Search Results (73)

The foot structure plays a decisive role in the trafficability of legged robots on granular media. Traditional foot-ends (spherical, cylindrical, flat-bottomed) are prone to sinkage and slippage, resulting in unstable locomotion. To solve this problem, a novel bionic-inspired reconfigurable foot with active opening and closing adjustment capability is designed based on bionics, combining the stable phalangeal contour of goat hoof capsules and the high-adhesion feature of beetle foot-end spines. A coupled EDEM–Adams simulation model is established, and physical experiments combined with simulation inversion are used to calibrate contact parameters between particles and between particles and the foot, including the coefficient of restitution, static friction and rolling friction. A high-fidelity numerical platform for foot–ground dynamic interaction is thus constructed. By comparing and analyzing the differences in anti-sinkage and traction performance between the bionic-inspired foot and traditional foot-ends, this study systematically revealed the influence law of bionic morphology on the mechanical behavior of the foot, and clarified the intrinsic mechanism through which bionic design improves foot–ground interaction. The results demonstrate that the spine structures of the bionic-inspired foot reshape the mechanical constitutive relationship of granular media. By expanding the ground contact area and optimizing contact pressure distribution, the maximum reduction in foot sinkage depth reaches 70.11%, and the traction coefficient is increased by up to 37.13%. Full article

Ship transit in vertical ship lift chambers represents a highly confined flow regime characterized by extreme blockage (N < 2), where ship-induced piston effects can significantly influence navigational safety and structural loads. This study presents an experimental investigation of the unsteady hydrodynamic responses of a 1000 t class ship operating in the Baise vertical ship lift. A 1:10 large-scale physical model was constructed to reproduce the ship lift chamber and auxiliary lock geometry under Froude similarity. Tests were conducted for prototype water depths of 3.7–3.9 m and sailing velocities between 0.4 and 1.1 m/s. Ship sinkage, free-surface oscillations, and dynamic chamber weight variations were synchronously measured. Results revealed a profound process asymmetry: the exit maneuver induced significantly higher sinkage (0.92 m at 1.1 m/s) and chamber weight fluctuations (810 t) than the entry process due to restricted return flow replenishment. A non-dimensional predictive P–K relationship was derived with a regression coefficient α = 1.9121. Based on safety margins and mechanical load limits, critical speed thresholds were established at 0.6 m/s for exit and 0.7 m/s for entry to ensure a minimum safety clearance of 0.48 m even under docking error conditions. Full article

This study investigates the hydrodynamic performance of the KVLCC2 tanker in deep and shallow water using computational fluid dynamics (CFD) simulations, focusing on resistance and self-propulsion with both ducted and non-ducted propellers. The Reynolds-averaged Navier–Stokes (RANS) equations, coupled with the SST k-ω turbulence model, are solved using STAR-CCM+ to analyze ship resistance, open-water propeller characteristics, and self-propulsion factors. Validation against experimental data confirms the numerical accuracy, with uncertainties below acceptable thresholds. In deep water, the body force propeller and body force ducted propeller methods are validated against the discretized propeller approach, yielding errors under 5%. The ducted propeller enhances open-water efficiency but results in higher thrust deduction and lower wake fractions, leading to reduced hull and overall propulsive efficiencies compared to the non-ducted case. In shallow water, as the depth-to-draft ratio (H/T) decreases to 1.5, added resistance, sinkage, and trim increase sharply due to blockage effects. The ducted configuration mitigates these penalties, achieving a 20.8% power reduction at H/T = 1.5. Added self-propulsion factors reveal that the duct improves hull efficiency and offsets shallow-water losses, enhancing propulsive efficiency. Flow field analysis shows accelerated stern wakes and asymmetric structures in shallow water, with the body force methods providing consistent predictions despite minor discrepancies in extreme conditions. This research highlights the efficacy of ducted propellers in shallow water and the reliability of body force methods for efficient simulations, offering insights for ship design in restricted depths. Full article

