This study investigates the factors influencing micropore formation during the selective laser melting (SLM) process of 2219 aluminum alloy. A mesoscopic evolution model for SLM of 2219 aluminum alloy was developed using Ansys and other software, considering the temperature-dependent thermophysical properties of the alloy. The results showed that the temperature, surface tension and flow velocity of the molten pool under different process parameters would affect the formation of micropores during the scanning process, and the temperature difference would change the surface tension and further affect the flow velocity of the molten pool. The flow state of molten pool and the distribution of micropore morphology are also different. Adjusting the combination of laser power and scanning speed can produce a better effect on the mesoscopic micropore evolution of 2219 aluminum alloy. The study demonstrates the effectiveness of using Ansys-Fluent and its secondary development port to control the physical phenomena during the SLM scanning process, providing numerical simulation results of molten pool flow and monitoring the evolution of mesoscale micropores. This approach offers a theoretical basis for optimizing actual processing conditions.

To enhance the understanding of the laser additive manufacturing process for aluminum alloy and corresponding composites, a thermal coupling finite element simulation method was employed to investigate the temperature and stress field distributions within aluminum alloy and composites during multi-pass laser cladding under varying laser process parameters. The results showed that when the laser power was 260 W, the scanning rate was 600 mm/s, and the laser energy density was 120.37 J mm-1, the peak temperature in the molten pool could reach 1 776.93 ℃. With the increase of the laser energy density, the peak temperature gradually increased, and the width and depth of the molten pool gradually increased. Affected by the heat conduction of the adjacent laser melt pool, the temperature in the boundary area of the solidified melt pool would be raised to 1030 ℃, and a remelting occurred, while the temperature in the central area of the melt pool was raised to 300~450 ℃, and no remelting occurred. The thermal stress of SiC/AlMgScZr composite was obviously higher than that of aluminum alloy, and the high thermal cracking tendency made the composites difficult to fabricate. Proper preheating, reducing the temperature gradient and reducing the thermal stress of laser cladding could be helpful to reduce the cracking tendency of laser forming composites.

The forming quality of selective laser melting (SLM) is mainly determined by the compound effects of scanning strategys and process parameters. This study investigates these combined effects using two scanning strategies—line scanning and checkerboard scanning—supplemented by a remelting process. The study focuses on the influence of suitable remelting power (110 W~170 W) and remelting times (once to twice) on the molding quality of specimens. The test results indicate that within the suitable remelting power and times, the checkerboard strategy with 110 W remelting power and two remelting passes significantly improves surface quality. The corresponding test specimen achieved a relative density of 99.54%, a roughness value of 18.0 m, a tensile strength of 1 010.2 MPa, and an elongation of 3.76%. Fracture analysis revealed that un-remelted specimens exhibited large brittle fractures, while once- and twice-remelted specimens showed ductile fracture characteristics, indicating enhanced mechanical performance. Microstructure analysis showed that specimens with 110 W remelting power and two remelting passes had uniform and dense microstructures with parallel needle-like martensite ′ phases. When remelting power was increased to 170 W and remelted twice, the specimen achieved the highest microhardness of 543.6 HV.

To address the automotive industry′s demands for lightweight, safety, and energy efficiency, laser welding of high-strength and ultra-high-strength steels has gained widespread application. In this paper, laser lap welding of dissimilar ultra-high-strength steels QP1180 and 22MnB5 was conducted to explore their adaptability to the laser welding process. The influences of process parameters on the microstructure and mechanical properties of the laser-welded joints were studied using optical microscopy (OM), scanning electron microscopy (SEM), Vickers hardness tester, hydraulic tensile testing machine, and other equipment. The results showed that under the selected process parameters, full penetration was achieved in all welded joints. With the increase of heat input, the macroscopic morphology of the weld seam changed from "hyperbolic" to "inverted trapezoidal", and the width of weld seam and heat-affected zone increased with the increase of heat input. Hardness measurements revealed that hardness values increased with heat input, though no complete softening was observed. Tensile strength of the welded joints ranged from 595 to 610 MPa, while elongation at break varied between 17.1% and 18.1%. The tensile strength and elongation at break were both between QP1180 and 22MnB5, and the fracture position of the tensile specimen occurred at the base metal of the 22MnB5 side, showing a uniform distribution of dimpled morphology, which belonged to ductile fracture.

