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Understanding earthquake nucleation is vital for predicting and mitigating seismic events, saving lives, and enhancing construction practices in earthquake-prone areas. Cascade triggering and preslip triggering are prevalent theories, posing challenges in differentiation based on field observations. Our study employs a novel unsupervised machine learning pipeline, integrating macroscopic- and grain-scale data from stick-slip experiments in a discrete element method (DEM) framework. Running 27 simulations, we cluster foreshocks and mainshocks separately and assess their correlation. The study supports the cascade triggering model on the macro-scale, as we did not observe any scaling between nucleation parameters and the mainshock size. On the other hand, further grain-scale analysis identifies that, separate from Coulomb stress transfer, there is an additional mechanism related to shear stress accumulation on the fault, which is likely the preslip triggering. Overall, while foreshocks may not directly influence the trend at which contact force evolves, they could prime the fault for dynamic rupture by increasing the proportion of contacts accumulating shear stresses. Our findings infer the possible coexistence of the two theorized mechanisms. [ABSTRACT FROM AUTHOR]

The level of detail (LOD) modelling of vector and terrain data is individual, resulting in geometric and topological inconsistencies in simplification processes. The three dimension Douglas Peucker (3D_DP)algorithm can realize gradual discrete point selection through threshold, which is mainly used in DEM synthesis, and its simplified process is very suitable for the dynamic establishment of massive data sets. A new LOD modeling method based on 3D_DP algorithm is proposed to simplify the consistency of river network vector elements and DEM in this paper. The specific steps are as follows: Firstly, the "Bending Adjustment Index (BAI)" is introduced to improve the 3D_DP algorithm, called the improved 3D_DP algorithm; Secondly, the DEM data is extracted into a 3D discrete point dataset, and the river line vector data is also converted into a discrete point dataset, assigned with elevation attributes, and merges with the DEM's 3D discrete points. The merged point datasets are equenced based on the importance of each point, which are computed by the improved 3D_DP algorithm. The order of deleting points is determined by the sequence and the corresponding model spatial errors are calculated with the deletion of points. Then, the DEM's 3D discrete points are constructed a Delaunay network with the river line as a mandatory constraint condition. The required triangulation is called in real time with the change of sight distance depending on the simple correspondence between screen projection error and model space error, and the unified LOD model for river line vector and DEM is established. The results show that the river's overall shape and the terrain's main features can be reserved under the same simplified factor based on the improved 3D_DP algorithm. The unified LOD model for the river network and DEM is feasible under the importance sequence of merged point datasets by the improved 3D_DP algorithm. Under the proper operation of data blocking, the rendering frame rate can meet practical application requirements. [ABSTRACT FROM AUTHOR]

Typical temperature characteristic of cold air pool (CAP) in the main producing areas of Xihu Longjing plantation was analyzed using data from 29 automatic meteorological stations and radar sounding inversion data during spring tea budding period in 2021. A method was explored to automatically identify areas prone CAP under complex terrain. The results showed that the occurrence frequency of CAP day was 45% in typical prone CAP areas of Xihu Longjing plantation from February 20 to March 31, 2021. The occurrence frequency and intensity of CAP were related to weather types. CAP was more likely to occur on sunny and cloudy weather conditions, less on overcast weather conditions, and strong CAP days predominantly appearing under clear sky conditions. CAP increased the frequency and intensity of inversions, with an increase of 23% in inversion frequency, and an increase of 1.26℃ per 100m in average maximum inversion intensity compared to flat areas. A typical daily variation of CAP included three stages: formation and strengthening, maintenance, and weakening and dissipation, with the maximum hourly temperature increase at the valley during the weakening and dissipation stage reaching 11.3℃·h−1, which was 4.1℃·h−1 higher than the maximum hourly temperature decrease during the formation and strengthening stage (7.2℃·h−1 ). To identify the CAP prone areas, three terrain factors in DEM data including slope, percentile of height relative to surroundings, and terrain curvature were constructed as discriminant indicators showing good identification effectiveness. Coincidence rates of stations located in CAP prone and non prone areas were 80% and 78% respectively. About 26% of the tea plantation in study area was located in CAP prone areas, making them more susceptible to spring tea frost damage during the budding period due to extreme low temperatures and rapid warming processes. [ABSTRACT FROM AUTHOR]

Traditional terrain analysis has relied on Digital Topographic Maps produced by national agencies and Digital Elevation Models (DEMs) created using Airborne LiDAR. However, these methods have significant drawbacks, including the difficulty in acquiring data at the desired time and precision, as well as high costs. Recently, advancements and miniaturization in LiDAR technology have enabled its integration with Unmanned Aerial Vehicles (UAVs), allowing for the collection of highly precise terrain data. This approach combines the advantages of conventional UAV photogrammetry with the flexibility of obtaining data at specific times and locations, facilitating a wider range of studies. Despite these advancements, the application of UAV LiDAR in terrain analysis remains underexplored. This study aims to assess the utility of UAV LiDAR for terrain analysis by focusing on the doline features within karst landscapes. In this study, we analyzed doline terrain using three types of data: 1:5000 scale digital topographic maps provided by the National Geographic Information Institute (NGII) of Korea, Digital Surface Models (DSMs) obtained through UAV photogrammetry, and DEMs acquired via UAV LiDAR surveys. The analysis results indicated that UAV LiDAR provided the most precise three-dimensional spatial information for the entire study site, yielding the most detailed analysis outcomes. These findings suggest that UAV LiDAR can be utilized to represent terrain features with greater precision in the future; this is expected to be highly useful not only for generating contours but also for conducting more detailed topographic analyses, such as calculating the area and slope of the study sites. [ABSTRACT FROM AUTHOR]

In recent years, drone-based Synthetic Aperture Radar (SAR) systems have emerged as flexible and cost-efficient solutions for detecting changes in the Earth's surface, retrieving topographic data, or detecting ground displacement processes in localized areas, among other applications. These systems offer a unique combination of short and versatile revisit times and flexible acquisition geometries that are not achievable with space-borne, airborne, or ground-based SAR sensors. However, due to platform limitations and flight stability issues, they also present significant challenges regarding instrument design and data processing, particularly when generating interferometric repeat-pass datasets. This paper demonstrates the feasibility of repeat-pass interferometry using a Ku-band drone-based SAR system. The system integrates a dual-channel Ku-band Frequency Modulated Continuous Wave (FMCW) radar with cross-track single-pass interferometric capabilities, mounted on a drone platform. The proposed repeat-pass interferometric processing chain leverages an accurate Digital Elevation Model (DEM), generated from the single-pass interferograms, to precisely coregister the entire stack of acquisitions, thereby producing repeat-pass interferograms free from residual motion errors. The results underscore the potential of this system and the processing chain proposed for generating multi-temporal repeat-pass stacks suitable for repeat-pass applications. [ABSTRACT FROM AUTHOR]

