Search Results (969)

To enable intelligent inspection of underground cable systems, this study presents a gecko-inspired quadruped robot that integrates multi-degree-of-freedom motion with a deep learning-based visual detection system. Inspired by the gecko’s flexible spine and leg structure, the robot exhibits strong adaptability to confined and uneven tunnel environments. The motion system is modeled using the standard Denavit–Hartenberg (D–H) method, with both forward and inverse kinematics derived analytically. A zero-impact foot trajectory is employed to achieve stable gait planning. For defect detection, the robot incorporates a binocular vision module and an enhanced YOLOv8 framework. The key improvements include a lightweight feature fusion structure (SlimNeck), a multidimensional coordinate attention (MCA) mechanism, and a refined MPDIoU loss function, which collectively improve the detection accuracy of subtle defects such as insulation aging, micro-cracks, and surface contamination. A variety of data augmentation techniques—such as brightness adjustment, Gaussian noise, and occlusion simulation—are applied to enhance robustness under complex lighting and environmental conditions. The experimental results validate the effectiveness of the proposed system in both kinematic control and vision-based defect recognition. This work demonstrates the potential of integrating bio-inspired mechanical design with intelligent visual perception to support practical, efficient cable inspection in confined underground environments. Full article

Resource-exhausted cities have long played a key role in national energy development. Urban renewal projects, such as the renovation of old underground commercial spaces, can improve urban vitality and promote sustainable development. However, in resource-based cities, traditional industries dominate, while new industries such as modern commerce develop slowly. This results in low economic dynamism and weak motivation for urban development. To address this issue, we propose a systematic method for analyzing construction risks during the decision-making stage of renovation projects. The method includes three steps: risk value assessment, risk factor identification, and risk weight calculation. First, unlike previous studies that only used SWOT for risk factor analysis, we also applied it for project value assessment. Then, using the Work Breakdown Structure–Risk Breakdown Structure framework method (WBS-RBS), we identified specific risk sources by analyzing key construction technologies throughout the entire lifecycle of the renovation project. Finally, to enhance expert consensus, we proposed an improved Delphi–Analytic Hierarchy Process method (Delphi–AHP) to calculate risk indicator weights for different construction phases. The risk analysis covered all lifecycle stages of the renovation and upgrading project. The results show that in the Fushun city renovation case study, the established framework—consisting of five first-level indicators and twenty s-level indicators—enables analysis of renovation projects. Among these, management factors and human factors were identified as the most critical, with weights of 0.3608 and 0.2017, respectively. The proposed method provides a structured approach to evaluating renovation risks, taking into account the specific characteristics of construction work. This can serve as a useful reference for ensuring safe and efficient implementation of underground commercial space renovation projects in resource-exhausted cities. Full article

To study hydrogeological characteristics after the occurrence of abnormal water bursts from the weak water-rich (permeable) aquifer of the Changxing Formation limestone overlying deep working faces during production in Guizhou karst landform mining areas, hydrogeological data covering the exploration and production periods of the Xinhua mining region in Jinsha County, Guizhou Province, were collected. On the basis of surface and underground drilling, geophysical exploration techniques, empirical equations, and indoor material simulation methods, the hydrogeological evolution characteristics of the Changxing Formation limestone in the mining region after mining damage to coalbed 9 were studied. The research results indicated that the ratio of the height of the roof failure fracture zone (as obtained via numerical simulation and ground borehole detection) to the mining height exceeded 25.78, which is far greater than the empirical model calculation values (from 13.0 to 15.8). After mining the underlying coalbed 9, an abnormal water-rich area developed in the Changxing Formation limestone, and mining damage fractures led to the connection of the original dissolution fissures and karst caves within the limestone, resulting in the weak water-rich (permeable) aquifer of the Changxing Formation limestone becoming a strong water-rich (permeable) aquifer, which served as the water source for mine water bursts. Over time, after mining damage occurrence, the voids in the Changxing Formation limestone were gradually filled with various substances, yielding water storage space and connectivity decreases. The specific yield decreased with an increasing water burst time and interval after the cessation of mining in the supply area, and the correlation coefficient R was 0.964, indicating a high degree of correlation between the two parameters. Full article

