Mining

Autonomous navigation is a key requirement for underground mine automation, where the choice of a suitable global path planner plays a significant role. In this study, four representative planning approaches—Dijkstra’s algorithm, A*, Rapidly exploring Random Tree (RRT*), and Particle Swarm Optimization (PSO)—were evaluated on a differential-drive mobile robot within the ROS navigation framework. The algorithms were tested in two simulated underground environments: a room-and-pillar layout with relatively open space and multiple path alternatives and a narrow tunnel scenario designed to reflect more constrained mining conditions. The results indicate that Dijkstra’s algorithm consistently produced the shortest paths with the lowest computation times, while A* showed comparable performance with slightly higher computational effort. RRT* required modifications to operate effectively in narrow tunnels and exhibited significantly longer planning times. PSO, although capable of generating near-optimal solutions in open spaces, showed limitations in constrained environments due to collision handling and path feasibility issues. Differences in replanning behavior were observed when unknown obstacles were introduced. Overall, graph-based planners such as A* and Dijkstra’s algorithm demonstrated more stable and predictable performance. Future work will focus on validating these findings in real mining environments, particularly considering wheel slippage, sensor noise, and path generation challenges in narrow tunnel conditions. Full article

While conventional numerical studies often treat excavated stopes as empty voids or as backfilled, few investigations have simulated the post-mining void as a weak granular caved rock material that evolves naturally from a hanging wall failure. This study addresses this gap by modeling the caved rock progressively, which makes the excavation representation more realistic for sublevel caving operations. This study introduces stope stability for the Zarmitan gold mine in Uzbekistan, where mining occurs at about a 500 m depth in a narrow quartz vein. A hybrid approach combining empirical and numerical methods was adopted. The Mathews stability graph method provided initial design guidance, while three-dimensional FLAC3D numerical modeling was used to simulate the mining sequence with explicit representation of caved rock behavior. A various study was conducted, which included the effects of stress ratio, stope length along strike, and pillar thickness on overall stability. The obtained results show that the stress ratio is the dominant factor controlling stope behavior. Stope length significantly affects failure extent, with shorter stopes showing better performance under similar conditions. Pillar thickness was found to improve stability and reduce tensile stresses in critical areas, though in all cases, hanging wall support remains essential. The numerical results confirm empirical predictions while providing quantitative insights into stress distributions and failure mechanisms not captured by empirical methods alone. These results provide mine operators with quantitative, site-specific design criteria, most notably that, under the measured high horizontal stress, limiting stope length to 40 m and increasing pillar thickness to 8 m substantially improves hanging wall stability, which demonstrates how a hybrid empirical-numerical methodology can directly support safer and more economic extraction in deep, narrow-vein operations. Full article

Flotation is a fundamental unit operation in mineral processing; however, achieving high selectivity while reducing the environmental impact of reagents remains a major challenge in phosphate ore beneficiation. Conventional depressants often exhibit limited selectivity and may pose environmental concerns, highlighting the need for sustainable alternatives. This study reports, for the first time, the application of starch nanostructures derived from potato pulp processing residues as a depressant in phosphate flotation, representing an innovative and eco-friendly approach. An exploratory and experimental methodology was adopted, including nanostarch synthesis via acid hydrolysis followed by centrifugation and sonication, as well as comprehensive physicochemical characterization. The primary objective was to evaluate the selective depressant performance of the nanomaterial in apatite–calcite flotation systems. The synthesized nanostructures exhibited particle diameters ranging from 179 to 443.6 nm. Microflotation tests conducted in a Hallimond tube using pure mineral samples under alkaline conditions (pH ≈ 9), at a depressant dosage of 500 mg/L and in combination with a plant-based fatty acid collector, revealed a pronounced selectivity window, resulting in an approximately 77% difference in flotation recovery between apatite and calcite. These findings demonstrate that nanostarch derived from agro-industrial residues is a promising, biodegradable, and sustainable depressant capable of enhancing selectivity in phosphate flotation. The results contribute to the advancement of greener mineral processing Technologies, although Further studies are required to elucidate the underlying interaction mechanisms. Full article

