USIM PAC 31 Starting Guide

Starting Guide

Version 3.1.1.0

Caspeo 3 avenue Claude Guillemin - BP 6009 45060 ORLEANS CEDEX 2 – FRANCE Tel: +33-238-643615 Fax: +33-238-259742 E-mail: [email protected]

BRGM is the author of USIM PAC Copyright © BRGM 1986 – 2004, © Caspeo 2004 – 2006

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TABLE TAB LE OF CONTENT CONTENT Pages 1 - INTRODUCTION........................................................................................................4 1.1 - The Simulation based Approach....................................................................4 1.2 - Unit operation models....................................................................................6 2 - GENERAL FEATURES OF USIM PAC......................................................................8 3 - INSTALLATION OF USIM PAC ........................... ............................... ....................... 8 4 - CASE 6: A DESIGN CASE STUDY ............................ ............................... ................ 9 4.1 - The Objectives...............................................................................................9 4.2 - The Methodology ............................ ............................ ............................ .......9 4.3 - Step one: enter data ............................ ............................ ............................ 10 4.4 - Step two: define plant performance .......................... ............................ .......15 4.5 - Step three: design the units of equipment .......................... ......................... 20 4.6 - Step four: estimate capital cost....................................................................24 REFERENCES..............................................................................................................26















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1 - INTRODUCTION Since 1986, BRGM has been developing a powerful process simulation software package, USIM PAC (Broussaud 1988; Durance et al. 1993; 1994; Guillaneau et al. 1997, Brochot et al. 2002). It is a user-friendly steady-state simulator that allows mineral processing engineers and scientists to model plant operations with available experimental data and determine optimal plant configuration that meets production targets. The simulator can also assist plant designers with sizing unit operations required to achieve given circuit objectives. The software package contains functions that can manipulate experimental data, calculate coherent material balances, sizes and settings of unit operations, physical properties of the processed materials, simulate plant operation and display results in tables and graphs. Widely used in industrial plant design and optimization, with more than one hundred fifty licenses sold in thirty countries, this software has been continuously improved, through successive versions, to make it more accurate, powerful and easier to use. These last years have seen significant developments in mineral processing technologies, particularly in hydrometallurgy, bio-hydrometallurgy (Cézac et al. 1999; Brochot et al. 2000) and mineral liberation. In addition, it is now necessary to take into account the environmental impact at each stage of a mining project, including water and power consumption, waste treatment and disposal (Sandvik et al. 1999; Guillaneau et al. 1999). This new version of the simulator, USIM PAC 3.1, incorporates these modern developments. Indeed, its structure and tools allow the user to take into account, at the same time, a wide range of technological, economic and environmental aspects (Brochot et al. 2002). The main features of USIM PAC 3.1 will be presented through the description of the design and optimization methodologies. The significance of these features will be illustrated by an example of design of a gold ore treatment plant. 1.1 - The The Simulatio n based App roach

Process modeling and simulation are used at all stages in the life of a mineral processing plant: from process development to site rehabilitation, including pre-feasibility and feasibility studies, engineering design, plant commissioning, plant operation and upgrading right through to decommissioning. From the beginning, the simulation-based approach describes the behavior and performance of the future plant. This description will be more and more precise owing to the capitalization of knowledge acquired through laboratory tests, pilot plant campaigns and plant operation. There is a continuous exchange between reality and the virtual plant constituted by its steady-state simulator. A simulator combines the following elements (see Figure 1): A fl ow sh eet that eet that describes the process in terms of successive unit operations and material streams. This flowsheet encapsulates the experience of the engineers responsible for the plant design or optimization. It can reflect various scenarios so they can be compared against given criteria. It takes into account numerous plant features such as reagents















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term behavior) for environmental impact can be evaluated. The phase description is critical for analyzing and optimizing the process. This statement reinforces the vital importance of field data and sampling protocols. A mat hemati hem ati cal mo del for each unit operation. This model formalizes the current scientific knowledge about the unit operation, and its level of complexity depends on the data available and the targeted objectives (i.e. flowsheeting, unit operation sizing, or optimization). The model parameters - dimensions, settings and calibration factors - are calculated or validated from field data. A set of alg or it hm s for data reconciliation, model calibration, unit operation sizing, full material balance calculation, power consumption and capital cost calculation. These algorithms are interfaced with a set of data representation tools. As a result, the plant simulator constitutes a highly efficient communication vector between the different actors who play a part in the plant life. PLANT FEED

MODELS

Feed rate Feed size distribution Feed mineral distribution

PLANT DESIGN Flowsheet Units of equipment

STEADY-STATE SIMULATOR

PLANT PERFORMANCE

Flowrates Size distributions Mineral distributions Power draws

PLANT CAPITAL COST

Figure 1: Main functions of a steady-state simulator Steady-state simulation does not compete with dynamic simulation: it is not a lower or higher level of simulation. Whereas dynamic simulation is an essential tool for the design of process-control strategies and a key element of advanced process-control systems, steady-state simulation is an essential tool for plant design and pre-control optimization: it is adequate to optimize the circuit design and the dimensions of the units of equipment before the implementation of a process-control system.















