Search Results (147)

Electric unmanned vehicles applied in complex terrains such as agricultural, forestry, and deep-space exploration scenarios are often required to travel on uneven roads. In particular, during climbing processes, their driving stability and terrain adaptability are of critical importance. To address the above challenges, an electric unmanned vehicle with variable-diameter wheels is proposed. By adjusting the wheel diameter, the vehicle can modify its pitch and roll angles to adapt to uneven terrains. The core research focuses on the relationship between quasi-static stability and wheel diameter variation. First, the configuration and working principle of the electric unmanned vehicle with variable-diameter wheels are introduced, with particular emphasis on the mechanism principle of the novel variable-diameter wheel. A kinematic model between the electric cylinder input and wheel diameter in the variable-diameter wheel is established. On this basis, based on the FASM (Force-Angle Stability Margin)—a stable cone theory, the relationships between stability and wheel diameter variation were investigated separately under lateral, longitudinal, and 45° steering composite conditions on a slope. The results indicate that the unmanned vehicle can achieve omnidirectional attitude adjustment. Finally, the relationship between the electric cylinder input and stability is derived, which can provide a theoretical basis for the quasi-static stability control of outdoor electric unmanned vehicles. Full article

The aim of the current study was to select and test the appropriate model and input parameters for remote sensing retrieval of surface soil moisture (SSM) in the case of bare Chernozems on flat and sloping terrains in northern Bulgaria under different tillage systems. Normalized synthetic aperture radar (SAR) measurements from Sentinel-1 C-band dual-pol products (Gamma-Nought in VV, ratio) were utilized in two ways to delineate SSM from environmental factors that bias determination. The accuracy of the obtained SSM prediction was evaluated against ground-based volumetric water content (VWC) measured in the 0–3.8 cm soil layer at multiple points using a TDR meter. The TDR VWC data were preliminarily calibrated against gravimetric measurements in the 0–5 cm soil layer. The obtained data for soil water retention curves in all studied variants were used to determine the range of soil moisture variation. The measured ground-based data for surface roughness generally correlate with the co-pol Gamma-Nought in VV. The data modeled with the surface soil moisture script in Sentinel Hub (SSM-SH) was calibrated using the ground-based data. Incidence angle normalization of Sentinel-1 products improved the relationship between SAR observables and SSM, when expressed as the ratio of soil moisture to total porosity (rVWC). The modeling indicated the highest importance of the optical indices, together with the temporal differences of radar descriptors sensitive to variations in soil moisture over time. Although the applied Random Forest Regression (RFR) model achieved higher accuracy during training (nRMSE of 7.27%, R² of 0.86), the Gaussian Process Regression (GPR) model provided better generalization performance on the independent validation dataset. The results proved the advantages of the joint utilization of temporal Sentinel-1 SAR measurements with Sentinel-2 optical acquisitions to determine SSM in different bare soil conditions for achieving high accuracy. Full article

This work presents a simulation-based approach to support the planning of Terrestrial Laser Scanning (TLS) surveys for landslide monitoring. Starting from an approximate digital model of the slope, the method estimates the spatial distribution of positional error induced by scanner characteristics, laser beam divergence and, critically, by the incidence angle between the laser beam and the local surface normal. Because complex morphologies cause rapid local variations in incidence angle, neighbouring points may exhibit markedly different error magnitudes, making a direct classification of raw error values insufficient to delineate homogeneous areas. To address this, a multidimensional variable is defined for each simulated point, combining position, estimated error, distance from the scanner and incidence angle. After dimensionality reduction through PCA, the dataset is clustered using K-means with a sufficiently large number of clusters to preserve spatial resolution. Each cluster is associated with a representative error level, and clusters are then merged into broader error classes that delineate zones of comparable expected precision. The procedure is repeated for alternative scanner positions, enabling a comparative evaluation of achievable accuracy across the slope and the identification of areas requiring multiple scans. The method provides a quantitative, reproducible framework to guide TLS station selection and optimize survey design in complex morphological settings. Full article

