Hasil untuk "Geology"

Shirong GE, Jing GUO

Deep coal resources with abundant reserves and considerable thermal potential are receiving increased attention in mining engineering, given the accelerating transformation of the global energy structure and the growing demand for clean energy. To address extraction challenges and environmental pressures while ensuring economic feasibility and sustainable development, efforts are made to enable carbon reduction and green transformation under high-efficiency utilization of deep coal resources. A systematic review of “deep coal resource fluidized mining”, “coal chemical mining”, and “coal-based power” informs the introduction of a detonation-generation mining approach and its technical framework. The approach places coal-powder detonation combustion technology at its core and integrates advanced detonation combustion-mechanical/magnetohydrodynamic power generation, forming a detonation-turbine/MHD hybrid power system that supports efficient conversion and clean utilization of coal resources. Four fundamental theories are presented, including the Coal-powder Detonation Energy Release mechanism, the Coupled Coal-powder Detonation-generation Power Scheme, a Full Life Cycle Detonation-power Generation Dynamic Management Mechanism, and the Blasting-electric Power Deep coal mining theory and method. Discussion centers on four key technologies: Stable coal/gas two-phase detonation, detonation model construction and dynamic process optimization, detonation-based power generation efficiency assessment, and comprehensive design for detonation-based coal mining, demonstrating their role in upgrading deep coal mining practices. On this foundation, a systematic engineering strategy is proposed to clarify the synergy between mining processes and the detonation-based power generation mode, highlight safety management and process optimization priorities at each critical stage, and refine the overall detonation-generation pathway for deep coal resource development. This pathway offers valuable insights for establishing a coal-based power system and promoting the clean and efficient utilization of deep coal resources in China.

Mohammed Saleh Alshaikh

The performance of Organic Solar Cells (OSCs) is intrinsically linked to the molecular, electronic, and structural properties of donor and acceptor materials. This study employs various machine learning techniques, namely the Generalized Regression Neural Network (GRNN), Support Vector Machine (SVM), and Tree Boost, to predict key performance metrics of OSCs, including power conversion efficiency (PCE), short-circuit current density (JSC), open-circuit voltage (VOC), and fill factor (FF). The models are trained and evaluated using an experimentally reported dataset compiled by Sahu et al. Correlation analysis demonstrates that material characteristics such as polarizability, bandgap, dipole moment, and charge transfer are statistically associated with OSC performance. The predictive performance of the GRNN model is compared with that of the SVM and Tree Boost models, showing consistently lower prediction errors within the considered dataset. In addition, sensitivity analysis is performed to assess the relative importance of the predictor variables and to examine the influence of kernel functions on GRNN performance. The results indicate that machine learning models, particularly GRNN, can serve as effective data-driven tools for predicting the performance of organic solar cells and for supporting computational screening studies.

Luzana Kamtangwala, Solomon Adeniyi Adekola, Jerome Edafe Asedegbega

Abstract The Nkhata basin located in the central part of the Malawi rift consists of Late Quaternary (Chibanian to present; <750 ka) sediments and are the youngest sediments within the great East African Rift System. Rock-Eval pyrolysis and Total Organic Carbon (TOC) analysis of 163 samples from cores GLAD7_MAL05_1B (56–390 m) and GLAD7_MAL05_1C (0–78 m), drilled in the western-central basin, integrated with X-ray Fluorescence (XRF) data are used to assess the source potential of these organic matter-rich sediments within Lake Malawi. Results reveal intervals of good to excellent organic matter-rich silty clay and carbonate mud (TOC > 6.02 wt% and S2 > 25.55 mg HC/g rock; 1 C: TOC up to 6.16 wt%, S2 up to 56.9 mg HC/g rock). The sediments were dominated by oil prone Type II and mixed Type II/II kerogens. Despite wide range TOC values (0.25–7.22 wt%) sandy silty clay facies show poor to good organic quantity and is dominated by Type III/IV kerogens. The overall thermal maturity index suggests immature to early oil window (Tmax: 327–444 °C; PI: 0.01–0.64) sediments. Redox proxies (V/Cr, V/(V + Ni), S/Fe) show deposition occurred under predominantly oxic-dysoxic bottom waters, with two discrete anoxic/euxinic events (1B: 186 m, 288–298 m). These events correlate with peak TOC values (6.02 wt% at 274.3 m), signifying that episodic euxinia significantly enhanced organic matter preservation by suppressing aerobic degradation. The Nkhata Basin exhibits compelling source rock characteristics comparable to other productive basins within the East African rift system but requires deeper burial to achieve generative maturity.