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Figure 2: Main Window of the USIM PAC simulator The simulator offers an array of powerful tools in response to the increasing demand for a multi-criteria, global approach by plant designers. It takes into account a wide spectrum of design criteria, including: -

Economic criteria such as capital cost, cost, reagent and power consumption, production quality in terms of valuable mineral grade or undesirable elements level;

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Technical aspects with the evaluation of various configurations and processing technologies, a complete and detailed description of all material streams and their behavior during process;

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Environmental factors such as water consumption and recycling, pollutant production or waste treatment.

USIM PAC is a very flexible flexible simulator (see Fig. 2). It can be used by process engineers for plant design or optimization, researchers for process model development, as well as academics for teaching process-engineering students. The previous version, USIM PAC 3.0, already represented a significant milestone towards integrating different industries through a global approach. It was possible to simulate treatment from the mine through the metallurgical plant. Studies on a global approach in urban waste management (Sandvik et al. 1999) or metal life cycle (Reuter 1998) already used steady state process simulation techniques. Version 3.1 goes further in that way. The material description has been enriched with additional criteria that give capabilities to simulate processes in various field. 1.2 - Unit operation models

















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2. Mathematical models for unit operations, which constitute the core of the system, albeit they are buried inside the simulator as modules. INPUT PLANT CAPITAL COST Flowrates Size distribution Mineral distribution

PHYSICAL PROPERTIES

MODELS

Output(s) Flowrates Size distributions Mineral distributions Power draws

Figure 3: Unit operation model Various mathematical models can be associated with each unit operation drawn on the flowsheet. Mathematical models calculate the output streams data from the input stream data and model parameters (see Figure 3). These parameters can be equipment sizes, operating conditions, physical properties, model adjustment parameters or simply performance criteria. Depending upon the simulation objective and the data available, different mathematical models can be used for the same piece of equipment. In USIM PAC, mathematical models are divided into four levels: -

Level 0 models enable the user to specify directly the performance of the units. For example, the performance of a classification unit can be modeled by a partition curve for which the user specifies the bypass, the imperfection and the cut-size (d50). Such models are also called flowsheeting models as they do not take into account any sizing parameters. During the simulation, the performance of the unit will be independent of its dimensions and the flowrate of the ore feeding it.

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Level 1 models take dimensional parameters into account. They require little (sometimes















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flotation, Gravity/Magnetic separation, etc.), hydrometallurgy (Leaching, Bioleaching, CIP, CIL, Precipitation, Cementation, Solvent extraction, Electrowinning, etc.), solid/liquid separation (Filtration, Sedimentation, etc.), waste treatment (Collection, Sorting, Incineration, composting, etc.).

2 - GENERAL FEATURES OF USIM PAC USIM PAC offers powerful and easy-to-use methods to help engineers reach their objectives. It requires no special training in computing or modeling. Basic functions of USIM PAC can be divided into plant modeling, data input, data processing and different tools for data and results display. High level functions are also available for configuration and incorporation of user defined functions.

USIM PAC runs under Windows™ 2000/XP. The minimum hardware is: Pentium-based PC with 256 Mb RAM, 50 Mb of free disk space. We recommend: Pentium-based PC with 512 Mb RAM, 128 Mb of free disk space.

The advanced user u ser of USIM PAC can create new n ew icons to represen t the devices on a flowsheet, or new equipment simulation models. Models and icons are introduced in the form of FORTRAN functions, which must respect a few simple, well-defined rules. These subroutines must be compiled and linked with an object code module supplied with the USIM PAC Development Kit. FORTRAN compiler and linker are provided with the program.

This flexibility makes it possible to satisfy the need of some USIM PAC users to insert their own models in the software, as well as to provide a legal guarantee on the delivered object code.

The user may also insert into the program completely new functions taking some or all of their data from the USIM PAC files.

3 - INSTALL ATION OF USIM PAC PAC The installation of USIM PAC from the CD Rom is done through a specific procedure,















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4 - CASE 6: A DESIGN CASE STUDY 4.1 - The Objectives

The example given here provides the opportunity to describe a general methodology, by which a preliminary design and capital cost evaluation of a plant can be achieved in a few hours with USIM PAC 3.1. It corresponds to a preliminary design of a comminution circuit in the mineral processing industry. It is delivered with the software as the CASE6 tutorial.