In this study, we examined the microclimates at eight entrances to a karst system distributed between an elevation of 812 and 906 m in Southern Spain. The karst system, characterised by subvertical open tectonic joints that form narrow shafts, developed on the slope of a mountainous area with a Mediterranean climate and strong chimney effect, resulting in an intense airflow throughout the year. The airflows modify the entrance temperatures, creating a distinctive pattern in each opening that changes with the seasons. The objective of this work is to characterise the outflows and find simple temperature-based parameters that provide information about the karst interior. The entrances were monitored for five years (2017–2022) with temperature–humidity dataloggers at different depths. Other data collected include discrete wind measurements and outside weather data. The most significant parameters identified were the characteristic temperature (T_y), recorded at the end of the outflow season, and the rate of cooling/warming, which ranges between 0.1 and 0.9 °C/month. These parameters allowed the entrances to be grouped based on the efficiency of heat exchange between the outside air and the cave walls, which depends on the rock-boundary geometry. This research demonstrates that simple temperature studies with data recorded at selected positions will allow us to understand geometric aspects of inaccessible karst systems. Dynamic high-airflow cave systems could become a natural source of evidence for climate change and its effects on the underground world. Full article

Corrosion-related failures have emerged as a critical driver of premature support bolt failures in underground mines, emphasizing the urgency of understanding the phenomenon with respect to enhancing safety in underground environments. This study investigated key factors influencing bolt degradation through extensive experimental evaluation of cable bolts in simulated underground bolt environments. Multi-stranded cable specimens were exposed to saturated clay, coal, mine water, and grout/cement environments. Water samples were collected weekly from critical packing sections and analyzed for pH, electrical conductivity, and dissolved oxygen. The mineralogy and atmospheric conditions were identified as principal corrosion factors, and clay-rich and coal matrices accelerated corrosion, linked to high ion mobility and oxygen diffusion. Secondary factors correlated context-dependently: pH was negatively associated with corrosion in mineral-packed environments, while conductivity was correlated with non-mineral matrices. Notably, multi-stranded cables exhibited higher localized galvanic corrosion in inter-strand zones, highlighting design vulnerabilities. This work provides pioneering evidence that geological conditions are primary drivers for corrosion-related failures, offering actionable guidance for corrosion mitigation strategies in mining infrastructure. Full article

This study addresses collision detection in the unmanned loading of ore from load-haul-dump (LHD) machines into mining trucks in underground metal mines. Such environments present challenges like heavy dust, confined spaces, sensor occlusions, and poor lighting. This work identifies two primary collision risks and proposes corresponding detection strategies. First, for collisions between the bucket and tunnel walls, LiDAR is used to collect 3D point cloud data. The point cloud is processed through filtering, downsampling, clustering, and segmentation to isolate the bucket and tunnel wall. A KD-tree algorithm is then used to compute distances to assess collision risk. Second, for collisions between the bucket and the mining truck, a kinematic model of the LHD’s working device is established using the Denavit–Hartenberg (DH) method. Combined with inclination sensor data and geometric parameters, a formula is derived to calculate the pose of the bucket’s tip. Key points from the bucket and truck are then extracted to perform collision detection using the oriented bounding box (OBB) and the separating axis theorem (SAT). Simulation results confirm that the derived pose estimation formula yields a maximum error of 0.0252 m, and both collision detection algorithms demonstrate robust performance. Full article

