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By F. Reyes, M. Hilden, G. Forbes, M. Yahyaei

Since AlphaGo defeated the best human player in the game of Go in 2016 - something thought to be an impossible achievement - machine learning, deep learning and reinforcement learning have caught the attention of scientists, the media and the general public alike. This recent development in machine learning (let us remember that neural networks have been available for decades now) opens new possibilities in the areas of modelling and process control. However, little has been reported in the minerals processing industry about these new possibilities and opportunities. This paper presents and introduces the topic of reinforcement learning and the different platforms that allow its implementation. The paper shows the consequences of using reinforcement learning for the specific area of process control and optimisation. As an example, the authors present the use of reinforcement learning for the control of a SAG mill closed with a pebble crusher using industrial data from an operation. A comparison with advanced model-based process control is provided, showing the benefits and shortcomings of reinforcement learning as a new control and optimisation technique. Keywords: Reinforcement learning, deep learning, process control, process optimisation

Jan 1, 2020

By S. K. Murphy

A partial shaft pillar extraction project was embarked on at a mine in the West Wits mining region in South Africa. Prior to the extraction, a rock engineering assessment was conducted with the main objective being to establish which areas of the shaft pillar could be extracted without unduly affecting the stability of major infrastructure within the shaft pillar. Standard numerical modelling methods were used to conduct this assessment and several areas were identified for extraction. However, during the extraction process, it was found that the infrastructure was affected more than was originally predicted by linear elastic modelling. In addition to this, several large events resulted in far more large aftershocks than would normally be predicted. In order to gain an understanding of this phenomenon, seismic data was integrated with numerical modelling as follows: > The seismic data in the form of displacements was integrated in 3D space within the model to assess the effect of static stress changes associated with seismic activity > Data from large events was integrated onto specific structures, where displacements associated with large events were integrated onto the plane of structure in question. This paper describes the methodology and results obtained from each of the above processes and include insights into the mining process that were previously unfathomable using standard linear elastic numerical modelling. The way forward for this rock engineering assessment of partial shaft pillar extraction is also discussed.

Jan 1, 2012

By I. Fedotov

One of the most effective methods of metal surface heat treatment is through laser hardening. In most cases, laser parameters are determined experimentally, which is expensive and time-consuming. A mathematical model for the surface heat treatment process will allow a significant decrease in costs, and reduce the time required for optimization. In the present work, the authors present a mathematical model for laser heat treatment with forced cooling which can be applied to medium carbon steel. The model is based on a three-dimensional heat transfer equation using Green?s function. The model allows one to calculate the temperature of the treated steel at different depths below the surface with and without cooling, for set values of the laser power and travelling speed, when the heat transfer coefficient is a known constant. It also takes variations in the radiation adsorption coefficient on the metal surface and laser beam spot size into account. The model was illustrated by comparing calculated and experimental temperature profiles of mild carbon steel with 0.5% C with and without cooling. A reasonably good agreement was achieved between experimental and predicted values to ensure that a high enough austenizing temperature with short enough cooling time was reached for direct martensite formation. It also predicted the depth of treatment accurately. The incorporation of cooling in the model substantially improves previous models based on heat transfer only. It delivers a tool that can with a reasonable accuracy predict the depth of surface heat treatment and cooling time required from operational parameters, such as laser power, speed of motion, and distance between laser and cooling source, that can be controlled in the work set-up. This can eliminate trial and error efforts and result insignificant time and cost savings. Keywords Laser, surface treatment, martensite transformation, carbon steel, heat treatment.

Jan 1, 2011

By J. W. van der Merwe, A. M. Maleka, V. J. Matjeke

The 10.5–12.5% chromium, titanium-stabilized ferritic stainless steel (FSS) plates used to fabricate coal line jumbo wagons is susceptible to undesirable chromium depletion during welding with 309L electrodes. In this work, non-stabilized FSS plates were welded using 308L welding electrodes. The objective was to weld non-stabilized FSSs using gas-shielded metal arc welding without causing sensitization. The welding process was optimized by lowering the heat input. Sensitization was assessed by rigorous etching techniques and anodic polarization scans. In addition, the welds were subjected to tensile testing, and their fracture surfaces were examined for intergranular cracking. Non-stabilized FSS plates were successfully welded using gas metal arc welding.

