The changes in clouds are complex and diverse, playing a significant role in weather forecast and disaster warning, and affecting our daily lives. The observation of clouds is mainly carried out through radar, remote sensing satellites, and all-sky imagers. The recorded cloud images are divided into radar cloud images, satellite cloud images, and ground-based cloud images, all of which are indispensable parts of cloud observation. With the development of machine learning in multiple fields, it has gradually been applied to cloud segmentation and has made great progress. Through extensive research on literature and achievements in related fields, machine learning cloud segmentation was divided into three types: cloud segmentation methods based on neural networks, cloud segmentation methods based on transfer learning, and cloud segmentation methods based on lightweight models. The methods proposed in recent years for each type were compared, and improvement methods for different problems in cloud segmentation were further summarized. Several improvement schemes were provided for reference.

There are various evaluation methods for the effectiveness of asphalt pavement grouting repair, most of which rely on on-site testing of a single indicator. Up to now, there are few related reports in the comprehensive evaluation of multiple indicators. In order to comprehensively understand the detection methods of asphalt pavement grouting repair effect and promote the development and application from single index evaluation to multi index evaluation methods, the research status of relative methods were summarized including drilling core method, grouting plug gauge method, deflection detection method, modulus inverse algorithm, ground penetrating radar method, and transient Rayleigh surface wave method in the detection of grouting filling quality, pavement strength, pavement modulus, compaction degree, void ratio, and grouting repair degree and other indicators. Furthermore, drawing on the current research status in the fields of tunnel grouting and goaf grouting, the application prospects of fuzzy analytic hierarchy process, grey correlation degree method were analyzed, as well as subjective and objective weighting cloud model in the evaluation of grouting repair effect of internal diseases in asphalt pavement, and looks forward to the development trend of precision, objectivity, and informatization in the evaluation of grouting repair effect of asphalt pavement were forecasted. Diversified method guidance is provided for evaluating the grouting repair effect of internal diseases in asphalt pavement.

In order to study the failure mode and energy dissipation law of granite with double elliptical defects, dynamic splitting tensile experiments were conducted on granite with double elliptical defect angles of 0°, 45°, 90°, and 135° using a SHPB(split Hopkinson bar) device. The relationship between the angle and spacing of double elliptical defects, as well as the failure morphology and energy of granite, was explored. The results show that when the distance between double elliptical defects remains constant, the larger the included angle, the easier the specimen is to fracture. When the angle remains constant, the spacing increases and the rock sample is more prone to fracture. The dissipated energy density of the specimen decreases with the increase of the included angle, and the downward trend gradually tends to be gentle. The failure mode of the specimen is highly sensitive to the angle, that is, as the angle increases, the degree of fragmentation of the rock sample gradually intensifies, the symmetry of the fragments disappears, the wedge effect gradually becomes obvious, and the plasticity increases. When the included angle exceeds 90°, the degree of fragmentation begins to decrease again, and the rock sample exhibits symmetrical fracture.

Guangxi is located in the South China block, its structure is relatively stable, the seismic activity observed by the instrument is relatively weak. The little observation data leads to weak research on the crustal stress field in the area. In 2019, the Beiliu earthquake sequence occurrence in this area leads to the accumulation of considerable focal mechanism data. The focal mechanism data were collected in Guangxi and its adjacent areas. Using the grid search algorithm, the stress field in overall region and subregions were inverted. The results show as follows. The statistics of the focal mechanism in this area is mainly strike-slip type, and from the distribution of NW to ES, the focal mechanism of the reverse type gradually increases, and the focal mechanism of the normal fault type gradually decreases. The principal compressive stress axis of the overall stress field is NW-SE direction, the principal extensional stress axis is NE-SW direction, both of them are close to horizontal, which representing strike-slip type. The direction of the principal compressive stress axis in the western region is close to the N-E direction, and that in the east gradually changes to the direction of NW-SE, which makes the pattern of the compressive stress direction present a fan-shaped in the overall area. Based on the stress field analysis of subregions: NE-SW and NW-SE faults are easily generated in region-a by primarily of strike-slip type. NNE-SSW and NWW-SEE faults are easily generated in region-b, with NNE-SSW faults more towards reverse strike-slip type and NWW-SEE faults tending towards strike-slip type. Pure azimuth N-S and E-W faults are easily generated in region-c, but its main fault properties are not reflected due to the influence of surrounding fault extensions, with faults mainly of reverse strike-slip and reverse fault types. NW-SE and NE-SW faults are easily generated in region-d, with NW-SE faults more towards reverse fault and NE-SW faults tending towards strike-slip.

The tectonic activities at the bottom and surrounding the sedimentary basin will inevitably lead to changes in the sedimentary filling characteristics and evolution of the basin. These changes serve as records of the sedimentary strata’s response to tectonic activities. Based on logging interpretation and outcrop data, the sedimentary evolution of the Middle and Late Jurassic to Early Cretaceous in the Ordos Basin was analyzed through paleogeography and sedimentary facies restoration. The results indicate that the southern part of the basin developed multi-phase depositional systems, including alluvial fan, river-delta-lake, and desert phases. There was a sedimentary divergence from east to west, with the sedimentary center migrating from east to west. During this period, the basin was primarily influenced by the Yanshan Movement, with strong tectonic activities occurring around it. Consequently, a tectonic pattern emerged within the basin, characterized by uplifting and tilting in the east and sinking and depression in the west. The intense tectonic activities at the western edge of the basin also led to the development of an intralittoral foreland basin at the southwestern edge during the Late Jurassic Fenfanghe Stage. Additionally, multiple sets of molasse formations and unconformity contacts were present during the Late Jurassic and Early Cretaceous periods. Based on these insights, a model map of the Middle and Late Jurassic to Early Cretaceous tectono-sedimentary evolution has been established. The occurrence of these sedimentary events serves as a record of the basin’s response to the early and middle stages of the Yanshan Movement, proving a close relationship between sedimentary evolution and the uplift of the Qinling-Qilian Mountain orogenic belt and the Lvliang Mountains. These insights not only complement and improve the theory of tectonic-sedimentary response in the southern basin during the Yanshan Movement but also have practical significance for the exploration and development of mineral resources such as oil, gas, and uranium in the southern basin.

