Search Results (908)

Carbon fiber-reinforced thermoplastic composite drilling is a secondary manufacturing process because the quality of drilled holes affects assembly system performance, structure, and sustainability. This paper compares all drill coating types and cutting conditions for PEEK-CF30 composite drilling utilizing a hybrid experimental–statistical method. DLC-, TiN-, and TiCN-coated HSS drills, as well as cutting speed and feed rate were tested using the Taguchi L27 design. Performance indicators were measured by including thrust force, surface roughness, drilling torque, and energy consumption. Experimental results showed that increasing cutting speed and feed rate increased the thrust force while decreasing torque and energy consumption. Smearing on the hole surface, chip adhesion, and short fiber adhesion/pull were identified as indicators of poor surface quality, and these occurrences increased with increasing drill coating removal at high cutting parameters. In terms of overall performance, the TiCN-coated drill created the lowest thrust force (50.85 N), surface roughness (1.038 µm), torque (17.54 Ncm), and energy consumption (136.45 J) at high feed conditions. Taguchi-based gray relational analysis methodology revealed that the TiCN-coated drill, a cutting speed of 40 m/min, and a feed rate of 0.1 mm/rev are the optimum parameters. Second-order prediction models developed for all responses proved to have high predictive capabilities with coefficients of determination above 94%. Ultimately, drill coating quality considerably affected surface integrity and drilling energy consumption performance in drilling PEEK-CF30. A hybrid optimization and modeling framework demonstrates that the drill quality cutting parameter will allow for optimum selection to ensure efficient processing of advanced thermoplastic composites. Full article

UAV-assisted data collection often suffers from spatial data holes and communication unfairness, a challenge exacerbated in Wireless Powered Communication Networks (WPCNs) by the inherent doubly near-far problem. To bridge these gaps, this paper proposes a novel Spatio-Temporal Trajectory-Driven Dynamic Time-Division Multiple Access (STD-TDMA) scheduling strategy. Deviating from conventional discrete hovering paradigms, we introduce a continuous-flight framework that exploits the UAV’s mobility to provide seamless spatial coverage. By jointly optimizing the UAV’s flight speed and dynamic time-slot allocation, the proposed strategy ensures that each sensor node can interact with the UAV at its optimal channel condition along the trajectory, thereby effectively mitigating the doubly near-far effect and ensuring quality of service-based fairness. To solve the formulated non-convex optimization problem, we develop a low-complexity algorithm that integrates Binary Search for speed optimization with the Hungarian algorithm for spatio-temporal mapping. Extensive simulations demonstrate that our STD-TDMA strategy significantly enhances nodal fairness and boosts overall task execution efficiency compared to conventional baseline schemes. Full article

Nano-TiO₂ is widely used in many industrial fields due to its unique physical and chemical properties. In recent years, it has become a core material in the research of road engineering for degrading automobile exhaust. Under ultraviolet irradiation, it can excite electron-hole pairs and use its strong redox capacity to decompose automobile exhaust and improve air quality. From the perspectives of materials, performance and engineering application, this paper briefly describes the structure and physicochemical properties of nano-TiO₂, reviews the recent research progress of nano-TiO₂ in the photocatalytic degradation of automobile exhaust, systematically compares the effects of various strategies such as incorporation methods and modified materials on exhaust degradation efficiency, and conducts a quantitative analysis of performance differences. It is pointed out that insufficient road durability, poor compatibility with pavement materials and limited adaptability to unconventional environments are the main current problems and challenges in this research direction. The future development directions such as developing self-healing composite systems and constructing machine learning prediction models are also prospected. Full article

To enhance the performance of the Social Network Search (SNS) algorithm in solving complex numerical optimization problems, this paper proposes a Multi-strategy Enhanced Social Network Search (MESNS) algorithm. The original SNS simulates human social behaviors through four decision-making emotions—imitation, conversation, disputation, and innovation—to perform population-based search. However, its uniform emotion selection mechanism and purely random interaction strategy may reduce convergence efficiency and weaken exploitation capability, particularly in the later stages of optimization. To overcome these limitations, MESNS incorporates three improvement strategies. First, an adaptive decision-making emotion selection mechanism is developed to dynamically adjust the probabilities of exploration and exploitation behaviors according to the iteration progress, thereby promoting a more symmetric and coordinated search transition over time. Second, an elite-guided communication strategy is introduced to enhance information propagation by integrating high-quality individuals into the interaction process, which improves convergence while maintaining population diversity. Third, a dynamic interaction radius adjustment mechanism is designed to adaptively regulate the search step size, achieving a better balance and dynamic symmetry between global exploration and local refinement. Extensive experiments are conducted on the IEEE CEC2014, CEC2017, and CEC2022 benchmark suites under multiple dimensional settings. The results demonstrate that MESNS achieves superior optimization accuracy, faster convergence speed, and improved solution stability compared with several state-of-the-art metaheuristic algorithms. Furthermore, the proposed algorithm is successfully applied to the three-dimensional wireless sensor network deployment optimization problem, where it produces a more uniformly distributed and spatially balanced sensor layout, reduces coverage holes and redundant overlaps, and thus exhibits desirable symmetry in deployment structure and sensing coverage. These findings indicate that MESNS is an effective and competitive optimization framework for complex global optimization tasks with both theoretical significance and practical value from the perspective of symmetry. Full article

