Search Results (5,057)

This study examines how 3D-printing orientation affects the mechanical behavior and environmental impact of polymer materials and heterogeneous PLA/TPU composites. Tensile properties of PLA, TPU, and PLA/TPU heterogeneous samples were systematically compared in horizontal and vertical printing orientations. Results show that printing orientation governs mechanical performance: vertical printing generally reduces ductility and exhibits unstable post-peak behavior, with heterogeneous samples performing worse than their single-material counterparts. In contrast, horizontal printing enhances strength, ductility, and energy absorption due to continuous load transfer along the filament path, improved interlayer adhesion, and larger effective contact areas. Specifically, TPU demonstrates higher ductility and energy absorption in the horizontal orientation, while PLA achieves higher strength but lower ductility; both materials degrade substantially in the vertical orientation. For heterogeneous composites, vertical printing yields the poorest outcomes due to load transfer across multiple perpendicular interfaces and thermal shrinkage mismatch, which promote crack initiation and propagation. Horizontal printing delivers an optimal balance of strength and toughness via stronger interface bonding. Life cycle assessment (LCA) indicates that horizontal printing reduces environmental burdens by lowering energy consumption and waste, whereas vertical printing amplifies these impacts, particularly for TPU and composite systems. Based on these findings, we recommend employing horizontally printed PLA/TPU heterogeneous composites to achieve favorable load paths and interface integrity while prioritizing bio-based PLA to enhance sustainability. Full article

Due to high specific energy absorption, composite/metal hybrid multi-cell thin-walled tubes hold significant potential in the field of automotive passive safety. However, the material coupling effect enhancing SEA often elevated the initial peak crushing force, reducing crushing force efficiency and compromising occupant protection. To balance SEA and CFE, trigger holes were introduced as an induced deformation mechanism for hybrid tubes to reduce IPCF while preserving SEA, with the optimized perforated configuration yielding higher CFE than the non-perforated counterpart. A high-fidelity finite element model of the hybrid tube was developed and experimentally validated, and the influences of induced structural parameters on SEA and CFE were investigated. Given the strong nonlinear coupling between trigger parameters and crashworthiness, a multilayer perceptron surrogate model was constructed using 200 optimal Latin hypercube sampling samples (20 for validation). A Q-learning enhanced particle swarm optimization (QL-PSO) algorithm was adopted for optimization, with reinforcement learning dynamically adjusting PSO parameters to balance global exploration and local exploitation. Finite element simulations validated that the proposed method achieved a favorable SEA-CFE trade-off, with SEA and CFE improved by 12.02% and 16.39% respectively, outperforming reported configurations. Compared with standard PSO, QL-PSO exhibited superior search efficiency and inverse mapping accuracy, with 22% higher optimization efficiency and full compliance with inverse design performance targets. This study provided valuable guidance for the design of thin-walled energy-absorbing structures in multi-material vehicle bodies. Full article

In automotive Computer-Aided Engineering (CAE), the fidelity of high-quality shell element meshes is fundamentally governed by the accuracy of mid-surface geometry extraction. Conventional manual extraction for complex automotive plastic components is labor-intensive, error-prone, and often compromises mesh quality. To address these issues, this paper proposes an automated mid-surface mesh reconstruction method based on point cloud registration, establishing an integrated framework comprising “Multimodal Registration—Displacement Binding—Surface Correction.” Using a source part with an ideal mid-surface as a template, the method integrates Random Sample Consensus (RANSAC) and Iterative Closest Point (ICP) for rigid registration and Coherent Point Drift (CPD) for non-rigid registration to achieve high-precision alignment between the target and source outer-surface point clouds. Subsequently, a K-Nearest Neighbor (K-NN) search-based displacement binding mechanism smoothly transfers the outer-surface displacement field to the source mid-surface point cloud. Following position correction and surface smoothing, a complete and high-quality target mid-surface mesh is generated. Experimental results on typical plastic snap-fit components demonstrate that the normal projection error between the generated mid-surface and the manually refined “gold standard” mesh is less than 0.05 mm. The processing time per component is approximately 38 s, representing an efficiency improvement of over 73% compared to manual extraction using commercial CAE software. This method effectively mitigates common issues such as mid-surface distortion and feature loss, offering a high-precision, fully automated solution for automotive CAE pre-processing. Full article