The discrete element method (DEM) is employed to investigate the impact of coupling between volumetric and axial strains on the flow liquefaction vulnerability of 3D cubic particulate specimens. The virtual testing program conducted here encompasses a wide range of initial states and varying degrees of coupling between volumetric and axial strains. Utilizing data obtained from DEM simulations, the evolution of micro- and macroscale variables, including coordination number, contact fabric anisotropy, redundancy index, strong force networks, invariants of the effective stress tensor, and excess pore-water pressure, is examined. Results from DEM tests indicate that coupling expansive volumetric strain with axial strain leads to a gradual loosening of the load bearing microstructure, a decrease in coordination number, and a faster change in contact anisotropy. DEM simulations demonstrate that the triggering of flow liquefaction instability is followed by a sudden increase in contact fabric anisotropy and abrupt drops in coordination number and redundancy index. Moreover, a detailed analysis of the findings suggests that the stress ratio at the onset of post-peak softening decreases with increasing expansive volumetric strains. [ABSTRACT FROM AUTHOR]

Vicens-Miquel, M.; Williams, D.D., and Tissot, P.E., 2024. Analysis of sandy beach morphology changes and inundation events from a high spatiotemporal resolution dataset. Journal of Coastal Research, 40(6), 1001–1018. Charlotte (North Carolina), ISSN 0749-0208. Coastal inundation creates significant beach management and conservation challenges. The frequency of these events is increasing because of the influence of sea-level rise in combination with background erosion and subsidence in some areas. More accurate predictive models are needed to anticipate potential coastal inundation events for public safety and protection of backshore infrastructure, as well as beach management that can be improved by including the influence of wave runup. Improvement of prediction accuracy requires an in-depth exploration of changes in beach morphology over time and an understanding of the complex interactions responsible for change. This study focuses on changes in beach morphology along a representative beach segment adjacent to Horace Caldwell Pier, Port Aransas, Texas. Ongoing monitoring, initiated in July 2022, provides a rich dataset for analyzing 21 beach-profile surveys, capturing the dynamic evolution of the coastal landscape. Emphasis is placed on quantifying the influence of metocean conditions, particularly high waves with varying periodicity, and wind patterns on morphologic alterations. This research identified two types of inundation events, with two of them resulting in erosion. Consequently, the findings suggest a correlation between the onset of erosion and a maximum dominant wave period of approximately 10 seconds in the study area. The findings contribute to a better understanding of the challenges inherent in predicting coastal inundation and event-based beach morphology changes, fostering informed decision-making that supports sustainable coastal management and developing effective conservation practices. [ABSTRACT FROM AUTHOR]

The interface is the weakest region of the coal-backfilling composite structure (CBCS) for underground mines, the sawtooth angles of which is one of the most critical concerns to be accounted. However, limited studies have focused on the deformation and failure behaviours of CBCS with different interface sawtooth angles under double shearing. To investigate the effect of interface sawtooth angles on the damage characteristics of CBCS under double shearing, CBCS with different interface sawtooth angles (i.e., 0°, 15°, 30°, 45°, 60°) were prepared and double shearing tests were carried out in the present research. Macroscopic failure characteristics (i.e., failure mode, failure process, and shear strength) of the CBCS were experimentally investigated via the digital image correlation (DIC), acoustic emission (AE), and 3D scanner system, whereas microscopic feature of which, including the contact force–microcrack evolution, and displacement vector of CBCS were numerical simulated by the discrete element modelling (DEM) method. The results showed that the failure modes of the CBCS can be classified into three types (e.g., climbing failure, cutting failure, and sliding failure). Among them, the climbing failure was only occurred when the loads on the sawtooth surfaces exceeded its shear strength, while the cutting failure occurred if the load on the sawtooth end of the coal element or backfilling element exceeded its shear strength. The sliding failure occurred, because the load applied to the interface exceeded the shear strength of the specimen interface. Moreover, the peak shear stress, the degree of strain concentration, and the extent of the strain concentration zone of the CBCS increased with the enlarged sawtooth angle. The research outcomes will contribute to obtain an in-depth understanding about the mechanical response of the coal-backfill composites under double shear loading. Highlights: Double shearing tests were carried out on coal-backfilling composite structures and the shear behaviour of CBCS was observed by DIC and AE monitoring systems. The contact force–microcrack distribution and displacement vector of CBCS during double shearing were investigated using DEM. Deformation and failure characteristics of CBCS were revealed from a microscopic and macroscopic perspective. The mechanisms of the double shearing failure process of CBCS with different interface sawtooth angles were revealed. [ABSTRACT FROM AUTHOR]

Accurate simulation of laboratory undrained and cyclic triaxial tests on granular materials using the Discrete Element Method (DEM) is a crucial concern. The evolution of shear bands and non-uniform stress distribution, affected by the membrane boundary condition, can significantly impact the mechanical behavior of samples. In this work, the flexible membrane is simulated by using the Finite Element Method coupled with DEM. In addition, we introduce a hydro-mechanical coupling scheme with a compressible fluid to reproduce the different undrained laboratory tests by using the membrane boundary. The evolution of pore pressure is computed incrementally based on the variation of volumetric strain inside the sample. The results of the membrane boundary condition are compared with more classical DEM simulations such as rigid wall and periodic boundaries. The comparison at different scales reveals many differences, such as the initial anisotropic value for a given preparation procedure, fabric evolution, volumetric strain and the formation of shear bands. Notably, the flexible boundary exhibits more benefits and better aligns with experimental data. As for the undrained condition, the results of the membrane condition are compared with experimental data of Toyoura sand and rigid wall boundary with constant volume. Finally, stress heterogeneity during undrained monotonic and cyclic conditions using the membrane boundary is highlighted. [ABSTRACT FROM AUTHOR]

This study investigates the influence of particle shape on the void space morphology and topology in granular materials. Numerical samples with spherical and ellipsoidal particle shapes were generated using the discrete element method. A segmentation algorithm was used to extract the pore space characteristics. The results reveal that particle shape significantly affects both constriction and pore sizes, with distinctive features according to flatness index or elongation ratio, the former being more significant than the latter. The obtained results were validated by conducting numerical filtration tests, which illustrated a direct correlation between the constriction properties derived from the pore space extraction and the blockage rate of fine particles in the filtration tests. The study revealed the importance of considering particle shape in filter design, emphasising its significant impact on pore space characteristics and filtration performance. [ABSTRACT FROM AUTHOR]

Peri-urban catchment areas are increasingly susceptible to floods due to rapid land use transformations and unplanned urban expansion. This study comprehensively examines flood vulnerability in the rapidly developing peri-urban areas of North Bhubaneswar, focusing on significant changes in Land Use/Land Cover (LULC) and hydrological dynamics from 2004 to 2024, utilizing Geographic Information System (GIS) tools. The analysis reveals substantial shifts in land use patterns, with the urban footprint expanding by 71.8%, cropland decreasing by 21.7%, and forest areas by 13.6%. These changes have led to increased impervious surfaces, resulting in higher surface runoff and decreased groundwater recharge, thereby exacerbating flood risks in the region. The GRID-based vulnerability analysis classifies 90 villages within the catchment area based on their vulnerability levels, identifying 20 villages as high-risk areas requiring urgent attention, 44 villages as medium vulnerable, and 26 villages as low vulnerable. These classifications are based on factors such as proximity to drainage networks, slope, geomorphology, and LULC characteristics, with areas near drainage channels and low-lying regions being prone to flooding. The analysis integrates multiple factors to provide a comprehensive assessment of flood risk, highlighting the need for sustainable land use planning, conservation of vegetated areas, and the implementation of advanced flood prevention strategies in the peri-urban areas. Extending this research to other fringe regions could offer further valuable insights, guiding flood prevention and sustainable development strategies for areas undergoing significant land use transformations to effectively mitigate future flood risks. [ABSTRACT FROM AUTHOR]

