In recent years, artificial intelligence has demonstrated strong pattern recognition and classification capabilities across various fields, providing new insights for lithology identification. Starting from three methods: support vector machines, neural networks, and ensemble learning, the basic principles, advantages and disadvantages of these machine learning algorithms were reviewed, as well as their research progress and application in the field of uranium ore bed lithology identification. The results show that machine learning can effectively identify the correlation between logging data and different lithologies through model training, transforming the process of lithology identification into a machine learning process. This can greatly improve the automation level and accuracy of lithology identification, holding significant practical importance and a broad development prospect.

The systematic construction of a biomechanical analysis of the full swing technique is considered essential to addressing the core issues and resolving technical problems from their root causes. Targeted special physical training is a powerful guarantee for the full utilization of technical skills. The research findings on the golf full swing technique were reviewed, its biomechanical characteristics were discussed and summarized. By further analyzing the strengths and weaknesses of full swing techniques in players of different genders and skill levels, rational recommendations for physical training were proposed, providing valuable insights for optimizing athletes' full swing techniques and enhancing the level of scientific training. During the full swing, the limbs follow the principle of proximal-to-distal motion, and muscle contractions adhere to the stretch-shortening cycle principle. Weight transfer is rationally adjusted based on specific swing patterns, and the terminal joint release effect is strengthened, contributing to the maximization of clubhead speed. In the downswing, the peak angular velocities of turnk and hip axial rotations, along with the timing and the peak speed of wrist release, are identified as the primary factors influencing clubhead speed. These factors also represent the key technical differences between male and female players. Strength and conditioning is regarded as a crucial pathway for improving full swing performance. Golfers are advised to focus on developing specific physical qualities, including upper limb muscle strength and explosiveness, lower limb muscle strength and explosiveness, as well as core stability and rotational power.

The mechanical properties of carbon fiber reinforced polymer (CFRP) composites are significantly impacted by residual stresses, which can even induce material cracking. Consequently, the accurate measurement of interlayer non-uniform residual stresses in CFRP laminates is of paramount importance for improving their manufacturing processes. The incremental hole-drilling method was employed to measure the interlayer non-uniform residual stresses in CFRP laminates. Finite element simulation was used to calculate the standard coefficient matrix between the released residual stresses and strains released in each layer. Coefficient matrix in conjunction with the measured strains was utilized to compute the residual stresses within each layer of the CFRP. The results indicate that the CFRP laminates exhibit an overall stress distribution characterized by compressive stresses externally and tensile stresses internally along the thickness direction. Furthermore, the measurement variance of residual stresses increases with the increase in drilling depth, and the interlayer residual stress values and their non-uniformity are higher in the layers closer to the center of the plate.

Aiming at the limitations of traditional synthetic aperture radar interferometry (InSAR) technology in monitoring karst collapse, a small baseline subset (SBAS)-InSAR surface deformation monitoring method integrating permanent scatterer (PS) technology was proposed to monitor the deformation characteristics of shallowly buried karst collapse groups. The study area was deliberately selected as the Dongdiu District in Libo County, Qiannan Prefecture, Guizhou Province. A dataset composed of 83 Sentinel-1A imagery acquisitions from January 30, 2020, to December 21, 2022, was thoroughly compiled and subsequently analyzed by time-series InSAR in a rigorous manner. The results show that during the period from 2020 to 2022, the collapse-prone areas undergo a phase of accelerated development in deformation rate. The monitoring results closely mirror the actual boundaries of the delineated collapse zones. The maximum deformation rate recorded within the collapse zones is -167.5 mm/a, predominantly occurring in regions with the most concentrated collapses. Moreover, a novel set of criteria for identifying karst collapse clusters was introduced, which was based on time-series InSAR technology. These criteria were founded on the analysis of the uniformity in the trends of deformation accumulation curves and the detection of local abrupt changes among any three interconnected points within the monitoring area. Such features were proposed as early indicators of the development of clustered karst collapses. The research findings are anticipated to provide valuable perspectives for the identification and characterization of the developmental processes associated with clustered, shallowly buried karst collapses.

Basalt laterite weathering profile is very suitable for studying the geochemical behavior of elements under extreme weathering. A laterite weathering profile developed on the Middle Pleistocene Duowen Formation basalt in Lingao County, northwestern Hainan Island was reported. Detailed analysis of main-trace elements, pH, Eh and cation exchange capacity (CEC) were carried out on 84 profile samples. The migration and redistribution behavior of elements in the profile was studied by mass balance calculation. The laterite weathering profile of Lingao in Hainan Island has high Fe₂O₃(17.0%~41.6%) and Al₂O₃(15.3%~28.4%), low SiO₂(10.6%~43.6%), and very high chemical index of alteration (CIA) (average 99.3). It reflects that the weathering profile has experienced strong chemical weathering with Fe and Al enrichment, and desiliconization under extreme weathering conditions. The mass balance calculation results show that alkali metals and alkaline earth metals are mostly lost along the whole pofile with a high degree. Among the transition metals, Sc, Cu and Zn are leached to a high degree in the section, V and Ni are enriched in the top and Ⅳ layer of the saprolite, respectively, and high field strength element (HFSE) are leached with different degrees in the profile. Among the redox sensitive elements, Fe mainly precipitates and accumulates in the form of Fe (OH)₃ at the top of the saprolite. Cr exists as water-insoluble Cr₂O₃ in the profile and is enriched at the top of the saprolite. Mn and Co exist in the form of soluble Mn²⁺ and Co²⁺, and their enrichment is caused by the dissolution of oxides containing Mn²⁺ and Co²⁺ during weathering. U precipitates and accumulates in the form of UO₂ at the bottom of the saprolite, while U in other layers exists in the form of soluble UO₂CO₃ and $\mathrm{UO}_{2}^{2+}$. The enrichment behavior is related to the adsorption of iron hydroxide in the profile. The slight enrichment of uranium throughout the profile may be due to groundwater introduction. It is found that the formation of ferrite laterite in Lingao section should be caused by the obvious leaching of Al and the enrichment of Fe at the top of the saprolite, while the ferrite laterite in Wenchang section is the product of both Fe and Al enrichment, which is helpful to understand the difference between the laterite weathering products of basalt in northeast and northwest Hainan Island, and has certain indicative significance for the development and utilization of mineral resources in the future.

To determine the accuracy of the light hydrocarbon parameter obtained from the headspace gas, crude oils and associated gases from six wells in the western part of the Qaidam Basin were collected. The composition and carbon isotopes of individual light hydrocarbons from headspace gas and natural gas were analyzed and compared. The results show that the content of C₅—C₇ light hydrocarbons obtained from headspace gas is higher than that in natural gas, but the relative contents of each light hydrocarbon obtained from two methods are similar. It is found that light hydrocarbon parameters calculated from headspace gas and natural gas share similar results in studying the genesis type, generation temperature and other aspects, but get different results in evaluating the maturity by using heptane and isoheptane values. Besides, the carbon isotopes of individual light hydrocarbons in headspace gas are greater than those in natural gas, among which cyclo-alkanes have the smallest carbon isotope difference. Particularly, the carbon isotopes of methylcyclohexane (δ¹³C_MCC6) in the headspace gas are close to those in natural gas. Therefore, the main parameters of light hydrocarbons and δ¹³C_MCC6 can be accurately obtained from the headspace gas of crude oil. The research results provide a basis for enriching the application of light hydrocarbon geochemistry in oil and gas accumulation.