Abandoned smelting sites in karst terrain pose a serious environmental problem due to the complex relationship between specific hydrogeological elements and heavy metal contamination. This review combines work from across the globe to consider how karst-specific features (i.e., rapid underground drainage, high permeability, and carbonate mineralogy) influence the mobility, speciation, and bioavailability of “metallic” pollutants, such as Pb, Cd, Zn, and As. In some areas, such as Guizhou (China), the Cd content in the surface soil is as high as 23.36 mg/kg, indicating a regional risk. Molecular-scale analysis, such as synchrotron-based XAS, can elucidate the speciation forms that underlie toxicity and remediation potential. Additionally, we emphasize discrepancies between karst in Asia, Europe, and North America and synthesize cross-regional contamination events. The risk evaluation is complicated, particularly when dynamic flow systems and spatial heterogeneity are permanent, and deep models like DI-NCPI are required as a matter of course. The remediation is still dependent on the site; however, some technologies, such as phytoremediation, biosorption, and bioremediation, are promising if suitable geochemical and microbial conditions are present. This review presents a framework for integrating molecular data and hydrogeological concepts to inform the management of risk and sustainable remediation of legacy metal pollution in karst. Full article

The time-dependent creep behavior of coal is essential for assessing long-term structural stability and operational safety in deep coal mining. Therefore, this work develops a full-stage creep constitutive model. By integrating fractional calculus theory with statistical damage mechanics, a nonlinear fractional-order (FO) damage creep model is constructed through serial connection of elastic, viscous, viscoelastic, and viscoelastic–plastic components. Based on this model, both one-dimensional and three-dimensional (3D) fractional creep damage constitutive equations are acquired. Model parameters are identified using experimental data from deep coal samples in the mining area. The result curves of the improved model coincide with experimental data points, accurately describing the deceleration creep stage (DCS), steady-state creep stage (SCS), and accelerated creep stage (ACS). Furthermore, a sensitivity analysis elucidates the impact of model parameters on coal creep behavior, thereby confirming the model’s robustness and applicability. Consequently, the proposed model offers a solid theoretical basis for evaluating the sustained stability of deep coal mining and has great application potential in deep underground engineering. Full article

In the global energy sector, water-bearing reservoir-typed gas storage accounts for about 30% of underground gas storage (UGS) reservoirs and is vital for natural gas storage, balancing gas consumption, and ensuring energy supply stability. However, when constructing the UGS in the M gas reservoir, selecting suitable areas poses a challenge due to the complicated gas–water distribution in the multi-layered water-bearing gas reservoir with a long production history. To address this issue and enhance energy storage efficiency, this study presents an integrated geomechanical-hydraulic assessment framework for choosing optimal UGS construction horizons in multi-layered water-bearing gas reservoirs. The horizons and sub-layers of the gas reservoir have been quantitatively assessed to filter out the favorable areas, considering both aspects of geological characteristics and production dynamics. Geologically, caprock-sealing capacity was assessed via rock properties, Shale Gouge Ratio (SGR), and transect breakthrough pressure. Dynamically, water invasion characteristics and the water–gas distribution pattern were analyzed. Based on both geological and dynamic assessment results, the favorable layers for UGS construction were selected. Then, a compositional numerical model was established to digitally simulate and validate the feasibility of constructing and operating the M UGS in the target layers. The results indicated the following: (1) The selected area has an SGR greater than 50%, and the caprock has a continuous lateral distribution with a thickness range from 53 to 78 m and a permeability of less than 0.05 mD. Within the operational pressure ranging from 8 MPa to 12.8 MPa, the mechanical properties of the caprock shale had no obvious changes after 1000 fatigue cycles, which demonstrated the good sealing capacity of the caprock. (2) The main water-producing formations were identified, and the sub-layers with inactive edge water and low levels of water intrusion were selected. After the comprehensive analysis, the I-2 and I-6 sub-layer in the M 8 block and M 14 block were selected as the target layers. The numerical simulation results indicated an effective working gas volume of 263 million cubic meters, demonstrating the significant potential of these layers for UGS construction and their positive impact on energy storage capacity and supply stability. Full article

