Search Results (1,162)

The objective of this study is to quantify and characterize ground deformations induced by underground coal mining in the Karaganda coal basin, Kazakhstan, in order to improve the understanding of subsidence processes and their long-term evolution. The SBAS-InSAR method was applied to Sentinel-1 (C-band) and TerraSAR-X (X-band) data from 2019–2021 to estimate the magnitude, extent, and temporal behavior of displacements over the Kostenko, Kuzembayev, Aktasskaya, and Saranskaya mines. The results reveal spatially coherent and progressive deformation, with maximum cumulative LOS displacements exceeding –800 mm in TerraSAR-X data within active longwall mining zones. Time-series analysis confirmed acceleration of displacement during active extraction and its subsequent attenuation after mining ceased. Comparative assessment demonstrated a strong agreement between Sentinel-1 and TerraSAR-X results (r = 0.9628), despite differences in resolution and acquisition geometry, highlighting the robustness of the SBAS-InSAR approach. Analysis of displacement over individual longwalls showed that several panels (3, 5, 8, 15, and 18) already exceeded their projected maximum subsidence values, underlining the necessity of continuous monitoring for ensuring safety. In contrast, other longwalls have not yet reached their maximum deformation, indicating potential for further activity. Overall, this study demonstrates the value of multi-sensor InSAR monitoring for reliable assessment of mining-induced subsidence and for supporting geotechnical risk management in post-industrial regions. Full article

With the progressive depletion of coal resources, the recovery of shaft pillars has become an important means of improving resource utilization and reducing waste. Taking the main shaft pillar recovery of the Longxiang Coal Mine at the stage of mine closure as the engineering background, this study systematically investigates ground subsidence prediction and shaft stability control under strip mining with symmetrical extraction. An improved subsidence prediction model was established by integrating the probability integral method with superposition theory, and its validity was verified through numerical simulations and field monitoring data. The results demonstrate that the proposed method can accurately capture the subsidence behavior under complex geological conditions, with prediction errors ranging from 6.4 mm to 399.1 mm. In fully subsided zones, the percentage error was as low as 1.1–3.5%, while larger deviations were observed in areas where subsidence was incomplete, confirming both the reliability and the practical limitations of the method under different conditions. Furthermore, the deformation mechanisms of the shaft during pillar recovery were analyzed. Monitoring results indicated that the maximum subsidence at the east and west sides of the shaft reached 7620.6 mm, accompanied by local cracks exceeding 1500 mm, which caused significant damage to surface structures. To address these risks, a safety control scheme based on an integrated “prediction–monitoring–control” framework is proposed, including shaft wall reinforcement, optimization of mining parameters, and continuous ground subsidence monitoring. By combining real-time monitoring with the superposition of small working face predictions, the scheme enables maximum recovery of shaft pillar coal while ensuring operational safety. This study provides a scientific basis and technical support for shaft pillar recovery in Longxiang Coal Mine and offers valuable theoretical guidance for similar mine closure projects, with significant implications for engineering practice. Full article

Mining activity has been and is one of the most important and indispensable industries for the development of society. Given its role in the provision of raw materials, advancing the development of environmentally friendly mining practices is essential for meeting the globally established goals of sustainable development. In this regard, actions and incentives are being promoted by the European Union, such as the Mine.io project presented in this research. In response to the needs identified within the mining sector, this research seeks to explore the functional and non-functional requirements across several mining contexts. The objective is to establish effective patterns that positively influence the sector activities. This effort is envisioned as a critical foundation for developing a digital architecture that addresses sector limitations and fosters the integration of Industry 4.0 principles into the mining domain. The results provide a solid basis for understanding the needs of the different mining sectors analyzed, while also demonstrating the potential advancements achievable through the project’s technological developments. They enable a comprehensive evaluation of the current technological state in relation to the broader context of global legacy practices, establishing informed guidelines for effective sector responses based on digitalization and the application of sustainable tools. Full article

