Search Results (2,276)

The stability of internal dumps in open-pit coal mines is critical for the safe production and economic performance of the entire mine. To further enhance slope stability and ensure safe production, a new method for constructing trenches (referred to as an anti-sliding trench) on the sloped basal bed of the dump slope in open-pit mines was proposed to improve slope stability. The internal dump slope at the Luzigou anticline of the Anjialing Open-Pit Mine was studied. The slope failure modes of the dumping steps were studied experimentally and by numerical simulations at different widths of anti-slide trenches at the slope’s toe in a staged loading state. Without anti-slide trenches, shear-layer and along-layer failure modes occurred, while the failure modes with anti-slide trenches included shear-layer, along-layer, and squeeze-out failure. Based on the limit equilibrium theory and the determined failure modes, the preset anti-slide trenches at the toe of the dumping steps were theoretically analyzed. The relationships between the slope stability coefficient and the width and depth of anti-slide trenches, as well as the physical and mechanical parameters of the slope body, were derived. Given the physical and mechanical parameters of the slope body and targeted improvement in the slope stability coefficient, the size parameters of anti-slide trenches were designed and optimized through the derived relationships. At the Anjialing Coal Mine, presetting anti-slide trenches with a depth of 1.5 m and a width of 22.68 m at the toe of the dumping steps increased the slope stability coefficient from 1.3095 to 1.6. The proposed method provides a guiding reference for designing similar internal dump slopes in open-pit coal mines and for disaster prevention. Full article

The integration of artificial intelligence (AI) and machine learning (ML) has revolutionised civil engineering, enhancing predictive accuracy, decision-making, and sustainability across domains such as structural health monitoring, geotechnical analysis, transportation systems, water management, and sustainable construction. This paper presents a detailed review of peer-reviewed publications from the past decade, employing bibliometric mapping and critical evaluation to analyse methodological advances, practical applications, and limitations. A novel taxonomy is introduced, classifying AI/ML approaches by civil engineering domain, learning paradigm, and adoption maturity to guide future development. Key applications include pavement condition assessment, slope stability prediction, traffic flow forecasting, smart water management, and flood forecasting, leveraging techniques such as Convolutional Neural Networks (CNNs), Long Short-Term Memory (LSTM), Support Vector Machines (SVMs), and hybrid physics-informed neural networks (PINNs). The review highlights challenges, including limited high-quality datasets, absence of AI provisions in design codes, integration barriers with IoT-based infrastructure, and computational complexity. While explainable AI tools like SHAP and LIME improve interpretability, their practical feasibility in safety-critical contexts remains constrained. Ethical considerations, including bias in training datasets and regulatory compliance, are also addressed. Promising directions include federated learning for data privacy, transfer learning for data-scarce regions, digital twins, and adherence to FAIR data principles. This study underscores AI as a complementary tool, not a replacement, for traditional methods, fostering a data-driven, resilient, and sustainable built environment through interdisciplinary collaboration and transparent, explainable systems. Full article

This study investigates the development of axial force in micro anti-slide piles under soil movement during slope stabilization. Axial force arises from two primary mechanisms: axial soil displacement ($z_{\mathrm{s}}$) and pile kinematics. The former plays a dominant role, producing either tensile or compressive axial force depending on the direction of $z_{\mathrm{s}}$, while the kinematically induced component remains consistently tensile. A sliding angle of $\alpha =5°$ represents an approximate transition point where these two effects balance each other. Furthermore, the two mechanisms exhibit distinct mobilization behaviors: $z_{\mathrm{s}}$-induced axial force mobilizes earlier than both bending moment and shear force, whereas kinematically induced axial force mobilizes significantly later. The study reveals two distinct pile–soil interaction mechanisms depending on proximity to the slip surface: away from the slip surface, axial soil resistance is governed by rigid cross-section translation, whereas near the slip surface, rotation-dominated displacement accompanied by soil–pile separation introduces significant complexity in predicting both the magnitude and direction of axial friction. A hyperbolic formulation was adopted to model both the lateral soil resistance relative to lateral pile–soil displacement (p-y behavior) and the axial frictional resistance relative to axial pile–soil displacement (t-z behavior). Soil resistance equations were derived to explicitly incorporate the effects of cross-sectional rotation and pile–soil separation. A novel beam-spring finite element method (BSFEM) that incorporates both geometric and material nonlinearities of the pile behavior was developed, using a soil displacement-driven solution algorithm. Validation against both numerical simulations and field monitoring data from an engineering application demonstrates the model’s effectiveness in capturing the distribution and evolution of axial deformation and axial force in micropiles under varying soil movement conditions. Full article