The digital transformation of the Architecture, Engineering and Construction sector is accelerating the adoption of digital platforms as critical enablers of data integration, stakeholder collaboration and process optimization. This paper presents a systematic review of 125 peer-reviewed journal articles (2015–2025), selected through a PRISMA-guided search using the Scopus database, with inclusion criteria focused on English-language academic literature on platform-enabled digitalization in the built environment. Studies were grouped into six thematic domains, i.e., artificial intelligence in construction, digital twin integration, lifecycle cost management, BIM-GIS for underground utilities, energy systems and public administration, based on a combination of literature precedent and domain relevance. Unlike existing reviews focused on single technologies or sectors, this work offers a cross-sectoral synthesis, highlighting shared challenges and opportunities across disciplines and lifecycle stages. It identifies the functional roles, enabling technologies and systemic barriers affecting digital platform adoption, such as fragmented data sources, limited interoperability between systems and siloed organizational processes. These barriers hinder the development of integrated and adaptive digital ecosystems capable of supporting real-time decision-making, participatory planning and sustainable infrastructure management. The study advocates for modular, human-centered platforms underpinned by standardized ontologies, explainable AI and participatory governance models. It also highlights the importance of emerging technologies, including large language models and federated learning, as well as context-specific platform strategies, especially for applications in the Global South. Full article

The safe disposal of high-level radioactive waste (HLW) is imperative for sustaining China’s rapidly expanding nuclear power sector, with deep geological repositories requiring rigorous site evaluation via underground research laboratories (URLs). This study presents a controlled-source audio-frequency magnetotellurics (CSAMT) survey at the Xinchang site in China’s Beishan area, a region dominated by high-resistivity metamorphic rocks. To overcome electrical data acquisition challenges in such resistive terrains, salt-saturated water was applied to transmitting and receiving electrodes to enhance grounding efficiency. Using excitation frequencies of 9600 Hz to 1 Hz, the survey achieved a 1000 m investigation depth. Data processing incorporated static effect removal via low-pass filtering and smoothness-constrained 2D inversion. The results showed strong consistency between observed and modeled data, validating inversion reliability. Borehole correlations identified a 600-m-thick intact rock mass, confirming favorable geological conditions for URL construction. The study demonstrates CSAMT’s efficacy in characterizing HLW repository sites in high-resistivity environments, providing critical geophysical insights for China’s HLW disposal program. These findings advance site evaluation methodologies for deep geological repositories, though integrated multidisciplinary assessments remain essential for comprehensive site validation. This work underscores the feasibility of the Xinchang site while establishing a technical framework that is applicable to analogous challenging terrains globally. Full article

This paper presents the procedures and results of the numerical modelling and simulations performed to analyse an innovative method of advanced methane drainage employing underground long-reach directional drilling (LRDD) technology. The analysis involved the implementation of geomechanical and dynamic reservoir models to simulate processes in coal seams and the surrounding rocks during coal mining and concurrent methane drainage, in accordance with the proposed technology. The analysis aimed to quantitatively assess the effectiveness of the technology, evaluate its sensitivity to the geological and geomechanical properties of the rocks, and identify the potential for optimisation of its technological and operational parameters in the proposed strategy. The works presented in this paper include the following key tasks: the construction of a system of geological, geomechanical, and dynamic simulation models; the analysis of the geomechanical effects of various types and regions of occurrence; the implementation of the correlation between the geomechanical states of the rocks and their transport properties; and the performance of the effectively coupled geomechanical and reservoir fluid flow simulations. The proposed approach was applied to the specific conditions of the multi-seam Murcki–Staszic Coal Mine operated by Jastrzębska Spółka Węglowa, Poland. Full article