The Ordos Basin's marine carbonate reservoirs often experience downhole complexities such as gas invasion, lost circulation, and borehole collapse during drilling. It is particularly important to systematically evaluate the overpressure mechanisms and accurately predict formation pressure for the exploration and development of the target strata. The carbonate reservoir of the Ordovician Majiagou Formation in the eastern Ordos Basin was selected as the research target. Overpressure mechanisms were analyzed using the combination of well log curve analysis, effective stress-acoustic velocity method, acoustic velocity-density method, and comprehensive analysis method. A physical model of elastic modulus for carbonate rock matrix, framework, mixed pore fluid, and saturated fluid rock was established, and combined with the effective stress principle, a method for predicting formation pressure was developed, applicable to the Majiagou Formation in the eastern Ordos Basin. Finally, the model's accuracy was verified using field data. The results indicate that hydrocarbon generation is the primary cause of overpressure in the target reservoir, with undercompaction and structural compression as secondary factors. The new model achieves a relative error of less than 10%, demonstrating strong applicability and high predictive accuracy. The research results provide guidance for the study of hydrocarbon accumulation in the Majiagou Formation in the eastern Ordos Basin.

The pore structure is a pivotal determinant of the physical properties of tight sandstone reservoirs, and elucidating its characteristics holds great significance for oil and gas exploration and development. Taking the 4th member of the Xujiahe Formation tight sandstone reservoirs in Tianfu Gas Area as an example, the pore structure characteristics, fractal features, and fluid mobility of the Xu-4 sandstone in the study area were systematically analyzed through thin section identification, scanning electron microscopy observation, nuclear magnetic resonance testing, high-pressure mercury intrusion testing, and X-ray diffraction experiments, combined with fractal theory. The results indicate that the sandstones of the 4th member of the Xujiahe Formation in the study area are predominantly composed of feldspar lithic sandstone, belonging to an ultra-low pore-ultra-low permeability pore type reservoir. The pore type is primarily feldspar-dissolved pores, and the throat type is predominantly sheet throats. According to the morphology of the high-pressure mercury injection curves and nuclear magnetic resonance outcomes, the pore structure of the 4th member of the Xujiahe tight sandstone reservoir is categorized into three distinct types. Among them, the material properties of the I-type samples are the best, with larger pore-throat radii, good connectivity and sorting of pore-throat, strong fluid mobility, and the best reservoir quality. The pore structure and fluid mobility of the fourth member of the Xujiahe tight sandstone reservoir are affected by sedimentary structures and mineral content. Specifically, reservoirs with coarser grain sizes and better sorting demonstrate superior pore structure and fluid mobility. Furthermore, quartz, the primary rigid mineral in sandstones, exhibits resistance to compaction, thereby safeguarding the reservoir pores to a certain extent. However, calcite and clay minerals will occupy pore space, resulting in deterioration of the pore structure and fluid mobility of the reservoir.

To enhance the long-term displacement prediction accuracy of landslides, the GCformer model was applied to landslide displacement forecasting, and a novel landslide displacement prediction approach grounded in the GCformer model was proposed. This methodology leveraged rainfall and displacement as input variables, utilized the GConv_msk module to capture the global information of the sequence, and combined a linear scaling technique of sequence length to efficiently extract data features. Concurrently, the PatchTST model was employed to automatically extract short-term and long-term signals from the sequence data, in order to obtain more comprehensive historical information and bolster the model's robustness and modeling capability. Finally, the landslide displacement monitoring data from Jinliuping Village and Yuanshitan Village in Huichuan County, Dingxi City, Gansu Province, were utilized for case validation. The findings demonstrate that the proposed model exhibits superior prediction accuracy and reliability. In comparison to the Autoformer model and the FEDformer model, the GCformer model is found to achieve the lowest error in both total displacement and vertical displacement.

Traumatic brain hemorrhage(TBH) often results in persistent cognitive and behavioral dysfunctions, with traditional rehabilitation models failing to adequately address self-efficacy and environmental interactions. Stage-based nursing interventions grounded in social cognitive theory(SCT) synergize cognitive restructuring, behavioral reinforcement, and environmental support. However, their application in TBH remains understudied. Aiming to examine the impact of SCT-based stage nursing interventions on cognitive function, self-management, self-efficacy, and daily living ability in TBH patients, a total of 105 TBH patients were randomly assigned to an intervention group(n=53) and a control group(n=52) by using a random number method. The control group received conventional rehabilitation therapy, while the intervention group received stage-based nursing interventions based on SCT in addition to conventional therapy. Changes in cognitive function, self-management ability, self-efficacy, and activities of daily living were compared between the two groups before and after the intervention. Cognitive function was assessed by using the Montreal cognitive assessment-basic(MoCA-Basic), self-management ability was evaluated by using the appraisal of self-care agency scale-revised(ASAS-R-C), self-efficacy was measured by using the general self-efficacy scale(GSES), and activities of daily living were assessed by using the Barthel index. The results reveal that after the SCT-based stage nursing intervention, the intervention group show significantly higher scores on MoCA-Basic, ASAS-R-C, GSES, and the Barthel index compared to the control group(P<0.05), with substantial improvements observed across all indicators. Stage-based nursing interventions grounded in SCT can significantly enhance cognitive function, self-management, self-efficacy, and activities of daily living in TBH patients, demonstrating considerable clinical value.

In order to compare the clinical effect of different surgical technique of ligamentum flavum in percutaneous endoscopic interlaminar lumbar discectomy. From March 2015 to March 2019, 86 cases of L₅-S₁ lumbar disc herniation (LDH) were analyzed retrospectively. According to the different treatment of ligamentum flavum during operation, the patients were divided into control group (n=55) and modified group (n=31). The age, gender, course of disease, duration of surgery, intraoperative bleeding, hospital stay, and surgical related complications between the two groups of patients were analyzed and compared. One month, three months and six months after the operation, the routine outpatient reexamination and follow-up were carried out. Numerical rating scale(NRS) and modified macnab were used to evaluate the effect of operation. SPSS 19.0 was used to process the data. Mean±SD was used for measurement data. Comparison between groups using independent sample t-test, and analysis of variance of repeated measurement data was used for the NRS score comparison before and after operation. The counting data were expressed in percentage, Fisher exact test or χ² test were used for comparison between groups, and Mann Whitney rank sum test was used for comparison of follow-up time and grade grouping data between groups. The results show that the postoperative pain score of both groups decrease significantly(overall variance within the group F_within=197.477, P=0.001). There is no difference between the two groups (inter group overall variance value F_interg=1.701, P=0.203).The time factor has no effect on the results of the two groups(Interaction effect value F_inter=2.231, P=0.108). The NRS score of the modified group is significantly lower than that of the control group (t=2.086, P=0.046). According to modified Macnab criteria, there is no significant difference between the two groups (distribution of postoperative outcomes U=782.000, P=0.308). It is concluded that the modifiedsurgical technique of ligamentum flavum in the PEILD will not prolong the operation time or increase the amount of bleeding. While removing the herniated intervertebral disc, it can preserve the integrity of the relevant tissue structure, achieve satisfied clinical effect, and conforms to the core concept of minimally invasive surgery.

