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By WenJun Dong

This paper presents the stability assessment of the steel pipe piles that are used to support a deadman beam to anchor an adjacent bulkhead wall. Finite element analyses are performed to assess the stability of the bulkhead wall and determine the required tie-back force to the pile. The piles are relatively close to the bulkhead wall such that their soil resistance wedge zones are not fully developed but truncated by the bulkhead wall. The reduced lateral resistance capacity of the anchor piles is determined by applying the Coulomb wedge method on the truncated soil passive zones between the pile and wall. Both the conventional soldier pile stability (in terms of force and moment equilibrium) and Winkler soil spring (for soil-pile-interaction) analyses are used to assess the stability of the anchor piles.

Sep 8, 2021

By Haoran Zhang, Chu Ho

A recent design-build project in New York involved various degrees of additions and improvements to four existing transit stations. Reuse of the existing foundations was considered a more sustainable alternative than constructing new foundations for the project. This approach mitigated the extent of demolition work and limited the amount of downtime for track operations. A key challenge for reusing the existing foundations was the lack of as-built drawings. In order to obtain some measure of confidence for the proposed foundation reuse, non-destructive investigation technology was adopted to evaluate the structural integrity of the piers and foundations. A total of 47 piers for the existing passenger platform were investigated for possible reuse. Several test pits, excavated to verify the foundation type and configuration, indicated the piers were founded on a combination of shallow footings and drilled shafts. Pile integrity tests were performed to verify the length of the drilled shafts. Geotechnical capacity of drilled shafts was evaluated for side friction and end bearing resistance, and confirmed using a proof load test conducted from the existing platform structure. This paper presents the investigation methodology and discusses the approach adopted for geotechnical design of the existing foundations for reuse.

Sep 8, 2021

By Amanda R. Parry, Chris R. Pray

Predicting and modeling the soil structure interaction of laterally loaded piles with significant unbraced lengths is one of the challenges faced in designing many waterfront structures. Designers often rely on pile specific design software to calculate forces in an embedded pile and then couple that with either a structural design software to capture the behavior of the rest of the structure or use potentially overly conservative assumptions to omit modelling the piles entirely. Given that some projects have hundreds of piles coupled with hundreds of loading conditions, the shuttling of results from the structural analysis software into the pile analysis software can become cumbersome, difficult to track and manage, and prone to user input errors. An alternative approach recently used on two large marine infrastructure projects consisted of calibrating a structural analysis software to replicate the resultant outputs from a software developed specifically for pile analysis. This calibration was done using thoughtfully placed springs along a pile modeled in the structural analysis software to replicate the soil-structure interaction of the piles. The focus of this paper will be on the methodology used to calibrate the two software programs and an evaluation of the results which showed close agreement. Based on the two case studies, calibrating a generic finite element analysis software via this method should be considered as a reasonable and time saving design approach for pile-supported structures.

Sep 8, 2021

By Rushikesh Battulwar, Javad Sattarvand, Joseph Seamons, Masoud Zare

In the last decade, new developments took place in the area of indoor positioning (or localization). Since the Global Navigation Satellite System (GNSS) cannot be used in underground mines, other technologies are needed for localization. Positioning and communication options today primarily include Wi-Fi, Bluetooth Low Energy (BLE), Ultra-Wideband (UWB), Radio Frequency Identification Device (RFID), etc. Smartphones and tablets currently have an array of sensors and radios, which can provide valuable information to allow indoor localization via various methods. Where mineworkers could keep smartphones with them, they can be highly effective at enabling localization and navigation. Recent applications of these technologies in underground mines have been thoroughly reviewed and examined for the likelihood of their utility for accurate localization where no other means exist. Some critical challenges and gaps that need to be addressed in future research have been identified.

