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By G-L. Wu, S-W. Wu

"The hot deformation behaviour of Nb-Ti microalloyed high-strength steel was investigated. Hot compression tests were conducted in the temperature range 900 to 1100°C under strain rates of 0.1, 1, and 5 s-1. Dynamic recrystallization (DRX) occurs as the main flow softening mechanism at high temperature and low strain rate. The hot deformation activation energy was calculated to be about 404 699 J/mol. The constitutive equation was developed to describe the relationship between peak stress, strain rate, and deformation temperature. The characteristics of DRX at different deformation conditions were extracted from the stressstrain curves using the work hardening parameter. The Cingara-McQueen equation was developed to predict the flow curves up to the peak strain. The processing maps were obtained on the basis of a dynamic materials model. The results predict an instability region in the temperature range 1010 to 1100°C when the strain rate exceeds 0.78 s-1. IntroductionThe 700 MPa grade HSLA steel is widely used in engineering machinery, automotive beams, carriages, and axle tubes, etc. (Pan et al., 2017 ). Generally, such grades contain a moderately high amount of Mn (approx. 1.4% and above), and microalloying elements like Nb, Ti, V, and Mo to impart the desired strength and toughness through solid-solution strengthening, precipitation hardening, and grain refinement dislocation strengthening (Chen and Yu, 2012; Opiela, 2014). However, the production costs can be greatly reduced by replacing part of the Nb, V, or Mo with inexpensive Ti and adopting the compact strip production CSP process (Opiela, 2014; Chen et al., 2015). Furthermore, the microalloying technology coupled with new-generation thermomechanical control processing (NG-TMCP) has proved efficient for achieving the proper balance between strength, toughness, ductility, and formability by means of a suitable combination of chemical composition and thermomechanical treatment parameters (Shukla et al., 2012; Wu, Zhou, and Liu, 2017).In hot forming processes, the complex microstructural evolutions are often induced by multiplicative hot deformation mechanisms, such as work hardening (WH), dynamic recovery (DRV), and dynamic recrystallization (DRX) (Zhang et al., 2014; Liang et al., 2015). Dynamic softening behaviour during hot processing has generated considerable interest because component properties are influenced significantly by its corresponding microstructural evolution (Wu et al., 2010). During deformation in the DRX process, deformed grains are replaced with substructures and newly formed fine and uniformly distributed grains. This occurs only when a critical strain for the onset of DRX is reached, and at the same time, the minimum rate of energy dissipating is reached (Ferdowsi et al., 2014). DRV occurs at a high strain rate and low temperature, reducing the stored energy greatly and making DRX difficult (Liang et al., 2015). The microstructural changes during DRX are sensitive to the processing parameters, such as strain rate, deformation temperature, and strain (Zhang et al., 2014; Ferdowsi et al., 2014). Therefore, in order to optimize the hot processing parameters, it is important to understand the behaviour of hot deformation visà- vis control of microstructural evolution."

May 1, 2019

By B. Mbuya, A. F. Mulaba-Bafubianda, J. M. Mvita

The paper explains the main effects of input leaching parameters, such as addition of a reducing agent, acidity, agitation, temperature, and leaching system potential, in relation to observed and predicted yields of sought-after cobalt. An artificial neural network coupled with graphical probability networks was developed wherein the abovementioned input parameters were used to predict the percentage of dissolved cobalt. Furthermore, similarities and differences between the Bayesian and neural network approaches in terms of their key outcomes are compared with respect to study of the dissolution of cobalt in sulfuric acid. Key results indicate that there is a need to use neural network results to predict conditions for dissolution of cobalt, while using Bayesian network to explain inferences about conditions of the input parameters, thereby achieving realistic predictions.

Jan 1, 2023

By M. Z. Emad, A. Khan, N. Abbas, K. G. Li

Probability-based empirical methods were employed as an alternative approach to predicting uncertainties associated with rock mass properties. The focus was on developing probabilistic spreadsheets to forecast rock mass classification indexes. Histograms were constructed to describe the best distribution in predicting rock mass properties. The developed models also offer utility in predicting the impact of discontinuities within the rock mass on rock strength and rock mass classification systems. Statistical analyses identified volumetric joint count, joint spacing, joint frequency, and rock strength as the most influential parameters. Moreover, the statistical analysis revealed varying degrees of correlation among different rock mass properties. While some properties demonstrated significant correlations suitable for modelling, others did not align well with any correlation model. The results highlight the need for a comprehensive approach to rock mass characterization, considering multiple factors beyond volumetric joint count. Geological complexities, including tectonic activity and weathering processes, may obscure direct correlations. These results emphasize the importance of empirical modelling and detailed site investigations for accurate assessment of rock mass quality and stability in the Himalaya.

