The construction of the pile-beam-arch-method(PBA method) exhibits a cluster-tunnel effect, which readily induces surface subsidence. To achieve safe construction and minimize surface settlement, the MatDEM discrete element software was employed to simulate the construction process of the PBA method. The potential deformation mechanism and metastable microstructure of soil were considered in the training of formation micromechanics parameters, and the variation rule of surrounding rock pressure under multi-guide tunnel construction was summarized. The research findings indicate that when adopting a construction sequence of “top-to-bottom and sides-to-center,” surface settlement is relatively small. When using the “center-to-sides” approach, the initially excavated central pilot tunnel leads to the formation of slip planes at 1.5 times the tunnel width. Conversely, with the “sides-to-center” method, the initially excavated side tunnels provide vertical support to the inner soil, reducing the surface settlement caused by the subsequent excavation of the central tunnel. During the construction of the upper pilot tunnels, the surrounding rock pressure at the vault and arch waist exhibits an increasing trend. The construction of the lower pilot tunnels results in stress concentration at the vault and inner arch waist of the upper tunnels. Approximately 72.65% of surface settlement occurs during the construction of the lower pilot tunnels, and the adoption of staggered construction can significantly mitigate soil disturbance.

In order to investigate the segregation characteristics of asphalt concrete with large size core walls, indoor and field tests were conducted. Firstly, the density ratio data of the indoor prepared asphalt concrete specimens were analyzed by extreme variance analysis. Secondly, the density data of the upper and lower parts of the asphalt concrete core samples with the maximum aggregate size of 37.5 mm drilled under different working conditions in the field were statistically analyzed based on the one-dimensional variance theory. Finally, the basic mechanical properties of the upper and lower parts of the asphalt concrete cores of the large-grain-size aggregate core wall were comparatively analyzed under different working conditions. The results show that the relatively large influence on the segregation of asphalt concrete in the heart wall is the largest aggregate size, followed by the test temperature, the smallest is the amount of asphalt, and the tendency of segregation of asphalt concrete in the heart wall increases with the increase of the aggregate size, the increase of asphalt dosage and the increase of the test temperature. The tendency of segregation of asphalt concrete with the largest aggregate size of 37.5 mm molded under different working conditions from large to small are: initial milling temperature of 145 ℃ with paving thickness of 30 cm, initial milling temperature of 130 ℃ with paving thickness of 30 cm, initial milling temperature of 145 ℃ with paving thickness of 40 cm and initial milling temperature of 130 ℃ with paving thickness of 40cm, respectively. The tendency of segregation of its own will be increased with the increase of the thickness, initial milling temperature and asphalt consumption, and with the increase of test temperature and asphalt consumption. The tendency of segregation will decrease with the increase of paving thickness and the decrease of initial milling temperature. The differences in Marshall stability, Marshall flow value and split tensile strength between the upper and lower parts of the core samples of asphalt concrete with the largest aggregate size of 37.5 mm molded under the above four working conditions are all within 6%, with good uniformity.

In the practice of energy renovation of existing buildings, the uncertainty of renovation parameters has a significant impact on the renovation results. To support energy renovation decision-making, a Monte Carlo method combined with Latin hypercube sampling was proposed to evaluate different renovation schemes, and a tree-based Gaussian method was used to screen key variables that affect the renovation process. The results show that uncertainty analysis can quantitatively evaluate renovation schemes at the preliminary design stage. The energy-saving rates of two typical renovation scenarios fluctuate between 32.7%~55.2% and 55.5%~108.4%, respectively, with higher uncertainty in schemes with better energy-saving effects. The cumulative probability distribution was used to assess the probability of renovation success, with the probabilities of meeting renovation targets being 58% and 96.4%, respectively. The integration of renewable energy technologies ensures the renovation results. Sensitivity analysis results show that infiltration rate and equipment power density are the most important factors in office building energy consumption, accounting for 80% of the output variance, which provides a theoretical basis and methodological reference for the selection of more building energy renovation schemes in the future.

In order to reveal the unsteady flow characteristics during the pre-compression process of the radial wave rotor combustor, the pre-compression mechanism induced by complex wave systems under typical operating conditions was simulated and analyzed using three-dimensional unsteady simulations. The impact of pressure differential across intake and exhaust ports, as well as rotor speed, on the propagation behavior of compression waves within the channels was focused on. The results indicate that as compression waves propagate within the channels, they are influenced by the curvature of the curved channels, leading to wave reflection, refraction, and attenuation. This results in energy loss and waveform distortion, which affect the propagation path and speed of the compression waves. Although a higher pressure difference enhances the intensity of the compression waves, it exacerbates overfilling of the fuel and flow instability, increases thermodynamic losses, and significantly reduces the isentropic compression efficiency. The rotational speed affects the propagation characteristics of compression waves within the channels by adjusting the operational timing of the wave rotor. At 1 200 r/min, the opening time of the intake port is extended, causing the compression waves to reflect and form expansion waves that propagate in the reverse direction. This results in a pressure ratio within the channel of only 103% and a substantial decrease in isentropic compression efficiency.

When a tunnel crosses a water-rich fault fracture zone, it is very easy to produce a water surge accident under a series of construction disturbances. In order to study the effects of fault zone width, dip angle and water pressure on tunnel water inflow, Yingshan tunnel was used as the engineering background, field tests were carried out, and an orthogonal test scheme was designed to carry out numerical simulation of coupled flow-solidity in the fault zone under multifactorial conditions, so as to analyze the sensitivity of the fault zone width, dip angle and water pressure on the water inflow of the tunnel. The results show that the tunnel water inflow increases with the increase of fault zone thickness, dip angle and water pressure, and the factors affecting the tunnel water inflow are water pressure, dip angle and width of the fault zone. The numerical simulation results are in good agreement with the field monitoring results. The results can provide theoretical references for the prediction of water influx in water-rich tunnels and the prevention and control technology.

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.

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.

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.

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.

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.