Sep 5, 2021

By BHAMIDIPATI S. SASTRY, ANMAYA NAIK, ASIF AHMAD, Srivatsan Jayaraman Sridharan, ADITYA PANDEY

Wet kata cooling power (WKCP) as measured by a kata thermometer is a well-known heat stress index used in the mining industry. Although, over the years, several researchers proposed different heat indices and indicated limitations of the kata thermometer, WKCP is used in the South African gold mining industry due to its simplicity and rapidity of assessment. This paper presents a comparative analysis of the newly developed empirical expression for the WKCP and some of the more commonly used empirical models. For this purpose, WKCP measurements are obtained based on experiments conducted in a low-speed wind tunnel. Based on a regression technique, the analysis presented aims to assess the disagreement between the empirical model predictions and actual measurements. The correlation is also presented between WKCP and the well-established thermoregulation models using parameters from the low-speed wind tunnel experiments, including dry-bulb temperature (Td), wet-bulb temperature (Tw), barometric pressure (P), and wind speed (v). It is found that the proposed empirical model for the WKCP represents the bioclimatic interaction quite well under the specific parameters that defines the harsh thermal environment and air condition, such as metabolic activity, clothing of the person, and the velocity of the ventilating air in which the person is working. The statistical analyses performed show that the empirical model proposed for the WKCP produces satisfactory estimates of the thermal stress experienced under lower air velocities, light clothing, and higher metabolic activity rates.

Sep 2, 2021

By M. Shamsi, M. Nehring

One of the most challenging aspects in semi-mobile in-pit crushing and conveying (SMIPCC) system design is determining the optimum depth at which to change from a purely truck-based haulage system to a conveyor-based haulage system. We used scenario analysis to determine the optimum transition depth between a truck and shovel (TS) system and a SMIPCC system. Traditional pit-limit algorithms were used to generate the final pit limit on a copper deposit, which was then divided into four pushbacks. The final operating pushbacks (phases) were designed for both TS and SMIPCC. The end depths for each phase are viewed as candidate transition points to switch from the TS to SMIPCC haulage system. Economic calculations were applied for five different scenarios, including adopting SMIPCC from the outset (pure SMIPCC), after the first, second, and third phases, and finally not using the SMIPCC system (pure TS) at all. The analysis indicates that the second scenario, at a depth of 335 m, results in the lowest cumulative discounted cost (CDC). In this case, the CDC is 17.6% lower than that for the pure TS scenario and 10.7% lower than for the pure SMIPCC system scenario.

Sep 1, 2021

By H. Askari-Nasab, S. Upadhyay, A. Moradi-Afrapoli

Material handling in surface mines accounts for around 50% of the operational cost. Optimum truck dispatching plays a critical role in the reduction of this operational cost in truck and shovel surface mines. Researchers in this field have presented several mathematical models to solve the truck dispatching problem optimally. However, a critical survey of the literature has shown that three significant drawbacks exist in the available truck dispatching models. The published models underestimate the importance of the interaction between truck fleet, shovel fleet, and the processing plants. They also disregard goals set by strategic-level plans. Moreover, none of the available models account for the uncertainty associated with the input parameters. In this paper we present a new truck dispatching model that covers all of these drawbacks, using a fuzzy linear programming method. The performance of the developed model was evaluated through implementatin in an active surface mining operation. The results show a significant improvement in production and fleet utilization.

Sep 1, 2021

By P. C. Pistorius, M. P. Maphutha, J. D. Steenkamp

Advanced high-strength steels (AHSS) are sophisticated materials being developed by the steel industry to mitigate challenges related to the performance of motor vehicles. To meet the requirements of AHSS, the ferromanganese alloys (FeMn) utilized in the production of the steel are required to contain acceptable levels of unwanted impurities, i.e. P, S, N, H, and C. The focus of the current study was to investigate dephosphorization of ferromanganese to produce a low-P alloy that could be effectively utilized in the production of AHSS. The study involved conducting laboratory-scale testwork to study the efficiency of CaO-based slag systems to dephosphorize FeMn alloys. The addition of Na2O, CaF2, and BaO to MnO-CaO-SiO2 slag was considered. The test work was carried out in a 25 kW induction furnace at temperatures of 1350°C, 1400°C, and 1450°C. The P partition coefficient (Lp) remained small at <1, which is an indication that dephosphorization had not been achieved. The baseline slag, comprising 40%CaO-40%SiO2-20%MnO, reported higher Lp values. Addition of Na2O and CaF2 did not show any further benefit. Substituting half of the CaO by BaO, resulted in similar Lp values to those of the baseline slag under conditions of 1350°C and 1450°C at 30 minutes. In summary, based on the Lp values obtained, the conditions investigated with the CaO-based slags appeared to have been unfavourable for dephosphorization of FeMn alloys, as most of this impurity element remained in the alloy.