Laurence Datrier, Geoffrey Lovelace, Joshua R. Smith et al.

Cosmic Explorer (CE) is a proposed next generation gravitational-wave observatory that would be sited in the United States. As of 2025, CE is in its design phase, with plans to begin operations in the 2030s together with the Einstein Telescope in Europe. CE's reference design consists of two widely separated L-shaped detectors, one with 20km arms and one with 40km arms, each based on technology proven by the National Science Foundation's highly successful Laser Interferometer Gravitational Wave Observatory (LIGO). There are unique challenges associated with identifying locations suitable for hosting Cosmic Explorer in the conterminous United States, not least of which is the order of magnitude upscaling of the observatory with respect to the 4km LIGO observatories. Cosmic Explorer's approach to site evaluation integrates physical, social and cultural criteria. Here we present improvements to the Cosmic Explorer Location Search (CELS) code used to identify and assess locations where CE would have low construction costs incurred by the geology, geography and topography of the land. We also report on efforts to integrate astrophysical requirements established by the Cosmic Explorer Science Traceability Matrix into the site evaluation process. National-level results are presented and combined with results from a related National Suitability Analysis to provide a list of locations that are preliminarily promising for a 40km CE.

Joaquín Martínez-Minaya, Lore Zumeta-Olaskoaga, Dae-Jin Lee

Compositional data (CoDa) plays an important role in many fields such as ecology, geology, or biology. The most widely used modeling approaches are based on the Dirichlet and the logistic-normal formulation under Aitchison geometry. Recent developments in the mathematical field on the simplex geometry allow to express the regression model in terms of coordinates and estimate its coefficients. Once the model is projected in the real space, we can employ a multivariate Gaussian regression to deal with it. However, most existing methods focus on linear models, and there is a lack of flexible alternatives such as additive or spatial models, especially within a Bayesian framework and with practical implementation details. In this work, we present a geoadditive regression model for CoDa from a Bayesian perspective using the brms package in R. The model applies the isometric log-ratio (ilr) transformation and penalized splines to incorporate nonlinear effects. We also propose two new Bayesian goodness-of-fit measures for CoDa regression: BR-CoDa-$R^2$ and BM-CoDa-$R^2$, extending the Bayesian $R^2$ to the compositional setting. These measures, alongside WAIC, support model selection and evaluation. The methodology is validated through simulation studies and applied to predict soil texture composition in the Basque Country. Results demonstrate good performance, interpretable spatial patterns, and reliable quantification of explained variability in compositional outcomes.

Surangkhana Rukdee

Studying the atmospheres of exoplanets is one of the most promising ways to learn about distant worlds beyond our solar system. The composition of an exoplanet's atmosphere can provide critical insights into its geology and potential habitability. For instance, the presence of certain molecules such as water vapor, oxygen, or methane have been proposed to indicate the possibility of life. From an observation point of view, over the past fifteen years, significant progress has been made in characterizing exoplanetary atmospheres. This work reviews recent developments in ground-based high-resolution spectroscopic instruments that make it possible to analyze distant atmospheres in great detail. High-resolution transmission spectroscopy, one of the most effective methods used, has examined the atmospheres of Jupiter-like and is pushing towards the smaller, sub-Neptunian exoplanets. Numerous molecules have been detected using this technique, including CO,H2O,TiO,HCN,CH4,NH3,C2H2,OH. We explore the intriguing possibilities that lie ahead for future ground-based instrumentation, particularly in the context of detecting biologically relevant molecules within Earth-analog exoplanetary atmospheres including molecular oxygen (O2). With detailed exposure time calculations for detecting O2 we find that at the same exposure time spectral resolution of 300,000 reaches higher significance compared to 100,000. The exposure time and therefore the needed number of transits is reduced by a factor of 4 in challenging haze and cloud scenarios.