Classical soil mechanics models are inadequate for predicting the traction of wheeled vehicles under high-velocity off-road conditions due to the complex dynamic soil response. To address this, this study proposes a velocity-segmented dynamic compression-shear model for aeolian sandy soil, enhancing classical theories with velocity-dependent corrections for the 0–10 m/s range. A theoretical patterned wheel–soil interaction model is developed, incorporating lug effects via an equivalent radius. Furthermore, a comprehensive vehicle traction model is established by integrating the soil model with a dynamic equilibrium iteration method that couples suspension dynamics, pitch attitude, and axle load distribution. Validation results demonstrate that the single-wheel traction theoretical model achieves an error of less than 18%, while the full vehicle traction model reaches a 73% prediction accuracy for drawbar pull and sinkage, as verified through soil bin tests and full-vehicle experiments. This research provides theoretical framework for the real-time and accurate prediction of wheeled-vehicle traction performance on unprepared terrain, offering significant improvements for high-velocity off-road mobility analysis. Full article

This study examines the confined compression behavior of soils with varying clay content under controlled boundary conditions. A carefully designed experimental setup was utilized, maintaining constant parameters including the soil thickness-to-plate diameter ratio (H/D), initial bulk density (ρ), and plate diameter (D). This controlled framework enabled the isolated investigation of the effects of clay content on soil compression behavior. A systematic range of soil textures, characterized by increasing clay content, was tested to observe trends and establish relationships between clay content and confined compression response. The evaluation involved the calculation of key parameters relevant to terrain–vehicle systems, such as the load-bearing capacity factor (k) and vertical soil pressure (p). By analyzing the variation in these parameters in relation to clay content, the study aims to clarify how clay proportion and associated soil characteristics, such as plasticity and cohesion, affect load-bearing capacity under confined conditions. Furthermore, the influence of moisture content on the load-bearing capacity factor was investigated within the same boundary conditions, providing additional insight into the interaction between moisture, clay content, and soil strength. The findings of this research will enhance the understanding of soil mechanical behavior under confined compression, with particular relevance to terrain–vehicle interactions and the optimization of off-road mobility. Full article

AgriRover was developed to address key operational constraints faced by smallholder vineyards in Peru, including sandy and saline soils, labor shortages, and limited access to advanced agricultural machinery. The platform features an articulated, all-wheel-drive chassis designed to ensure mobility and stability on loose terrain while minimizing soil compaction. This study presents the simulation-driven development of a digital pre-twin, conceived as a virtual prototype prepared for future sensor integration but currently operating without real-time data feedback. The pre-twin was implemented in MATLAB/Simulink (vers. 2024b) using a multibody dynamics model and evaluated through eight scenario-based simulations, varying field geometry, soil type, and slope conditions. The results show stable operation on slopes up to 10°, wheel sinkage values ranging between approximately 20 and 45 mm depending on terrain conditions, and a moderate battery state-of-charge reduction across most scenarios, with higher power demand observed on sandy soils. A scenario-based comparison indicates a potential reduction of approximately 50% in total monitoring time relative to manual field scouting, while advanced sensing, autonomous navigation, and AI-based analytics remain part of future developments. The current pre-twin provides a validated, low-cost foundation for context-specific phenological monitoring and early-stage precision agriculture applications in developing regions. Full article

Off-road vehicle control designs often neglect the complex tire–soil interactions inherent to soft terrain. This paper proposes a Variable Impedance Control (VIC) strategy integrated with a high-fidelity terramechanics model. First, a real-time sinkage estimation algorithm is derived using experimentally identified Bekker parameters and the quasi-rigid wheel assumption to capture the nonlinear feedback between soil deformation and vehicle dynamics. Building on this, the VIC strategy adaptively regulates virtual stiffness, damping, and inertia parameters based on real-time suspension states. Comparative simulations on an ISO Class-C soft soil profile demonstrate that this framework effectively balances ride comfort and safety constraints. Specifically, the VIC strategy reduces the root-mean-square of vertical body acceleration by 46.9% compared to the passive baseline, significantly outperforming the Linear Quadratic Regulator (LQR). Furthermore, it achieves a 48.6% reduction in average power relative to LQR while maintaining suspension deflection strictly within the safe range. Moreover, unlike LQR, the VIC strategy improves tire deflection performance, ensuring superior ground adhesion. These results validate the method’s robustness and energy efficiency for off-road applications. Full article

