Engineered cementitious composites (ECC) have good crack width control ability and self-healing potential, which can effectively improve the performance and durability of concrete structures and has been used in various environmental conditions. The healing ability of ECC varies under different environmental conditions, and currently there is relatively little research on the healing behavior of ECC in different environments. In order to study the effects of different environmental conditions on the self-healing behavior of ECC, three different environments including 0.5 mol/L NaCl solution, saturated Ca(OH)₂ solution, and natural environment were selected. Pre-cracked specimens were placed in each of the three environments, and the healing behavior and mechanism in different environments were explored through crack closure tests, strength recovery tests, electron microscopy scanning, and energy spectrum analysis. The experimental results show that the cracks in ECC under different healing environments have varying degrees of closure. As the healing cycle gradually increases, the degree of crack healing also gradually improves. NaCl solution and saturated Ca(OH)₂ solution have a positive effect on the crack healing. The ranking of the healing ability of ECC under different environments is obtained as follows: saturated Ca(OH)₂ solution > NaCl solution > natural environment. Healing materials in natural environment mainly include calcium-silicate-hydrate (C-S-H) gel and Ca(OH)₂. The healing material at the crack site in NaCl solution is mainly filled in the form of ettringite and Ca(OH)₂. In a saturated Ca(OH)₂ solution environment, a large amount of healing material is generated at the cracks, mainly in the form of CaCO₃ filling the crack.

Based on the actual welding process of rectifier sample structure, the numerical simulation of high temperature vacuum nickel-based alloy brazing process was carried out, and the flow model of melting-wetting filling weld of nickel-based alloy filler metal in high temperature brazing vacuum furnace was established. The numerical calculation was based on the volume of fluid(VOF)method. Considering the factors such as surface tension, gravity, and latent heat of phase change, the laminar flow model was used to solve the flow behavior of the solder with time. The distribution of solid and liquid solder and the distribution of temperature field were calculated. The phenomenon of braze material loss and weld bead formation on the surface of the base material, along with a good filling effect of the braze material inside the weld seam, verifies the rationality of the arrangement of solder and temperature control in this brazing process. An empirical formula for the volume ratio of braze material filling the weld seam with respect to time and temperature has been provided, offering guidance for actual brazing processes.

As the oil and gas industry continues to expand into deeper layers and the development of deep geothermal resources progresses, the hardness of reservoir rocks increases, making rock breaking more difficult and raising development costs. To address the problem of difficult rock breaking in deep granite, the mechanism of electromagnetic radiation-assisted rock breaking was investigated. This method utilizes the interaction between electromagnetic waves and reservoir rocks to induce thermal stress damage or fracturing of the rock, thereby reducing rock strength and improving breaking efficiency. Firstly, based on the mineral composition of deep granite, a heterogeneous core model with random distribution of minerals was established. Secondly, a numerical model of electrothermal-solid-damage coupling of granite damaged by electromagnetic radiation was established. Finally, the electromagnetic field, temperature field, stress and damage distribution of granite under electromagnetic radiation were calculated by sequential coupling method. Due to the selective heating property of electromagnetic waves, the electromagnetic power loss density of biotite is 2~3 orders of magnitude higher than that of quartz and feldspar, resulting in different electromagnetic heating degrees and forming local hot spots near biotite. Based on the difference of temperature and thermal expansion coefficient of different minerals, a non-uniform stress distribution is formed. Quartz and biotite are strained, while feldspar is pressured. After 3 kW electromagnetic radiation for 5 min, the damage volume of granite is 42%, and the tensile damage of quartz is the main damage. The damage of granite under electromagnetic radiation is significant, the strength of rock is reduced, and the rock breaking of deep granite is promoted.

Vertical joint steel anchor ring grouting connection (referred to as vertical seam tight splicing connection) shear wall system uses steel anchor ring connection for vertical joints, followed by secondary grouting connection. Based on actual projects of the enterprise, the feasibility of vertical joint tight fitting connection has been verified through experimental research, seismic performance analysis, and design and construction practice.

With the development of DC (direct current ) distribution networks and the large-scale integration of distributed energy storage and photovoltaics into the distribution network, the structure of the distribution network has undergone revolutionary changes. After a short circuit fault occurs in the DC distribution network, the short circuit voltage drops sharply, the short circuit current rises rapidly, and the stability of the power system operation is disrupted. To address this issue, a model for inter pole and single pole short circuit faults in DC systems was proposed. Firstly, by sampling voltage data at both ends of the DC line, the voltage equation was written, and the transition resistance was eliminated. Then, a fitness function was constructed, and the adaptive optimization red fox algorithm with faster convergence speed and higher positioning accuracy was used to calculate the distance from the fault point to the protection installation site for fault location in the DC distribution network. Based on the red fox algorithm, combined with the isolation forest algorithm to remove abnormal data, the algorithm performance and accuracy were improved by improving adjustable feedback factors and introducing genetic crossover operators. When the sampling frequency is low, the accuracy of fault localization is improved through adaptive interpolation. Simulation verification was conducted in Simulink, and the results show that the method has strong resistance to transition resistance, small positioning error, is not affected by system parameters, and can effectively reduce the impact of low sampling frequency on fault localization, and has good robustness.

