Search Results (1,287)

Rolling bearings operate under complex contact conditions, and their tribological and dynamic behaviors are highly sensitive to their lubrication performance. Based on previous studies on surface texturing, three types of representative textures (wholly distributed dimples, locally distributed dimples, and grooves) with optimized parameters were fabricated on the shaft washers using the laser marking method. This was done to investigate the synergistic effect of surface textures and polytetrafluoroethylene (PTFE) nano-additives on the tribological and friction-induced vibration performance of cylindrical roller thrust bearings under starved lubrication. Lubricating oils containing various mass fractions (0.5 wt%, 1.0 wt%, and 3.0 wt%) of PTFE nano-additives were prepared and employed. The coefficients of friction (COFs), wear losses, worn morphologies, and time/frequency-domain vibration responses were analyzed. The results show that the appropriate integration of surface textures and solid lubricant additives can establish a highly effective synergy for rolling bearings under starved lubrication. PTFE nano-additives significantly improved the tribological performance of the smooth bearings and those with dimples (both wholly distributed and locally distributed), with the optimal performance observed at a mass fraction of 3.0 wt%. In contrast, the tribological performance of the groove-textured bearings noticeably deteriorated with the addition of PTFE nano-particles, especially at higher mass fractions. The bearing with wholly distributed dimples exhibited the best overall tribological performance at a mass fraction of 3.0 wt%, achieving a 61.8% reduction in the average COF, a 99.6% reduction in wear loss, and significantly suppressed vibration amplitudes. Full article

Air–ground collaborative systems leverage the complementary strengths of unmanned aerial vehicles (UAVs) and unmanned ground vehicles (UGVs) and hold significant potential for logistics in complex, unstructured environments. However, trajectory planning in infrastructure-free mountainous regions remains challenging owing to the need for continuous tight coupling, obstacle avoidance, and reliable communication-link maintenance. To address these challenges, this study proposes a cooperative trajectory planning framework that enforces strict inter-vehicle distance constraints to maintain communication connectivity. By formulating the coordination problem in terms of relative configurations between air and ground vehicles, the proposed framework exhibits translational invariance, reflecting an underlying symmetry with respect to global position shifts. This symmetry-aware formulation reduces reliance on absolute coordinates and promotes consistent cooperative behavior under environmental variability. The trajectory planning problem is mathematically formulated as a constrained multi-objective nonlinear programming (MONLP) model that balances energy consumption and trajectory smoothness. An adaptive inertia weight particle swarm optimization (AIWPSO) algorithm is developed to efficiently solve the resulting optimization problem. Simulation results demonstrate that the proposed approach generates smooth, collision-free trajectories while maintaining stable air–ground coordination, demonstrating improved feasibility and robustness over conventional planning methods in unstructured mountainous environments. Full article

Path planning of mobile robots on grid maps is a complex optimization problem, and applying standard particle swarm optimization (PSO) to this task often leads to stagnation and premature convergence. To address these issues, a particle swarm optimizer enhanced by fluid mechanics and differential evolution (FMDEPSO) is proposed. The method integrates fluid-inspired neighborhood feedback with a differential evolution recombination mechanism to construct a semi-discrete population evolution framework. Specifically, FMDEPSO introduces a pressure repulsion term and a viscous diffusion term to mitigate early population collapse and suppress oscillations caused by abrupt velocity variations. Meanwhile, a gas–liquid phased adaptive scheduling strategy is adopted to dynamically adjust the learning factors, thereby balancing exploration and exploitation. In addition, the mutation–crossover–greedy selection operator of differential evolution (DE) is embedded into the update process to preserve population diversity and enhance the capability of escaping local optima. On the CEC2017 benchmark suite, FMDEPSO achieved the best mean results on 17, 19, and 17 functions under 30-, 50-, and 100-dimensional settings, respectively, compared with eight representative PSO variants. It maintained a top-three ranking on the majority of functions and obtained the overall best average rank according to the Friedman test. The Wilcoxon rank-sum test further confirmed its statistical advantage on most benchmark functions. In grid-based path-planning experiments on multi-scale environments ($20\times 20$, $40\times 40$, and $60\times 60$), FMDEPSO generates smooth and goal-directed feasible trajectories in successful runs and achieves the best overall performance among PSO-based methods while maintaining a favorable balance among path quality, success rate, and runtime across different complexity levels. Overall, the proposed method exhibits stable convergence behavior and competitive solution quality in both numerical benchmark optimization and mobile robot path-planning tasks. Full article