Background/Objectives: This study aimed to clinically investigate how variations in foot morphology influence spinal and lower limb alignment, based on the concept of an ascending kinetic chain. Methods: We analyzed the medical records of 100 patients who met the inclusion criteria. The X-ray image data used in the analysis included weight-bearing lateral views of both feet, whole-spine anteroposterior (AP) and lateral views, and full-length standing AP scanograms of the lower legs. In the obtained X-ray images, Calcaneal Inclination Angle (CIA), Tibiotalar Tilt Angle (TTA), Tibiotalar Angle (TA), Quadriceps Angle (Q-angle), Pelvic Incidence (PI), Pelvic Tilt (PT), Sacral Slope (SS), and L1–S1 Lordosis (LL) were measured. Participants were categorized into subgroups based on their CIA values: Pes Planus, Normal, and Pes Cavus. These subgroups were analyzed by foot orientation (right and left) using one-way analysis of variance (ANOVA) and Pearson correlation coefficient analysis. Results: The one-way ANOVA identified significant differences in mean right foot PT values among subgroups. Correlation analysis shows moderate associations between foot CIA and Q-angle of the knee, as well as pelvic parameters including PI, PT, SS, and LL. Conclusions: Analysis of the correlation between foot parameters and body alignment, in the context of diagnostic and evaluative aspects of Chuna manual medicine (CMM), revealed moderate correlations among the foot, ankle, knee, pelvis, and lumbosacral regions. These findings suggest that foot morphology may play a clinically relevant role in posture-related disorders and could contribute to preventive and corrective strategies for musculoskeletal alignment. Full article

The long-term stability of embankments is directly influenced by the stress paths associated with river water level fluctuations. To investigate the anisotropic characteristics of slope soil in embankments under such drainage-induced gradual loading conditions, a series of drained directional shear tests was conducted on slope soil to investigate the coupled effects of the principal stress direction angle α and the intermediate principal stress coefficient b on its strength, deformation, and non-coaxial characteristics. Results showed that radial strain exhibited minimal sensitivity to variations in the principal stress direction angle α at the constant principal stress coefficient b. The circumferential and axial strain directions demonstrated symmetry. Specimens initially contracted then dilated during shearing. Octahedral shear strain anisotropy was more significant at b = 0.5 and 1 than at b = 0. For a constant α, the normalized strength at b = 0.5 exceeded that at b = 0 and 1. Strength showed significant anisotropy across angles α at a constant b. Specimens exhibited significant non-coaxial behavior under axial-torsional shear loading. This study offers theoretical insight into embankment slope behavior under anisotropic stress paths. Full article

This study investigates the impact of non-ideal wordline sidewall angles caused by photoresist profile variation during the wordline etching process in DRAMs employing a buried-channel array transistor (BCAT) structure. Using Technology Computer-Aided Design (TCAD), a two-dimensional (2D) BCAT-based DRAM cell was modeled to analyze the resulting variations in device characteristics as well as write and hold operations. The simulation results show that increased etch slope angles lead to degradation in device performance, including failure to meet the read pass/fail criterion and data retention during the 300 ms hold interval. To mitigate these issues, we inserted a buried oxide (BOX) layer beneath the active wordline (AWL). The incorporation of the BOX layer effectively improved overall device robustness and reduced the degradation induced by non-ideal etch slopes. Full article

