Search Results (82)

Clay slopes are particularly sensitive to variations in soil strength, groundwater conditions, and slope geometry, making their rapid and reliable assessment essential for geotechnical design, landslide prevention, and infrastructure risk management. This study develops and evaluates an empirical express method for estimating the stability of clay slopes based on the relationship between soil mechanical parameters, slip surface geometry, and the factor of safety. The proposed approach derives empirical dependencies for the radius of the potential circular slip surface and the coordinates of its centre as functions of slope height, cohesion, internal friction angle, and water-related conditions. The method is supported by long-term field observations and geotechnical investigations of clay slopes, including dry and water-affected scenarios. Two representative stability conditions are considered: dry slopes and slopes influenced by an elevated depression curve. The method was evaluated for 45° clay slopes with heights up to 60 m, using eight representative cases: four dry scenarios and four water-affected scenarios. The calculated factors of safety were compared with GEO5 SLOPE results obtained using Bishop’s simplified method. The comparison showed that most analysed cases presented differences below 5% between the proposed express method and the Bishop-based numerical benchmark, with larger deviations occurring only in selected boundary cases. The results demonstrate that the proposed method can provide a rapid preliminary assessment of clay slope stability, supporting early-stage geotechnical diagnosis, risk screening, and decision-making in regions where clayey formations and slope instability are recurrent. Full article

The path-tracking and motion control of autonomous tractor–trailer systems (TTSs) in unstructured off-road environments have become important research topics of intelligent equipment. Traditional control architectures face challenges due to multiple physical constraints such as time-varying soil rheology, time-varying wheel slip, multi-body nonlinear coupling, and vehicle stability constraints. This review provides an overview of advanced control technologies for autonomous TTSs in off-road environments. First, this review analyzes multi-source sensors and joint state estimation frameworks for time-varying terrain classification, all-wheel slip ratio estimation, and articulation angle. Secondly, nonholonomic kinematic, multi-body three-dimensional spatial dynamic, and tire–soil interaction mechanic models are deconstructed for on-axle and off-axle hitching configurations. On this basis, adaptive kinematic control, model predictive control (MPC), robust disturbance rejection, and distributed electric-drive control strategies are compared horizontally, and the application of active trailer steering, torque vectoring, and implemented chassis cooperative control in active safety is elaborated. Finally, emerging research directions, including online tire–soil interaction learning, embodied AI foundation models, and V2X-enabled multi-vehicle cooperative platooning, are discussed to provide insights into the development of next-generation fully autonomous off-road tractor–trailer systems. Full article

Reliable estimation of vehicle states, tire cornering stiffness, and the tire-road adhesion coefficient are essential for vehicle lateral stability and intelligent chassis control. Under low adhesion, nonlinear tire operation, and weak excitation, lateral-force residuals are jointly affected by cornering-stiffness variation, adhesion-coefficient variation, and tire-force saturation, which may cause erroneous parameter adaptation. This paper proposes a reliability- and sensitivity-guided co-estimation method for vehicle states, tire cornering stiffness, and the tire-road adhesion coefficient. A hierarchical framework is developed based on a planar 3-DOF vehicle model and a Fiala-type nonlinear tire model. Front- and rear-axle lateral-force pseudo-measurements are reconstructed from lateral acceleration and yaw angular acceleration, without requiring additional tire-force sensors. Parameter-update reliability is evaluated by considering lateral excitation, longitudinal slip, adhesion utilization, and normalized lateral-force residual consistency. Normalized lateral-force sensitivities are then used to allocate the residual between the cornering-stiffness and adhesion-coefficient update channels. CarSim/Simulink co-simulations under high-, intermediate-, and low-adhesion double-lane-change maneuvers demonstrate that the proposed method improves sideslip-angle and lateral-velocity estimation accuracy, suppresses erroneous cornering-stiffness adaptation, and provides more stable estimates of the tire-road adhesion coefficient. Full article