High‐resolution digital elevation models (HRDEMs), derived from LiDAR, are widely used for mapping hydrographic details in flat terrains. However, artificial flow barriers, particularly from roads, elevate terrain and prematurely end flowlines. Drainage barrier processing (DBP), such as HRDEM excavation, is employed to address this issue. However, there is a gap in quantitatively assessing the impact of DBP on HRDEM‐derived flowlines, especially at finer scales. This study fills that gap by quantitatively assessing how DBP improves flowline quality at finer scales. We evaluated HRDEM‐derived flowlines that were generated using different flow direction algorithms, developing a framework to measure the effects of flow barrier removal. The results show that the primary factor influencing flowline quality is the presence of flow accumulation artifacts. Quality issues also stem from differences between natural and artificial flow paths, unrealistic flowlines in flat areas, complex canal networks, and ephemeral drainage ways. Notably, the improvement achieved by DBP is demonstrated to be more than 6%, showcasing its efficacy in reducing the impact of flow barriers on hydrologic connectivity. [ABSTRACT FROM AUTHOR]

The Andes region has an exceptional record of high-altitude settlements integrated within widespread regional chains of mobility and exchange. The Sierra de Aconquija (NW Argentina, south-central Andes) is an effective climatic barrier that has afforded an enduring indigenous approach to land use, mobility, and exchange over millennia. Despite this rich history, the Sierra has been largely considered marginal in pre-Columbian regional cultural developments. Today, the expansion of extractive industries threatens the region's heritage and the sustainable futures of local communities. Innovative, integrative methodologies are needed for landscape characterisation, heritage assessment, and sustainable policy development. Building on earlier work, we undertook the first comprehensive mapping of archaeological features over 3800 sq. km of the Sierra using interpreter-led assessment of commercial and open-access satellite imagery and DSM data, to verify earlier assumptions and to identify previously unnoticed trends in the aggregation, distribution, and connectivity of archaeological features. The mapping identified 6794 features distributed unevenly but with clear tendencies towards maximising topographic, ecologic, and connectivity advantages expressed consistently across the study area. The outcomes confirm the important role the Sierra had in pre-Hispanic times, highlighting the significance of ancient indigenous practices for the sustainability of vulnerable upland landscapes both in the Andes and worldwide. [ABSTRACT FROM AUTHOR]

AbstractAs the domain of artificial intelligence has advanced, the integration of deep learning techniques into terrain and landform analysis has become more prevalent. Nevertheless, many existing methods are fully supervised and designed for specific tasks; thus, their transferability is limited and massive annotated samples are required. This study introduces a geomorphic pretrained model (GeomorPM) capable of performing multiple tasks. First, an architecture was designed that combined a convolution-based Vector Quantised-Variational Autoencoder (VQVAE) with a Transformer-based masked autoencoder (MAE) framework, allowing it to autonomously learn local details and global patterns from large-scale digital elevation model (DEM) data. Subsequently, GeomorPM, based on the VQMAE architecture, was pretrained on massive DEM data and fine-tuned for three specific tasks: DEM void filling, DEM superresolution, and landform classification. GeomorPM outperformed the traditional and other deep learning methods in all three tasks, demonstrating the superior learning ability and transferability of the model. This study provides a practical framework for developing pretrained models based on DEMs that can be expanded to other continuous geoscientific data. [ABSTRACT FROM AUTHOR]

The present study using a 90-m resolution Shuttle Radar Topography Mission (SRTM), digital elevation model (DEM), and geospatial techniques and an in-depth study of geomorphic and structural characteristics has been carried out for the Cauvery River basin (CRB) of India. The study of terrain characteristics and their evolution has, in fact, been transformed in recent years by the combination of remote sensing data such as the SRTM, DEM with GIS technology. The analysis involves morphometric assessments of the drainage system, focusing on linear, aerial, and relief aspects. Additionally, the longitudinal profile analysis synthesizes the influence of lithology on the basin's characteristics. Notably, Cauvery is identified as the 8th order drainage basin, covering a substantial area of 85,071.6 km2. River basin structural control is found to be low to moderate, according to the bifurcation ratio study. Because of the hard rock lithology, there is less stream frequency (0.22) and drainage density (0.6 km/km2), which indicates that there may be more permeability in the strata below the surface, river's mean stream length, which varies from 1.8 to 241.4 for all orders, and the stream length ratio, which varies from 0.38 to 0.65, which has a surface area of 85,071.6 sq. km and a circumference of roughly 2573.2 km. The vastness of the basin, as seen by its area and perimeter, emphasizes how important it is to the dynamics of peak flow and runoff in hydrological processes. The basin is extremely elongated, as indicated by the shape parameters, which makes managing flood control within the basin comparatively easier and river watershed management. [ABSTRACT FROM AUTHOR]

AbstractThe determination of the pullout capacity of anchors has been a key point of offshore and onshore applications, considering factors such as the shape, size, penetration velocities, and pull-out velocities of the anchors. Multi-plate expandable anchors can be considered as an alternative that exhibits higher capacity compared to single plate anchors. While previous studies have demonstrated the influence of penetration velocity, there is a lack of research investigating the pullout capacity of multi-plate expandable anchors. In the present study, experimental tests were conducted to investigate the effect of various pull-out velocities. Different soil relative densities and the distance between anchors were examined in the laboratory tests. The study also employed two analytical methods—constant control volume and movement control volume—to investigate the results of pull-out velocity. In addition, the Discrete Element Method (DEM) was used to analyze the effect of particle shape on the results. In the experimental tests, the findings suggest that increasing the pull-out velocity from 10 to 30 mm/min improved the pullout capacity of anchors and the optimal distance between plate anchors was determined to be 1B. The DEM findings showed that the sharp-cornered shape had good agreement with experimental results. [ABSTRACT FROM AUTHOR]

A novel high-temperature particle solar receiver is developed using a light trapping planar cavity configuration. As particles fall through the cavity, the concentrated solar radiation warms the boundaries of the receiver and in turn heats the particles. Particles flow through the system, forming a fluidized bed at the lower section, leaving the system from the bottom at a constant flowrate. Air is introduced to the system as the fluidizing medium to improve particle heat transfer and mixing. A laboratory scale cavity receiver is built by collaborators at the Colorado School of Mines and their data are used for model validation. In this experimental setup, near IR quartz lamp is used to provide flux to the vertical wall of the heat exchanger. The system is modeled using the discrete element method and a continuum two-fluid method. The computational model matches the experimental system size and the particle size distribution is assumed monodisperse. A new continuum conduction model that accounts for the effects of solid concentration is implemented, and the heat flux boundary condition matches the experimental setup. Radiative heat transfer is estimated using a widely used correlation during the post-processing step to determine an overall heat transfer coefficient. The model is validated against testing data and achieves less than 30% discrepancy and a heat transfer coefficient greater than 1000 W/m2 K. [ABSTRACT FROM AUTHOR]