Jun 10, 2024

By S. Krishnannair

Singular Spectrum Analysis (SSA) is an effective data-adaptive multimodal tool for monitoring chemical processes. However, monitoring multiscale signals using principal component analysis obtained from the multilevel decomposition of process signals using basic SSA assume the upper control limits of monitoring charts (" ) to have a Gaussian distribution. This assumption deteriorates the performance of basic SSA when applied to the monitoring of nonlinear processes. To address the issue in this paper, the kernel density estimation (KDE) was used to estimate upper control limits of monitoring charts for basic SSA based nonlinear process monitoring techniques. The monitoring performance of the resulting basic SSA-KDE approach was then compared with a basic SSA approach of which upper control limits of the monitoring charts were determined based on a Gaussian distribution. Application on nonlinear dynamic simulated process and base metal flotation plant chemical processes showed that the SSA-KDE approach provided better overall performance than the SSA approach with Gaussian assumption-based upper control limits for its monitoring charts. Keywords: Fault detection, singular value decomposition, singular spectrum analysis, kernel density estimation

Jan 1, 2020

By T. Nghipulile, M. Moys, M. Bwalya, H. Simonsen

The quest for efficiency in comminution is an ongoing concern as comminution usually constitutes a major cost component in the metal production industry. Such improvements can be made by circuit optimization or development of more efficient equipment. A novel crusher, known as the rotary offset crusher (ROC), promises to deliver in this space. The ROC was invented in 2002 by Michael Hunt, Henry Simonsen, and Ian Sinclair, but failed to garner enough support to progress to production. The original design concept was recently rekindled, and a laboratory version of the crusher has been built and commissioned at the University of the Witwatersrand. The crusher is simple in design, with two cylindrical discs that are parallel to each other, and, as the name implies, there is an offset between the vertical axes of the discs. The top disc has a conical section on its lower face, and this creates a crushing zone between the opposite faces of the two spinning discs. Centrifugal motion transports particles through the crushing zone. Batch experiments have been conducted with quartz at various crusher settings (discs offset, rotational speed, and vertical exit gap) for various feed size distributions. The indications so far suggest that the disc speed is a key factor affecting the performance. Size reduction ratios as high as 11 were recorded from experiments with quartz at a speed of 830 r/min.

Jan 1, 2021

Dr c. J. Fauconnier, Pr. Eng., has a D. Eng. from the University of Pretoria, an M.RA. from the University of Oregon, and an M.Sc. (Eng.) and B.8c. (Min. Eng.) from the University of Pretoria. Dr B. K. Loveday obtained a degree in Chemical Engineering at the University of Natal, where he also obtained a Ph.D. in the kinetics of froth flotation.

Jan 1, 1983

By M. Khodadazadeh, K. G. van den Boogaart, T. Leißner, L. Tusa, J. Gutzmer, R. Gloaguen, M. Kern

Ore sorting is a technology that is increasingly used to process primary raw materials. Timeconsuming and expensive empirical state-of-the-art test work is carried out to assess whether the use of ore sorting for the enrichment of a particular ore makes technical and economic sense. With the innovative simulation-based approach presented here, it is possible to direct the selection of a suitable sensor based on quantitative mineralogical and textural data, thus avoiding much of the empirical studies. Required data can be collected quickly and cost-effectively using available methods of automated mineralogy. The obtained parameters such as mineral grain size distribution, modal mineralogy, mineral area and mineral density distribution have been utilised in this study to simulate the prospects of success of ore sorting, applying different types of sensors. Empirical tests with commercially available sensor systems have been conducted to experimentally validate the predictions of the simulations. The estimation of the target mineral grade can be further optimised by the use of machine learning algorithms for the integration of automated mineralogy data and sensor data. The approach can easily be adapted to other types of raw materials and thus has great potential to become a key technology for the optimisation of processing experiments. Keywords: Automated mineralogy, hyperspectral imaging, machine learning, ore sorting

