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By A. I. Kalugin, A. A. Abramov, D. E. Kozlov

As a result of thermodynamic analysis of a mineral-sodium, oleate-water system, flotation and adsorption tests at various pH values, and sodium oleate concentrations, it has been established that due to regularities of phosphate-containing minerals (fluorapatite, hydroxyapatite, carbonatapatite) flotation cannot be explained by the formation of alkali-earth metal oleates on their surface. This paper presents a novel theory that connects optimal conditions for mineral flotation with zero charge of its surface, which can explain the regularity of minerals flotation observed. The quantitative physicochemical flotation models developed based on the theory are suitable for improving industrial processes, conditioning of recycling waters, and application in automatic control systems at the plants. Key words: apatite, oleate, flotation, modeling, control, and regulation.

Jan 1, 1999

By Wei Bin, Liu Zhe, Liping Xiao, Jichi Bai

The Acid Mine Drainage has characteristics of low pH, high concentrations of heavy metal ions, such as Fe2+, Mn2+, Cu2+ and Zn2+. In this paper, the composite particles that consisted of bentonite and steel slags were used to dispose the Acid Mine Drainage. Bentonite is the mineral materials and can adsorb heavy metal ions excellently. The steel slags are alkaline and industrial solid waste for the treatment of the Acid Mine Drainage. The main influencing factors, such as adsorbent dosages, shaking rates, concentrations of heavy metal ions, temperatures, adsorption time and pH value were studied by the static experiment. Increasing the adsorbent dosages and the concentrations of the heavy metal ions, speeding up the shaking rates, raising the temperatures, extending the adsorption time and improving pH would improve the removal efficiencies of heavy metal ions. Through considering the removal efficiencies and the treatment costs, the optimum reaction conditions for the four kinds of heavy metal ions were obtained. The adsorbent dosage 21 mg/L, the rotational speed 120 r / min, the temperature 25?, adsorption time 100 min and the initial wastewater pH 7. The four kinds of heavy metal ions existed independently in the simulated mine wastewater. The highest initial concentrations of Fe2+, Mn2+, Cu2+ and Zn2+ were 150 mg/L, 100 mg/L, 170 mg/L and 140 mg/L respectively. The removal rates were 93.42%, 92.64%, 93.86% and 95.17% respectively. The determination of the particles’ SEM-EDS Microscopic characterization showed the composite particles could play a part in neutralizing, absorbing and the chemical precipitation. The acidity decreased notably and the heavy metal ions of Fe2+, Mn2+, Cu2+ and Zn2+were adsorbed and precipitated effectively. The research results can extend the practical engineering application of the composite particles.

Jan 1, 2017

By J. C. Yingling, R. Kumar, J. Sottile

The capability for on-line measurement of the quality characteristics of conveyed coal now enables mine operators to take advantage of the inherent heterogeneity of those streams and split them into wash and no-wash stocks. Relative to processing the entire stream, this reduces the amount of coal that must be washed at the mine and, thereby reducing processing costs, recovery losses and refuse-genera¬tion levels. In this paper, new ap¬proaches for optimal control of the segregation process using time-se¬ries models and empirical distribu¬tions are presented and demon¬strated using field data.

Jan 1, 2000

The capability for on-line measurement of the quality characteristics of conveyed coal now enables mine operators to take advantage of the inherent heterogeneity of those streams and split them into wash and no-wash stocks. Relative to processing the entire stream, this reduces the amount of coal that must be washed at the mine and thereby reduces processing costs, recovery losses, and refuse generation levels. In this paper, new approaches for optimal control of the segregation process, using time series models and empirical distributions, are presented and demonstrated using field data.

Jan 1, 1998

By J. Abdollahisharif

Optimal cut-off grade is one of the most critical parameters in open-pit mine design because it defines the ore and waste and thus determines the maximum net present value possible from the mining operation. Although the algorithm presented by Lane (Choosing the optimum cut-off grade. Colorado school of Mines Quarterly, vol. 59, no. 4, 1964. pp. 811-829) is the most common one in the literature, it does assume constant capacities of the mine, processing, and refinery. In this paper, Lane's original algorithm has been modified to consider variable processing capacities in order to determine the optimal cut-off grade in open-pit mines. The new algorithm proposed here is compared to both Lane's original algorithm and to a previous modification that incorporated rehabilitation costs into the cut-off grade estimation. The algorithm proposed here that permits variable processing capacities is shown to be superior for the determination of optimal cut-off grade to both these previous versions. In addition, a computer-based program was developed in Microsoft Office Excel© to calculate the optimal cut-off grade as proposed here.