Aquatic habitat analysis is crucial in determining the relationship between river flow and habitat availability for aquatic species. This helps in identifying the environmental flow requirements of rivers. However, conducting habitat analysis in Indian rivers is challenging because of the unavailability of reliable and high-resolution terrain data. To address this challenge, a study was conducted to explore the possibilities of using Digital Elevation Models (DEMs) to extract required hydraulic data and to evaluate their accuracies. The extracted data were coupled with ecological data of a keystone fish species, namely Golden Mahseer (Tor putitora), to develop habitat analysis models for the Upper Ganga Basin (UGB) in India. The study adopted a hierarchical three-step approach for evaluating the accuracy and performance of DEMs as surrogate data sources. Firstly, cross sections at selected sites in the UGB were extracted from three different DEMs (SRTM, ASTER, and CARTOSAT) and evaluated against surveyed cross-section data with turning point tests and correlation coefficients. These data were then used to establish hydraulic and habitat analysis models. Four parameters (top width, flow cross-sectional area, hydraulic mean depth, and wetted perimeter) were evaluated using five error estimators to determine the accuracy and performance of hydraulic modelling. Finally, the hydraulic parameters were coupled with ecological requirements to develop a habitat model for different life stages of Golden Mahseer, namely fingerling, juvenile, and adult stages. We found that the SRTM predictions were better than those of the other DEMs, indicating its suitability to replicate channel geometry with higher accuracy, thus better predicting hydraulic parameters at all flow ranges. In habitat area estimation for adult Golden Mahseer, all the DEMs performed reasonably well (within ±20%) within the flow range of 100 m³/s, which covers the low to average flow season. Beyond this flow range, ASTER and CARTOSAT resulted in considerable underestimations, averaging 22% and 54%, respectively. It is important to note that DEM-based cross sections lack high-resolution channel information, resulting in unstable habitat predictions for younger life stages like fingerling. However, overall, the study established that DEM-based data can be relied upon for habitat modelling-based assessment of environmental flows with some precautions for sensitive cases. Remote sensing presents a promising avenue for habitat analysis studies of Indian species, offering the potential to unlock significant progress in environmental flows (E-Flows) assessments and thus providing ecological benefits. [ABSTRACT FROM AUTHOR]

The study was carried out to see whether it would be possible to use remote sensing and Geographic Information System (GIS) to create a morphometric geodatabase for the largest valley basin in the western Plateau (Houran Valley), Iraq. ArcGIS V.10.8 measured morphological or hydrological features using a digital elevation model (DEM). These properties are considered a crucial database for planning for dry or wet river basins and valleys, saving time, money, and resources compared to extensive regional research. A quantitative investigation of the morphological characteristics determined that the longitudinal drain density was 0.1698 km/Km2, indicative of both high soil permeability and an arid to semi-arid desert environment. The basin is in an early geomorphological stage, and the linear structures determined the design of its drainage network according to the circulation ratio of 0.08566. area's geological structure has considerable changes in hardness, as indicated by the elongation ratio of 0.112, which would facilitate the use of water in the process of the area's sustainable development. [ABSTRACT FROM AUTHOR]

Soil arching is one of the main load transfer mechanisms of geosynthetic‐reinforced and pile‐supported (GRPS) embankments. This study established a numerical spring‐based trapdoor model that can consider the coupling effect between embankment filling, horizontal geosynthetic, piles, and soft soil between piles by the discrete element method (DEM). The effects of multiple factors on the deformation pattern, load transfer, and the settlement at the top surface of GRPS embankments were analyzed, such as soft soil stiffness, geosynthetic stiffness, fill height, and pile clear spacing. The multiple spring‐based trapdoor (MS‐TD) model effectively replicated the actual deformation of soft soil between piles in engineering practice by elucidating the nonuniform settlement of the fill on the trapdoor. Although the geosynthetic indirectly reduces the load transferred to the pile top by weakening the soil arching, it can directly increase the load transferred to the pile top by the membrane effect, thereby increasing the total load transferred to the pile top. The effect of the geosynthetic on reducing settlement decreases with the increase of soft soil stiffness, and the displacement reduction ratio at the top surface remains unchanged when it exceeds a certain value. In addition, the shape of the soil arch evolves rather than unchanged during the growth of pile clear spacing. [ABSTRACT FROM AUTHOR]

The anisotropic microstructure of granular materials has a profound effect on their macroscopic behaviour and can be characterised using a fabric tensor. To include of fabric in the critical state theory (CST), anisotropic critical state theory (ACST) was proposed by modifying the state parameter (ψ) of CST to a fabric-dependent dilatancy state parameter (ζ) . Noteworthy that ψ showed a very strong correlation with characteristic features (e.g. instability, phase transformation and characteristic state) of macroscopic behaviour and, as a result, it has been adopted in many constitutive models. While ζ aided the inclusion of fabric in ACST models, the correlation between ζ and characteristic features has not been evaluated in detail yet, although a large number of works are found on micromechanics and fabric only. In this study, a large number of discrete element method simulations for drained and undrained triaxial were conducted to evaluate the correlation between ζ and characteristic features. To this purpose, the correlation between stress ratio and both classic and dilatancy state parameter (ψ and ζ ) were studied in important characteristic features (e.g. instability, phase transformation and characteristic state). It was found that this correlation was improved using ζ which might be due to the inclusion of fabric in our model. This observation is new and significant for inclusion of fabric evolution in constitutive modelling. [ABSTRACT FROM AUTHOR]

A new model called the Transformer-Unet Generative Adversarial Network (TUGAN) is proposed for super-resolution reconstruction of digital elevation models (DEMs). Digital elevation models are used in many fields, including environmental science, geology and agriculture. The proposed model uses a self-similarity Transformer (SSTrans) as the generator and U-Net as the discriminator. SSTrans, a model that we previously proposed, can yield good reconstruction results in structurally complex areas but has little advantage when the surface is simple and smooth because too many additional details have been added to the data. To resolve this issue, we propose the novel TUGAN model, where U-Net is capable of multilayer jump connections, which enables the discriminator to consider both global and local information when making judgments. The experiments show that TUGAN achieves state-of-the-art results for all types of terrain details. [ABSTRACT FROM AUTHOR]

This paper presents a numerical study on the investigation of microscopic mechanism governing the interaction of woven geotextile and angular sand employing the 3D discrete element method (DEM). The surface texture and tensile properties of the geotextile were simulated using overlapping spherical particles, and the angular sand was simulated using rigid blocks. The DEM models were fully calibrated based on previous experimental data. The shear and dilation zones of sand near the interface were quantitatively determined based on particle displacement gradients. Analysis of contact forces was conducted to explain the microscopic mechanism behind the macroscopic strength evolution. The influence of geotextile surface roughness on the shear strength of the geotextile-sand interface is also discussed. The results show that the failure mode of the woven geotextile-sand interface is a combination of particle sliding failure along the geotextile surface and shear failure of the sand within the shear zone above the interface. There is a rapid redistribution of contact forces prior to reaching peak shear resistance, and the average normal contact force within the shear zone remains relatively constant after the peak shear stress is achieved. A completely developed shear zone stabilizes soil deformation, typically after achieving the peak shear resistance. • The thickness of the stabilized shear zone decreases as the normal stresses increase. • The shear zone is completely developed after the peak shear resistance is reached. • Contact forces are rapidly redistributed prior to reaching peak shear resistance. • The evolution of shear strength is caused by interparticle sliding in the shear zone. [ABSTRACT FROM AUTHOR]

