Search Results (726)

Illegal mining operations induce cascading ecosystem degradation by causing extensive ground subsidence, necessitating accurate underground goaf localization for effectively induced-hazard mitigation. The conventional locating method applied the synthetic aperture radar interferometry (InSAR) technique to obtain ground deformation to estimate underground goaf parameters, and the locating accuracy was crucially contingent upon the appropriateness of nonlinear deformation function models selection and the precision of geological parameters acquisition. However, conventional model-driven underground goaf locating frameworks often fail to sufficiently integrate prior geological information during the model selection process, potentially leading to increased positioning errors. In order to enhance the operational efficiency and locating accuracy of underground goaf, deformation model selection must be aligned with site-specific geological conditions under varying cases of prior information. To address these challenges, this study categorizes prior geological information into three different hierarchical levels (detailed, moderate, and limited) to systematically investigate the correlations between model selection and prior information. Subsequently, field validation was carried out by applying two different non-linear deformation function models, Probability Integral Model (PIM) and Okada Dislocation Model (ODM), with three different prior geological information conditions. The quantitative performance results indicate that, (1) under a detailed prior information condition, PIM achieves enhanced dimensional parameter estimation accuracy with 6.9% reduction in maximum relative error; (2) in a moderate prior information condition, both models demonstrate comparable estimation performance; and (3) for a limited prior information condition, ODM exhibits superior parameter estimation capability showing 3.4% decrease in maximum relative error. Furthermore, this investigation discusses the influence of deformation spatial resolution, the impacts of azimuth determination methodologies, and performance comparisons between non-hybrid and hybrid optimization algorithms. This study demonstrates that aligning the selection of deformation models with different types of prior geological information significantly improves the accuracy of underground goaf detection. The findings offer practical guidelines for selecting optimal models based on varying information scenarios, thereby enhancing the reliability of disaster evaluation and mitigation strategies related to illegal mining. Full article

In outdoor environments, GNSS is commonly used for vehicle navigation and various location-based ITS services. However, in GNSS shadow roads such as tunnels and underground highways, it is challenging to provide these services. With the rapid expansion of GNSS shadow roads, the need for radio positioning technology that can serve the role of GNSS in these areas has become increasingly important to provide accurate vehicle navigation and various location-based ITS services. This paper proposes a new GNSS shadow road radio positioning technology using multidirectional BLE beacon signals. The structure of a multidirectional BLE beacon that radiates different BLE beacon signals in two or four directions is introduced, and explains the principle of differential RSSI technology to determine the vehicle’s location using these signals. Additionally, the technology used to determine the vehicle’s speed is described. A testbed was constructed to verify the performance of the developed multidirectional BLE beacon-based radio navigation system. The current status and future plans of the testbed installation are introduced, and the results of position and speed experiments using the testbed for constant speed and deceleration driving are presented. Full article

The development of urban underground space is a necessary way to realize the sustainable development of the city, and it is also an essential means to solve urban environmental problems such as traffic congestion and resource shortage. Scientific suitability evaluation is the prerequisite for the rational planning and development of underground space. Previous studies have encountered problems such as an imperfect index system, a single weighting method, and loss of membership degrees in fuzzy evaluation, which have led to unreasonable evaluation results. Taking the northern coastal cities of Weifang as the research area, the evaluation index system is established, and the index weights are calculated by the improved structural CRITIC. An improved fuzzy mathematical evaluation model based on the weighted summation method is proposed to carry out the suitability evaluation of underground space development in the research area. The results show that: (1) The proposed method of combination weight and improved fuzzy mathematics evaluation takes into account the scientific weight and avoids the subjective bias, and also corrects the issue of membership degree loss in the membership matrix of comprehensive evaluation. (2) When the area of the grid unit is 0.02% of the area of the research area, the size of the evaluation unit is more reasonable. (3) The area that is very suitable for underground space development accounts for 8.69%, and the more suitable area accounts for 25.55%, mainly located in the northwest and central–southern regions of the research area. It can provide a reference for the suitability evaluation of underground space development. Full article

