Open Pit Research Articles

Thiosulfate leaching in carbonaceous gold-bearing ores in Ethiopia

One of the main unit operations in metallurgical processing plant designs is gold leaching. The traditional cyanidation process was chosen and is currently in widespread use. However, the mining sector is looking for lixiviants other than cyanide. Cyanide’s effects on the environment have made it difficult for humans and other biotic creatures to survive. There is now research to discover a substitute for this cyanide. It is currently argued that thiosulfate is a preferable substitute for cyanide. The effectiveness of thiosulfate as a leaching agent in carbonaceous gold-bearing ores in Ethiopia is discussed in this paper compared to cyanide. The study has looked into the advantages of employing thiosulfate over cyanide from a technical, and economic standpoint. The leaching effects of both lixiviants on carbonaceous gold-bearing ores extracted from MIDROC Legadembi Open Pit mine in Southern Ethiopia, Oromia region, were examined in a laboratory experiment. After 48 h of leaching, it was discovered that thiosulfate has a better and quicker recovery of 91.54% over 61.70% of cyanide recovery. Tables and graphs are used to demonstrate thiosulfate’s technical advantage over cyanide. As a result, this paper provides evidence regarding the Legadembi gold mine in Ethiopia’s amenability to thiosulfate leaching on carbonaceous gold-bearing ores. A further research perspective is also sought for thiosulfate leaching in other refractory ores.

Landslide Characteristics and Stability Control of Bedding Rock Slope: A Case Study in the Sijiaying Open-Pit Mine

Landslide Characteristics and Stability Control of Bedding Rock Slope: A Case Study in the Sijiaying Open-Pit Mine

Leveraging machine learning and Landsat time series for high-resolution mapping of mining-induced vegetation changes in Ouagadougou, Burkina Faso

Quarries are open pit mines, where construction materials such as granite and clay are extracted from the earth's surface, leading to a major disturbance of vegetation and subsequent degradation of ecosystem services. Assessing mining-associated degradation over time remains a challenge. This paper uses a temporal series of Landsat satellite image extracted from Google Earth Engine (GEE) for monitoring mining effects on land cover around the West African city of Ouagadougou, Burkina Faso. We conducted a binary classification of quarry and non-quarry using Landsat 9 images. To account for varying quarry patterns, we applied the LandTrendr algorithm to analyze images from 1990 to 2022, mapping annual vegetation disturbance and recovery. This generated high-resolution land cover maps with over 90 % accuracy across 257 quarries (38 km²). LandTrendr identified disturbance years with 87 % accuracy and assessed recovery in abandoned quarries. Remote sensing accuracy was validated through fieldwork and analysis of historical aerial photos. Our findings revealed that major disturbances coincided with new quarrying activities, particularly during urban expansion from 2005 to 2019, with NDVI decreasing by 0.3 in active mining areas. Vegetation recovery was observed in 23 % of the abandoned quarries, with NDVI increases by 0.15 within five years post abandonment, particularly in clay quarries. The strongest recovery occurred in given up abandoned from 2015 to 2019, aligned with increased conservation efforts. Our approach offers valuable insights into mining impacts and vegetation resilience in semi-arid environments, informing sustainable urban planning and environmental management in rapidly transforming regions of West Africa.

Sentiment analysis of student feedback: A comparative study employing lexicon and machine learning techniques

One of the most pressing concerns in contemporary education examines the integration of big data and artificial intelligence methodologies to enhance the educational learning outcome. Towards that purpose, it is imperative to leverage the unstructured data originating from student feedback, particularly in the form of comments to open-ended questions aiming to extract emotions and opinions conveyed within their messages. Our research goal is to ascertain the most efficient approach to tackle this difficult task by conducting a comparison of sentiment analysis methods, including Machine Learning (ML) and Lexicon based models. Both lexicon based and machine learning approaches were implemented using an open source data mining platform while also utilizing student comments submitted at the end of academic semesters. Our study reveals a promising approach that effectively addresses the issue at hand, particularly within the domain of educational data. Additionally, it emphasizes the key aspects that led to the selection of this approach effectively highlighting the weaknesses and strengths inherent in each method

Mechanisms of microbial diversity modulation of mineral black clay to achieve ecological restoration of open-pit mine dump