Electric unmanned vehicles applied in complex terrains such as agricultural, forestry, and deep-space exploration scenarios are often required to travel on uneven roads. In particular, during climbing processes, their driving stability and terrain adaptability are of critical importance. To address the above challenges, an electric unmanned vehicle with variable-diameter wheels is proposed. By adjusting the wheel diameter, the vehicle can modify its pitch and roll angles to adapt to uneven terrains. The core research focuses on the relationship between quasi-static stability and wheel diameter variation. First, the configuration and working principle of the electric unmanned vehicle with variable-diameter wheels are introduced, with particular emphasis on the mechanism principle of the novel variable-diameter wheel. A kinematic model between the electric cylinder input and wheel diameter in the variable-diameter wheel is established. On this basis, based on the FASM (Force-Angle Stability Margin)—a stable cone theory, the relationships between stability and wheel diameter variation were investigated separately under lateral, longitudinal, and 45° steering composite conditions on a slope. The results indicate that the unmanned vehicle can achieve omnidirectional attitude adjustment. Finally, the relationship between the electric cylinder input and stability is derived, which can provide a theoretical basis for the quasi-static stability control of outdoor electric unmanned vehicles. Full article

Binder Jetting 3D Printing (BJ3DP) offers an effective pathway for the rapid fabrication of complex high-entropy alloy (HEA) components. In this study, the macroscopic characteristics, microstructural evolution and mechanical properties of Al_0.5Cr_0.9FeNi_2.5V_0.2 HEA green parts prepared via BJ3DP were investigated under various sintering conditions. Results showed that the relative density of the sintered parts increased significantly with temperature, transitioning from a low density (<90%) at 1300–1330 °C to near-fully dense (~98%) at 1340–1350 °C. Consequently, the mechanical properties were remarkably improved. The yield strength (σ_0.2) increased from 300 MPa to 710 MPa (a 136% increase), and the ultimate tensile strength (σ_b) rose from 310 MPa to 780 MPa (a 148% increase) as sintering temperature rose from 1300 °C to 1350 °C. Microstructural analysis revealed that at lower sintering temperatures, the alloy exhibited high porosity and a non-coherent structure composed of an FCC matrix and Cr-rich BCC phase, with Al/Ni intermetallic compounds distributed around pores. Conversely, at the final sintering stage, pore closure was achieved, and a coherent structure consisting of an FCC matrix and scale-like L1₂ precipitates was formed. Optimal mechanical properties (tensile strength ≥ 700 MPa) were achieved when sintering at 1340 °C, primarily attributed to densification and precipitation strengthening. Full article

Jin Cang embroidery, characterized by elaborate metallic threadwork and intricate textural patterns, is an important form of intangible cultural heritage. The digital preservation of Jin Cang embroidery is hindered by the scarcity of specialized datasets and the lack of object detection models that balance high performance with computational efficiency for edge deployment. To address these challenges, a dedicated dataset comprising 3050 images across eight core stitch categories is introduced as the first dataset of its kind for Jin Cang embroidery. Building upon this foundation, Lite-YOLOv11s, a domain-specific lightweight detection framework, is proposed with MobileNetV4 as its backbone to improve the extraction of high-frequency texture cues associated with metallic threadwork. Experimental results show that Lite-YOLOv11s achieves an mAP@0.5 of 0.951, outperforming the YOLOv11s baseline (0.927) while reducing model parameters by 40% and FLOPs by 46%. EigenCAM visualizations further show that the model can localize discriminative stitch-level features even under complex backgrounds. This work provides an efficient and deployable solution for intelligent embroidery recognition and offers a useful reference for the digital preservation of other fine-grained cultural heritage crafts. Full article

To address the emergency obstacle-avoidance problem of intelligent vehicles on structured roads, this paper proposes an integrated planning and control method that combines an improved Artificial Potential Field (APF) with fuzzy Model Predictive Control (MPC). Different from a direct APF + MPC combination, the planning layer introduces a braking-distance threshold, an effective obstacle-influence boundary, and sinusoidal shape factors to reshape the obstacle repulsive field and alleviate local-minimum behavior. A seventh-order polynomial smoothing strategy is then adopted to generate a reference path with higher-order continuity. For trajectory tracking, a fuzzy adaptive MPC controller adjusts the prediction horizon and control horizon online according to lateral error, while a fuzzy PID controller regulates longitudinal speed. MATLAB/Simulink and CarSim co-simulation results in single-static, double-static, and double-dynamic obstacle scenarios show that the proposed method can generate smoother trajectories and achieve more stable tracking, thereby improving obstacle-avoidance safety and ride comfort. In the double-static scenario, the peak lateral error is reduced from about 0.7 m to within 0.1 m, while in the double-dynamic scenario the longitudinal speed is maintained within 78–80 km/h instead of dropping to about 67 km/h under the baseline controller. The study provides a practical technical framework for integrated decision-planning-control design in structured-road intelligent vehicles. Full article