The surface quality of machined gears is closely related to operational energy efficiency and service durability, which affect the achievement of dual carbon goals in sustainable manufacturing. This study proposes a radial pre-stressed grinding method for gear manufacturing. Firstly, an analytical model for the radial pre-stress exerted on the gear inner hole was established by virtue of thick-walled cylinder theory. Secondly, a simulation and experiment were conducted under the same pre-stress conditions to obtain the radial stress. The theoretical, simulated, and experimental results were compared and discussed. Then, gear grinding simulations were performed at different pre-stress levels, grinding depths and grinding speeds. Finally, the grinding parameters were optimized by means of response surface methodology (RSM). This study recommends incorporating gears manufactured with radial pre-stressing into relevant industrial standards for green and low-carbon development. The results indicate that applying radial pre-stress to the gear inner hole significantly influences surface roughness and residual compressive stress after grinding, whereas it exhibits a minimal effect on grinding force. After optimization, compared with the initial simulation results, surface roughness is reduced by 12.5%, the absolute value of residual compressive stress is increased by 52.6%, and grinding force is decreased by 2.1%. The implementation of radial pre-stressed grinding in gear manufacturing requires institutional support, including its integration into green standard institutions, the development of technical specifications, and the establishment of promotion mechanisms. Such integration can be facilitated through national ‘Green Factory’ initiatives, comprehensive intellectual property protection, and targeted personnel training. Full article

To improve the blasting performance of tunnel wedge cutting while mitigating vibration effects, this study proposes a precise delayed blasting method and evaluates its effectiveness through a three-dimensional numerical simulation, similarity model test, and field application. The proposed method divides the cut holes into initial and secondary groups and uses electronic detonators to control the delay time. The numerical results show that delayed blasting reduces the peak stress in the surrounding rock, accelerates stress-wave attenuation, improves cavity integrity, and lowers the peak particle velocity (PPV), while maintaining sufficient rock breaking capacity. Model tests conducted under different delay times indicate that the delayed scheme increases the pull efficiency, decreases the ratio of large fragments, and reduces the PPV, with an optimal delay time range of 4~8 ms for moderately weathered limestone. Field tests in the Da Balai Tunnel further verify the effectiveness of the proposed method. Compared with conventional blasting, delayed blasting increases the pull efficiency from 77.8% to 97.3%, reduces the large fragment ratio from 30.6% to 11.4%, decreases the PPV by 52.5%, and increases the dominant vibration frequency by 48.7%. These results demonstrate that the proposed method can simultaneously enhance the rock-breaking quality and vibration control, providing practical guidance for tunnel blasting excavation under complex geological conditions. Full article

Queen bees form the core of honeybee colonies for reproduction, and their quality is the most critical factor affecting their reproductive and productive performance. In apicultural production, queen rearing requires beekeepers to perform manual larval grafting. This is strongly limited by the beekeepers’ eyesight and technical proficiency and has become a bottleneck restricting the development of modern apiculture. To overcome this long-standing technical challenge, we designed beeswax-based tools for queen rearing without grafting larvae for Apis mellifera. The tools consist of three core components: a single-sided hollow beeswax comb foundation, beeswax larval holders and beeswax queen cells with a hole at the bottom. The holders are paired with the hollows of the beeswax comb foundation and the hole of the beeswax queen cells. Following the construction of the comb by honeybees on the hollow foundation, the queen was confined to lay eggs on the single-sided comb. Subsequently, larval holders containing eggs or larvae were pulled out, assembled with beeswax queen cells, embedded in the buckles of queen-rearing frames, and placed into colonies for queen rearing. In order to verify the feasibility of the tools, a paired comparative experiment was conducted using Apis mellifera, with the tools as the treatment group and manual larval grafting as the control group. We evaluated multiple key indicators, including acceptance rate of queen cells, queen cell length at emergence, emergence rate, weight of newly emerged queen, morphological indices (thorax length/width, forewing width, hindwing length, head width), ovariole number and the relative mRNA expression of four queen development-related genes (Vg, Hex110, Hex70b, Jhamt). No significant differences were observed in queen cell acceptance rate and emergence rate between the two groups. However, compared with the control group, queens reared using the tools exhibited significantly greater queen cell length at emergence, higher emergence weight, superior morphological traits, more ovarioles and significantly upregulated expression of all four assayed genes. In conclusion, the tools can be used to rear high-quality Apis mellifera queens effectively with superior phenotypic and molecular traits compared to conventional grafting, which provides efficient and convenient queen-rearing tools for beekeepers. Full article

