Overlap Rate Research Articles

Research on the Application and Performance Optimization of GPU Parallel Computing in Concrete Temperature Control Simulation

With the development of engineering technology, engineering has higher requirements for the accuracy and the scale of simulation calculation. The computational efficiency of traditional serial programs cannot meet the requirements of engineering. Therefore, reducing the calculation time of the temperature control simulation program has important engineering significance for real-time simulation of temperature field and stress field, and then adopting more reasonable temperature control and crack prevention measures. GPU parallel computing is introduced into the temperature control simulation program of massive concrete to solve this problem and the optimization is carried out. Considering factors such as GPU clock rate, number of cores, parallel overhead and Parallel Region, the improved GPU parallel algorithm analysis indicator formula is proposed. It makes up for the shortcomings of traditional formulas that focus only on time. According to this formula, when there are enough threads, the parallel effect is limited by the size of the parallel domain, and when the parallel domain is large enough, the efficiency is limited by the parallel overhead and the clock rate. This paper studies the optimal Kernel execution configuration. Shared memory is utilized to improve memory access efficiency by 155%. After solving the problem of bank conflicts, an accelerate rate of 437.5× was realized in the subroutine of the matrix transpose of the solver. The asynchronous parallel of data access and logical operation is realized on GPU by using CUDA Stream, which can overlap part of the data access time. On the basis of GPU parallelism, asynchronous parallelism can double the computing efficiency. Compared with the serial program, the accelerate rate of inner product matrix multiplication of the GPU asynchronous parallel program is 61.42×. This study further proposed a theoretical formula of data access overlap rate to guide the selection of the number of CUDA streams to achieve the optimal computing conditions. The GPU parallel program compiled and optimized by the CUDA Fortran platform can effectively improve the computational efficiency of the simulation program for concrete temperature control, and better serve engineering computing.

Engineering Process Optimization and Quality Stability Control of High-Speed Laser Cladding Coatings Based on AHP-FCE

Due to the rapid advancement in processing efficiency, high-speed laser cladding has demonstrated significant potential in the repair and protection of various substrates. In this study, we established a comprehensive evaluation model for the coating quality of Fe-Cr-Ni-based alloy with high-speed laser cladding using the analytic hierarchy process and fuzzy comprehensive evaluation method (AHP-FCE). The weights obtained through the analytic hierarchy process for forming quality, microstructure, and surface performance are as follows: WB1 = 0.1365, WB2 = 0.2385, and WB3 = 0.625, respectively. During the fuzzy comprehensive evaluation step, an evaluation level was graded while quantifying the level range through membership function judgment. By combining subjective and objective evaluations, qualitative issues were transformed into quantitative assessment methods. Through comprehensive evaluation analysis, it was concluded that the scanning speed of high-speed laser cladding had a greater impact on coating thickness compared to powder feeding speed while significantly enhancing microstructure densification. The overlap rate exerted the most influence on dilution rate homogenization of near-surface dendrites. Simultaneously, the optimal preparation technology was determined: laser power 660 W, scanning speed 14,400 mm/min, overlap rate/min. This study transforms multi-objective quality evaluation of high-speed laser cladding coatings into a single objective problem by realizing comprehensive quality quantification and providing a new method for quantitative evaluation and visualization of coating quality.

Signal-Vehicle Coordination Control Modeling and Roadside Unit Deployment Evaluation under V2I Communication Environment