The mining method of ion-type rare earth ores has been optimized by the in-situ leaching process. However, unorganized leakage may cause resource loss and impacts on the ecological environment. Therefore, anti-seepage work during the mining process is of particular importance. Based on three grouting anti-seepage materials, namely cement composite material (C-CM), liquid silicon-based composite material (Si-CM), and acrylate composite material (A-CM), and compounded with kaolin tailings, various indicators of each curtain grouting material were analyzed and compared through tests including the pH, density, viscosity, setting time, solid sand body strength test, slurry diffusion simulation, permeability, and durability test of the curtain grouting materials. The results indicate that the solid sand body of C-CM has relatively high strength, while A-CM and Si-CM have lower viscosity, stronger groutability, and the solid sand bodies formed have lower permeability coefficients, making them more suitable for anti-seepage in areas with smaller fractures. Si-CM degrades relatively quickly in dry-wet cycles and freeze-thaw cycles, and the degradation product is mainly SiO₂. In addition, the strength and anti-seepage performance of the solid sand body of the anti-seepage material can be improved to a certain extent by adding kaolin tailings, and the early durability of the material is also increased.

In the process of coal seam mining, it is easy to cause problems such as large roof overhang area and long collapse step, which affects the failure form of the surrounding rock of the roadway and the deterioration and failure of the supporting body. In view of the occurrence of thick and hard roofs in the 113105 working face of the Bojiang Haizi Mine and the instability of the narrow coal pillars along the empty roadway, the use of roof cutting and pressure relief is an effective way to effectively solve the problem of roof overhang, and the design of its key parameters has an important impact on the pressure relief effect. In order to explore the influence of different roof cutting pressure relief heights on the roof stress evolution law above the narrow coal pillar along the empty roadway, the effect of lateral roof cutting of roadway was studied by combining theoretical analysis, numerical simulation and field observation. Based on the slip-revolve stability theory of masonry beams, the mechanical model of the roof of the coal pillar under different roof cutting heights was constructed, and the bearing stress distribution equation of the coal pillar after different roof cutting heights was obtained. FLAC3D software was used to simulate the stress distribution and displacement evolution characteristics of the coal pillar roof under different roof cutting heights. The simulation results show that the slitting surface formed after the implementation of roof cutting technology effectively blocks the stress propagation path, and the vertical stress peak value in the coal body on both sides of the roadway decreases, and the pressure relief effect gradually increases with the increase of the roof cutting height, when the roof cutting height reaches 19 m, the stress of the coal pillar roof decreases by 17.22 MPa, and the pressure relief rate is 43.4%. The displacement of the roof of the coal pillar gradually decreases with the increase of the roof cutting height, and the reduction rate gradually decreases. The field test shows that according to the designed roof cutting height, the stress of the surrounding rock is significantly reduced, and the deformation degree of the roadway meets the normal mining requirements.

The conflict between coal resource extraction and ecological environmental protection is particularly pronounced in the Gaojialiang coal mine of Inner Mongolia. To accurately characterize the deformation extent and evolutionary patterns of mining-induced ground subsidence within the study area, small baseline subset interferometric synthetic aperture radar (SBAS-InSAR) technology combined with Sentinel-1 radar remote sensing data were utilized to obtain the annual average deformation velocity and time-series cumulative deformation over three primary panels. Additionally, the Kriging interpolation method was employed to predict and supplement data in decoherence regions, ensuring comprehensive coverage of the deformation field. The results show that three distinct subsidence zones are identified, spatially correlated with the mined-out areas of panels 203, 301, and 401, respectively. The subsidence is characterized by slow deformation, with a peak annual average deformation velocity of approximately -34 mm/a. The temporal initiation and spatial propagation of subsidence in the three panels align closely with the actual mining sequence and operational conditions. Among these, panel 401 exhibited the largest subsidence area, covering approximately 4.56 km², with a maximum cumulative deformation of -189 mm, followed by panels 301 and 203 in descending order. Ground fractures identified through high-resolution optical remote sensing imagery are consistent with field investigations, predominantly distributed in the zones of maximum deformation intensity. Based on the deformation characteristics and fractures distribution, three high-risk geohazard zones are delineated within the study area. The primary driver of ground subsidence is attributed to longwall mining activities, while geological structures and precipitation infiltration also contributed to the deformation process. SBAS-InSAR technology has good application effects in monitoring large-scale mining-induced ground subsidence, and can provide crucial technical and data support for geological disaster prevention and ecological environment restoration in Gaojialiang mining area.

The evolution of submarine channels and their sedimentary units under a million-year scale is related to factors such as sediment supply, sea-level change, paleotopography and tectonic movements. However, the changing rate of sea level has not been deeply associated with the type, scale, and sand-body distribution of submarine channels and their surrounding sedimentary units. Taking the central Oligocene submarine channel in the northern Atlantic basin as an example, based on three-dimensional seismic data cube, seismic-facies characteristics of submarine channels with their sedimentary units were characterized. 90°-phasing transformation and stratal slicing techniques were used to depict the planar distribution of submarine channel with sedimentary units. Frequency spectral decomposition was used to analyze the evolution of sedimentary units and the distribution of sand bodies. The sedimentary model of submarine channels with changing rate of sea level at a million-year scale was established. The results indicate that from the early to late Oligocene, a composite system of sandy submarine channel-terminal fan, a composite system of sandy-muddy filled submarine channel-crevasse fan and a composite system of muddy submarine channel are developed in sequence. The mass transport deposits are always accompanied. Sedimentary evolution process is mainly controlled by global sea level and can be divided into a slow sea-level dropping period of early Oligocene, a rapid sea-level rise period of middle Oligocene and a rapid sea-level dropping period of late Oligocene. The slow sea-level fall is conducive to the transportation of coarse terrestrial clastics through submarine channels into the oceanic basin, which is an important prerequisite for the formation of sandy submarine channels, terminal fans and large associated mass transport deposits. Therefore, sand bodies are most developed in the lower Oligocene.

In deep oil and gas development, it is difficult to drill targeted with traditional sliding drilling tools because of the increasing number of wells with complex structure. To help solve the problem of wellbore trajectory control in complex structural wells, a discontinuous directional rotary steerable structure was proposed. Moreover, a mechanical model of discontinuous directional rotary steerable bottom hole assembly(RSBHA) was established by combining the element division idea of finite element method and the continuous beam-column theory. The bit side force and dip angle of were calculated by compiling mechanics program. The effects of borehole geometry parameters, drilling parameters and drill assembly structure parameters on mechanical properties were analyzed. It is concluded that weight on bit and inclination of hole have little influence on bit side force, but the structural parameters of drill assembly have great influence. The research results provide theoretical premise for the optimization of RSBHA structure and drilling parameters, and provide mechanical support for accurate control of wellbore trajectory.