The Sichuan Basin, situated in the heart of China, is renowned for its abundant oil and gas reserves within a geologically intricate sedimentary basin. A multitude of strike-slip faults, characterized by their extensive reach, substantial scale, and modest displacement, are particularly prominent in the basin’s central region. In order to elucidate the influence of these faults on the formation of oil and gas reservoirs, high-precision seismic data analysis and numerical simulation techniques were used to investigate the strike-slip fault system in the central Sichuan area. The results show that the primary strike-slip faults in the central Sichuan region bifurcate into two distinct orientations: nearly EW(east-west) and NE(northeast-southwest). These first-order faults are inclined to emerge along the peripheries of secondary tectonic units. The near EW-oriented faults were predominantly active prior to the Permian era, coinciding with the Hercynian phase, whereas the NE-oriented faults were shaped later, during the transition from the Late Hercynian to the Indosinian period. The evolution of these strike-slip faults is intricately tied to a series of overlapping tectonic events. The culmination of the ancient uplift in central Sichuan predating the Permian era precipitated the genesis of the near EW-oriented faults. Subsequently, a pivotal tectonic regime shift during the Late Hercynian epoch, coupled with the subsequent Indosinian period’s fore-arc structural modifications near the Longmen Mountains, catalyzed the emergence of the NE-oriented faults. Moreover, the Deyang Anyue fault trough is identified as a pivotal factor in dictating the regional stress distribution, effectively hindering the east-west faults from traversing beyond the fault trough boundary, thereby stifling their further development.

To observe the effects of LPS(lipopolysaccharide)-HDAC3(induced histone deacetylase 3) on the expression of HMGB1(high mobility histone B1) and nuclear translocation in RAW264.7 cells, and the intervention effect of SFI(Shenfu injection). RAW264.7 cells were induced by LPS to establish a cellular inflammatory injury model, and the cells were intervened with SFI at doses of 3, 6, and 12 μL/mL for 24 h. RT-qPCR(real-time fluorescence PCR) was used to detect the transcriptional levels of HDAC3, HMGB1, IL-1β, and TNF-α in the cells, and Western-blot was used to detect the protein expression of HMGB1 and HDAC3, and immune immunoassay to detect the protein expression of HMGB1 and HDAC3.HDAC3 protein expression, immunofluorescence to observe the effect of SFI on the subcellular localization of HMGB1. ELISA to detect the secretion levels of HMGB1, IL-1β, and TNF-α in the cell supernatant. And small interfering RNA(siRNA) after targeting to silence the HDAC3 in RAW264.7 cells. to observe the effect of SFI on HMGB1 subcellular localization. Compared with the control group, the transcription and expression of HDAC3 in RAW264.7 cells in the model group were significantly reduced (P<0.01), and the expression of HMGB1 was significantly elevated (P<0.01) and simultaneously migrated from the nucleus to the cytoplasm. The inflammatory factors in the supernatant of the cells, such as HMGB1, IL-1β and TNF-α, were significantly elevated (P<0.01). And compared with the model group, SFI (6, 12 μL/mL dose group) up-regulated the transcription and expression levels of HDAC3, down-regulated the transcription, expression, and nuclear translocation of the inflammatory factor HMGB1, and inhibited the secretion of HMGB1, IL-1β, and TNF-α in RAW264.7 cells. After targeted silencing of HDAC3, a large amount of HMGB1 was localized in the cytoplasm, and there was no significant change in protein localization after LPS stimulation, and SFI could not reverse the abnormal localization of HMGB1. SFI may inhibit LPS-induced extra-nuclear migration of HMGB1 in RAW264.7 cells by up-regulating HDAC3 expression, which in turn inhibited its downstream inflammatory response.

Addressing the issues of large model parameters and high computational complexity in apple target detection algorithms for complex orchard environments, which hinder application on devices with limited computational resources, an improved and lightweight apple target detection algorithm named YOLOv8n-Apple based on YOLOv8 was proposed. The backbone network, yaniaNet, was introduced to reduce model parameters and complexity. The original C2f module in the model was replaced with the C2fGhost module, which further decreased model parameters by obtaining similar feature maps through fewer convolutional operations. The lightweight upsampling operator CARAFE was utilized to address the issues of semantic loss and excessively small receptive fields associated with traditional upsampling operators. Given that traditional loss functions cannot fully capture the relative position and size differences between targets, the WIoU bounding box was adopted as the regression loss function. A dataset comprising 3 120 images of mature apples in various scenarios, including distant and close views under front-light and backlight conditions, was collected from diverse angles and backgrounds, to mitigate potential dataset uncertainties. The improved apple detection model for orchard environments demonstrated an average detection accuracy of 90%, which was 7.5, 4.8, 2.2, 3.8, and 3.4 percentage points higher than SSD, Faster R-CNN, YOLOv5, YOLOv7, and YOLOv8, respectively. The detection speed reached 286 frames per second, and the model size was reduced to 1.8 MB, representing an improvement of 41 frames per second compared to the original model, while occupying only 60.0% of size.

There are certain requirements for the mechanical properties of paper or paper-based materials during their service. However, existing experimental and theoretical studies of size effects indicate that the mechanical properties of specimens with different sizes are not identical. Therefore, it is necessary to clarify the size effect of their mechanical properties to ensure their safety. The kraft paper, which is easy to obtain and has high strength, was selected to carry out uniaxial tensile tests on with different sizes. And then the size effects of mechanical properties and their dispersions were determined. By analyzing the deformation characteristics and macro-microscopic damage features of different sizes specimens, the intrinsic mechanism of the size effect on the mechanical properties of kraft paper was revealed. Finally, a size effect model of mechanical properties for kraft paper was established. The study finds that the nominal tensile strength and nominal peak strain of kraft paper first increase and then decrease as the sizes increases. This is because the cut edge fibers cause the edges of the kraft paper specimens to have weaker stress and strain capabilities, and the proportion of weakened edges in small-sized specimens is relatively large, leading to an increasing size effect on the nominal tensile strength and nominal peak strain. In large-sized specimens, the proportion of weakened edges can be ignored, and the internal fracture process zone plays a dominant role, leading to a decreasing size effect on the nominal tensile strength and nominal peak strain. The established edge-internal fracture process zone size effect model can well describe the size effect on the nominal tensile strength and nominal peak strain of kraft paper. However, this model cannot capture the nonlinear characteristics of the increasing size effect stage for the nominal tensile strength and nominal peak strain.

As a major risk source, slope in open-pit coal mine is one of the main challenges faced by mine safety production. Taking Wanyuan open-pit coal mine in Wuhai City, Inner Mongolia Autonomous Region as an example, based on detailed investigation of slope development characteristics, deformation and failure modes were analyzed, slope radar deformation monitoring was carried out, and early warning models were established, a monitoring and early warning platform was built to achieve risk control. The results show that the slope of Wanyuan open-pit coal mine involves reverse, cross and consequent rock slope and soil slope of dump, and its deformation and failure modes are respectively tensile fracturing, wedge failure, slip-bending and creep (-tensile cracking). There is a possibility of instability under the influence of mining, blasting, rainfall or unreasonable stacking. On this basis, in order to realize the monitoring of slope without blind area, two sets of slope radar were respectively installed at the stable bedrock on the northeast and southwest sides of the mine, and the slope safety grade was divided into four grades: blue (<3 mm/h), yellow (3~8 mm/h), orange (8~15 mm/h) and red (>15 mm/h). Combined with the organizational structure of mining enterprises, the slope safety management system from slope radar deformation monitoring data-early warning model-early warning platform-risk management and control are constructed, which can provide technical reference for the construction of regional coal mine safety production capacity.