Metallurgical coal operations are a significant but poorly constrained source of methane (CH₄) in Canada. We present a multi-instrument analysis of 63 methane plume detections at Fording River Operations, British Columbia (January 2022–March 2026), using the Airborne Visible/Infrared Imaging Spectrometer—Next Generation (AVIRIS-NG; n = 39), the Earth Surface Mineral Dust Source Investigation (EMIT; n = 4) and Tanager-1 (n = 20). Of these, 41 plumes (65%) were quantified, with retrieved emission rates of 34–3622 kg CH₄ h⁻¹; 54% exceeded the 500 kg h⁻¹ super-emitter threshold. Because 73% of detections fall in September and no detections are available for 2023, results characterize the late-summer overpass window and should not be extrapolated seasonally without further coverage. The central finding is a systematic, asymmetric wind-speed disagreement between two numerical weather prediction (NWP) products that maps onto the Integrated Mass Enhancement (IME) quantification outcome. A univariate logistic regression identifies HRRR wind speed as a significant predictor of quantification success (OR = 0.29 per m s⁻¹, 95% CI [0.15, 0.56], p < 0.001; AUC = 0.80; 5-fold cross-validated AUC = 0.79 ± 0.20, fold range 0.45–1.00). Cross-validation against ERA5-Land shows that HRRR exceeds ERA5 by a mean of +0.86 m s⁻¹ (+43%) for unquantified events but shows near-zero disagreement for quantified events (–0.09 m s⁻¹, –6%). A sensitivity analysis restricted to HRRR-forced retrievals (EMIT + Tanager-1, n = 24) confirms the finding is not an artefact of mixed wind data sources (OR = 0.28, AUC = 0.83, p = 0.018). Full article

The Carajás Province, located in the southeastern Amazon, hosts some of the world’s largest high-grade iron deposits. Despite their economic importance, the processes linking lateritic weathering and iron enrichment remain incompletely understood. This study investigates the role of lateritic weathering in the evolution of the Serra Leste iron deposit through the characterization of a weathering profile and its parent rocks using drill-core samples. Analytical methods included X-ray diffraction (XRD), optical microscopy, scanning electron microscopy coupled with energy-dispersive spectroscopy (SEM-EDS), whole-rock geochemistry, and Mössbauer spectroscopy. Jaspilites weathered into ferruginous saprolite while preserving relic banding and mineral textures. Magnetite alteration produced pseudomorphic hematite with dissolution cavities progressively infilled by goethite, indicating iron remobilization during weathering. Weathering of chloritites generated clayey saprolite enriched in kaolinite and iron oxyhydroxides, with gibbsite occurring in more advanced stages. The uppermost horizon consists of a ferroaluminous duricrust composed of massive, spherulitic, and brecciated iron oxyhydroxides associated with gibbsite. Up-profile geochemical trends are marked by decreasing SiO₂ and increasing Fe₂O₃. The mineralogical, textural, and geochemical relationships indicate that the ferroaluminous duricrust was developed through contributions from both ferruginous and clayey saprolitic systems, particularly from the latter. These results support the interpretation that lateritic weathering played an important role in iron redistribution and supergene enrichment within the Serra Leste deposit, consistent with mature Amazonian lateritic systems. Full article

Compressed CO₂ energy storage (CCES) in deep sedimentary basins offers a promising option to integrate carbon management with long-duration energy storage. However, most existing subsurface energy-storage studies focus on salt caverns or generic porous reservoirs, while the potential of evaporite-bounded carbonate reservoirs remains insufficiently explored. This study presents the first application-oriented numerical assessment of CCES in Southern Ontario. It investigates the feasibility of CCES in the Upper Silurian Salina Group beneath offshore Lake Huron, focusing on a porous A-2 carbonate interval vertically confined by B and A-2 halite caprocks. A fully coupled three-dimensional thermo-hydro-mechanical model is developed in COMSOL Multiphysics 6.3 to simulate two-phase (brine-CO₂) Darcy flow, heat transfer, and poroelastic deformation under a realistic Michigan Basin stress, pressure and geothermal regime. After an initial cushion-gas stage at 8 kg/s that establishes a caprock-parallel supercritical CO₂ wedge beneath the B-salt, 24 h injection-production cycles are imposed for two years, followed by a five-month high-resolution window. Three well completion strategies are compared: full-length, upper-only, and split (upper + lower) perforations. Results indicate that in all simulations the CO₂ plume stabilizes as a persistent gas cap beneath the B-salt, far-field pressures remain close to hydrostatic, and reservoir deformations are very small, pointing to a substantial geomechanical safety margin. Among the three completion strategies, the split completion provides the best compromise: it maintains high and relatively stable CO₂ production while avoiding the stronger lower-zone depressurisation seen in the full-length case and the more limited working volume of the upper-only case. These findings suggest that a Salina A-2 carbonate reservoir bounded by B and A-2 salts can accommodate cyclic CCES under realistic basin conditions, and that appropriately designed split completions offer a practical balance between storage utilisation and operational robustness in this setting. Full article

