Search Results (114)

Slope stability assessment is a critical component of engineering safety. Conventional analytical methods frequently struggle to integrate heterogeneous slope data and model intricate failure mechanisms, thereby constraining their efficacy in practical engineering scenarios. To tackle these issues, this study presents a novel slope stability classification model grounded in the Optuna-TPE-CatBoost framework. By leveraging the Tree-structured Parzen Estimator (TPE) within the Optuna framework, the model adaptively optimizes CatBoost hyperparameters, thus enhancing prediction accuracy and robustness. It incorporates six key features—slope height, slope angle, unit weight, cohesion, internal friction angle, and the pore pressure ratio—to establish a comprehensive and intelligent assessment system. Utilizing a dataset of 272 slope cases, the model was trained with k-fold cross-validation and dynamic class imbalance strategies to ensure its generalizability. The optimized model achieved impressive performance metrics: an area under the receiver operating characteristic curve (AUC) of 0.926, an accuracy of 0.901, a recall of 0.874, and an F1-score of 0.881, outperforming benchmark algorithms such as XGBoost, LightGBM, and the unoptimized CatBoost. Validation via engineering case studies confirms that the model accurately evaluates slope stability across diverse scenarios and effectively captures the complex interactions between key parameters. This model offers a reliable and interpretable solution for slope stability assessment under complex failure mechanisms. Full article

Background and Objectives: General-purpose multimodal large language models (LLMs) are increasingly used for medical image interpretation despite lacking clinical validation. This study evaluates the diagnostic reliability of ChatGPT-4o and Claude 2 in photographic assessment of adolescent idiopathic scoliosis (AIS) against radiological standards. This study examines two critical questions: whether families can derive reliable preliminary assessments from LLMs through analysis of clinical photographs and whether LLMs exhibit cognitive fidelity in their visuospatial reasoning capabilities for AIS assessment. Materials and Methods: A prospective diagnostic accuracy study (STARD-compliant) analyzed 97 adolescents (74 with AIS and 23 with postural asymmetry). Standardized clinical photographs (nine views/patient) were assessed by two LLMs and two orthopedic residents against reference radiological measurements. Primary outcomes included diagnostic accuracy (sensitivity/specificity), Cobb angle concordance (Lin’s CCC), inter-rater reliability (Cohen’s κ), and measurement agreement (Bland–Altman LoA). Results: The LLMs exhibited hazardous diagnostic inaccuracy: ChatGPT misclassified all non-AIS cases (specificity 0% [95% CI: 0.0–14.8]), while Claude 2 generated 78.3% false positives. Systematic measurement errors exceeded clinical tolerance: ChatGPT overestimated thoracic curves by +10.74° (LoA: −21.45° to +42.92°), exceeding tolerance by >800%. Both LLMs showed inverse biomechanical concordance in thoracolumbar curves (CCC ≤ −0.106). Inter-rater reliability fell below random chance (ChatGPT κ = −0.039). Universal proportional bias (slopes ≈ −1.0) caused severe curve underestimation (e.g., 10–15° error for 50° deformities). Human evaluators demonstrated superior bias control (0.3–2.8° vs. 2.6–10.7°) but suboptimal specificity (21.7–26.1%) and hazardous lumbar concordance (CCC: −0.123). Conclusions: General-purpose LLMs demonstrate clinically unacceptable inaccuracy in photographic AIS assessment, contraindicating clinical deployment. Catastrophic false positives, systematic measurement errors exceeding tolerance by 480–1074%, and inverse diagnostic concordance necessitate urgent regulatory safeguards under frameworks like the EU AI Act. Neither LLMs nor photographic human assessment achieve reliability thresholds for standalone screening, mandating domain-specific algorithm development and integration of 3D modalities. Full article