Mohd Hasfarisham Abd HALIM, Mohd Amin ALI, Shyeh Sahibul Karamah MASNAN et al.

This study provides primary evidence about the geological features in Kuala Muda district, indicating significant potential for development as a geotourism product. To collect primary data, we conducted survey and mapping activities to gather information about the current condition of 11 geosites, as well as the facilities already in place to facilitate seasonal tourism. In addition, a review of previous scientific research for each geosite is also carried out so that geosite speciality data can be summarized. The study's results have facilitated the creation of 17 tourism packages under the AncKed Sungai Batu Association, encompassing geology, geoarchaeology, biology, history, heritage, and culture tourism products in the Kuala Muda district. Offering tour packages enables the district to conduct knowledgeable tourism activities involving people from all walks of life and ages, with trained locals serving as tour guides. This ensures the preservation of geotourism at its optimal level.

Mingshuai Zhu, Daniel Pastor–Galán, Matthijs A. Smit et al.

Abstract The opening of oceans within accretionary orogens is important for understanding the Wilson cycle. The Mongol–Okhotsk Ocean (MOO) began opening within the early Paleozoic accretionary collage of the Central Asian Orogenic Belt (CAOB), representing a world‐class example to constrain the geodynamic history of ocean opening in accretionary orogens, but the kinematics and mechanisms associated to this process are highly debated. We report on a newly‐discovered bimodal volcanic suite and associated volcanic‐sediments that comprise part of the Altay‐Sayan Rift System, which indicate a widespread Early Devonian extensional event within the CAOB. This extension regime is attributed to a Devonian mantle plume, which is thought to have impinged upon and weakened the lithosphere of the Early Paleozoic collage, and drove the opening of the MOO. Opening of the MOO suggests continent breakup in accretionary orogens tends to focus along intervening weak orogenic lithosphere between the rigid microcontinents.

Yu Zhang, Lianjin Tao, Xu Zhao et al.

For the project of pipe jacking in cohesionless soil, it is key to determine the vertical load on jacked pipe so as to predict the jacking force accurately. In this paper, a new parabolic soil arching model was proposed to calculate the vertical load on jacked pipe. This proposed analytical model was composed of parabolic soil arching zone, parabola-typed collapse zone and friction arch zone. Combined with existing literature, the key parameters (i.e., height of parabolic soil arching, horizontal pressure coefficient and width and height of friction arch) were determined. In addition, considering that the trajectory of major stress is parabola, the formula of horizontal pressure coefficient was deduced in the friction arch. The parabolic soil arching zone is assumed as a three-hinged arch with reasonable arch axis, and the formula of load transfer was derived considering the transition effect of parabolic soil arching. The results of experiment, theoretical models and numerical model were adopted to verify the proposed analytical model. Finally, the influence of the key parameters on the vertical load on jacked pipe were also discussed in detail. This work provides a meaningful reference for evaluating the vertical load on jacked pipe for design of pipe jacking.

Hailu Gisha Kuma, Ermias Mekonnen Chinasho, Abrham Asha Tolke

Soil erosion and sediment buildup are the factors that speed up the decline in capacity and function of reservoirs, agricultural products, and water resources. In order to simulate sediment and runoff and map high sediment-yielding sub-basins in the Gibe Gojeb catchment in southwest Ethiopia, this study used the Soil and Water Assessment Tool (SWAT) model. Using data on sediment and river flow, calibration and validation were carried out. Between 2003 and 2016, the catchment produced an average annual sediment loading of 62.5 tons ha−1 yr−1, with loading fluctuations ranging from 0.2 to 108.4 tons ha−1 yr−1. The acceptable sediment yield threshold value ranges from 12.3 to 108.4 tons ha−1 yr−1 for 56 sub-basins, and from 0.2 to 10 tons ha−1 yr−1 for 5 sub-basins. The most significant sub-basins with very high to extremely severe sediment yields were sub-basins 1 to 30, 32 to 44, 47, 48, 50, 51, and 53 to 61. After thirteen years of operation, the yearly amount of 58,802 tons of sediment transferred from the catchment and deposited into Gibe One reservoir has decreased the capacity by 5.7 %. The accumulation of sediment in a reservoir has an impact on its functionality, power production, and capacity, affecting the safety of dams and the environment. The study's findings enhanced our comprehension of sediment accumulation in reservoirs and furnished us with the necessary information regarding reservoir safety, integrated soil, and water management.