With the growing global emphasis on space resources, the significance of space detection and surveillance technologies has escalated. Currently, space-based optical surveillance stands as the primary means for acquiring information on space objects. However, constrained by the diffraction limits of space telescopes, distant space objects are typically imaged as point sources. The resulting lack of sufficient spatial resolution renders traditional image-based recognition algorithms ineffective. In contrast, the Bidirectional Reflectance Distribution Function (BRDF) fully characterizes surface light scattering properties through four-dimensional features, significantly outperforming traditional two-dimensional spectral techniques in material identification. Consequently, leveraging BRDF signatures at varying phase angles has emerged as an effective approach for Space Object Identification. In this study, we developed an automated BRDF measurement system to characterize various typical aerospace materials and investigated the BRDF properties of mixed-material surfaces. A material composition ratio prediction model was constructed based on a One-Dimensional Convolutional Neural Network (1D-CNN). This model effectively extracts key features, including local slope variations and global waveform characteristics, from the BRDF curves. Experimental results demonstrate that the model achieves a maximum relative percentage error of 6.21%, implying a prediction accuracy for mixed-material composition ratios consistently exceeding 93.79%. Compared to image classification methods based on remote sensing imagery, the proposed approach offers higher computational efficiency, significantly reduced model complexity and computational cost, and enhanced robustness. This work provides essential data support for material identification by space-based telescopes and establishes an algorithmic and experimental foundation for intelligent space situational awareness systems. Full article

Slope stability is a critical and extensively researched topic that is important in structural design, especially when slopes are located near residential or civil engineering structures, as human lives are at risk. This paper presents a detailed analysis and evaluation of slope stability, synthesizing current understanding of slope behaviour, soil shear strength parameters, and the methodologies applied in stability assessment. In the conducted parametric study, the stability of slopes composed of fine-grained soils was investigated using both the limit equilibrium method (LEM) and the finite element method (FEM). The principal objective of the research was to assess the influence of soil shear strength parameters on the resulting factor of safety (FoS), while also accounting for variations in slope height. The results of the study show that an increase in soil shear strength parameters leads to a linear increase in FoS, with this relationship being more pronounced for changes in soil cohesion than for changes in the angle of internal friction. The effect of shear strength variations on stability is more pronounced in slopes of smaller height. Furthermore, the comparative analysis indicates that LEM provides more conservative estimates of slope stability in comparison with FEM. Full article

The mechanical response of geomembranes in hydraulic structures is strongly influenced by temperature variations, which alter both material stiffness and interface shear strength behavior. This study develops a non-linear, temperature-dependent tensile behavior constitutive model for a polyvinyl chloride (PVC) geomembrane and evaluates its implications for the stability of geomembrane-lined reservoir slopes. The empirical relationship was calibrated using tensile tests reported in literature for temperatures between 10 °C and 60 °C, reproducing the observed non-linear softening and modulus reduction with increasing temperature. A classical thermal dilation formulation was incorporated to simulate cyclic thermal expansion and contraction. The constitutive and thermal formulations were implemented in FLAC2D and applied to a 2H:1V covered geomembrane slope representative of dam lining systems. The results show that temperature-induced softening significantly increases tensile strain within the geomembrane. The model also shows that the lower surface interface friction angle of the geomembrane plays a significant role in the slope stability. Thermal cycle analysis demonstrates the accumulation of efforts resulting from the fatigue of the geomembrane. The proposed model provides a practical framework for incorporating thermo-mechanical coupling in design analyses and highlights the necessity of accounting for realistic thermal conditions in assessing the long-term stability of geomembrane-lined reservoirs. Full article

