Search Documents

By David S. Graham, Benjamin Turner, Paul J. Axtell

Seismic challenges were at the forefront of design for two parallel replacement bridge structures over the Arkansas River as part of the I-30 Crossing Project in Little Rock, Arkansas. Although not an area of the country typically associated with high seismicity, proximity to the New Madrid Fault Zone resulted in design ground motions sufficient to trigger liquefaction in alluvial channel and point bar deposits. A detailed post-award subsurface investigation program utilized CPT with complimentary borings to obtain samples for laboratory testing to assess the continuity of potentially liquefiable layers, from which we concluded that continuous zones of liquefaction across the extent of the north approach could lead to lateral spreading towards the river. An overview of the foundation and superstructure design to resist lateral spreading forces in accordance with the latest published design guidelines and research is presented. Other seismic aspects of the design are covered including timber pile ground improvement to mitigate liquefaction at the north approach embankment and foundation input motions that differ from code-based ground surface motions due to foundation stiffness, strength, and geometry. The project showcases an example of successful collaboration between geotechnical and structural designers with contractor input to address seismic challenges in the South Central US. Furthermore, the importance of considering kinematic demands on columns and other superstructure components – not just foundations – is highlighted.

Sep 8, 2021

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 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 S. R. Grobler, S. Bilessuris, M. E. Greenway

Ensuring that all the head ropes on a multi-rope friction winder share the load equally has been a design and maintenance issue since they were first developed. Accurate machining of the rope grooves is necessary to meet this objective. Early analysis of the change of rope loads for ropes in grooves that are mismatched in depth treated the grooves as rigid. Groove depth tolerances deduced from this analysis are stringent and difficult to achieve in practice. Test work indicated that the inherent flexibility of groove lining materials alleviates the load-sharing problem. However, no analysis of rope load changes due to mismatched flexible grooves has been published. In this paper we develop new equations for the rope load variation for flexible grooves. By allowing flexibility to reduce to zero, the corresponding rigid rope groove equations are obtained. New criteria for tolerable groove depth variations are developed from this analysis, which depend on the flexibility of the groove lining material.

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 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 H. Dudycz, A. Skoczylas, P. Stefaniak, P. Pyda

In the era of Industry 4.0, technologies such as Big Data (BD) and the Internet of Things (IoT) play a key role, especially for multi-site manufacturing companies. In such companies, the challenge is to collect and process massive amounts of data from industrial devices and extract key information from this data in real-time for ad hoc decision-making. The ability to analyse data from industrial devices translates directly into streamlined production processes, cost optimisation, prevention of unplanned events, and safety during operation. In this context, particular attention should be paid to Big Data Analytics (BDA), whose main source is the Industrial Internet of Things (IIoT). The purpose of this paper is to propose an IT system architecture incorporating BD and the IoT for a mining company. The paper presents results from a literature review focusing on available BD and the IoT solutions for industry (mining in particular) for the purposes of the acquisition, integration, and advanced analysis of data. The advantages and disadvantages of the different solutions were indicated and gaps in the accessibility to dedicated functionality are identified. Based on the analysis of a multi-site mining company, the main challenges faced by such companies planning to implement BD and IoT solutions are identified. Also, a proposal for an IT system architecture incorporating BD and IoT for a mining company is described in the paper. The contribution of the article consists of the identification of the challenges faced by mining companies planning to implement BD and the IoT solutions, and the proposal of an IT system architecture that allows BDA whose main source is the IIoT.

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. V. Lukichev, O. V. Nagovitsyn, V. V. Laptev

In this paper the authors describe the developed algorithms of short- and medium-term planning of underground mining operations. The algorithms were developed using the example of the flat-back cut-and-fill method, and provide multifactor accounting of mining conditions, technical and technological limitations: state and properties of the rock mass; the current mining situation; mining rules; availability of safety pillars; properties of the filling; additional characteristics of technological objects that complicate the driving of workings; sufficiency of human and technical resources; employee specialisation; existing machinery and equipment; opportunities and limitations of the transport scheme of the mine, and work schedule. The paper is presented by means of a dynamic model of mining development, which shows the sequence of mining operations in the mine workings. Besides animation, the tool provides an opportunity to form tabular and graphical reports.