Puyu Cao, Meicheng Yao, Bin Chen

As a fundamental force, friction exerts a profound influence on various aspects of our daily lives across multiple disciplines. To understand why adhesive friction is associated with the contact area, here we investigate the generic sliding of elastic solids adhered to a rigid surface by considering re-attachment/healing. We then reveal multiple adhesive fronts closely aligning along the interface with the number of these regions generally increasing with the contact area. These adhesive fronts exhibit rich dynamics and their accumulation along an interface can aid each other through re-attachment/healing in friction, apparently resulting in the increase in the calculated shear-off force with the contact area. Based on these findings, we propose a refined law of adhesive friction. Our analysis further suggests that accumulating adhesive fronts along the interface can trigger crack-like propagation of individual fronts at high velocities, which potentially bridges the gap between tribology and fracture mechanics. We also discuss the relevance of this work to earthquake mechanics, which might provide a unified framework that captures key aspects of fault behavior. We expect that this work can supply a fundamental understanding of healing-mediated interfacial phenomena in diverse systems spanning biology, geology, and engineering.

Zhiqin Ma, Chunhua Zeng, Yi-Cheng Zhang et al.

Complex systems can undergo critical transitions, where slowly changing environmental conditions trigger a sudden shift to a new, potentially catastrophic state. Early warning signals for these events are crucial for decision-making in fields such as ecology, biology and climate science. Generic early warning signals motivated by dynamical systems theory have had mixed success on real noisy data. More recent studies found that deep learning classifiers trained on synthetic data could improve performance. However, neither of these methods take advantage of historical, system-specific data. Here, we introduce an approach that trains machine learning classifiers directly on surrogate data of past transitions, namely surrogate data-based machine learning (SDML). The approach provides early warning signals in empirical and experimental data from geology, climatology, sociology, and cardiology with higher sensitivity and specificity than two widely used generic early warning signals -- variance and lag-1 autocorrelation. Since the approach is trained directly on surrogates of historical data, it is not bound by the restricting assumption of a local bifurcation like previous methods. This system-specific approach can contribute to improved early warning signals to help humans better prepare for or avoid undesirable critical transitions.

Juan Camilo Mejía-Fragoso, Manuel A. Florez, Rocío Bernal-Olaya

Accurate determination of the geothermal gradient is critical for assessing the geothermal energy potential of a given region. Of particular interest is the case of Colombia, a country with abundant geothermal resources. A history of active oil and gas exploration and production has left drilled boreholes in different geological settings, providing direct measurements of the geothermal gradient. Unfortunately, large regions of the country where geothermal resources might exist lack such measurements. Indirect geophysical measurements are costly and difficult to perform at regional scales. Computational thermal models could be constructed, but they require very detailed knowledge of the underlying geology and uniform sampling of subsurface temperatures to be well-constrained. We present an alternative approach that leverages recent advances in supervised machine learning and available direct measurements to predict the geothermal gradient in regions where only global-scale geophysical datasets and course geological knowledge are available. We find that a Gradient Boosted Regression Tree algorithm yields optimal predictions and extensively validate the trained model. We show that predictions of our model are within 12% accuracy and that independent measurements performed by other authors agree well with our model. Finnally, we present a geothermal gradient map for Colombia that highlights regions where futher exploration and data collection should be performed.

Marjana Zajc, Alojzij Grebenc

After the discovery of an archive document regarding an underground crypt beneath the floors of the Church of St. Margaret (Sv. Marjeta) in Dol pri Ljubljani, Slovenia, further research was carried out to confirm its presence. An area filled with construction waste was discovered during a recent small-scale renovation of the church floor. This finding suggested the potential underground chamber may have been partly filled in during one of the previous restorations. A non-invasive GPR study was carried out along eight profiles inside the church to prove the existence of an underground crypt. Results show the presence of an air-filled chamber, confirmed later by a hole drilled in the floor. Additional findings in the church archive and pictures taken by a camera, lowered through a drilled hole, revealed three previously unknown caskets in the crypt. According to the archives, two of them belong to Baron Wolf Daniel Erberg and his wife who died in 1783 and 1774, respectively.