Cirque landforms, which are distinctive features of cold regions, play a pivotal role in understanding environmental changes and climate research. Currently, machine learning-based automatic glacier recognition models have significantly improved recognition speed. However, these models rely solely on elevation data from Digital Elevation Model (DEM), neglecting other topographic factors that influence cirque identification, such as slope and aspect. This study integrates DEM, slope, and aspect data through pseudo-color fusion technology and utilizes the RetinaNet network to achieve automatic cirque recognition. The pseudo-color fusion image-based recognition model outperforms methods solely relying on DEM, achieving mAP (Intersection over Union: IoU @0.5) of 82.3 %. In practical applications, the pseudo-color fusion image-based recognition model demonstrates balanced performance in identifying different categories of cirques, particularly excelling in recognizing intricate terrains and irregularly shaped cirques. [ABSTRACT FROM AUTHOR]

To improve the crushing efficiency and crushing pass rate of high-moisture corn ears (HMCEs), a multi-stage crushing scheme is proposed in this paper. A two-stage crushing device for HMCEs is designed, and the ear crushing process is analyzed. Firstly, a simulation model for HMCEs was established in EDEM software (2018), and the accuracy of the model was verified by the shear test. Subsequently, single-factor simulation experiments were conducted, with the crushing rate serving as the evaluation index. The optimal working parameter ranges for the HMCE device were identified as a primary crushing roller speed of 1200–1600 revolutions per minute (r/min), a secondary crushing roller clearance of 1.5–2.5 mm, and a secondary crushing roller speed of 2750–3750 r/min. A Box–Behnken experiment was conducted to establish a multiple regression equation. With the objective of maximizing the qualified crushing pass rate, the optimal combination of parameters was revealed: a primary crushing roller speed of 1500 r/min, a secondary crushing roller clearance of 2.5 mm, and a secondary crushing roller speed of 3280 r/min. The pass rate of corn cob crushing in the simulation test was 98.2%. The physical tests, using the optimized parameter combination, yielded a qualified crushing rate of 97.5%, which deviates by 0.7% from the simulation results, satisfying the requirement of a qualified crushing rate exceeding 95%. The experimental outcomes validate the rationality of the proposed crushing scheme and the accuracy of the model, providing a theoretical foundation for subsequent research endeavors. [ABSTRACT FROM AUTHOR]

The materials involved in geotechnical engineering are objects of concern in granular mechanics. In order to study the influence of the sliding friction coefficient corresponding to different-sized elements in the discrete element method (DEM) on the simulation results, we establish a two-dimensional DEM model based on the experimental method to analyze a slope example. The correctness of the DEM model is verified by comparing the sliding surface of a finite element method (FEM) model and the DEM slope model. A sliding friction coefficient algorithm based on the experimental method is embedded into the DEM slope model and compared with the original model. The comparison results show that embedding the DEM model into the sliding friction coefficient algorithm leads to an increase in displacement. The reason for this is that the contact information between elements of different sizes has changed, but the displacement trend is the same. Different sliding friction coefficients should be set based on different-sized elements in the DEM, as they can improve simulation accuracy. [ABSTRACT FROM AUTHOR]

The Digital Elevation Model (DEM) is a typical type of topographic data. Data on elevation are often used as a major information source for analysis and modeling by geographic information systems. Modern continuous changes across space are represented by DEM. Particularly, the European Union Digital Elevation Model (EU-DEM), a new dataset derived from the EU's Copernicus Land Monitoring Service, which features contours developed for all DEMs which are compared with the contours of a topographic map. One of the most important sources of topographical information is the Advanced Spaceborne Thermal Emission and Reflection Radiometer Global Digital Elevation Model (ASTER GDEM). Compared to data from the Ground Control Points (GCPs), the vertical differences in ASTER products are utilized to calculate the Root Mean Squared Error (RMSE). The vertical accuracy of this DEM is assessed to be 13.13 m, which is the RMSE that was determined based on the data collected in the field by GNSS. In addition, the Standard Deviation (SDT) error came in at 2.60 m. After considering the effect of correcting bias, the error findings may range from a minimum of -6.47 m to a maximum of 1.998 m. Variations in RMSE and SDT are less than 0.991 m and 0.960 m, respectively. [ABSTRACT FROM AUTHOR]

A Geographic Information System (GIS) is a computer system for gathering, storing, transmitting, and presenting data related to positions on Earth's surface. This research aims to authenticate the GIS data during transmission via internet based on transform-based invisible watermarking. The proposed framework makes use of the singular value decomposition and discrete cosine transformation in the frequency domain. The proposed framework is evaluated on National DEM images obtained from the Geospatial Information Agency's (Badan Informasi Geospasial--BIG) geoportal, under several types of attacks. Two performance metrics (Peak to Signal Noise Ratio (PSNR) and Mean Square Error (MSE)) were considered for the evaluation of the security of the designed framework. Likewise, Normalized Correlation (NC) was computed to assess the robustness by calculating the similarity between the original and the extracted images. The experimental outcomes show that the extracted logos are readable even if they are altered, which guarantees that the received DEM data are authentic. [ABSTRACT FROM AUTHOR]

The sustainable utilization of biomass, particularly troublesome waste biomass, has become one of the pathways to meet the urgent demand for providing energy safety and environmental protection. The variety of biomass hinders the design of energy devices and systems, which must be highly efficient and reliable. Along with the technological developments in this field, broad works have been carried out on the mathematical modeling of the processes to support design and optimization for decreasing the environmental impact of energy systems. This paper aims to provide an extensive review of the various approaches proposed in the field of the mathematical modeling of the thermochemical conversion of biomass. The general focus is on pyrolysis and gasification, which are considered among the most beneficial methods for waste biomass utilization. The thermal and flow issues accompanying fuel conversion, with the basic governing equations and closing relationships, are presented with regard to the micro- (single particle) and macro-scale (multi-particle) problems, including different approaches (Eulerian, Lagrangian, and mixed). The data-driven techniques utilizing artificial neural networks and machine learning, gaining increasing interest as complementary to the traditional models, are also presented. The impact of the complexity of the physicochemical processes and the upscaling problem on the variations in the modeling approaches are discussed. The advantages and limitations of the proposed models are indicated. Potential options for further development in this area are outlined. The study shows that efforts towards obtaining reliable predictions of process characteristics while preserving reasonable computational efficiency result in a variety of modeling methods. These contribute to advancing environmentally conscious energy solutions in line with the global sustainability goals. [ABSTRACT FROM AUTHOR]