Sep 1, 2021

By B. McFadzean, M. Tadie, T. Dzingai, M. Becker

Ores from a single deposit may exhibit extensive variability in their mineralogy and texture. The ability to quantify this variability and link it to mineral processing performance is one of the primary goals of process mineralogy. This study focuses on the effect of alteration in three platinum group element ore samples from the Great Dyke in Zimbabwe – two of which were more pristine compared to the third, which was locally classified as ‘oxidized’ ore. These ores are known to be characterized by varying degrees of alteration, resulting in numerous challenges in flotation and affecting both grade and recovery. Alteration, by near-surface oxidation, of the valuable base metal sulphides and platinum group minerals resulted in lower flotation recoveries of Cu, Ni, Pt, and Pd. Evidence of incipient oxidation was more readily observed in the base metal sulphide assemblage than the platinum group mineral assemblage, even though the loss in recovery (because of oxidation) was most significant for Pd. Alteration through hydration resulted in a significant increase in mass pull and dilution of concentrate grade through the inadvertent recovery of naturally floating gangue comprising composite orthopyroxene and talc particles. In this study, the amount of naturally floating gangue was more strongly correlated with the talc grain size distribution than the grade of talc in the flotation feed. The oxidation and hydration alteration reactions are not necessarily mutually exclusive, although one may be more dominant than the other, giving rise to ore variability.

Sep 1, 2021

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 N. Duda, P. Śliwiński, P. Stefaniak, B. Jachnik

Ventilation and air-conditioning are some of the most energy-consuming processes in deep underground mining. Additionally, the energy consumption of these processes systematically increases along with the expansion of the mine. Therefore, proper energy efficiency assessment and consumption forecasts of these systems are particularly important in modern mines for ongoing tracking and planning of the likely costs. In the article, a short-term prediction model for surface air–conditioning stations is described. This model takes into account dependencies that were identified, based on the data from the supervisory control and data acquisition (SCADA) systems. These dependencies between the response value and the external conditions are then incorporated into the model. This way, for example, the ambient temperature or the total number of specific days of the week (with sometimes significantly lower or higher than the weekly average energy consumption levels) are included. Taking into account these dependencies, and e.g. forecasted average monthly temperatures allow us to include the seasonality of energy consumption in the presented model. In the article, a sample energy efficiency analysis of the A/C system based on an example of the KGHM Polish Copper Polkowice-Sieroszowice mine is performed. The results of the solution proposed in the article are then evaluated, and compared to the currently functioning, more basic forecasting methods. However, given the general nature of the dependencies used in the model, similar solutions could be used in other case studies.

Sep 1, 2021

By A. Melkumyan, M. Balamurali, J. Zigman

Understanding the contribution of geophysical variables is vital for identifying ore indicator regions. Both magnetometry and gamma-rays are used to identify the geophysical signatures of the rocks. Density is another key variable for tonnage estimation in mining, and needs to be re-estimated in areas of change when a boundary update has been conducted. Modelling these geophysical variables in 3D will enable investigation of the properties of the rocks and improve our understanding of the ore. The Gaussian Process (GP) was previously used to generate 3D spatial models for grade estimation using geochemical assays. This study investigates the influence of the following two factors on the GP-based autonomously generated 3D geophysical models: the resolution of the input data, and the number of nearest samples used in the training process. A case study conducted on a typical Hammersley Ranges iron ore deposit using geophysical logs, including density, collected from the exploration holes, is examined in this paper.