Apr 5, 2023

By N. C. Joughin

A simplified economic model is derived for the financial return from a new gold mining project. The model is used to analyze the effects of changes in the mining rate, capital costs, working costs, value of the reef and the stoping width. The most effective avenues for improving the return from a new project are indicated. It is shown that those technological innovations which would improve the return significantly, and therefore make it possible to open more mines, are the use of smaller mines, means for improving the mining rate to capital costs ratio for smaller mines, planning and control of mines by computer simulation, an improved mine valuation procedure and means for mining at a decreased stope tramming width.

Jan 1, 2014

By M. S. Shishvan, J. Sattarvand, R. S. H. Meij

Navigating miners during an evacuation using a smart evacuation technology can significantly decrease the evacuation time of an underground mine in case of an emergency. This paper presents a mathematical programming model to calculate the most efficient escape path for each miner as a critical component of the smart evacuation technology. In this model, the total evacuation distance of the crew is minimised and scenarios with blocked pathways, and stamina categories for the miners are simulated. It was found that all the tested scenarios are technically feasible. Using the feature that filters out blocked pathways has no downsides, as safer routes are calculated, and there is no penalty in the computation time. The paper also discusses the social and technical issues that need to be overcome before the algorithm can be implemented as an actual escape solution.

Sep 1, 2021

By Brian Wyatt, Neil Webb, Marcel Roche, John Thirkettle

Recent developments in survey techniques and measuring equipment now allow for an accurate assessment of external coating condition and cathodic protection performance. These developments build on 20 years of experience of using Direct Current Voltage Gradient (DCVG) and Close Interval Potential Survey (CIPS) methods. The techniques use the latest advances in measurement systems coupled to a bespoke data processing system. The paper describes tests and trial surveys carried out on a hydrocarbon transmission pipeline in West Africa during 2005. The survey works described and conclusions drawn are from the data collected. Of particular interest are the apparent capacitance effects which are thought to occur under disbonded coating and the characteristics that these may show on the integrated CIPS and recorded DCVG profiles. This paper was originally presented at the Cefracor conference in Aix, France, in June 2006 The pipeline was originally installed on a phased basis between 1989 and 1994. The external coatings were three layer polyethylene factory coating and shrink sleeve field joint coating. An impressed current cathodic protection system was installed. The pipeline has subsequently been affected by disbondment of the coatings. It was a primary objective of the trials to attempt to identify such affected areas. In addition to a technically detailed account of the survey works undertaken and the results obtained the authors will consider the practical and commercial aspects of these surveys with input that provides a perspective from the specifier, pipeline surveyor, pipeline operations personnel and the pipeline owner. It is intended that the data presented will provide greater awareness of the benefits and limitations of the techniques used and their role for both stand-alone interpretation and the integration of the survey information with other inspection methods used for external corrosion assessment. The application of the described techniques is well developed and proven to locate and characterise through?coating defects and to provide a full audit of cathodic protection status. However, the possibility of the techniques being able to indicate disbonded coating is unproven and further tests and trials are planned which may allow a greater understanding of the electrical characteristics which are believed to be associated with disbonded coatings which may or may not be filled with an electrolyte. Further work is currently planned in West Africa, South Africa and Scotland in order to improve the understanding of this technique and to determine if the reported indications do actually represent a method of locating disbonded coatings. Keywords: External Coating, Cathodic Protection, DCVG, CIPS, corrosion assessment.

Jan 1, 2006

By A. O. Filmer

In the mining and metals industry, business strategy demands that leaders extract more from any set of capital assets. This improvement is achieved through a combination of continuous improvement and upgrading of the assets. Continuous Improvement involves a series of incremental changes in the workplace to stabilize the process, remove waste, and test the limits of process capability. Enhanced Technology involves the replacement of an existing as set with a different process or equipment, to achieve a similar function in a more efficient and effective manner. The paper compares and contrasts the two methodologies and outlines the key business considerations which dictate how and when to select one or other improvement method. The paper also addresses the implications for these two improvement methods for those undertaking R&D in support of the mining and metals business.

