Search Results (582)

The valve serves as the actuating component within the valve mechanism. Under braking conditions, the valve is prone to swaying, which significantly compromises the reliability and service life of the engine. Hence, this paper focuses on researching the deviation characteristics of engine valves. Through a three-dimensional numerical simulation, we analyze the flow field around the valve in the instantaneous states. Our research has revealed that the flow surrounding the valve exhibits a complex multi-vortex structure. Specifically, we observed the evolution pattern of the asymmetric multi-vortex flow along the valve axis within three distinct zones: the asymmetry increase zone, the symmetric development zone, and the asymmetry re-increase zone. The asymmetry increase zone and the asymmetry re-increase zone are located in the curved section and the cylindrical body of the valve, respectively. These zones are the primary contributors to the lateral force acting on the valve, which in turn induces deviation. Based on these analysis results, further research must be conducted on the dynamic characteristics of the flow during valve movement and on optimizing the valve structure through flow control strategies. Full article

This paper studies a MuJoCo-based locomotion framework that couples an adaptive-frequency central pattern generator (AFCO-CPG) with single rigid-body dynamics model predictive control (MPC) for the RENS Q1 quadruped with elastic parallel knee joints. AFCO-CPG combines multi-scale phase coordination, saturated phase correction, and load-gated feedback, while MPC supplies feasible ground-reaction forces and returns load cues to the timing layer. In MuJoCo, the controller achieves stable diagonal-trot speed tracking from 0.4 to 1.2 m/s and recovers from short external pushes. A matched elastic-versus-rigid timing sweep shows a favorable flat-ground parameter band around $\omega =1.8$ Hz, with a best-case cost-of-transport reduction of 12.83% for the elastic model under identical controller gains. A flat-to-slope ascent case further verifies that AFCO timing is modulated when load conditions change. Ablation across nine controller variants shows that multi-scale coordination is the dominant component, causing a 135% increase in phase error and a 536% increase in recovery time when removed. A reduced-order early/late-contact benchmark further confirms faster re-locking than diagonal-only and minimal variants. The results support the value of combining neural timing, predictive force optimization, and compliant-leg feedback in high-fidelity simulation, while hardware validation remains future work. Full article

Unlike traditional marine floating platforms, floating offshore wind turbines (FOWTs) are subjected to larger overturning moments. This study presents a novel floating offshore wind turbine concept—termed the Multi-Body Anti-Pitching Floating Wind Turbine (MAFWT)—designed to mitigate excessive pitching motion of semi-submersible FOWTs. The MAFWT integrates three Wave-star-like appendages arranged in the UMaine VolturnUS-S platform. A fully coupled dynamic model is developed within the FAST-to-AQWA (F2A) simulation framework. Parametric time- and frequency-domain analyses are subsequently conducted under both regular wave/steady wind and irregular wave/turbulent wind conditions to investigate the influence of stiffness parameter K and damping parameter B on system dynamics. Results demonstrate that increasing stiffness enhances the restoring moment, thereby reducing the static pitching offset and overall dynamic response (with the maximum and average values decreasing by 27.6% and 31.9%, respectively). However, it may amplify low-frequency slow-drift motions (with the maximum and average values of surge increasing by 9.4% and 9.5%, respectively). In contrast, damping primarily dissipates kinetic energy, yielding up to a 25.5% reduction in pitch angular velocity and significantly mitigating power output fluctuations (the standard deviation decreased by 16.4%). Furthermore, increases in the stiffness coefficient and damping coefficient result in respective slight increments of 0.12% and 0.18% in the average power output. This work elucidates the distinct physical mechanisms through which stiffness and damping govern pitch suppression. Full article