Fiber laser is used to cut carbon steel plate with different thickness at short distance and long distance to study whether fiber laser is suitable for cutting carbon steel plate. Experimental results indicate that selecting an appropriate cutting speed significantly enhances the slit surface quality of carbon steel plates. The fiber laser demonstrated the capability for fine cutting of carbon steel plates up to 30 mm thick at short distances and rough machining of plates up to 50 mm thick at long distances. These findings highlight the potential of fiber lasers to meet diverse industrial cutting requirements.

To study the impact of temperature transfer between different channels in multi-channel cladding and explore the selection of process parameters for successful preparation of melted coatings, COMSOL Multiple-Field Numerical Simulation Coupling Software was used to melt multi-channel WC-12Co coating onto the surface of M2 high-speed steel substrate. The simulation temperature influence law was experimentally verified. The results indicate that the temperature transfer greatly affects each pass of the cladding layer during the preparation of the next two passes, with less influence on the next third pass. The heating rate of the first four channels differs from that of subsequent channels in the multi-channel melting process. Multichannel cladding with lower power is more advantageous in reducing heat accumulation and successfully preparing cladding coatings. When the laser power is 900 W, the laser energy during the preparation of the cladding coating matches well with the degree of thermal influence between adjacent subsequent channels, resulting in a cladding coating with better macroscopy, fine structure, and no defects.

High-speed laser cladding was utilized to prepare Inconel625 alloy coating on the surface of 304 stainless steel to improve the wear resistance of its components. Process parameters were optimized using feed rate, laser power, and scanning speed as variables, with hardness and width of the cladding layer as characterization metrics. Analysis of variance and extreme value analysis of orthogonal experiments were used to optimize these parameters, and the surface morphology of the cladding was examined. The physical composition of the cladding layer was detected using X-ray diffraction. Wear performance and morphology were analyzed using a friction and wear testing machine and scanning electron microscopy (SEM). The results show that the optimal combination of cladding process parameters is: laser power of 1 000 W, powder feeding rate of 3.0 r/min, scanning speed of 55 mm/s; the cladding layer phase mainly consists of Fe0.64Ni0.36, Mo2C, Cr2Fe14C, NbC and other phases, which are enriched with a large number of hard phases and solid solution organizations. The friction coefficient of the base material is 0.850, and the friction coefficient of the fusion cladding layer is 0.504, which indicates that the wear resistance of the fusion cladding layer is better than that of the base material, and the wear of the fusion cladding layer is only 38.46% of that of the base material, which further indicates that the Inconel625 coating can significantly improve the wear resistance of 304 stainless steel.

To investigate the influence of laser processing parameters on the structural parameters of microstructures on the surface of cemented carbide, a nanosecond laser was employed to create grooved microstructures on YG8 cemented carbide. A one-factor test was conducted to analyze the variation in groove width and depth under different laser parameters. The results of one-factor test show that: the groove width and depth with the laser parameters of the law of change is consistent, both increase with the increase in scanning power, decrease with the increase in laser repetition frequency, decrease with the increase in scanning speed, increase with the increase in scanning times. In addition, the laser repetition frequency has a greater impact on the width of the groove than on the depth of the groove; the scanning power, scanning speed, and scanning times have a greater impact on the depth of the groove than on the width of the groove.

Based on the dual closed-loop control strategy of binocular vision and ultraviolet radiation feedback, a low-power intelligent laser rust removal system is designed. The binocular camera is used to shoot the workpiece, and the computer obtains the three-dimensional coordinate information of the rust area, and identifies the rust area based on the HSV color space conversion method. The distance between the laser light outlet and the rust surface is adjusted according to the three-dimensional coordinate information to avoid underablation. During low-power laser rust removal, a wide bandgap semiconductor photoelectric sensor detects the UV component of plasma, enabling real-time laser adjustment to avoid overablation. The dual closed-loop strategy is used to control the laser to remove rust in a reasonable ablation range. The results show that adaptive rust removal can be achieved for workpieces with uneven thickness and density of rust layer. The low-power laser rust removal system can avoid uneven rust removal and workpiece damage, and achieve precise rust removal.