Blasting is one of the most widely used and cost-effective techniques for rock excavation and fragmentation in open-pit mining, particularly for large-scale operations. However, repeated or poorly controlled blasting can generate excessive ground vibrations that threaten slope stability by causing structural damage, fracturing of the rock mass, and potential failure. Evaluating the effects of blast-induced vibrations is essential to ensure safe and sustainable mining operations. This study investigates the impact of blasting-induced vibrations on slope stability at the Saindak Copper-Gold Open-Pit Mine in Pakistan. A comprehensive dataset was compiled, including field-monitored ground vibration measurements—specifically peak particle velocity (PPV) and key blast design parameters such as spacing (S), burden (B), stemming length (SL), maximum charge per delay (MCPD), and distance from the blast point (D). Geomechanical properties of slope-forming rock units were validated through laboratory testing. Slope stability was analyzed using pseudo-static limit equilibrium methods (LEMs) based on the Mohr–Coulomb failure criterion, employing four approaches: Fellenius, Janbu, Bishop, and Spencer. Pearson and Spearman correlation analyses quantified the influence of blasting parameters on slope behavior, and sensitivity analysis determined the cumulative distribution of slope failure and dynamic response under increasing seismic loads. FoS values were calculated for both east and west pit slopes under static and dynamic conditions. Among all methods, Spencer consistently yielded the highest FoS values. Under static conditions, FoS was 1.502 for the east slope and 1.254 for the west. Under dynamic loading, FoS declined to 1.308 and 1.102, reductions of 12.9% and 11.3%, respectively, as calculated using the Spencer method. The east slope exhibited greater stability due to its gentler angle. Correlation analysis revealed that burden had a significant negative impact (r = −0.81) on stability. Sensitivity analysis showed that stability deteriorates notably when PPV exceeds 10.9 mm/s. Although daily blasting did not critically compromise stability, the west slope showed greater vulnerability, underscoring the need for stricter control of blasting energy to mitigate vibration-induced instability and promote long-term operational sustainability. Full article

Slope stability analysis is conventionally performed using the strength reduction method with the proportional reduction in shear strength parameters. However, during actual slope failure processes, the attenuation characteristics of rock mass cohesion ($c$) and internal friction angle ($\phi$) are often inconsistent, and their reduction paths exhibit clear nonlinearity. Relying solely on proportional reduction paths to calculate safety factors may therefore lack scientific rigor and fail to reflect true slope behavior. To address this limitation, this study proposes a novel approach that considers the non-proportional reduction of $c$ and $\phi$, without dependence on predefined reduction paths. The method begins with an analysis of slope stability states based on energy dissipation theory. A Bayesian Gaussian Mixture Model (BGMM) is employed for intelligent interpretation of the dissipated energy data, and, combined with energy mutation theory, is used to identify instability states under various reduction parameter combinations. To compute the safety factor, the concept of a “reference slope” is introduced. This reference slope represents the state at which the slope reaches limit equilibrium under strength reduction. The safety factor is then defined as the ratio of the shear strength of the target analyzed slope to that of the reference slope, providing a physically meaningful and interpretable safety index. Compared with traditional proportional reduction methods, the proposed approach offers more accurate estimation of safety factors, demonstrates superior sensitivity in identifying critical slopes, and significantly improves the reliability and precision of slope stability assessments. These advantages contribute to enhanced safety management and risk control in slope engineering practice. Full article

The shear strength of rock discontinuities is a critical parameter in rock engineering projects for assessing the safety conditions of rock slopes or concrete dam foundations. It is primarily controlled by the frictional contribution of rock texture (basic friction angle), the roughness of discontinuities, and the applied normal stress. While proper testing is essential for accurately quantifying shear strength, engineering geologists and engineers often rely on published historical databases during early design stages or when test results show significant variability. This paper serves two main objectives. First, it intends to provide a comprehensive overview of the basic friction angle concept from early years until its emergence in the Barton criterion, along with insights into distinctions and misunderstandings between basic and residual friction angles. The other, given the influence of the basic friction angle for the entire rock joint shear strength, the manuscript offers an extended database of basic friction angle values. Full article

The automatic feeding device is crucial in grassland livestock farming, enhancing feeding efficiency, ensuring regular and accurate feed delivery, minimizing waste, and reducing costs. The shape and size of pellet feed render it particularly suitable for the delivery mechanism of automated feeding troughs. The uniformity of pellet flow is a critical factor in the study of automatic feeding troughs, and optimizing the movement characteristics of the pellets contributes to enhanced operational efficiency of the equipment. However, existing research often lacks a systematic analysis of the pellet size characteristics (such as diameter and length) and flow behavior differences in pellet feed, which limits the practical application of feed troughs. This study optimized the angle of repose and structural parameters of the feeding trough using Matlab simulations and discrete element modeling. It explored how the stock bin slope and baffle opening height influence pellet feed flow characteristics. A programmable logic controller (PLC) and human–machine interface (HMI) were used for precise timing and quantitative feeding, validating the design’s practicality. The results indicated that the Matlab method could calibrate the Johnson–Kendall–Roberts (JKR) model’s surface energy. The optimal slope was found to be 63°, with optimal baffle heights of 28 mm for fine and medium pellets and 30 mm for coarse pellets. The experimental metrics showed relative errors of 3.5%, 2.8%, and 4.2% (for average feed rate) and 8.2%, 7.3%, and 1.2% (for flow time). The automatic feeding trough showed a feeding error of 0.3% with PLC-HMI. This study’s optimization of the automatic feeding trough offers a strong foundation and guidance for efficient, accurate pellet feed distribution. Full article