To address rapid tool wear and unstable hole surface quality during roughing and semi-finishing operations using indexable shallow-hole drills, an optimization study on the spatial mounting posture of the insert is conducted, aiming to improve tool life and machined surface quality. Considering that tool life and surface quality are significantly influenced by cutting force and cutting temperature, radial cutting force and cutting temperature are selected as the multi-objective optimization criteria. A mapping model between the insert mounting posture parameters and cutting performance metrics is established. An improved LO-NSGA-II algorithm is employed to perform multi-objective optimization, yielding a Pareto-optimal solution set, and the entropy weighted-TOPSIS method is subsequently applied to determine the optimal insert mounting posture. Experimental results demonstrate that the optimized spatial mounting posture significantly enhances the overall cutting performance of the tool. Compared with the non-optimized tool, the optimized configuration exhibits a significant extension in tool life and a notable improvement in machined hole surface quality. This study provides an effective methodology for the structural optimization design of indexable shallow-hole drills. Full article

Bacterial spot disease in peaches, also known as bacterial shot hole disease, with Xanthomonas arboricola pv. pruni (Xap) as the causal agent, poses a significant threat to peach yield and quality due to its long latency period, rapid onset, and difficulty in control. This article presents the first systematic review of research on the peach bacterial spot pathogen, Xap, comprehensively integrating the latest advances in disease distribution, pathogen identification, integrated control strategies, and mechanisms of pathogenesis and host resistance, thereby forming a complete and up-to-date knowledge framework. The aim is to provide a reference for the control of peach bacterial spot disease and to promote the sustainable and rapid development of the peach industry. Full article

Sandwich materials are increasingly used due to the possibility of improving their combined properties. However, some manufacturing operations become more complex, such as drilling, where it is more difficult to determine the optimal cutting conditions that provide the appropriate hole quality. In this context, the quality of the drilled holes of the carbon fiber plates with a foamed polyvinyl chloride core, a material used in marine environments at very low temperatures, among others, is analyzed. Due to the importance of surface quality in operations prior to the assembly of plates and the influence of delamination on the in-service behavior of materials, the objective is to determine the diameter deviation (∆D), circularity (CIR), and delamination (FD) at the entrance and exit of the hole after drilling plates of this material. This sandwich material has been drilled at low temperatures (−15, 0, and 15 °C) using compressed air as cooler. Different cutting conditions have been used regarding rotation speed and feed. An experimental and statistical study, including a response surface optimization for FD, and multiple response surface optimization for ∆D and CIR were used. Several ranges of suitable cutting conditions can be identified for each temperature. Full article

To address the poor cutting stability and deterioration of hole quality caused by the inherent trade-off between chip evacuation performance and drill-body stiffness in U-drilling, a multi-objective optimization framework was established. The design variables were the core thicknesses ${\mathrm{L}}_1$ and ${\mathrm{L}}_2$ of the inner and outer chip flutes, the inner and outer offset angles ${\mathrm{\theta }}_1$ and ${\mathrm{\theta }}_2$, and the inner and outer helix angles ${\mathrm{\beta }}_1$ and ${\mathrm{\beta }}_2$. The objectives were to maximize the chip evacuation force and minimize the drill-body strain (which serves as an equivalent indicator of maximizing drill-body stiffness). The chip evacuation force was rapidly evaluated using a mechanistic chip evacuation force model derived from mechanism-based analysis. The drill-body strain was efficiently predicted using a GA–BP neural-network surrogate model. An NSGA-II algorithm combined with the entropy-weighted TOPSIS method was employed to solve the optimization problem, yielding the optimal parameter combination for the U-drill chip-flute geometry. The results show that drilling experiments on 42CrMo under the optimal structural parameter combination reduced the cutting forces in the $x$, $y$, and $z$ directions by approximately 11.2%, 13.1%, and 11.8%, respectively. The root-mean-square acceleration in the $x$ and $y$-directions decreased by about 17.3% and 22.9%, respectively. These improvements effectively enhanced the hole-wall surface roughness and hole diameter accuracy, and further improved chip evacuation smoothness and cutting stability of the U-drill. Full article