Liurong Tao, Haoran Ren, Zhiwei Gu

Seismic impedance inversion is a vital way of geological interpretation and reservoir investigation from a geophysical perspective. However, it is inevitably an ill-posed problem due to the noise or the band-limited characteristic of seismic data. Artificial neural network have been used to solve nonlinear inverse problems in recent years. This research obtained an acoustic impedance profile by feeding seismic profile and background impedance into a well-trained self-attention U-Net. The U-Net got convergence by appropriate iteration, and the output predicted the impedance profiles in the test. To value the quality of predicted profiles from different perspectives, e.g., correlation, regression, and similarity, we used four kinds of indexes. At the same time, our results were predicted by conventional methods (e.g., deconvolution with recursive inversion, and TV regularization) and a 1D neural network was calculated in contrast. Self-attention U-Net showed to be robust to noise and does not require prior knowledge. Furthermore, spatial continuity is also better than deconvolution, regularization, and 1D deep learning methods in contrast. The U-Net in this paper is a type of full convolutional neural network, so there are no limits to the shape of the input. Based on this, a large impedance profile can be predicted by U-Net, which is trained by a patchy training dataset. In addition, this paper applied the proposed method to the field data obtained by the Ceduna survey without any label. The predictions prove that this well-trained network could be generalized from synthetic data to field data.

Shankar Dutt, Christian Notthoff, Xue Wang et al.

The annealing kinetics of the high energy ion damage in amorphous silicon dioxide (a-SiO2) are still not well understood, despite the material's widespread application in material science, physics, geology, and biology. This study investigates how annealing temperature, duration, and ambient environment affect the recovery of irradiation damage produced along the trajectory of swift heavy ions in a-SiO2. The track-annealing kinetics and the changing ion track morphology were investigated using synchrotron-based small-angle X-ray scattering (SAXS) and etching methods. We found that track annealing proceeds quicker near the sample surface demonstrated by a changing track etch rate as a function of depth. Measurements of ion tracks using SAXS show only small changes in the radial density distribution profile of the ion tracks. Activation energy of the annealing process at different sample depths was determined and the effect of the capping layer during the annealing process was also studied. Combination of oxygen diffusion and stress relaxation may contribute to the observed behaviour of preferential and anisotropic healing of the ion track. The results add to the fundamental understanding of ion track damage recovery and may have direct implications for materials for radioactive waste storage and solid state nanopores.

Hang Wang, Yunfeng Chen, Rui Min et al.

Distributed acoustic sensing (DAS) is an emerging technology for recording vibration signals via the optical fibers buried in subsurface conduits. Its relatively easy-to-deploy and high spatial and temporal sampling characteristics make DAS an appealing tool to record seismic wavefields at higher quantity and quality than traditional geophones. Considering that the usage of optical fibers in the urban environment has drawn relatively less attention aside from its functionality as a telecommunication cable, we examine its ability to record seismic signals and investigate its preliminary application in city traffic monitoring. To solve the problems that DAS signals are prone to a variety of environmental noise and are generally of weak amplitude compared to noise, we propose a fast workflow for real-time DAS data processing, which can enhance the detection of regular car signals and suppress the other components. We conduct a DAS experiment in Hangzhou, China, a typical metropolitan area that can provide us with a rich data library to validate our DAS data-processing workflow. The well-processed data enable us to extract their slope and coherency attributes that can provide an estimate of real traffic situations. The one-minute (with video validations) and 24 h statistics of these attributes show that the speed and volume of car flow are well correlated demonstrates the robustness of the proposed data processing workflow and great potential of DAS for city traffic monitoring with high precision and convenience. However, challenges also exist in view that all the attributes are statistically analyzed based on the behaviors of a large number of cars, which is meaningful but lacking in precision. Therefore, we suggest developing more quantitative processing and analyzing methods to provide precise information on individual cars in future works.

Denis Težak, Ivana Dobrilović, Mario Dobrilović et al.