The Jidong Oilfield No. 2 Underground Gas Storage (UGS), located in an active fault zone in Northern China, is a key facility for ensuring natural gas supply and peak regulation in the Beijing–Tianjin–Hebei region. To evaluate the effectiveness of a combined surface and shallow borehole monitoring system under deep reservoir conditions, a 90-day microseismic monitoring trial was conducted over a full injection cycle using 16 surface stations and 1 shallow borehole station. A total of 35 low-magnitude microseismic events were identified and located using beamforming techniques. Results show that event frequency correlates positively with wellhead pressure variations instead of the injection volume, suggesting that stress perturbations predominantly control microseismic triggering. Events were mainly concentrated near the bottom of injection wells, with an average location error of approximately 87.5 m and generally shallow focal depths, revealing limitations in vertical resolution. To enhance long-term monitoring performance, this study recommends deploying geophones closer to the reservoir, constructing a 3D velocity model, applying AI-based phase picking, expanding array coverage, and developing a microseismic-injection coupling early warning system. These findings provide technical guidance for the design and deployment of long-term monitoring systems for deep reservoir conversions into UGS facilities. Full article

Underground cast-in-place pipes (CIPP, Diameter of 2’–5’) are used to transport water for the Phoenix, AZ area. These pipes have developed leaks due to their age and changes in the environment, resulting in a significant waste of water. Currently, leaks can only be identified when water pools above ground occur and are then manually confirmed through the inside of the pipe, requiring the shutdown of the water system. However, many leaks may not develop a puddle of water, making them even harder to identify. The primary objective of this research was to develop an inspection method utilizing drone-based infrared imagery to remotely and non-invasively sense thermal signatures of abnormal soil moisture underneath urban surface treatments caused by the leakage of water pipelines during the regular operation of water transportation. During the field tests, five known leak sites were evaluated using an intensive experimental procedure that involved conducting multiple flights at each test site and a stringent filtration process for the measured temperature data. A detectable thermal signal was observed at four of the five known leak sites, and these abnormal thermal signals directly overlapped with the location of the known leaks provided by the utility company. A strong correlation between ground temperature and shading before sunset was observed in the temperature data collected at night. Thus, a shadow and solar energy model was implemented to estimate the position of shadows and energy flux at given times based on the elevation of the surrounding structures. Data fusion between the metrics of shadow time, solar energy, and the temperature profile was utilized to filter the existing points of interest further. When shadows and solar energy were considered, the final detection rate of drone-based infrared imaging was determined to be 60%. Full article

Geometallurgy is an approach that utilizes predictive models that can support business decisions, mitigate risks, and enhance production efficiency. To develop an accurate geometallurgical model, it is essential to understand the behavior of each lithology within the ore body through geometallurgical testing. In this context, the present study aims to evaluate the performance of bench-scale tests conducted on the main mining fronts of a zinc mine operation located in Brazil. The mineral processing plant was designed to process lead and zinc sulfide ores without material stockpiling, where all ores extracted from the underground mine are immediately processed. The geometallurgical characterization was conducted through the following steps: sampling, crushing, grinding, and flotation. The recovery, concentrate, and tailing contents during the flotation stages of galena and sphalerite were analyzed. A mineralogical characterization using a Mineral Liberation Analyzer (MLA) was performed to assess the degree of particle liberation and mineral associations within the studied mining fronts. The results indicate that a higher degree of pyrite liberation leads to greater metallurgical recovery of mineralized bodies A (breccia-hosted orebody), B (sphalerite-rich doloarenite orebody), and C (upper replaced stratiform orebody). Among these, mineralized body C presents the highest recovery in the zinc and lead stages, with 99.5% and 86.2%, respectively. Full article