Signal-vehicle coordinated control holds substantial promise for enhancing urban transportation efficiency. However, its development faces notable challenges: (1) most existing studies have been conducted based on the assumption of perfect communication conditions. This assumption overlooks the significant impact of vehicle-to-infrastructure (V2I) communication quality on control performance, which leads to poor applicability in practice. (2) The evaluation of roadside unit (RSU) deployment for optimizing signal-vehicle control has not been well studied. Hence, the modeling of signal-vehicle coordination control and RSU deployment evaluation under V2I environment are studied in this paper. First, we introduce a communication model that characterizes the imperfections in communication between RSUs and connected vehicles (CVs). Second, we propose a model for signal-vehicle coordination control within this connected environment. This model integrates strategies from both signal control optimization and the speed optimization of CV platoons. Finally, to assess the impact of the RSU deployment parameters on the performance of signal-vehicle coordination control, we introduce a systematic evaluation method. The reduction in vehicle delays is introduced as the evaluation indicator for control performance. Six other indicators—the number of vehicles in the RSU communication domain, connectivity probability between the CV and RSU, number of vehicles whose speeds are successfully optimized, number of speed adjustments, green extension time, and overlap rate of the communication domains of multiple RSUs—are introduced as the observation indicators. The simulation experiments verify the effectiveness of the proposed model in implementing signal-vehicle coordination control under imperfect communication and environments in low-traffic, medium-traffic, and high-traffic scenarios. Furthermore, these experiments show the quantitative impact of RSU deployment parameters (communication distance, command transmission cycle, installation position, and number of RSUs) on control performance.

Curved fiber compound eye camera inspired by the Strepsiptera vision.

The Strepsiptera vision possesses intriguing features of a large field of view (FOV) and relatively high resolution compared to normal compound eyes. However, it presents a significant challenge of the mismatch between the curved compound eyelet lens array and the planar image sensor to image in a large FOV for artificial compound eyes (ACE). We propose what we believe to be a novel curved fiber compound eye camera (CFCEC) here, which employs coherent fiber bundles as the optical relay system to transmit sub-images curvilinearly. A total of 106 eyelets are arranged based on a scheme similar to the Goldberg polyhedron, with the advantages of uniform interval and minor edge blindness. Then, a prototype of the CFCEC is fabricated and assembled. A series of experiments are conducted to assess the FOV, contrast, resolution, and overlap rate of FOV of the prototype. The results prove that the CFCEC has a total FOV of up to 160°×160° and a total overlap rate of FOV of approximately 65%, demonstrating the promising potential of the CFCEC in various applications, such as panoramic surveillance, 3D detection, and motion tracking.

The forming quality of Tungsten-Carbide coatings synthesized in situ by laser remelting

The work aimed to improve the forming quality of multi-pass coatings synthesized by laser remelting in situ. The influence-relation model of the overlap rate on surface flatness and dilution rate of coatings was constructed by the single-factor method. The functions of laser power, scanning speed, defocusing distance, and scanning mode on the surface flatness and pore area of remelted coatings were studied by mixed horizontal orthogonal test, and the influence law of process parameters on surface flatness and internal pore area was revealed. Flatness increased first and then decreased with the increased overlap rate. Energy acting on the substrate decreased, and the dilution rate decreased. When the dilution rate was satisfied, the overlap rate corresponding to the maximum value of the flatness fitting curve was 26.7%. The scanning speed and laser power of remelting significantly affected coating flatness and the signal-to-noise ratio of the pore area. The signal-to-noise ratio of flatness to the pore area was positively correlated with laser power and negatively correlated with the scanning speed. When the scanning speed of remelting decreased, the duration of the molten pool increased, and its solidification rate decreased. Therefore, bubbles in the molten pool had sufficient time to overflow, which increased coating flatness and decreased the internal pore area.The optimum process parameters under multi-index optimization of integrated flatness and pore area were as follows using grey relational analysis: the laser power of 1,600 W, scanning speed of 3 mm/s, a defocusing distance of 10 mm, and parallel cladding direction. Sticky powders in the coating disappeared under the optimal remelting process parameters, and flatness and the internal pore area were improved. Maximum hardness was increased from 1,281.7HV to 1,454.2 HV, with an increase of 13.46%. The grain size was small and hardness was improved due to the increased tissue density in the remelting area of the coating.