The harsh climatic conditions and severe scarcity of surface soil present significant challenges to ecological restoration in open-pit mine dumps within China's type II plant cold resistance zone. To address the topsoil shortage, mineral black clay was used to create synthetic soil. This study explored the application of an ecological restoration bacteria (ERB) consortium to accelerate the ecological restoration of synthetic soil-covered areas by enhancing soil ecosystem construction. The results demonstrated that ERB significantly influenced the native bacterial community structure in mixed black clay. Specifically, ERB disrupted the inhibitory effects of the Actinobacterota phylum on the development of native bacterial diversity, leading to an increase in unclassified_o_Solirubrobacterales sp., norank_f_norank_o_norank_c_KD4-96 sp., Sphingomonas sp., Luteitalea sp., norank_f_Vicinamibacteraceae sp., and other aerobic and anaerobic bacteria. These alterations in soil microbial structure directly impacted soil composition and vegetation diversity. The plant diversity survey and metabolomics analysis revealed that the reduction of harmful substances, such as HPED, HODE, and HOME, in black clay soil improved the growth and distribution of Salsola collina Pall. and Medicago sativa L. This increase facilitated the cycling of key nutrients, such as nitrogen (N) and phosphorus (P), and promoted the establishment of symbiotic relationships between plants, microorganisms, and soil. Ultimately, the ecological remediation of the synthetic soil was achieved through the synergistic effects of ERB, which included the degradation of inhibitory soil components, enhanced nutrient consumption by microbiota and plants, and the overall promotion of ecosystem stability in the reclamation area.

A Stochastic Energy-Efficient Robust Simulation-Based Truck Dispatching Optimization for Simultaneous GHG Mitigation and Operational Excellence in Open-Pit Mines

Almost all currently active large open-pit mines across the globe heavily rely on fleet of shovels and haul trucks for material handling. This material handling system has a significant contribution not only to the production cost of the mine (+50%), but also to its energy consumption (+41%) and greenhouse gas (GHG) emissions (+37%). However, traditionally, operation management in general and truck dispatching, in particular, focused primarily on production targets and operational efficiency, neglecting environmental considerations in open-pit mines. Nowadays, growing awareness of climate change and responsible resource extraction has shifted, however, the focus towards sustainable practices throughout the mining industry, open-pit mining not excluded. The significant contribution of this study lies in the development of an integrated simulation and optimization framework that simultaneously accounts for anthropogenic GHG emissions resulting from energy (fuel) consumption and enhances the operational efficiency of the material handling system, thus yielding direct economic and environmental benefits. The paper fulfills its goals with the aim of simultaneous achievement of four interdependent objectives: minimizing the deviations from target production rates set by strategic plans, minimizing the shovel idle time, minimizing the truck wait time, and minimizing the truck fuel consumption. The performance and the robustness of the proposed framework has been evaluated in a case study at Gol-E-Gohar mine in Iran, demonstrating a successful achievement of up to 6% reduction in fuel consumption per tonne of production leading to a significant overall decrease of up to 20,000 liters in fuel consumption, equivalent to 61,000 carbon dioxide (CO2) emissions, in a 10-day operation with 12 hours of operation per day.

Regular short‐term evaluation of slopes in open pit mines

Regular short‐term evaluation of slopes in open pit mines

Long-term open-pit mining activities at the world's largest light rare earth mine significantly affect light rare earth elements in road dust over long distances

The long-term effects of decades of open-pit mining at the Bayan Obo deposit, the world's largest light rare earth mine, on the concentrations of several elements in road dust over long distances are unknown. Here, bulk road dust (BRD) and resuspended road dust (RRD) were collected from different distances from the mine for subsequent analysis of mining impacts. As a result of mining activities, light rare earth elements (LREEs), especially La, Ce, Pr and Nd, show different statistical and spatial variations compared to other elements. These LREEs decrease with increasing distance from the mine, and the values found in RRD are higher than those in other particle sizes. Mining emissions and soil have the most significant influence on these LREEs compared to other factors. Spatially, these four LREEs changed significantly over a large area (up to 60km from the mine) due to mining emissions. However, long-term mining activities affect these elements mainly through mining-contaminated soil as opposed to mining emissions. This study confirms the significant impact of mining activities on LREEs in road dust via a comprehensive data-driven framework, emphasizing the significant environmental effects of long-term open pit mining.

