̇�𝑐.𝑣. - work input to the control volume [kJ/s or kW],

�̇�𝑙𝑜𝑠𝑡 - heat lost to the environment [kJ/s or kW],

�̇�𝑠𝑙 - slurry mass flow rate [kg/s],

h2, h1 - slurry discharge and feed enthalpy respectively [kJ/kg].

In order to simplify the relationship, the work input consider as only the heat input into the control

volume which for ball mill grinding is assumed to be 99% of the mill input power.

Assuming constant pressure, an incompressible fluid and solid in the slurry, it is possible to

expand the energy balance to the following:

�̇�𝑐.𝑣. − �̇�𝑙𝑜𝑠𝑡 = (�̇�𝑜𝑟𝑒𝑐𝑜𝑟𝑒 + �̇�𝑤𝑎𝑡𝑒𝑟𝑐𝑤𝑎𝑡𝑒𝑟)(𝑇2 − 𝑇1) (2)

where:

core, cwater - specific heats of the ore and water [kJ/kg-K],

T2, T1 - discharge and feed slurry respective temperatures [K].

Using the thermodynamic model, the definition of Carnot efficiency along with anecdotal and

published grinding circuit data, it was demonstrated that energy recovery potential for a temperature

difference of 30C between a discharge slurry temperature and a cold water source was up to 10% of the

energy used in comminution.

Knowing the energy recovery potential of comminution systems, it is then possible to look at how

this energy can be converted to a usable form such as electricity. There are mechanical means such as a

Sterling cycle engine or a organic Rankine turbine that approach Carnot efficiency. However, such systems

require a significant infrastructure. On the other hand, there are electrical means that can be used to

accomplish this too. One such electrical system is a thermoelectric generator as illustrated in Figure 4.

With a 30C temperature difference, the expected energy conversion performance of this particular

system would be 1.27 kW/m2.

As a point of comparison, acoustic energy potential is estimated to be in the hundredths of a W/m2

(Sound, 2011), wind energy potential is estimated to be around 1 W/m2 (current wind technology potential

(Wind, 2012) divided by earth’s surface) and solar energy potential is estimated to be 300 W/m2 (average

solar energy at Earth’s surface (680 W/m2) x solar cell efficiency (Sun, 2014)).

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a) general structure of a TEG (TEG, 2014) b) power output for eTEG HV56 thermoelectric generator

(reproduced from Nextreme, 2012b)

Figure 4 - Structure and performance of a thermoelectric generator

Although quite promising, this initial study also emphasized the need to address a number of

questions especially related to the underlying assumptions through the use of industrial data before any

industrial implementation can be envisioned.

THERMAL DATA COLLECTION

The ore processed is a nickel bearing ore coming from 4 different mines in the area. The average

ore composition is illustrated in Table 1 along with the respective mineral’s heat capacity determined from

Waples and Waples (2004). The concentrator has a SAG mill circuit feeding a ball mill circuit. The general

specifications of the SAG and ball mills can be found in Table 2.

Table 1 - Heat Capacities Table 2 - Mill Data

One control volume was defined around the SAG mill circuit and another control volume was

defined around the ball mill. Temperature measurement points were determined at the control volume

boundaries as illustrated in Figure 5. All other data was collected from the plant’s data historian.

Temperature data was collected on four different occasions using both an immersion and an

infrared thermometer (see Figure 6) and recorded manually.

Composition Heat Capacity

[%] [kJ/kg-K]

Pentlandite: 10 0.576

Infotherm (2015) :

0.445 kJ/mol-K x

0.77194 kg/mol

Chalcopyrite: 5 0.534

Pyrrhotite: 15 0.594

Gabbro: 70 0.825average of 0.65 and

1.0 kJ/kg-K

average ore 0.7509

Water 4.183

Soda Ash 1.06

CommentMineral Parameter Ball mill SAG mill

Diameter [m] 4.27 7.3

Belly length [m] 6.4 3.2

Shell thickness [m] 0.075 0.1

Liner (average)

thickness[m] 0.25 0.185

Liner material rubber steel

Thermal

conductivity[W/m-K] 0.13 43

Estimated forced

convection coef.[W/m

2-K] 200

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Figure 5 - Raglan Mine’s SAG and ball mill circuit with temperature measurement points

a) measuring temperature at the

sump

b) temperature sensor used at the

sump

c) infrared sensor used to capture

ball mill discharge temperature

Figure 6 - Temperature measurement system and locations

DETERMINING HEAT LOSSES

Heat losses for the Raglan Mine’s ball mill and SAG mill circuit can be determined using

appropriately defined energy balances for each context.