Jan 1, 2020

By N. Naude, R. Foisy, F. Bornman

Spiral separators have been widely accepted as one of the most flexible gravity separation devices for several decades. The International Journal of Mineral Processing, 84, pp. 118 – 132 mentioned that spirals are for treating material too coarse for flotation and too fine for dense-media separation. Powder Technology V 102, pp 244 – 252, 1999 stated that there exists a genuine need for extending the performance envelope of spirals – whether to treat finer or coarser material than the traditional size ranges. In recent times there has been an upsurge in interest, particularly in the development of newer fine gravity separators. Spiral separators for the recovery of ultra-fine particles have a unique profile, pitch and features to ensure efficient performance. The flow on the spiral trough must be controlled to minimise turbulence that will entrain fine particles in the outer section of the trough. The experimental test work showed a movement of mass from the outer region towards the centre column of the spiral, i.e., from the fine tailings band towards the concentrate. As recovery on the spiral trough is a function of mass yield and grade, the ultra-fine 7 spiral had a better recovery than the HX5. This makes the UF7 an ideal rougher spiral. Keywords: Ultra-fine particles, spiral, design, recovery

Jan 1, 2020

By S. Kirkpatrick, J. Mukendwa

"The mining operation at Namdeb’s Southern Coastal Mine (SCM) is unique. It targets gravel layers up to 30 m below sea level, which continue to dip deeper, further west, under the Atlantic Ocean. On this storm-dominated coastline, severe water seepage into mining areas, rugged orebody footwall characteristics, and highly variable resource grades all contribute to a challenging operational environment. Namdeb has a proud history of innovation, and as the mine progresses further westwards and associated technical and economic challenges increase, this innovative culture has become essential to the future of the mine. The Theory of Constraints (ToC) has been widely used at SCM, and across the mining discipline, to focus efforts on improving overall business profitability. Through analysis of the mining processes, opportunities were identified, solutions developed, and initiatives implemented with staggering results across all three mining disciplines, i.e. stripping, load and haul, and bedrock bulking and cleaning. This paper outlines the solutions adopted and the results of the ToC analysis. IntroductionSouthern Coastal Mine (SCM) is one of three Namdeb operations located in the southwestern corner of Namibia, between the Orange River in the south, the Namib Desert to the east and the Atlantic Ocean to the west (Figure 1). These three geographical features set the backdrop for the world’s greatest marine diamond mining placer (Badenhorst, 2003). SCM is situated along the coastline extending from the mouth of the Orange River to Chameis Bay approximately 120 km to the north. The active mining area, called Mining Area 1 (MA1) is, however, limited to very narrow strip, 30 km in length, in the south of the licence area, close to the town of Oranjemund.Namdeb, a wholly owned subsidiary of Namdeb Holdings, is a 50/50 joint venture between De Beers and the Government of Namibia. Diamonds were first discovered along the Namibian coastline in April 1908, close to the town of Luderitz, but mining operations started in the SCM mining area only in February 1929 (Schneider, 2009). Initially all Namdeb mining operations exploited massive land-based deposits, producing nearly 40 million carats from MA1 between 1920 and 1977 (Schneider, 2009) when mining targeted onshore raised beaches west of the high water line. Since 1977 however, SCM and Namdeb have developed a unique mining method to economically extract the resource which extends westward under the Atlantic Ocean."

Feb 1, 2019

By J. P. Garnier, T. Bhambhani, J. A. Garcia, N. Renaud

Most flotation plants use a static reagent scheme, i.e., a set combination of collectors, frothers, and modifiers. This scheme is usually developed and refined over time to deliver optimal (not necessarily the highest) performance when the major ore types are fed to the plant. However, when ore types or mineralogy coming to the plant change substantially (and this often happens as different areas of the pit(s) are mined and crushed at the same time), there are upsets in the process, typically leading to lower recoveries. Adapting to this variability is usually done only when performance drastically suffers, and the changes made may be too late and bring additional variability in performance. The premise for SmartFloat™ is that the reagent suite needs to be dynamic, adapting continuously to changes in the ore and operating conditions. Solvay has combined advanced analytics and data science techniques with its expertise in flotation reagent chemistry to systematically and automatically achieve the above, and in real time. Thus, SmartFloat™ is optimizing the reagent suite continuously, removing the additional variability created by belated human interactions resulting in a better and more stable process. In addition, this advanced approach allows for continuous improvement by identifying poor performing ore domains and improving the reagent suite using Solvay’s FM-100 approach to design appropriate solutions.