This paper proposes a multi-sensor data-fusion-based method for real-scene 3D reconstruction and digital twin visualization of coal mine tunnels, aiming to address issues such as low accuracy in non-photorealistic modeling and difficulties in feature object recognition during traditional coal mine digitization processes. The research employs cubemap-based mapping technology to project acquired real-time tunnel images onto six faces of a cube, combined with navigation information, pose data, and synchronously acquired point cloud data to achieve spatial alignment and data fusion. On this basis, inner/outer corner detection algorithms are utilized for precise image segmentation, and a point cloud region growing algorithm integrated with information entropy optimization is proposed to realize complete recognition and segmentation of tunnel planes (e.g., roof, floor, left/right sidewalls) and high-curvature feature objects (e.g., ventilation ducts). Furthermore, geometric dimensions extracted from segmentation results are used to construct 3D models, and real-scene images are mapped onto model surfaces via UV (U and V axes of texture coordinate) texture mapping technology, generating digital twin models with authentic texture details. Experimental validation demonstrates that the method performs excellently in both simulated and real coal mine environments, with models capable of faithfully reproducing tunnel spatial layouts and detailed features while supporting multi-view visualization (e.g., bottom view, left/right rotated views, front view). This approach provides efficient and precise technical support for digital twin construction, fine-grained structural modeling, and safety monitoring of coal mine tunnels, significantly enhancing the accuracy and practicality of photorealistic 3D modeling in intelligent mining applications. Full article

Mining, mineral processing, and power generation are just a few of the industries that have made extensive use of pneumatic conveying systems in recent years. The market for pneumatic conveying is anticipated to grow to a value of $30 billion by 2025. However, problems with the pneumatic conveying process are common and include coal particle damage, pipe wall wear, and excessive system energy consumption. A new systematic framework for decision-making is created by combining the Theory of Inventive Problem Solving (TRIZ) with the Decision-Making Trial and Evaluation Laboratory (DEMATEL). This methodology employs TRIZ-Ishikawa to determine the underlying causes of issues from six different perspectives. It then suggests remedies based on TRIZ technical contradictions and uses DEMATEL to examine how the solutions interact to determine the best course of action. This study confirms the viability of this approach in recognizing fundamental contradictions, producing workable solutions, and reaching scientific conclusions in challenging issues by using instances such as wear and tear, obstructions, and low conveying efficiency in pneumatic conveying system elbows. It offers particular references for real engineering projects and suggests practical solutions like employing quick-release flanges and installing multiple sets of airflow regulators. Full article

Seawater reverse osmosis (SWRO) desalination generates a concentrated brine byproduct rich in dissolved salts and minerals. This study presents an extensive economic and technical analysis of recovering all major ions from SWRO brine, which includes Na, Cl, Mg, Ca, SO₄, K, Br, B, Li, Rb, and Sr in comparison to conventional mining and chemical production of these commodities. Data from recent literature and case studies are compiled to quantify the composition of a typical SWRO brine and the potential yield of valuable products. A life-cycle cost framework is applied, incorporating capital expenditure (CAPEX), operational expenditure (OPEX), and total water cost (TWC) impacts. A representative simulation for a large 100,000 m³/day SWRO plant shows that integrated “brine mining” systems could recover on the order of 3.8 million tons of salts per year. At optimistic recovery efficiencies, the gross annual revenue from products (NaCl, Mg(OH)₂/MgO, CaCO₃, KCl, Br₂, Li₂CO₃, etc.) can reach a few hundred million USD. This revenue is comparable to or exceeds the added costs of recovery processes under favorable conditions, potentially offsetting desalination costs by USD 0.5/m³ or more. We compare these projections with the economics of obtaining the same materials through conventional mining and chemical processes worldwide. Major findings indicate that recovery of abundant low-value salts (especially NaCl) can supply bulk revenue to cover processing costs, while extraction of scarce high-value elements (Li, Rb, Sr, etc.) can provide significant additional profit if efficient separation is achieved. The energy requirements and unit costs for brine recovery are analyzed against those of terrestrial or conventional mining; in many cases, brine-derived production is competitive due to avoided raw material extraction and potential use of waste or renewable energy. CAPEX for adding mineral recovery to a desalination plant is significant but can be justified by revenue and by strategic benefits such as reduced brine disposal. Our analysis, drawing on global data and case studies (e.g., projects in Europe and the Middle East), suggests that metals and salts recovery from SWRO brine is technically feasible and, at sufficient scale, economically viable in many regions. We provide detailed comparisons of cost, yield, and market value for each target element, along with empirical models and formulas for profitability. The results offer a roadmap for integrating brine mining into desalination operations and highlight key factors such as commodity prices, scale economies, energy integration, and policy incentives that influence the competitiveness of brine recovery against traditional mining. Full article