GFII: A new index to identify geological features during shield tunnelling

Geological features play an essential role in ensuring the safety and enhancing the construction efficiency of shield tunnelling. However, owing to the concealed nature of the excavation environment, these features remain unobservable. Relying on a single shield parameter is insufficient to determine these geological features owing to the lack of detailed geological data. Consequently, a novel index, called geological feature identification index (GFII), has been introduced. This index incorporates shield parameters and employs various weighting techniques. First, the forces exerted on the shield machine throughout the tunnelling process are analysed. The shield parameters obtained from field recordings and their corresponding weights, which are affected by geological features, are evaluated using different weighting techniques. Subsequently, the GFII is used to assign index value to the geological conditions based on their resistance to the tunnelling procedure. The results reveal that both cutterhead torque and shield thrust weights are profoundly influenced by various geological features. Notably, the entropy-weighted GFII shows superior performance, evidencing a minimal overlap rate (19.4%) for hard rock. Thus, GFII can better represent the geological features compared to the fuzzy C-means algorithm classification and other existing indices. Furthermore, any pronounced fluctuation in the GFII may indicate the severity of the wear conditions of disc cutters. Therefore, GFII can assist engineers in planning shield maintenance schedules.

Point Cloud Registration With Zero Overlap Rate and Negative Overlap Rate

Point Cloud Registration With Zero Overlap Rate and Negative Overlap Rate

Timing jitter reduction of CW-LD-pumped 1.34 µm high-repetition-rate Nd:YVO4/V:YAG laser with optimal spatial overlap rate

In this work, we investigated the characteristics of a continuous-wave (CW) laser diode (LD) end-pumped 1.34 µm passively Q-switched Nd:YVO4/V:YAG laser experimentally and theoretically. A four-level theoretical model for 1.34 µm passively Q-switched Nd:YVO4/V:YAG laser which includes the non-radiative transition, the effective pump power, the spatial overlap effect and the thermal lens effect was demonstrated to give a transcendental equation that can accurately reflect the output characteristics of the laser. Based on the theoretical analysis, the spatial overlap rate was further optimized, we finally realized high-repetition-rate pulse output with time jitter of 180 ns at 220 kHz repetition rate and 200 ns at 357 kHz repetition rate. The good agreement between the experiment results and theoretical model provides a reference for the accurate prediction of the output characteristics of 1342 nm passively Q-switched laser.

Corrosion Resistance Mechanism of Stellite-6 Coating on 42CrMo Substrate by Overlap Remelting

To delay the corrosion rate of 42CrMo steel in oil and gas drilling industry, Co-based coatings were prepared on 42CrMo steel through laser cladding at different overlap rate (20%, 50% and 60%). The relationships between microstructure and corrosion behaviour of Stellite-6 coating in Cl ion corrosion medium were analysed by means of SEM, polarization curve and EIS. The results showed that the microstructures of Stellite-6 coating were mainly equiaxial crystal, and the corrosion form of cladding Stellite-6 alloy was pitting corrosion. The best corrosion resistance of Stellite-6 coating was the coating prepared at the overlap rate 50%. The formation of passivation films (Cr2O3 and Cr(OH)3) on the coating could obviously improve the corrosion resistance in Cl ion corrosion medium.

An ImprovedD2GAN‐based oversampling algorithm for imbalanced data classification

AbstractTo address the problems of pattern collapse, uncontrollable data generation and high overlap rate when generative adversarial network (GAN) oversamples imbalanced data, we propose an imbalanced data oversampling algorithm based on improved dual discriminator generative adversarial nets (D2GAN). First, we integrate the positive class attribute information into the generator and the discriminator to ensure that the generator only generates the samples for positive class samples, which overcomes the problem of uncontrollable data generation by the generator. Second, we introduce a classifier into D2GAN for discriminating the generated samples and the original data, which avoids the overlap among the generated samples and the negative class samples, and ensures the diversity of the generated samples, the problem of pattern collapse is solved. Finally, the performance of the proposed algorithm is evaluated on 9 datasets by using SVM and neural network classification algorithm for oversampling experiments, the results show that the proposed algorithm effectively improve the classification performance of imbalanced data.

