Abstract: Nonlocal elasticity theory plays a significant role in the analysis of small-scale effects in micro- and nanostructures. In continuum mechanics, Eringen’s integral constitutive relation is often considered more general than its differential counterpart. However, the governing equations are complex integro-differential equations, which complicate numerical solution and can limit their use in nonlocal analyses of micro- and nanostructures. To address this challenge, this paper proposes a numerical solution method based on a symplectic system for the study and resolution of the free vibration problem of small-scale Kirchhoff plates. By integrating an element that accounts for long-range interaction forces, this method effectively discretizes the nonlocal integral operator. The model is used to systematically investigate the effects of nonlocal parameters, mixture parameters, mode numbers, kernel function types, and geometric parameters on the natural frequencies of nonlocal Kirchhoff plates. The numerical results indicate that nonlocal effects soften structural stiffness and that higher-order modes are more sensitive to nonlocal parameters. The convergence and accuracy of the proposed algorithm are verified by comparison with existing differential nonlocal solution schemes.

Abstract: Fast and universal grasping remains a critical challenge for robotic hands operating in unstructured and industrial environments. Conventional pin-array-based robotic hands exhibit strong adaptability to objects with diverse geometries, yet their grasping speed is often limited by centralized motor-driven actuation. To address this limitation, this paper presents the development of a fast-acting cluster-tube self-adaptive robotic hand (CTSA-FA hand), which transforms traditional active actuation into a passive energy-storage-and-release-driven grasping mechanism. A spring-cam-based structure is introduced to enable rapid energy release during the grasping phase, significantly reducing the gathering time. A theoretical model of the CTSA-FA hand is established, including cam trajectory planning and mechanical analysis, to guide parameter design and performance optimization. A physical prototype is developed and experimentally validated. Experimental results demonstrate that the proposed CTSA-FA hand can complete approximately three grasp-release cycles per second, corresponding to a grasping time of about 0.25~s per cycle, while maintaining robust adaptive grasping performance. These characteristics indicate that the proposed design is well suited for applications requiring fast and universal grasping, particularly in intelligent mining equipment and industrial automation scenarios.

Abstract: Transverse shear deformation plays a non-negligible role in lightweight periodic-core structures and motivates the use of shear-corrected reduced-order plate and beam models. However, the shear correction factor ks is often treated as a constant despite its strong dependence on cross-sectional heterogeneity and geometry. This work quantifies the global sensitivity of ks in corrugated paperboard by combining an energy-consistent pixel-based identification of the effective shear stiffness GA)eff with a space-filling exploration of the parameter domain. Representative 3-ply (single-wall) and 5-ply (double-wall) configurations are generated directly in the pixel domain using sinusoidal fluting descriptions and non-overlapping liner bands. The effective shear stiffness is obtained from a heterogeneous shear-energy equivalence, where a normalized two-dimensional shear-stress shape function is computed from pixel-based sectional descriptors and integrated with spatially varying shear moduli. Latin Hypercube Sampling is employed to explore wide ranges of flute period, height, and thickness, liner thicknesses, and liner–flute shear-modulus contrasts. Global sensitivity is reported using unit-free normalized indices, including log-elasticities (based on the slope of lnks versus lnx) and partial rank correlation coefficients. The results demonstrate that flute geometry is the primary driver of ks variability, while material contrast significantly modulates shear-energy localization, particularly in double-wall boards with two distinct flutings. The proposed framework enables high-throughput shear correction assessment and supports robust parameterized reduced-order models for corrugated structures.

Abstract: To address the prevalent domain inadaptation issue in multi-source domain transfer fault diagnosis, this study proposes a novel model integrating graph embedding technology and adaptive classifiers. The framework combines multi-statistic multi-scale permutation entropy methods to simultaneously optimize projection and classifier performance, thereby enhancing generalization capabilities and diagnostic accuracy. During model construction, a weighted non-parametric maximum mean difference approach is employed to quantify and minimize differences in edge distributions and conditional distributions between source and target domains. Through similarity weight allocation, norm adjustment, and row sparsity learning strategies, the model effectively reduces interference from irrelevant samples. Additionally, by embedding category information and domain manifold structures, the model ensures classification validity of mapped features. Using labeled source domain data and unlabeled target domain data, the study develops a structure-aware adaptive classifier that narrows distribution differences while preserving manifold consistency, significantly improving diagnostic performance under variable operating conditions. Experimental results demonstrate that this multi-source domain transfer model achieves higher accuracy than single-domain approaches. Notably, in rotating machinery variable operating scenarios, the proposed method outperforms existing techniques in both precision and generalization capabilities.