Jan 1, 2009

By А. V. Aksenov, S. G. Rybkin, А. Y. Senchenko

Recovered activated carbon fines result from processing of ore and concentrates via cyanide leaching and sorption of valuable metals on carbon at gold-mining plants. This intermediate product is characterised by the particles sized smaller than 0.6 mm and gold grade up to 300-500 g/t. Processing of carbon fines with recovery of valuable metals is not available at many plants due to the lack of optimal technology. The paper describes the testwork and development of an efficient technology to process carbon fines with the recovery of valuable metals into the target gold alloy. This innovative technology involves pelletising of fine activated carbon particles using an organic binder, drying and further firing of pellets in a grate fired furnace at 800-900 °С. The produced ash is subject to sintering with sodium nitrate and hydroxide at 600-700°С. The sintered ash is then leached in water. The insoluble residue containing gold and silver is removed by filtration, dried and smelted to produce gold alloy. Water solution containing sulphur and arsenic is subject to detoxification. Processing of recovered carbon fines according to the developed technology implies the use of standard full-scale equipment. The offered method to treat gold-bearing carbon fines was patented by the Eurasian Patent Office. Key words: Fine activated carbon particles, valuable metals, pelletizing, firing, ash, sintering, leaching, smelting

Jan 1, 2020

By D. Marcotte, R. V. Dutaut

"In mineral resource evaluations, geostatistical methods known as global change of support allow prediction of the theoretical histogram and gradetonnage curves prior to interpolations or simulations of grades. Two methods commonly used by professionals to guide the choice of interpolation parameters and assess results are the discrete Gaussian model (DGM) and the indirect lognormal correction (IndLog). These models rely upon an estimate of the dispersion variance of the blocks, which is derived by numerical integration of the variogram model over a discretized block. Due to difficulties in obtaining well-formed traditional experimental variograms (especially in the presence of outliers and limited clustered data), many professionals prefer to use ‘normalized’ variograms such as correlogram (non-ergodic variogram), pairwise-relative, or variogram of the normal score transform. A series of simulations with different grade distributions and variogram models are used to assess the performances and robustness of the various variogram estimators with respect to the DGM and IndLog global change of support. Our results show that the traditional variogram, the correlogram, and normal score variogram have better performances, compared to pairwise, for both DGM and IndLog. Moreover, DGM provided better results than IndLog for the grade distributions that are not strictly lognormal. These findings provide valuable guides for geostatistics practitioners. IntroductionWhen reporting resource estimates,practitioners are required to follow generalstandards described in the NI43-101 (CIMguidelines), JORC, or SAMREC codes. One cangenerally recognize three main parts directlyrelated to the block model:•,Pre-processing: exploratory data analysis (EDA), domaining, capping, compositing, declustering, variography•,Processing: block size, neighbourhood, interpolation types (linear or nonlinear)•,Post-processing: classification, reporting.Pre-processing aims to simplify and strengthen the processing step. Ideally, domaining, capping. and compositing is aimed at defining a single homogenous population. During the processing phase, a common practice is to use a block size corresponding to the planned selective mining unit (SMU). In most precious metal deposits (gold, notably), the SMU size is frequently smaller than the recommended half data spacing (Journel and Huijbregts 1978), resulting in high estimation variance and either a high degree of smoothing if the regression slope is managed or a high degree of conditional bias if it is not. Most actual resource estimates are made using block sizes between one-quarter to one-sixth of the average data spacing, sometimes even smaller. In addition to the block size, the interpolation choices for the neighbourhood selection and interpolator (e.g. inverse distance (ID) or ordinary kriging) are often based on the Qualified Person’s (the QP) experience and some basic validation plots that often do not consider the conditional bias (e.g. trends or SWATHs plots, which are designed to compare two sets of population using a one-dimensional graph)."

Jan 1, 2018

By M. Frenzel, K. Bachmann, M. Rudolph, R. Tolosana-Delgado, E. Schach, M. Buchmann, L. Pereiraa, K. G. van den Boogaart, N. Kupka