Ball mill heat loss

In the ball mill case, the energy balance found in equation (2) is sufficient as all the ore and water

components of the slurry at the feed and discharge are at a similar temperature of T1 and T2 respectively.

Solving equation (2) for energy lost �̇�𝑙𝑜𝑠𝑡 and using the data provided in Table 3, it is possible to estimate

the average portion of energy input into ball mill grinding lost to the environment which in this case is 30%

or 681 kW.

Using mill make-up water (16C) as the cold source and the average slurry temperature (34.4C) as

the hot source, the energy capture potential efficiency is estimated to be defined by the Carnot efficiency.

For this particular case, the Carnot efficiency is 5.99% which represents some 132.7 kW.

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Table 3 - Ball Mill Thermal Quantities

SAG mill circuit heat loss

Examining the temperature data for the SAG mill circuit found in Table 4 indicates that the three

input streams (rock, water and soda ash) all have different temperatures. In addition, for water, the input

stream is actually two input streams both at the same temperature. Further, energy input into the control

volume comes from two principle sources which are the SAG mill and the crusher. As a result, it becomes

necessary to expand further the energy balance described in equation (2).

With respect to the control volume approach, it should be noted that only the control volume

inputs and the outputs are considered and not the location in the circuit of these inputs and outputs.

Assuming a similar circuit discharge temperature (T2) for all components, the resulting expanded energy

balance for the SAG mill circuit is:

�̇�𝑐.𝑣. − �̇�𝑙𝑜𝑠𝑡 = �̇�𝑟𝑐𝑟(𝑇4 − 𝑇𝑟𝑖𝑛) + �̇�𝑤𝑐𝑤(𝑇4 − 𝑇𝑤𝑖𝑛

) + �̇�𝑠𝑎𝑐𝑠𝑎(𝑇4 − 𝑇𝑠𝑎𝑖𝑛) (3)

where the subscripts “r”, “w”, “sa” designate rock, water and soda ash respectively and the sub-

subscript “in” indicates input.

Defining �̇�𝑐.𝑣. for this SAG mill circuit requires assuming the amount of energy converted to heat

for both the SAG mill and the crusher. This can be accomplished by referring to the work of Nadolski et.

al. (2014) who defined a “Benchmark Energy Factor” (BEF) which is the “ratio of actual equipment energy

to a minimum practical energy” required to break ore to a desired target size. Using the BEF for a ball mill

circuit (1.71) and the BEF for a SAG mill circuit (2.46) which includes a pebble crusher and assuming that

the efficiency of the ball mill circuit is indeed 1%, it is possible to estimate the efficiency of the SAG mill

circuit as being (1.71/2.46) 0.7%.

Therefore, the work input (as heat) into the SAG mill circuit control volume is defined as:

�̇�𝑐.𝑣. = 0.993(�̇�𝑆𝐴𝐺 + �̇�𝐶𝑟𝑢𝑠ℎ𝑒𝑟) (4)

Due to the short contact time at the screens, the water addition there is assumed to be outside of

the control volume. As a result, the temperature of the slurry and the rock leaving the SAG mill circuit

control volume is considered to be the same.

The addition of soda ash (sodium carbonate) to the SAG mill feed is a means to control slurry pH

by neutralizing the sulphuric acid generated by the oxidation of the massive sulphide ore being ground.

The soda ash - sulphuric acid reaction is exothermic and produces CO2 gas which should bubble off. As the

mass rate of the soda ash addition is quite small as compared to the rock and water, it will not be included

in the energy balance. Further, it will be assumed that the difference between the energy generated by the

Mill

Power

slurry

flow

rate

slurry

densityore density

point 1

temperature

point 2

temperature

Slurry

Specific

Heat

Heat

Input

(Ẇcv)

Shell

Temperature

[kW] [m3/hr] [% solids] [s.g] [C] [C] [kJ/kg-K] [kW] [C]

initial data 2240 173 71 3 33.8 37.4 1.75 2218

1 1746.9 250 71 3.35 28.8 33.8 1.75 1729 29

2 1730.5 208 71 3.26 28.1 32 1.75 1713 27

3 1755.3 166.4 71 3.3 25 31.9 1.75 1738 23

4 1794.5 77.1 71 3.19 31.5 39.4 1.75 1777 27

average 1853.44 174.98 71 3.2 29.4 34.9 1.75 1834.91 26.6

˙

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exothermic reaction and that lost through CO2 mass transfer to the atmosphere is small and will not affect

the overall energy balance.