Landslides are a persistent and destructive hazard in Angra dos Reis, located in the highlands of Rio de Janeiro State, southeastern Brazil, where steep slopes, intense orographic rainfall, and unregulated urban expansion converge to trigger recurrent mass movements. In this study, we applied Multiscale Geographically Weighted Regression (MGWR) to examine the spatially varying relationships between landslide occurrence and topographic, hydrological, geological, and anthropogenic factors. A detailed inventory of 319 landslides was compiled using high-resolution PlanetScope imagery after the December 2023 rainfall event. Following multicollinearity testing and variable selection, thirteen predictors were retained, including slope, rainfall, lithology, NDVI, forest loss, and distance to roads. The MGWR achieved strong performance (R² = 0.94; AICc = 134.99; AUC = 0.99) and demonstrated that each factor operates at a distinct spatial scale. Slope, rainfall, and lithology exerted broad-scale controls, while road proximity had a consistent global effect. In contrast, forest loss and land use showed localized significance. These findings indicate that landslide susceptibility in Angra dos Reis is primarily driven by the interaction of orographic rainfall, steep terrain, and geological substrate, intensified by human disturbances such as road infrastructure and vegetation removal. The study underscores the need for targeted adaptation strategies, including slope stabilization, restrictions on road expansion, and vegetation conservation in steep, rainfall-prone sectors. Full article

This study looks at the role of foreign finance in promoting the shift to renewable energy in the Developing-8 (D8) countries—Bangladesh, Egypt, Indonesia, Iran, Malaysia, Nigeria, Pakistan, and Turkey—between 2000 and 2023, with particular focus given to the moderating role of globalization. Utilizing an unbalanced panel dataset covering eight D8 countries over 2000–2023 and applying advanced econometric techniques, including System-GMM, Common Correlated Effects, nd Driscoll–Kraay estimators, the analysis accounts for slope heterogeneity, cross-sectional dependence, and possible endogeneity. The results indicate that foreign finance, and particularly foreign direct investment (FDI), is highly significant in enhancing the supply and demand of renewable energy. Globalization also has an amplification effect as it spurs technology transfer, policy convergence, and market access. The combined impact of foreign finance and globalization is significant and positive in all specifications, indicating that the optimal benefits of foreign capital inflows are realized in highly integrated economies. Alternative globalization measures and tests of renewable energy robustness confirm the stability of the findings. It argues that institutionally reinforcing the foundations, strengthening global integration, and channeling foreign finance into green sectors are central policies for fostering renewable energy transitions in developing economies. This paper provides three contributions to the existing literature. First, it is the pioneering paper that examines systematically the moderating function of globalization on the foreign finance–renewable energy transition nexus in the D8 economies. Second, it applies the latest econometric techniques—System-GMM, CCE, and Driscoll–Kraay—that control for slope heterogeneity, cross-sectional dependence, and endogeneity. Third, it offers policy recommendations for emerging economies on how best to mobilize foreign finance in a globalization context. Unlike prior works that examine these dimensions separately, this study highlights their joint influence, thereby contributing a dual perspective that has been largely absent from the literature. Full article

Argillaceous slate (AS) is a typical metamorphic rock with well-developed bedding, widely distributed globally. Its bedding structure significantly impacts slope stability assessment, and the challenges associated with slope anchoring and support arising from bedding characteristics have become a focal point in the engineering field. In this study, with bedding dip angle as the key variable, mechanical tests such as uniaxial compression, triaxial compression, direct shear, and Brazilian splitting tests were conducted on AS. Additionally, field anchoring grouting diffusion tests on AS slopes were carried out. The aim is to investigate the basic mechanical properties of AS and the grout diffusion law under different bedding dip angles. The research results indicate that the bedding dip angle has a remarkable influence on the failure mode, stress–strain curve, and mechanical indices such as compressive strength and elastic modulus of AS specimens. The stress–strain curves in uniaxial and triaxial tests, as well as the stress-displacement curve in the Brazilian splitting test, all undergo four stages: crack closure, elastic deformation, crack propagation, and post-peak failure. As the bedding dip angle increases, the uniaxial and triaxial compressive strengths and elastic modulus first decrease and then increase, while the splitting tensile strength continuously decreases. The consistency of the bedding in AS causes the grout to diffuse in a near-circular pattern on the bedding plane centered around the borehole. Among the factors affecting the diffusion range of the grout, the bedding dip angle and grouting angle have a relatively minor impact, while the grouting pressure has a significant impact. A correct understanding and grasp of the anisotropic characteristics of AS and the anchoring grouting diffusion law are of great significance for slope stability assessment and anchoring design in AS areas. Full article