Jan 1, 2012

By Y. Idrogo

Electronic delay detonators have been used in most types of blasting application with great success, with the accuracy and precision being used effectively to control negative environmental impacts like vibration. They have also provided consistent repeatable fragmentation and heave results. With the very wide choice in delay period and powerful timing design software, the choice of firing times to optimise blast results is not always clear to the designer. So the improved results achievable from the use of electronic delay detonators are often not optimally achieved.

Jan 1, 2018

By Thien Sok, Yaojun Lu, Craig Gilbert, Jeremy Scott

Feedwells play a pivotal role in gravity thickeners, governing flow distribution, feed dilution, and flocculation condition during solid–liquid separation. This study presents an optimized design and digital prototyping framework for FLSmidth’s E-volute and E-Duc Feedwell systems, integrating advanced computational fluid dynamics (CFD) with quantitative criteria introduced at SME2024. Building on established FLS technologies, a series of novel configurations were developed and systematically assessed under full-scale and site-specific conditions. CFD provided quantitative insight into flow distribution, feed dilution, and flocculation efficiency, enabling iterative refinement of design parameters. The optimized feedwell demonstrated superior hydraulic performance, enhanced mixing, and improved flocculation outcomes. Beyond the specific design advances, the work highlights CFD as an effective and economical tool for digital prototyping, facilitating early identification of design limitations, reducing dependence on physical trials, and accelerating innovation. The methodology underscores the value of simulation-driven design in advancing feedwell performance and improving thickener technology.

Feb 22, 2026

By Y. Xi

This paper offers an algorithm to determine the optimal panel size with the objective of minimizing the overall stripping cost. The approach is presented both in analytical form for regular layers of coal and overburden, and in graphical form for the cases of irregular and multiple coal seams. When the optimal panel width needs to be changed due to some circumstance, we prove in general that increasing the panel width is better than reducing it in both economics and operational efficiency.

Jan 1, 1994

By S. J. Jung

The prime criteria in the design of underground openings with complicated geological structures is ground control. Stability of underground openings for deep mines is critical because incorrect orientation or geometry of shaft, stope, and accessways often results in the failure of openings due to high stress conditions. Current design procedures for complicated orientation and geometry of mines are rapidly becoming inadequate as mines are being developed. In this study, finite element method has been used with optimization criteria to design more stable and safe underground openings.

Jan 1, 1993

By Karl P. Norrena, Clayton V. Deutsch

Ore and waste cannot always be visually separated. The distinction between ore and waste may need to be made on the basis of blasthole sampling. Hand drawn dig limits or computer-generated contour lines do not account for uncertainty, economics or equipment. Geometric methods for interpreting grade information such as the polygonal or triangulation methods share the same limitations as contouring. Geostatistical techniques exist for the realistic modeling of grade variations and uncertainty. Decision analysis techniques exist for the binary classification of ore, and waste blocks in the presence of this uncertainty. Block-by-block classification is not enough; mining equipment cannot exercise free selection of blocks. There is a need for procedures to determine optimal dig limits that account for (1) the uncertainty in the grades, (2) the economics of risk-qualified decision-making, and (3) the ability of the mining equipment to dig to specific limits. This paper presents a procedure for optimal determination of dig limits that account for these constraints. Simulated annealing (SA) is used with modest computational requirements because the number of variables is relatively small. The solution of the optimization problem is dig limits that maximize profit under multiple constraints. The method is illustrated with different constraints and tested against hand drawn dig limits in a "Dig Limit Challenge," which illustrates the efficacy of the new method.

Jan 1, 2002

By M. E. Gershon

Conventional methods of drill hole site selection are reviewed briefly. Two approaches using geostatistics are then discussed, both of which have been shown to yield improved results. Finally, a branch and bound algorithm is described which will select the best locations for drilling from a user specified number of possible drill sites. Two options are discussed. First, the user can specify a maximum drilling investment or a maximum number of drill holes and the program will select the locations yielding the minimum estimation variance. This amounts to getting the most for a given investment. Alternatively, a maximum tolerable estimation variance can be specified and the program will select the number and location of the drill holes to obtain the desired information at a minimum cost. Another benefit of the approach is the quantification of the tradeoffs between investment and information obtained.

Jan 1, 1985

By M. E. Gershon

Conventional methods of drill hole site selection are reviewed briefly. Two approaches using geostatistics are then discussed, both of which have been shown to yield improved results. Finally, a branch and bound algorithm is described which will select the best locations for drilling from a user specified number of possible drill sites. Two options are discussed. First, the user can specify a maximum drilling investment or a maximum number of drill holes and the program will select the locations yielding the minimum estimation variance. This amounts to getting the most for a given investment. Alternatively, a maximum tolerable estimation variance can be specified and the program will select the number and location of the drill holes to obtain the desired information at a minimum cost. Another benefit of the approach is the quantification of the tradeoffs between investment and information obtained.