Sep 1, 2021

By K. M. Seiler

Automation in mining requires accurate maps of road networks on site. Because roads on open-cut mines are dynamic in nature and continuously changing, manually updating road maps is tedious and error-prone. This paper investigates the possibility of automatically deriving an accurate representation of the road network using GPS data available from haul trucks operating on site. We present an overview of approaches proposed in literature and test the performance of publicly available methods on GPS data collected from trucks operating on site. Based on shortcomings seen in all tested algorithms, a post-processing step is developed which geometrically analyses the created road map for artefacts typical of free-drive areas on mine sites and significantly improves the quality of the final road network graph.

Sep 1, 2021

By Z. Saw, C. Poveda, N. L. Mai

Optimising the throughput of a mining network comprising all equipment from shovels to semi-autogenous grinding (SAG) mills is a complicated task, yet the potential benefits can be significant. Key modelling challenges stem from the sheer number of possible routes which material can travel, different equipment operating under different constraints, and the rate of SAG mills being calculated through a nonlinear function of the blended materials’ rock attributes. Nevertheless, this is an ideal onapplication area of mathematical programming, a branch of operations research. This paper describes an application of mixed integer linear programming (MILP) to optimise the mining equipment network of one of the world’s largest copper mines.The model takes as input a year-long monthly mine schedule of shovels in different pits, pushbacks, sequences and faces which produce material to be moved through a network of crushers, conveyors, silos, distributors, stockpiles and SAG mills, ultimately outputting a daily operational plan for all equipment that maximises the throughput of the network. All operational constraints and business rules are considered, including three quality attributes of copper ore. Comparing model results with actual data shows an improvement of 4.47% in network throughput tonnage. Additionally, although the model is solved using a free, open-source solver, optimal solutions are still achieved within a practical timeframe.

Sep 1, 2021

By N. Madani, S. Abulkhair

In multivariate geostatistics, it is common to have different types of complexities between variables of interest. In this context, an inequality constraint is an example of complex bivariate relationships. Unfortunately, traditional co-kriging and co-simulation algorithms cannot reproduce this type of bivariate complexity, leading to the overestimation of disturbing elements. This paper proposes a new algorithm based on a hierarchical sequential Gaussian co-simulation framework, integrated with inverse transform sampling, to model inequality constraints between variables. First, the proposed methodology's validity was evaluated by applying it to a real case study from an iron deposit, with an inequality constraint between iron and aluminum oxide. Then the simulated results were compared with a conventional hierarchical co-simulation algorithm to investigate the effect of inverse transform sampling on the quality of the co-simulation. The results showed that the proposed algorithm can reproduce an inequality constraint between variables.

Sep 1, 2021

By Stanisław Prusek, CHONG WEI, Huawei Xu, Jun Wang, Andrzej Walentek, Artur Dyczko, Derek B. Apel

The excavation-induced stresses transferred from the panels or pillars in upper coal seams play a key role in the occurrence of rockbursts in driving roadways during close-distance coal seam mining, which has become a common problem and threat to many underground mines. The authors established a 3D finite-difference numerical model via FLAC3D software using the closedistance coal seam mining conditions in the Zofiówka Mine as a case example to reveal the rockburst mechanism in such conditions. The excavation-induced vertical stresses are analyzed, which provides a basis to build a conceptual model to explain the possible source mechanism of the rockburst under such conditions. Nine typical rockburst indicators considering different contributing factors are then selected as the evaluation criteria to assess rockburst potential in the study site. The results suggest that the superposition of multiple excavation-induced stresses of the main drift and tailgate provides an environment for stress concentration and energy accumulation. The side abutment stress induced by mining in the upper coal seam has a “strengthening” effect to the rockburst occurrence. The great deviatoric stress induced by complex excavating situations is another important exterior cause. A strict calibration procedure should be implemented before using indicators to predict rockburst potential. A methodology was proposed to estimate the location and magnitude of rockbursts combined with numerical modeling, laboratory tests, and feedbacks from the field. The study could provide some references and guidelines for preventing and mitigating rockbursts in underground mines under similar engineering conditions.