Fracturing and packing is a key technology for maintaining and enhancing production in medium-to high-permeability unconsolidated sandstone reservoirs. However, after production begins, the loose cementation of the reservoir, combined with proppant embedment and formation sand invasion, significantly reduces fracture conductivity. Currently, there is a lack of methods to predict fracture conductivity under the combined effects of proppant embedment and formation sand blockage in such reservoirs. A fracturing and packing simulation device was used to conduct composite experiments on proppant embedment and formation sand blockage under closure stresses ranging from 5 MPa to 20 MPa, unconsolidated rock plate samples were used to simulate fracture surfaces. Based on the experimental results, the controlling factors and developed models were analyzed to predict permeability loss due to proppant compaction, fracture width loss caused by embedment, and dynamic permeability changes due to formation sand blockage. The results show that proppant embedment and compaction after fracture closure significantly reduce fracture conductivity, with the main factors being closure stress, reservoir strength, and particle sizes of the proppant and formation sand. Formation sand blockage also exhibits a time-dependent effect, contributing to dynamic conductivity decline. In a typical unconsolidated sandstone reservoir in the Bohai Oilfield, the calculated fracture width loss due to embedment is approximately 19.34%, permeability loss from closure and compaction is about 34.15%, and dynamic permeability loss from formation sand invasion is around 22.89%. The combined effect of these factors results in a total fracture conductivity loss of approximately 59.06%. To prevent excessive blockage, it is recommended that the initial fracture width be maintained at no less than 12.5 mm, large-particle proppants be used, and production rates be controlled during the early production phase. The research results provide important guidance for optimizing fracturing and packing parameters and improving production in unconsolidated sandstone reservoirs.

Under the traditional design scheme, the design quantity of main girder of the bridge erector is redundant and there are many consumables, which will reduce the production efficiency, and the existing optimization methods have the problem of low convergence accuracy. An enhanced beluga whale optimization (EBWO) based on quadratic interpolation strategy was proposed, and lightweight design of main girder of the 600t bridge erector was carried out. Firstly, six test functions were applied to evaluate and compare the effectiveness of the beluga whale optimization (BWO), EBWO and three other prevalent optimization algorithms, focusing on their convergence characteristics. Then, a mechanical analysis was conducted on the bridge erector girder under the real loading conditions. An optimization model was established by combining bridge girder design specifications and mechanical requirements, and the cross-sectional area optimization of main girder of the bridge erector was carried out. The results show that EBWO has the enhanced stability and convergence characteristics. It is proved that the optimized main girder is reduced by 19.3%, and can meet the safety requirements.

In order to resolve the problem that the volume of APP-based car-hailing industry increases and the trip counting results are susceptible to errors due to environmental influences, a novel method of APP-based car-hailing trip counting detection was proposed. The conversion mechanism between global navigation satellite system(GNSS) coordinate system and other coordinate systems was analyzed, and a network car counting device was designed by using loose coupling model and Kalman filter processing for combined navigation. The test results show that the distance counting device has a distance counting error of 0.42% in the straight road section and a distance counting error of 0.56% in the circular road section, and the distance counting accuracy meets the maximum error range required by the Verification Regulation of Taximeters(JJG 517—2016), which provides a new method for solving the distance counting error problem of APP-based car-hailing.

In order to solve the problems of large heat leakage and unclear stress of the adiabatic support structure in the cryogenic storage tank, a finite element model of a 37.4 m³ storage tank was established by the method of thermal-solid interaction, and the heat transfer, stress and deformation of the tank were analyzed, and the supporting structure was optimized. The results show that the daily evaporation rate of liquid nitrogen is 0.10%/d when the heat leakage through the supporting structure is 62.18 W, and the heat leakage of the supporting structure decreases with the decrease of ambient temperature. The influence of liquid temperature on the storage tank is mainly concentrated in the support structure and the inner tank, and the stress and deformation of the support structure increase greatly after considering the influence of temperature, and the maximum stress of the inner tank is less affected, and the deformation is increased by 11.81 times. When storing liquid hydrogen, the heat transfer of the support structure increases by 26% compared with liquid nitrogen. The topology of the supporting structure under the sliding end was optimized with the minimum heat transfer as the optimization goal. The heat transfer of the “Y” type support structure is reduced by 27.20% and the maximum stress is reduced by 7.73%.

With the transformation of the modern power system, the application of grid-connected inverters is increasing, and the transient synchronization stability of inverters after disturbance is becoming prominent. Previous research on transient synchronization stability mainly focuses on the dynamic of the phase-locked loop, with less consideration of the impact of outer loop control, resulting in a cognitive bottleneck in understanding transient synchronization mechanism. To address these issues, the grid-following voltage source inverter system was modelled, taking into account the inverter control strategy and limiting elements in detail. Subsequently, the impact of different voltage drops on the stability region of the equilibrium point was analyzed, and the effects of outer loop control proportional integral (PI) and limiting elements on transient synchronization were discussed. The influence mechanism of outer loop control on the transient synchronization stability of inverters was revealed systematically. Finally, the effectiveness of the proposed theory was verified in PSCAD/EMTDC.

To enhance the safety monitoring of power transmission lines, the distributed fiber Bragg grating array sensing technology was employed to measure the dynamic motion characteristics of optical power ground wire (OPGW) cables in laboratory conditions. The results show that this technology can effectively monitor the dynamic behavior of OPGW under simulated aeolian vibrations and galloping states, clearly recording various vibration patterns. The experimental data reveal that by increasing the spatial density of the grating array sensors and reducing the system's low-frequency phase drift, the monitoring performance can be further enhanced. It is evident that the distributed vibration sensing technology based on fiber Bragg grating arrays provides a novel technical approach for the distributed dynamic structural health monitoring of OPGW cables.

The armature structure and characteristic parameters in electromagnetic launch systems have a significant impact on the launch performance. In order to explore the dynamic characteristics and influencing factors of composite armatures, based on Maxwell's equations and electromagnetic field theory, a mathematical model of dynamic emission coupling between embedded and semi embedded composite armatures was derived. The influence of factors such as the capacity and initial working voltage of energy storage capacitors, the number of turns of driving coils, and the structural parameters of composite armatures on acceleration performance were analyzed and studied. The influence of structural parameters a, c, and d of composite armatures on emission performance was calculated. The results show that the higher the initial working voltage and capacitance of the energy storage capacitor, the higher the emission efficiency of the composite armature. The number of turns of the driving coil in the synchronous induction coil gun also affects the firing performance of the composite armature. As the number of turns increases, the firing efficiency does not always increase. The parameters a and c have little impact on the emission performance, while parameter d has a significant impact on the emission performance. The proposed mathematical model and analysis results can provide a theoretical basis and data reference for the design of composite armatures.

In the coal-water slurry gasification system, a reduction in the temperature of the syngas pipeline can cause acid gases to condense, which may lead to corrosion of the pipeline's inner surface and potentially result in perforation leaks. To enable prompt detection and precise localization of any leakage or damage within the syngas pipeline, The techniques were explored for identifying and locating such issues through distributed temperature sensing(DTS). An algorithm based on an adaptive variance threshold was proposed for DTS detection and localization. Initially, hierarchical clustering was utilized to recognize detected signals, facilitating differentiation between normal operating conditions and those indicative of leaks or damages. Following this, identified leak signals undergo processing via variance analysis combined with adaptive threshold settings to accurately determine leak or damage locations. This approach shows improved accuracy in pinpointing leak or damage sites compared to fixed threshold methods as well as selective average threshold methods, enhancing positioning precision by 0.32 m and 0.17 m respectively. A temperature measurement experiment conducted at a coal gasification facility successfully confirmed accurate identification of leakage or damage points.