Jan 1, 2023

By T. M. Evers, R. P. Van Den Berg

Ancient mining in Southern Africa, with reference to a copper mine in the Harmony Block, north-eastern Transvaal T. M. EVERS. B.A. (Birm.) (Visitor) and R. P. VAN DEN BERG. B.Sc. (Wits.) (Visitor) A recently discovered mine on the farms Harmony 24 and 25 in the Letaba district has been investigated archaeologically by T. M. Evers and geologically by R. P. van den Berg. The archaeological investigations shed light on the mining techniques and accompanying metallurgical techniques, while the geological investigations give information on the structure and mineralization of the mine. Comparisons with other investigated ancient workings show that mining was well understood in Iron Age times, before the African peoples had any contact with Europeans.

Jan 1, 1974

By K. Basaure, S. Palma, R. L. Castro

"Mud rushes are sudden inflows of fine wet ore within underground mines; they can harm people and equipment as well as cause production delays. Block and panel caving mines are prone to mud rushes in their production levels, with mud flowing from the drawpoints. Different mines have developed methods to control drawpoint conditions and thus perform safe ore extraction. The aim of this study is to develop a decision matrix and apply it to samples from drawpoints for the Diablo Regimiento mine, Codelco, El Teniente Division (Chile). The Abrams’s Cone was used to perform slump tests on mud samples and characterize their consistency by setting the saturation degree and packing. The unconfined strength for different saturation degrees and packing was then evaluated. The results show that conditions for fluid response in slump tests correspond to conditions for low strength in unconfined compression tests. We also found the water content value at which the flowing consistency changes from plastic to soft behaviour according to the slump test classification for each sample. This value varied between 12.2% and 16.9%, depending on the sample tested. Finally, a fluid security factor was defined in order to design an extraction pattern for the samples tested, based on the water content. We conclude that a very densely packed ore is not prone to flowing. The flow properties depend strongly on the specific properties of the ore tested, and consequently a specific criterion should be developed for different types of ore at a particular mine. The criterion developed for Diablo Regimiento ore provides critical water content values from 11% to 15%, depending on the ore type. IntroductionBlock/panel caving has the lowest cost and the highest production rates of all underground methods (Heslop, 2000; Hubert et al., 2000). Good management of the risks is important to ensure the security of personnel and infrastructure. Operational risks for the method include rockbursts, air blasts, and mud rushes (Hubert et al. 2000). A mud rush is defined as a sudden inflow of mud from a drawpoint or other underground opening into the mine (Butcher, Joughin, and Stacey, 2000; Butcher, Stacey, and Joughin, 2005). Mud rushes can cause dilution, production delays, and damage to equipment as well as injuries and fatalities. The elements necessary for mud rushes are mud-forming material, disturbances, a discharge point, and water (Butcher, Joughin, and Stacey, 2000). All these elements are present in block/panel caving mines. Mud-forming material comes from ore milled by the caving process; water comes from underground and surface sources. Drawpoints in the production level are discharge points for the mud. Finally, several types of disturbance could trigger the mud rush phenomena: blasting, earthquakes, operation of equipment (Call & Nicholas, Freeport McMoRan, and Hydrologic Consultants, 1998; Jakubec, Clayton, and Guest, 2012), arch collapse above drawbells (Butcher, Joughin, and Stacey, 2000; Butcher, Stacey, and Joughin, 2005; Jakubec, Clayton, and Guest, 2012) and ore drawing (Butcher, Joughin, and Stacey, 2000; Butcher, Stacey, and Joughin, 2005; Call & Nicholas, Freeport McMoRan, and Hydrologic Consultants, 1998; Jakubec, Clayton, and Guest, 2012)."