Optimizing a high-fidelity GT3 race car setup is a serious dimensional, nonlinear problem in which small changes to mechanical parameters can affect lap time, handling balance, and vehicle stability. Existing motorsport AI studies largely emphasize racing line optimization, autonomous control, race strategy, or offline vehicle dynamics estimation, while the mechanical setup layer is often treated as fixed or tuned manually. This paper presents a staged simulator-based setup optimization framework augmented with setup-conditioned telemetry response modeling. Using the virtual BMW Z4 GT3 vehicle model implemented within the Assetto Corsa (v1.16.4) simulation environment as a controlled GT3 test platform, 134 setup configurations were evaluated at the Red Bull Ring under a fixed simulator AI driving policy. The staged search improved the best lap time from 91.430 s to 91.040 s, corresponding to a 0.390 s reduction. To move beyond a single aggregate lap-time claim, the full telemetry corpus was processed into 585 stable laps and 29,250 track-position segment samples. A setup-conditioned LightGBM model was trained to predict segment time and local vehicle response metrics from setup parameters and segment context, using five-fold GroupKFold validation by telemetry file to avoid random row leakage. The setup-conditioned segment model reconstructed held-out file-level lap time with 0.223 s mean absolute error and Spearman correlation of 0.961, outperforming a setup-only model at 0.288 s, a track-only segment model at 0.687 s, and a shuffled-setup placebo at 0.776 s. The same setup-conditioned model also improved the prediction of segment-level speed, slip angle, tire load spread, rake (defined here as rear-front ride height difference), tire temperature, yaw response, and lateral acceleration. These results show that high-frequency telemetry can support not only staged setup search, but also quantifiable learning of where and how setup changes alter vehicle behavior around the lap. Full article

Four-wheel independent steering (4WIS) vehicles can improve low-speed maneuverability and high-speed stability by independently regulating the steering angles of all four wheels. However, under large-curvature trajectories, parameter perturbations, and external disturbances, inconsistent coordination among the four-wheel steering angles may increase tire lateral slip, yaw response deviation, and trajectory tracking errors. To address the difficulty of conventional trajectory tracking methods in simultaneously ensuring geometric consistency, tracking accuracy, and robustness, this paper proposes an adaptive sliding mode trajectory tracking control method based on instantaneous center of rotation (ICR) constraints. First, the tire instantaneous turning center (TTC) of each wheel is derived using rigid-body spatial kinematics, and the TTCs are mapped onto a unified vehicle-body reference plane based on the SAE J670 coordinate system to obtain a real-time vehicle-level ICR estimation. Second, a lateral–yaw dynamic model and a trajectory tracking error model are established. The yaw rate and sideslip angle are corrected using ICR geometric information, and an adaptive sliding mode controller is designed with an equivalent control term, adaptive switching gain, adaptive boundary layer, and sideslip suppression term. The uniform ultimate boundedness of the sliding variable and closed-loop tracking errors is proven using Lyapunov theory. Finally, MATLAB (2023a)2024/CarSim (2019) co-simulations are conducted under small-curvature sinusoidal, double-lane-change, large-curvature sinusoidal, low-adhesion, and mass-perturbation conditions. The results show that the proposed ICR-SMC method significantly reduces lateral and heading errors compared with U-LQR and U-SMC, especially under large-curvature and low-adhesion conditions, demonstrating improved tracking accuracy and robustness for 4WIS vehicles. Full article

This paper proposes an enhanced adaptive unscented Kalman filter (SH-AUKF) method based on the Sage–Husa algorithm to address the issue of insufficient estimation accuracy for state parameters and road adhesion coefficients in distributed drive mining dump trucks under complex mining conditions. By integrating a seven-degree-of-freedom vehicle dynamics model with the Dugoff tire model, a collaborative observer is constructed for estimating state parameters and the four-wheel road adhesion coefficient. Through joint simulation verification using Trucksim–Matlab 2025b, it was demonstrated that under sinusoidal steering, step steering, and varying road adhesion coefficients (0.3~0.7), the root mean square error (RMSE) of longitudinal vehicle speed, slip angle, and yaw rate estimation using SH-AUKF was significantly reduced compared to the traditional UKF. Additionally, the estimation error of the four-wheel road adhesion coefficient was decreased by 8~26%. This has significant application value for improving the automation level of mining transportation. Full article