Sep 1, 2021

By S. Yaw Amponsah, E. Ben-Awuah, P. M. Takouda, P. Eme

Mining production scheduling is the process of determining the sequence of block extraction over a period of time that will yield the maximum net present value for a mining operation. The block extraction sequence needs to occur under certain resource constraints which presents an NP-hard problem that is computationally intractable and complex to solve for large scale problems using exact mathematical models such as Mixed Integer Linear Programming (MILP). In this paper, we used a metaheuristic optimisation model based on a Genetic Algorithm (GA) to solve the production scheduling problem. The problem definition and resource constraints are formulated using a mining specific GA that enforces block extraction precedence and mining capacity constraints through a normalisation method. A case study is implemented with the GA model, and the results and computational time are compared with that of a MILP model with CPLEX solver which is based on a branch-and-cut algorithm.

Sep 1, 2021

By M. Z. Naghadehi, F. F. Nasategay, J. Sattarvand, R. Battulwar, E. E. Gohari

After the recent increase in catastrophic failures of tailings dams such as the Burmadinho, Brazil failure in 2019, the mining industry has actively engaged in the stabilisation of tailings dams. Most of the tailings storage facility (TSF) guidelines suggest a laborious action that can be facilitated through imaging by unmanned aerial vehicles (UAVs). Although UAVs are not unknown to most mining operations, automated rill detection through aerial image processing is a new concept. This study utilises images from sites in the U.S. and employs semantic segmentation with a UNet architecture to detect location and size of these rills. The developed model can be used as a tool for monitoring surface erosion of TSFs.

Sep 1, 2021

By N. Duda, W. Koperska, S. Anufriiev, P. Stefaniak

In mineral processing plants ore extracted from mines is processed to obtain a concentrate with the highest possible concentration of this valuable product. It is a complicated multi-stage process. Usually, the first step is sieving the ore, which is typically done using vibrating mining screens. There is often only a limited number of these machines in the technological chain, which is why their continuous operation, and proper maintenance is crucial for the whole process. Predictive maintenance is the best strategy in this case because it allows for minimising the number and duration of unexpected stoppages. It consists of the prediction of future failures based on available real-time data, and predictive models built upon this data using, for example, machine learning techniques. In this paper we concentrate on feature generation for future predictive maintenance model development for a vibrating screen, based on an example of a KGHM ore processing facility in Polkowice-Sieroszowice. We focus on two types of measurements: bearings temperature and vibrational data. Based on the raw data, the process of more advanced feature engineering is described. By transforming the temperature data we calculate characteristics of bearing cooling and heating dynamics, while based on vibrational data, the aggregated characteristics of the vibrations are derived. Such features are calculated on a long-term basis, and then they are compared to the data related to vibrating screen maintenance to estimate their significance for the prediction of particular failures of the machine.

Sep 1, 2021

By F. Navarro, F. Soto, G. Díaz, E. Jélvez, G. Morales, N. Morales

The increasing availability of tools on the web provides a great opportunity for the research community to boost investigation by accessing computational resources from all over the world. For example, data analytics libraries implemented in languages like Python can be accessed through many open and commercial platforms, therefore providing researchers with a common set of tools or shared datasets. Unfortunately, that is not the case with research in resource assessment and mine planning, where the most standardised tools are commercial applications designed to work on the desktop, but there are not many standard platforms for research. As a result, researchers from different groups often need to start from scratch in order to develop their work, and rarely share implementations details. Similarly, apart from a few publicly available examples, there is a lack of common datasets that are validated and can be used to compare results between different approaches. In this paper, we introduce a platform that provides tools for resource assessment and mine planning, which can be accessed remotely utilising Jupyter Notebooks. In its current version, the platform provides (i) definition and implementation of basic structures for managing samples and models (loading, saving, adding or removing columns, etc.), (ii) definition of experimental and modelled variograms for spatial continuity analysis, (iii) definition of standard interpolation methods in resource evaluation (inverse distance and kriging), (iv) definition of standard problems in mine planning (ultimate pit and precedence constrained production scheduling), (v) generation of 2D standard graphs like grade distribution, conditional means, tonnage-grade, and production plans (vi) a set of datasets, which can be used for case studies, and (vii) a set of notebooks with examples and documentation. In this paper, we introduce the platform and show some examples that illustrate some of the possibilities that it has for research and education in the area of resource assessment and mine planning.