This study proposes a heterogeneous fusion path planning framework for unmanned aerial vehicles (UAVs) operating in complex emergency rescue and civil environments. Existing single-mechanism metaheuristics—including Particle Swarm Optimization (PSO), Ant Colony Optimization (ACO), and Genetic Algorithms (GAs)—suffer from fundamental limitations in three-dimensional kinematic path planning: PSO converges rapidly but stagnates at local optima due to population variance collapse; ACO offers robust local exploitation but incurs prohibitive cold-start overhead; GAs maintain diversity at the cost of expensive crossover operations. To address these complementary deficiencies simultaneously, the proposed framework introduces a spherical coordinate representation that reduces computational complexity and naturally enforces UAV kinematic constraints, combined with adaptive weight factors and a serial PSO-ACO fusion strategy, and subsequently incorporates adaptive weight factors. A serial fusion strategy is then introduced, wherein the sub-optimal trajectory generated by the Spherical PSO phase is mapped into the ACO pheromone field via a Gaussian Kernel Density Mapping (GKDM) mechanism, enabling the ACO phase to perform fine-grained local exploitation within a kinematically feasible corridor. Various constraints along the flight path are formulated into distinct cost functions, which cover aircraft track length, pitch angle variation, altitude difference variation, obstacle avoidance, and smoothness; the core task of the algorithm is to find the flight path with the minimum total cost. The proposed algorithm is dedicated to UAV path planning in complex emergency rescue environments (disaster-stricken areas, hazardous zones) and is further applicable to civil low-altitude logistics delivery, industrial facility inspection, ecological environment monitoring and urban air mobility (UAM) scenarios with complex obstacle constraints. It can effectively improve the safety and efficiency of UAVs in reaching rescue points, delivering emergency supplies, conducting disaster surveys, and completing various civil low-altitude operation tasks. Full article

This study reveals the structure–property relationship between Cu powder characteristics on 6063 Al alloy surface and the interface behavior of cold spray coatings. Through systematic experiments, we examined the effects of different oxygen content in atomized Cu powder to deposition thickness and coating interface adhesion strength. Results showed that #2 Cu powder exhibited smooth surfaces with clear particle distribution and low oxygen content, while #1 powder contained more fine particles and higher oxygen content. Under identical process conditions, #2 cold spray coatings achieved thickness distributions ranging from 73.94 μm to 162.27 μm with excellent density, whereas #1 products displayed uneven thickness distribution (minimum 34.27 μm, maximum 136.69 μm) and crack formed between coatings. The adhesion strength between #2 products substrate and coating exceeded 70 MPa, which was 61 MPa higher than #1’s maximum adhesion strength. Full article

The increasing need for energy-efficient and environmentally friendly electricity generation has led to the extensive use of hybrid electric systems. These systems integrate different energy sources in an effort to take advantage of the positives of each technology, as using a single source of energy comes with many limitations and disadvantages; hence, the popularity of hybrids has increased in recent times. In this regard, this paper proposes a lithium-ion battery (LIB) and ultracapacitor (UC)-based hybrid architecture considering an optimal energy management framework. In the transportation sector, hybrid vehicles (LIB and UC-based vehicles) effectively utilize the high energy density and power density of LIBs and UCs. This LIB and UC-based hybrid architecture provides an efficient power management solution considering the high power density of the LIB for smooth road profiles, and the high power density of the UC is driven during sudden spikes in load demand because the LIB will not function optimally during the sudden spikes due to lower power density. Furthermore, in order to achieve efficient utilization of the proposed hybrid system, an optimal energy management framework is used. In this regard, in this study, a fractional-order proportional–integral–derivative (FOPID) controller has been designed for effective and optimal energy management. Furthermore, the designed FOPID has been optimized using a metaheuristic technique, namely particle swarm optimization (PSO), to enhance LIB and UC-based hybrid electric vehicle energy management performance. Employing dynamic and optimal energy flow control, the FOPID-based system improves energy consumption, extends LIB life, and improves overall system performance and reliability. Full article