The traditional particle swarm optimization (PSO) algorithm still has shortcomings in terms of performance and efficiency of cloud computing task scheduling, such as low local search efficiency and limited search accuracy, which often makes it difficult to find the global optimal solution and easily falls into the local optimal solution. To solve this problem, an improved particle swarm optimization task scheduling algorithm(IPSO) was proposed. Firstly, a opposition-based learning strategy was used to create a more homogeneous initial population and the Rate of convergence of this algorithm was enhanced. Secondly, in the particle update process, the sine cosine algorithm(SCA) was introduced to enhance the optimization ability of the particles and balance the two processes of global search and local development. Finally, a search behavior based on average fitness was added to further expand the search solution space to find better optimal solutions and prevent falling into local optima. Experimental verification was conducted on the CloudSim simulation platform. The experimental results show that the improved particle swarm algorithm has significant advantages in reducing the cost and maximum completion time of system tasks. In particular, when the number of tasks reaches 500, IPSO improves the total cost by 10%, 4.6%, 8.6%, 9.2%, 8.2%, 10.4% and 11.3% respectively compared with adaptive particle swarm optimization (AdPSO), sine cosine algorithm-particle swarm optimization (SCA-PSO), simulated annealing particle swarm optimization (SAPSO), enhanced phagocytosis genetic algorithm (EPGA), competitive crossover mechanism genetic algorithm (C2PGA), opposition based learning-particle swarm optimization (OBL-PSO) and PSO, and improves the maximum completion time by 34.1%, 27%, 41.7%, 28.5%, 21.6%, 50.3% and 54.8% respectively, which verifies the feasibility and effectiveness of IPSO in solving cloud computing task scheduling problems under different task scales.

Aiming at the issue of how to realize the dynamic updating of the digital twin model of historic buildings, a “build-compare-update” updating idea was proposed. Firstly, the shape distribution method was used to draw the shape distribution curve of the digital twin model of the historical building at different time points, based on completing the construction of the digital twin model of the historical building. Secondly, the mean absolute error method was used to assess the similarity of the two models. Furthermore, according to the results of the similarity assessment, the updating strategy for the model of the components of the historic building was set up and the updating of the digital twin model was completed with the help of relevant software. Finally, to validate the design, the arch column component of the Jade Buddha Hall of Hongci Temple was used as a case study. The results show that the proposed idea of updating the historical building model and its implementation method not only lay the foundation for realizing the dynamic updating of the digital twin model of historical buildings, but also provide reference value for the intelligent protection of historical buildings.

Modeling social networks using directed graphs and calculating the influence of nodes in settlement graphs using deep learning methods are important branches in the field of social research. In order to solve the problem that graph neural networks cannot well calculate the influence of nodes based on constructed node features, inspired by GraphGPS, a heat module was designed to propose a method of calculating the influence of nodes that integrated semantic, behavioral, and heat information in real networks. Firstly, the self-information obtained based on nodes' multiple centrality and orthogonal distribution sampling was used as the initial semantic features of the nodes. Secondly, the node features were fused by graph neural network. Once again, the node heat information was learned by the heat module. Finally, the fusion of the extracted semantic, behavioral, and heat features was implemented to calculate the node influence. Experiments were conducted on four real network datasets. The results show that the model with the addition of the heat module can effectively calculate node influence.

The traditional steady-state visual evoked potential (SSVEP) brain computer interface system usually uses a small number of frequencies for encoding, resulting in a limited number of encodings to dozens, which cannot meet the demands of environmental tasks with a large number of instructions. To address this issue, a Hamming distance multi frequency code (HDMFC) paradigm and corresponding recognition algorithm based on Hamming distance were proposed. The Hamming distance was combined with stimulus paradigm encoding and signal recognition algorithms to encode 120 instructions using 8 frequency signals. Data collection and classification experiments were conducted on 7 subjects. The results show that the accuracy of the 120 encoding online experiment based on Hamming distance can reach 90.60%. The research results provide an effective method for increasing the number of SSVEP paradigm codes and improving classification performance, verifying the practicality and effectiveness of Hamming distance in this field.

In response to the challenges of low efficiency, high cost, and difficulty in deployment on mobile devices in current road damage detection technology, a novel road crack detection method based on the improved YOLOv8 algorithm, named YOLOv8 road crack (YOLOv8-RC), was proposed. The C2f module, based on the YOLOv8n architecture, was enhanced through the introduction of dynamic snake convolution technology, which more accurately identified tubular structural features and adaptively focuses on fine and curved local structures. Furthermore, a highly efficient multi-scale attention(EMA) mechanism was incorporated into the algorithm, effectively enhancing recognition accuracy. In the neck structure of the model, a weighted bidirectional pyramid network(BiFPN) was added to achieve multi-scale fusion of features, thereby optimizing both the accuracy and efficiency of the algorithm. Experimental results on the RDD2022-China-MotorBike and RDD2022-Japan datasets demonstrate that the improved YOLOv8n-RC model achieves mAP50 scores of 78.8% and 43.8%, respectively, representing improvements of 3.9% and 3% over the original YOLOv8n model. The total number of model parameters for the proposed algorithm is only 2.84 M, and the computational complexity is 7.8 G, underscoring the practicality and superiority of this method.

An improved DGA-YOLOv8 offshore ship target detection algorithm was proposed to tackle the issues of low accuracy and single ship detection categories that are present in traditional ship target detection algorithms. Firstly, the network was adapted to include deformable convolution, which expanded the model's receptive field. Learnable offsets were introduced, allowing the model to adaptively adjust the size and shape of the receptive field in response to the actual shape of the object, ensuring that the convolution area can precisely cover the contour of the ship object. Secondly, the incorporation of a GAM(global attention mechanism) attention mechanism enabled the network to effectively emphasize the key features of ship targets, thereby enhancing the target recognition capability. The experimental results demonstrate that the improved algorithm achieves accuracy and average accuracy mean (mAP) of 96.4% and 92.2%, respectively. An frames per second(FPS) of 43.55 is recorded, indicating not only an enhancement in accuracy but also the maintenance of a certain detection speed, thus fulfilling the requirements for real-time detection. When compared with other mainstream algorithms, such as faster region-based convolutional neural network(Faster R-CNN) and YOLOv5s, YOLOv10. The results show that the proposed algorithm exhibits higher average accuracy and significant superior classification performance.

In order to improve the accuracy of in-camera parameter calibration and reduce the error caused by inaccurate estimation of corner coordinates, a subpixel iterative corner optimization algorithm was proposed. By modeling the camera image, integrating the distortion mathematical model, and using the subpixel iterative algorithm, the gradient value changes of points in the search window were calculated and the corner coordinates were iteratively optimized to provide more accurate initial values for calibration. Combining with the optimized corner coordinates, Zhang's calibration method was used to solve the internal parameters, and the influence of corner points on the acquisition of diagonal points and camera calibration was discussed through experiments. The calibration accuracy was characterized by reprojection error, and the effectiveness of the iterative algorithm was tested. The experimental results show that the algorithm can effectively improve the accuracy of corner acquisition and the calibration accuracy of camera parameters by using fewer iterations.