Accurate trajectory tracking is challenging for tracked agricultural vehicles in orchards. Uneven terrain, track slip, and vehicle posture variations are the main causes, often leading to model mismatch and degraded control performance. To address these issues, this paper proposes an improved nonlinear model predictive control (NMPC) strategy integrated with curvature feedforward compensation for trajectory tracking of tracked agricultural vehicles under uneven terrain conditions. An enhanced kinematic model based on the instantaneous center of rotation is developed by incorporating vehicle roll and pitch angles, and track slip parameters are estimated online using a Levenberg–Marquardt optimization method to improve prediction accuracy. Furthermore, curvature feedforward information derived from the reference trajectory is embedded into the NMPC objective function to provide anticipatory control inputs and reduce computational burden. Simulation results demonstrate that compared to conventional NMPC, the proposed method reduces the mean and standard deviation of tracking error by 30.28% and 32.46% respectively, while decreasing the mean and standard deviation of heading error by 37.27% and 35.05%. Concurrently, the maximum of optimize solution time is significantly reduced, effectively resolving tracking accuracy degradation caused by system solution timeouts. Field experiments conducted under different load conditions further validate that the proposed control strategy significantly reduces lateral, longitudinal, and heading tracking errors compared with conventional NMPC, confirming its effectiveness and robustness for tracked agricultural vehicle trajectory tracking in complex orchard environments. Full article

Introduction: Slipped capital femoral epiphysis (SCFE) is commonly treated using percutaneous in situ fixation. After screw fixation, remodelling of the proximal femur can occur; however, the factors influencing this process are poorly understood. This study aimed to measure the amount of remodelling after in situ SCFE fixation and determine the influence of the transphyseal screw position across the physis. Methods: In this retrospective study, all eligible patients with SCFE who had percutaneous screw fixation at Erasmus MC—Sophia Children’s Hospital between 2012 and 2020 were included. The amount of remodelling was determined by measuring the Southwick angle, alpha angle and displacement from Klein’s line directly after screw fixation and at final follow-up. Transphyseal screw position was measured through AP and frog-leg lateral radiographs by measuring the placement of the centre of the screw in relation to the centre of the epiphysis. A linear mixed model was used to determine factors influencing the amount of remodelling. Results: 86 patients with 96 affected hips were included; the mean age was 12.4 (±2.0) years at surgery, and the mean follow-up duration was 3.7 (±2.0) years. All measurements showed significant remodelling at follow-up compared to baseline. Over the follow-up period, the mean change in Southwick angle was 4.6° (95% CI: 2.5; 6.7, p < 0.001), the mean change in Alpha angle was 10.4° (95% CI: 7.3; 13.5, p < 0.001) and the mean change in displacement from Klein’s line was −1.2 mm (95% CI: −1.7; −0.61, p < 0.001). Linear mixed model analyses showed that remodelling was significantly correlated with deformity at baseline for all measurements. Also, a more lateral screw position was significantly correlated with more improvement in displacement from Klein’s line (estimate: −4.2, 95% CI: −8.0 to −0.5). However, the effect observed was relatively small. Conclusions: A statistically significant amount of remodelling was measured after percutaneous screw fixation for patients with SCFE. The amount of remodelling was relatively limited, but was shown to be influenced by the severity of the initial slip and a more lateral transphyseal screw position. Full article

Most falls occur while walking, making gait quality a logical therapeutic target. Many temporo-spatial variables have been implicated in increased fall risk, but these are dependent upon kinematic parameters of the joints involved in the gait cycle. The widespread availability of wearable sensors has made the acquisition of kinematic data feasible, and those related to the ankle are most relevant, as they relate most closely to causes of falls, trips, slips, and mis-steps. The purpose of this study is to estimate the extent to which measures of ankle angular velocity (AV) during walking are associated with falls. This is a comparative study of ankle AV metrics between people who have or have not experienced a fall in the past year. Data came from experimental use of the Heel2Toe™ sensor in a variety of settings, including demonstrations and clinical research studies. The sample comprised 387 participants, of whom 68 (17.6%) self-reported falling in the past year. Logistic regression with a natural cubic spline with 3 degrees of freedom identified AV of the angle at heel strike to discriminate between fallers and non-fallers, and the regression parameters were used to propose an algorithm to estimate fall risk. Applying the algorithm to the existing data yielded a range of probabilities from 0.0480 to 0.7245 depending on age of the person assessed. Further testing of this algorithm in different samples is warranted. Full article