CO₂ flooding is an important part of the CO₂ geological utilization process in CCUS(carbon capture, utilization and storage). The CO₂ flooding and storage project carried out in the Yanchang Oilfield has achieved good results in increasing production and storing CO₂. But the reasons of pipe string corrosion failure are still unclear during CO₂ injection. SEM(scanning electron microscopy), 3D confocal microscopy, EDS(energy dispersive spectrometer) and XRD(X-ray diffraction spectroscopy) were used to characterize the corrosion morphology of the gas injection pipe string in the CO₂ flooding and storage demonstration area of Wuqi Oilfield. The pipe string corrosion products are analyzed to clarify the reasons for pipe string failure caused by CO₂ corrosion. The results show that local corrosion dominated by CO₂ corrosion causes corrosion failure of the pipe string. Corrosion products include FeCO₃, high-priced oxides of Fe and a small amount of FeS. Continuous injection of low-temperature CO₂ cannot cause corrosion. However, the increase in wellbore temperature and the return of formation water caused by stopping CO₂ injection can create conditions for CO₂/H₂S corrosion in the pipe string. In addition, pipe string corrosion is accelerated when gas injection wells are converted into water injection wells. It is recommended to strengthen the sterilization and anti-corrosion measures for the pipe string during the period of stopping CO₂ injection and switching to water injection.

For the research on the characteristics and main controlling factors of volcanic rock reservoirs, core observation, casting thin section identification, physical property testing and logging data analysis were utilized to conduct the study on the characteristics, distribution and main controlling factors of the Carboniferous volcanic rock reservoirs in the Junggar Basin. The results show that in the Chepaizi uplift, the Carboniferous volcanic rock reservoirs mainly developed volcanic effusion facies, explosive facies, tuffaceous facies and volcanic sedimentary facies, and the lithologies are mainly andesite, basalt, volcanic breccia, tuff and tuffaceous sandstone. The reservoir spaces are classified into connected pore type, fracture type, fracture-pore type and pore-cavity-fracture type according to the configuration relationship between pores and fractures. Affected by lithology and lithofacies, weathering and leaching effects and tectonic actions, the reservoir properties have strong heterogeneity. The dominant reservoir lithologies are andesite, volcanic breccia and tuff. A three-layer weathering crust structure composed of clay layer, hydrolysis layer and weathering and leaching layer is developed at the top of the Carboniferous, which significantly improved the reservoir physical properties. Fractures are an effective supplementary factor for reservoir development. Different from the previous studies that mainly focused on characterizing the characteristics of the dominant volcanic rock reservoirs, based on the coupled controlling effects of lithology and lithofacies, weathering and leaching, and strike-slip faults on the reservoirs, it is innovatively recognized that two dominant volcanic rock reservoir development models, namely fault-block body and fault-fracture body, are mainly developed in the study area. The research results have certain guiding significance for the exploitation of the Carboniferous oil and gas resources from east to west in the Chepaizi uplift.

The sedimentary process and evolutionary model of crevasse fans are of great significance for predicting fluvial reservoirs and remaining oil potential. Taking the Dongyingzi fan in Liangcheng County as an example, based on satellite imaging and field geology, sedimentary features of Dongyingzi fan was analyzed. Using the SFM, the simulation gridding system, simulation parameters, and boundary conditions were designed to establish a numerical model of the crevasse fan. The plane distribution of sedimentary thickness, flow velocity and sand content at different numerical simulation stages were analyzed, as well as vertical sedimentary structure of the crevasse fan. The sedimentary model of crevasse fans was summarized to discuss its significance for Reservoir architecture. Research suggests that the crevasse fans consists of crevasse channels, composite proximal fans, and an distal fans. From a humid to an arid climate, the formation process of crevasse fans can be divided into four stages, which are river crevasse stage, proximal-fan forming stage, proximal-fan flourishing stage and diatal fan forming stage. As the flooding hydrodynamics decreases, crevasse channels, composite proximal fans and diatal fans are formed in sequence. The composite proximal and distal fans are sand-rich area, which are favorable types of sand bodies during the exploration. Crevasse channels are mud-rich area as the main type of interlayer. Composite proximal fans around the crevasse channels is the main site for residual oil enrichment in the later stage of hydrocarbon development.

The rheological parameters of drilling fluid have an important impact on accurately predicting the hydraulic parameters of deepwater and ultra-deepwater drilling wells. The rheological experiments were carried out on commonly used HEM(high efficient mud) drilling fluids and synthetic-based drilling fluids in the deep waters of the South China Sea under conditions of 4 to 210 ℃ and 30 to 180 MPa. The variation laws of rheological parameters such as apparent viscosity, plastic viscosity, and dynamic shear stress with temperature and pressure were revealed in a wide range of temperature and pressure. Based on the experimental data, nine existing rheological models were compared and evaluated. It was found that the Ross model is suitable for synthetic-based drilling fluid, and the Herschel-Bulkley model is suitable for HEM drilling fluid. On this basis, a general predictive model for rheological parameters of HEM and synthetic-based drilling fluids was created, which is applicable to alternating high and low temperatures, high and low pressures. The maximum error of this model is 11.95%, with an average error of 0.62%, which is better than existing models.The bottom hole pressure error is 0.28% when using HEM drilling fluid and 0.181% when using synthetic drilling fluid, which can meet the requirement of deep water drilling in the South China Sea.

In order to enhance the output performance of axial flow helical turbine drilling tools, it is crucial to conduct research on the structure and hydraulic performance of the turbine. Firstly, an analytical computational model for the hydraulic characteristics of two types of helical turbines, namely constant thickness blade and variable thickness blade, was established using calculus principles. Secondly, the blade profile equation was constructed to analyze the influence of helix angle on the hydraulic performance of the turbine. Finally, based on the design example of an underground helical turbine generator, the output performance parameters of the two types of helical turbines and the impact of helix angle were analyzed. Furthermore, a mud pulse generator was manufactured based on the optimized analysis results of the helical turbine, and indoor experiments were conducted to study the impact of different displacements on the power generation performance. The research findings show as follows. Under given conditions, the variable thickness helical turbine exhibits significantly higher hydraulic performance compared to the helical turbine with constant blade thickness. The turbine output characteristics curve sharply decreases as the helix angle of the blade increases. However, the decrease in turbine output characteristics becomes insignificant when the helix angle exceeds a certain value (approximately 30°). With 7 blade counts and a helix angle of 38°, the underground turbine generator reaches a maximum power of 300 W with a load of 8 Ω. Through indoor testing, the power of the generator meets the requirements of underground tools. This research provides a reliable power source for underground intelligent drilling equipment.