Blasting-induced ground vibrations, typically quantified by peak particle velocity (PPV), pose one of the most critical environmental challenges in surface mining and can damage nearby structures and disrupt surrounding ecosystems. Consequently, the development of reliable and accurate predictive models is essential for designing safe, environmentally responsible, and sustainable blasting operations. This study develops a robust predictive framework using a harmonized database of 506 blasting events, from which 386 high-quality records were retained after preprocessing to model PPV as a function of charge per delay (Q), monitoring distance (R), and rock mass rating (RMR). Several machine learning (ML) algorithms, including artificial neural networks trained using the Levenberg–Marquardt algorithm (ANN-LM), adaptive neuro-fuzzy inference systems (ANFIS), Gaussian process regression (GPR), and decision trees (DT), were evaluated alongside conventional empirical models such as the USBM, Ambraseys–Hendron, Langefors–Kihlstrom, and BIS. To further enhance predictive capability, two optimization strategies, Bayesian optimization (BO) and differential evolution (DE), were applied to the GPR model, producing optimized BO-GPR and DE-GPR variants. Model performance was assessed using the correlation coefficient (r), variance accounted for (VAF), mean absolute error (MAE), and relative root mean square error (RRMSE). Results indicate that the BO-GPR model achieved the best predictive performance during testing for both the two-input (Q, R) and three-input (Q, R, RMR) configurations, with r values of 0.97426 and 0.98381, respectively, and VAF values exceeding 94%. SHAP analysis revealed monitoring distance as the dominant attenuating factor controlling PPV. The optimized framework provides an accurate, interpretable tool for vibration prediction and precision blast design, supporting environmentally responsible, sustainable mining operations. Full article

This paper presents a comprehensive methodology for assessing supply chain transparency and resiliency using a data-driven approach. Leveraging global trade data and Harmonized System (HS) codes, the methodology maps each stage of the supply chain to enhance regulatory compliance and mitigate operational risks. Transparency is evaluated using a novel classification system that categorizes branches as fully transparent, highly transparent, moderately transparent, or non-transparent. This enables raw material traceability, Scope 3 greenhouse gas (GHG) emission estimation, and identification of high-emission nodes for targeted reductions. Resiliency is assessed through graph analytics and stress testing, incorporating metrics such as the Giant Connected Component (GCC) and probabilistic simulations to analyze vulnerabilities and develop recovery strategies. A case study on the Cr-13 Steel Drill Pipe supply chain highlights the benefits of incorporating scrap materials for sustainability, alongside challenges related to traceability due to regulatory gaps and non-transparent networks. Monte Carlo simulations identify critical nodes whose disruption significantly affects network connectivity; therefore, resiliency, and transparency. This methodology delivers actionable insights to improve supply chain resiliency, sustainability, and operational efficiency. It is scalable across industries, enabling stakeholders to optimize management strategies, align with global climate initiatives, and build resilient and transparent networks. Full article

Quantifying time-dependent rock mass degradation is critical for assessing long-term slope stability during open-pit mine closure. This study evaluates the geotechnical evolution of Paleoproterozoic arenites and argillites in the semi-arid Essakane Main Zone (Burkina Faso) over a 0–9-year atmospheric exposure period. Field characterization across 32 sampling stations included density measurements, point load testing (I_s(50)), determination of the Geological Strength Index (GSI), and petrographic analysis. The results demonstrate a time-dependent reduction in physico-mechanical properties, modeled with a high correlation (R² = 0.80–0.99). While density exhibited minor reductions, structural degradation was pronounced; the GSI decreased by 10 points for both lithologies, and I_s(50) dropped significantly, particularly in argillites (4.1 to 2.3 MPa) relative to arenites (4.0 to 3.6 MPa). Petrographic evidence indicates negligible chemical weathering and mineral neoformation. Consequently, the degradation was attributed primarily to physical processes, specifically microcracking and discontinuity deterioration driven by thermal cycling and phyllosilicate sensitivity in argillites. These empirical relationships provide essential quantitative input for numerical slope stability modeling in semi-arid mine closure scenarios. Full article