Photonic-crystal surface-emitting lasers (PCSELs) are a new type of semiconductor laser with the potential for high-power output and high-beam-quality operation. Integrating a distributed Bragg reflector (DBR) into PCSELs can significantly enhance device performance. However, the growth of high-aluminum-content DBRs on photonic crystal layers with buried air holes presents two major challenges. First, the low mobility of aluminum atoms increases the propagation of surface roughness from the substrate into the DBR, increasing defect density. Second, the high growth temperatures required for DBR growth can deform the thermally unstable air holes. In this work, we investigated a metal–organic chemical vapor deposition (MOCVD) regrowth process for fabricating DBRs on PCSELs. By adjusting the epitaxial growth temperature and V/III ratio, we effectively controlled the diffusion of adatoms on both the sample surface and inside the holes. As a result, the root mean square (RMS) surface roughness decreased by ~96%, and uniform buried air holes were obtained, with a filling factor of ~ 18.8% and a depth of ~ 270 nm, without significant deformation. Finally, we fabricated a PCSEL device with a DBR structure, exhibiting a beam divergence angle of ~ 0.5° and a peak power of about 0.86 W. This study provides a key process solution for the development of PCSELs with high-quality DBR structures, enabling further improvement in optical output performance. Full article

Wireless sensor network (WSN) coverage optimization is a critical factor in improving network service quality, yet it faces challenges such as deployment uniformity, high-dimensional optimization, and the balance between exploration and exploitation under limited node resources. To address the shortcomings of the cultural historical optimization algorithm (CHOA), including insufficient global exploration, lack of dynamic regulation, and limited local exploitation accuracy, this paper proposes a film and television strategy-based multi-strategy cultural historical optimization algorithm (FTSCHOA). The proposed algorithm enhances performance through three synergistic mechanisms: a DE-style evolutionary operator that strengthens global exploration and population diversity; a film-and-television strategy that balances exploration and exploitation via random perturbations and adaptive parameter regulation; and a memory-based neighborhood local search that performs refined exploitation around high-quality solution sets to improve local optimization accuracy. Extensive experiments conducted on the CEC2017 and CEC2022 benchmark suites with dimensions of 10, 20, 30, and 50 demonstrate that FTSCHOA outperforms comparative algorithms in terms of optimization accuracy, convergence speed, and stability. The Friedman mean rank test indicates that FTSCHOA consistently achieves the best average ranking, while the Wilcoxon rank-sum test confirms that its performance differences with respect to competing algorithms are statistically significant ($p<0.05$). When applied to WSN coverage optimization in a $100\hspace{0.17em}\mathrm{m}\times 100\hspace{0.17em}\mathrm{m}$ monitoring region, FTSCHOA achieves coverage rates of 0.9351 and 0.9738 with 25 and 30 sensor nodes, respectively, which are significantly higher than those obtained by PSO, GWO, CHOA, and other algorithms. Moreover, the resulting node deployments exhibit greater uniformity, fewer coverage holes, and lower redundancy. The experimental results demonstrate that FTSCHOA effectively overcomes the limitations of traditional algorithms and provides an efficient and practical solution for WSN node deployment optimization, with strong potential for application in real-world scenarios such as environmental monitoring and smart agriculture. Full article

This study addresses the inline dielectric characterization of liquids using a prototype planar resonant sensor with two capacitively coupled spirals, fabricated by inkjet printing on a Rogers RO4003C substrate. The device includes a central hole designed to host a sample vial or a pipe, enabling contactless characterization of liquid solutions, including biological samples. Experimental validation includes stylus profilometry and optical microscopy to verify the thickness, uniformity, and continuity of the conductive film, as well as scattering parameter measurements in the frequency range from 3.5 GHz to 4.0 GHz. The frequency response exhibits two distinct resonances; the corresponding resonance parameters for each mode (resonant frequency $f_r$, amplitude, and quality factor Q) were extracted through complex-domain fitting using Lorentzian profiles. The electrical characterization of the device was assessed as a function of the effective permittivity of water–ethanol test mixtures by varying the ethanol volume fraction. The proposed sensor showed a monotonic and nearly linear response to ethanol concentration, with frequency sensitivities of approximately 20 kHz/% and coefficients of determination up to $R^2=0.99$. Full article

Die design plays a critical role in achieving high-quality aluminum extrusion products with optimal efficiency. Porthole dies are widely employed to produce hollow profiles for diverse industrial applications, yet their design parameters significantly influence surface quality, geometry, and productivity. In this study, a two-hole porthole die was investigated using both numerical and experimental approaches. The 6060 aluminum alloy (produced in the foundry of Alumil SA, Kilkis, Greece) was selected as the material of focus. Finite Element Analysis was conducted with HyperXtrude™ 2022 software, while experimental trials were performed on a 35 MN extrusion press. To further enhance productivity, a liquid nitrogen cooling system was integrated into the process. The combined numerical and experimental results demonstrated that the redesigned die and the integration of liquid nitrogen cooling significantly improved process performance. Productivity increased by 8.76%, with ram speed rising from 6.8 mm/s to 9.5 mm/s while maintaining dimensional accuracy and stable extrusion conditions. Full article