Aluminum alloy surface exists naturally occurring oxide film, which is prone to defects such as porosity in the aluminum alloy body welding process. Laser cleaning is an effective method to remove aluminum alloy oxide film. This study investigates the energy density window for nanosecond pulsed laser cleaning of aluminum alloy oxide films by examining the physical and chemical behaviors of oxide film removal under pulsed laser action. The laser with a maximum average power of 100 W was used for laser cleaning. The physical and chemical behaviors of vaporization and thermal vibration peeling during the process were studied by a high-definition camera system. Surface morphology and oxygen mass fraction after laser cleaning were also studied. A numerical model was established to verify the observed physical and chemical behaviors. The average power vaporization and melting thresholds were derived. As the energy density increases, the thermal vibrational peeling phenomenon gradually becomes more intense. The oxide film removal mechanism changes from melting and vaporization to thermal vibrational peeling mechanism. The optimal process window for oxide film removal is 18 J/cm2~30 J/cm2, and the effective removal of aluminum alloy oxide film can be achieved by laser cleaning within the window.

The V-shaped steel is crucial for connecting road and railway structures in dual-use mega-sized bridges. This article proposes an intelligent extraction method for V-shaped steel based on template matching using unmanned aerial vehicle airborne LiDAR point clouds. The method involves centralization and two-dimensional principal component analysis to achieve coordinate transformation of bridge point clouds, establishing an independent coordinate system for the bridge. A complete individual segment of the V-shaped steel is manually segmented as a template point cloud, and a template matrix is established. Using the length, width, and height of the template point cloud as parameters, a projection matrix is created for each point corresponding to points within the bounding box. Finally, a similarity criterion is established, and V-shaped steel point clouds are extracted based on the similarity between the projection matrix and the template matrix. The results show that the proposed method achieves extraction accuracy exceeding 90%, providing a valuable theoretical and practical approach for maintaining V-shaped steel in mega-sized bridges.

To address the low efficiency and poor accuracy of hidden danger detection in UAV inspections of transmission channels using traditional methods, this paper proposes a 3D point cloud-based method for detecting hidden dangers in transmission channel space, which effectively enhances detection accuracy and efficiency. Firstly, an adaptive density down-sampling algorithm is designed to achieve sparse and density homogenization of point cloud data, and the aerial point cloud and ground object point cloud are separated by an elevation grid algorithm. Secondly, the traditional RANSAC algorithm is improved, and the seed point selection method and inner point determination function are optimized by introducing curvature factor to achieve power line point cloud extraction. Finally, the KD-Tree structure is constructed to determine the hidden danger region and the hidden danger is classified by the method of Angle variance. Through field data collection experiments, the results show that the proposed method can effectively detect the spatial hidden dangers of transmission channels, the accuracy and recall rate of power line point cloud extraction can reach 96.8% and 97.1%, and the accuracy rate of spatial hidden dangers detection can reach more than 96%. Compared with the traditional method, the proposed method has obvious advantages in the accuracy and efficiency of the hidden trouble detection in the transmission channel space, and has good practical value in the intelligent inspection of the transmission channel.

The Fine segmentation of 3D laser point clouds is a challenging aspect of 3D reconstruction, often resulting in over-segmentation or under-segmentation. Addressing the complexity of vertical segmentation in point cloud buildings and the suboptimal classification outcomes, this paper presents an improved supervoxel over-segmentation algorithm that integrates normal vector angles and feature distances. Firstly, octree is used to screen seed voxels in 3D point clouds. Secondly, the similarity between seed points and non-seed points is judged by combining normal vector angle and feature distance to realize supervoxel over-segmentation, and the points with unreliable normal vectors generate in the over-segmentation process are marked. Finally cluster supervoxels semantically by using region growing algorithm, and reassign marked points by using kd tree. Experimental results show that the proposed algorithm can generate relatively complete semantic clustering of building facades, and the segmentation accuracy is 91.65% and 90.5%. Compared to the VCCS algorithm and a boundary-enhanced supervoxel over-segmentation approach, the segmentation accuracy is improved by nearly 30%.