To address the issue of sustained deformation in the main roadway surrounding rock triggered by intense movement of overlying strata following the reduction of width of the stopping pillar (WSP) in closely spaced double extra-thick coal seams (CSDECS). Analyze the evolution patterns of abutment pressure, principal stress vector lines, and zones of deviatoric stress concentration (ZDSC) of the main roadways using multi-method approaches. The findings are as follows: As the WSP is reduced, the maximum abutment pressure (MAP) on both sides of the gate roadways’ surrounding rock becomes significantly more asymmetric and intense. The deflection trajectory of the maximum principal stress line (MPSL) in the two coal seams, induced by the advancing underlying panel, follows an approximate inverted ︺ shape. The evolution of the ZDSC and the main roadways in the adjacent working faces all shows three-stage characteristics. For the upper coal seam, it is characterized by crescent-shaped symmetry → slow and asymmetric increase of the peak value and the offset of the ZDSC → the ZDSC on the non-mining side (NM-S) reaches the maximum while the mining side (M-S) shows the reverse trend. For the lower coal seam, it is characterized by crescent-shaped symmetry → quasi-annular distribution with a slight increase in the peak value → significant and asymmetric increase of the peak values. Based on the identification of the key control zones in the ZDSC, an asymmetric reinforcement segmented control method was proposed. The findings provide useful guidance for analogous engineering projects. Full article

Post-occupancy evaluation is a critical mechanism for ensuring the sustained success and continuous improvement of industrial heritage revitalization initiatives. The quality of the visitor experience plays a key role in determining a project’s long-term vitality. This study focuses on assessing user satisfaction with a revitalized industrial heritage site by employing web crawling and data mining techniques to systematically collect and analyze user-generated reviews from major online platforms. Using the 1933 Old Millfun in Shanghai, China, as an example, this research identifies six core evaluation dimensions derived from extensive user commentary: project accessibility, cultural legibility, aesthetic distinctiveness, commercial appeal, facility completeness, and sense of security. These dimensions are integrated into a comprehensive analytical framework, with the Fuzzy Comprehensive Evaluation (FCE) method applied to quantitatively assess the site’s performance across each category. By combining qualitative sentiment data with quantitative evaluation techniques, the data-driven presentation provides nuanced insights into the evolving user experience. The research results contribute to the development of a replicable and scalable paradigm for measuring user experience in industrial heritage revitalization and highlights the potential of digital platforms as valuable tools for heritage site management and continuous optimization. Full article

The sustainable transformation of areas associated with mining is an essential contemporary challenge. In the course of such transformations, economic benefits are confronted with community criticism of heavy industry. In this context, the study examines spatial solutions implemented in the revitalisation of areas adjacent to active industrial sites. The article aims to characterise solutions applied in locations that elude a straightforward division into industrial and post-industrial. The motivations of the entities involved in the construction and the effects of implementing such projects are investigated. To achieve this aim, compositional and visual linkages in four locations (in Germany and Poland) were analysed, along with the intentions of designers and investors and the opinions of users. The study revealed the influence of political decisions on spatial solutions, an aspect not previously analysed, which has led to a limited understanding of the role they play in the transformation. It was indicated that drawing users’ attention to the aesthetic values of active industrial areas coincides with diverting attention from their nuisances. The discreet cooperation between local authorities, designers, and industry (as expressed in architectural solutions) was emphasised. The research opens a field for discussion on managing community perceptions through spatial solutions. Full article