Polyamide (PA) is widely used as a high-performance engineering thermoplastic in automotive components and textiles, due to its superior mechanical strength and chemical resistance. However, the increase in PA waste has posed significant challenges to resource sustainability and environmental protection. Despite breakthrough development achieved in PA recycling, key barriers remain in process scale-up and high-value recovery. This review examines the current state of PA recycling, analyzing the research prospects of mechanical and chemical recycling from economic feasibility and environmental impact. We present discussions on innovative recycling approaches for PA, including upcycling, molecular design of novel PA derivatives, chemo-biological coupling and solvent-based recovery, offering potential solutions to the sustainable circular economy and green cycles. Finally, by presenting case studies, we highlight pathways toward future innovation that inform industrial-scale implementation. Full article

Cerium dioxide (CeO₂) has emerged as a structurally versatile oxide for dye-wastewater purification because its architecture, porosity, and surface accessibility can be tuned over a wide range while maintaining good chemical stability and environmental compatibility. Recent studies show that template-free or low-template routes can generate porous, mesoporous, multilayered, and flower-like CeO₂ architectures with rapid dye uptake and, in some systems, adsorption-assisted photocatalytic removal. However, CeO₂-based dye removal has often been discussed either within broad surveys of environmental applications or from composition-centered viewpoints, whereas the more fundamental question is how synthesis route controls architecture formation and how architecture, in turn, governs adsorption and subsequent removal behavior. This mini-review addresses that question from a morphology-centered perspective. It first examines template-free and low-template routes for constructing structured CeO₂, then discusses how porosity, hierarchical assembly, and surface accessibility regulate adsorption kinetics and equilibrium capacity in dye-containing aqueous systems. It further considers adsorption-assisted photocatalytic removal and argues that dark adsorption should be regarded as the structural first step rather than a secondary contribution. On this basis, the review shows that rare-earth doping in these systems is most usefully understood as a secondary tuning strategy that refines an already favorable host architecture by modifying surface interaction, optical response, or reactive-species generation. Overall, the available evidence indicates that CeO₂-based dye-wastewater purification is most meaningfully interpreted through a route–architecture–function framework in which morphology defines the host, adsorption organizes the local reaction environment, and doping serves mainly as structure-assisted tuning. This perspective shifts the design logic of CeO₂ from empirical performance optimization toward rational structure-directed construction of integrated removal platforms. Full article

This work presents a case study detailing an end-to-end workflow for reconstructing a damaged plastic component when no original design data are available. The approach integrates microscopic inspection of fracture surfaces, selective enhancement of 3D scan data, CAD-based modification of geometrically and functionally critical features, and continuous fibre-reinforced additive manufacturing. The component examined functions as a structural mounting element in an automotive lighting module, where it maintains correct alignment and provides mechanical support in service. The study concentrates on the cost-effective replacement of unique parts produced in very small batches. The results indicate that this fracture-analysis-informed reverse engineering strategy offers a practical solution for reproducing low-volume, custom, or replacement components in situations where standard manufacturing methods are not economically viable. The reconstructed part matched the geometry necessary for installation in the original assembly and successfully passed initial functional checks; however, this study did not include quantitative measurements of mechanical performance. Full article

Extracting periodic fault pulses caused by gear surface fatigue in reducers is often hindered by transmission path interference and strong background noise. Moreover, the traditional Variational Mode Decomposition (VMD) and Maximum Correlation Kurtosis Decomposition (MCKD) method rely on manual parameter selection, which limits its practicality. To address these issues, this paper proposes a parameter-adaptive VMD-MCKD method based on vibration signals for extracting gear surface fatigue fault features. Using the reciprocal of the peak indicator squared of decomposed signals as fitness functions, the method employs the global search capability of the Sparrow Search Algorithm to adaptively select optimal VMD-MCKD configurations. The optimized VMD-MCKD method is applied to decompose gear surface fatigue fault signals, effectively filtering out noise while highlighting periodic fault pulses caused by gear fatigue. Envelope demodulation is then performed to extract characteristic frequency components of gear surface fatigue faults. Experimental results demonstrate that the proposed method can adaptively extract periodic fault pulse components from strong noise environments, achieving a 2-fold improvement in signal kurtosis and enhanced robustness. Full article

The time-varying mesh stiffness excitation of helical gears impacts the vibration state of the rotor–bearing systems, while the existence of mechanical dynamic eccentricity makes the rotor–bearing dynamics equation a system of parametric excitation. To address this situation, the time-varying mesh stiffness of the helical gear is substituted into the coupled bending–torsion–axial dynamic equation of the rotor–bearing system. By considering dynamic eccentricity, the rotor’s vibration displacement response is calculated. The unified strength theory is introduced to compute the complex stress state. The study’s results indicate that time-varying stiffness significantly influences the system’s vibration characteristics, with the equivalent stress values exceeding those under twin-shear stress. This finding demonstrates the advantage of using the unified strength theory under high-load conditions, providing an essential reference for optimizing the dynamic performance of high-speed helical gear transmission systems. Full article