In order to study the erosion behaviour of the gooseneck pipe in the drilling fluid environment and the evaluation of the surface strengthening effect, the influence of the drilling fluid density on the erosion behaviour of the gooseneck pipe and the evaluation method of the surface strengthening of the inner lumen were investigated by the finite element simulation and analysis method. The results show that: the erosion rate of gooseneck pipe is the largest in the inner diameter of the bend, and the maximum erosion rate becomes larger with the density of drilling fluid becoming higher, but the maximum erosion rate still occurs in the inner diameter of the bend. The maximum deformation displacement can be effectively reduced by 34.23% after surface strengthening of the inner lumen of the gooseneck pipe. It can be seen that the effect of drilling fluid density on the erosion behaviour of the gooseneck pipe cannot be ignored, and surface strengthening can effectively reduce the maximum deformation displacement.

In order to solve the problem of difficulty in determining the optimal measurement points for bearing signal acquisition. Taking the NU306 bearing-housing system as the research object, the bearing housing to carry out multi-measurement points vibration test experiment. The local linear embedding algorithm was used to linearly reduce the multi-dimensional space data of the bearings to obtain the sensitivity matrix of the measurement point. The optimal position of the measuring point under varying load and rotation speed was studied when the inner or outer ring are defective. The results show that for bearings with outer ring failures, the optimal measurement point is the one closest to the location of the failure when the load or rotational speed increases. For bearings with inner ring failures, the optimal measurement point is the one at lower loads far from the center of the housing when the load or rotational speed increases. The results can provide an effective reference for the selection of measurement points under different operating conditions.

To further meet the plasma heating requirements of EAST (experimental advanced superconducting tokamak) device, NBI (neutral beam injection) system requires higher beam power. Accordingly, the EAST NBI laboratory has developed a 120 keV accelerator for this purpose. The analysis of the whole accelerator needs to be carried out from various perspectives such as beam optics, insulation support, active cooling and materials. Taking into account factors such as plasma parameters, electrostatic lens, voltage resistance between grids, and assembly errors, the numerical simulation program was utilized to beam optics analysis for the slit tetrode ion source accelerator. Beam trajectory, electric field strength distribution, and beam divergence angle were investigated and optimized to preliminarily determine the grid parameters of the new multi-slit accelerator. The accelerator obtains the beam with the minimum divergence angle of 0.6° in the vertical direction with perveance of 1.52 μp, meeting the design criteria for beam current intensity of 60 A and divergence angle below 1° of the ion source.

The switching of power devices in servo drive can lead to bus voltage ripple, which may result in performance degradation, electromagnetic interference, and harmonic issues in permanent magnet synchronous motor AC servo systems. To address these issues, the influence of the switching process of power device on the voltage ripple of bus was analyzed and studied for the DC power supply servo drive system. Firstly, based on the working principle of PMSM (permanent magnet synchronous motor)and SVPWM (space vector pulse width modulation) algorithm, the ripple current of the busbar capacitor was analyzed. Then, according to the law of charge conservation, the relationship between the busbar capacitance, busbar voltage and current amplitude under the seven-stage and five-stage SVPWM modulation was analyzed theoretically, and its simplified expression was given. Finally, the theoretical results were verified by simulation experiments.

In order to ensure the safe and stable operation of the power system after large-scale grid-connection of new energy, it is necessary to quantitatively assess the vulnerability of the power grid before and after grid-connection. Therefore, a composite new energy power grid vulnerability analysis method based on complex networks and electrical characteristics was proposed, and the IEEE-39 node was simulated. Firstly, a vulnerability assessment system was constructed by selecting degree centrality, proximity centrality, eigenvector centrality, electric power flow interval, voltage stability and power balance, and then solving each secondary index according to the formula. Secondly, entropy weight method was used to calculate the index weight, TOPSIS method was used to rank the vulnerability of nodes before and after grid connection, and comparative analysis was made. Finally, the obstacle factor model was used to analyze the influence degree of each index on the vulnerability of power grid. The research results indicate that the number and location of new energy sources connected to the grid affect the vulnerability of the power grid. Among the influencing factors of grid vulnerability, the order of influence is voltage stability indicator > closeness centrality indicator > active power balance indicator.

To explore the feasibility of using AI (artificial intelligence) three-dimensional motion analysis for analyzing the influencing factors on the distance of ski jumping and optimizing athletes’ technical movements, a study was conducted during the 2022 FIS Continental Cup Beijing event. Sixteen athletes’ take-off phase motions were captured within a fixed range using AI-based three-dimensional motion analysis system. This system automatically parsed the videos to obtain biomechanical parameters of the athletes’ take-off phase. By comparing the correlation coefficients and differences between manually processed data and AI-generated data of the three-dimensional coordinates of body joints over time, the validation of the equipment for ski jumping was conducted. The multiple correlation coefficient was found to be greater than 0.91, with an average difference value of less than 1.48 cm, indicating the reliability of the system. Furthermore, a comparison was made between the technical parameters of high-level foreign athletes and domestic athletes. Using t-tests and Pearson correlation coefficient analysis, the relationship between body posture parameters during the take-off phase and sports performance was examined. The results reveal correlations between take-off speed and angles of ankle and knee during the take-off phase, and between the final score and ankle angle during take-off, suggesting that Chinese athletes should focus on achieving full extension during take-off and timing their jumps appropriately to significantly enhance sports performance. Overall, the system demonstrated precise feedback for ski jumping technique analysis. Additionally, it enabled the acquisition of biomechanical parameters from world champion athletes to construct a champion model, providing valuable training references for Chinese athletes.

Aiming at the problem of poor model accuracy caused by poor stability and strong randomness of wind power output. A short-term prediction model of wind power based on quadratic decomposition error compensation was proposed. Firstly, BiLSTM (bidirectional long short-term memory) prediction model is established to predict wind power and output prediction errors. Secondly, an IDBO (improved dung beetle optimizer) algorithm was used to initialize the population by using chaotic mapping, update the position of rolling dung beetles by introducing golden sine strategy, and update the position of thieving dung beetles by adding dynamic adaptive weight coefficient to optimize the parameters of the prediction model. Prevent the network from falling into the local optimal solution, and adaptively search the optimal parameter combination. Then, using the decomposition-reconstruction-decomposition strategy, CEEMDAN (complete ensemble empirical mode decomposition with adaptive noise) was used for the first decomposition. In addition, SE(sample entropy) and K-means are introduced to reconstruct the sequence according to frequency, and the high-frequency error sequence was decomposed into error sequences of different frequency bands by VMD(variational mode decomposition). Improve the prediction efficiency and accuracy of subsequent models. Finally, the input error compensation model of each component was used to predict and the Attention mechanism was introduced to learn the feature relationship of different time steps and give different weight values to enhance the attention to key information. Through the measured data of a wind farm in Xinjiang, the prediction accuracy of the proposed model is proved to be high and has significant advantages.