Optimized GICP registration algorithm based on principal component analysis for point cloud edge extraction

For iterative closest point (ICP) algorithm, the initial position and the number of iterations are needed in registration. At the same time, the ICP algorithm is easy to fall into local convergence and convergence speed is slow. By constructing K-D tree to search neighborhood points and artificially set threshold, plane fitting is carried out, the on-time point cloud to be deployed is separated from the complex background, and statistical analysis is used to calculate the distance between the point cloud and the neighborhood point to quickly remove the invalid point cloud. The surface equation is set to calculate the tangent plane of point cloud normal vector and each normal vector, and the local coordinate system is constructed. The angle between adjacent vectors and the local coordinate system is calculated to determine the feature point set of edge contour. According to the covariance matrix of the feature points set, the principal feature component is obtained, the principal axis direction of the two sets of point clouds is found, and the rotation matrix and the displacement vector are obtained. Finally, GICP precise registration of point cloud is carried out according to initial pose parameters and rigid body transformation matrix obtained by maximum likelihood estimation method. The results show that the optimized algorithm can effectively avoid local convergence. Compared with the traditional ICP algorithm, when the algorithm achieves the same registration accuracy in the public dataset experiment, the registration speed is on average 44.82% faster and the overlap rate is on average 15.26% higher. In the real dataset experiment, the registration speed is on average 59.04% faster, the registration accuracy is on average 30.24% higher and the overlap rate is on average 10.61% higher. This shows that the optimization algorithm is superior to the traditional ICP algorithm in registration accuracy and convergence speed.

Do ESG Ratings of Chinese Firms Converge or Diverge? A Comparative Analysis Based on Multiple Domestic and International Ratings

Since the Chinese economy has transitioned to a sustainable model, the Chinese socially responsible investment (SRI) market has expanded rapidly, which has deeply stimulated the development of environmental, social, and governance (ESG) ratings for Chinese firms. Domestic agencies, such as SynTao, Rankins (RKS), Sino-Securities (SSII), and China Alliance of Social Value Investment (CASVI), and international agencies, such as Bloomberg, FTSE Russell (FTSE), and Morgan Stanley Capital International (MSCI), have launched their own ESG rating systems. These emerging ratings may provide users of information with more diverse references; however, if their results are too divergent, they may also confuse users. To what extent do these ESG rating results in the Chinese market converge or diverge? Aiming to answer this question, we used Hushen 300 index firms in 2019 as the initial sample, and selected 195 firms covered by the above seven ratings for the analysis. Firstly, by comparing the overlap in the top 100 lists of these sample firms, we found that the list overlap rate between each pair of ratings was between 66.36% and 82.35%; however, only 35% of the firms were listed in the top 100 of all seven ratings. Furthermore, the Pearson correlation analysis showed that the correlation coefficients between each pair of ratings ranged from 0.057 to 0.736, and the average was only 0.411. These results suggest a wide divergence in the ESG rating results for Chinese firms. We suggest that information users need to consider a more diverse and comprehensive perspective when utilizing these ratings.

Flight Path Setting and Data Quality Assessments for Unmanned-Aerial-Vehicle-Based Photogrammetric Bridge Deck Documentation.

Imagery from Unmanned Aerial Vehicles can be used to generate three-dimensional (3D) point cloud models. However, final data quality is impacted by the flight altitude, camera angle, overlap rate, and data processing strategies. Typically, both overview images and redundant close-range images are collected, which significantly increases the data collection and processing time. To investigate the relationship between input resources and output quality, a suite of seven metrics is proposed including total points, average point density, uniformity, yield rate, coverage, geometry accuracy, and time efficiency. When applied in the field to a full-scale structure, the UAV altitude and camera angle most strongly affected data density and uniformity. A 66% overlapping was needed for successful 3D reconstruction. Conducting multiple flight paths improved local geometric accuracy better than increasing the overlapping rate. The highest coverage was achieved at 77% due to the formation of semi-irregular gridded gaps between point groups as an artefact of the Structure from Motion process. No single set of flight parameters was optimal for every data collection goal. Hence, understanding flight path parameter impacts is crucial to optimal UAV data collection.