This paper investigates the stability of telehandlers operating on inclined terrain through a sequential methodological approach. In a first stage, stability is assessed using quasi-static methods based on force and moment equilibrium, including the load transfer matrix and the stability pyramid. These approaches account for gravitational and inertial effects through equivalent external forces and moments applied at the global centre of gravity, enabling efficient evaluation of load redistribution and proximity to rollover thresholds under generalized quasi-static conditions. The application of these methods highlights intrinsic limitations when addressing structurally complex machines such as telehandlers equipped with a pivoting rear axle and evolving mass distribution due to boom motion. In particular, quasi-static approaches require a priori assumptions regarding the effective rollover axis and cannot fully capture the coupled geometric and contact interactions between rear axle articulation limits, centre of gravity migration, tyre–ground interface behaviour, and support polygon evolution. To overcome these limitations, a nonlinear dynamic multibody model based on the three-dimensional Bond Graph (3D Bond Graph) methodology is introduced. The model is implemented within a virtual tilt–rotation test platform and validated against experimental results obtained from ISO 22915-14 stability tests. The comparison confirms compliance with normative requirements and demonstrates that the dynamic framework captures condition-dependent rollover mechanisms and transitions between distinct virtual rollover axes that cannot be fully explained by quasi-static formulations. Unlike most previous studies, which focus on fixed configurations or forward-driving scenarios, the proposed framework analyzes stability evolution under spatial inclination while accounting for structural articulation constraints. The explicit identification of rollover axis transitions induced by rear axle articulation provides a deeper mechanistic interpretation of telehandler stability and supports the use of high-fidelity dynamic simulation as a complementary tool for test interpretation, experimental planning, and the development of predictive stability and operator assistance systems. Full article

Mitigating heat stress in high-density historical districts remains a critical challenge in urban renewal due to complex morphological heterogeneity. Existing research often relies on isolated intervention measures, lacking systematic, multi-strategy assessments driven by high-precision spatial data. This study addresses this gap by establishing a quantitative framework that couples thermal infrared remote sensing with Computational Fluid Dynamics (CFD) to optimize microclimate responses in Beijing’s Liulichang Historic District. Remote sensing data were utilized to retrieve high-resolution Land Surface Temperature (LST), providing accurate thermal boundary conditions for micro-scale wind-thermal simulations. A baseline scenario (S0) and seven renewal strategies (S1–S7)—integrating varying configurations of greenery, water bodies, and permeable pavements—were evaluated using pedestrian-level comfort indices. Results reveal that single-factor interventions yield marginal improvements or thermodynamic trade-offs; specifically, adding greenery (S1) in narrow street canyons increased aerodynamic roughness, thereby obstructing ventilation and inducing localized warming. Conversely, composite strategies significantly enhanced microclimatic quality. The “greenery-water-permeable pavement” strategy (S4) achieved optimal synergistic effects, characterized by substantial cooling and spatial homogenization. Regression analysis identified water bodies as the dominant cooling driver, where a 10% increase in water coverage resulted in a temperature reduction of approximately 5.17 °C. Conversely, greenery alone showed no statistically significant cooling contribution (p > 0.05) without the synergistic presence of water or pavement modifications. This research suggests that urban renewal in high-temperature zones (>36 °C) should prioritize composite cooling networks. Furthermore, vegetation layouts near wind corridors must be precisely regulated to prevent ventilation degradation. These findings provide a scientific basis for the climate-adaptive sustainable regeneration of culturally significant, high-density urban blocks. Full article

Urban rail wheels endure prolonged exposure to frequent starts and stops, heavy cyclic loads, and complex track conditions, which often lead to premature failure modes such as wear, fatigue cracking, and corrosion in conventional wheel materials. These limitations restrict their ability to meet the evolving demands of modern rail systems for enhanced durability and performance. To address this, the present study uses laser cladding to deposit high-entropy alloy coatings with systematically varied aluminium content onto wheel substrates. The study compares phase composition, microstructure, and mechanical properties across the different coatings. Results show that increasing Al content transforms the coating microstructure from a single face-centred cubic (FCC) phase to a dual-phase structure of FCC and body-centred cubic (BCC) phases, accompanied by notable grain refinement. Among the variants, the CrMnFeCoNi(Al)₈ coating has the densest microstructure and the most favourable mechanical performance. It achieves a microhardness of 399.62 HV_0.5 in the as-clad state and 450 ± 5 HV_0.5 after heat treatment, representing an increase of approximately 12.6%. This coating also demonstrates improved corrosion resistance, with an open-circuit potential 0.07 V higher than the CL60 substrate. Multi-body dynamics simulations confirm that the clad wheels maintain excellent operational stability and safety under service conditions. Full article