With China’s Manufacturing 2025 Plan, the military industry to implement the unmanned production line, and AGV (automated guided vehicle) as a fully automated production line of the main logistics carrier, the scheduling of its strengths and weaknesses directly determines the capacity and efficiency of the entire production line. Due to the security requirements of military industrial places, wireless communication and other means cannot be used, and only point-to-point optical communication can be used, which also worsens the real-time communication of AGVs. Based on Plant Simulation software, a simulation system model was established, the real-time data interaction channel between the logistics simulation software and the field controller was opened, the synchronous operation of the simulation system and the reality was realized, and the seamless connection between the logistics simulation software and the field controller was completed, which effectively solves the difficult problem of poor real-time AGV scheduling caused by the lack of wireless power in the military industry. Experiments have proven that this method effectively simplifies the difficulty of writing the scheduling system and improves the overall real-time performance of the system by 0.058 seconds. Compared with the traditional method, the writing time is shortened by 9.7 times, and the debugging time is even shorter by 22 times. This study lays the foundation for the realization of full automation of military production lines and provides technical support for the use of pulsation production lines in hazardous places.

In order to improve the path planning ability and efficiency of AUV (autonomous underwater vehicle), an AUV path planning algorithm based on the community information transmission mechanism was proposed. Firstly, based on the community information transmission mechanism, the global short and long connection operators were designed to achieve the optimal search of the neighborhood of the planned path points and the probabilistic search outside the neighborhood. Then, the local short and long connection operators were designed, which implements the search for four boundary derived points of the path center point and the connections of feasible paths outside the derived points. Finally, the AUV path planning algorithm flow was completed. Six simulation and two seabed map simulation tests show that, compared with other algorithms, the algorithm has the advantages of strong planning ability, high planning efficiency, and smooth planning path.

Establishing an accurate rolling bearing performance degradation prediction model plays a crucial role in subsequent processing such as bearing fault classification and life prediction. In order to solve the problem of inaccurate prediction of bearing performance degradation model, an IBA(improved bat algorithm) was proposed to improve the accuracy of degradation model prediction. Firstly, Cat chaotic mapping was applied to the initial position of the population to enhance the traversability of the population and improve the quality of the initial solution. Secondly, an inverse tangent-like control factor was added in the iterative process to improve the algorithm’s accuracy in finding the optimum. Finally, the position updating strategy was improved to prevent from falling into the local optimum. By comparing the results with those obtained from SVR(support vector regression machine) optimized by BA(bat algorithm), SVR optimized by particle swarm optimization algorithm, and SVR optimized by gray wolf optimization algorithm, the results show that the absolute mean error of the prediction model optimized by the IBA decreases by 70.60%, 67.19%, 55.56%, and the root-mean-square error decreases by 76.64%, 76.12%, and 76.12%, respectively. 76.64%, 76.12%, and 30.29%, respectively, further proving the accuracy of the improved prediction model.

To address the issues of long stitching time due to numerous mismatched feature points and insufficient stitching accuracy when using all feature points directly in image stitching tasks, an optimized image stitching method combining a matching point increasing strategy with RANSAC(random sample consensus) was proposed. The method initially screened feature points to prevent numerous ineffective samples, thus improving computational efficiency. Then, a progressive sampling strategy was employed to incrementally increase matching points and repeatedly sample for precise results. Finally, the optimal model was obtained by utilizing a new loss function based on root mean square error to filter the results. The experimental results indicate that, without a noticeable increase in time consumption, the interior point rate of the algorithm in this paper is further enhanced, the mean and root mean square errors of feature points have decreased significantly, the accuracy of image stitching is improved, the misalignment phenomenon at the stitching seam is effectively improved, and the stitching errors in image stitching tasks are significantly reduced.

Content Aiming at the problems of single convolution model, insufficient Receptive field and inaccurate feedback information of single discriminant network in current face image super-resolution reconstruction algorithm, an algorithm based on adaptive convolution and joint Loss function was designed. A generation adversarial network architecture was used by the model. On the generator side, adaptive convolution was used to construct dual path residual blocks and further form efficient residual groups. It can independently learn feature weights extracted under different receptive fields and supplement missing information from a single branch. The subpixel convolution layers were used to complete quadruple reconstruction of face images. In terms of discriminators, Vgg and U-net architecture networks were used as dual discriminant networks, and dual discriminant results were used to calculate adversarial losses. The losses, content losses, and perceptual losses form a joint loss function. Experiments on the Celeba dataset show that compared with RWSA, this algorithm improves PSNR by 1.166 dB, SSIM by 0.037, LPIPS by 0.033, and PI by 0.119, compared with other mainstream algorithms, it has advantages in image detail clarity.

For the motion control of four-rotor UAV in attitude, the main method is the application of ADRC (active disturbance rejection control) system. For this system to deal with the complex interference with sensor noise, the previous fal function design still has many defects in application. Under the function of traditional fal function, the ESO(extended state observer) has the problems of insufficient observation accuracy and high chattering rate. Therefore, a new nonlinear smooth tfal function was improved on the basis of the previous fal function, and ESO was studied with this function. Finally, other ADRC methods were compared with this method in MATLAB/Simulink software, and the newly designed tfal function shows better convergence. The new ESO based on tfal design has obvious improvement in error estimation and error following performance. At the same time, compared with the improved function galn and the traditional function fal, the tracking capability of the new ESO attitude active disturbance rejection control system is improved by 2.3% and 4% respectively, and the anti-interference performance is improved by 50% and 67% respectively.

The significant advantages of point cloud data are presented in domains such as architectural reverse modeling, 3D reconstruction, and construction progress monitoring. Vast amounts of data are typically involved in the collection of point clouds for architectural structures, with the point clouds of components like beams and columns being particularly crucial. The challenges faced by current semantic segmentation methods for 3D point clouds when processing large-scale data include insufficient extraction of local features and suboptimal recognition accuracy. An enhanced approach for the semantic segmentation of large-scale point clouds of key architectural components using the RandLA-Net deep learning network was proposed. In this regard, the robustness of segmentation results was improved by incorporating a coordinate attention module in the local spatial encoding section. Furthermore, an extended channel attention module has been developed to strengthen the model’s capability in feature discernment, and a focal loss function has been introduced to effectively train the network, while addressing class imbalance issues within architectural point cloud scenes. Consequently, the efficient processing of architectural structure point cloud data and the extraction of key components are enabled. The performance comparisons and analyses conducted through experiments demonstrate that the original RandLA-Net model is outperformed by our model in terms of overall accuracy and component extraction precision in semantic segmentation of large-scale point clouds, thereby confirming the enhanced performance and practical value of the proposed method.