Geometallurgy - the science of predicting the behaviour of ores along the value chain based on their geological and mineralogical characteristics - has barely moved beyond process minerology studies. These studies typically link process behaviour to the mineralogical and microstructural characteristics of pristine or processed ores in a qualitative or semi-quantitative manner. Eventually, a trial-and-error optimisation of the operation is achieved. However, to deliver on its promise, geometallurgy should progress beyond this current approach to a fully quantitative understanding of process behaviour, including the various uncertainties involved, namely predictive geometallurgy. One of the barriers currently hindering this development is the neglect of most ore characterisation data obtained in geometallurgical studies. This is mostly due to the large extent of this information exceeding the capacity of conventional software. To address this challenge, we developed a data mining platform consisting of an SQL database, an R front-end in-house package, and back-ends to interpret data from several analytical instruments. This platform enables the use of the statistical and data mining power of the R open-source environment for any geometallurgical study. Potential applications range from ore characterisation to process understanding and forecasting, and from geostatistical prediction to operational control and optimisation. The scripting abilities of R allow for the: 1) processing of many streams in loops, thus freeing the user from repeating tedious click-and-drop tasks; 2) computation of virtually any derivate or aggregate quantity from the data; 3) distribution of the work among several processor clusters; and 4) keeping of a log file for the calculations done. This contribution presents the building blocks of this platform, and illustrates with several examples its potential to enable predictive geometallurgy. Keywords: Data mining, entropy, kernel methods, LASSO regression, predictive geometallurgy

Jan 1, 2020

By A. R. Javadi

Pyrite (FeS2), chalcopyrite (CuFeS2), sphalerite (ZnS) and galena (PbS) generate hydrogen peroxide (H2O2) when placed in water, with pyrite generating the most amount of H2O2. The order of these minerals for generating H2O2 in water is: pyrite > chalcopyrite > sphalerite > galena. In previous research, the methods of generation of H2O2 in the grinding mill were studied. In this study, data from experiments were included by using MODDE 9 software for six parameters composed of water, grinding media, particle size; adding collector to the grinding, and adding depressant and pH. Finally the optimal condition was achieved. According to the results, most of the recovery is related to the particle 75 μ size and when using processed water, adding 100% collector and without depressant and pH 10. The most recovery of lead in the case of the use of fresh water is in the case of 100% collector, without depressant, pH 10 and 150 μ particle size. Maximum recovery in fraction size 45 μ in the case of water process is 100% collector, without depressant and pH 10. Maximum depressant of pyrite will be the fraction size 75 μ, distilled water, without collector, 100 depressant. Keywords: Sulfide mineral, hydrogen peroxide, flotation, oxidation

Jan 1, 2020

By E. Moosavi, K. Tolouei

In mine production scheduling problems are well-known, where most are categorised into deterministic and non-deterministic NP-hard problems because of their complexity. Many researchers have attempted to solve the problem by applying various optimisation techniques. While using traditional methods they observed extreme difficulty in solving highly complex problems. In the 1990s, many researchers addressed long-term production scheduling (LTPS) by using simulated annealing, the genetic algorithm, the tabu search algorithm, and the ant colony algorithm. These algorithms are known as the meta-heuristic algorithms, and have proved to be the most efficient algorithms for solving LTPS thus far. The firefly algorithm is one of the best methods for visualising problems related to LTPS, and provides the best possible optimisation. It is one of the simplest methods, and easy to apply to any NP-hard problem. The experimental, and comparison with other recently published algorithms shows that the proposed algorithm is feasible, and is an effective approach for long-term production scheduling problems. The results indicated that a better solution is obtained by the proposed method, compared to other methods in terms of cumulative net present value, and average ore grade. Additionally, the CPU time via the proposed model is roughly 2.52% higher than the other method.

Sep 1, 2021

By V. Yahorava

Resin-in-pulp (RIP) technology has recently often been considered for the direct recovery of base metals and uranium from dense pulps. Implementation of RIP will eliminate the requirement for any solid-liquid separation downstream of leaching and has the potential to combine the recovery and purification steps, hence reducing both capital and operating costs. The recovery of the valuable metal is expected to be higher when RIP is used, especially where the leached solids are difficult to settle or filter, and to wash. The main concerns about the use of RIP for uranium recovery from dense pulps are the impact of silica on the resin?s metallurgical performance and the operating costs that would be associated with resin loss. Although a number of resin manufacturers have been developing much improved RIP-grade resins, it is critical that the most cost-effective resin be selected. Mintek currently is doing a significant amount of work on silica fouling of RIP-grade strong-base resins in acidic leach liquors and the effect it has on the performance of the resin, including its durability. This paper describes the results of the test work done on silica fouling and its impact on plant design input data. Resin durability test work was done using various laboratory techniques, but durability was also evaluated on a relatively large scale using actual pumps, screens, and mechanical agitation. Based on the results generated, a preliminary economical evaluation was done to estimate the impact of resin loss on the overall economic viability of a specific application. Keywords: resin-in-pulp, silica fouling, resin loss, equilibrium, kinetics, elution, durability, mechanical strength, resistance to attrition.