Permanent ground deformation caused by fault movement threatens the safe operation of buried pipelines. Accurate fragility assessment of buried pipelines subjected to faulting is essential for pipeline design and risk management. However, buried pipelines exhibit nonlinear mechanical responses due to the coupled effects of multiple factors. Moreover, the effects of key parameters remain insufficiently quantified, limiting the accuracy and engineering applicability of existing fragility assessments. In this study, a three-dimensional finite element model incorporating large deformation and nonlinear pipe–soil interaction is developed and validated against representative experimental data. Using this model, numerical simulations are performed for 352 parameter combinations covering fault type, dip angle, burial depth, soil type, and pipe material. Nonlinear regression of the simulation results yielded predictive models for pipeline peak axial strain under normal-slip and reverse-slip faulting. A fragility framework is then established with fault displacement as the intensity measure, and fragility curves are derived for both faulting modes. The predicted peak axial strains agree with the finite element results: 78.6% (normal-slip) and 72.5% (reverse-slip) of predictions fall within ±20% error. The fragility curves enable quantitative estimation of fault-displacement thresholds. In the case study, the intact-to-damage displacement threshold is approximately 0.6 m for normal-slip faults but approximately 0.2 m for reverse-slip faults, indicating a higher failure likelihood under reverse-slip faulting. Within the investigated parameter ranges, the fault dip angle is the most significant factor affecting the pipeline failure probability for both normal-slip and reverse-slip faulting. Sandy soil and greater burial depth substantially increase the probability of moderate-to-severe damage, whereas higher steel grade increases the displacement threshold for transition from intact to failure. This study provides a rapid quantitative tool and a theoretical basis for pipeline design and risk quantification of buried pipelines in fault zones. Full article

Real-time estimation of vehicle sideslip angle is essential for both safety and performance applications. This study presents a temperature-adaptive Extended Kalman Filter (EKF) that estimates the sideslip angle of a racing vehicle by integrating dynamic and kinematic information. A temperature-dependent Pacejka tire model, derived directly from track tests, is embedded in a 3-degree-of-freedom dual-track vehicle model and used within the EKF to compensate for temperature-induced variations in tire behavior. The adaptive model parameters are identified from standard on-track maneuvers conducted at different tire temperatures, without the need for additional indoor rig testing. Experimental validation on a race track demonstrates that incorporating tire temperature adaptation and combining dynamic and kinematic estimation significantly enhance estimation accuracy, particularly underow-grip and high-performance driving conditions attested by a reduction of 40–50% in RMS error and a further reduction in maximum absolute error. Full article

To investigate the anti-slip characteristics of the main cables in a three-tower suspension bridge with spatial cable systems, this paper proposes an analytical calculation method for the anti-slip safety factor of the main cables and establishes an equivalent mechanical analysis model for multi-tower suspension bridges with spatial cable systems. Based on the deformation of the towers and cables under live load, as well as the equilibrium relationship of the main cable forces in loaded and unloaded spans, analytical formulas for the anti-slip safety factor of the main cables at the middle tower saddle are derived. A finite element model is developed to validate the formulas. The influence of parameters such as the spatial cable inclination angle, tower-to-cable stiffness ratio, dead-to-live load ratio, sag-to-span ratio, span length, and friction coefficient between the main cable and saddle on the anti-slip safety factor is analyzed. The results indicate that the formula proposed in this paper provides a highly accurate estimation of the slip resistance safety factor for main cables in spatial cable multi-tower suspension bridges. The adoption of spatial main cable configuration enhances the stability of the slip resistance safety factor at the intermediate tower saddle. The slip resistance safety factor of the main cable decreases with the increase in the tower-to-cable stiffness ratio, while it increases with the rise in the sag-to-span ratio. Moreover, the influence of the sag-to-span ratio on the slip resistance stability of the main cable becomes more pronounced with higher tower stiffness. The slip resistance safety factor of the main cable exhibits an approximately linear increase with the rise in the dead-to-live load ratio and the coefficient of friction. Furthermore, the slip resistance safety factor increases with the span length, and this rate of increase becomes more pronounced with smaller sag-to-span ratios. The research findings presented in this paper provide a theoretical basis for the design of spatial cable multi-tower suspension bridges. Full article