The characteristics of the reinforced soil interface are the basis of the design of the reinforced structure. The method of stitching transverse rib geotextile reinforcement is a new reinforcement technology for the improvement of traditional geotextiles. It improves the interaction of the reinforced soil interface through three-dimensional reinforcement and gives full play to the advantages of high strength of geotextiles. In order to study the influence of the number and height of transverse ribs on the characteristics of the reinforced soil interface, the discrete element numerical simulation of the direct shear test was carried out according to the indoor test results, and the mechanical response of the reinforced soil interface under different number and height of transverse ribs was analyzed from the macroscopic and mesoscopic parameters. The results show that the shear strength of the reinforced soil interface can be significantly improved by stitching the transverse rib geotextile. The shear stress-displacement curve is mainly divided into two parts: linear growth stage and stable stage. With the increase of the number and height of the transverse ribs, the overall shear strength of the geotextile increases. When the ratio of the height of the transverse ribs to the thickness of the soil layer is 0.5, the shear strength of the interface is significantly improved and the strain value on each transverse rib is more uniform. Therefore, it is recommended that the height of the transverse ribs is 0.5 times the reinforcement spacing in practical application. With the increase of the number of transverse ribs, the quasi-cohesive force increases obviously and the quasi-friction angle changes little. With the increase of the height of transverse ribs, the quasi-friction angle increases obviously and the quasi-cohesive force changes little. In the process of direct shear test, the strain of the paving part of the geotextile and the strain on the transverse rib increase with the increase of the number and height of the transverse ribs. The maximum strain is at the joint of the two. The strain of the first transverse rib is the largest and the fastest increase, which makes the joint of the transverse rib become the key of the whole system. Therefore, the height, setting position and stitching strength of the first transverse rib should be paid attention to in practical application. This study can provide a reference for the engineering application and further research of geotextiles as reinforcement materials.

To study the effect of anchor length on anchorage effect of weak rock masses in a deep tunnel, the indoor similar model tests were carried out on failure test of rock masses during the excavation opening. The variation characteristic on the failure, displacements and stress of the rock mass after excavation were analyzed comparatively under three conditions (without anchors, with short anchors and long anchors).In the loading test, the failure process of rock mass around the opening shows that the failure process of surrounding rock occurs first at the side wall, then the arch waist and the arch collapse. The surrounding rock in the arch roof after reinforcing rock bolts forms the effect of strengthening beam because of the reinforcement of rock bolts, which leads to the significant increase in the maximum settlement and failure load of the arch roof. The length of rock bolts need to pass through the plastic loosening zone of the arch roof. If the length of anchor rod is not enough to anchor the whole plastic loosening zone, there will be stratification between the anchored surrounding rock and the unanchored surrounding rock. Based on the theory of homogenization strength of rock mass, the short bolt mainly increases the effective support force of surrounding rock at shallow tunnel wall, thus improving the strength of surrounding rock, and the long bolt (cable) can regulate the stress in the elastic zone of deep surrounding rock. Therefore, the combination of the long bolt (cable) effectively regulates the stress state of surrounding rock.

Bonding with existing concrete is one of the important application situations of self-compacting concrete. With the aim of investigating the bonding characteristics between DSSC (desert sand self-compacting concrete) and other existing concrete, the bond-casting test, bonding interface splitting tensile strength and sand-filling method was used to determinate the failure mode and analyze the influence of concrete type and interface treatment method on the bonding characteristics between old and new concrete. Scanning electron microscope was used to photograph the micro-morphological characteristics of the bonding interface and determinate the distribution of gap width. The results show that the bonding performance is stronger when the linear grooving is consistent with the loading direction. Compared with linear groove cutting, the drilling interface is more efficient in interface efficiency and bonding strength. Low water-to-cement ratio reduces the bond interface gap. The effect of desert sand on the reduction of the bond interface gap is more significant with low water-to-cement ratio.

In order to reduce the panalkalisation of alkali-inspired materials for repair, the inhibition of panalkalisation of alkali-inspired materials for repair was investigated by means of surface spraying of admixtures, doping of glass powder, and doping of red mud. The inhibition mechanism was also analysed by scanning electron microscopy, nitrogen adsorption analysis and super depth of field image analysis. The results show as follows. After brushing PNC401 waterproof coating or organosilicon waterproofing agent on the surface of mortar specimen, the amount of alkali flooding is reduced by 61.3% and 26.7%, respectively. The dosage of glass powder and red mud within 15% meets the requirements of the performance of the repair mortar. The amount of alkali flooding was reduced by 60.7% and 52.0% after doping of 15% glass powder and red mud, respectively, and the number of pore spaces inside the mortar was less, no obvious cracks were produced, which reduced the dissolution of alkaline ions. The number of pores inside the mortar is less, and there is no obvious crack, which reduces the dissolution channel of alkaline ions, and it has a good inhibition effect on the alkaline flooding of alkaline stimulating materials for repairing.

Utilizing phase change materials and carrier materials to prepare phase change particles, replacing concrete aggregates for the production of phase change concrete, represents a novel technique for enhancing the durability of concrete in cold regions. In order to investigate the correlation between the compressive strength of PCC and its pore characteristics, a novel type of phase change particles with cement-encapsulated, named EPC₁₄, was prepared by using n-tetradecane (C₁₄) and EP (expanded perlite) as raw materials. Subsequently, phase change concrete (PCC-EPC₁₄) was prepared by replacing fine aggregates at an equal volume. The PCC-EPC₁₄s underwent 50, 100, 150, and 200 freeze-thaw cycles. Then, uniaxial compression tests and nuclear magnetic resonance tests were uesd to test the compressive strength and pore characteristics of the PCC-EPC₁₄s. Finally, the fractal dimension of the PCC-EPC₁₄ was calculated using fractal theory, and the relationship between compressive strength and fractal dimension was analyzed. The results show that the optimal volume replacement ratio of phase change particles to fine aggregates is 20%. At this ratio, the PCC-EPC₁₄(20%) exhibites the maximum NMR (nuclear magnetic resonance) fractal dimension, minimum porosity, and maximum compressive strength after 200 freeze-thaw cycles. Additionally, a proportional relationship is observed between compressive strength and NMR fractal dimension, while an inverse relationship is found with relaxation time signal area.

In order to study the influence of overlying load on the internal deformation of soil outside the foundation pit, a transparent soil test chamber with controllable deformation mode of retaining structure was designed and combined with particle image velocimetry technology to analyze the influence of different deformation modes of retaining structure and overlying load on the internal deformation of soil. The reliability of the test results was verified by comparing the data obtained from the transparent soil test with the prediction curve and the engineering example. The results show that the overlying load has a significant effect on the displacement field of the soil outside the pit. Increasing the overlying load or reducing the distance between the overlying load and the retaining structure will make the influence area of soil displacement outside the pit expand to the deep soil layer, and the maximum vertical settlement and horizontal displacement will also increase. The soil depth of the soil outside the cantilever type and the convex type is significantly affected by the overlying load pressure and distance. The displacement of the upper soil is significantly affected by changing the pressure and distance of the overlying load in the cantilever deformation mode, but the displacement of the middle and lower soil is more significantly affected by changing the pressure and distance of the overlying load in the convex deformation mode. Compared with reducing the distance of the overlying load in the same proportion, increasing the overlying load has a greater impact on the displacement. It can be seen that in the actual project, it is necessary to combine the local building distribution with the underground engineering environment, and take appropriate measures to avoid the most unfavorable deformation mode of the retaining structure.