The resulting energy balance for the SAG mill circuit control volume is reduced to:

�̇�𝑐.𝑣. − �̇�𝑙𝑜𝑠𝑡 = �̇�𝑟𝑐𝑟(𝑇4 − 𝑇𝑟𝑖𝑛) + �̇�𝑆𝐴𝐺𝑐𝑤(𝑇4 − 𝑇𝑤𝑖𝑛

) (5)

The result is that the average portion of input energy lost to the environment is determined by

solving the energy balance (equation 5 in this case) for) for energy lost �̇�𝑙𝑜𝑠𝑡 and using the data provided in

Table 4. In the Raglan Mine SAG mill circuit case, the average energy lost to the environment represents

21.6% of the energy input to the circuit at a rate of 500 kW.

Using mill make-up water (16C) as the cold source and the average slurry discharge temperature

(26.2C) as the hot source, the energy capture potential efficiency is estimated to be defined by the Carnot

efficiency. For this particular case, the Carnot efficiency is 3.41% which represents some 79 kW.

Table 4 - SAG Mill Circuit Thermal Quantities

MODELLING SOURCES OF ENERGY LOSS

There are essentially three sources of energy loss which are related to conduction/convection, radiation and

mass transfer.

Conduction / Convection Losses

Estimating the effect of conduction/convection on the slurry heat losses requires the development

of a heat transfer model. In the literature, Kapakyulu and Moys (2007 a, b) presented a rather complete

heat transfer model between the mill charge and the mill exterior. However, for the present case, a lumped

parameter model will be defined for the simplified mill cross-section illustrated in Figure 7.

Figure 7 - Simplified tumbling mill cross-section

feed rate feed temp.feed rate

SAG

feed rate

screensfeed temp. feed rate feed temp.

[kW] [kW] [t/hr] [C] [m3/hr] [m

3/hr] [C] [l/min] [C] [C] [C]

1 2264.4 63.04 180 -14.5 39.14 17.28 16.6 28.77 18.9 28.4 28

2 2464.58 63.35 177 -20 32.28 22.5 16.2 59.03 16.5 28.4 30

3 1854 60 204 -1.2 40.6 23.2 12.6 30.1 12.6 21 21

4 2451 57.6 166 0 43.6 23.8 17.7 61.9 16.7 27 28

average 2258.50 61.00 181.75 -8.93 38.91 21.70 15.78 44.95 16.18 26.2 26.88

Rock Water Soda Ash

sample no.

Crusher

Power

SAG Mill

Power

Discharge

Temp.

Shell

Temp.

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In the context described in Figure 7, part of the heat lost is through the mill shell by conduction

and then convection (Qcc). The relationship that describes this heat transfer context is defined as (Holman,

1976):

sossll

acc

hAAk

rr

Ak

rr

TTfQ

12312

1

lnln (6)

where:

T0 – average slurry temperature [C]

T1 – inside liner surface temperature [C]

T2 – liner/shell interface temperature [C]

T3 – outside shell temperature [C]

Ta – ambient temperature [C]

Al, As, Aso – surface area of liner, liner/shell interface, shell outer [m2]

r1 – radial distance to the average inside liner surface [m]

r2 – radial distance to the liner/shell interface [m]

r3 – radial distance to the outside shell surface[m]

kl, ks – thermal conductivity of liner and shell [kW/m-K]

h – convection coefficient [kW/m2-K]

f – adjustment factor (f = 1.5)

An adjustment factor was introduced into equation (6) in order to compensate for the fact that the

mill ends are not included in the surface area over which heat is lost to the environment. In this particular

case, it is assumed that the mill ends add another 50% to the conductive/convective heat losses.

For the ball mill the conduction/convection losses are determined to be 0.84 kW which is 0.05%

of the energy input into the ball mill. For the SAG mill, the conduction/convection losses are determined to

be 48.1 kW or 2.07 % of the input energy.

As a validation of the conduction/convection model (equation 6), the mill shell temperature (T3)

was calculated with a modified form of equation (6) giving 27.7C for the ball mill and 25.3C for the SAG

mill. Comparing these calculated values with the average measured shell temperatures (see Tables 3 and 4)

on the Kelvin scale indicates that the calculated values are within 1% of the average measured shell

temperatures.