Total knee arthroplasty (TKA) is a commonly conducted surgery to relieve pain and enhance mobility in patients with end-stage knee osteoarthritis. Patient-reported outcome measures are often used whereas biomechanical variables are too complicated for clinicians and patients to assess functional improvement. There is a need for a simplified integrated knee biomechanics index (KBI) to compare improvements in TKA patients across various daily activities and examine the relationships between clinical functional tests and daily activities. Age-, gender-, and BMI-matched three groups (20 each in posterior stabilized TKA, bi-cruciate stabilized TKA, and healthy controls) were recruited and tested pre-op and 6-month post-op to perform walking on level, slope, and stairs, and two clinical tests (timed-up-go, 10-time sit-to-stand). Knee joint kinematics and kinetics variables were calculated from motion data and ground reactions captured at 120 Hz and 1200 Hz, respectively. KBI was developed based on these variables relative to healthy controls. The longitude comparison of KBI and the differences of KBI across various daily activities were identified using repeated-measure ANOVA. Pearson correlation analysis was used to compare clinical tests and KBI of daily activities. KBIs of five daily activities were significantly increased following TKA follow-up. KBI improvement during level walking was significantly higher than those during stair ascending and descending. Significant correlations were found between timed-up-go test time and KBIs for stair ascending and descending. Full article

Coal seams, as critical components of open-pit mine slopes, are subjected to both quasi-static and dynamic loading disturbances during mining operations, with their mechanical properties directly influencing the slope stability. Consequently, to clarify the mechanical properties and failure mechanisms of coal seams affected by the strain rate under the static–dynamic loading conditions, the mineral composition and meso-structural characteristics of lignite were analyzed in this study, and uniaxial compression tests with different quasi-static loading rates and dynamic compression tests with different impact velocities were conducted. The results indicate that there is an obvious horizontal bedding structure in lignite, which leads to differences in mechanical response and failure mechanism at different strain rates. Under the quasi-static loading, lignite exhibits significantly lower strain-rate sensitivity than compared to dynamic impact conditions. The Poisson’s ratio difference between the bedding matrix and the lignite will produce interfacial friction, which gradually decreases with the increase in the distance from the interface, thus promoting the transformation of lignite from multi-crack tensile shear mixed fracture to single-crack splitting failure. Under the dynamic impact conditions, low-impact velocities induce stress wave reflection at bedding interfaces due to wave impedance disparity between the matrix and lignite, generating tensile strains that result in bedding-plane delamination failure; at higher velocities, incomplete energy absorption by the rock specimen leads to fragmentation failure of lignite. These findings are of great significance for the stability analysis of open-pit slopes. Full article

This study investigates slope stability in an open-pit mining area by integrating engineering geological surveys, field investigations, and laboratory rock mechanics tests. A coordinated multimethod analysis was carried out using finite element-based numerical simulations from both two-dimensional and three-dimensional perspectives. The integrated approach revealed deformation patterns across the slopes and established a multiscale analytical framework. The results indicate that the slope failure modes primarily include circular and compound types, with existing step slopes showing a potential risk of wedge failure. While the designed slope meets safety requirements under three working conditions overall, the strongly weathered layer in profile XL3 requires a slope angle reduction from 38° to 37° to comply with standards. Three-dimensional simulations identify the main deformations in the middle-lower sections of the western area and zones B and C, with faults located at the core of the deformation zone. Rainfall and blasting vibrations significantly increase surface tensile stress, accelerating deformation. Although wedges in profiles XL1 and XL4 remain generally stable, coupled blasting–rainfall effects may still induce potential collapse in fractured areas, necessitating preventive measures such as concrete support and bolt support, along with real-time monitoring to dynamically optimize reinforcement strategies for precise risk control. Full article