Jan 1, 2017

By V. A. Leão, V. S. Coimbra, V. A. A. Oliveira, R. F. M. de Souza, G. M. de Lima

A willemite concentrate consisting mainly of willemite (55.3%) and dolomite (15.6%) was reduced in a tube furnace with charcoal as reductant. The effects of temperature and varying reductant additions on zinc extraction were studied. A zinc recovery of 86% was achieved with 20% reductant in the charge at 1100°C. During reduction, the calcium oxide generated through calcination of the dolomite promoted decomposition of the willemite, thus lowering the temperature at which reduction took place. The presence of CaO improved the zinc recovery at all temperatures studied. The best zinc recovery (93%) was obtained in the presence of 5% CaO, 20% charcoal reductant, and at a temperature of 1100°C. The results show that the willemite concentrate studied has great potential to be used as a raw material for the Waelz process.

Nov 6, 2023

By C. Hartford, T. Holmes

Bulk-solids handling systems are often the most over-looked component and thereby weakest links in a processing plant’s value chain. Since their performance can dictate that of the entire operation, they actually deserve special attention. When designing a liquid handling plant, density and viscosity are well known and commonly used as design parameters. Bulk solids however, differ. While the design process is similar, the relevant parameters in handling bulk solids are instead friction, cohesive strength, compressibility, and permeability. These then vary depending on the mineralogy, particle size distribution and shape, moisture content, storage time-at-rest, temperature, and consolidation pressure. With so many variables, it becomes important to characterize each individual bulk solid across the full range of representative process conditions within the handling system, plant wide – or if you are not very lucky, suffer the consequences of poor material flow. Measuring flow properties and applying them correctly in bulk solid handling system design reduces project risk, saves significant capital, and drastically increases throughput, especially when done in the early stages of a project. Keywords: Flow Properties, Bulk Solids, Process Conditions, System Design

Jan 1, 2020

By C. Karageorgos, J. Sakala, A. Prinsloo, B. Ngambi

The sulphide flotation circuit at First Quantum Minerals’ Kansanshi mine in Zambia produced over 100,000 t of copper in 2019. For this circuit, mineralogical analysis has shown that the majority of the copper lost is hosted in fine liberated chalcopyrite, which is a paramagnetic mineral. The objective of this work was therefore to improve fine chalcopyrite recovery in the sulphide flotation circuit at Kansanshi, using a magnetic conditioning technology to agglomerate fine paramagnetic minerals. This theoretically increases the probability of attachment during collision and therefore improves recovery. A four-month paired ‘t’ test plant trial was carried out and comprised of consecutive ON-OFF periods with and without magnetic conditioning in the rougher flotation bank of the sulphide circuit. The experimental design involved assessment of recovery by size based on daily and weekly composite samples of feed and tails, sized using both wet-screening and cyclosizer. Both the daily plant data and the sized samples showed an increase in Cu recovery with magnetic conditioning ON. A 0.56% copper recovery improvement was measured with magnetic conditioning at a 99.4% confidence level. Keywords: Flotation, fine mineral, chalcopyrite, magnetic aggregation

Jan 1, 2020

By L. Thomas, D. Muteba, L. I. Nsenga, B. Mbao, G. Longo Banza

Owing to the high ore grades in the African Copperbelt and variable acid consumption, agitated leaching is common practice and is used more widely in Africa than in other regions. Two common challenges for agitated leach–solvent extraction circuits are higher presence of colloidal silica in the pregnant leach solution and elevated levels of total suspended solids. Both can negatively affect the physical and metallurgical performance of the solvent-extraction circuit, and lead to higher processing costs or reduced copper production. Operating in organic continuity is preferred to address such challenges, but is not always possible: additional treatment options may be advantageous. For this reason, Solvay recently introduced ACORGA® CR60LT, a new chemical additive to address these concerns. Continuous addition to the pregnant leach solution improves physical performance without negatively affecting Cu transfer or cathode quality. Results and benefits from commercial utilization of ACORGA® CR60LT at different operations in the Copperbelt are reviewed