Abstract: Designing linear conveyor feeders with passive fences for automated part orientation remains largely trial-and-error because the final orientation distribution is difficult to predict reliably before physical testing. We present a simulation-driven deep learning pipeline that predicts the full distribution of final in-plane orientations for extruded, z-axis-symmetric parts interacting with linear feeders containing up to two straight or curved fences. Using Bullet physics-based simulation in CoppeliaSim, we generate 1,048 main part--feeder samples across 38 part geometries, plus 78 fence-generalization and 110 unseen-part samples for a total of 1,236 (41 unique parts), and train regression networks and a Variational Autoencoder, or VAE, to predict 360-bin orientation probability distributions. On known parts, the regression model achieves high accuracy on held-out test configurations, R² on circular CDFs = 0.97 ± 0.05, and on unseen fence combinations, R² on circular CDFs = 0.89 ± 0.11. Generalization to previously unseen part geometries is more challenging, with R² on circular CDFs = 0.75 ± 0.18, indicating that geometric representation and dataset diversity are primary limitations. We also evaluate VAE reconstruction on datasets generated from simulations at different iteration counts, 5--100% of 1000 iterations in 5% increments. While within-level reconstruction remains high, cross-convergence evaluation shows partial-iteration PMFs are far from fully converged labels in this dataset (overall CDF R² = 0.01 at 5%, 0.32 at 50%, and 0.87 at 75%), so reduced-iteration simulations do not substitute for full convergence here. Overall, the proposed approach provides a data-driven foundation for feeder analysis and design, with future work focusing on improved geometric generalization and physical validation for industrial deployment.

Abstract: This study investigates the fatigue behavior of cold-finished mild steel coated with nickel as a hydrogen permeation barrier. Hydrogen was introduced to the coated specimens through electrochemical charging at controlled charging current densities to induce varying levels of hydrogen exposure. Subsequent fatigue tests were carried out to assess the impact of hydrogen permeation on fatigue life. The primary objective was to assess the influence of hydrogen on the number of cycles to failure, and to evaluate the effectiveness of nickel coatings as permeation barriers to impede hydrogen ingress under cyclic loading conditions. The experimental results revealed a non-monotonic relationship between fatigue life and hydrogen charging severity. At low to moderate hydrogen charging levels, the fatigue response of the coated steel was relatively stable, reflecting the ability of the nickel coating to limit hydrogen ingress. However, at higher charging current densities, the fatigue life decreased abruptly, indicating the existence of a threshold beyond which the protective capability of the nickel coating diminishes and hydrogen embrittlement (HE) becomes dominant. The findings from this research provide insights into the fatigue performance of nickel-coated steels and supports the informed design of structural components for service in hydrogen-rich environments.

Abstract: Fused Deposition Modelling (FDM) is widely employed in additive manufacturing (AM) of polymer components, where process parameters play a critical role in determining mechanical performance and resource efficiency. Although process parameters, such as layer height, build orientation and infill density, have been extensively studied with respect to tensile strength, the combined influence of infill pattern, density, and skin layer configuration remains insufficiently explored. In this research, six infill patterns, namely concentric, line, triangle, honeycomb, grid, and gyroid, are evaluated at three density levels (50%, 75%, and 90%) with multiple skin layer configurations using an L36 orthogonal experimental design. Tensile tests are analyzed using analysis of variance (ANOVA) to identify the significant factors and their interactions, supported by pattern-specific interaction plots. The results indicate that tensile strength increases by increasing infill density in a similar pattern; however, when comparing different patterns, the concentric infill consistently exhibits superior tensile strength along with reduced printing time, material consumption, and energy usage. This behavior can be primarily explained by the filament alignment parallel to the applied tensile load, which promotes load transfer through continuous material paths rather than interlayer bonding with implications for effective build orientation selection through controlled filament alignment. Overall, the findings demonstrate that concentric infill provides an effective strategy for optimizing the tensile strength while minimizing the environmental impact, offering practical guidance for sustainable FDM part design.