Aug 26, 2021

By Dong Yang, Jicai Han, Xiaoshuang Guo, Tichang Sun, Zhengyao Li

Straw charcoal was used as a novel reductant in the co-reduction roasting of laterite ore and red mud. The influence of the reductant dosages, co-reduction temperature, and co-reduction time were investigated. Results showed that a powdered ferronickel product of 1.81wt.% nickel and 81.40wt.% iron was obtained under straw charcoal dosage of 15wt.% and roasted at 1250 °C for 80 min. The corresponding recovery of nickel and total iron were 97.21wt.% and 98.87wt.%, respectively. The performance of straw charcoal was also compared to that by the conventional coke reductant. Results showed that ferronickel particles using straw charcoal were larger in size than coke, mainly due to the lower S (0.14wt.%) and ash content (3.80wt.%), which could not hinder the agglomeration of the ferronickel grains, and lower melting point that producing liquid phase and promoting ferronickel particles growth. In addition, the gasification reactivity of straw charcoal is better than that of coke, which is beneficial to the iron oxide reduction and the recovery of iron. To conclude, straw charcoal is a promising reductant for the co-reduction of laterite ore and red mud in coal-deficient areas.

Aug 12, 2021

By Shahab Alizadeh, Ahmad Khodadadi Darban, Mehdi Mohseni, Mahmoud Abdollahy

This study probed the selective separation of lanthanum and yttrium in a nitrate medium in the presence of aluminum and calcium impurities using di-(2-ethylhexyl) phosphoric acid (D2EHPA). The factors studied in a central composite design (CCD) included extractant concentration, pH, concentration ratio of total impurities to rare earth elements, and interaction of these three factors. The extraction mechanism and types of extracted metal-containing species were delineated by the slope analysis method. The obtained thermodynamic data showed that lanthanum and yttrium extraction by the D2EHPA extractant was exothermic. The extraction of both rare earth elements was accompanied by an entropy reduction. The negative magnitude of ΔS in yttrium extraction reaction suggests stronger D2EHPA-Y(III) complexation relative to La(III). As entropy decreased and enthalpy increased, the extraction process became unspontaneous. Using the proposed flowsheet, lanthanum and yttrium products with > 90% purity were obtained.

Aug 10, 2021

By B. P. Watson, A. Carpede, W. O. Kekana, N. Fernandes, W. Theron, M. P. Mahlangu, G. Betz

The research described in this paper was done to confirm the Upper Group 2 (UG2) PlatMine peak pillar strength formula (Watson et al., 2007), which was determined from a back-analysis of failed and unfailed pillars. Underground measurements were made on a stable pillar that was loaded by firstly reducing it’s length and then by mining the surrounding pillars until pillar failure took place. The pillar was instrumented with suitably positioned strain cells and closure meters, which allowed both the average pillar stress and strain to be determined. The paper describes the methodology applied to identify a suitable position for the instrumentation, as well as the results. A stress/strain curve is presented for a UG2 pillar with a w/h ratio of 2.0, at Booysendal Platinum Mine. The measured pillar strength was similar to the predicted strength using the PlatMine pillar strength formula for UG2 pillars. The PlatMine formula has been successfully implemented on Booysendal Platinum Mine, and about 3 670 pillars have been cut without a single failure. An additional revenue of US$1.3 billion was calculated for the 25-year life of the mine as a direct result of the improved pillar design, given the January 2020 platinum group metals basket price. An extended life of mine and better mining efficiencies will also be realized.