Jan 1, 2009

By S. Liaghat, J. Rosenkranz, P. Semsari Parapari, S. Chehreh Chelgani, A. Tohry

It is commonly accepted that the energy consumption for comminution within mineral processing is responsible for around 3% of the global electrical energy usage. However, it was clearly noted that inside mills, less than 1% of this energy efficiency is actually consumed for particle size reduction. Therefore, monitoring of grinding parameters and modelling of product particle size distribution (e.g. characterised by the 80% passing size P80) play an essential role in operating costs of a mineral processing plant. Several empirical models have been introduced for the prediction of the P80. Since in the industrial scale usually a few numbers of grinding variables are monitored, these models cannot identically be used in plants. In addition, these empirical models do not always indicate the magnitude of correlations between milling variables. This study proposes to introduce the Hilbert-Schmidt independence criterion (HSIC) as an intelligent model for exploring linear and nonlinear relationships between grinding variables and P80 for an industrial scale data assessment. HSIC can rank variables based on their importance and help to select the most effective one for the generation of predictive models. HSIC modelling through various monitored grinding variables (ball charge, feed input rate, F80, power draw and work index) of an industrial plant indicated that F80 as a feed property has the highest effect on P80 of the ball mill products. Modelling results highlighted that the P80 can be accurately predicted, based on effective variables by using a HSIC model. These outcomes showed that HSIC as a powerful modelling tool can assess the relationships between monitored grinding parameters, select the most effective grinding parameters and satisfactorily predict the P80. Keywords: Product particle size, variable importance measurement, Hilbert-Schmidt independence criterion, mill charge

Jan 1, 2020

By E. C. de Beer

"SynopsisA number of important areas in nuclear fuel cycle, at both the front end and back end, offer ideal opportunities for the application of non-destructive evaluation techniques. These techniques do not only provide opportunities for non-invasive testing of e.g. irradiated materials, but also play an important role in the development of new materials in the nuclear sector. The advantage of penetrating radiation used as probe in the investigation and testing of nuclear materials makes X-ray and neutron radiography (2D) and tomography (3D) suitable for various applications in the total nuclear fuel cycle. The unique and different interaction modes of the two radiation probes with materials provide several opportunities. Their complementary nature and non-destructive character makes them most suitable for nuclear material analyses, analytical method development, and the evaluation of the performance of existing nuclear material compositions. This article gives an overview of the X-ray and neutron radiography/tomography applications in the field of nuclear material testing, and highlights a few of the success stories. Several selected areas of application in the nuclear fuel cycle are discussed to illustrate the complementary nature of these techniques as applied to nuclear materials.IntroductionDuring the development of new materials for the nuclear industry, materials testing and characterization are of the outmost importance to maintain safety standards and reliability. No compromise on safety in the workplace in any area within the total nuclear fuel cycle can be tolerated, and therefore most in-situ material characterization and testing is conducted by certified and qualified personnel schooled in destructive and non-destructive testing (DT and NDT) methods. Certification and qualification in NDT can be obtained through many training centres in South Africa in accordance with European, American, and other international standards (SGS, n.d.; SAIW, n.d.; African NTD Centre, n.d.)."

Jan 1, 2015

By K. Böde

Hochtief AG Germany has developed a comprehensive management and information system for the construction industry named Aristoteles. This system is an efficient supporting tool to manage a variety of construction sites as well as operating business units with required economic targets. As such, Aristoteles offers wide-ranging control of complex economic processes in construction in a consistent manner. In this paper the process oriented functions of the system will be described with special emphasis on finance accounting and cost control. The basic elements in this respect are tender estimation, creation of initial project budgets and running budgets, regular determination of work done and result forecast to the end of the project. Further, cost accounting, monthly reporting, and all balance-related postings are included. On the basis of the extensive reporting (targeted/actual cost comparison, cost manager, project report, actual/targeted hours worked comparison, overhead cost report, amendment report or project (result) lists of all projects realized by one business unit), the responsible managers can make justified project evaluations, project controls and variance analyses during the project period and derive appropriate management measures. Thus, Aristoteles includes all substantial elements for the risk management of the operational business. In big construction joint-stock companies it is of crucial importance to satisfy the information requirements of the investors. In this respect the system provides a transparent presentation of the financial, investment and profitability situation of the company. In the international construction industry the balancing rules according to IAS (International Accounting Standards) have already been used to a larger extent. In accordance with these rules the partial profits of the work during execution can be shown as realized even before completion of a long-term contract. The validity of Aristoteles will be outlined briefly. Major advantages using the system are highly enhanced accuracy of project controlling, systematic overhead allocation to projects, change of attitude of the project personnel due to increased cost consciousness and improved flow of information within the company.