Abstract: In this study, we examined the influence of coating thickness on surface roughness, hardness, phase composition, and tribological behavior of arc-sprayed FeCrAl coatings deposited on steel substrates. We measured coating thickness, phase composition, and surface roughness using optical microscopy, X-ray diffraction (XRD), and profilometry, respectively. Results showed that surface roughness decreased with increasing coating thickness due to improved splat coalescence. However, Rockwell hardness remained nearly constant (at approximately 95 HRB), denoting a limited dependency on coating thickness. Using pin-on-disk tribometry, we found that the thickest coating showed the highest coefficient of friction (CoF, mean value of 0.864). This is because there is an in-creased tendency for the formation of hard oxide phases (Cr₂O₃ and Al₂O₃) in thicker coatings. These oxides increased friction by generating abrasive debris during sliding. The novelty of this work is that CoF is sensitive not only to surface morphology but also to thickness-dependent phase composition, whereas most previous studies found that CoF was primarily correlated with surface roughness only. Our research findings show that both microstructural and phase composition behavior during deposition are crucial for optimizing the friction and wear properties of FeCrAl coatings in high-temperature, steam-rich applications. Therefore, accurate control of oxidation behavior as a function of coating thickness can lead to more durable, reliable coatings in those environments.

Abstract: This paper investigates the stability of telescopic handlers 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 an 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 systems, such as telehandlers equipped with a pivoting rear axle, and when interpreting certain results obtained from standardized stability tests. To overcome these limitations, a dynamic multibody model based on the three-dimensional Bond Graph (3D Bond Graph) methodology is subsequently introduced. This virtual model is not intended to replace the quasi-static analyses, but to complement them by providing a physically consistent interpretation of the observed behaviour.The dynamic model is implemented within a virtual tilting and rotation test platform and validated against experimental results obtained from ISO 22915-14 stability tests. The comparison confirms compliance with the normative requirements and demonstrates that the model captures different rollover modes and transitions between virtual stability axes that cannot be fully explained by quasi-static approaches alone. Unlike most previous studies, which focus on fixed orientations and isolated configurations, the proposed framework analyses how stability evolves as the vehicle changes its orientation on inclined terrain. This contributes to a more realistic assessment of operating conditions and supports the use of dynamic simulation as a complementary tool for test interpretation, experimental planning, and the future development of predictive stability and operator assistance systems.

Abstract: In the field of parallel robots, traditional rigid joints compromise motion accuracy owing to inherent friction and backlash, thus driving the demand for high-performance com-pliant joints. This paper proposes a parametric design method for a two-axis compliant joint that employs flexure leaf springs (FLSs) as rigid joint alternatives. The joint con-figuration consists of four FLSs arranged in a revolute-revolute (RR) layout. Based on Euler–Bernoulli beam theory and the deformation superposition principle, linear ana-lytical models for the compliance and stress characteristics of both the flexure leaf spring (FLS) and the compliant joint are derived. These models are validated through finite element analysis (FEA) and rotational motion experiments. The results indicate that the relative errors between the analytical model (AM) and finite element model (FEM) are below 8%, while the relative errors between the AM and experimental data are within 12%. The proposed parametric design method enables rapid preliminary design and performance evaluation of compliant joints, which highlights its potential for practical engineering application.