Remote sensing images are characterized by diverse scales, dense arrangement and small target sizes, etc. Aiming at the problem that there is much background noise in remote sensing images and vehicle targets are small and difficult to be acquired. A vehicle target detection algorithm based on improved feature fusion method, Atiny-YOLO was proposed. Firstly, an additional detection layer for small targets was introduced into the Neck layer of YOLOv5 so as to generated a small target detection algorithm for drone remote sensing images. Neck layer to introduce an additional detection layer for small targets, so as to generated a larger-scale feature map and effectively identified the detailed features of small objects. Secondly, a split operation was added to the C3 module to reuse the image feature information, and the Swin Transformer module was further optimized to improve the usage rate of the effective information. Lastly, by improving the feature fusion channel, the detection accuracy was improved while the model parameters were reducing the model parameters. The Atiny-YOLO algorithm was tested on the AU-AIR(aerial universal autonomous inspection and recognition) dataset. The experimental results show that the average detection accuracy of the Atiny-YOLO algorithm compared to the baseline algorithm is improved by about 2.9%. It reaches 95.5% and the detection speed reaches 234 frames/s. These results verify that the Atiny-YOLO algorithm meets the real-time performance while the model detection accuracy is greatly improved.

In order to study the mechanical properties of the column foot joint of a self-resetting cylindrical pier, the mechanical mechanism of self-resetting cylindrical pier column foot joint with circular section was analyzed theoretically. The calculation formula of key points of the whole force and displacement hysteresis curve of the pier was derived, including yield point, failure point, etc. The theoretical analysis model of the relationship between pier jacking force and displacement was established. Based on OpenSees platform, fiber hinge model was used to model the section of pillar foot of self-resetting energy-consuming pier. Combined with pseudo-static test results, the feasibility and accuracy of the fiber hinge model were verified. On this basis, a self-resetting cylindrical pier was set up by fiber hinge model, and the key point of the deduced force-displacement hysteresis curve was compared with the skeleton curve of the simulated cylindrical pier to verify the accuracy of the deduced method. The results show that the derivation method can obtain the pressure relief point, yield point and failure point of self-resetting cylindrical pier, which can provide reference for the research of self-resetting pier with circular section in the future.

In order to study the applicability of the assembled subway station structure in the liquefiable site of the seismic fortification area, based on the engineering practice of Shuangfeng Station of Changchun Metro, the seismic response analysis of the assembled subway station structure in the liquefiable stratum was carried out by using the finite difference software FLAC^3D. Compared with the calculation results of the corresponding cast-in-place subway station conditions, the pore water pressure of the foundation, the dynamic response and floating characteristics of the subway station structure and the deformation characteristics of the assembled subway station structure were studied. The results show that, similar to the calculation condition of cast-in-place underground structure, in the calculation condition of assembled subway station in liquefiable site, the pore pressure ratio of site soil shows three stages: initial slow increase stage, middle rapid increase stage and final gentle stage. When the seismic intensity is high, the underground structure has a significant inhibitory effect on the liquefaction of the surrounding soil. The acceleration response of the prefabricated station structure is smaller than that of the cast-in-place structure, which reflects its flexible adaptation to the deformation of the terrain in the liquefiable site. The connection between the side wall and the middle plate is the key part of structural strength control. When the intensity of the input ground motion is low, the vertical displacement changes of the structure are manifested at different positions of the bottom plate show the development stage of a small amount of sinking at the beginning, then a sharp rise, and finally a downward trend, but with the increase of the intensity of the ground motion, this phenomenon is gradually not obvious. The deformation of the assembled subway station structure under horizontal ground motion is closer to the shear deformation. Its flexible connection is easier to adapt to the larger vertical relative deformation than the rigid connection of the cast-in-place station, and its anti-overturning ability is better.

In order to realize the optimal design of rock-socketed pile foundation in mountainous area and effectively prevent the rupture of the rock, the compression mechanical behaviors and failure mechanisms of brittle rocks with different lithologies were experimentally and numerically investigated. Firstly, uniaxial compression tests were carried out on five kinds of brittle rocks based on the self-made compression testing system. Acoustic emission (AE) monitor system and digital image correlation (DIC) technology were used to discuss the characteristic parameters of AE signals during the crushing. Moreover, the characteristics of critical failure precursors and the evolution rules of damage failure of different rocks were obtained by using the nonlinear explicit finite element (FE) method. The experimental results were in good agreement with the corresponding FE ones. The results show that there are the obvious AE phenomena in brittle rocks during the uniaxial compression test, and the active degree of ringing count and accumulated energy can describe the internal damage of the specimens effectively. At the initial stage of the compression, there is no obvious crack on the rock surface. However, more cracks appear on the surface of the specimens with the increase of the compressive stress. The specimens are destroyed instantaneously when the compressive stress reaches the peak stress, and no new cracks are generated. The distribution and evolution of local strains can intuitively predict the breeding and expansion of new fissures. The research results provide theoretical reference for monitoring and warning of rock failure and foundation design of transmission line in mountainous area.

Cultural relics protection units are important carriers of Chinese outstanding traditional culture. It is of great significance to study the spatial differentiation of cultural relics protection units and the differences in the results of multi-scale driving factors, in order to continuously promote the inheritance of history and culture, and to prosper the development of regional cultural undertakings and cultural industries. Huizhou cultural relics protection units were taken as the research object, and standard deviation ellipse, kernel density estimation and geographic detector methods were used in the analysis of spatial and temporal differentiation and driving factors of cultural relics protection units. The results show that the cultural heritage units in Huizhou region present the time series characteristics of “dispersed-concentrated-dispersed”, and the center of distribution gradually shifts from the middle to the south. The spatial aggregation of cultural heritage units is remarkable, the overall performance of the “V” distribution pattern, specifically concentrated in Shexian County and Jixi County. Natural geographic factors and human geographic factors have an impact on the spatial differentiation of cultural heritage units.

The water absorption and expansion characteristics of the swelling surrounding rock can have adverse effects on the tunnel lining structure, which can easily lead to the induction of various engineering disasters, and impact the progress of the project, as well as the normal operation of the train in subsequent stages. Therefore, the mechanical characteristics and support method selection of such tunnels have always been of great concern. Taking a tunnel passing through expansive mudstone in Inner Mongolia as an example, based on field monitoring and numerical calculation methods, the deformation and failure characteristics of the tunnel lining structure in mudstone tunnel under the original lining conditions were analyzed. Subsequently, the applicability of double-layer preliminary lining in such tunnels was studied from the aspects of support deformation and mechanical properties, and corresponding lining parameter suggestions were proposed. The results indicate that the expansion of mudstone causes the deformation of the original lining structure (single-layer preliminary lining) to reach a magnitude of 309 mm. Such deformation leads to significant encroachment of the lining and necessitated forced arch replacement during the tunnel construction process. In comparison to the single-layer preliminary lining, the double-layer preliminary lining construction method has been found to significantly improve the deformation and stress state of the tunnel in expansive mudstone, achieving a deformation reduction rate that exceeds 63.88%. As the thickness of the secondary preliminary lining increases, the deformation and stress of the preliminary lining gradually decrease, achieving a maximum deformation reduction of 234.5 mm and a compressive stress reduction rate of up to 39% under various conditions. Consequently, the double-layer lining construction method can be considered for tunnels in expansive mudstone, with the thickness of the secondary preliminary lining being reasonably selected based on deformation requirements. The research findings can serve as a valuable reference for similar projects in the future.