Off-road path planning involves navigating vehicles through areas lacking established road networks, which is critical for emergency response in disaster events, but is limited by the complex geographical environments in natural conditions. How to model the vehicle’s off-road mobility effectively and represent environments is critical for efficient path planning in off-road environments. This paper proposed an improved A* path planning algorithm based on a Delaunay triangular NavMesh model with off-road environment representation. Firstly, a land cover off-road mobility model is constructed to determine the navigable regions by quantifying the mobility of different geographical factors. This model maps passable areas by considering factors such as slope, elevation, and vegetation density and utilizes morphological operations to minimize mapping noise. Secondly, a Delaunay triangular NavMesh model is established to represent off-road environments. This mesh leverages Delaunay triangulation’s empty circle and maximum-minimum angle properties, which accurately represent irregular obstacles without compromising computational efficiency. Finally, an improved A* path planning algorithm is developed to find the optimal off-road mobility path from a start point to an end point, and identify a path triangle chain with which to calculate the shortest path. The improved road-off path planning A* algorithm proposed in this paper, based on the Delaunay triangulation navigation mesh, uses the Euclidean distance between the midpoint of the input edge and the midpoint of the output edge as the cost function $g\left(n\right)$, and the Euclidean distance between the centroids of the current triangle and the goal as the heuristic function $h\left(n\right)$. Considering that the improved road-off path planning A* algorithm could identify a chain of path triangles for calculating the shortest path, the funnel algorithm was then introduced to transform the path planning problem into a dynamic geometric problem, iteratively approximating the optimal path by maintaining an evolving funnel region, obtaining a shortest path closer to the Euclidean shortest path. Research results indicate that the proposed algorithms yield optimal path-planning results in terms of both time and distance. The navigation mesh-based path planning algorithm saves 5~20% of path length than hexagonal and 8-directional grid algorithms used widely in previous research by using only 1~60% of the original data loading. In general, the path planning algorithm is based on a national-level navigation mesh model, validated at the national scale through four cases representing typical natural and social landscapes in China. Although the algorithms are currently constrained by the limited data accessibility reflecting real-time transportation status, these findings highlight the generalizability and efficiency of the proposed off-road path-planning algorithm, which is useful for path-planning solutions for emergency operations, wilderness adventures, and mineral exploration. Full article

In cold regions, the rock mass of open-pit mine slopes is continuously exposed to freeze–thaw (FT) environments, during which the fracture structures and their infilling materials undergo significant degradation, severely affecting slope stability and the assessment of service life. Conventional laboratory FT tests are typically based on uniform temperature settings, which fail to reflect the actual thermal variations at different burial depths, thereby limiting the accuracy of mechanical parameter acquisition. Taking the Wushan open-pit mine as the engineering background, this study establishes a temperature–depth relationship, defines multiple thermal intervals, and conducts direct shear tests on structural plane filling materials under various FT conditions to characterize the evolution of cohesion and internal friction angle. Results from rock mass testing and numerical simulation demonstrate that shear strength parameters exhibit an exponential decline with increasing FT cycles and decreasing burial depth, with the filling material playing a dominant role in the initial stage of degradation. Furthermore, a two-dimensional fracture network model of the rock mass was constructed, and the representative elementary volume (REV) was determined through the evolution of equivalent plastic strain. Based on this, spatial assignment of slope strength was performed, followed by stability analysis. Based on regression fitting using 0–25 FT cycles, regression model predictions indicate that when the number of FT cycles exceeds 42, the slope safety factor drops below 1.0, entering a critical instability state. This research successfully establishes a spatial field of mechanical parameters and evaluates slope stability, providing a theoretical foundation and parameter support for the long-term service evaluation and stability assessment of cold-region open-pit mine slopes. Full article