Aug 1, 2021

By Manchao He, Xiaoding Xu, Yubing Gao

Based on the geological conditions of the 15,600 working face in Pingba Mine, this paper establishes the mechanical model of the stress distribution in the pre-working face under the influence of mining pressure based on a hemispherical stress distribution theory. The analytical formula for the stress distribution is determined. A numerical model for the mining pressure under the influence of key layer is also constructed, and dynamic stress interruptions under various roof-cutting relief schemes in different horizontal positions are simulated. The stress distribution of the stope under different pressure relief schemes is analyzed and compared with the theoretical results. Results show that blasting roof cutting blocks the transmission of the abutment pressure to the working surface to the coal and rock mass in front of the working face, reducing the significant working face mining pressure influence range, which decreases as blasting pressure relief position moves toward the working face. Stress accumulation in the coal in front of the working face also increases as the blasting pressure relief position moves toward the working surface. Engineering practice results show that blasting cutting can effectively block the propagation of mining pressure, and the stress impact range is shortened by approximately 1/3.

Jul 31, 2021

By Chiranjibi Santi, Amit Kumar Gorai, VIVEK KUMAR HIMANSHU

Air overpressure (AOp) and peak particle velocity (PPV) are the most undesirable effects of blasting in mines. It is an urgent need to design a predictor model for AOp and PPV for universal applications to minimize environmental effects and damages that occur due to blasting. The present study attempts to design an artificial neural network (ANN) model for the prediction of AOp and PPV in different conditions. In this study, the blast design parameters (number of holes, depth of the blast hole, stemming length, spacing, burden, distance of vibration monitoring location from the blast site, charge weight per delay) of two active mines (coal and iron ore) are considered in four different conditions for training and testing of the model for the prediction of AOp and PPV. The model was trained and tested in four different combinations of data (trained using data of one mine and tested using data of another mine, trained and tested using data of coal mine, trained and tested using data of an iron ore mine, trained and tested using combined data of both the mines) for examining the applicability in different conditions. The results indicate that R2 values are ranged from 0.886 to 0.908 and 0.8728 to 0.8959, respectively, in the prediction of PPV and AOp. A comparative study of the performances of the developed model with the other empirical model is also demonstrated. For this, the site constants of different empirical models were estimated individually for both the mines. The study results indicated that the ANN model performs much better than all the empirical models. It can be inferred from the results that blast vibration cannot be accurately predicted only from charge per delay and distance from the blast hole. The ANN model was considered many other factors and thus can predict the vibration level more accurately.

Jul 30, 2021

By Nikhil Dhawan, SHAILA MIR

The emerging problem of electronic waste has promoted the interest in exploring metal recovery from secondary sources under the umbrella of urban mining. This study presents the physical and chemical characterization of various components present in end-of-life laptops to help ascertain the sites of metallic values and develop sustainable and environment-friendly recycling. The recycling potential of a laptop is evaluated by sequential disassembly, separation, and characterization of components such as body (49.8 wt.%), printed circuit board (9.7 wt.%), hard disk drive (4.9 wt.%), and battery (12.4 wt.%). The printed circuit boards comprise metallic values, majorly copper (25 wt.%), tin (5.8 wt.%), and lead (3.1 wt.%). The precious metals (Au, Ag) with an economic advantage are abundantly present in electronic components such as integrated circuits, capacitors, resistors, and processors. Critical elements such as lithium, cobalt, and rare earth elements are detected in the discarded laptops' batteries and hard disk drives. The recycling potential representing the amount of material that can be recycled in various components, depending on the type, concentration, and purity, is determined in the range of 36–100%. On average, a unit laptop contains~ 386 g of Cu (14.45 wt. %), 49.73 g Co (1.86 wt. %), ~346 mg Ag, ~141.2 mg Au, ~650 mg of rare earth elements (Nd, Dy). This study presents a database for investigating integrated and economical recycling techniques from different components of a laptop, and an overall process flow is also proposed.

Jul 24, 2021