Accurate numerical simulations of soil-tire interactions are essential for optimizing agricultural machinery to minimize soil compaction and enhance crop yield. This study developed and compared two approaches for identifying and validating parameters of a LS-Dyna soil model. The laboratory-based approach derives parameters from triaxial, consolidation, and cone penetrometer tests (CPT), while the optimization-based method refines them using in-situ CPT data via LS-OPT to better capture field variability. Simulations employing Multi-Material Arbitrary Lagrangian–Eulerian (MM-ALE), Smoothed Particle Hydrodynamics (SPH), and Hybrid-SPH methods demonstrate that Hybrid-SPH achieves the optimal balance of accuracy (2% error post-optimization) and efficiency (14-h runtime vs. 22 h for SPH). Optimized parameters improve soil–tire interaction predictions, including net traction and tire sinkage across slip ratios from −10% to 30% (e.g., sinkage of 12.5 mm vs. 11.1 mm experimental at 30% slip, with overall mean-absolute percentage error (MAPE) reduced to 3.5% for sinkage and 4.2% for traction) and rut profiles, outperforming lab-derived values. This framework highlights the value of field-calibrated optimization for sustainable agriculture, offering a cost-effective alternative to field trials for designing low-compaction equipment and reducing yield losses from soil degradation. While sandy loam soil at 0.4% moisture content was used in this study, future extensions to different soil types with varied moisture are recommended. Full article

In order to tackle the issues of poor mobility and unstable traction of electric vehicles on sandy landscapes, this research develops a high-accuracy numerical model for wheel–sand interaction relying on the Discrete Element Method (DEM). An innovative parameter calibration procedure is proposed herein, which optimizes the sand contact parameters. This reduces the error between the simulated and measured angles of repose to merely 1.2% and substantially improves the model’s reliability. The model was then used to systematically compare the performance of a 205/55 R16 slick tire with a treaded tire on sand. Simulations demonstrate that at a 30% slip ratio, the treaded tire exhibited significantly higher traction and greater sinkage than the slick tire. This indicates that tread patterns enhance traction mechanically by increasing the contact area and promoting shear deformation of the sand. The trends of traction with slip ratio and the corresponding sand flow patterns showed excellent agreement with experimental observations, which validated the simulation approach. This research provides an efficient and accurate tool for evaluating tire-sand interaction, providing critical support for the design and control of electric vehicles on complex terrains. Full article

To address the limited adaptability of traditional fixed-parameter strategies for hexapod robots operating in multi-material terrain environments, this study proposes a terrain-aware gait optimization method based on an improved particle swarm optimization algorithm that incorporates foot-end sinking perception. This method establishes a ground sinking detection mechanism based on foot-end position sensors, constructs a dynamic weight allocation strategy based on ground bearing capacity, and develops a Terrain-aware Ground Particle Swarm Optimization algorithm (TGPSO) that integrates Latin hypercube sampling, linearly decreasing inertia weights, and stagnation exploration mechanisms. Furthermore, it establishes a unified terrain-based reward function framework to achieve dynamic adjustment of weights for velocity, stability, and transportation efficiency. Simulink simulation verification demonstrates that TGPSO achieves superior optimization performance compared to traditional strategies across three typical terrain types, while exhibiting faster convergence speed and enhanced stability. The research findings provide theoretical foundations and technical support for intelligent motion control of hexapod robots across varying material properties, achieving targeted optimization of locomotion performance under diverse terrain conditions. Full article

The interaction between tires and snow layer is fundamental for vehicle safety on snowy roads. Due to the instantaneous high torque output characteristics of electric vehicles, they are more prone to slipping when driving in snow, which exacerbates the complexity of tire–snow interaction. In order to construct a more accurate tire–snow interaction model in Northern China, the Bekker formula is introduced to establish the snow pressure–sinkage relationship formula, and the parameters are calibrated by disk experiments. Then the improved tire–snow interaction model is proposed by combining the use of the brush model on the rigid road surface and the dynamic discussion of the tire’s motion behavior on the snow. A coupled finite element (FE) tire model and discrete element (DE) snow terrain model are established, with interactions governed by snow–rubber contact mechanics. The simulation tests the sinking depth of tires on snowy road surface under different slip rates and different loads, as well as the force on tires. The model provides high-precision input to the EV snow traction control algorithm to optimize motor torque distribution to improve energy efficiency. By comparing and analyzing with theoretical values, the traditional empirical model, and the modified physical model, it is finally concluded that the modified model has better reliability than the original model. Compared with the empirical model, the improved model reduces the vertical stress prediction error from 5% to less than 1%, and the motion resistance error from 6% to approximately 2%, providing high-precision input for the snow traction control of electric vehicles. Full article