In structured orchard environments, harvesting robots operate where rigid bodies (e.g., trunks, poles, and wires) coexist with flexible foliage. Strict avoidance of all obstacles significantly compromises operational efficiency. To address this, this study proposes an end-to-end autonomous harvesting framework characterized by an “avoid-rigid, push-through-soft” strategy. This framework explicitly propagates uncertainties from sensor data and reconstruction processes into the planning and policy phases. First, a multi-task perception network acquires 2D semantic masks of fruits and branches. Class probabilities and instance IDs are back-projected onto a 3D Gaussian Splatting (3DGS) representation to construct a decision-oriented, semantically enhanced 3D scene model. The policy network accepts multi-channel 3DGS rendered observations and proprioceptive states as inputs, outputting a continuous preference vector over eight predefined motion primitives. This approach unifies path planning and action decision-making within a single closed loop. Additionally, a dynamic action shielding module was designed to perform look-ahead collision risk assessments on candidate discrete actions. By employing an action mask to block actions potentially colliding with rigid obstacles, high-risk behaviors are effectively suppressed during both training and execution, thereby enhancing the robustness and reliability of robotic manipulation. The proposed method was validated in both simulation and real-world scenarios. In complex orchard scenarios, the proposed AE-TD3 algorithm achieves a harvesting success rate of 77.1%, outperforming existing RRT (53.3%), DQN (60.9%), and TD3 (63.8%) methods. Furthermore, the method demonstrates superior safety and real-time performance, with a collision rate reduced to 16.2% and an average operation time of only 12.4 s. Results indicate that the framework effectively supports efficient harvesting operations while ensuring safety. Full article

Contemporary physiotherapy requires technological tools to provide effective therapy to the increasing group of patients with neurological conditions, among others. This can be achieved with rehabilitation robots, which can also be exoskeletons—wearable devices that mobilize multiple joints with complex motions representing activities of daily living. To perform kinesiotherapy conveniently in home-like environments, the exoskeletons need to be relatively lightweight. The paper presents the methodology for decreasing the mass of the exoskeleton design with real-life data-driven simulations of motions, followed by multibody dynamics simulations, and finite element method (FEM) multistep optimization. The process includes sequential initial parametric optimization, topology optimization, and final parametric optimization. The steps are used to set initial dimensional and material parameters, extract new geometrical features, and adjust the final geometry dimensions of a new design. The presented case of the SmartEx-Home exoskeleton resulted in a total mass reduction of almost 50% for the main construction elements while meeting the criteria of the minimum safety factor and maximum internal stress and strain for all components. The final design was manufactured and tested with humans, reflecting an almost fully automatic passive and active therapy. Full article

Background: Pumping in Laser-class sailing is a dynamic propulsion technique used in marginal wind conditions and characterized by repetitive, coordinated oscillations of the sailor–sail system. Despite its practical relevance, its biomechanical and ergonomic demands remain insufficiently characterized. Methods: A mixed-methods framework was applied combining questionnaire data, kinematic analysis, ergonomic assessment, and musculoskeletal modelling. Thirty-six competitive Laser sailors completed a Borg CR-10-based questionnaire on perceived discomfort/fatigue across body regions at predefined time points (during pumping, immediately after training, and the following day). A controlled land-based multi-angle video acquisition was used to reconstruct a standardized pumping posture and parameterize a digital human model in DELMIA^® for postural/kinematic analysis. Ergonomic risk was assessed using REBA, and muscle activity was estimated using the AnyBody^® Modeling System (simulation-derived normalized muscle activity across 129 muscles). Results: the simulation identified high neuromuscular demand in the trunk and shoulder complex, with several deep trunk stabilizers and the left latissimus dorsi reaching 100% modeled normalized muscle activity. Marked lateral asymmetry was observed, with right-sided trunk dominance and left-sided shoulder dominance. Kinematic analysis showed substantial joint excursions, with large lumbar motion amplitudes, while REBA yielded a score of 11 (Very-High Risk). Questionnaire data indicated a high prevalence of pumping-related musculoskeletal discomfort (72.2%), most frequently involving the lower back, shoulders, and knees. A dissociation was observed between modeled muscle activity and perceived fatigue, with the lower limbs rated as most fatigued despite lower modeled activation than the trunk. Conclusions: Findings identify the deep trunk stabilizers, latissimus dorsi, and lower extremities as key regions involved in pumping, with marked lateral asymmetry and high ergonomic risk. They support targeted training, injury-prevention, and ergonomic strategies to improve performance and reduce injury risk in competitive sailing. Full article