Jan 1, 1985

By Mark E. Gershon

Conventional methods of drillhole site selection are reviewed briefly. Two approaches using geostatistics are then discussed, both of which have been shown to yield improved results. Finally, a branch and bound algorithm is described which will select the best locations for drilling from a user specified number of possible drill sites. Two options are discussed. First, the user can specify a maximum drilling investment or a maximum number of drillholes and the program will select the locations yielding the minimum estimation variance. This amounts to getting the most for a given investment. Alternatively, a maximum tolerable estimation variance can be specified and the program will select the number and location of the drillholes to obtain the desired information at a minimum cost. Another benefit of the approach is the quantification of the tradeoffs between investment and information obtained.

Jan 1, 1983

By L. Chunpongtong

One of the challenges of mine planning is to determine the most cost-effective replacement time for aging equipment. The lifespan of equipment, such as haul trucks and shovels, deployed in mining operations varies due to the nature of the material and ground conditions in which it operates. For engineering economists dealing with aging equipment, the options become an economic trade-off between higher maintenance cost versus the cost of new equipment. The discount rate plays a significant role in this decision; the higher the rate, the longer the economically optimal lifespan. Therefore, the ultimate question is: ?How can the relationship between the discount rate and the economically optimal lifespan be expressed mathematically??

Aug 1, 2013

By Arka Jyoti Das, Prabhat Kumar Mandal

"Coal mining in India has a strategic importance for the energy security of the country. Presently, the majority of coal production is coming from open-cast mining. Due to the fast depletion of reserves amenable to open-cast mining, future coal production will depend primarily on underground production. In conventional bard-and-pillar/room and pillar mining as it is practiced in India, the percentage of extraction is very low. In fact, within most Indian coalfields, a large number of coal seams extract only 15- 20% of coal, but no pillar extraction is done due to the presence of surface or sub-surface structures leading to huge amount of coal being locked-up in underground. Spontaneous heating and fire, the accumulation of poisonous gases, severe stability issues, unsafe workings and environmental hazards are all major problems associated with these developed coal pillars, so there is a pressing need for technology in the mining industry to extract this huge amount of coal locked up under different constraints. In this study, we propose that the locked-up coal be extracted by replacing the developed coal pillars with artificial pillars. The paper briefly discusses the extraction methodology designed for this and its evaluation through numerical modeling for applied suitability underground.INTRODUCTIONDriven by rising populations and urbanization, an expanding economy and also a quest for improved quality of life, energy usage in India is expected to increase manifold in the coming years. As for India's energy scenario and its projected future plans, there is no doubt that coal will remain a prime source of energy, even over the next few decades.The majority of coal production in India comes from open-cast mining because of large-scale mechanization, but the coal reserves amenable to open-cast mining are gradually depleting - which may impose adverse impacts on the energy sector if underground production does not increase. Underground coal extraction, meanwhile, is going to become more complicated in near future due to the fast exhaustion of easily mineable coal reserves."

Jan 1, 2016

By Rodney L. Williamson

Optimal estimation theory has been applied to the problem of estimating process variables during vacuum arc remelting (V AR), a process widely used in the specialty metals industry to cast large ingots of segregation sensitive and/or reactive metal alloys. Four state variables were used to develop a simple state-space model of the V AR process: electrode gap (G), electrode mass (M), electrode position (X) and electrode melting rate (R). The optimal estimator consists of a Kalman filter that incorporates the model and uses electrode feed rate and measurement based estimates of G, M and X to produce optimal estimates of all four state variables. Simulations show that the filter provides estimates that have error variances between one and three orders-of-magnitude less than estimates based solely on measurements. Examples are presented that verify this for electrode gap, an extremely important control parameter for the process.

Jan 1, 2001

By B Belle

In a predrained gassy coalmine, ventilation control plays a secondary role to the longwall (LW) goaf drainage systems to safely manage panel return gas levels. Typically, the LW specific gas emission (SGE) estimation models provide anticipated goaf gas emissions and arriving at required gas drainage capacity for various coal production scenarios. A study comparing the various LW goaf gas hole spacing patterns with weekly production rates of up to 270 kt/w of an operating mine with high SGE rates (~20 m3/t) was carried out. The goaf capture efficiency of LW panels ranged from 64 per cent to 85 per cent. For the first time, gas content of upper seam data post LW retreat were used to verify the current SGE prediction models. This study has shown that an average of 50 m goaf spacing is optimal for management of high production retreat gassy LW panels in presence of multiple upper and lower seams with gas emission zone influence reaching up to 200 m above workings. Due to the horizontal stress direction related geotechnical issues, goaf hole failures just behind the LW face is a recurring challenge resulting in significant and immediate increase in LW panel return gas levels. This paper highlights the shortcomings of current SGE prediction models for goaf gas estimation, and evolution of 50 m goaf hole spacing embedded in design process in managing the LW tailgate gas levels.CITATION:Belle, B, 2017. Optimal goaf hole spacing in high production gassy Australian longwall mines – operational experiences, in Proceedings Australian Mine Vent Conference 2017, pp 15–26 (The Australasian Institute of Mining and Metallurgy: Melbourne).