Uranium is a resource with exceptionally high energy density, releasing substantially more energy per unit mass than conventional fossil fuels. In uranium mining, in situ leaching offers significant advantages over open-pit and underground mining, including reduced environmental impact, lower operational costs, enhanced safety, and improved controllability. Within the in situ leaching framework, acid leaching faces limitations in high-carbonate ore bodies, while alkaline leaching is unsuitable for deposits rich in pyrite and other sulfide minerals due to side reactions and precipitate formation that hinder leaching efficiency. In contrast, CO₂-O₂ leaching, as a neutral leaching approach, exhibits broader applicability across diverse ore types and geological settings. Incorporating CO₂ into the leaching process also enables carbon utilization, offering a potential pathway to cleaner uranium extraction aligned with carbon reduction and sustainable energy goals. This review systematically examines the geochemical principles, as well as hydrological and transport phenomena governing CO₂-O₂ in situ leaching. Recent technological advances are summarized, including progress in reaction kinetics and leaching efficiency, leaching solution design and control, and reservoir modification. Furthermore, the techno-economic implications of CO₂-O₂ in situ leaching are critically assessed, with particular emphasis on operational cost structures and the evolution of techno-economic analysis methodologies. On this basis, key challenges and future directions are identified. This work aims to support the future large-scale and economically efficient deployment of CO₂-O₂ in situ leaching for uranium resource development. Full article

Mining practices and operating conditions are continually evolving, and the respirable fraction of coal mine dust is accordingly expected to change in composition and particle characteristics over time. Between the early 2000s and late 2010s, several regulatory and operational changes occurred in U.S. underground coal mining that could plausibly influence respirable coal mine dust (RCMD), including expanded rock-dusting practices, increased emphasis on respirable crystalline silica, and reductions in diesel emissions. This study evaluated temporal differences in RCMD by comparing samples collected in 2003–2005 and 2018–2020 using particle-level scanning electron microscopy with energy-dispersive X-ray spectroscopy (SEM–EDX). The most consistent temporal change observed was an increase in carbonate particles, consistent with expanded rock-dusting practices. Shifts in coal- and rock-strata-derived dust were observed but were not consistent across regions, and no consistent trend toward finer particle sizes was identified. These results demonstrate the value of particle-level analysis for evaluating changes in RCMD characteristics over time. Full article

Strategic Mine Planning (SMP) creates the long-term economic baseline for mining operations, yet economic variability necessitates Dynamic Mine Planning (DMP) to rapidly stress-test those financial assumptions. Currently, this capability is hindered by fragmented software ecosystems that require manual data handoffs, slowing iteration and breaking the audit trail between market data and valuation models. While Generative AI affords an opportunity to automate these workflows, its adoption in the mining industry is stalled by concerns over data quality and the risk of uncritical acceptance of automated outputs. Addressing these challenges, this paper describes the Mine Intelligence and Decision Support (MINDS) framework. We present MINDS as a modular reference architecture that uses Large Language Model (LLM) agents to orchestrate the economic evaluation process while maintaining strict engineering oversight. The system integrates a conversational interface with a multi-agent assessment layer that acts as an adversarial review, assessing price assumptions against market intelligence before generating economic valuation scenarios. A proof-of-concept using the Marvin copper benchmark evaluates the framework, demonstrating automated request-to-report orchestration, execution stability with an average debate latency of 10.69 s and a transparent decision audit trail. These findings show that MINDS can systematize economic scenario analysis without sacrificing the governance and verification required for definitive feasibility studies. Full article

This study assessed the feasibility of cultivating Lavandula dentata in Technosols produced from fine and coarse coal mining waste, focusing on plant development, substrate functionality, essential oil production, and post-mining ecosystem restoration. The Technosols were formulated using coal waste from the Moatize Coal Mine, Mozambique, combined or not in different configurations with agricultural soil and amended with sewage sludge (3% organic matter) and chemical fertilizer to ensure adequate nutrient availability. The experiments were conducted in 30 L containers, performed in triplicate for each experimental group. All settings allowed good plant growth, although the treatment that used only fine waste presented the closest performance to agricultural soil in terms of the production of aerial biomass. In this case, the dried biomass production of the shoots reached an average of 165 g per pot over 8 months (with a standard deviation of 20.3). The study showed a positive correlation between plant development and the available water capacity of the substrates. The plant tissue of L. dentata, in all the Technosols configurations studied, presented a similar composition to the control, with a biomass composition within the standard range established by the literature. The essential oil production ranged from 0.3 to 0.7% (m/m), averaging 0.5% (m/m), with chemical characteristics also alike the control trial. Technosols composed of coal waste from Moatize appear to be an alternative, both to provide a suitable destination for mining waste and to provide conditions for the revegetation and recovery of degraded areas by coal mining. This avoids the commissioning of nearby areas to supply soil for the restoration process. L. dentata, in addition to its various medical, ornamental, and aromatic uses, has potential as an “ecological trigger” in the restoration process with environmental and socioeconomic benefits. Full article