This paper introduces a new quadruped spider robot platform specializing in environmental reconnaissance and mapping. The robot measures 180 mm × 180 mm × 95 mm and weighs 385 g, including the battery, providing a compact yet capable platform for reconnaissance missions. The robot consists of an ESP32 microcontroller and eight servos that are disposed in a biomimetic layout to achieve the biological gait of an arachnid. One of the major design revolutions is in the power distribution network (PDN) of the robot, in which two DC-DC buck converters (LM2596M) are used to isolate the power domains of the computation and the mechanical subsystems, thereby enhancing reliability and the lifespan of the robot. The theoretical analysis demonstrates that this dual-domain architecture reduces computational-domain voltage fluctuations by 85.9% compared to single-converter designs, with a measured voltage stability improving from 0.87 V to 0.12 V under servo load spikes. Its proprietary Bluetooth protocol allows for both the sending and receiving of controls and environmental data with fewer than 120 ms of latency at up to 12 m of distance. The robot’s mapping system employs a novel motion-compensated probabilistic algorithm that integrates ultrasonic sensor data with IMU-based motion estimation using recursive Bayesian updates. The occupancy grid uses 5 cm × 5 cm cells with confidence tracking, where each cell’s probability is updated using recursive Bayesian inference with confidence weighting to guide data fusion. Experimental verification in different environments indicates that the mapping accuracy (92.7% to ground-truth measurements) and stable pattern of the sensor reading remain, even when measuring the complex gait transition. Long-range field tests conducted over 100 m traversals in challenging outdoor environments with slopes of up to 15° and obstacle densities of 0.3 objects/m² demonstrate sustained performance, with 89.2% mapping accuracy. The energy saving of the robot was an 86.4% operating-time improvement over the single-regulator designs. This work contributes to the championing of low-cost, high-performance robotic platforms for reconnaissance tasks, especially in search and rescue, the exploration of hazardous environments, and educational robotics. Full article

Root tensile strength (T_r) is a fundamental root mechanical trait and serves as a key parameter for assessing the contribution of vegetation to slope stability. T_r is known to exhibit high intraspecific variability, but whether T_r varies with season remains unclear. Here, we investigated the seasonal variation in T_r in two commonly seen herbaceous species, i.e., Artemisia argyi and Cirsium setosum, both of which can be future candidates for revegetating species along roadsides in temperate and subtropical regions. We examined the T_r of their first- (closest to the stem base) and third-order lateral roots sampled in the southwest of Henan, China, in two distinct periods: September (late growing season) and December (dormant season). We found that the T_r of the thicker, first-order roots in September was significantly greater than that in December. However, such seasonal variation was not found for the thinner third-order roots. When fitting the relationship between T_r and root diameter using a two-parameter power law equation, the calibrated equation using the data collected in September led to a marked predictive bias to the data collected in December. All the above patterns were consistent for both species. Soil moisture, which exhibited strong seasonal variation in the study area, might be the key cause of variation in T_r. Our study is among the first to demonstrate seasonal variation in root mechanical traits, indicating that season potentially plays a non-negligible role in impacting soil reinforcement and slope stability by modifying roots’ mechanical quality. Full article

Due to cost and variability of geotechnical test results, the number of samples for geotechnical material parameters in one engineering project is limited, resulting in a certain degree of errors in the calculation of probability distribution, mean, and variance of mechanical parameters of the geotechnical materials. To improve the reliability of geotechnical engineering design, reducing the variance of shear strength is one of the methods. Currently, the least squares method is widely used to regress the shear strength of soil; however, the regression residuals often exhibit heteroscedasticity and correlation, which undermine the validity of the variance estimates of soil shear strength parameters. This study aims to address this issue by applying the generalized least squares method to eliminate the heteroscedasticity and correlation of regression residuals. The results of triaxial consolidated drained (CD) tests on the coarse-grained soil; triaxial unconsolidated undrained(UU), CD, and consolidated undrained (CU) tests on gravelly clay; and triaxial CD tests on sand were analyzed to estimate the mean and variance of their shear strength. The results show that while the mean values of shear strength parameters remain largely unchanged, the generalized least squares method reduces the standard deviation of cohesion by an average of 30.575% and that of the internal friction angle by 14.21%. This reduction in variability enhances the precision of parameter estimation, which is critical for reliability-based design in geotechnical engineering, as it leads to more consistent safety assessments and optimized structural designs. The reliability analysis of an infinitely long slope stability shows that the reliability index of the soil slope calculated by the traditional method is either large or small. The generalized least squares method, which eliminates the heteroscedasticity and correlation of the regression residuals, should be adopted to regress the shear strength of soil. Full article