This study investigates the dynamic performance of mountainous crawler tractors during small-radius slope steering, providing theoretical support for power machinery design in hilly and mountainous regions. Addressing the mechanization demands in complex terrains and existing research gaps, a steering dynamics model is established. The model incorporates an amplitude-varied multi-peak cosine ground pressure distribution, employs position vectors and rotation matrices to characterize 3D pose variations in the tractor’s center of mass, and integrates slope angle, soil parameters, vehicle geometry, center-of-mass shift, bulldozing resistance, and sinkage resistance via d’Alembert’s principle. Numerical simulations using Maple 2024 analyzed variations in longitudinal offset of the instantaneous steering center, bilateral track traction forces, and bulldozing resistance with slope, speed, and acceleration. Variable-gradient steering tests on the “Soil-Machine-Crop” Comprehensive Experimental Platform demonstrated model accuracy, with <8% mean error and <12% maximum relative error between predicted and measured track forces. This research establishes a theoretical foundation for predicting, evaluating, and controlling the steering performance/stability of crawler tractors in complex slope conditions. Full article

This study focuses on optimizing track and grouser structural parameters to enhance UATV drawbar pull, particularly under soft soil conditions. A numerical soil thrust model for single-track shoes was developed based on track–soil interaction mechanics, revealing distinct mechanistic roles: track structural parameters (length/width) govern pressure–sinkage relationships at the track base, while grouser structural parameters (height, spacing, V-shaped angle) dominate shear stress–displacement dynamics on grouser shear planes. A novel DEM-MBD coupling simulation framework was established through soil parameter calibration and multi-body dynamics modeling, demonstrating that soil thrust increases with grouser height and V-shaped angle, but decreases with spacing, with grouser height exhibiting the highest sensitivity. A soil bin test validated the numerical model’s accuracy and the coupling method’s efficacy. Parametric optimization via the Whale Optimization Algorithm (WOA) achieved a 55.86% increase in drawbar pull, 40.38% reduction in ground contact pressure and 57.33% improvement in maximum gradability. These advancements substantially improve the tractive performance of UATVs in soft beach terrains. The proposed methodology provides a systematic framework for amphibious vehicle design, integrating numerical modeling, high-fidelity simulation, and experimental validation. Full article

Waterborne transportation serves as a critical pillar of trunk-line freight systems, offering unparalleled advantages in transport capacity, energy efficiency, and cost-effectiveness. As cargo throughput demands escalate, optimizing lock capacity becomes imperative. This study investigates ship sinkage dynamics through computational fluid dynamics (CFD) simulations for a representative inland cargo vessel navigating the Three Gorges on the Yangtze River. We develop a predictive sinkage model that integrates four key hydrodynamic parameters: ship velocity, draft, water depth, and bank clearance, applicable to both open shallow water and lockage conditions. The model enables determination of maximum safe drafts for lock transit by analyzing upstream/downstream water levels and corresponding chamber depths. Our results demonstrate the technical feasibility of enhancing single-lock cargo capacity while maintaining safety margins. These findings provide (1) a scientifically grounded framework for draft control optimization, and (2) actionable insights for lock operation management. The study establishes a methodological foundation for balancing navigational safety with growing throughput requirements in constrained waterways. Full article

In this study, a correction procedure for ship mass and its longitudinal location of center of gravity suitable for a simulation environment is proposed in OpenFOAM v6.0. The concept is implemented ensuring static equilibrium and an approximately zero-pitch moment on the ship before the simulation. The viscous flow field around the ship in calm water is simulated using the VOF (Volume of Fluid) free surface two-phase and SST (Shear Stress Transport) k–ω turbulence models. Using static mesh, the resistance error of medium and fine grids is 4%, on average, against the experimental value. As the sinkage and trim are predicted using dynamic mesh, the increasing ship’s resistance causes larger errors, except for the container ship. Through the proposed correction, the ship’s vertical motions are significantly improved, and the resistance error decreases for the dynamic simulation. For the container ship, the error of resistance and motion achieved is less than 1%. The sinkage and trim errors improve tremendously for the tanker and bulk carrier, and the resistance errors are reduced slightly, by less than 3%. In the end, the detailed flow field is analyzed, as well as the ship wave-making pattern and the nominal wake velocity distribution, and these are compared with the measurement data available. The characteristics of the flow phenomena are successfully modeled. The resistance value for each hull form satisfies the requirement of Verification and Validation, and the uncertainty values are estimated. Full article