The repeated extraction of coal seams in the Loess Plateau mining region has greatly increased the severity of surface deformation and associated damage. Accurately characterizing the spatio-temporal evolution of subsidence and the underlying mechanisms is a critical engineering challenge for mining safety. Taking the Dafosi Coal Mine located in the loess gully region as a case study, this paper thoroughly examines the variations in surface deformation and damage characteristics caused by single and repeated seam mining. The analysis integrates surface movement monitoring data, global navigation satellite system (GNSS) dynamic observations, field surveys, unmanned aerial vehicle (UAV) photogrammetry, and numerical simulation methods. Notably, to ensure the accuracy of prediction parameters, a refined Particle Swarm Optimization (PSO) algorithm incorporating a neighborhood-based mechanism was employed specifically for the inversion of probability integral parameters. The results indicate that the subsidence factor and horizontal movement factor increase markedly following repeated mining. The maximum surface subsidence velocity also increases substantially, and this acceleration remains evident after normalizing by mining thickness and face-advance rate. The fore effective angle is smaller in repeated mining than in single-seam mining, and the duration of surface movement is substantially extended. Repeated mining fractured key strata and caused a functional transition from the classic three-zone response to a two-zone connectivity pattern, while the thick loess cover responds as a disturbed discontinuous-deformation layer, which together aggravates step-like and slope-related damage. The severity of surface damage is strongly influenced by topographic features and geotechnical properties. These findings demonstrate that the proposed integrated approach is highly effective for geological hazard assessment and provides a practical reference for engineering applications in similar complex terrains. Full article

This study investigates rainstorm-induced highway subgrade slope collapses in the coastal areas of Southeast China. By integrating the seepage–stress coupled finite element method with the strength reduction method, we simulate the entire process of seepage, deformation, and slope collapse under rainstorm conditions, analyzing the variation in the stability factor. The key findings are as follows: (1) During rainstorms, water infiltration increases soil saturation and pore water pressure, while reducing matrix suction and soil shear strength, leading to soil softening. (2) The toe of the subgrade slope first undergoes plastic deformation under rainstorms, which develops upward, and finally the plastic zone connects completely, causing collapse. The simulated landslide surface is consistent with the actual one, revealing the collapse mechanism of the subgrade slope. Additionally, the simulated displacement at the slope toe when the plastic zone connects provides valuable insights for setting warning thresholds in landslide monitoring. (3) The stability factor of the subgrade slope in the case study decreased from 1.24 before the rainstorm to 0.985 after the rainstorm, indicating a transition from a stable state to an unstable state. (4) Parameter analysis shows that heavy downpour or downpour will cause the case subgrade slope to enter an unstable state. The longer the rainfall duration, the lower the stability factor. Analysis of soil parameters indicates that strength parameters, internal friction angle, and effective cohesion exert a significant influence on slope stability, whereas deformation parameters, elastic modulus, and Poisson’s ratio have a negligible effect. Slope collapse can be timely forecasted by predicting the stability factor. Full article

Granular flow, a dynamic mass from loose deposits or landslides in mountains, severely damages structures along its path. Barriers are widely used to mitigate such disasters, making studies on granular flow kinematics and interaction with barriers crucial for disaster reduction. This study conducts physical model experiments to observe the movement and impact behavior of dry granular flow, exploring the effects of variations in particle size, channel slope angle, and barrier height on the interaction between granular flow and vertical barriers. Additionally, a model for estimating the impact force of dry granular flow on vertical barriers is proposed, with its reliability validated through experimental data. The results indicate that barriers exhibit a significant retention effect on granular flow. Larger particle sizes and steeper slope angles lead to a marked increase in both the mobility of granular flow and its impact force on barriers. A substantial increase in barrier height significantly enhances its ability to block or intercept the flow. The results in the research clarify how particle size, slope angle, and barrier height jointly govern deposit morphology and peak impact force on vertical walls, and the proposed force decomposition provides a physically interpretable framework for estimating wall-normal impact forces from measurable kinematic quantities. Full article