Water content in polyetherimide (PEI) materials is one of the critical factors influencing their quality. Terahertz time-domain spectroscopy (THz-TDS) technique was employed to detect the THz spectra of PEI samples with varying water content. The time-domain spectra were obtained, along with the corresponding variations in the maximum probe current and absorption coefficients. The intrinsic relationships between the maximum time-domain probe current, its variation, absorption coefficients, immersion time, and actual water content were analyzed. Predictive models based on the relationship between the maximum current variation, mean absorption coefficient, and water content were established through linear regression, and experimental validation was conducted. The research demonstrates that both PEI water content prediction models can effectively predict PEI water content, with linear correlation coefficients reaching 0.993 and 0.991, and root mean square errors of 0.0034 and 0.0078, respectively. The findings of this experimental research can provide valuable reference for future studies on novel non-destructive detection methods for water content in polymer materials.

To address the critical challenges of noise interference, low classification accuracy, and limited robustness in medium-voltage power line point cloud classification, this study presents an enhanced deep learning framework based on improved PointNet++ architecture. Initially, multiple techniques are employed to extract multi-dimensional features, including spatial information, geometric features, and local geometric features, creating a 40-dimensional feature vector for each point in the point cloud. Subsequently, PointNet++ is enhanced by incorporating a point attention module (PAM) and a group attention module (GAM), along with layer normalization and residual connection structures, to improve its detail capture capabilities and mitigate the impact of complex environments on classification performance. Finally, the paper utilizes 10 kV medium-voltage power line corridor data, collected from a specific area, to construct a dataset for validating the method. Experimental validation demonstrates superior performance over conventional machine learning methods and baseline PointNet/PointNet++ models, achieving respective improvements of 1.6%, 5.3%, and 4.6% in precision, recall, and F1-score compared to PointNet++ (XYZ+Features). Visualization analyses confirm the critical role of attention mechanisms in enhancing structural feature clarity and environmental differentiation. The proposed method demonstrates greater accuracy in medium-voltage power line point cloud extraction, clearer structural features, and higher differentiation from the surrounding environment.

Optical waveguides serve as fundamental components in integrated photonic systems, where minimizing propagation loss and enhancing refractive index modulation are critical for device performance. This study employs astigmatic beam shaping technology to fabricate low-loss optical waveguides in fused quartz (JGS1), systematically investigating the influence of laser parameters on waveguide quality and transmission characteristics. By optimizing laser processing conditions—including single-pulse energy (0.570.60 J), scanning speed (15 m/s), and eight iterative scans—straight waveguides with a propagation loss of 0.231 dB/cm and coupling loss of 0.1 dB/facet were achieved. The fabricated waveguides exhibited high geometric symmetry in cross-sectional profiles and near-field mode circularity of 0.98.

Oral mucosal diseases, characterized by diverse etiologies and treatments, remain incurable both domestically and internationally. The unique oral environment often renders conventional treatments ineffective. In contrast, the Nd:YAG laser, known for its strong penetration and therapeutic efficacy, has gained popularity in treating oral mucosal diseases. However, laser parameters currently vary, and no standardized operating guidelines exist. This paper aims to evaluate the application of the Nd:YAG laser in treating oral mucosal disorders and provide a theoretical basis for its practical use.

Objective:To evaluate the effects of intranasal photobiomodulation therapy (PBMT) on blood lipids and hepatic fat fraction in patients with hyperlipidemia.Methods:Twenty-two patients with hyperlipidemia were randomized into PBMT group and control group. PBMT group received intranasal 650 nm 10 Hz 10 mW/cm2 PBMT for 30 minutes once a day for consecutive 28 days. The control group received placebo-controlled treatment. All patients underwent three hepatic MRI IDEAL-IQ scans pre-treatment, the 14th day post-and the 28th day post-treatment to obtain hepatic fat fraction. Blood lipids profiles of two groups were collected pre-and the 28th day post-treatment. P<0.05 was considered statistically significant.Results:ANOVA showed significant systemic bias between FFpre, FF14days and FF28days in PBMT group (P<0.05) but no significant changes in control group. Tukey post-test showed that FF28days have significant changes compared with both FFpre and FF14days in PBMT group (P<0.05). However, FF14days had no significant change compared with FFpre. Paired T-test results showed that total cholesterol (TC), triglyceride (TG), high density lipoprotein (HDL-c) and low density lipoprotein (LDL-c) in PBMT group were significantly changed between pre-and post-PBMT (P<0.05), however there was no significant difference in control group.Conclusion:Long-term and repeated application of 650 nm 10 Hz 10 mW/cm2 intranasal PBMT can reduce blood lipids and hepatic fat fraction in patients with hyperlipidemia, and prevent the occurrence of liver diseases.