This study developed a biomimetic jumping robot inspired by frogs to enhance its obstacle-crossing capabilities. The biological principles underlying the jumping biomechanics of frog hindlimbs were integrated into the robotic mechanism; quantitative analysis of the bionic structure and its jumping performance not only provides mechanical engineering insights for investigating frog locomotion mechanics but also offers practical design references for the development of biomimetic mobile robots. Through theoretical calculations and application scenario analysis, a six-bar linkage mechanism was designed to simulate the force generation of frog hindlimbs, with tension springs mimicking the elastic energy storage function of the semimembranosus and gastrocnemius muscles. A reducer was integrated into the trunk to enable energy storage, and an adjustable single-hinge structure was adopted for the forelegs to realize take-off angle adjustment and shock absorption. Finite element simulations were conducted to validate the load-bearing capacity and strength of critical components. Multi-body dynamics and the particle swarm optimization (PSO) algorithm were employed to explore the relationship between input parameters and output performance metrics (jumping height and jumping distance), while orthogonal experimental analysis was used for comprehensive parameter evaluation. Finally, a physical prototype was fabricated, and its performance parameters were tested. The prototype has a mass of 150 g, generates a ground push force of 50 N, attains a jumping height of 380 mm, and achieves a maximum jumping distance of 500 mm. This study establishes a biologically inspired working principle for jumping robots and provides a novel practical prototype for research into biomimetic mobile robots. Full article

This paper proposes a novel and efficient mesostructure generation framework integrating stochastic geometry with physically based packing. First, a random radius field (RRF) method is developed, utilizing multi-scale noise superposition and topology optimization to generate 3D aggregates with realistic and controllable morphologies. Second, a packing strategy based on Rigid Body Dynamics (RBD) is developed to simulate the physical casting process including gravity falling and vibration, achieving high-density aggregate skeletons. The framework is validated through the generation of a multi-phase mesostructure and the fracture simulation of recycled aggregate concrete (RAC). The simulation results successfully reproduced the crack propagation patterns and damage evolution paths associated with different aggregate shapes. These findings confirm the capacity and effectiveness of the proposed framework as a robust tool for the mesoscopic modeling of heterogeneous concrete materials. Full article

Traditional passive hydraulic dampers face the challenges of extended design cycles, inefficient parameter matching, and fixed performance, limiting their adaptability. This paper proposes an integrated solution that combines inverse parametric design with active, continuously adjustable damping. First, a high-fidelity nonlinear model is developed based on valve plate elasticity and multi-valve coupling dynamics, achieving a simulation error of ≤4%. An improved genetic algorithm is then designed to inversely optimize five key parameters. This optimization reduces the deviation between the prototype’s damping force–velocity characteristics and the target curve to ≤3% and shortens the design cycle by approximately 40%. Building on this foundation, a pilot-operated electro-hydraulic proportional relief valve is integrated to enable continuous damping adjustment. Co-simulation using AMESim2404 and MatlabSimulinkR2022 reveals the influence of solenoid valve parameters on damping characteristics and calibrates the current–damping force mapping. A co-simulation of a skyhook-controlled quarter-vehicle model demonstrates that the semi-active suspension system reduces the root mean square (RMS) of vertical body acceleration by 21.7%, indicating a significant theoretical improvement in ride comfort. This study establishes a complete technical pathway of “modeling → inverse optimization → integration → verification,” providing an efficient and viable core component solution for intelligent suspension systems. Full article