Discovery and Underground Mining of Large Deposits: Essential Training to Ensure Copper Supply

Editor’s note: The aim of the Geology and Mining series is to introduce early career professionals and students to various aspects of mineral exploration, development, and mining in order to share the experiences and insight of each author on the myriad of topics involved with the mineral industry and the ways in which geoscientists contribute to each. Abstract A supply shortfall of at least 6 million tonnes (Mt) Cu is expected by 2031—with total demand now forecast to increase from 25 Mt in 2023 to >36 Mt, and possibly to a suggested 50 Mt by 2050—given the present trend in demand. The deficit can be partially filled by increased mine production, expanding currently installed mine production capacity, and increasing Cu recycling. However, satisfying demand in 2050 as the demand-to-mining supply gap increases will require the accelerated discovery of at least five large Cu deposits—individually producing >0.5 to >1.0 Mt/yr Cu—and their related mine development, by 2030. These five deposit discoveries are required to replace mines scheduled to close in the 2050s, given the >20 years needed to take a deposit from discovery to mine production. The two largest sources of Cu supply, porphyry and sediment-hosted Cu deposits, can potentially fill the gap if enough discoveries are made; however, there is no evidence that this is about to occur. Future porphyry Cu discoveries are expected to be mined underground, mostly by a caving method. The demand increase is occurring at a time when the capital intensity of porphyry Cu mine development has almost doubled since 2006. We predict that the only solution to the future Cu demand-supply challenge for society and the mining industry in the short to medium term rests with simple demand-supply economics and a substantially increased Cu price. Copper substitution by other materials and recycling could potentially benefit from a significantly increased price; however, the major advantage will be conferred on deposits amenable to open-pit mining that are undeveloped because of price-dependent, failed feasibility studies. The challenge of possibly doubling Cu supply by ca. 2050 through developing mines on large Cu deposits—both discovered and undiscovered, in an unprecedented number and in a shorter period—will require a major increase in the number of competent mining industry personnel. This comes at a time when the industry faces an aging workforce, leading to a critical skills gap compounded by a chronic shortage of students graduating in the sciences and engineering with mining-related university degrees. There is an acute shortage of experienced professionals in cave mining, and the substantial number of open-pit mining professionals who are predicted to retire by 2030 will need to be replaced. On-the-job training of geoscientists and engineers after graduation, delivered by experienced practitioners through university-accredited professional development programs, is suggested as the solution.

A comprehensive study on the application of soft computing methods in predicting and evaluating rock fragmentation in an opencast mining

A comprehensive study on the application of soft computing methods in predicting and evaluating rock fragmentation in an opencast mining

How do high phosphate concentrations affect soil microbial communities after a century of ecosystem self-reclamation?

The use of rock phosphate (RP) instead of soluble phosphate fertilizers is preferred for the development of more sustainable agriculture. However, the impact of high concentrations in RP on bacterial and fungal communities remains poorly documented. Thus, next-generation sequencing was used to characterize bacterial and fungal communities in the soils and roots of four plant species growing naturally in a self-restored ecosystem, on former open-pit phosphate mines where past exploitation generated locally a substantial phosphate enrichment of the soil. Our results show that bacterial communities are dominated by Actinobacteria and Proteobacteria phyla, while the Ascomycota and Basidiomycota phyla predominate in the fungal community. The alpha and beta diversities of both bacterial and fungal communities differ significantly between the root and soil compartments but are not significantly affected by RP inputs. However, Amplicon Sequence Variants (ASVs) indicative of RP-enriched soils have been identified; among them are bacteria representative of Streptomyces, Bacillus, Mycobacterium or Agromyces. Implications of these results open new ways of reflection to understand the microbial response following RP-inputs and long-term soil restoration, as well as to formulate microbial-based bioinoculants for sustainable agriculture applications based on microorganisms better adapted to high concentrations of RP.