The rehabilitation of mining environments poses significant challenges due to the contamination risks associated with hazardous materials, such as arsenic and other chemical products. This research study presents the development of a Digital Twin for the Lavrion Technological and Cultural Park (LTCP), a former mining and metalworking site that is currently undergoing environmental restoration. The Digital Twin integrates advanced technologies, including real-time sensor monitoring, geophysical methods, and 3D modeling, to provide a comprehensive tool for assessing and managing the environmental conditions of the site. Key elements of the project include the monitoring of hazardous-waste storage, the evaluation of contaminated soils, and the assessment of the Park’s infrastructure, which includes both deteriorating buildings and successfully restored structures. Real-time sensor data are collected to track critical parameters such as conductivity, temperature, salinity, and levels of pollutants, enabling proactive environmental management and mitigation of potential risks. The integration of these technologies enables continuous monitoring, historical data analysis, and improved decision making in the ongoing efforts to preserve the site’s ecological integrity. This study demonstrates the potential of using Digital Twins as an innovative solution for the sustainable management and valorization of mining heritage sites, offering insights into both technological applications and environmental conservation practices. Full article

As global efforts accelerate towards low-carbon transportation, power batteries from new energy vehicles (NEVs) have become critical resources, presenting both opportunities and environmental challenges. These batteries contain significant quantities of critical metals—such as nickel, cobalt, and lithium—that are crucial for the energy transition but face substantial supply risks. Megacities like Shanghai, leaders in NEV adoption, increasingly serve as significant reservoirs of these valuable materials. Maximizing the recovery of these metals from retired NEV batteries is therefore essential for enhancing resource security, minimizing environmental impacts, and promoting urban sustainability. This study employs a dynamic material flow model to estimate the demand and retirement volumes of critical metals in NEV power batteries in Shanghai from 2014 to 2050. Rather than assessing specific recycling technologies, this research evaluates the broader strategic, environmental, and economic benefits of recycling. Key findings include the following: (1) Annual peak demand for critical metals will range from approximately 0.3 to 34 thousand tons, with domestic cobalt production expected to be inadequate beyond 2029 under high-intensity adoption scenarios. (2) By 2050, the volume of discarded critical metals will surpass the demand for newly mined resources, reaching annual volumes of up to 29 thousand tons. The cumulative recoverable quantities from 2014 to 2050 are projected to range between 0.7 and 227 thousand tons for nickel, 2 and 43 thousand tons for cobalt, and 0.6 and 24 thousand tons for lithium. (3) Recycling these critical metals significantly reduces dependency on primary extraction, lowers greenhouse gas emissions, prevents secondary pollution, and ensures economic sustainability. The study concludes with targeted policy recommendations to facilitate efficient and large-scale recovery of critical metals from NEV batteries in Shanghai. Harnessing this urban resource stream can reinforce China’s strategic metal supply chain and support the city’s sustainable, circular, and low-carbon development goals. Full article

The landfill mining and reclamation (LFMR) project is increasingly recognized as crucial for achieving sustainable waste management and supporting global environmental goals, such as the United Nations Sustainable Development Goals related to clean energy, responsible consumption, and sustainable cities. This study evaluated the potential of combustible polymer composites (CPCs) derived from landfill mining waste for energy recovery and chemical recycling as well as resource recovery potential of soil-like fractions (SLFs). Through physico-chemical analysis and pyrolysis reaction with catalytic upgrading process, the study evaluates the suitability of CPCs for energy recovery as a solid recovered fuel (SRF) and chemical recycling feedstock. For assessing the SLFs for potential use as recycled aggregates and cover materials, total organic carbon, heavy metal concentration, and biodegradability were investigated. CPCs exhibited varied SRF and chemical feedstock qualities depending on site-specific polymer composition, while SLFs met environmental criteria for both inert waste and stabilization soil classification. The findings not only highlight technical feasibility, but also provide a transferable evaluation framework supporting ‘circular economy’ policies. Therefore, LFMR projects can contribute to sustainable waste management and energy production and provide solutions for effective material recycling, aligning with global environmental and resource conservation goals. Full article