Jan 1, 2003

By M. Asghari, R. Amiri, A. Haratian, M. Noue Parast, S. Haji

Today the roller screen has a wide range of applications in the steel-making industry. It is used for screening of green pellets before using the kiln. Since the appropriate size of a green pellet is -16+9 mm, there are different gaps between rollers that make green pellets classified in three categories: -9 mm (undersize), -16+9 mm (onsize) and +16mm (oversize). The efficiency of a roller screen is specified according to the weight percent of undersize in onsize as a fine material, and weight percent of onsize in oversize (loss). This efficiency is influenced by different operational parameters such as roller diameter, roller speed, and roller gap, material type of rollers and inclination of roller screen. This study investigates the effect of different material types of rollers in efficiency of Ardakan roller screens, located in the Yazd province of Iran. The rollers of the existing roller screens in this pelletising plant are made of polyurethane which according to this investigation, has a maximum lifetime of about six months. Operating the polyurethane rollers beyond its lifetime generates serious problems such as high wear of rollers, and consequently, material buildup on the roller surface which then significantly decreases the roller screen efficiency. So, after examining different roller materials, stainless steel 304 with higher surface roughness to help pellets move properly on the roller screen surface was selected as a solution to this problem. The new roller screen was constructed by Fakoor Meghnatis Spadana (FMS) and replaced the previous one. In this way, the maximum capacity of the roller screen was increased about 17% and the roller screen efficiency was increased about 15%. Keywords: Roller screen, green pellets, efficiency, onsize, operational parameters

Jan 1, 2020

By L. Cheng, Y. Liu, Z. Shen, H. Shang, Y. Li

The pre-concentration process of magnetic coarse particles can discharge waste rock or liberated gangue before milling, which is an effective means to reduce cost and increase the efficiency of the concentrator, but the weakly magnetic ore doesn’t have the effective separation method of coarse particle such as hematite, limonite, ilmenite and so on, Because the composite iron minerals contain both strong and weak magnetic elements, the pre-concentration process cannot be applied, or the existing pre-concentration process has problems of complicated configuration and high operation cost. By researching a new type of external magnetic separation technology, the pre-concentration process of composite iron ore was realised by single equipment, which can have a good recovery rate with simple arrangement. In this paper, the separation principle and structure characteristics of the external magnetic separator were researched, and the magnetic circuit characteristics of the external magnet were analysed. The laboratory tests of vanadium titanium magnetite were conducted, and the test results proved that the external magnetic separator can be applied for the pre-concentration process. The industrial application shows that a product of TFe 24.76% with 90.08% recovery, TiO2 10.10% with 91.78% recovery can be achieved from the feed of TFe 20.67%, TiO2 8.33%. Keywords: Coarse particle pre-concentration, composite iron ore, external magnet, magnetic separator

Jan 1, 2020

By N. Naudé, J. de Villiers, C. P. Bergmann

It is proposed that the physical and chemical composition of individual mineral particles are an appropriate basis from which to model the performance of minerals processing equipment. Such a particle-based approach enables modelling across disciplines such as comminution, classification and flotation and automatically generates the traditional mass and chemistry balances. The general approach followed is to generate full grade-recovery curves for a separator by sampling product and tailings at varying mass yields. AutoSEM characterisation of each sample provides particle data that is used to reconcile mineral deportment and liberation to the measured size and assay data. In this way, partition surfaces can be generated and modelled. In this paper, an empirical model for the performance of a gravity spiral concentrator treating fine chromite ore is proposed. The model is based on the combination of two partition surfaces and is able to accommodate both forward and reverse gravity concentration effects per size fraction. The results show that this approach is well suited to represent spiral performance for the cases evaluated. The effect of two feed particle size distributions on the performance of the Multotec SC21 and SC25 spirals is demonstrated. Simulations are run in an Excel environment, linked to Python-enabled routines for enhanced data management and calculation speed. Keywords: Spiral concentrator, gravity separation, particle-based modelling

Jan 1, 2020