Complex carbonate reservoirs feature large-scale karst cavern structures, exhibiting complex pore and bottom water energy distributions, which increase the difficulty of reservoir development and require targeted research. This paper proposes a new method for dynamic reserves calculation in these reservoirs based on the Differential Processing Method (DPM) and aimed at optimizing the development of complex reservoirs. The AD22 unit of the Tarim Oilfield in Xinjiang is taken as the research object, and this reservoir features complex karst and fault characteristics, which traditional reserves calculation methods cannot effectively capture due to its complex heterogeneous distribution. This study constructs a refined reservoir numerical model through 3D geological modeling and impedance inversion techniques, calculates dynamic reserves using the DPM, and compares the result with traditional material balance and production data analysis methods. The results indicate that the DPM has an advantage in estimating the petrophysical parameters and reserve utilization in such reservoirs. The error between the constructed reservoir numerical model and the actual reservoir development historical data is only 2.04%, demonstrating a good reference value. The model shows that more than 60% of the recoverable reserves in the target unit are located in areas shallower than 160 m underground, while the current development degree is only 12.6%. The model shows that the recovery rate is low in the strong bottom water energy areas of the unit, while the recovery potential is high in the weak bottom water areas. Therefore, a differentiated development strategy based on varying bottom water energy is required to enhance development efficiency. The model indicates that this strategy can improve the comprehensive development benefits of the reservoir by 81.66% over the existing baseline, demonstrating significant potential. This study provides new ideas and methods for dynamic reserve estimation and development strategy optimization for complex carbonate reservoirs, verifies the effectiveness of the DPM in evaluating the development of complex bottom water energy reservoirs, and offers data references for related research and field applications. Full article

The acceleration of industrialization and urbanization worldwide has dramatically improved living standards but has also introduced serious environmental and public health challenges. One of the most critical challenges is air pollution, particularly indoors, where individuals typically spend over 90% of their time. Ensuring good Indoor Air Quality (IAQ) is essential, especially in heavily frequented public spaces such as shopping malls. This study focuses on assessing IAQ in a large shopping mall located in Tabuk, Saudi Arabia, covering retail zones as well as an attached underground parking area. Monitoring is conducted over a continuous two-month period using calibrated instruments placed at representative locations to capture variations in pollutant levels. The investigation targets key contaminants, including carbon monoxide (CO), carbon dioxide (CO₂), fine particulate matter (PM_2.5), total volatile organic compounds (TVOCs), and formaldehyde (HCHO). The data are analyzed and compared against international and national guidelines, including World Health Organization (WHO) standards and Saudi environmental regulations. The results show that concentrations of CO, CO₂, and PM_2.5 in the shopping mall are generally within acceptable limits, with values ranging from approximately 7 to 15 ppm, suggesting that ventilation systems are effective in most areas. However, the study identifies high levels of TVOCs and HCHO, particularly in zones characterized by poor ventilation and high human occupancy. Peak concentrations reach 1.48 mg/m³ for TVOCs and 1.43 mg/m³ for HCHO, exceeding recommended exposure thresholds. These findings emphasize the urgent need for enhancing ventilation designs, prioritizing the use of low-emission materials, and establishing continuous air quality monitoring protocols within commercial buildings. Improving IAQ is not only crucial for protecting public health but also for enhancing occupant comfort, satisfaction, and overall building sustainability. This study offers practical recommendations to policymakers, building managers, and designers striving to create healthier indoor environments in rapidly expanding urban centers. Full article

Ground-penetrating radar (GPR) plays a critical role in detecting underground targets, particularly locating and characterizing leaks in buried pipelines. However, the complex nature of GPR images related to pipeline leaks, combined with the limitations of existing neural network-based inversion methods, such as insufficient feature extraction and low inversion accuracy, poses significant challenges for effective leakage reconstruction. To address these challenges, this paper proposes an enhanced UNet++-based model: the Multi-Scale Directional Network PlusPlus (MSDNet++). The network employs an encoder–decoder architecture, in which the encoder incorporates multi-scale directional convolutions with coordinate attention to extract and compress features across different scales effectively. The decoder fuses multi-level features through dense skip connections and further enhances the representation of critical information via coordinate attention, enabling the accurate inversion of dielectric constant images. Experimental results on both simulated and real-world data demonstrate that MSDNet++ can accurately invert the location and extent of buried pipeline leaks from GPR B-scan images. Full article