Разработка трудноизвлекаемых запасов угля мобильными горнодобывающими комплексами без постоянного присутствия людей в зоне ведения горных работ

Today, millions of tons of coil remain in the subsoil and are written off as losses. These include hard-to-recover reserves unfit for mining with traditional high-performance means of integrated mechanization. One of the all-purpose technical solutions to the problem of developing such reserves can be technologies using robotic mobile mining equipment based on a heading-and-winning machine and a self-propelled car. Flowcharts for coal deposit development have been designed for seams unfit for mining with integrated mechanization means (medium thick seams, thick seams, flat and steeply inclined seams). These include open-pit and underground mining of marginal reserves from the side of the pit wall and limited reserves from the daytime surface performed by mobile mechanization means. During the operation of these means, the following process operations are repeated: coal breaking, loading into a self-propelled car, transportation along a preset trajectory, unloading into a reloader or other transport vehicle, or a warehouse on the bench. These operations can be robotized, which will increase both the safety and efficiency of coal mining. In order to perform coal-mining operations without constant attendance of maintenance staff, the existing mechanization means must be retrofitted with machine vision and a remote control system. Moreover, a robotized control system for the set of equipment must be developed to resolve the following problems. For the heading-and-winning machine: transportation (feed) along a straight line; transportation along the preset curve (formation of a diagonal entry); coal breaking at the preset thickness; coal breaking within coal-rock boundaries or along a preset cross-sectional contour; loading of broken coal into a self-propelled car; and control of the car loading level. For a self-propelled car: transportation along a preset trajectory from the loading point to the unloading point; control and management of the completeness of loading (unloading).

The Impact of Open-Cast Diabase Mining at Niedźwiedzia Góra Quarry in Southern Poland on the Surrounding Forest Ecosystems

The Impact of Open-Cast Diabase Mining at Niedźwiedzia Góra Quarry in Southern Poland on the Surrounding Forest Ecosystems

Analysis of the mining equipment replacement time. A case study focused on drilling rig

Mining equipment is subjected to degradation throughout its operation lifetime, being the definition of the replacement time for mining equipment a vital question. Requiring accurate information about the performance of the equipment to identify the optimal replacement time. This study determines the replacement time using an improved method, Overall Mining Equipment Effectiveness (OMEE), that analyses the technical factors from mining equipment performance in real-time, such as the technical availability rate, the mechanical availability rate, the production rate and the productivity index. The suitability of the method has been tested using a real open pit mine and information gathered from six drilling rigs, which have been performing around 27,000 engine hours each, over the last twelve years. The results obtained show that the OMME methodology is reliable to analyse the mining equipment performance and determine the technical replacement time.

Model of environmental management due to coal mining on the Separi River in Tenggarong Seberang District, Kutai Kartanegara Regency, East Kalimantan Province

Coal mining has a significant impact on reducing river water quality. The decline in river water quality causes problems for human life and the environment. Therefore, this research aimed to evaluate river water quality and develop strategies for improving river water quality due to open pit coal mining activities in Tenggarong Seberang District and develop environmental improvement strategies. Several chemical parameters, including pH, TSS, Fe, and Mn, were observed through laboratory tests to determine water quality in the Separi River used in coal mining. The next step was determining environmental improvement strategies using the ISM approach. Twenty stakeholders from related agencies and institutions using FGD were involved in developing a policy strategy. The results of the analysis showed that there has been a decrease in river water quality standards due to mining activities in the research area, and the quality is still below the standard quality. Therefore, two significant strategies must be a priority for the environmental management of the Separi River. First, Conducting an environmental audit of the factors causing the decline in river water quality is necessary. Second, there must be warnings and legal sanctions for negligence in oil spills and oil used from coal mining.

Rectifying Discrepancies Between GB-SAR Images and Terrain Model Caused by Measurement Deviations in Open-Pit Mines

Ground-based Interferometric Synthetic Aperture Radar (GB-InSAR) is a valuable technique for monitoring deformation of landslides. GB-InSAR can construct high-resolution 2D images in a range-doppler plane. However, it is difficult for geo-engineers who are unfamiliar with radar monitoring geometry to interpret the results. Geometric mapping method has been applied to the co-registration of terrain models and radar images for the deformation zonation, but the mismatching correction with GB-InSAR and terrain model is not fully investigated by existing researches. To address this issue, this paper proposes a method exploiting an optimum linear transformation based on ground control points (GCPs). The proposed method was evaluated on simulated data and a field campaign in an open pit mine. The deformation mapping result of the method was verified by a collapse event. The method proposed in this paper has an RMSE value ranging from 0.502 to 0.720[Formula: see text]m (@700[Formula: see text]m average monitoring range) when the average density of the terrain point cloud is 0.5[Formula: see text]m. Although this method cannot accurately evaluate the antenna footprint vector deflection parameters, it can meet the needs of coarse matching calibration in relatively flat slope sub-target areas of open-pit mines for engineering applications.