Abstract: Ti6Al4V (TC4) titanium alloy is widely used in aerospace, biomedicine, and other high-precision applications due to its excellent specific strength, corrosion resistance, and biocompatibility. However, its surface quality directly affects the fatigue life and service performance of parts, and traditional polishing methods suffer from low efficiency and high pollution. As a non-contact, controllable surface treatment technology, nanosecond laser polishing has demonstrated unique advantages in balancing processing efficiency and surface quality. This study systematically discussed the influence of key process parameters (spot overlap rate, laser power, and scanning times) on nanosecond laser polishing of TC4 titanium alloy. It revealed the internal physical mechanism by analyzing the temperature and velocity fields and vortex dynamics during molten-pool evolution. It is found that the polishing effect is determined by the process parameters, which adjust the thermal-fluid coupling physical field (temperature distribution, melt flow, and vortex structure) in the molten pool. There is an optimal combination of parameters (spot overlap rate of 79%, laser power of 0.8W, scanning speed of 5m/min, scanning 3 times) that can place the molten pool in an optimal dynamic balance state and achieve effective flatness. The experimental results show that under this parameter, the surface roughness of the specimen with an initial roughness of 1.223 μm is reduced by about 32%. The research further clarified the mechanism by which the initial roughness of the base metal influences the molten pool: the greater the initial roughness, the more pronounced the "peak shaving and valley filling" effect. Under the same parameters, the improvement rate of the specimen with the initial roughness of 1.623 μm could reach about 40%. This study not only establishes the optimized process window, but also reveals the essential relationship between "process parameters - bath behavior - surface quality" from the level of the physical field of the molten pool, which provides an essential theoretical basis and practical guidance for the laser polishing process of TC4 titanium alloy high-precision surface.

Abstract: The present study investigates the influence of low temperature on starting torque, viscous friction, and power intensity of a precision cycloidal reducer TwinSpin TS 140115EP190583. Two types of plasticity lubricants with differing viscosity were compared in the experiment: Castrol TT1 (low-viscosity, optimized for low-temperature) and Vigo RE0 (higher viscosity, designated for greater loads). The measurements were taken in a climate chamber in the temperature ranging from +24 °C to −20 °C in the mode accounting for no external load. The results have shown that Castrol TT1 maintains its beneficial rheological properties at as low as −20 °C, which is manifested in low starting torque (~0.30 Nm) and low power intensity (~0.33 kW). On the contrary, Vigo RE0 shows a significant increase in friction – at −20 °C, the starting torque is 1.0–1.1 Nm and the power intensity of the operation increases to consume more than 1.5 kW. The study has confirmed that the correct choice of lubricant is the critical factor in reliable starting and efficient operation of reducers in extreme cold.

Abstract: Parallel electric-hydraulic hybrid (PEHH) powertrains offer benefits of lower energy consumption and increased battery lifetime compared to pure electric ones. These merits can be extended with advanced control methods that optimally deploy on-board energy sources. This work proposes a nonlinear model predictive control (NMPC) energy management strategy (EMS) for a PEHH wheel loader. The optimization minimizes energy usage and battery degradation by selecting the optimal power ratio between the electric and hydraulic subsystems. The state prediction is based on a discrete nonlinear dynamic model and an estimate of the future exogenous inputs developed from a high-fidelity digital-twin model of a wheel loader. The NMPC formulation is compared to a baseline rule-based EMS inspired by offline optimal control. The proposed NMPC results in 38.8\% less battery degradation and 7.5\% energy consumption reduction, even with 20\% error in the preview information. Hardware-in-the-loop (HiL) experiments validate our results and show that the NMPC EMS can be implemented in real-time, even with higher prediction error increasing the maximum computational time.

Abstract: This study addresses the challenge of consistently transferring atomistic parameters of the C–C bond into phenomenological material characteristics within framework of continuum mechanics. Particular attention is given to determining the effective transverse diameter of the covalent C–C bond in carbon nanostructures. The dependence of this diameter on the Poisson’s ratio ν is examined, and the influence of the interatomic stiffness constants k_r,k_θ,and k_τ is systematically analyzed. Classical representative-volume models of the C–C bond based on the Euler–Bernoulli beam hypothesis violate thermodynamic stability conditions and lead to nonphysical Poisson’s ratio values exceeding 0.5, due to the neglect of shear deformation effects. To overcome this limitation, an approach based on Timoshenko beam theory is proposed, accounting for both bending and shear deformations. This approach enables estimation of energetically equivalent states between the phenomenological representative volume and the corresponding atomistic C–C bond model. As a result, a sixth-order algebraic equation is derived linking the effective bond diameter, the Poisson’s ratio, and the molecular mechanics force constants. Analysis of this equation reveals a narrow range of effective bond diameters and Poisson’s ratios for which thermodynamic stability conditions are satisfied. Within this range, physically consistent macroscopic material parameters can be directly expressed in terms of atomistic force constants.