Mining involves daily descents underground and enduring dangerous and difficult conditions. Hence, it is very important to use solutions that will reduce the risk in miners’ work and ensure the greater safety and comfort of work in accordance with the goals of sustainable development. One way is training using virtual reality. Virtual reality provides greater safety (safe training conditions, the possibility of making a mistake without health consequences, practicing emergency scenarios, etc.) and aligns with the Sustainable Development Goals—particularly SDG 3 (health), SDG 8 (decent work), SDG 9 (innovation), and SDG 12 (sustainable production). However, it is also a technology that has its weaknesses (occurrence of contraindications, side effects, etc.). Therefore, the use of VR-based training should be examined in terms of the well-being and health of training employees. Due to this, this article examines the occurrence of psychophysical complaints during VR training; the tolerance and adequacy of the duration of a 50 min training session in VR was assessed; and the average time needed to adapt to the virtual environment was determined. The VR training was developed as a result of a research project conducted by JSW Nowe Projekty S.A. (ul. Ignacego Paderewskiego 41, 40-282 Katowice, Poland), Główny Instytut Górnictwa—Państwowy Instytut Badawczy (plac Gwarków 1, 40-160 Katowice, Poland), JSW Szkolenie i Górnictwo Sp. z o.o. at Jastrzębska Spółka Węglowa Capital Group (ul. Górnicza 1, 44-335 Jastrzębie-Zdrój, Poland) on the development and implementation of innovative training using VR for miners. The solution was developed in the context of mining’s striving for sustainable development in the area of improving working conditions and human safety. The first method used in the study is a survey completed by participants of training courses using virtual reality. The second method is the analysis of trainer observation sheets, which contain observations from training courses. The results revealed that for over 70% of respondents, the need to carry out activities in VR was not associated with fatigue. No average score for psychophysical symptoms assessed by respondents on a scale of 1 to 6 (including disorientation, blurred vision, dizziness, confusion, etc.) exceeded 1.4. The vast majority (85.5%) did not take off the goggles before the end of the training—the training lasted 50 min. This research contributes to the discussion on sustainable industrial transformation by demonstrating that VR training not only improves worker safety and preparedness but also supports development goals through human-centered innovation in the mining sector. Full article

In the Karaganda coal basin, deteriorating geomechanical conditions have been observed, including seam disturbances, diminished strength of argillite–aleurolite strata, water ingress, and pronounced floor heave, all of which markedly increase the labor intensity of maintaining developmental headings. The maintenance and operation of these entries for a reference coal yield of 1000 t necessitate 72–75 man-shifts, of which 90–95% are expended on mitigating ground pressure effects and restoring support integrity. Conventional heave control measures—such as relief drifts, slotting, drainage, secondary blasting, and the application of concrete or rock–bolt systems—deliver either transient efficacy or incur prohibitive labor and material expenditures while lacking unified methodologies for predictive forecasting and support parameter design. This study therefore advocates for an integrated framework that synergizes geomechanical characterization, deformation prognosis, and the tailored selection of reinforcement schemes (incorporating both sidewall and floor-anchoring systems with directed preloading), calibrated to seam depth, geometry, and lithological properties. Employing deformation state assessments to optimize reinforcement layouts for floor stabilization in coal mine workings is projected to curtail repair volumes by 30–40% whilst significantly enhancing operational safety, efficiency, and the punctuality of face preparation. Full article

Modern challenges in civil engineering require decision-making that supports the development of technologies in line with sustainable development principles, including minimizing environmental impact and improving occupational safety. Open caisson sinking, commonly used in underground construction, is particularly prone to generating complex negative impacts that affect construction quality, material efficiency, and working conditions. This study aims to identify the cause-and-effect relationships and assess the intensity of negative impacts associated with the open caisson sinking process. A comprehensive multi-criteria decision-making approach was developed, based on a novel hybrid method combining fuzzy WINGS and Analytic Network Process (ANP). This approach accounts for uncertainties and difficult-to-measure factors, providing a valuable tool for supporting complex engineering decisions. The proposed method facilitates improvements in process quality, reduces environmental risk, and helps eliminate typical execution errors. Research findings confirm that mitigating adverse impacts during caisson sinking enhances sustainable risk management in construction and supports rational decision-making under uncertainty. The method is universal and applicable in other domains requiring cause–effect analysis and the evaluation of impact intensity, especially in the context of implementing sustainable construction management practices. Full article