Offshore synthetic fuel production and marine carbon dioxide removal can be enabled by direct ocean capture, which extracts carbon dioxide from the ocean that then can be used as a feedstock for fuel production or sequestered underground. To maximize carbon capture, plants require a variety of low-carbon energy sources to operate, such as variable renewable energy. However, the impacts of variable power on direct ocean capture have not yet been thoroughly investigated. To facilitate future deployments, a generalizable model for electrodialysis-based direct ocean capture plants is created to evaluate plant performance and electricity costs under intermittent power availability. This open-source Python-based model captures key aspects of the electrochemistry, ocean chemistry, post-processing, and operation scenarios under various conditions. To incorporate realistic energy supply dynamics and cost estimates, the model is coupled with the National Renewable Energy Laboratory’s H2Integrate tool, which simulates hybrid energy system performance profiles and costs. This integrated framework is designed to provide system-level insights while maintaining computational efficiency and flexibility for scenario exploration. Initial evaluations show similar results to those predicted by the industry, and demonstrate how a given plant could function with variable power in different deployment locations, such as with wind energy off the coast of Texas and with wind and wave energy off the coast of Oregon. The results suggest that electrochemical systems with greater tolerances for power variability and low minimum power requirements may offer operational advantages in variable-energy contexts. However, further research is needed to quantify these benefits and evaluate their implications across different deployment scenarios. Full article

Underground mine surveys present unique challenges, including the logistics of deploying an energy source, placing geophones in solid rock, managing reverberation from the adit, and ensuring safety. We present the results of seismic surveying at the historic Deer Trail Mine in south-central Utah (USA). The mine is located along the eastern side of the Tushar Range. The surveys utilised a narrow, mostly horizontal adit, 120–510 m below the ground surface. The country rock consists of highly fractured and mineralised Permian to Pennsylvanian quartzites, shales, and limestones. A short test of a 96-channel common midpoint (CMP) P-wave profile was conducted using an accelerated weight-dropper source. We supplemented the P-wave survey with tests of surface-wave dispersion and horizontal-vertical spectral ratio modelling for shallow S-wave structure. These tests confirmed the capability to map shallow, small-scale structure. A conventional CMP 264-channel survey with an explosive source covered 1728 m. A static recording array was used for both surveys with 4.5-Hz vertical geophones. The conventional CMP profile imaged horizontal and dipping reflectors down to about 2000 m, interpreted as lithologic variations in the bedrock. Our study demonstrates the potential for high-resolution seismic exploration in an unconventional and challenging setting to guide the exploitation of deeply buried mineral resources. Full article

The Sierra de las Navajas is a Late Pliocene volcanic complex with a rhyolitic composition and peralkaline affinity. It is located on the northeastern edge of the Trans-Mexican Volcanic Belt in the state of Hidalgo. Within this rocky massif lies Cerro de las Navajas, the site of the most intensively exploited archaeological obsidian deposit in Mesoamerica. Obsidian extraction in this area has been carried out through open-pit mining and unique underground mining. The geological identity of the deposit encompasses the origin, distribution, and petrological characteristics of the obsidian from Cerro de las Navajas, determined through detailed geological mapping, petrographic study, and geochemical analysis. The results reveal the obsidian deposit’s style as well as its temporal and spatial position within the eruptive evolution of the region. The deposit originated from a local explosive eruptive mechanism associated with the partial collapse of a lava dome, forming a Block and Ash Flow Deposit (BAFD). The obsidian blocks, exploited by different cultures, correspond to the pyroclastic blocks within this deposit, which can reach up to 1 m in diameter and are embedded in a weakly consolidated ash matrix. The BAFD was later buried by (a) subsequent volcanic events, (b) structural adjustments of the volcanic edifice, and (c) soils derived from the erosion of other volcanic units. This obsidian deposit was mined underground from the Early Formative period to the Colonial era by the cultures of the Central Highlands and colonized societies. Interest in the vitreous quality and exotic nature of obsidian lithics from the BAFD led to the development of a complex exploitation system, which was generationally refined by the Teotihuacan, Toltec, and Aztec states. Full article