This paper develops a two-dimensional fully Lagrangian meshless fluid–structure interaction solver by integrating the Moving Particle Semi-implicit (MPS) method with continuum mechanics to investigate the nonlinear interaction between waves and floating bodies. The stability and accuracy of the proposed model are validated through several benchmark cases. Furthermore, the solver is employed to analyze the dynamic response of a flat plate floating body in waves. The numerically generated waves exhibit a minimum error of approximately −0.5% and a period consistent with theoretical values, maintaining a smooth and continuous free surface. Due to the inherent limitations of the two-dimensional wave-floating body simulation, the Root Mean Square Error (RMSE) of the interaction results ranges from 5.4% to 15.2%. These findings indicate that the proposed method provides a valuable reference for the design and analysis of floating structures in ocean engineering. Full article

Zr alloy-shaped charge liners (SCLs) offer broad application prospects due to their multiple post-penetration damage effects. However, research on these liners is still in its early stages. The mechanisms of jet formation and penetration for Zr alloys SCL remain unclear, and the specific contribution of different liner regions to the penetration process is not yet understood. This gap in knowledge has limited their structural design to a black-box correlation between global structural parameters and macroscopic penetration efficiency. To address this gap, a region-tracing Smoothed Particle Hydrodynamics (SPH) simulation was employed. Following a strategy of “wall thickness layering + axial segmentation,” the Zr alloy liner was partitioned into ten characteristic regions. This methodology facilitated the tracking of material transport from each region during jet formation and penetration into an AISI 1045 steel target. The contribution of each region to the penetration depth was then quantitatively assessed via post-processing. For the first time, the “critical region” contributing most to penetration depth was identified, and the influence of the liner’s cone angle and wall thickness on the contribution of each region was revealed. This study enhances the theoretical framework for understanding the damage effects of Zr alloy shaped charge liners. It not only advances the fundamental understanding of jet penetration mechanisms but also provides a theoretical basis for the refined design and performance optimization of these liners. Full article

Inspired by the erosion-resistant dorsal armor of the desert scorpion, this study developed biomimetic ZTA ceramic composites with enhanced resistance to solid particle erosion. Three biomimetic configurations, namely convex-bump (CH-O), convex-curved-surface (CH-CS), and convex hybrid rigid–flexible (CH-HS) structures, were fabricated by direct ink writing (DIW) 3D printing. Their erosion performance was evaluated by gas–solid two-phase erosion tests at impact angles ranging from 15° to 90°, and the underlying mechanisms were elucidated through erosion morphology analysis, actual impact angle analysis, and stress-wave propagation analysis. The results showed that the erosion rate of all samples first increased and then decreased with increasing impact angle, reaching a maximum at around 60°. Compared with the smooth control sample, CH-O exhibited lower erosion resistance under low-angle erosion conditions but showed clear improvement under high-angle erosion conditions, with the erosion resistance increased by 18.39–32.54%. CH-CS further improved the erosion resistance of CH-O, with enhancements of 14.31–53.92% at low impact angles and 24.57–35.17% at high impact angles. Among all the biomimetic designs, CH-HS exhibited the best overall erosion resistance, showing an additional improvement of 9.22–32.16% over CH-CS across the tested impact angle range. The superior erosion resistance was attributed to the synergistic effects of convex-bump morphology, curved-surface-induced particle deflection, and rigid–flexible coupling. These biomimetic features modified the actual impact angle of the particles, deflected their trajectories, reduced direct particle impact, and generated a shadow effect, while the flexible layer dissipated impact energy through reflection unloading at the rigid–flexible interface. This study provides a novel strategy for the biomimetic design of erosion-resistant ceramic composites and offers new insights into mitigating erosion damage in ceramic-based mechanical components. Full article