High-reliability localization is essential for underground mining autonomous vehicle, as inaccurate positioning triggers collision risks and limits deployment in safety-critical environments. Underground mining localization faces unique challenges: kilometer-scale signal-free tunnels restrict traditional technologies, while wheel slippage-induced non-Gaussian noise and geometric-degraded tunnel localization failures further reduce accuracy—issues existing methods cannot address simultaneously. To resolve these bottlenecks, this study develops a scenario-adapted, self-correcting positioning system for underground autonomous vehicles, fusing multi-source onboard sensor data to suppress slip noise and ensure feature-deficient environment robustness. We propose a three-stage cascaded filtering system: it first fuses LiDAR, IMU, wheel speed, and steering angle data for a self-contained framework, then adds two dedicated modules for core challenges. For wheel slippage noise, an anti-slip prior estimation algorithm integrates kinematic models with IMU data, plus a low-adhesion mine surface-tailored slip compensation mechanism to ensure reliable state estimation and eliminate slip deviations. For geometrically degraded tunnel failures, an anti-degradation algorithm uses point cloud degradation-derived regularization constraints and regularized Kalman filtering to enable stable positioning updates. Experiments show that the system achieves sub-meter accuracy and full-area coverage underground, with improved performance under severe wheel slip and in feature-deprived zones. This work fills the gap in high-reliability, self-contained localization for kilometer-scale underground mining vehicles and provides a safety-oriented paradigm for autonomous vehicle scaling, aligning with critical scenario driving safety demands. Full article

This work presents a study on the fabrication of polymethyl methacrylate (PMMA) coatings on NiTi alloys using the spin-coating technique, combining numerical simulation with COMSOL Multiphysics 6.3 and experimental validation. This study provides a numerical framework and parametric study of a COMSOL-based simulation framework for estimating the PMMA coating thickness during the spin-coating process. We present an axisymmetric numerical framework, consistent with classical analytical trends; we provide parametric maps (viscosity, rpm, volume) to delimit thickness ranges (e.g., 100–300 μm). Limitations with no experimental validation are included and evaporation is not modeled; therefore, the figures are indicative estimates. The spin-coating parameters, such as the rotation speed, internal pressure, viscosity of the PMMA solution, and initial volume of the polymer solution, are considered important factors for the simulation process. The coating parameters determine the thickness of the coating layer achieved during the process of spin coating. The 2D axisymmetric flow considers internal factors of a surface tension of 0.07 N·m, a contact angle of 90°, and a density of 1150 kg/m³ for the coating process without evaporation effects. The moving mesh (coating layer) is considered a free surface without any slip boundary with the substrate surface. The coating thickness was determined by various rotations and dynamic viscosities, using a simulation method. The experimental findings and simulation output of the coating thickness as a function of various dynamic viscosities and rotations match well. The final coating thickness ranged from 100 to 300 μm, depending on a viscosity of 11 mPa·s and 100, 500 rpm. Full article

Tailings dams are unique structures due to the materials they store and the methods applied in their construction, often resulting in complex three-dimensional (3D) problems. Most current slope-stability analyses neglect the 3D effects without significant consequences. However, certain conditions, such as the valley shape, the spatial variability of the tailings’ resistance, and the presence of internal dikes, may render the 2D simplification inadequate. For translational slides, the sliding-mass width-to-height ratio (W/H) is a reliable estimator of the 3D effects. However, it is unclear whether this geometric ratio is the most suitable for rotational slides, where the width of the sliding mass varies along its height. This paper presents a parametric study of the 3D effects of the dam’s height (H_M) and the valley shape, namely the abutments’ slope angle with the horizontal (β) and the thalweg width (L_M), on the overall stability of a tailings dam raised by the upstream method, by means of 2D and 3D Limit Equilibrium (LE) analyses. The study evaluates the dam stability using a straightforward and practical methodology, specifically the FS_3D to FS_2D ratio (R_3D/2D), to compare the results of the 3D and 2D analyses, adapting current state-of-the-art techniques originally for translational slides, focused on pre-defined, closed-form slip-surface geometry, to rotational ones where the main focus is the geometry of the whole structure as a physical constraint for the sliding mass. The results show that the model average width-to-height ratio (W_M,avr/H_M), developed in this study, may be a better estimator of the 3D effects for rotational slides than the W/H ratio. Full article