To address the cumbersome calibration process of fisheye cameras and its inapplicability to everyday scene images, a novel convolutional neural network(CNN)-based method was proposed that simultaneously calibrates the intrinsic parameters of fisheye lenses and corrects image distortion. The accuracy of fisheye camera calibration and image distortion correction was improved by predicting the displacement of pixel points under different distortion parameters. A coordinate attention module was introduced in the encoding part to enhance the model's accuracy and generalization ability to increase attention to image position information. Additionally, a cross-scale fusion module was designed in the skip connections to enhance image detail features. To address the issues of dataset scarcity and incomplete distortion parameter distribution, a new large-scale dataset labeled with corresponding distortion parameters and images after distortion correction was created. Experimental results show that compared to other fisheye camera calibration methods, this method achieves a reprojection error of 0.312 pixel, indicating the highest calibration accuracy. Additionally, compared to other image distortion correction methods, a peak signal to noise ratio(PSNR) of 38.055 dB and an structural similarity(SSIM) of 0.874 are achieved, indicating the best quality of image distortion correction.

The double semi-trailer truck train has strong transportation capacity and relatively low transportation costs. However, compared to semi-trailers, double semi-trailer truck train has more vehicle units, resulting in higher driving difficulty and lower lateral stability at high speeds. To address this issue, a control strategy combining model predictive control (MPC) with differential braking was proposed. Based on the principles of MPC, an MPC lateral stability controller for double semi-trailer truck trains has been designed. MPC regulates the yaw moments of three vehicle units, with differential braking technology dynamically allocating braking forces to individual wheels. The double semi-trailer truck train model has been built in Trucksim, and a simplified vehicle model has been established in MATLAB/Simulink. Through joint simulation of Trucksim and MATLAB/Simulink, the effectiveness of the designed system was verified under different vehicle speeds, loads, and friction coefficients. The research results indicate that the designed controller effectively reduces the centroid yaw angle, lateral acceleration, and yaw rate of each vehicle unit, thereby enhancing the stability of double semi-trailer truck train during high-speed lane changes.

As the service life of China's oil and gas pipelines increase, the pipelines are inevitably subjected to defects such as corrosion and denting due to external factors. It becomes imperative that the impact of these defects, including denting and corrosion, on the ultimate bearing capacity of the pipelines be analyzed. A simulation was conducted on the safety of an X80 pipeline with dents and corrosion defects. By changing factors such as dent length, width, depth, and material type, the influence of a single dent area under the action of spherical and ellipsoidal pressure heads on the ultimate bearing capacity of the pipeline was analyzed. At the same time, the influence of various factors such as the size and spacing of dents and dents on pipeline safety was studied when composite defects such as dents and corrosion coexist. The results show that the length of dents, corrosion length, and corrosion depth are important factors affecting the ultimate bearing capacity of composite defects, and the damage to pipelines is greater when dents act in the vicinity of the corrosion center point.

To address the issue of bridge collisions induced by earthquakes, seismic vulnerability curves for the overall system and individual components of conventional and irregular box girder highway bridges, with and without collisions, were developed and compared based on nonlinear time history analysis using the OpenSees finite element software. Four damage states, ranging from minor to severe, were established. The fragility function was employed to elucidate the interaction between structural irregularities and collisions between the bridge deck and the abutment on the seismic vulnerability of multi-span box girder highway bridges. A conversion coefficient, r_p, was introduced to quantify the impact of collisions on the vulnerabilities of bridge components and the overall system. Traditional analysis methods, including static and simplified analyses, alongside technical seismic models, were applied to adjust the vulnerability values associated with collisions and irregularities. The findings reveal that collisions exert adverse effects on all structural components. As the damage level increase, the variability in RP values for the ductility of bridge columns and anti-falling beams also increase. Specifically, for earthquake number 2, the r_p values under damage conditions are 0.95 for mild(DC₁) and 1.02 for moderate(DC₂). Under pulse type seismic motion, collisions significantly increase the degree of damage to engineering demand parameters (EDP). For earthquake number 3, the average r_p value for foundation translation was 0.71 with collisions and 0.57 without, highlighting the significant destructive influence of collisions on foundation translation. By comparing the median values across all categories, it was observed that the median values for earthquake numbers 3 and 1A were lower than those for earthquake numbers 2 and 1B, indicating that collisions caused more severe damage under lower ground motion intensities. This study provides a valuable reference for seismic bridge design, offering insights to improve design specifications, enhance the seismic performance of bridge structures, and deliver significant engineering and practical applications.

Logging data constitutes the basis for oil and gas field development and evaluation. However, in actual mining, factors like poor wellbore stability and equipment failure give rise to the distortion or loss of logging data. A prediction model based on variational mode decomposition (VMD) was proposed to address the issues of unstable and inaccurate results in existing prediction models. The model combines convolutional neural networks (CNN), bidirectional long short term memory (Bi-LSTM), and attention mechanism to predict missing sections in well logging curves. With logging sequence data as input, the VMD algorithm was employed to decompose the sequence into a series of amplitude-modulated and frequency-modulated signal subsequences. The features were extracted by the CNN network and trained by the Bi-LSTM network. During training, the Attention mechanism was utilized to learn the importance weight of each time step dynamically. Finally, the predicted value of the logging curve was outputted. The method was applied to predict logging curves in the Biyang Block of Henan Province and compared with other common machine learning prediction models. The results show that the application effect of the CNN-BiLSTM-Att model improved based on VMD is remarkable, with an error of only the order of 10^-3 and a prediction accuracy of 92.02%. The research results provide new ideas for accurate prediction of logging curves.