Large-scale aerospace components (e.g., wings, fuselage sections, wing boxes, and rocket segments) feature large dimensions, low stiffness, complex interfaces, and strict assembly tolerances. Traditional rigid tooling and manual alignment struggle to meet the demands of high precision, efficiency, and flexibility in modern aerospace manufacturing. This paper presents a structured literature review on the automated assembly of large-scale aerospace components, summarizing advances in three core domains: pose adjustment and positioning mechanisms, digital measurement technologies, and trajectory planning and control. Particular emphasis is placed on two cross-cutting themes: measurement uncertainty analysis and flexible assembly, which are critical for high-quality docking. The review classifies pose adjustment mechanisms into four categories (NC positioners, parallel kinematic machines, industrial robots, and novel mechanisms) and digital measurement into five branches (vision metrology, large-scale metrology, measurement field construction, uncertainty analysis, and auxiliary techniques). It also outlines five trajectory planning and control routes, covering traditional methods, multi-sensor fusion, digital twins, flexible assembly, and emerging intelligent approaches. The analysis reveals that current research suffers from fragmentation among mechanism design, metrology, and control, with insufficient integration of uncertainty propagation and flexible deformation modeling. Future systems will rely on heterogeneous equipment collaboration, uncertainty-aware closed-loop control, high-fidelity flexible modeling, and digital twin-driven decision-making. This review provides a unified framework and a technical reference for developing reliable, flexible, and scalable automated assembly systems for next-generation aerospace structures. Full article

The present paper proposes an adaptive steering weight allocation strategy based on a non-cooperative Stackelberg game and Model Predictive Control (MPC) for dynamic steering authority allocation in human–machine shared control of intelligent vehicles. First, the human–machine steering interaction is modelled as a Stackelberg game, and the steering control problem is formulated as an MPC optimization problem. The optimal control sequences of the driver and the Advanced Driver Assistance System (ADAS) under game equilibrium are then derived through backward induction. Subsequently, driver behaviour is classified as aggressive, moderate, or conservative according to lateral preview error and lateral acceleration, and the driver state is quantified using parametric indicators. Furthermore, by integrating potential field-based driving risk assessment with human–machine conflict intensity, a fuzzy logic-based dynamic weight adjustment mechanism is constructed. Simulation results show that when the steering intentions of the driver and the ADAS are highly consistent, the proposed strategy can effectively reduce driver workload and improve driving safety. In high-risk driving situations, the strategy automatically transfers more steering authority to the ADAS to enhance safety, whereas under low-risk conditions with strong human–machine steering conflict, greater driver authority is preserved to ensure that the vehicle follows the intended path. Hardware-in-the-loop experiments in lane-changing assistance scenarios further verify the effectiveness of the proposed strategy under different driving styles. Quantitative results show that, compared with manual driving, the proposed strategy reduces the maximum lateral overshoot by 98.75%, 85.54%, and 98.58% for aggressive, moderate, and conservative drivers, respectively. In addition, the peak yaw rate and driver control effort are significantly reduced, indicating smoother vehicle dynamic response and lower steering workload. These results demonstrate that the proposed strategy can effectively improve lane-change stability, reduce driver burden, and maintain safe and coordinated human–machine shared control. Full article

Hybridization in vehicle powertrains extends beyond the aggregate system level and can target individual components to enhance engine performance. While prior studies have highlighted the performance benefits of electrified turbochargers, this work focuses on mitigating engine-out emissions for a medium- to heavy-duty diesel engine with an electrified airpath. Unlike conventional engines and actuators, the alternative engine architecture with an electrified airpath provided superior airpath control. This is critical for fuel-led diesel engines, where the initial combustion cycles during the tip-in phase of a transient operate at a rich equivalence ratio. In this work, a 3.2 L two-cylinder opposed piston two-stroke (OP2S) engine equipped with an Electrically Assisted Turbocharger (EAT) and an electrically operated EGR pump was experimentally tested in a Hardware in the Loop (HIL) setup under transient conditions. Actuator positions were varied to identify strategies that mitigate soot and NO_x without compromising transient response. The experiments are discussed case-wise, where the effects of each airpath actuator, including fuel rate shaping, are analyzed, showing to what extent each strategy mitigates emissions. At the end, an optimized case is presented to the readers for their perusal. The electrified airpath, along with fuel rate shaping, demonstrated cumulative soot reduction up to 92% and NO_x emissions by 77% for a transient load step between 3 and 13 bar BMEP at a mid-engine speed of 1250 rpm. Full article