Background/Objectives: Enteric glial cells (EGCs) are key players in regulating enteric neurons and gastrointestinal functions including disturbed gut motility in diabetic patients. Enteric neuronal damage has been shown in type 1 diabetes, but EGCs’ vulnerability to hyperglycaemic insults requires more investigation. Therefore, we aimed to study the quantitative changes in the EGC network enmeshing enteric plexuses, intestinal smooth muscle and mucosa in streptozotocin-induced acute (1-week) and chronic (10-weeks) diabetic rat models. Methods: Fluorescent immunohistochemistry using Sox10 glial and HuC/HuD pan-neuronal markers, immunogold electron microscopy and ELISA were performed on different gut segments. Results: In the submucosal ganglia of the ileum and colon, the density of Sox10-immunoreactive EGCs was significantly reduced in acute and increased in chronic hyperglycaemic rats without any changes in the duodenum. In the myenteric ganglia, regionally distinct alterations of glial density were noted in acute hyperglycaemia; however, a remarkable decrease was observed in chronic animals. Alterations of neuronal density did not follow the pattern of glial changes, resulting in shifts in the glia/neuron ratio. The presence of Sox10-HuC/HuD-immunoreactive cells and their diabetes-related quantitative changes were also revealed in enteric plexuses. The density of Sox10-labelling gold particles was significantly increased in the duodenal myenteric glia of diabetic rats. Muscular EGC density increased only in the colon after acute hyperglycaemia and changed in all segments after chronic hyperglycaemia. Glial fibrillary acidic protein levels decreased in the small intestine of chronic hyperglycaemic rats. Conclusions: Our present findings reveal time-dependent and regionally distinct changes in the EGC network in response to hyperglycaemia, contributing to diabetic enteric neuropathy and gut motility disturbances. Full article

In this paper, we propose the Manifold Random Drift Particle Swarm Optimization (MRDPSO) algorithm for matrix optimization on smooth manifolds. Conventional swarm intelligence methods generally converge prematurely in constrained domains. To mitigate this issue, we introduce the swarm intelligence methods to the manifold and a Random Drift mechanism that regulates the search process. Using Riemannian geometry, our framework treats constrained problems as unconstrained ones on the manifold, which preserves the intrinsic geometric structure of the data. Particles are initialized on the manifold, while updates are performed in tangent spaces. Since geodesic calculations are computationally expensive, we use an inverse retraction as a faster alternative to standard logarithmic mapping. Numerical experiments on Grassmann, Stiefel, and Oblique manifolds show that MRDPSO achieves higher accuracy and superior convergence stability compared to recent state-of-the-art manifold-adapted heuristics, namely IISSO and MSSO. Full article

Caking and powder adhesion are widespread challenges in dry powder processes. The influence of process parameters such as humidity and temperature on the adhesion behavior of dry powders has been extensively studied in numerous studies. Besides that, the impact of other process characteristics, such as additional process parameters or wall materials, has received little attention so far. In addition, existing methods to characterize caking behavior do not account for powders in a fluidized state. To address phenomena based on process and material behavior, a test rig was specifically designed to investigate the adhesion of dry particles to different metal walls at varying speeds at a 90° angle, representing the main novelty of this study. The deposition area, deposition mass, and maximum deposition thickness were evaluated, and the correlations were discussed. The investigations revealed that at low velocities (<12 m/s) and for smooth surfaces (Sq < 0.3–0.4 µm), wall materials with a high ratio of dispersive to polar surface energy components (D/P: 13–15.8) exhibit minimal powder adhesion. The test rig has demonstrated its effectiveness as a straightforward method for measuring adhesion across various powder–wall material pairs and could serve as a valuable preliminary test for industrial applications. Full article