The location of the main boundary fault of the Yadong-Gulu Rift (YGR) shifts from the east side in the southern segment to the west side in the northern segment. The Nyemo Graben Group (NGG) connects the southern and northern segments of the YGR and provides clues for understanding the migration of boundary fault locations along the YGR. However, the NGG has received very little attention. In this study, we map the geometry of the Pabu normal fault, which is the boundary fault of the westernmost graben in the NGG, using high-resolution remote sensing images. We then utilized a digital elevation model (DEM) with a spatial resolution of 1 m. Morphometric parameters such as scarp height, width, and slope were obtained from elevation profiles in three typical deformation regions. Our results reveal a fault segment approximately 3 km long that links the southern and northern segments of the Pabu Fault. Each fault segment could be a major segment. Furthermore, based on regional tectonic activity, the Pabu Fault has the potential to produce an earthquake with a magnitude of around M 6.7. [ABSTRACT FROM AUTHOR]

Integrating coastal topographic and bathymetric data for creating regional seamless topobathymetric digital elevation models of the land/water interface presents a complex challenge due to the spatial and temporal gaps in data acquisitions. The Coastal National Elevation Database (CoNED) Applications Project develops topographic (land elevation) and bathymetric (water depth) regional scale digital elevation models by integrating multiple sourced disparate topographic and bathymetric data models. These integrated regional models are broadly used in coastal and climate science applications, such as sediment transport, storm impact, and sea-level rise modeling. However, CoNED's current integration method does not address the occurrence of measurable vertical discrepancies between adjacent near-shore topographic and bathymetric data sources, which often create artificial barriers and sinks along their intersections. To tackle this issue, the CoNED project has developed an additional step in its integration process that collectively assesses the input data to define how to transition between these disparate datasets. This new step defines two zones: a micro blending zone for near-shore transitions and a macro blending zone for the transition between high-resolution (3 m or less) to moderate-resolution (between 3 m and 10 m) bathymetric datasets. These zones and input data sources are reduced to a multidimensional array of zeros and ones. This array is compiled into a 16-bit integer representing a vertical assessment for each pixel. This assessed value provides the means for dynamic pixel-level blending between disparate datasets by leveraging the 16-bit binary notation. Sample site RMSE assessments demonstrate improved accuracy, with values decreasing from 0.203–0.241 using the previous method to 0.126–0.147 using the new method. This paper introduces CoNED's unique approach of using binary code to improve the integration of coastal topobathymetric data. [ABSTRACT FROM AUTHOR]

With the renewed interest in the lunar surface exploration, the European Space Agency is supporting, as part of the Moonlight program, the development of a dedicated Lunar Communications and Navigation Service (LCNS) infrastructure. This should enable to achieve real time positioning and autonomous navigation in the cislunar space, including, among others, lunar landing and surface operations. One of the services proposed, as part of the LunaNet framework (NASA, 2022), is called the Lunar Augmented Navigation Service (LANS) and it is based on a GNSS-like concept. However, compared to Earth-based GNSS, the expected number of available satellites in lunar orbit will initially be limited, which triggers the interest of coupling these technologies at the receiver level with other navigation data sources. In the case of surface rovers, use of digital elevation model (DEM) data has shown to be a potential other source of information to support positioning. The purpose of this contribution is to look at the actual navigation performances achievable when using a simple (four satellites constellation) lunar radio navigation constellation combined with a DEM, through a state estimation filter, for different rover dynamic and different DEM accuracy levels. It is shown that a 5 meter real-time horizontal position accuracy can be achieved, for 99.7% of the time, using a precise enough DEM (5 m/pixel) and a 4 satellite-constellation under different rover's dynamic conditions (i.e. velocities). [ABSTRACT FROM AUTHOR]

We explore the viability of modeling dynamic problems with a new formulation of an impulse‐based Level‐Set DEM (LS‐DEM). The new formulation is stable, fast, and energy conservative. However, it can be numerically stiff when the assembly has substantial mass differences between particles. We also demonstrate the feasibility of modeling deformable structures in a rigid body framework and propose several enhancements to improve the convergence of collision resolution, including a hybrid time integration scheme to separately handle at rest contacts and dynamic collisions. Finally, we extend the impulse‐based LS‐DEM to include arbitrarily shaped topographic surfaces and exploit its algorithmic advantages to demonstrate the feasibility of modeling realistic behavior of granular flows. The new formulation significantly improves the performance of dynamic simulations by allowing larger time steps, which is advantageous for observing the full development of physical phenomena such as rock avalanches, which we present as an illustrative example. [ABSTRACT FROM AUTHOR]

AbstractCapturing the accurate behavior of anchors has been a challenge in geotechnical engineering because of uncontrolled parameters in laboratory settings. The use of numerical modeling methods such as the finite element method, discrete element method (DEM), and coupled Eulerian-Lagrangian method can help address this issue. Among these methods, the DEM is notable for its ability to model the interaction of the anchor and soil particles. However, the limitations of DEM, including the shapes and sizes of the particles, can affect the results. Researchers have proposed different sizes and shapes for geotechnical issues, but, a gap remains about the interaction of particles tailored for dynamic anchors that has not been thoroughly explored. The current study investigated soil particles of different shapes and sizes to assess the pullout capacity of dynamic anchors that can be used in offshore engineering. The results indicate that the use of a mixture of particles with realistic shapes can increase the accuracy of the assessment of the anchor behavior. Different scenarios for particle mixing have been proposed and the numerical results showed good agreement with the experimental test results. A novel numerical method also has been introduced with which to simulate sand pluviation techniques. [ABSTRACT FROM AUTHOR]

Objectives: Vegetation widely spread in the southwestern mountainous regions of China. In the remote sensing images of this area, the landslides are usually shaded by vegetation. The error rate of forested landslide detection in remote sensing images is high, which is hard to meet practical needs. Methods: To address this issue, this paper uses light detection and ranging (LiDAR)-derived digital elevation mode (DEM) and hillshade to remove the forest on the landslides. In addition, a new dataset for forested landslide detection is also constructed. On this basis, an intelligent landslide detection model base on multi-modal deep learning is proposed. The proposed model uses DEM and hillshade to identify forested landslides, which consists of three neural network models: A transformer network for automatically extracting DEM features, a transformer network for automatically extracting hillshade features, and a convolution neural network with attention mechanism for merging multi-modal remote sensing data. Results: The proposed model is compared with ResU-Net, LandsNet, HRNet and SeaFormer. Experimental results show that the proposed model achieves the highest prediction accuracy. Intersection over union and F1 are improved by 9.3% and 6.8%, respectively. Conclusions: LiDAR is able to remove the impact of forest cover, which is suitable for identifying the forested landslides in the southwest mountain areas of China. The proposed LiDAR-based landslide detection model is able to predict the position of landslides, which is useful for deciding the position of landslide monitoring devices. [ABSTRACT FROM AUTHOR]