Radiation Losses

Heat transfer by radiation can be defined as follows (Holman, 1976):

soarad ATTfQ 44

3 (7)

where:

– surface emissivity [0.96 (painted surface)]

– Stefan-Boltzman constant [5.6703 x 10-11

kW/m2-K

4]

Using the mill shell temperature (T3) previous calculated, it was possible to estimate the ball mill

heat losses by radiation heat transfer as about 4.97 kW or some 0.27% of the ball mill input energy. For the

SAG mill the heat losses due to radiation are about 2.71 kW or some 0.12% of the input energy.

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Evaporative Losses

Mass loss (�̇�𝑒𝑣𝑎𝑝) due to evaporation in a tumbling will be approximated by following

relationship developed to evaluate the evaporative mass loss of small water surface areas (Asdrubali, 2009,

Engineering, 2015, Rafferty, 1986):

3600xxAfm ssleevap (8)

where:

v1925 (9)

and:

v – velocity of air over water surface [m/s]

Asl – area of water surface [m2]

xs – humidity ratio in saturated air at the surface water temperature (Tw) [kg/kg]

x – humidity ratio in the air [kg/kg]

fe – correction factor [unity]

The humidity ratio for saturated air can be determined as follows:

wsawss pppx 621980. (10)

where:

pa – atmospheric pressure of moist air [kPa]

pws – saturation pressure of water vapour [kPa]

further:

28

723500560345077

1000 .

..

T

ep

TT

ws

(11)

The resulting energy lost by evaporation can now be determined as:

evapevapevap hmQ (12)

where: hevap – heat of vaporization of water [hevap = 2260 kJ/kg]

The slurry surface area for an overflow ball mill will be estimated by 1.25 Rmill Lmill which is the

radius of the mill plus the radius of a typical trunnion (0.25 Rmill) times the average length of the mill. As a

slurry pool is an undesired operating condition (Powell, Valery, 2006), the slurry pool over which energy is

lost by evaporation will be estimated to be 35% of a ball mill or 0.35 Rmill Lmill.

Table 5 summarised the energy lost to evaporation along with the associated results for

evaporation and those related to energy lost by conduction/convection and radiation. It should be noted that

the correction factor (fe = 1.53) was determined from the ball mill case and applied to the SAG mill case.

Table 5 - Estimated losses in Raglan Mine’s SAG and ball mills

Mill PowerConduction &

convection lossLoss by radiation

Loss by

evaporationOther losses Total lost

[kW] [kW] [kW] [kW] [kW] [kW]

Ball mill 1853.44 0.84 4.97 635.23 - 641.04

SAG mill circuit 2319 48.10 2.71 50.33 399.26 500.40

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Based on these loss models, it is interesting to note that the majority losses in the ball mill case is

due to evaporation while in the SAG mill circuit it is relegated to other losses. This may be due to the

smaller “slurry pool” in the SAG mill as well as to higher losses around the circuit.

INVESTIGATING AVENUES TO MAXIMISE ENERGY RECOVERY POTENTIAL

Having determined the source of energy losses to the environment for these two particular cases, it

now becomes possible to expand equations (2) and (5) to include these losses as well as solve them for the

respective ball mill and SAG mill circuit discharge temperatures as illustrated:

Ball mill discharge temperature

𝑇2 =�̇�𝑐.𝑣.−(�̇�𝑐𝑐+�̇�𝑟𝑎𝑑+�̇�𝑒𝑣𝑎𝑝)

(�̇�𝑜𝑟𝑒𝑐𝑜𝑟𝑒 + �̇�𝑤𝑎𝑡𝑒𝑟𝑐𝑤𝑎𝑡𝑒𝑟) + 𝑇1 (13)

SAG mill circuit discharge temperature

𝑇4 =�̇�𝑐.𝑣.+�̇�𝑟𝑐𝑟𝑇𝑟𝑖𝑛

+�̇�𝑤𝑐𝑤𝑇𝑤𝑖𝑛−(�̇�𝑐𝑐+�̇�𝑟𝑎𝑑+�̇�𝑒𝑣𝑎𝑝)

�̇�𝑟𝑐𝑟+�̇�𝑤𝑐𝑤 (14)

This will allow the possibility to start exploring different means to increasing the energy recovery

potential as defined by Carnot efficiency. Knowing the Carnot efficiency, it becomes possible to estimate

the associated potential value.

In the case of the ball mill, leaving the mill shell un-painted (iron dark grey surface: = 0.31)

would reduce radiation losses by about two thirds to 1.48 kW. Reducing air flow through the mill by 80%

would drop evaporative heat loss by about two thirds also to 180 kW.