The objective is to make a preliminary design of a goldgrinding/classification/leaching/adsorption plant capable of treating 100 t/h of a gold ore with 95 % recovery. •

Size distribution: 0×8 mm

•

Gold content: 7 ppm.

•

Specific gravity: 3.

Plant specifications are (see flowsheet fig. 7): •

Primary grinding with a rod mill in open circuit.

•

Secondary grinding with a ball mill in closed circuit.

•

Classification by hydrocyclone with with a circulating load from 150 % to 250 %.

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Leaching tank series with d80 = 75 µm for the feed.

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CIP tank series series with 50 ppm of gold in the recycled recycled carbon.

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Dewatering of the barren pulp in a thickener with water recycling for percent solids regulation.

Laboratory tests give: •

Work Index: 14 kWh/st.

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Maximum recovery of gold by cyanidation: 98 %.

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Leaching rate constant: 0.3 h-1 (assuming a first order kinetic).

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Adsorption rate constant: 700, time constant: constant: 0.3 (assuming the kn equilibrium model).

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Maximum percent solids after clarification: 70 %.

The following sections details the succession of steps used in preliminary plant design: plant















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Objective Pre-feasibility study

Conventional flowsheet hypothesis

USIM PAC simulation of the plant plant using simple models without equipment dimensioning

Laboratory experimentation: -measurement of Bond index - mesurement of flotation kinetics

USIM PAC dimensioning the equipment for the plant

USIM PAC technical results printout of a full report with flowsheet, graphs and tables

USIM PAC simulation of the full operation of the plant. Comparisons between several possible flowsheets USIM PAC economical results calculation of the approximate capital cost of the main equipment and the overall cost of the plant

Figure 4: Methodology for a preliminary design 4.3 - Step one: enter data Draw Draw p lant flo wsheet

The Flowsheet Drawing Drawing option of USIM PAC is used to draw or modify a flowsheet; it is entirely graphic and icon driven (see Fig. 5). The arrow is used to select functions in the Toolbox Toolbox with the mouse (see Fig. 6) and to position equipment icons, material streams or texts on the screen. The Unit button opens the icon library organized in groups of icons, depending on their function. The created flowsheets are not simply saved as drawings: they are also analyzed and error messages are displayed if the flowsheet is not physically comprehensible. Flowsheets can be displayed on the screen, modified using the Flowsheet Drawing Drawing option, or plotted on paper using File\Print... option. File\Print... option.















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Figure 5: Screen drawing plant flowsheet

Figure 6: Tools box of the flowsheet drawing option Any flowsheet can be copied and pasted through the clipboard. A copy of the described flowsheet is presented on Figure 7. 9

Feed 17

1

Rod mill feed 4

2 1

8

Rof mill product

3

Cyclone feed 7

5 3

2

OF

16

4

Recycled water

6

14 5

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For this case study, the ore is described in terms of a size distribution for grinding and classification and a global gold content for leaching. The predefined phase named “Gold ore” fits this description. The other phases present in the process are the water used for wet treatment and leaching and the carbon used for the CIP stage. These phases are described by their gold content (see Figures 8, 9 and 10).

Figure 8: Description of the t he phase model The units used above can be configured and adapted to the units used in the plant. For a given project, the user of the program must define a phase model - i.e. he must decide how to represent the material in the streams: the number of particle-size classes and the corresponding mesh sizes, the number and names of the minerals or mineral groups, with their specific gravities. The user can define types of mineral particles, and/or the flowrates of flotation reagents associated with the slurry stream. Specific gravity of gold (19) is not















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Figure 10: Description of the phase model – composition for the three phases In this case, connections between phases are defined. They represent the capability of gold to transfer from one phase to another (Ore to Solution through leaching, Solution to carbon through adsorption – see fig. 11 & 12).















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Gold Ore

Carbon

Leaching water

Gold transfer















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The input interface for the stream data follows the phase model structure. It gives, stream by stream, the list of phases and solid-liquid pairs (see Figure 14). Available data for each phase are the mass flowrate, the volumetric flowrate and the t he density; if they are known, the component grade and the size distribution for the ore phase. Depending on the study, stream density may be required and descriptions such as composition by size classes or floating ability by component can be necessary. Available data for each solid-liquid pair are the pulp mass flowrate, the pulp volumetric flowrate and density if they are known and the percent solids. For a given solid-liquid pair, only two values among both phase flowrates, pulp flowrate and percent solids are necessary. The other two are calculated. Size distribution can be input using individual % passing or cumulative % passing or retained.