With the gradual formation of “trunk-branch” linkage multi-level air cargo transportation system, the problem of low turnover efficiency of airport cargo is becoming more and more prominent, and the “trunk-branch” linkage efficient cargo allocation methods have become one of the key technologies to solve the above problems. An integer programming linkage allocation model was established with the maximum loading rate under “trunk-branch” linkage as the optimization objective while simultaneously satisfying constraints such as cabin position, cabin size, center of gravity, and weight for both trunk and branch aircraft. This model was applied based on genetic algorithms to optimize the cargo allocation between the B757-200 trunk aircraft and the ARJ21-700F branch aircraft. It was found that the average loading rate of “trunk-branch” linkage allocation was increased by 5.45% to 72.05% compared with sequential allocation.By demonstrating that the proposed “trunk-branch” linkage allocation method in this study can significantly increase the overall cargo loading capacity, and thus effectively improving the efficiency of cargo turnover at airports, laying a theoretical foundation and providing technical support for the safe and efficient development of the “trunk-branch” linkage multi-level air cargo transportation system.

The anti-corrosion maintenance workload of railway fasteners and bolts in China is large, and the cost of manual lubrication operation is high, the efficiency is low, and the labor intensity is high, and there are problems such as operation safety risks and ballast pollution. In order to solve this series of problems, an automatic lubrication device based on PLC(programmable logic controller)control that can automatically lubricate fasteners and bolts on railway tracks was developed to realize the efficiency, intelligence and automation of the construction process. Optimize the design of the equipment’s traveling mechanism, lubrication system, fastener bolt identification and sensing device, control system, etc. The adjustable spraying structure was innovatively designed to realize the oil coating operation of different types of tracks, and the sensor device that can adapt to the change of the height and position of the rail fastener bolts was innovatively designed, so as to realize the accurate identification of the track fastener bolts with different height distribution. According to the characteristics of anti-rust grease, the quantitative atomization technology of the device was analyzed and optimized. Delta’s DVP ES2-24MR PLC is connected to an external actuator, which processes data through the PLC to control the corresponding sensors in real time, and uses compensation algorithms to achieve accurate control of the equipment oil coating operation. The experiment shows that the automatic lubrication device shortens a large number of construction periods, solves the pollution phenomena such as inaccurate lubrication, oil dripping and wire pulling of the existing mechanical lubricating machine, and the device can effectively guarantee the quality and safety of the lubrication operation, effectively improve the construction efficiency and reduce the construction cost.

In order to solve the problem of real-time monitoring and accurate prediction of structural deformation of platform doors on high-speed railway lines, an artificial intelligence-based neural network method was used. Structural deformation data of platform doors, involving 210 different conditions of train length, blocking ratio, installation distance, and speed, were selected as training samples for the network model. Two neural network models, CNN(convolutional neural network) and K-Fold(K-Fold cross-validation) optimized GRNN(general regression neural network), were used to establish predictive models for platform door structural deformation under different working conditions of high-speed railways. These models were compared and verified with the remaining sample data. The research shows that both models effectively predict the operation and maintenance data of railway platform door structures. The K-Fold optimized GRNN model is superior to the CNN model in prediction accuracy. The Mean Square Error of the K-Fold optimized GRNN model is maintained within 0.22, and theRoot Mean Square Error is within 0.27, which is at the leading level in the field. The K-Fold optimized GRNN model better predicts the structural deformation of platform doors when trains pass, providing data references for the design and maintenance of high-speed railway platform doors.

In response to the common problem of secondary lining cracking in double-arch tunnel without middle drift, how to improve its mechanical characteristics to ensure the safety of tunnel construction and operation is the focus of this study. Based on the arch section of Yijin Expressway Huangjiaoping Tunnel Project, numerical simulation method was adopted, the influence of support parameters such as the thickness of the initial support, the spacing of the steel frame, and the thickness of the secondary lining of the advanced tunnel on the displacement of surrounding rock, the mechanics characteristics of the initial support and the secondary lining of the advanced tunnel were deeply studied, and reasonable and optimized support parameters were proposed. The results show that as the thickness of the initial support increases or the spacing of the steel frame decreases, the displacement of the surrounding rock of the advanced tunnel and the principal stress of the secondary lining continue to decrease, and the principal stress of the initial support continues to increase. Among them, the maximum tensile stress of the secondary lining decreases significantly. When the thickness of the initial support is 0.28 m or the spacing of the steel frame is 0.5 m, the maximum tensile stress decreases by about 15% compared with the most unfavorable condition. As the thickness of the secondary lining increases, the displacement of surrounding rock, the principal stress of the initial support and the secondary lining of the advanced tunnel decrease significantly. Compared with the thickness of the secondary lining of 0.7 m and the thickness of the secondary lining of 0.5 m, the maximum tensile stress of the secondary lining is reduced by 23.8%. Therefore, moderately increasing the thickness of the initial support or decreasing the spacing of the steel frame or increasing the thickness of the secondary lining can effectively improve the stress of the secondary lining. It is suggested that the thickness of the initial support of the advanced tunnel should be 0.28 m, the spacing of the steel frame should be 0.5 m, the corresponding steel frame type is I22b, and the thickness of the secondary lining should be 0.7 m under the shallow buried state of V-class surrounding rock.

To explore the effects of typical uncertainty factors on the seismic performance of small-and medium-span bridges during design, construction, and service, a four-span continuous small box girder bridge was taken as the engineering background, and a nonlinear dynamic model was built based on OpenSees. The influence mechanisms of seismic uncertainty, modeling parameter uncertainty, and capacity uncertainty on the seismic demand of key components were analyzed. On this basis, combined with the theory of fragility analysis, the linkage effect of the above uncertainty factors in the establishment of component fragility curves was explored, and then the degree of influence of each type of uncertainty factors on the analysis of structural seismic performance was quantified. The results show that the differences in the seismic hysteresis curves of the components are mainly caused by the uncertainties of the modeling parameters, while the differences in the peak seismic response are mainly caused by the combined uncertainties of ground shaking and modeling parameters. The modeling parameter uncertainty and component seismic capacity uncertainty can lead to an increase in the probability of structural damage, which consequently makes some components unable to meet the required damage state. The consideration of the uncertainty factor increases the probability of failure of the bridge system susceptibility curve, and the effect of uncertainty increases as the degree of damage deepens, biasing the analysis results by more than 30 percent.