Currently, most studies on slope stability either neglect or consider only one of the two critical factors—rainfall conditions and crack state—that influence the stability of recent landslides. To address this limitation, eleven parameters, including slope height, internal friction angle, cohesion, rainfall conditions, and crack state, were selected as evaluation indexes. GeoStudio software 2018 R2 was also used to simulate the slope safety factor under various parameters, and 363 datasets were obtained. The eXtreme Gradient Boosting–Particle Swarm Optimization–Support Vector Regression (XGBoost–PSO–SVR) model was employed to train the simulation results and construct a predictive model. The MSE of XGBoost–PSO–SVR when compared with the MSE of the single-machine methods of XGBoost and PSO–SVR is reduced by 71.9% and 57.8%, respectively. Furthermore, when compared with four single-machine models—Decision Tree (DT), Naive Bayes (NB), Random Forest (RF), and K-Nearest Neighbors (KNN)—the XGBoost–PSO–SVR model had the smallest MSE of 0.0016 and the largest R² of 0.9919. Thus, the XGBoost–PSO–SVR model demonstrated superior training performance. The predicted safety factor for a recent landslide in Yongchun County, Fujian Province, China, during 4–7 November 2016 was 0.9658, which closely aligned with the actual conditions. This study could provide a new method for the stability prediction of recent landslides based on various factors, such as rainfall conditions and crack state. Full article

Landslide prevention is crucial, particularly for protecting roads and infrastructure in rock landslide-prone areas. This global issue has garnered significant attention from researchers worldwide. This study addresses landslide prevention by modeling the factor of safety (FoS) for slope stability through the Geological Strength Index (GSI), limit equilibrium method (LEM), and finite element method (FEM). A GSI analysis was conducted using RocLab software version 1.0, and slope modeling was performed using RocScience SLIDE version 6.0 and RS2 version 11. The results revealed various cohesion and friction angles across six slopes, with Slope 5 exhibiting the highest FoS values (up to 3.27 with the FEM) and Slope 1 exhibiting the lowest (1.59 with the FEM). All slopes, designed with a uniform geometry, remained stable, exhibiting FoS values greater than 1.1. This study further provides an optimal slope design for the open pit in the andesite mining plan at Anugerah Berkah Sejahtera. These findings highlight the important role of accurate modeling in the assessment of slope stability. With a suggested safe slope height of 10 m and an angle of 80° (FoS = 1.62), slope stability analysis based on the factor of safety (FoS) showed that single slopes made of andesite maintain stability at steep angles. Claystone slopes, however, have a maximum slope height of 30 m at 20° (FoS = 1.27) and 27 m at 50° (FoS = 1.34), requiring more conservative geometries to maintain their stability. For an overall slope that comprises both rock types, a height of 30 m with a slope angle of 60° is recommended (FoS = 1.23) to ensure stability. The critical design condition for a claystone slope occurs at a height of 30 m with a slope angle of 50°, yielding a factor of safety (FoS) of 0.92, which indicates instability (FoS < 1.1). Similarly, a 35 m-high slope with a slope angle of 20° produced an FoS of 1.04, and a 35 m-high slope with a slope angle of 50° produced an FoS of 0.89, further confirming instability. For the overall slope configuration, instability occurs at a height of 30 m with a slope angle of 65° that produces an FoS of 1.09. Full article

Urban population growth has led to increased air pollution, influenced by disrupted wind patterns and the heterogeneous distribution of pollutants. Although the relationship between urban form and air quality is well recognized, it is often examined in isolation and through simplified urban geometries. This study addresses these limitations by numerically analyzing pollutant dispersion in densely populated hillside areas using idealized but topographically representative building geometries. A three-dimensional microclimatic simulation is conducted with ENVI-met software, incorporating parametric slope angles and building height variations. The results demonstrate that both slope steepness and building height significantly affect local pollutant concentrations: steeper slopes and taller buildings are associated with higher peak pollution values in the environment. Additionally, the simulation results show that vegetation is critical in mitigating pollution, acting as a natural barrier that enhances dispersion. These findings highlight the need for slope-sensitive urban planning and strategically integrating vegetation in hillside developments to improve air quality in complex urban terrains. Full article