Similar type reduction can be expected for the SAG mill. Further, it is interesting to note that in

the case of the SAG mill conduction/convection losses could be reduced from 48.1 kW to 0.4 kW by

changing to a rubber liner.

Effect of warmer water addition

In the Raglan Mine context, it is difficult to envision a heat source with which to warm up the feed

water. However, through the sunny time of year, it is possible to consider a solar concentrator to increase

feed water temperature by 10C. The resulting effect on the ball mill slurry feed would be to increase it by

some 5C. In the case of the SAG mill circuit, 10C warmer make-up water would increase discharge

temperature by about 5C.

It should be noted that these changes in feed water temperature also affect heat losses due to

conduction/convection, radiation and mass transfer through evaporation. The net effect on discharge

temperature is captured by equations (13) and (14). In both cases, the resulting ball mill discharge and the

SAG mill circuit discharge temperature increase by about 5C. As a result, the associated increase in Carnot

efficiency (assuming a cold source temperature of 16C) is 7.18% from the baseline 6.14% for the ball mill

and 4.75% from the baseline 3.41% for the SAG mill circuit.

Effect of colder cold source

Considering that the average underground ambient temperature is around -15C, it is possible to

envision a geothermal propylene glycol (-59C freezing point) based system to provide a -15C cold source.

The resulting increase in energy recovery potential according to Carnot increases to 15.91% for the ball

mill and 13.69% for the SAG mill circuit.

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Cumulative Effect

Graphically, the effects of all of these changes on heat loss are illustrated in Figure 8 along with

the cumulative result of all of the changes.

a) ball mill losses b) SAG mill circuit losses

Figure 8 - Effect of changes on comminution heat loss

Examining these results, one can notice that overall heat loss is in the order of 20% to over 40%

depending on the context. In the ball mill case, evaporation makes up the vast majority of the heat loss

followed by heat loss by radiation while conduction and convection represents a very small portion of the

total loss. This is undoubtedly the result of using rubber liners in the ball mill. In the SAG mill circuit case,

one more loss term is included which is “other” and represents the losses in the circuit as opposed to those

from the mill. In this case, evaporative losses are similar in terms of magnitudes to those through

conduction and convection. This is understandable as the SAG mill liners are steel having a rather high

thermal conductivity coefficient. Changing the liners to rubber or even poly-metallic liners would reduce

significantly such losses. Evaporative losses in both the ball mill and the SAG mill could potentially be

reduced by limiting air flow through these mills. In addition for the SAG mill circuit, if the “other” losses

can be reduced through various yet to be defined means, it is possible to bring SAG mill losses to a

minimum.

The effect of these changes on the slurry discharge temperature can be determined as described

previously. As a result, the associated Carnot efficiency can be determined and then used to estimate the

energy recovery potential for both the ball mill and the SAG mill circuit. In turn, the energy recovery

potential can be used to estimate the potential annual value of the energy of the slurry. Figure 9 illustrates

both the changes in the Carnot efficiency and the associated annual value of the energy in the slurry.

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a) ball mill case b) SAG mill circuit case

Figure 9 - Carnot efficiency and annual value of energy in the slurry

In summary, if all of the measures were employed on the Raglan Mine SAG and ball mills the

resulting recovery potential would increase from the current 5.79% to 17.4% for the ball mill and from

3.32% to 16.02% for the SAG mill circuit. This represents an annual energy recovery potential (95%

equipment availability, $0.40/kWhr) for the current baseline case just under $0.7 million per year and $2.5

million per year for the cumulative improvement case.

DISCUSSION

In the paper Radziszewski (2013), five assumption were made which include slurry heat capacity,

portion of input energy converted to heat, portion of energy captured in slurry, the influence of water

addition to the grinding circuit and adiabatic/sealed operation conditions.

With respect to slurry heat capacity, in the Raglan Mine case no assumption was made as the

general ore composition was used to determine the slurry heat capacity.

It was assumed that 99% of the input energy is converted to heat. This was somewhat modified for

the SAG mill circuit using the “Benchmark Energy Factor” (Nadolski et.al., 2014). However, the basis of

this assumption is that all energy loss paths eventually lead to generating heat.

No assumption was made on how much energy was captured in the slurry. This was calculated

directly from the model with the use of the feed and discharge temperature measurements.

No assumptions were made on the influence of water addition at the cyclones and circuit in

general. All water inputs to the circuit were taken into account. However; it was assumed that energy value

of soda ash addition was equal to the energy value loss of carbon dioxide gas.