In order to study the structural strength of platform fire fighting vehicles, and to address the impact of the structural design of its sub-frame, stabilizers, and booms on the stability and safety of the entire vehicle, ANSYS software simulation was used to study its structural strength, and experimental verification was conducted. A simplified 3D model of the sub-frame with stabilizers, and the booms were established separately, the stress distribution under various working conditions was simulated. Then, an experimental environment was set up for stress testing. The results show that when the entire boom is horizontally extended to the left or right of the fire fighting vehicle, it is more likely to experience the phenomenon of virtual legs, with the values of 22.5 mm and 17.5 mm, respectively. The maximum stress of the boom during the retraction and extension process occurs in the area of the folding arm's variable amplitude hinge point and the overlapping area of the telescopic arm. And the difference between the stress data obtained from experiments and simulations is about 4%. This not only provides good guidance for the security testing of platform fire fighting vehicles, but also verifies the credibility of the simulation method, which is helpful for the structural design and optimization of platform fire fighting vehicles.

The confined space and fluctuating brightness levels inside and outside highway tunnels result in notable disparities in driving behaviors across various sections. It's difficult to achieve differential management of various sections within tunnels due to the challenge of implementing uniform warning and control across the entire roadway. Based on the Tongji road trajectory sharing platform (TJRD TS), continuous microscopic parameters of vehicles were extracted to quantify driving characteristics using eight indicators. This approach was aimed at analyzing the differences in driving behavior and safety risks of vehicles at different tunnel locations. Based on unsupervised learning algorithms, a segmenting method was proposed for highway tunnel sections that considers driving characteristics. Firstly, principal components analysis (PCA) was employed to determine the main features representing driving behavior and traffic safety. Subsequently, the K-means clustering algorithm was utilized to divide the distribution of main features along the tunnel direction into segments. Finally, the rationality of tunnel section division was validated through significance analysis. The results show that the driving behavior and safety vary significantly at different positions within the tunnel. Based on driving characteristics, the tunnel sections are segmented into six parts using PCA-K-means clustering: approach section, entrance section, transition section, middle section, exit section, and departure section. The entrance and transition sections exhibit high variability in speed changes and unstable traffic flow, while conflict frequencies are high in the transition and exit sections, with vehicle deceleration and acceleration reaching peak values of 14.89% and 15.65%, respectively. The research results reveal the evolution pattern of vehicle driving characteristics within tunnels and facilitates effective segmentation of highway tunnels. The research results contribute to the formulation of proactive safety control strategies for tunnel vehicles and the realization of precise vehicle-road cooperative control.

Aiming at the current problem of rail transit feeder buses being affected by competition from shared motorcycles, which has led to a significant loss of passenger flow, the service quality of feeder buses was studied and evaluated in order to enhance the competitiveness of feeder buses. Firstly, a questionnaire was designed to collect passenger satisfaction data, and the object importance of each service index of the feeder bus in the passenger perspective was obtained through the random forest algorithm. The subject importance degree of each service indicator under the experts' perspective was obtained through the analytic hierarchy process(AHP), and the competitive importance degree of the service indicators under the competition with shared motorcycles was obtained. Next, the evaluator weight determination method based on the stakeholder perspective was used to weight the combination of the three importance degrees to obtain the comprehensive importance degree of the feeder bus service indicators, and the importance-performance analysis(IPA) matrix was constructed to classify the indicator improvement priority. Finally, the technique for order preference by similarity to an ideal solution (TOPSIS) was used to confirm the specific priority of the service indicators to be improved by combining the comprehensive importance degree and satisfaction degree. The results show that waiting time, transfer fare and ride congestion are the three most effective indicators for improving the service quality of rail-connected buses, and the priority weights for improvement are 0.368, 0.235, and 0.164, respectively. Among them, the waiting time shows high importance under all three perspectives, and is the most prioritized key factor for improvement. Two service indicators, transfer fare and travel time, have high importance in the expert and competitive perspectives, respectively, suggesting that perspectives other than passenger perceptions can also reveal the key role of different indicators in improving service quality. A proposed comprehensive assessment method based on the importance of service indicators in multiple perspectives and the quantification of improvement priority, which can more accurately assess the service quality of feeder buses and provide the direction of improvement.

In order to improve the prediction accuracy of pedestrian crossing patterns by conventional vehicles in unsignalized crosswalk road sections, a pedestrian crossing pattern prediction model integrating extreme gradient boosting (XGBoost) and multilayer perceptron (MLP) algorithms was proposed. First, the pedestrian-vehicle interaction data in the unsignalized crosswalk section were collected based on the cameras and LiDAR installed on the roadside, and the behavioral characteristics of pedestrians and vehicles were analyzed, and then the factors affecting the pedestrian crossing patterns were screened. Next, the predictive effects of different combinations when used as model inputs were explored. Finally, vehicle speed, vehicle-to-zebra crossing distance, time to collision(TTC) and pedestrian step speed were used as model inputs, and pedestrian crossing patterns were categorized into direct crossing and waiting crossing and used as model outputs, and the XGBoost-MLP model for pedestrian crossing pattern prediction was established. The prediction accuracy of this model for pedestrian crossing patterns reaches 88.65%, which compares with the single XGBoost model and the MLP model, and its accuracy is improved by 3.85% and 2.61% compared to the single XGBoost model and MLP model, respectively.

Due to the complexity and variability of the marine environment as well as the complexity of the dynamic characteristics of the offshore stabilized corridor bridge in a series-parallel hybrid configuration, the analysis of the dynamic characteristics of the offshore stabilized corridor bridge in the working process has always been a key point and a difficult point in the related research process. To address this problem, firstly, the projection matrix and Jacobi matrix of each component of the bridge were derived based on the vector method and Kane's method, as well as the dynamic equations under the generalized coordinate system, and the overall explicit dynamics model of the bridge was derived by using the Kane's method and the principle of virtual work. Secondly, a joint simulation model of MATLAB and Adams was constructed based on Simulink and the simulated motion of the vessel was simulated by the MSS toolbox to simulate the ship's motion as an excitation for analysis. Finally, theoretical calculations and simulation analysis were carried out under two working conditions, with and without personnel and cargo transfer, to verify the correctness of the established model. Further, the effects of loads of different masses on the driving force of the strut chain were investigated, and the compensating effect of the sea-stabilised corridor bridge was analysed. The research results are of guiding significance for the development of the sea-stabilised corridor bridge and its application on real ships.

In order to ensure the regular and punctual operation of civil aviation transportation, the efficient aviation spare parts supply is the fundamental basis. However, the stochastic replenishment lead time and demand aggregates the uncertainty of spare parts supply. An original equipment manufacturer-orientated aviation industry supply chain location-inventory problem under an uncertain environment was investigated. A two-stage stochastic optimization model, including facility location, inventory control, production decisions, etc., was constructed to maximize the supply chain's profit. A novel robust optimization approach was proposed for a resilient supply chain network design under an uncertain environment. The results show that original equipment manufacturer facilities are more likely to establish double-sourcing and multiple-sourcing strategies with the upstream tier suppliers as the supply lead time and demand uncertainty increase and the on-hand inventory and average ordering quantity of tier suppliers increase accordingly. In addition, high uncertainty in spare parts supply and demand leads to declining profits in the aviation industry supply chain, which can be relieved by robust and resilient supply chain design and efficient inventory control. It is concluded that the optimal strategic and tactical decisions of the aviation industry supply chain in the context of supply and demand uncertainty provide an effective solution for the robust and efficient operations of the global aviation industry supply chain.