In recent years, significant exploration successes and research progress in volcanic hydrocarbon reservoirs across China’s offshore basins have highlighted their importance as key targets for deep hydrocarbon exploration. In the Shimentan Formation of the Xihu Sag, East China Sea Shelf Basin (ECSSB), low-yield gas flows have been encountered through exploratory drilling; however, no major reservoir breakthroughs have yet been achieved. Assessing the large-scale reservoir potential of volcanic sequences in the Shimentan Formation is thus critical for guiding future exploration strategies. Based on previous exploration studies of volcanic reservoirs in other Chinese basins, this study systematically evaluates the hydrocarbon potential of these volcanic units by microscopic thin section identification, major element analysis, integrates drilling data with seismic interpretation techniques—such as coherence cube slicing for identifying volcanic conduits, dip angle analysis for classifying volcanic edifices, and waveform classification for delineating volcanic lithofacies. The main findings are as follows: (1) The Shimentan Formation is primarily composed of intermediate to acidic pyroclastic rocks and lava flows. Volcanic facies are divided into three facies, four subfacies, and six microfacies. Volcanic edifices are categorized into four types: stratified, pseudostratified, pseudostratified-massive, and massive. (2) Extensive pseudostratified volcanic edifices are developed in the Hangzhou Slope Zone, where simple and compound lava flows of effusive facies are widely distributed. (3) Comparative analysis with prolific volcanic reservoirs in the Songliao and Bohai Bay basins indicates that productive reservoirs are typically associated with simple or compound lava flows within pseudostratified edifices. Furthermore, widespread Late Cretaceous rhyolites in adjacent areas of the study region suggest promising potential for rhyolitic reservoir development in the Hangzhou Slope Zone. These results provide a robust geological foundation for Mesozoic volcanic reservoir exploration in the Xihu Sag and offer a methodological framework for evaluating reservoir potential in underexplored volcanic regions. Full article

Rock slopes containing weak interlayers are highly prone to instability under the disturbance of blasting vibrations due to the influence of structural planes. To address the limitations of traditional models in predicting vibration attenuation for such slopes, this study conducted in situ blasting tests on sand–mudstone interbedded slopes from the Pinglu Canal project. Based on dimensional analysis, the Sadowsky formula was modified to incorporate both elevation difference (H/R) and soft interlayer dip angle (θ), resulting in an enhanced predictive model. Field data revealed that the proposed model significantly improved prediction accuracy, with determination coefficients (r²) increasing from 0.847 to 0.9946 in the vertical (Z) direction. Compared to traditional models, the root mean square error (RMSE) decreased by 96%, demonstrating superior capability in capturing vibration attenuation influenced by geological heterogeneity. Key findings reveal that steeper interlayer dip angles significantly accelerate PPV attenuation, particularly in the X direction. These findings provide a critical tool for optimizing blasting parameters in layered rock slopes, effectively mitigating collapse risks and enhancing construction safety. The model’s practicality was validated through its application in the Pinglu Canal project, offering a paradigm for similar engineering challenges in complex geological settings. Full article

The Yellow River Basin features a unique geographical environment with challenges like seawater erosion and soft soil. In this context, the construction of foundation pits can significantly impact the settlement of adjacent structures. Grounded in a real-world project, this study employs the finite element software Midas GTS to construct a 3D interaction model between foundation pit excavation and nearby buildings. Through this model, we analyze the settlement patterns of adjacent buildings influenced by variables such as foundation soil strength, slope gradient, and construction sequence. By integrating orthogonal experimental design and range analysis, we identify the sensitive factors affecting the settlement deformation and stability of foundation pits. Our analysis reveals that among the factors significantly influencing settlement deformation at the foundation pit base, groundwater levels and internal friction angles are the most critical. Slope gradient and soil cohesion also play substantial roles, whereas the compressive modulus of soil shows relatively less impact. However, a comparison with actual engineering data indicates that groundwater factors considerably affect slope deformation, underscoring the necessity for stringent control of groundwater level fluctuations. Full article

This study quantifies morphological features of global braided river deltas using Google Earth imagery, analyzing eight systems (e.g., Yukon–Kuskokwim, Poyang Lake, Lena River deltas). Methods include listwise deletion for missing data (retaining 87% of Poyang Lake delta samples) and sensitivity analysis (threshold changes ≤2.4%). Nonparametric tests (Kruskal–Wallis, H = 12.73, p = 0.005) show significant differences in bifurcation angles across deltas, with the wave-dominated Po River (59.2°) having an 18% higher 80% threshold the than tide-dominated Poyang Lake (50.1°, p = 0.003). Key quantitative results include the following: 1.65% of bifurcation angles cluster at 30–60°, differing from fan deltas (p < 0.01); wavelength–amplitude relationships are nonlinear (R² = 0.537–0.913), with positive slopes indicating a high sediment supply (e.g., Yukon–Kuskokwim) and negative slope channel avulsion (e.g., Poyang Lake); bifurcation spacing correlates with the sediment supply—54% of Poyang Lake spacings < 2000 m (dense networks) vs. 80% of Lena River spacings < 15,000 m (stable channels). The resulting dataset enables global, remote-sensing-based comparisons, providing thresholds for sedimentary modeling and reservoir prediction. Moderate missing data (≤13%) minimally affect results, though high-missingness cases need further analysis. This study replaces empirical rules with statistical validation, showing that morphometric differences reflect depositional dynamics, which are critical for reservoir heterogeneity assessments. Full article