Object-level complete coverage path planning for excavators in earthwork construction

Autonomous excavators are gradually gaining attention because they can reduce the waste of human resources and improve the efficiency. This study proposed a complete coverage path planning algorithm for autonomous excavators based on the Rotating Calipers Path Planning (RCPP) algorithm, which called the Excavator-Rotating Calipers Path Planning (E-RCPP) algorithm. This study uses boustrophedon cellular decomposition (BCD) to decompose the construction area to obtain the convex and non-convex sub-areas without obstacles, and describes a non-decomposition principle to determine whether to decompose non-convex areas that are difficult to plan. To obtain the optimal path, an adaptive spacing adjustment model which is used to adjust the spacing between parallel paths is designed. To improve the coverage rate at the corner, this study proposed a novel boundary corner turning method. The algorithm's cost function considers the path length, the number of turns, the coverage rate and the overlap rate. The Digital Orthophoto Map (DOM) of the construction area is created by Unmanned Aerial Vehicle (UAV) and cropped into three polygonal areas, the 2D top-views of the them are used for simulation experiments to verify the performance of E-RCPP algorithm, the results show that the E-RCPP algorithm has better performance when applied to the complete coverage path planning for excavator compared with the traditional RCPP algorithm.

Parametric evaluation of segmentation techniques for paddy diseases analysis

In most paddy plant diseases, the leaf is the primary source of information for image-based disease identification and classification. Image segmentation is an important step in the plant disease analysis process. It is used to separate the normal part of the leaf from the disease-affected part of the leaf. In this paper diseases like Bacterial leaf blight, Brown spot, and Leaf smut are segmented using existing, K-means clustering, the Otsu thresholding method. Color space-based segmentation is newly proposed for paddy disease analysis. The intelligence of segmentation techniques is evaluated using the Error Rate and Overlap Rate across the three paddy diseases namely, Bacterial Leaf Blight (BLB), Brown Spot (BS) and Leaf Smut (LS). The results were compared among the Otsu, K-means and color thresholding segmentation techniques. The results revealed that, the color thresholding method using the Lab model emerged as a novel segmentation method for all three paddy diseases with an average Error Rate (ER) and Overlap Rate (OR) of [0.36, 0.95]. The proposed work is carried out in the department of Electronics and Communication research centre at Ballari Institute of Technology and Management, Ballari, Karnataka during the period from August 2022 to February 2023 with the expert suggestions of the plant pathologist, from the University of Agricultural Science, Dharwad, Karnataka.

Study on the formation mechanism of functional surface microstructure by ultrasonic vibration assisted laser processing

In this paper, a novel ultrasonic vibration-assisted laser surface processing technology is proposed for preparing microstructures on metal surfaces. Firstly, the formation mechanism of single laser spot on metal surface is analyzed, and the mathematical model of three-dimensional morphology of single crater is derived, the influence of ultrasonic vibration on the crater morphology is studied. Secondly, the influence of ultrasonic vibration on the position distribution of heat affected zone in single laser path is studied. After, the influence of ultrasonic vibration and laser scanning speed on the shape of the laser path is expressed by pushing the overlap rate between the heat affected zones. The calculation results show that the larger ultrasonic amplitude, the greater effect on the curve shape. Finally, the correctness of the calculation and simulation results is verified by experiments. It is observed that ultrasonic vibration can promote the discharge of the melt and provide a new method for changing the surface microstructures.

Study on overlap rate and machinability of selected laser melting of maraging steel

Abstract In order to investigate the material properties of maraging steel laser additive manufacturing, the cladding layers with different overlap rates on the surface of 18Ni300 were prepared by laser cladding technology, and the morphology, microstructure, and hardness of the cladding layer with different overlap rates were analyzed by various means. The results show that the macroscopic morphology of the cladding layer mainly presents three states under different overlap rates, and the change of overlap rate has no effect on the microstructure in the same area of the cladding layer, but does have an effect on the size of the cladding layer. In the end, the optimum overlap rate is 50%, the surface is smooth, the inner is free from defects, the bonding effect is good, and the metallographic structure is even with high hardness. Milling experiments were carried out on the material after laser additive manufacturing, and the surface morphology was observed, confirming a smooth and well-flattened surface with a roughness of 0.342 μm had been obtained. The suitable overlap rate can make the coating surface smoother, reduce the subsequent processing loss, and improve the production efficiency and powder utilization rate while ensuring the coating quality.