State-of-the-art optimization methods for short-term mine planning

Maintaining short-term planning aligned with the ultimate long-term plan is challenging. This requires many details to be modelled on a daily or weekly basis to reach this target. Short-term planning is more challenging than medium- and long-term planning because it deals with uncertainties, which increases the gap between medium- and long-term plans. Short-term mine planning teams are expected to identify and manage potential risks to mitigate them, and eventually achieve the long-term objective of maximizing the Net Present Value (NPV). Very few studies have identified the problems that exist in short-term mine planning and provided technical solutions to overcome them for open-pit mines. One of the complexities associated with short-term planning is the creation of polygons or mining cuts by clustering before optimizing and scheduling the plan to reduce the computational expense of mine planning models. The primary objective of this study is to review the latest papers describing short-term mine planning challenges and technical solutions proposed to optimize mine planning for open-pit mines.

Optimisation of open pit slope design considering groundwater effects using particle swarm optimisation and scaled boundary finite element method

Slopes are a crucial structures in open pit mines. Their design has implications on the economic, safety and environmental operation of the mining industry. Designing stable slopes can be challenging due to the complexities introduced by the stratigraphy and hydrology of the strata. With rising commodity costs and inflation rates, mining operating costs are increasing. Reducing operational costs is necessary for mining industries to remain competitive. While steepening the pit slope can decrease stripping materials and save money, it also increases the risk associated with slope surges. Therefore, optimising slopes is crucial for both financial and safety reasons. Numerical models such as the finite element method experience challenges in mesh generation of heterogeneous systems characterised by varying material properties and stratigraphies. Moreover, the need for repetitive geometry update necessitates recursive mesh regeneration that increases the computational burden. Moreover, previous slope optimisation studies focus solely on dry conditions. To consider the complex condition of hydrology along with heterogeneity in the soil stratigraphy, this study develops an optimisation procedure by combining the particle swarm optimisation algorithm and the scaled boundary finite element with an image-based meshing technique to optimise slopes with groundwater and achieve the desired factor of safety (FoS). The method changes the slope design parameters and the phreatic surface of groundwater simultaneously, considering user-defined parameters while iteratively re-meshing the optimisation processes. Several cases are presented, demonstrating the optimisation of bench width, bench angle, backfill parameters, and groundwater pumping levels.

Landslide failure time prediction with a new model: case studies in Fushun west open pit mine, China

Landslide failure time prediction with a new model: case studies in Fushun west open pit mine, China

Scheduling as a Constraint Satisfaction Problem (Using the Example of Open-Pit Minе Production Scheduling Problem)

The research described in the work is aimed at developing methods for Scheduling. The fundamental disadvantage of the existing methods of Mixed-Integer Linear Programming in application to the problems under consideration is the fact that they are too demanding on the amount of RAM. The difficulty of applying local search procedures to such high-dimensional problems is to develop an effective way to find an acceptable initial approximation and determine the neighboring state transition function, which would allow achieving the optimum fast enough. In the Operations Research Theory, adding additional conditions to a problem can lead to a fundamental change in the problem-solving scheme. The methods proposed in the study are implemented within the framework of the Constraint Programming Paradigm which makes it possible to represent the subject domain dependencies saving RAM, as well as to provide the ability to step-by-step take into account heterogeneous problem conditions without essentially changing the scheme of finding solutions. A significant part of the research deals with methods of logical inference on constraints to reduce the search space and speed up the computational process. The approach to scheduling is illustrated by the Open-Pit Mine Production Scheduling Problem, which was first proposed to be solved as a Constraint Satisfaction Problem. In order to find the first feasible solution, a «greedy» search method is proposed, the result of which can be improved using the developed hybrid method. Both methods rely on original procedures of inference on constraints. The proposed approach has proven its efficiency for block models with sizes of tens and hundreds of thousands of blocks.