As a significant geological hazard in large–scale engineering construction, deep subsurface voids demand effective and precise detection methods. Cross–hole radar tomography overcomes depth limitations by transmitting/receiving electromagnetic (EM) waves between boreholes, enabling the accurate determination of the spatial distribution and EM properties of subsurface cavities. However, conventional inversion approaches, such as travel–time/attenuation tomography and full–waveform inversion, still face challenges in terms of their stability, accuracy, and computational efficiency. To address these limitations, this study proposes a deep learning–based imaging method that introduces the concept of travel–time fingerprints, which compress raw radar data into structured, low–dimensional inputs that retain key spatial features. A large synthetic dataset of irregular subsurface cavity models is used to pre–train a UNET model, enabling it to learn nonlinear mapping, from fingerprints to velocity structures. To enhance real–world applicability, transfer learning (TL) is employed to fine–tune the model using a small amount of field data. The refined model is then tested on cross–hole radar datasets collected from a highway construction site in Guizhou Province, China. The results demonstrate that the method can accurately recover the shape, location, and extent of underground cavities, outperforming traditional tomography in terms of clarity and interpretability. This approach offers a high–precision, computationally efficient solution for subsurface void detection, with strong engineering applicability in complex geological environments. Full article

The former Provence coal basin, closed since 2003, has been monitored by a microseismic network since 2008. The objective is to detect the precursor signs of a brittle subsidence that would be caused by the collapse of the old underground mining works. Since the start of monitoring, no subsidence has affected the risk areas, and nearly 4000 events with a local magnitude between −3 < M_L < 3 have been recorded. One sector in particular, called the Fuveau swarm, located outside the risk zones and therefore outside the brittle subsidence hazard zones, has attracted attention since 2012 because it was the subject of several seismic episodes felt in 2010, 2012, 2014, late 2016–early 2017, and August 2017. Since 2017, it has been established that the observed seismicity cannot be explained only by instability phenomena in the old mining works. The most likely hypothesis is that of the remobilization of faults hydraulically connected to the mining works, with seismic activity that is closely linked to variations in the groundwater level, which are themselves influenced by pumping and effective rainfall. This paper shows, through multiplet analysis method of the seismic data recorded by the monitoring network stations, that part of the seismicity in the monitoring areas is also due to the reactivation of tectonic faults. This conclusion is based on the concordance between the location of the multiplets and the orientation of the main faults mapped in the studied areas, as well as on the fact that the strongest events belong to these multiplets. This finding underscores the need to integrate fault reactivation into seismic monitoring strategies, beyond the current focus on mining-induced instabilities. This conclusion leads us to recommend revising the list of post-mining hazards, as post-mining seismic risk is often overlooked in many European regulations. Full article

Swift urbanization and technical progress in Cambodia, specifically in Phnom Penh, require underground transmission lines (UGTL) as a viable substitute for overhead transmission lines (OHTL). However, the substantial cost of UGTL has prevented its extensive integration. In this respect, we identified the most cost-effective technological route for an underground transmission line between substations. Using geographic information system (GIS) data, we generated algorithms to define the optimal route for the installation of a UGTL and minimize the costs of the material and labor required. The research results presented an automated tool for route optimization which simplifies the planning of energy projects and partially relieves the financial burden of UGTL integration. The proposed method radically changes the planning of urban energy infrastructure, as it provides a technology-based, cost-efficient, and environmentally favorable decision for UGTL routing. It also fosters the development of sustainable and resilient urban energy systems in similar urban locations. Full article