The organization of safe industrial waste management is an integral part of the global sustainable development strategy. This study provides a preliminary assessment of the processing and recycling potential of strongly alkaline (pH 11–12) sediments accumulated in an abandoned sludge pond (Berezniki, Perm Krai, Russia), based on the initial characterization of their material composition. Sediment samples from the sludge pond were collected, layer-by-layer, over the entire depths of four sediment cores. The collected samples have the following characteristics: sediment particles are composed of up to 80% fine particles < 0.05 mm, with up to 20% fine particles < 0.002 mm. XRD data showed that the sediment consisted of calcite (67.7 wt.%), halite (11.5 wt.%), and other hydrogenic and terrigenous minerals. XRF data also found that the primary constituents in the sediment are CaO (up to 40%), Cl (up to 13%), and LOI (up to 35%). The results of the material composition study indicate a high degree of similarity between the accumulated sediments and solid waste from soda ash production, known as ammonia–soda residue (ASR). Based on experience with calcium-containing waste, this study recommends options for the secondary use of sludge, identifying two main possibilities: environmental protection and construction. We have developed an algorithm for the recycling and reuse of sludge that identifies risks, limitations, and recommended next steps. However, significant knowledge gaps regarding the environmental, toxicological, and the physical–mechanical properties of sludge prevent us from recommending a specific disposal option. The results of this review will serve as guidelines to help develop a roadmap for the disposal process. They will also inform decision-makers about sustainability issues related to industrial waste disposal. Full article

Underground gas storage (UGS) in salt caverns is increasingly important for a flexible and secure energy supply and for stabilizing the gas market. However, cavern operations can induce surface ground movements that must be monitored to safeguard infrastructure integrity and environmental compatibility. This research analyzes horizontal (W–E) and vertical ground movements above the cavern field Gronau-Epe in northwestern Germany, using radar interferometry (InSAR), specifically the SBAS (Small Baseline Subset) approach, combined with clustering and multi-criteria analysis. The study was conducted in cooperation between Uniper Energy Storage GmbH, the Research Center for Post Mining at THGA Bochum, and the company EFTAS. Freely available Copernicus Sentinel 1 data were integrated with public soil maps and operational storage information. A multistage workflow quantified deformation patterns, classified coherent deformation zones via clustering, and evaluated geological and technical drivers using multi-criteria analysis to better distinguish operational (primary) from overburden (secondary) influences. Results reveal long term deformation trends closely linked in time and space to injection/withdrawal cycles. Locally confined vertical and horizontal movements near caverns are attributed to salt convergence triggered by cyclic pressure changes, but they are linked to (hydro)geological and pedological factors. The developed approach shows strong monitoring potential in addition to classic mine surveying. Full article

Underground mining environments are complex and hazardous operations where emergencies continue to happen. Underground mine emergencies require rapid, high-stakes decision-making under conditions of uncertainty, stress, and limited visibility. Conventional mine emergency training largely relies on instruction-based approaches which provide insufficient exposure to the cognitive and behavioral demands of real underground emergency situations. There has been an identified need to train miners for knowledge, skills, abilities, and other characteristics (KSAOs). This study proposes an Adaptive Immersive Training Framework (AITF), a cognitively grounded architecture that integrates cognitive task analysis (CTA), KSAOs, and situational awareness assessment for miner self-escape training and readiness. The AITF aligns NIOSH-identified self-escape competencies with immersive training scenarios designed to assess and develop cognitive readiness and decision-making. CTA of historical mine accidents is introduced as a foundational design method for translating accident investigation findings into simulation scenarios and performance metrics. A CTA of 2006 Darby Mine No. 1 explosion is presented as a proof of concept. The proposed framework supports individualized assessment, iterative scenario refinement, and data-driven feedback. The AITF advances miner training toward cognitive preparedness during mine emergencies and provides a foundation for future training systems that leverage digital tools, digital twins, and artificial intelligence for the mines of the future. Full article