This paper investigates the influence of rolling resistance on fuel consumption in Class 8 heavy-duty vehicles, with a focus on a modeling approach through variations in the rolling resistance coefficient ($C_{rr}$) across different driving scenarios. Leveraging TruckSim’s multibody modeling approach for vehicle dynamics and MATLAB/Simulink co-simulation capability, the study provides insights into how tire rolling resistance affects energy efficiency under varying conditions while enabling controlled, repeatable comparisons across various scenarios. Results show that across the evaluated scenarios, increases in $C_{rr}$ impact the vehicle’s speed, fuel consumption, engine torque, and crankshaft spin. Specifically, increasing $C_{rr}$ from 0.004 to 0.013 was found to lead up to 68% higher fuel consumption in high demand scenarios. These findings aim to guide efforts to optimize tire design and vehicle performance that help achieve improved fuel efficiency. Full article

Aiming at the challenge of simultaneously controlling ride comfort and wheel grounding performance for mining dump trucks, this paper proposes a multi-dimensional synergistic optimization control (MDSOC) strategy based on model predictive control (MPC) for active hydro-pneumatic suspension. First, an accurate hydro-pneumatic suspension and hinged mining truck full-vehicle-dynamics model is established, and the model accuracy is validated through actual vehicle testing. Subsequently, an MDSOC-MPC for active hydro-pneumatic suspension is constructed to minimize the mean square root of the three-axis acceleration of the body, pitch angle, roll angle, and wheel dynamic tire load. Comparative analysis is performed with traditional single-MPC longitudinal, lateral, and vertical control, and the simulation results showed: under emergency braking conditions, the root mean square (RMS) value of the pitch angle is reduced by 18.2%; under single and double-shift conditions, the RMS values of the roll angle are reduced by 40.4% and 30%, respectively; under D-class random road, the RMS values of the longitudinal, lateral, and vertical body acceleration are significantly reduced by 22%, 21.5%, and 21.2%, respectively, while the RMS values of pitch angle and roll angle are reduced by 22.5%, and 20.2%, respectively, systematically improving riding comfort, vehicle wheel contact, and driving safety. This study provides a theoretical basis and feasible engineering methods for the active control of hydro-pneumatic suspension systems in heavy engineering vehicles. Full article

To address performance degradation and control instability in electro-hydraulic servo active suspension systems due to internal leakage faults arising from wear and aging of hydraulic components, this paper proposes an innovative fuzzy PID fault-tolerant controller based on the Improved Giant Armadillo Optimization (IGAO) algorithm. Specifically, to overcome the limitations of the standard Giant Armadillo Optimization (GAO), which is prone to local optima and exhibits poor convergence performance when handling multi-constraint parameter optimization problems, this study introduces a nonlinear dynamic inertia weight mechanism and a random reflection strategy for out-of-bounds particles to improve the original algorithm’s performance. These enhancements significantly enhance its ability to balance global exploration and local exploitation. Furthermore, this research develops a comprehensive performance evaluation fitness function by quantifying key performance indicators such as body acceleration, suspension dynamic deflection, and tire dynamic load. A quarter-car model incorporating an internal leakage fault was established as a simulation validation platform to demonstrate the reliability of the proposed method. Simulation results indicate that under various road excitation conditions, the proposed IGAO algorithm can rapidly and stably converge to superior parameters for the fuzzy PID controller. Compared to the Particle Swarm Optimization (PSO) and standard GAO algorithm, the control system optimized by IGAO not only significantly more effectively suppresses body vibration and reduces shock amplitude but also exhibits stronger dynamic recovery performance and control robustness under varying degrees of internal leakage faults. This research provides a robust control approach for addressing internal parameter uncertainties in hydraulic systems and offers a new approach to theoretical modeling for enhancing the reliability of design and fault-tolerant control capabilities of active suspension systems. Full article