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This step obviously requires some expertise from the software user. The time has not yet come when the software is able to define relevant performances for each unit operation from such a general objective as "required circuit performance: d80 = 60 µ m at the hydrocyclone overflow". In the present application, the software user (plant designer) suggests the following local objectives, using level 0 models (see Table 1).

Table 1 Level 0 models Units

Models and main parameters

#1 – Feeder

Mixer (0)

Values

#2 – Rod mill regulator Density Regulator (0) Percent solids at regulator output (%) #3 – Rod mill

Mill (0A) d80 at the mill discharge (mm)

#4 – Hydrocyclone regulator

#6 – Leaching

1

Density Regulator (0) Percent solids at regulator output (%)

#5 – Hydrocyclone

70

40

Hydrocyclone (0B) Short circuit of fines (%)

25

d80 of output fine stream (mm)

0.075

Corrected partition curve imperfection

0.3

Leaching (0) Leached percentage per component of ore and 95

















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Figure 15: CIP – Carbon-In-Pulp (0) mathematical model parameters Run a Level 0 simulation

The ideal description of all the streams is calculated by the direct simulation algorithm from the feed description using the selected performance models. This preliminary material balance predicts a first estimate of: •

The circulating load in the grinding circuit,















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circulating load in the grinding circuit is 204%;

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d80 of the cyclone underflow is 75µm

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gold recovery is over 95% (635.6/665)

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addition of water is 35.7 m3/h (53.7+50.1-68.1). Recycling 210 t/h of water to the hydrocyclones (with splitter 9) will optimize water addition.















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4.5 - Step three: design the units of equipment Select Level 1 or Level 2 unit operation models

Target.UP3 file needs to be saved as Design1.UP3. Then, the Equipment Description option is used to replace the Level-0 models with Level-1 or Level-2 predictive models, and to specify some characteristics of the equipment (see Table 2).

Table 2 Level 1 and 2 models Units

Models and main parameters

#3 – Rod mill

Rod Mill (1)

????

Values

Number of mills in parallel

1

Inside mill diameter (m)

2.7

Length/diameter ratio

2

Percent volumetric loading of rods

35

Fraction of critical speed

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#11 – Ball mill

????

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Ball Mill (1) Number of mills in parallel

1

Inside mill diameter (m)

3.8

Length/diameter ratio

1.2

Percent volumetric loading of balls

40

Fraction of critical speed

0.7

Ball specific gravity

7.8

Work index per component (kWh/st)

14

Parameters preceded by ???? are calculated by the unit sizing algorithm. The associated value is the result. The Rod Mill (1) and Ball Mill (1) models are based on the energy-based theories of grinding and in particular on Bond’s law and the Allis Chalmers methods for dimensioning grinding mills (Rowland and Kjos, 1978). The choice was made to use one rod mill and one ball mill with predefined conditions such as mill shape, grinding media loading and speed. Only the diameter will be calculated to fit the target size distribution.

















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At the end of this step, it is recommended to verify the consistency of the results of the simulation again using the Results and Graphs menu. Figure 22 shows a comparison between the objective and the simulated values for the Gold partial flowrates. Figure 23 shows a comparison of the targeted partition curve and the simulated one.















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A table in which various ratios are applied to this purchase cost to provide a budgetary breakdown of the total plant investment.















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REFERENCES Brochot, S., Wiegel, R.L., Ersayin, S., Touze, S., "Modeling and Simulation of Comminution Circuits with USIM PAC", 2006, Advances in Comminution, Ed. S.K. Kawatra, SME, pp 495-511. Brochot, S., Durance, M.-V., Villeneuve, J., Mugabi, M., "Modelling of the bioleaching of sulphide ores: application for the simulation of the bioleaching / gravity section of the Kasese Cobalt Company Ltd process plant", 2003, Processing & Disposal of Mineral Industry Wastes '03 conference, Falmouth, UK, June 18-20.

















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Guillaneau, J.-C., Morin, D., Durance, M.-V., Morizot, G., “Biotechnology and process simulation: two















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Villeneuve, J., Durance, M. V., Guillaneau, J. -C., Santana, A. N., Silva, R. V. G., Martin, M. A. S.,















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Mineral Processing Symposium, September, Cappadocia, Turkey, A. A. Balkema, pp. 539-547.















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Villeneuve, J., Guillaneau, J.-C., Pilotte, R., Broussaud, A., 1992, "Objective Driven Simulation: a new















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Broussaud, A., Fourniguet, G., Guillaneau, J.-C., Conil, P., Guyot, O., 1990, "Conception assistée par















USIM PAC 31 Starting Guide

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