Nanosecond laser coloration of Ti-based metallic glass under various laser parameters and irradiation atmospheres

Laser coloration is an emerging technique for surface functionalization of metallic glasses (MGs). Understanding the influence of laser parameters on surface color of MGs will accelerate their commercialization. Herein, surface coloration was conducted on a Ti-based MG, and the hue–saturation–intensity (HSI) color space was employed to evaluate color variation. Various colors were achieved by varying the average power and scanning speed in an ambient atmosphere. The results indicated that the overlap rate and number of repetitive scans had a negligible effect on the color and significantly changed the microscopic morphology. The irradiated surfaces were yellowish and colorless in nitrogen and argon atmospheres. Furthermore, the effect of morphology on the surface color and the mechanism of surface coloration were examined. This study demonstrates that nanosecond laser irradiation is an effective method for achieving surface coloration of MGs, which is expected to enrich the surface functionality of MG products.

Study on the CFRP nanosecond laser cutting damage and efficiency by aspiration system assisted method

In the present work, the aspiration system assisted method is investigated on low-damage and high-efficiency carbon fiber reinforced polymer (CFRP) nanosecond laser cutting. Experiments parameters with three aspiration system assisted conditions (no aspiration system assisted, unilateral aspiration system assisted, bilateral aspiration system assisted), different frequencies, and overlap rates are designed. The analysis focuses on the cutting time of through-cut, heat affect zone (HAZ) on the entrance surface, roughness, and microdefect on sidewall of cutting holes. The results indicate aspiration system assisted can reduce the HAZ of laser cutting hole, the sidewall roughness, and cutting time. The cutting time with bilateral aspiration system assisted is shortest, with a maximum reduction of 24.8 % compared to no aspiration system assisted at a frequency of 100 kHz and an overlap rate of 85 %. Aspiration system assisted reduces the HAZ, and its placement has an effect on cutting hole quality, proximal HAZ 11.11 μm is greater than distal HAZ 6.96 μm with unilateral aspiration system assisted. All sidewalls of cutting holes have a ladder-like interface, and an interface height difference up to 43 μm. It appears in the intermediate position of CFRP plate or exit of cutting holes. With no aspiration system assisted, large voids appear below a ladder-like boundary surface, and the maximum value of voids reaches 290 μm. Aspiration system assisted remove the carbon fiber debris and the plasma plume generated by laser cutting, avoiding accumulation and combustion in the slit, reducing the absorption of laser energy by carbon fiber debris and plasma plume, effectively improving cutting quality and efficiency.

Ultrawide coverage receiver based on compound eye structure for free space optical communication

Free space optical communication (FSOC) is a potential technology for next generation communication. To reduce the construction cost for the receiving node in FSOC network, in this paper, we propose an ultrawide coverage (UC) receiver based on compound eye structure. The UC receiver consists of nine compound eye channels arranged in 3 rows multiply 3 columns. All the channels in the receiver use the same signal collecting system (SCS). Among the channels, the difference between the central channel and the non-central channel is that each non-central channel is equipped with a field of view (FOV) transform system to change the cover region and expend the coverage. Simulation results of coverage indicate that the effective coverage of the proposed system is 2.433sr, which is about 19.36% of the whole spherical space. Besides, when it works outside the presupposed blind distance, no blind zone coverage has achieved and the overlap rate of coverage is only 3.93%. Compared with the normal receiver with the same parameter, the coverage of the proposed receiver is increased by 57.6%. Moreover, performance simulation results show that, the average Bit Error Ratio (BER) of the proposed receiver is better than 2.47 × 10−6 in strong turbulence, which is enough to have a stable communication link. The new designed UC receiver has a great potential as an airborne suspended receiving node to establish FSOC network and may paves a new way for the design of FSOC receiver with an ultrawide coverage.