No assumptions were made on adiabatic and sealed conditions for the mills. Instead models for

heat and mass transferred were developed which required the establishment of a few more assumptions and

a couple of factors.

Namely, for conduction and convection as lumped parameter model was used to estimate heat lost

through the mill shell. Comparing the average measured shell temperature with the calculated estimate

indicates that this model is within 1% of the measured value. However, it should be noted that the surface

over which conduction convection occurs is assumed to be 50% greater than just the circumferential mill

shell area.

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With respect to radiation loss, the same 50% greater surface area was used to estimate the surface

over which radiation loss occurred. No validation of the resulting radiation loss was made.

With respect to mass transfer, the model used assumes that evaporative heat loss is a function of

“pool” area, the speed of air over that surface and the relative humidity around the mill. In this case, “pool”

area was estimated for both the ball and SAG mills as a function of the mill dimensions while air speed

was estimated and relative humidity was taken from local humidity records. Further, a correction factor

was used.

To summarise, the results presented here are the product of a reduced number of assumptions due

to the use of industrial data. However, in so doing, a few more assumptions were made related to heat

transfer and mass loss models used to estimate sources of energy loss.

Efficiency

It was described that energy efficiency, expressed as a percentage, is defined as a dimensionless

ratio of the work produced over the energy consumed or input in order to produce that work. In the case of

comminution processes, the work produced is defined by the new surface energy produced in grinding and

is typically considered to be less than 1% of the input energy. Therefore comminution efficiency (comm) is

defined as the efficiency of producing new surface energy (nsa):

𝜂𝑐𝑜𝑚𝑚 = 𝜂𝑛𝑠𝑎 (15)

However, if comminution were to be seen as a process that produces two usable products (ground

ore and energy), it may be possible to redefine comminution efficiency as:

𝜂𝑐𝑜𝑚𝑚 = 𝜂𝑛𝑠𝑎 + 𝜂𝐶𝑎𝑟𝑛𝑜𝑡 (16)

where:

Carnot – Carnot efficiency defining potential energy recovery from the mill slurry.

If this were the case, the potential efficiency of the Raglan Mine’s SAG mill circuit would be

about 17% while for the ball mill the efficiency would be about 18%.

On the other hand, it is important to include the efficiency of a particular technology (tech) to

meet the efficiency defined by Carnot which suggests that comminution efficiency should actually be

defined as:

𝜂𝑐𝑜𝑚𝑚 = 𝜂𝑛𝑠𝑎 + 𝜂𝑡𝑒𝑐ℎ 𝜂𝐶𝑎𝑟𝑛𝑜𝑡 (17)

In either case, the potential to recover comminution energy should be included in the definition of

comminution efficiency in order to underline that comminution processes have potentially two products.

CONCLUSIONS

An initial study of the comminution energy recovery potential indicated that there is potential

value that can be capture from a mills slurry through a few possible technological means. However, a

number of assumptions were used in that development that could only be addressed using industrial data.

In examining these assumptions in the case of Glencore Raglan Mine’s SAG and ball mill circuits,

the thermodynamic analysis indicates that the current energy recovery potential is in the order of 190 kW

(ball mill and SAG mill circuit) or 4.6% of the total comminution grinding energy. Exploring possible

means of improving this recovery potential indicates that it can potentially be increased to 684 kW (ball

mill and SAG mill circuit) or 16.6%.

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In working to estimate Raglan Mine’s comminution energy recovery potential, it was possible to

make a number of observations:

Average energy lost from the Glencore Raglan Mine ball mill is 34.6%

Average energy lost from the Glencore Raglan Mine SAG mill circuit is 21.6%

Conduction/convection represents a small amount of energy lost for the two cases examined.

Conduction/convection losses can be reduced by the use of rubber. Although it was not estimated, one

could expect similar reductions with polymetallic liners.

Possible means to reduce radiation losses are related to mill paint can coatings.

Mass transfer due to evaporation was found to be the major cause of heat loss to the environment.

Possible means to reduce mass transfer heat loss is through sealing the comminution circuit.

As a result, it is possible to consider that energy is a potential second product of comminution.

Accepting this observation means that comminution efficiency can be redefined as the sum of new surface

energy produced and energy recovered divided by energy input.

One final concluding remark:

Lord Kelvin stated: “If you cannot measure it, you cannot improve it”.

Our response: “So measure it!”

ACKNOWLEDGEMENTS

The authors would like to thank Glencore’s Raglan Mine and Metso for granting permission to

publish and present this work and associated data and results.

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