Blasting in clay soil in the field of anchoring and foundation of objects and structures has its benefits in construction and geotechnical practice. The foundations of the method lay in the fact that a shock wave is generated when the explosive charge is detonated. The shock wave, with high pressure at the wavefront, causes the natural structure of the clay soil to be destroyed, and a spherical expansion in the clay mass is formed. The presented research is focused on determining the shape and volume of the resulting expansion in test blasts performed with several types of explosives. An application named Borehole was developed to determine the resulting spherical expansion formed after the detonation of an explosive charge with the integration of the GNSS method of measurement, depth camera, and laser. The application Borehole calculates expansion volume based on the coordinates obtained with the GNSS and the laser-obtained distance of the formed expansion and provides a graphical interpretation in 2D and 3D views. Additionally, when developing the application Borehole, compatibility with CAD tools was considered, primarily for better verification and a more detailed graphical interpretation of 3D views. The developed method allows for simple determination of the volume and dimension of the spherical expansion in clay soil with acceptable accuracy for the design and building of geotechnical structures constructed above and underground.

MA Jingzhi, QU Shaopeng, LI Guangyi et al.

BACKGROUND The fast detection of Cu, Pb, Zn and Ni in geochemical samples helps to determine the level of heavy metal pollution, thus assisting in the employment of efficient treatments. OBJECTIVES To establish a method for the simultaneous determination of Cu, Pb, Zn and Ni in geochemical samples by AC Arc direct reading atomic emission spectrometry with solid sampling technique. METHODS With sodium fluoride, alumina, silicon dioxide and carbon powder as buffer agents and germanium as the internal standard element, the element analysis line pairs were optimized, and the exposure time was also optimized at 25s. The standard curve of synthetic silicate was corrected using national first-class reference materials (soil, rock and sediment), so as to reduce the interference of the matrix. Sensitive line and hyposensitive line were selected to enhance the accuracy as well as expand the measurable linear range of elements. Average value of two parallel analyses was adopted for further improved analytical precision. RESULTS The detection limits of Cu, Pb, Zn and Ni were 0.45μg/g, 1.46μg/g, 2.40μg/g and 1.58μg/g, respectively. The precision ranges of the method were 1.36%-6.25% for Cu, 1.17%-8.06% for Pb, 1.64%-9.68% for Zn and 0.91%-5.31% for Ni. Measured values with this method for the national first-class reference materials of soil, sediment and rock were consistent with the certified values (|△logC| ≤ 0.05), qualification rates of the actual samples and external quality control samples were all above 90%. CONCLUSIONS With simple operation, direct solid sampling technique is applied. The method reported here is more environmentally friendly compared to the acid dissolving method, sample contamination caused by reagent blank and vessels used is avoided at the same time. The average results of twice spectral acquisitions are calculated, which is more accurate and precise than the single analysis reported in the literature. All indicators of this method are better than the requirements of regulation (1:250000) DZ/T 0130.5-2006.

Claudia Adam, Valérie Vidal, Pablo Grosse et al.

Abstract Arc volcanoes, created by magma generated from the dehydration of subducting slabs, show great variability in their sizes and along‐arc spatial distributions. In this study, we address a fundamental question, namely, how do subduction zones and volcanic arcs respond to the subduction of “atypical” oceanic lithosphere. We investigate the correlation between the geographical location and volume of arc volcanoes and the subduction of linear oceanic features, including hotspot tracks, oceanic plateaus, volcanic ridges, mid‐oceanic ridges, arc volcano chains, and fracture zones, around the Pacific basin. We use multidisciplinary and complementary data sets (topography and bathymetry, seismology and volcano morphometry), and design new analytical and data processing methods. We analyze 35 oceanic linear features. The subduction of three oceanic plateaus and five hotspot chains are clearly associated with volcanism increase, whereas four hotspot chains are related to volcanic gaps. We propose that the patterns of volcanism increase or decrease related to these oceanic features depend on the interplay between chemical (potentially enhancing melting) and thermo‐mechanical (inhibiting melting) effects, and/or by the variations of the chemical signatures along hotspot chains. The subduction of volcanic ridges is generally associated with small increases in arc volcanism, which may be accounted for by the fact that these features are highly hydrated and therefore promote melt. The subduction of active mid‐oceanic ridges is generally associated with slab windows and arc volcano gaps. No clear inference is found for the subduction of inactive arc ridges.