The issue of gate assignment at modern airports involves coordinating multiple interests, including passenger satisfaction, efficient allocation of airport resources, and control of carbon emissions. A multi-objective nonlinear integer programming model was developed to solve this complex problem, which considering constraints such as flight type, aircraft model, and gate availability. The optimization objectives of model include minimizing passengers' walking distance, maximizing aircraft-gate matching, and minimizing carbon emissions. An improved adaptive genetic algorithm was proposed to solve the gate assignment problem. In the population initialization phase, a combination of random and greedy-perturbation strategies was employed to generate a more diverse initial population. The probabilities of crossover and mutation were adaptively adjusted during the algorithm's iterations. Both crossover-first and mutation-first evolutionary strategies were applied to enhance solution efficiency and global search ability. To validate the effectiveness of the algorithm, some simulation experiments were conducted using operational data from the domestic airport. The improved adaptive genetic algorithm was compared with traditional genetic algorithms and particle swarm optimization algorithms. Results show that the improved algorithm significantly outperforms the others in terms of gate utilization efficiency, passenger satisfaction, and carbon emission control. Furthermore, the effectiveness of the proposed improvement strategies was confirmed through experimental analysis, demonstrating the stability and performance of the algorithm. The proposed model and algorithm provide robust decision support for gate management, contributing to enhanced passenger satisfaction, efficient resource utilization, and sustainable environmental development.

The disruption recovery is regarded as a crucial role in the operation of freighter airlines. To expand the application scenarios of the freight flight network, elements such as mandatory nodes and external arcs were introduced to enhance the applicability of the network. In general, aircraft and cargo were defined in separate networks and are recovered using a sequential solving method. To explore the correlation between each research object and to complete each recovery action, the entity flow was defined to integrate different types of entities in the same network. To solve the problem of crew recovery, constraints such as crew duty and flight qualifications were added to the model, and a mixed integer linear programming model was constructed based on an improved flight network. This model can achieve integrated recovery of aircraft, cargo, and crew. To accurately evaluate the capacity constraints of the cargo aircraft, a unit load device was used to represent the volume of cargo and to improve the relevant models of capacity constraints. An entity aggregation approach was employed to reduce the number of entities to control the model complexity. The model evaluation was performed using operational data provided by a small freighter airline. The results show that the recovery solution causes a 42% reduction in the delay time. In the subsequent simulation experiments, six different disruption scenarios were established for two freighter airlines with multiple fleets. As the disruption rate increases, medium freighter airlines adopt the strategy of re-routing aircraft and rescheduling crew, while large freighter airlines focus on flight delays. The proposed integrated air cargo schedule recovery model based on an improved flight network can solve all the cases exactly in limited time, and the average error is 0.47%.

To enhance the efficiency of carbon monoxide (CO) emission control during drill-and-blast construction in high-altitude tunnels and to improve the working environment for personnel, a tunnel currently under construction at a high altitude was investigated. Utilizing the computational fluid dynamics simulation software Fluent, three factors were examined under forced ventilation conditions: the distance between the air duct and the tunnel face, the position of the air duct, and the varying elevations. To model the diffusion characteristics of harmful CO gases. The simulation results indicate that when the air duct is positioned too close to the tunnel face, vortices form, causing CO accumulation near the tunnel face, which is detrimental to the effective dispersal of CO from this area. Conversely, when the duct is positioned too far, the airflow loses a significant amount of kinetic energy before reaching the tunnel face, which also hinders the effective removal of harmful CO gases in the vicinity of the tunnel face. Optimal removal efficiency of harmful CO gases near the tunnel face is achieved when the air duct is placed at a distance of 25.2 m from the tunnel face and located at the top of the tunnel. This configuration significantly improves the working environment for personnel within a short period. Compared to plain regions, the distance between the duct and the tunnel face in high-altitude areas should be approximately 3 \sqrt{S} (S is the cross-sectional area of the tunnel) that of the plain regions. The trend of CO movement within the tunnel is generally consistent across different altitudes. As the altitude increases, the concentration of CO also increases, and the speed of CO movement within the tunnel decreases, necessitating longer ventilation times in high-altitude areas.

To investigate the contribution and temporal variability of lake-groundwater interactions in the water balance of flood-controlled lakes, Honghu Lake in the middle reaches of the Yangtze River was selected as a case study. Based on the analysis of water level dynamics of Honghu Lake and surrounding groundwater, the recharge-discharge relationship between Honghu Lake and groundwater were identified and calculated by a water balance equation. The contribution of groundwater-lake interactions to the water balance of Honghu Lake and its temporal variability were examined. The results indicate that there is a significant water level difference between Honghu Lake and the adjacent phreatic groundwater, with dynamic changes in both showing a significant positive correlation, correlation coefficient r=0.729. The aquifer in the Honghu Lake area is permeable, which indicates that there are interaction conditions between Honghu Lake and groundwater. On an inter-annual scale from 2017 to 2022, Honghu Lake generally infiltrate into the groundwater, with an average annual discharge volume of 6.43×10⁸ m³, accounting for 14.11% of the lake's outflow. On a multi-year average monthly scale from 2017 to 2022, Honghu Lake infiltrates into the groundwater during the dry season (September to February of the following year), with an average monthly discharge volume of 0.8×10⁸ m³. During the rainy season (April to August), groundwater-lake interactions are dynamic, with an average monthly exchange volume of -1.17×10⁸~0.88×10⁸ m³. Honghu Lake presents an opposite seasonal variation characteristic of the lake water-groundwater interaction compared with the reported Yangtze-connected lakes such as Poyang Lake and Dongting Lake. This is mainly because the water level of Honghu Lake, affected by water conservancy regulation, has altered the natural interaction process between the lake and groundwater. These findings provide new insights into groundwater-lake interactions in flood-controlled lake systems and hold significance for the management of water resources and ecological protection in the Honghu Lake region.

Lithium slag holds significant potential for recycling and reuse. The barriers in the recycling process were addressed, such as surface protectants and surface by-products (diffusion pump oil and lithium hydroxide), that impeded efficiency, and the risk of uncontrolled reactions leading to explosions. A method of using water jet impact to desorb surface protectants and by-products from lithium slag and prevent reactive explosions was proposed. Based on the binding relationship between the lithium slag, surface protectants, and lithium hydroxide by-products, a bridging model for oil-lithium-hydroxide lithium particles was proposed. Subsequently, a water jet computational fluid dynamics-discrete element method (CFD-DEM) triple-component coupled depolymerization action model was proposed to explore the depolymerization characteristics of the oil-lithium-hydroxide lithium bridging model under different water jet pressures. The results show that the destruction time of particle adhesive bonds in the oil-lithium-hydroxide lithium model is inversely proportional to the jet pressure. At a jet pressure of 0.1 MPa, a particle adhesive bond destruction rate of over 95% can be achieved within 0.05 s. When the jet pressure exceeds 0.5 MPa, the time to reach a 95% bond destruction rate is just 0.015 s. This method effectively removes the surface protectant of the lithium slag and promptly eliminates lithium hydroxide and the foam it forms while ensuring safety, efficiency, and continuous digestion operations. These findings provide significant guidance for the application of water jet technology in the recovery of reactive metals and can be specifically applied to the high-efficiency, controlled, and safe recycling field of lithium slag.