Sep 1, 2021

By M. S. Shishvan, S. Klerkx, J. Sattarvand

The inaccurately drilled blastholes from the planned locations cause changes in the spatial distribution of explosive energy; some areas of the blast may receive a surplus of explosive energy, while others see a reduction. This results in less uniform fragmentation, reduces the efficiency of mining operations and increases costs. Additionally, it can lead to slope stability issues, flyrock, and uneven benches. To mitigate these problems, this study attempts to reduce differences in the explosive energy distribution (EED) through an optimization approach that adjusts the height of explosive columns in blastholes. Two optimization algorithms, the Genetic Algorithm (GA) and Tabu Search (TS), are tested. The latter is preferred for its local search neighbourhood strategy that gives superior computation times. Applications on different blast patterns result in improvements of 0.53–1.54%, or 2.14–3.94% when only the affected blocks are considered.

Sep 1, 2021

By S. Blancher, A. Perroton, H Smith, T. Nzima, T. Wallmach, V. Dieudonné

Chromite beneficiation is generally performed by crushing and density separation using spirals. At the Dwarsrivier Chrome mine spiral efficiencies seam to vary, the reason for which is not evident. This sometimes results in the production of low-grade products, which are sold at relatively low prices. This paper represents a Qemscan® study that investigated mineralogical reasons for these variations. Variations in liberation of chromite particles as well as variations in chromite compositions were investigated. The results showed that the so-called low grade chromite product can be improved to become a high grade chromite product by means of a refinement in mineral processing. A detailed Qemscan® database (SIP file) was developed to account for variations in chromite chemistries. It can be shown that chemical variations with respect to Cr, Al, Mg and Fe in chromite particles reporting to the scavenger tails are larger than in the high grade product. A combination of these chemical variations together with a decrease in liberation of chromite particles in the scavenger tails can potentially help to recover more chromite particles from this specific process stream.

Sep 1, 2021

By M. Kumral, S. Li, M. Balci, Z. Shao

Main haulage roads play an important role in the performance of underground mines because of the cost of transportation of the extracted ore, equipment, and workers. During mine development, these roads are designed through manual tools or CAD-based software. However, the optimisation of these roads is still a complex problem due to some constraints such as minimum turning radius and maximum gradient. By utilising Dubins path theory, three elevation cases; namely low, medium and high are defined, considering gradient constraint as well as the minimum turning radius in a three-dimensional space. The shortest path between two points can then be found by the three-dimensional Dubins path algorithm with elevation constraint. As a further step, a three-dimensional Dubins path algorithm with elevation constraint for multiple points is also developed for multi-point cases. The effectiveness of these algorithms is tested through case studies in order to determine the optimal path between different points.

Sep 1, 2021

By T. J. Otto, I. D. Ungerer, G. C. Lindeque, T. J. van Heerden

Anglo American Kumba Iron Ore (Kumba) continues to implement technologies focussed on improving safety and productivity; this forms part of the groups FutureSmart Mining initiative. The paper provides insights into the implementation of three technology solutions that improves the productivity of heavy mining equipment (HME). Enhancements to the short term mine planning (STMP) process, the effective use of a fleet management system (FMS) and the deployment of drones or Remotely Piloted Aircraft Systems (RPAS) are discussed. The implementation of these and other technologies contributed to a 13% and 22% increase in the overall equipment efficiency (OEE) of the primary HME at Kumba’s Sishen and Kolomela mines respectively. Four key success factors (KSF) are highlighted namely that Kumba’s technology implementation drive is a key enabler to the company’s strategy, has a strong focus on value-add, is underpinned by a holistic and integrated implementation approach and is people-centric.

Sep 1, 2021