Aug 28, 2017

By K. Norrena, E. Magri

An important problem in mine operations is the classification of material as waste, low-grade stockpile and ore. This classification must often be made with blasthole data that are widely spaced and that have sampling errors. Geostatistical-simulation techniques combined with basic economic principles allow a procedure for classification that maximizes the expected profit. Geostatistical-simulation methods (Gaussian, indicator or annealing-based) allow the integration of hard and soft data in the creation of alternative, equally probable realizations of the mineral grades. At each location, for each realization one calculates the "profit" if the block were to be classified as ore or waste. The optimal classification is the one that maximizes expected profit (a maximum profit selec¬tion or MPS procedure). In this paper, the authors discuss the theoretical justification of the method and implementation details. The use of blasthole data from different types of mineral deposits, that is, different levels of continuity, are considered. The authors also show the efficacy of the procedure with different levels of sampling error. The increased revenue due to the MPS procedure and improved sampling is shown. The paper shows the geostatistical-simulation procedure and the uncertainty in block grades that result from incomplete and imperfect sampling. The optimal classification is presented. Optimal block classifications are transferred to realizable dig limits by hand-drawing polygonal boundaries. The results of the proposed method are compared to classification based on kriging. Limitations and areas of future work are identified.

Jan 1, 2000

An important problem in mine operations is the classification of material as waste, low-grade stockpile, and ore. This classification must often be made with blasthole data that are widely spaced and that have sampling errors. Geo-statistical simulation techniques combined with basic economic principles allows a procedure for classification that maximizes expected profit. Geostatistical simulation methods (Gaussian, indicator, or annealing-based) allow the integration of hard and soft data in the creation of alternative, equally-probable, realizations of the mineral grade(s). At each location, for each realization, we calculate the "profit" if the block were to be classified as ore or waste The optimal classification is the one that maximizes expected profit (a Maximum Profit Se-lection (MPS) procedure). We discuss the theoretical justification of the method and implementation details. The use of blasthole data from different types of mineral deposits, that is, different levels of continuity, is considered. We also show the efficacy of the procedure with different levels of sampling error. The increased revenue due to the MPS procedure and improved sampling is shown. We show the geostatistical simulation procedure and the uncertainty in block grades that result from incomplete and imperfect sampling. The optimal classification is presented. Optimal block classifications are transferred to realizable dig-limits by hand-drawing polygonal boundaries. We compare the results of the proposed method to classification based on kriging. Limitations and areas of future work are identified.

Jan 1, 1999

By T Wambeke, J Benndorf

A risk-robust development of a heavy mineral resource requires an assessment of the geological uncertainty and spatial variability of the key factors impacting the mining and processing operation. Attributes of interest are the total heavy mineral grade, the slime content and the amount of oversized particles. The modelling of a mineral sand deposit presents two main challenges. Firstly, the exact location of the geological boundaries are obscure due to the complex interaction of the deposit formation processes. Secondly, the properties of interest exhibit a rather complex transitional behaviour across the so-called soft boundaries. Traditionally, the modelling exercise is restricted to a consecutive stochastic simulation of distinct geological facies and orebody properties. This results in different zones separated by hard boundaries, ignoring the typical transitional behaviour.This contribution presents an alternative approach which models the entire sand body as a single domain while accounting for the complex trends present. Error curves are used to infer covariance model parameters without the need of a prior removal of the trend. The principle is based on minimising the differences between empirical and theoretical errors resulting from two methods of prediction calculated for different rings of influence. The added value results from the unambiguous decomposition of the spatial variation into a deterministic trend and a stochastic residual. The trend model neither overfits nor underfits the data. The calculated residuals are thus unbiased and the uncertainty can be correctly assessed.The effort results in a characterisation of the resource uncertainty which provides a more realistic image of the spatial variability of the key properties in and across the geological domains of an existing heavy mineral sand deposit.CITATION:Wambeke, T and Benndorf, J, 2014. Optimal inference of modelling parameters to simulate complex trends across soft boundaries – a case study in heavy mineral sands, in Proceedings Orebody Modelling and Strategic Mine Planning Symposium 2014 , pp 73–84 (The Australasian Institute of Mining and Metallurgy: Melbourne).

Nov 24, 2014