This study explores the effect of steel ball size and proportion on mineral grinding characteristics using Discrete Element Method (DEM) simulations. Based on batch grinding kinetics, this paper analyzes the contact behavior during grinding, discussing particle breakage conditions and critical breakage energy. The results indicate that while increasing the size of the steel balls leads to higher collision energy, the collision probability decreases significantly; the opposite is true for smaller steel balls. Simulation results with different ball size combinations show that increasing the proportion of smaller balls does not significantly change the collision energy but greatly increases the collision probability, providing a basis for optimizing ball size distribution to improve grinding performance. Furthermore, appropriately increasing the proportion of smaller balls can reduce fluctuations in grinding energy consumption, thereby enhancing collision energy and collision probability while reducing energy costs. Liner wear results demonstrate that larger ball sizes increase liner wear, but different ball size combinations can effectively distribute the forces on the liner, reducing wear. [ABSTRACT FROM AUTHOR]

The shaft resistance of rock-socketed piles (RSPs) is primarily influenced by the interactions between the pile, rock and any soft interface materials. This study presents a fundamental experimental and numerical investigation to predict the shaft resistance of model RSPs in soft rocks through a comprehensive shear strength framework incorporating the major variables such as roughness and smear fabric. By calibrating the Discrete Element Method (DEM) results with the experimental outcomes, this study evaluates the load-resistance attributes of RSPs in three different soft rocks for a wide range of roughness and smear configurations. The interface roughness effect of the RSPs in terms of the friction coefficient was correlated with the ultimate shaft resistances, uniaxial compressive strength and Young's modulus of the rock. The study then incorporated the effect of smear fabric (placement, thickness and area proportion) in the shear strength framework of clean shafts. Comprehensive review of the DEM results revealed that the socket roughness effect diminishes at a critical roughness factor (RF) of 0.4, beyond which the smear predominantly influences the shaft capacity. Following this, the effects of roughness and smear fabric were incorporated into a single equation representing the interface shear strength of RSPs, where the existence of smear results in a maximum reduction of up to 75% of the ultimate shaft resistance. The distinctive feature of this unified interface shear strength framework lies in its integration of the new smear fabric parameter and the linkage to the mechanical properties of soft rocks, which is the limitation of the earlier studies. It thereby sets a strong base for future studies aimed at advancing the pile-rock interface models. Highlights: Reports the experimental and numerical test results for various rocks in terms of different roughness and smear configurations. Formulates a friction coefficient to correlate the ultimate shaft resistances with the interface roughness and mechanical properties of soft rocks. Evaluates the effects of smear fabric on the shaft resistance of different soft rocks in terms of different area proportions and thicknesses. Proposes a unified interface shear strength framework to predict the shaft resistance of rock-socketed piles in soft rocks. [ABSTRACT FROM AUTHOR]

At least 10 global digital elevation models (DEMs) at one-arc-second resolution now cover Earth. Comparing derived grids, like slope or curvature, preserves surface spatial relationships, and can be more important than just elevation values. Such comparisons provide more nuanced DEM rankings than just elevation root mean square error (RMSE) for a small number of points. We present three new comparison categories: fraction of unexplained variance (FUV) for grids with continuous floating point values; accuracy metrics for integer code raster classifications; and comparison of stream channel vector networks. We compare six global DEMs that are digital surface models (DSMs), and four edited versions that use machine learning/artificial intelligence techniques to create a bare-earth digital terrain model (DTM) for different elevation ranges: full Earth elevations, under 120 m, under 80 m, and under 10 m. We find edited DTMs improve on elevation values, but because they do not incorporate other metrics in their training they do not improve overall on the source Copernicus DSM. We also rank 17 common geomorphic-derived grids for sensitivity to DEM quality, and document how landscape characteristics, especially slope, affect the results. None of the DEMs perform well in areas with low average slope compared to reference DTMs aggregated from 1 m airborne lidar data. This indicates that accurate work in low-relief areas grappling with global climate change should use airborne lidar or very high resolution image-derived DTMs. [ABSTRACT FROM AUTHOR]

A comprehensive modelling methodology is proposed to describe wheat seeds using the discrete element method. By analysing the geometrical characteristics of wheat seeds, the multi-sphere approach is employed to establish 7-, 11-, 15-, 19-, and 23-sphere models based on ellipsoids. The physical and mechanical characteristics of wheat grain are measured and calibrated. Then, the proposed model is verified with several assessment criteria by contrasting the results of the experiment and simulation, including the wheat seed volume fraction, static angle of repose, hopper discharge, rotating drum and "self-flow screening". By balancing the accuracy of the multi-sphere model and computational efficiency, the 7-sphere or 11-sphere model is found to be the optimal model for determining the static stacking behaviour and hopper discharge of wheat seeds. For the rotating drum and the "self-flow screening", there is a considerable discrepancy between the simulation and experimental findings due to the surface roughness of the 7- and 11-sphere models. However, 15-, 19-, and 23-sphere models show a high accuracy, which can be applied for drying seeds of the rotating drum and accurately reproducing the sieve permeability of the "self-flow screening" experiment. In summary, the proposed multi-sphere method can be extended to related industry fields by demonstrating satisfactory accuracy in several validation tests. • A general multi-sphere modelling approach for wheat seed based on DEM is proposed. • DEM parameters of wheat grain are measured and calibrated. • Wheat grain experiments are conducted to verify the accuracy of the model. • Provides an effective guide for the validation of irregular particle models. [ABSTRACT FROM AUTHOR]

In precision seeding operations, the irregular shapes of maize seed particles and the suboptimal geometric structure of the seed tube contribute to the rolling and bouncing of seeds upon falling into the furrow, ultimately compromising seeding uniformity. To address this issue, a convergent groove-guided (CGG) seed tube was proposed based on the principle of brachistochrone curve considering friction (BCCF). The discrete element method (DEM) was employed to conduct a comprehensive phenomenological analysis and numerical investigation of particle guide characteristics. Bench tests and field experiments were designed to verify the simulation results. Through response surface analysis, the optimal seeding performance was achieved at a groove angle of 111.34°, tube incline angle of 1.56°, and ground speed of 7.2 km h−1, resulting in a lateral dispersion landing range of 11.10 mm, angular velocity of 17.38 rad s−1, seed landing speed variation coefficient of 2.29%, and plant spacing variation coefficient of 6.04%. Bench test results unveiled that, under a ground speed of 7.2 km h−1, the variation coefficient of plant spacing for CGG seed tubes was measured at 7.63%, with a deviation of 1.59% from the simulation results. At high ground speeds of 9.0–14.4 km h−1, the seed guiding performance was also better than traditional seed tubes. Consistent results were also verified through field experiments. Therefore, the CGG seed tube manifested superior seed guidance efficacy when juxtaposed with its conventional counterpart, and this design can provide technical support for the realization of seed-to-ground positioning technology. [Display omitted] • A novel convergent groove-guided seed tube was proposed based on BCCF. • The seed guiding performance of different maize seed shapes was investigated. • The key parameters of seed tube were optimised by response surface fitting. • Alteration in seed posture within the seed tube was examined by high-speed camera. • Bench and field experiments verified improvement performance. [ABSTRACT FROM AUTHOR]