This study establishes a dynamic evolution model of the physical and mechanical properties of lunar simulant as a function of sampling-induced disturbance on the lunar surface, aiming to eliminate design errors in sampling missions caused by neglecting the disturbance of lunar soil. A standard probe was inserted into the lunar soil simulant both before and after disturbance, and the variation in penetration resistance at the exact location was proposed as an indicator of the regolith’s disturbance state. Compression tests and disturbance tests were conducted on CUG-1A lunar soil simulant, with the experimental results subjected to regression analysis and neural network prediction. Based on the compression tests, a regression equation was derived relating the slope of the probe penetration resistance to the internal friction angle and density of the lunar soil simulant, showing a strong correlation between predicted and actual values. The disturbance tests provided penetration resistance curves under various disturbance conditions. By integrating these two components, a correspondence was established between the disturbance conditions and the internal friction angle and density of the lunar soil simulant. The predictive performance of three typical neural network algorithms—LM, BR, and SCG—with varying numbers of neurons was compared. The LM algorithm with 10 neurons was selected for its superior performance. Ultimately, a sampling disturbance model was developed to predict the internal friction angle and density of the lunar soil simulant based on disturbance conditions, demonstrating an extremely high correlation between predicted and actual values. Full article

Lateral pipe-soil interaction is crucial for the on-bottom stability design of submarine pipelines, particularly on deep-water sloping silt seabeds. To address this, a mechanical-actuator facility has been specially designed and utilized to simulate the lateral instability process of a pipe on silt slopes (α) ranging from −15° to +15°. In this study, variations in the dimensionless submerged pipeline weight (G = 0.607–1.577) and initial embedment ratios (|e₀|/D = 0.01–0.50) are also considered. Experimental results reveal several key findings. First, brittle pipe-soil responses are observed: under embedment ratios larger than 0.05, the breakout soil resistance is dominated by suction due to negative pore pressure generation at the rear of the pipe, whereas under lower embedment ratios, it is primarily governed by interface friction and cohesion. Second, for a constant submerged pipeline weight (G = 1.092), the breakout drag force increases linearly with slope angle, whereas the breakout soil resistance decreases linearly—a difference attributed to the gravitational component W_ssinα. Specifically, compared to a horizontal flat seabed, the breakout lateral drag force increases by approximately 33% for upslope instability (α = +15°), but decreases by about 24% for downslope instability (α = −15°). Third, the dimensionless lateral-soil-resistance coefficient on silt increases nonlinearly and monotonically with the slope angle, a trend opposite to that reported for sandy seabeds. Finally, an improved model is proposed that explicitly incorporates silt slope angle, submerged pipeline weight, and embedment ratio. This study aims to offer valuable insights into the stability of pipelines on partially drained continental silt slopes and to support the adoption of slope-specific criteria in future engineering designs. Full article

With the rapid development of coastal and nearshore engineering projects in China, geotextile pipe and bag (GPB) structures have been increasingly applied in marine land reclamation and coastal protection works. To better understand the mechanical behavior of GPB structures on soft soil foundations, this study conducts a systematic investigation into the mechanical properties of both soft soils and GPBs using a physical model test system. By integrating numerical simulations, the stress–deformation characteristics of GPB structures on soft soils and the evolution of pore pressure are further analyzed. The results indicate that the compression curve of soft soil exhibits significant nonlinearity, with silt showing higher apparent compressibility than silty clay. Experimental data yielded the compression coefficient λ and rebound coefficient μ for both soil types. As consolidation pressure increases, deviatoric stress in the soft soil rises notably, demonstrating typical strain-hardening behavior. Based on these findings, the critical state effective stress ratio M was determined for both soil types. The study also establishes the development laws of cohesion c and friction angle φ during soil consolidation, as well as the variation of pore water pressure under different confining pressures. Interface tests clarify the relationships between cohesion and friction angle at the interfaces between geotextile pipe bags and sand, and between adjacent pipe bag layers. Numerical simulations reveal that the reclamation construction process significantly influences structural horizontal displacement. Significant stress concentration occurs at the toe of the slope, while the central portion of the pipe-bag structure experiences maximum tensile stress—still within the material’s allowable stress limit. The installation of drainage boards effectively accelerates pore pressure dissipation, achieving nearly complete consolidation within one year after construction. This research provides a scientific foundation and practical engineering guidance for assessing the overall stability and safety of (GPB) structures on soft soil foundations in coastal regions. Full article