The principal difficulty in studying the physico-mechanical and filtration-capacity properties of coals and host rocks under laboratory conditions using core samples lies in reproducing natural thermodynamic conditions characteristic of in situ depths. To address this issue, specialized equipment and methodologies for transferring measurement results are employed, including the Hoek–Brown failure criterion, the structural weakening coefficient, and the development of thermodynamic models. The reliability and accuracy of such measurements are determined by the degree of conformity between the adopted laboratory conditions and natural in situ conditions, the number of samples representing different lithological varieties, and the adequacy of sampling procedures ensuring representativeness. Particular challenges arise when sampling cleated and fractured coals formed under natural stress–strain conditions and contain methane, which significantly influences their physical properties. These difficulties are especially pronounced in prepared-for-mining high-gas-content coal seams of the Karaganda Basin at depths of approximately 700 m, where obtaining representative samples is technically complicated. Reliable values of the physico-mechanical properties of the coal–rock mass are essential for geomechanical calculations aimed at ensuring safe mining of high-gas-content seams through risk assessment of geodynamic phenomena, particularly in zones of geological disturbances, floor heave, and roof collapse. In this context, the use of a comprehensive suite of geophysical logging data from exploration boreholes makes it possible to obtain continuous, high-precision information on physico-mechanical and filtration-capacity properties. These methods are particularly important for characterizing the coal–rock mass in operating mines, since the natural state of host rocks and prepared coal seams is altered due to stress relief caused by mine workings, preliminary degasification measures, and hydraulic fracturing. The problem addressed is the need for reliable assessment of rock and coal seam parameters under natural thermodynamic stress–strain conditions, taking into account lithological composition, structural heterogeneity, fracture development, stratigraphic differentiation, and gas saturation. The aim of this study is to ensure efficient and safe coal extraction based on geomechanical calculations utilizing physico-mechanical and filtration-capacity properties of host rocks and gas-bearing coal seams, whether prepared for mining or not yet extracted. The research methods are based on an integrated complex of geophysical logging of exploration wells, specialized software tools, and statistical processing techniques to identify patterns in physico-mechanical and filtration-capacity properties of host rocks and coal seams under natural stress–strain conditions, as well as to determine the nature of changes in these properties within coal seams and roof and floor rocks in prepared mining areas. The physico-mechanical and filtration-capacity properties of host rocks and coals from the Lenin and Kazakhstanskaya mines were determined. Regularities governing the application of these parameters to coals of different formations and depths were established; fracture orientations and characteristics were evaluated; and relationships between changes in coal seam parameters and gas content were identified. A comprehensive methodological framework for studying the physical and capacity properties of the coal–rock mass under natural thermodynamic conditions has been developed. Its primary application is the investigation of coal seams prepared for mining to support geomechanical calculations for efficient and safe coal extraction, the implementation of degasification measures for high-gas-content seams, and the assessment of gas-dynamic risks based on the character of variations in physical parameters. Full article

Background: Bucket-wheel excavators are critical assets in surface mining operations, where structural modifications to increase productivity must be validated through rigorous stress analysis to ensure operational safety. Following modification of an ERc 1400-30/7 excavator’s bucket wheel from 18 to 20 buckets, increased operational loads necessitated experimental verification of structural integrity. Methods: A custom 10-channel strain-gauge data acquisition system with 0–10 kHz bandwidth measured stresses in cable anchoring lugs and H-type diagonal members under operational conditions at the Jilț lignite mine, Romania. Measurements were performed during both left and right bucket-wheel rotation. Finite element analysis validated experimental results. Results: Maximum equivalent stresses of 210.0 MPa and 167.1 MPa were measured in the left and right anchoring lugs, respectively, during left bucket-wheel rotation, representing 59% and 47% of material yield strength with safety factors of 1.69 and 2.12. Significant load asymmetry was observed, with left rotation inducing 220–284% higher stresses than right rotation. FEA validation showed <15% agreement with measurements. Dynamic stress amplification of 15–32% above quasi-static values was attributed to bucket–soil interaction and structural vibration. Conclusions: Despite increased operational loads, measured stresses remain below yield strength, confirming structural adequacy. Both anchoring lugs require prioritized monitoring due to elevated stress levels and load asymmetry. The validated methodology provides a framework for post-modification verification of large mining equipment. Full article