Geometric morphological features significantly influence the shear mechanical properties of rock fractures, which are quantitatively assessed using roughness indicators. However, it remains uncertain whether fractures with identical roughness indicators exhibit similar shear mechanical behavior. This study employed three-dimensional scanning and the roughness index θ*max/(C + 1) to investigate the roughness of fracture profiles oriented differently on the fracture surface. The findings confirm that natural fracture profiles can have similar roughness levels but distinct morphologies. Consequently, a methodology was proposed to construct fractures with identical roughness but differing morphologies, based on 10 fracture profiles exhibiting varying roughness gradients. Numerical models of rough fracture samples were established, and direct shear tests were conducted using the discrete element method (DEM). The results reveal significant variability in shear strength, shear deformation, and macro-microscopic failure characteristics among fracture samples with identical roughness levels. As the θ*max/(C + 1) of fractures increases, more morphological asperities contribute to resisting external shear forces, although both the mean values and variability of shear mechanical indicators across fracture samples demonstrate an increasing trend. The distribution of fracture morphological features notably influences the characteristics of contact force distribution, as well as the scale and orientation of microcrack development within fracture samples. The contribution of different segments of fractures to resisting external shear forces correlates closely with their specific morphological feature distribution, particularly the location where θ*max/(C + 1)​ occurs. [ABSTRACT FROM AUTHOR]

Deciphering geological phenomena, including planetary evolution, is accomplished by studying Earth’s impact craters. An attempt has been made to identify the buried lineament anomalies using multisensor satellite data in the Aorounga impact structure in Chad, Africa. In order to improve the visibility of buried lineaments, interferometric synthetic aperture radar (InSAR) coherence, backscatter coefficient, land surface temperature (LST), and digital elevation model (DEM) were processed. The analysis of InSAR coherence data reveals that coherence values are low to moderate in disparate regions encompassed by dune systems with rocks and higher in monotonous areas like dynamic dunes and fractured rock exposures. The results show that backscattering coefficient values of VV and VH polarization decreased in buried lineament regions covered by dunes, whereas high backscattering is experienced in regions encompassed by rocks. It was observed that nighttime has the highest LST in the linear features, whereas daytime LST is found to be low in buried lineaments regions. Thus, in this study, the backscatter coefficient of VH and VV polarization and DEM give promising interpretations to other methods for identifying buried lineament features. The study has demonstrated the potential of multisensor satellite data for identifying buried lineament anomalies that could be potential sources of groundwater, minerals, and hydrothermal activity. These anomalies may also be indicators of tectonic and structural activities. [ABSTRACT FROM AUTHOR]

Solid lubrication is a green manufacturing technology with high efficiency, which saves energy and material and thus it is suitable for extreme conditions in mechanical engineering fields such as aerospace and high temperature mold. In this study, a graphite layer of specified thickness was prepared on the end face of the upper specimen by the directional spray method. The effect of velocity and load on the friction characteristics of the graphite layer were investigated using a friction tester capable of real time observation of the friction interface. Subsequently, a 3D surface profilometer, SEM, and EDS were used to characterize the morphology and elemental composition of the worn surfaces. The results show that the lubrication performance of the graphite layer is most effective with a flatter worn surface (Sa and SZ are smaller) and higher carbon content when the velocity is 12.5 mm/s and the load is 4N. Meanwhile, force chains are short, numerous and lasting for a long time, while being uniformly distributed in all directions and velocity fluctuates greatly, with slowly decreased coordination numbers. This study aims to provide a reasonable explanation for the mechanisms by which velocity and load influence the lubrication effect of the powder layer. [ABSTRACT FROM AUTHOR]

In underground excavations at great depths, rocks are likely to experience complex in-situ stresses such as coupled static and dynamic loads. The current work numerically investigates the dual effects of pre-tension and structural defect (i.e., prefabricated hole) on the dynamic tensile behavior of hollow rock using the flattened Brazilian disc (FBD) method. The split Hopkinson pressure bar (SHPB) system for dynamic loading is established based on the discrete element method (DEM). The results show that the total tensile strength of the specimen decreases with the increase of the hole radius and is independent of the pre-tension ratio. The dynamic tensile strength decreases with increasing pre-tension ratio in rocks with different hole radii. The fragmentation analysis shows that the rock is more discretized with a smaller hole size and fails more evenly with a greater mean fragment size as hole radius increases. In addition, the acoustic emission (AE) moment magnitude is further discussed to interpret the rock cracking process microscopically, incorporating the wave transmission trajectory within the specimen. The primary cracks initiated in the vicinity of the hole along the loading direction have a higher moment magnitude than those of the secondary cracks that start at the upper and lower boundaries of the rock. [ABSTRACT FROM AUTHOR]

This study employs the discrete element method to simulate triaxial compression tests and investigate the effects of bedding plane inclination and confining pressure on the mechanical properties, crack evolution, and anisotropy of laminated slate. Additionally, the study analyzed simulation results by using the Hoek–Brown, Ramamurthy, and Saeidi strength criteria, and extend the applicability of the Hoek–Brown criterion in the absence of corresponding bedding angle test data. The research results indicate that both compressive strength and elastic modulus exhibit a "U" shaped variation, initially decreasing and then increasing with the increase in sample inclination. As the bedding plane inclination increases, the failure mode of the laminated slate gradually transitions from shear failure to a combination of tensile and shear failure. With the increase in confining pressure, the percentage of cracks for PBM and SJM follows a trend that shifts from a "U" shaped and inverted "U" shaped pattern to a stable linear trend with the change in inclination. This indicates that an increase in confining pressure can reduce the impact of bedding plane inclination on compressive strength. The anisotropy ratio of compressive strength decreases with the increase in confining pressure, while the anisotropy ratio of elastic modulus increases with the increase in confining pressure. In evaluating the fitting accuracy and generalization ability of the model, the Hoek–Brown criterion appears superior. The modified Hoek–Brown strength criterion can accurately predict the standard results forecasted by the Hoek–Brown criterion in the absence of corresponding bedding angle experimental data. [ABSTRACT FROM AUTHOR]

In this study, the gas−particle flow field in a real-size industrial-scale micron air classifier manufactured by Phenikaa Group using 3D transient simulations with the FWC-RSM–DPM (Four-Way Coupling-Reynold Stress Model-Discrete Phase Model) in ANSYS Fluent 2022 R2 and with the assistance of High-Performance Computing (HPC) systems is explored. A comparison among three coupling models is carried out, highlighting the significant influence of the interactions between solid and gas phases on the flow field. The complex two-phase flow, characterized by the formation of multiple vortices with different sizes, positions, and rotation directions, is successfully captured on the real-size model of the classifier. Additionally, analyzing the effects of the vortices on the flow field provides a comprehensive understanding of the gas–solid flow field and the classification mechanism. The effect of the outlet mass airflow rate is also investigated. The classifier's Key Performance Indicators (KPIs: d50, K, η, ΔP) and the constrained condition of the particle size distribution curve of the final product are used to evaluate the classification efficiency. The contributions of this work are as follows: (i) a simulation analysis of a real-size industrial-scale classifier is conducted that highlights its advantages over a lab-scale one; (ii) a comparison is conducted among three coupling models, showing the advancement of four-way coupling in providing accurate results for simulations of interactions between the gas phase and particles; and (iii) the particle size distribution curve performances of a classified product under different simulation models and outlet airflow rates are addressed, from which optimal parameters can be selected in the design and operation processes to achieve the required efficiency of an air classifier. [ABSTRACT FROM AUTHOR]