Abstract: Floating involute splines are widely used in aviation power transmission systems to transmit torque. In this paper, by establishing a finite element model of the dynamic deformation of the floating involute spline shaft, the influence of the dynamic deformation of the spline shaft on the misalignment state of the spline pair under various typical dynamic overloads was analyzed. And a contact simulation model of the floating spline pair with the actual tooth profile was established to study the influence of the spline misalignment caused by dynamic deformation on the contact pressure distribution on the tooth surface. The contact stress fatigue strength of the spline pair under dynamic loads such as limit loads and ultimate loads was evaluated. The results show that the axial overload can lead to the axial movement of the mating surface of the floating spline, reducing the effective axial contact length; the radial overload and gyroscopic moment can lead to the parallel misalignment and angular misalignment of the spline. When the overloads are superimposed, the angular misalignment of the spline is the most significant under the limit load, and the parallel misalignment is the most significant under the ultimate load. There are obvious stress concentrations and uneven load-bearing in the contact stress distribution of the spline under the limit and ultimate loads. According to the infinite life and static strength design methods, the evaluation shows that the long-term working contact fatigue strength of the floating spline of a certain type of engine under the ultimate load does not meet the design requirements, and the spline parameters need to be optimized. The quantitative analysis method for the misalignment of the floating spline under the superposition of various dynamic loads formed in this paper provides an important theoretical reference for the design of the misalignment of the aviation floating spline and the improvement of its long-term working ability.

Abstract: Accurate quantification of the crack tip driving force (ΔK) is fundamental to predicting the fatigue life of engineering structures. Analytical formulations of ΔK are rarely available for components with complex geometries. In such cases, finite element (FE) analysis has become a widely accepted approach for determining ΔK. In this study, an FE-based solution for the crack-tip driving force of a fatigue crack in an asymmetric L-shaped bell crank geometry, a representative complex structure, is established. The structure is fabricated from AISI 410 martensitic stainless steel. The FE-predicted ΔK_I for crack growth in the Paris regime has been independently validated using the multifractal stress-intensity-factor model. Results show that the fatigue crack in the bell crank structure is driven by a combined Mode-I (opening) and Mode-II (shearing) crack tip loading along a curved crack path trajectory, as dictated by the asymmetric stress distribution. The fatigue crack edge exhibits fractality with fractal dimensions ranging from 1.00 (Euclidean) to 1.18 over the crack length, (a-a_o) up to 9.947 mm. The FE-calculated crack tip driving forces of the bell crank structure are comparable with those computed based on the corrected crack edge fractal dimensions, thus validating the FE simulation outcomes. The resulting fatigue crack growth rates, determined from crack-tip driving forces based on validated FE-computed contour integrals, are comparable to those obtained from the ASTM standard tests.

Abstract: This study experimentally investigates a novel hybrid system integrating thermoelectric generators (TEGs) with direct contact membrane distillation (DCMD) for simultaneous low-grade heat recovery, electricity generation, and water desalination. Commercial TEG modules were sandwiched between heat spreaders to transfer thermal energy from a source (approx. 140°C) to a cooling sink, driving saline water evaporation through a hydrophobic membrane. A validated mathematical model showed strong agreement with experimental results. The system achieved freshwater mass fluxes of 8–9.5 kg/m²/h and electrical power outputs density of 25–35 W/m². Increasing heat input (450–700 W) significantly enhanced freshwater production and electrical output, improving the gain output ratio (GOR) and reducing specific energy consumption (SEC). While higher feed salinity (up to 35,000 ppm) measurably declined mass flux and thermal efficiency, thermoelectric generation and thermal resistance remained largely unaffected. Energy and exergy efficiencies showed moderate sensitivity to operating conditions, while the Water–Electrical Energy Cogeneration Index (WEeCI) increased at high salinity, highlighting the robust contribution of electricity generation. These results demonstrate the potential of the TEG–DCMD system for sustainable co-generation of water and power from industrial waste heat or renewable thermal sources.