Existing research has preliminarily achieved stable walking in humanoid robots; however, natural human-like leg motion and adaptive capabilities in dynamic environments remain unattained. This paper proposes a bionic central pattern generator (CPG) gait generation method based on Kimura neurons. The method maps the CPG output to the spatial motion patterns of the robot’s center of mass (CoM) and foot trajectory, modulated by 22 undetermined parameters. To address the vague physical interpretation of CPG parameters, the strong neuronal coupling, and the difficulty of decoupling, this research systematically optimized the CPG parameters by defining an objective function that integrates dynamic balance performance with step constraints, thereby enhancing the naturalness and coordination of gait generation. To further enhance the walking stability of the robot under varying road curvatures, a vestibular reflex mechanism was designed based on the Tegotae theory, enabling real-time posture adjustment during slope walking. To validate the proposed approach, a virtual simulation platform and a physical humanoid robot system were constructed to comparatively evaluate motion performance on flat terrain and slopes with different gradients. The results show that the energy consumption characteristics of robot-coordinated gait are highly consistent with the energy-saving mechanism of human natural motion. In addition, the established reflection mechanism significantly improves the motion stability of the robot in slope transition, and its excellent stability margin and environmental adaptability are verified by simulation and experiment. Full article

To reveal the influence mechanism of shear creep behavior of the weak interlayer (carbonaceous mud shale) from a microscopic perspective, acoustic emission (AE) technology was introduced to conduct shear creep tests to capture micro-fracture acoustic signals and analyze the microscopic damage evolution laws. The results indicate that, as normal stress increased, shear creep strain decayed exponentially, while the steady state creep rate increased gradually. Additionally, the peak value and cumulative value of the AE ringing count rate also increased gradually. The AE b-value had a staged pattern of “fluctuation adjustment → stable increase → abrupt decline”. The sudden drop in the b-value could serve as a precursor feature of creep failure. The higher the normal stress, the earlier the sudden drop in b-value and the larger the Δb value. The damage variable was defined based on the AE ringing count rate, and a new creep damage model was constructed by combining fractional-order theory. The model can uniformly describe the creep damage law of carbonaceous mud shale under different normal stresses. The reliability of the model was verified through experimental data. The research results provide a theoretical basis for long-term stability analysis of mine slopes containing weak interlayers. Full article

With the rapid development of deep-sea resource exploration and marine scientific research, wheeled remotely operated vehicles (ROVs) have become crucial for seabed operations. However, under complex seabed conditions, traditional ROV control systems suffer from insufficient trajectory tracking accuracy, poor disturbance rejection capability, and low dynamic torque distribution efficiency. These issues lead to poor motion stability and high energy consumption on sloped terrains and soft substrates, which limits the effectiveness of deep-sea engineering. To address this, we proposed a comprehensive motion control solution for deep-sea wheeled ROVs. To improve modeling accuracy, a coupled kinematic and dynamic model was developed, together with a body-to-terrain coordinate frame transformation. Based on rigid-body kinematics, three-degree-of-freedom kinematic equations incorporating the slip ratio and sideslip angle were derived. By integrating hydrodynamic effects, seabed reaction forces, the Janosi soil model, and the impact of subsidence depth, a dynamic model that reflects nonlinear wheel–seabed interactions was established. For optimizing disturbance rejection and trajectory tracking, a hierarchical control method was designed. At the kinematic level, an improved model predictive control framework with terminal constraints and quadratic programming was adopted. At the dynamic level, non-singular fast terminal sliding mode control combined with a fixed-time nonlinear observer enabled rapid disturbance estimation. Additionally, a dynamic torque distribution algorithm enhanced traction performance and trajectory tracking accuracy. Full article