The rapid increase in highway tunnel mileage also signifies a gradual rise in operational costs, and the pressing issue of high electricity operation costs for highway tunnels urgently needs to be addressed. To reduce the electricity operation costs of highway tunnels and achieve energy conservation and emission reduction, it is essential to consider optimizing the energy structure under the “dual carbon” background. This involves exploring the application prospects of renewable energy supply systems in highway tunnels and establishing a wind-solar-storage complementary power generation system. Taking a 498 m long highway tunnel load as an example, an optimization based on an improved PSO (particle swarm optimization) algorithm was conducted. The goal was to minimize the full lifecycle costs of equipment construction and maintenance, with constraints on the power shortage load rate and storage capacity, specifically for the wind-solar-storage complementary system. The results show as follows. The improved discrete adaptive particle swarm algorithm obtained the optimal solution after the 20th iteration, while the standard particle swarm algorithm reached the optimal solution near the 300th iteration, indicating a stronger optimization capability of the discrete adaptive particle swarm algorithm. Compared to the standard particle swarm algorithm, the improved discrete adaptive particle swarm algorithm reduced the investment and usage costs of the wind, solar, and storage equipment by 578 300 yuan, approximately 17.37%.Compared to the annual electricity cost of the example tunnel, which is 515 000 yuan, the full lifecycle cost of the wind-solar-storage complementary system is 3 328 800 yuan. The investment cost will be recouped within 7 years, and the investment return rate of this wind-solar complementary system is 10.47%. Over the 20-year lifespan of the equipment, the wind-solar-storage complementary power generation system will save 6 971 200 yuan in electricity expenses.

To analyze the hydrodynamic characteristics of light beacons in wind-wave environments and propose an optimization scheme based on stress concentration points, the VOF (volume of fluid) method was used to calculate the pressure distribution on the surface of the light beacon under wave and wind conditions and the resulting deformations. The results indicate that stress concentration occurs at the base of the central support of the light beacon, with the maximum displacement at the top of the light beacon. Two optimization schemes were investigated based on these findings. In the slanted support scheme, stress concentration shifted to the top of the support, reducing by 32.2% compared to before optimization. The maximum deformation was at the base in the middle, a 40.1% reduction compared to before optimization. In the end-strengthened scheme, stress concentrated at the bottom, with a reduction of 0.08% compared to before optimization, while the maximum deformation was at the top of the light beacon, which was reduced by 23.1% compared to before optimization. It is evident that the light beacon structure with slanted supports can effectively reduce stress intensity and disperse the impact of wind and waves on other parts of the light beacon, representing a better structural optimization scheme.

In response to the problem of insufficient analysis of the risk impact on system components and inadequate classification management in civil aircraft maintenance, which leads to sudden failures during component operation, a comprehensive risk impact factor was introduced to accurately evaluate the importance and potential hazards of civil aircraft system components, and a component preventive maintenance strategy considering the comprehensive risk impact of multiple factors was established. A chance maintenance decision model for civil aircraft systems was established with the objective of optimizing the maintenance cost of components, taking into account the comprehensive risk impact of multiple factors on components. The model comprehensively considers the time correlation between system components and the cost generated by the comprehensive risk impact of multiple factors on components. Example verification shows that compared to preventive maintenance decisions that do not consider the impact of component risks, the maintenance decision proposed in this article reduces the total maintenance cost of civil aircraft systems by about 20.20%, and the reduction rate of preventive maintenance and replacement frequency is about 41.23%.

The problem of scheduling and collaborative decision-making in airport metroplex or terminal areas can be significantly approached by obtaining accurate ETA (estimated time of arrival). Traditional methods are short of the ability to fine-tune the arrival metering nodes. The accurate quantitative estimation of large-volume and complex flight traffic situations is hard to achieved especially under the influence of highly dynamic environments in a medium to long term. An ETA correction method based on error feedback was proposed. Based on the aircraft performance parameters, an aircraft kinematics model was firstly constructed combined with route planning and meteorological data, which was used to give a preliminary ETA prediction through the calculation of 4D trajectory then. After that an error sequence would be constructed by comparing the difference between ATA (actual time of arrival) and the predicted results, with it the next error could be predicted using the error feedback model and the results obtained previously would be corrected. Finally, the arrival flights to a large hub airport were taken as examples to conduct a simulation, in which the rate of error within ±5 minutes that predicted 30 minutes in advance was chosen as the evaluation criteria. The simulation results show that the accuracy of ETA prediction can be improved by more than 25% in bad weather after corrected by the proposed method when compared with traditional means.

As industry and agriculture continue to evolve, the threat of organic contamination in groundwater to human health is gaining attention. Following the health risk assessment method recommended by the USEPA, and considering local natural geographical and hydrogeological conditions, organic pollutants in Zhuzhou City’s groundwater were assessed. Using a health risk assessment model, non-carcinogenic and carcinogenic risks from three exposure pathways-drinking water, skin, and inhalation-were evaluated. Results show that key organic pollutants in Zhuzhou City’s groundwater include dichloromethane, 1,2-dichloroethylene, trichloroethylene, tetrachloroethylene, p,p'-DDE, and p,p'-DDD. Non-carcinogenic risks from these pollutants are below specified limits, but every sampling points exceed carcinogenic risk limits, with ZZS119 surpassing the maximum acceptable carcinogenic risk. Inhalation is the primary exposure pathway, contributing to approximately 81% of total risk. Tetrachloroethylene poses the highest carcinogenic risk at 81.08%, followed by trichloroethylene at 11.65%. Urban discharges, volatile organic compounds from chemical plants, insecticide use in forestry, and domestic wastewater discharge have severely contaminated Zhuzhou City’s groundwater, resulting in unacceptable carcinogenic risks for local residents.

Land ecological security is the core of sustainable use of land resources, and land use changes caused by human activities change the structure and function of ecosystems, which have a serious impact on the regional ecological security system. In order to explore the changes in ecological security in Chongqing in recent years and in 2030, Chongqing was taken as the research object and PLUS (patch-level land use simulation) model was employed to simulate land use changes under the scenarios of natural development, ecological priority and development priority in 2030. Based on the ecological perspective, an ecological security evaluation index system was constructed, and the mutation model was combined to quantitatively evaluate the level of land ecological security. The results show that the spatial distribution of land use types in Chongqing is quite different, the cultivated land area decreased by 3 995.14 km², and the construction land area increased by 1 147.36 km², realizing rapid urban development. At the same time, 64.53%, 67.31% and 55.97% were relatively safe or above under the three scenarios. The spatial pattern of ecological security in Chongqing is opposite to the spatial pattern of population density and GDP, and consistent with the spatial pattern of natural data such as vegetation cover and slope. Through the ecological assessment of land use changes in previous years and under different scenarios, it provides a basis for high-quality coordinated development of ecology and economy.