Abstract: This study examines the synergistic effect of aluminum oxide (Al₂O₃) and cerium oxide (CeO₂) nanoparticle additives on a CI engine using diesel-Jatropha biodiesel blends. Jatropha biodiesel was produced via transesterification. Blends (B5–B25) were prepared, and nanoparticles (Al₂O₃: 150 ppm; CeO₂: 50 ppm) were dispersed into B20 using ultrasonication and surfactant. Engine tests at varying loads showed that the B20 blend with combined nanoparticles achieved a peak brake thermal efficiency of 34.1%, surpassing diesel (32.5%). Its brake-specific fuel consumption was comparable to diesel. Emissions reduced significantly: carbon monoxide by 55%, unburnt hydrocarbons by 34%, and smoke opacity by 31% versus diesel. Notably, NOx emissions were reduced by 12.4%, countering biodiesel's typical increase. The B20 blend with 150 ppm Al₂O₃ and 50 ppm CeO₂ is identified as an optimal, sustainable alternative fuel requiring no engine modifications.

Abstract: Gas emissions containing particulate matter are the most prevalent in technological processes. To reduce emissions into the atmosphere, it is necessary to apply gas pre-treatment before high-efficiency filters, which in interaction helps to achieve a favorable result for reducing the level of fine and ultrafine particles particularly dangerous to the human health. Electric field manipulator (agglomerator) can influence these fine particulate matter and results in an increase in their size. Comprehensive aerodynamic study aim to elucidate the gas flow distribution, variation of trajectories and dynamics at different flow rates, specifically the trajectories and velocities of particles within the gas flow. These factors provide meaningful assumptions about the possible behavior of particles in the flow and there are critical for optimizing an agglomeration and its intensity. Such phenomena can have an impact on the probability of agglomeration in the manipulator channels, i.e., the sticking of small particles into larger ones, and this allows improving the design and operating conditions of the apparatus. Gas flow velocities and pressure were analyzed experimentally at various cross-sectional points in the inlet and outlet ducts at the inflow rate of 3.4-50 l/s. Pressure-based solver with the coupled scheme for pressure-velocity coupling was used. The static pressure at the inlet of manipulator varied from 8 to 178 Pa. This study provides new insights into flow pre-treatment using the electric field mechanism in a multichannel modular apparatus and provides a reasonable understanding of the necessary characteristics of the gas flow distribution for its subsequent improvement for highest agglomeration.

Abstract: Semantic point cloud maps play a pivotal role in smart agriculture. They not only provide core three-dimensional data for orchard management but also empower robots with environmental understanding, enabling safer and more efficient navigation planning. However, traditional point cloud maps primarily model surrounding obstacles from a geometric perspective, failing to capture distinctions and characteristics between individual obstacles. In contrast, semantic maps encompass semantic information and even topological relationships among objects in the environment. Furthermore, existing semantic map construction methods are predominantly vision-based, making them ill-suited to handle rapid lighting changes in agricultural settings that can cause positioning failures. Therefore, this paper proposes a positioning and semantic map reconstruction method tailored for orchards. It integrates visual, radar, and inertial sensors to obtain high-precision pose and point cloud maps. By combining open-vocabulary detection and semantic segmentation models, it projects two-dimensional detected semantic information onto the three-dimensional point cloud, ultimately generating a point cloud map enriched with semantic information. The resulting 2D occupancy grid map is utilized for robotic motion planning. Experimental results demonstrate that on a custom dataset, the proposed method achieves 74.33% mIoU for semantic segmentation accuracy, 12.4% relative error for fruit recall rate, and 0.038803m mean translation error for localization. The deployed semantic segmentation network Fast-SAM achieves a processing speed of 13.36 ms per frame. These results demonstrate that the proposed method combines high accuracy with real-time performance in semantic map reconstruction. This exploratory work provides theoretical and technical references for future research on more precise localization and more complete semantic mapping, offering broad application prospects and providing key technological support for intelligent agriculture.