Deep multi-coal seam mining is plagued by intense mining pressure, significant impacts of multi-working face mining on system roadways, and difficult surrounding rock deformation control—these issues severely threaten the safe and normal operation of roadways, creating an urgent need for effective dynamic disaster control technologies. Taking the 131,105 working face of Liuzhuang Mine (burial depth up to 740 m) as an example, this study addresses a critical research gap; existing roof cutting pressure relief technologies mostly focus on shallow/thin-coal-seam mining and fail to tackle secondary dynamic pressure induced by repeated mining in deep multi-coal seams—where the superposition of mining stress, ground stress, and goaf stress severely threatens system roadways. To fill this gap, three novel contributions are made. (1) A hierarchical “upper break and middle cut” deep-hole blasting design is proposed, distinct from single-mode roof cutting in existing studies. It achieves directional roof failure by “upper break” (damaging overlying hard rock) and “middle cut” (creating fissures between goaf and protective coal pillars), blocking stress transmission to roadways. (2) Numerical simulations specifically for deep strata (740 m) optimize key parameters: 25 m as the optimal cutting height and 35° as the optimal cutting angle, quantifying their effects on pressure relief (a gap in existing parameter optimization for deep mining). (3) A rapid sealing scheme combining AB material grouting with high-strength detonator pins is developed, solving the problem of slow hardening and poor sealing in traditional deep-hole processes (e.g., cement-only sealing), enabling blasting within 10 min after sealing. This cut off the integrity of the roof, blocked the pressure transmission of the roof stress to the existing system roadway, and achieved a 43.7% reduction in roadway surrounding rock stress (from 32 MPa to 18 MPa) and a 46.7% reduction in maximum roadway deformation (from the pre-blasting 15 cm to 8 cm). This study provides a reference for similar deep multi-coal seam projects. Field monitoring and numerical simulation results show the following. (1) The maximum deformation of the protected East Third Concentrated main roadway is only 8 cm, fully meeting normal operation requirements. (2) The “upper break and middle cut” technology effectively reduces the mining influence range (from 156 m without roof cutting to 125 m with 25 m roof cutting) and weakens roof stress transfer to roadways. This study verifies the feasibility and effectiveness of deep hole blasting for roof cutting, pressure relief, and roadway protection in deep multi-coal seam mining. It provides direct technical references and engineering application templates for similar projects facing roadway protection and dynamic disaster control challenges, contributing to the safe and efficient mining of deep coal resources. Full article

To carry out data analysis, it is necessary to implement a model that guides the process in an orderly and sequential manner, with the aim of maintaining control over software development and its documentation. One of the most widely used tools in the field of data analysis is the Cross-Industry Standard Process for Data Mining (CRISP-DM), which serves as a reference framework for data mining, allowing the identification of patterns and, based on them, supporting informed decision-making. Another tool used for pattern identification and the study of relationships within systems is network analysis (NA), which makes it possible to explore how different components are interconnected. The integration of these tools can be justified and developed under the principles of Situational Method Engineering (SME), which allows for the adaptation and customization of existing methods according to the specific needs of a problem or context. Through SME, it is possible to determine which components of CRISP-DM need to be adjusted to efficiently incorporate NA, ensuring that this integration aligns with the project’s objectives in a structured and effective manner. The proposed methodological process was applied in a real working group, which allowed its functionality to be validated, each phase to be documented, and concrete outputs to be generated, demonstrating its usefulness for the development of analytical projects. Full article

Currently, supermarket-run shopping centers, known as “Big Marts,” monitor sales information for every single item in order to predict potential customer demand and update inventory management. Anomalies and general trends are commonly discovered through data warehouse mining using a range of machine learning techniques, and businesses such as Big Marts can use the obtained data to forecast future sales volumes. Compared to other research publications, this one forecasted sales with higher accuracy using machine learning models including KNN (K Nearest Neighbors), Naïve Bayes, and Random Forest. To adapt the proposed business model to anticipated outcomes, the sales forecast is based on Big Mart sales for various stores. Using different machine learning methods, the data that is produced may then be used to predict potential sales volumes for retailers such as Big Marts. The projected cost of the suggested system includes the following identifiers: price, outlet, and outlet location. In order to facilitate data-driven decision-making in retail operations and help Big Marts optimize their business models and effectively satisfy anticipated demand, this study emphasizes the importance of incorporating cutting-edge machine learning approaches. Full article