Jan 1, 2023

By S. A. Lorentz, Y. Xu, C. Theron

The failure of tailings storage facilities (TSFs) results in the discharge of significant quantities of hazardous waste material into the natural environment. Research studies relating to slope instability have identified physical mechanisms such as rainfall-induced erosion, liquefaction, and shear failure as the main triggers. The generation of transient pressure waves and the mobilization of pre-event water in the unsaturated zone have been found to trigger shallow landslides in natural hillslopes. In this paper we review these physical mechanisms, known as groundwater ridging (GWR) and the Lisse effect (LE), from other studies. Previous researchers have explained both these phenomena through field and laboratory observations, numerical modelling, as well as conceptual discussions. These case studies demonstrate the impact of rainfall characteristics on the generation of transient pressure waves that rapidly increase the phreatic surface and change pore water suction. Reference is also made to the influence and behaviour of physical porous medium characteristics on the establishment of a continuous water phase that facilitates the transmission of an induced pressure head. However, previous studies fail to recognize the possibility that the pressure increase in pre-event water through pore air propagation could cause slope instability in tailings dams. The authors suggest that the physical properties and hydraulic behaviour of unsaturated porous tailings media make it susceptible to GWR and the LE, resulting in the creation of a potential failure plane.

Feb 2, 2022

By E. J. Y., G. J. McLachlan, E. Amini, Koha

Inferring individual component flotation rates from recovery-time data of ore complexes is important in optimising and designing minerals processing plants. However, existing two-component first-order flotation models are computationally intensive to solve using conventional non-linear least squares regression. In this paper, a Convolutional Neural Network (CNN) is used to approximate the inverse function which predicts the two-component first-order model parameters using recovery-time data. This paper compares the accuracy and computation speed of the proposed CNN against traditional non-linear least squares regression on 1 million generated data based on a known two-component firstorder kinetic model. It is shown that using a CNN is possible to approximate the inverse function for the non-invertible two-component model with recovery-time as an input matrix for convolution operations. The CNN method is 450 times faster to compute than the Trust-Region (TR) non-linear least squares regression algorithm. However, the CNN model is less accurate compared to the TR algorithm overall. Keywords: Flotation kinetics, convolutional neural network, inverse problem, modelling and simulations

Jan 1, 2020

By M. Rudolph, R. Tolosana-Delgado, G. van den Boogaart, M. Reuter, U. Peuker

This paper addresses the challenge to define a concept of entropy (state of order) for a textured particle system. Both the particle texture, the intergrowth respectively, and the particle size influence the order of a particle system. The smaller the particles become, the more particles form the solid system and the more permutations of the structure of the particle bed are possible. The texture within a particle is fixed, as long as it is not subjected to changes due to comminution, flocculation or agglomeration. The paper will present a definition of entropy, which is able to reflect qualitatively and quantitatively the intergrowth and the size (distribution) of the particles. Theoretical examples will show how different breakage mechanisms can be identified using the entropy definition. Furthermore, we will define the specifications for data sets to calculate the entropy of a particle system. Keywords: Milling, mineral liberation, intergrowth, statistical entropy, modelling

Jan 1, 2020

By A. McQuillan, N. Bar

Geotechnical engineers are routinely tasked with advising suitable stand-off distances below highrisk sections of slopes in open-pit mines that are identified to have potential to deform or collapse. Accurate prediction of failed material runout can mean the difference between continuous safe mining and unwanted high-potential incidents that result in loss of production, equipment damage, injury, or loss of life. This paper updates previous empirical relationships presented by the authors for estimating the volume and runout distance of excavated slope failures, in an open-pit mine operation, using slope geometry as the primary predictor. Cases are sourced from varying slope geometries (fall heights up to 385 m, slope angles up to 80°) and a range of commodities (iron ore, coal, nickel, gold, copper, boron, and limestone), excavated in sedimentary, banded-sedimentary, epithermal, and copper-porphyry deposits, across all six inhabited continents. Analysis of these cases identified positive correlations between slope height and runout distance, and slope height and failed material volume. In general, negative correlations were identified between Fahrböschung angle and slope height, and Fahrböschung angle and failed material volume; however, significant scatter is observed in these datasets. A definitive relationship could not be derived comparing Fahrböschung angle with failed material runout. Slope angle was also found to be a poor indicator of runout. Of the parameters analysed, slope height (i.e., fall height) was found to be the simplest and best predictor of runout distance. This paper presents new charts for predicting failed material runout distance for rock slopes. Relationships are defined for structurally and rock-mass driven slope failure mechanisms at average, 75%, and 95% prediction intervals

Jul 10, 2024