This paper presents an improved hybrid Eulerian–Lagrangian framework, which has been augmented with an adaptive mesh refinement technique, for simulating passive scalar transport on deforming interfaces. We capture interface deformation using an Eulerian level-set method while solving the interfacial transport equation with a single-layer smoothed particle hydrodynamics method. As a result, the proposed hybrid approach combines the high efficiency of the Eulerian formulation with the strict mass conservation property of smoothed particle hydrodynamics method. To further accelerate the simulations, we employ adaptive mesh refinement for the Eulerian solver and restrict particles to the finest refinement level. To mitigate Lagrangian particle clustering, we adopt a remeshing procedure that generates particle distributions adapted to the local interface geometry on the finest mesh. This remeshing also enables accurate, mass-conservative reconstruction of the interfacial concentration field. Moreover, by incorporating an adaptive remeshing strategy, we tune the remeshing frequency to balance computational cost and accuracy. The accuracy and robustness of the proposed method are demonstrated through a suite of benchmark test cases. Additionally, we evaluate the effectiveness of adaptive mesh refinement through benchmark test cases, verifying its compatibility with the interfacial smoothed particle hydrodynamics method and quantifying the resulting speedup. Full article

In this paper, an innovative design of a silicon spiral drift detector (SDD) has been proposed. In this design, gaps under the SiO₂ layer between the cathode rings are kept constant, with a minimum value to reduce the surface leakage current. The cathode pitch profile $\mathrm{P}\left(\mathrm{r}\right)$ as a function of radius $\mathrm{r}$ is allowed to change in an arbitrary way to achieve the optimum field distribution. The concept, design considerations, modeling and electrical simulations have been carried out for this novel structure with a hexagonal spiral silicon drift detector. Using one-dimensional analyses, we obtain the exact solution of the spiral design $\mathrm{r}=\mathrm{r}\left(\mathrm{\theta }\right)$ with a near-arbitrary pitch profile $\mathrm{P}\left(\mathrm{r}\right)={\mathrm{P}}_1{\left({\displaystyle \frac{\mathrm{r}}{{\mathrm{r}}_1}}\right)}^{{\displaystyle \frac{1}{\mathrm{\eta }}}}$, with $\mathrm{\eta }$ as an arbitrary real number. We also obtained the electric potential and field profiles on both surfaces of the detector. Using a Technology Computer-Aided Design (TCAD) tool, we made 3D simulations of the detector’s electrical properties. The hexagonal spiral silicon drift detector has excellent electrical properties: a uniform electric field, smooth distribution of electric potential and electron concentration, and a clear electron drift channel. The distributions of the electric field, electric potential, and electron concentration are symmetrical and smooth, which is beneficial for applications in photon sciences (X-ray) and safeguards and homeland security (particle radiation). The theoretical work and simulation results serve as solid foundations for the detector design and the expansion of semiconductor technology. Full article

Autonomous aerial refueling is a key technology for enhancing the endurance of unmanned aerial vehicles; however, the wingtip vortices generated by the tanker create a strong three-dimensional wake-vortex flow field, whose downwash and lateral airflow can impose significant rolling moments on the follower Unmanned Aerial Vehicle (UAV), posing a serious threat to flight safety. To address this issue, this study proposes an integrated framework that combines wake-vortex risk-field modeling with optimal path planning. The classical Hallock–Burnham (HB) model is first employed to predict vortex descent and lateral transport, while a two-phase model is used to characterize the temporal decay of vortex circulation. The predicted vortex parameters are then coupled with the UAV’s aerodynamic characteristics, and the rolling-moment coefficient (RMC) is introduced as a risk metric to compute its spatiotemporal distribution in three dimensions, thereby transforming the invisible wake-vortex disturbance into a visualizable and quantifiable dynamic three-dimensional risk map. On this basis, a wake-vortex-aware path-planning algorithm based on particle swarm optimization (PSO) is developed, incorporating adaptive weighting and elitist mutation strategies. A multi-objective cost function considering path length, safety, and smoothness is further constructed to search for an optimal safe path under wake-vortex influence. Simulation results indicate that, compared with the classical A* and Rapidly-Exploring Random Tree (RRT) algorithms, the proposed method reduces cumulative risk exposure by approximately 90% and 75%, respectively, while limiting the increase in path length to about 8% (significantly lower than the increases of 40% for A* and 44% for RRT). In addition, the maximum turning angle is constrained within 10°, and the computation time remains around 0.052 s, satisfying real-time requirements. These results demonstrate that the proposed method can generate safe, efficient, and dynamically feasible paths for UAV aerial refueling and provide a valuable reference for wake-vortex avoidance in similar aerospace missions. Full article