The pathogenesis of diabetic nephropathy is complex and can ultimately progress to end-stage renal disease, imposing a heavy burden on patients. Current treatment methods show limited efficacy. The protein kinase RNA-like endoplasmic reticulum kinase (PERK)-eukaryotic initiation factor-2$\alpha$(elF2$\alpha$) -activating transcription factor 4 (ATF4)-C/EBP homologous protein (CHOP) signaling pathway serves as a critical pathway in endoplasmic reticulum stress, with downstream regulation of pathological processes such as apoptosis and autophagy closely related to the progression of diabetic nephropathy. Traditional Chinese medicine regulates the PERK-eIF2$\alpha$-ATF4-CHOP pathway through methods that tonify$\mathrm{{Qi}}$and nourish$\mathrm{{Yi}}$, strengthen the spleen and benefit the kidneys, promote diuresis and reduce edema, clear heat and detoxify, as well as invigorate blood and eliminate stasis. These interventions protect the glomerular filtration barrier, reduce capillary basement membrane thickening, enhance protein reabsorption in urine, and delay renal interstitial fibrosis. The mechanistic role of the PERK-eIF2$\alpha$-ATF4-CHOP signaling pathway in diabetic nephropathy was elucidated, the theoretical basis for traditional Chinese medicine interventions in this pathway was summarized, and recent advances were reviewed in the mechanisms of action of effective components of traditional Chinese medicine targeting this pathway, aiming to provide new ideas and methods for the prevention and treatment of diabetic nephropathy through traditional Chinese medicine.

With the increasing number and aging of in-service oil and gas pipelines in China, issues such as corrosion, aging, and geometric deformation have become increasingly apparent. Due to the limitations of manual inspections, such as complex spatial environments and narrow pipe diameters, the use of pipeline robots for inspection and maintenance has emerged as a dominant trend in both domestic and international research. To address the risks of pipeline failure after prolonged service, understanding the latest advancements in pipeline robotics is crucial for setting forward-looking development goals and minimizing redundant research efforts. A comprehensive review of recent developments in in-service pipeline robotics was provided, these robots were divides into two main types based on their movement mechanisms and working environments: internal (passive and active) and external pipeline robots. By examining specific examples of each type, their overall performance were compared and highlighted key considerations for field applicability. Furthermore, the future directions were explored for pipeline robotics, emphasizing the importance of multi-parameter integration in ensuring the safe operation of oil and gas pipelines in the future.

As a widely distributed and abundant clean energy source, geothermal energy may lead to inefficient resource utilization and a series of ecological environmental issues when improperly developed. The typical geothermal distribution area in Linqing, Liaocheng City, Shandong Province was selects as the research object. Based on detailed geothermal geological survey data, the construction of a "multi-well coordination system" geothermal heating model was explored and the feasibility analysis with operational benefit was conducted. The results demonstrate that the proposed coordinated multi-well geothermal heating mode can reduce geothermal resource extraction by 41.46% while maintaining equivalent heating coverage and quality standards, significantly enhancing maximum utilization efficiency of geothermal resources. The system simultaneously achieves geothermal tailwater reinjection with favorable economic returns. The static investment payback period approximates 3 years, and the total revenue over 20 heating seasons reaches 25.742 million yuan. Through zoning division implementation in key operational areas, this model effectively addresses challenges including dense well distribution, uneven development patterns, and difficulties in reinjection well construction. The findings provide technical references and application demonstrations for geothermal heating development in other regions.

In order to study the formation mechanism, paleoenvironment, paleoclimate, tectonic background, and source of black shale in the Shengping Formation of the Middle Ordovician in northern Guangxi, sixteen samples of black shale and black siliceous shale were collected from the Shengping Formation at Xishuiyuan section in Quanzhou County, Guilin City, Guangxi Zhuang Autonomous Region, and element geochemistry testing and analysis were conducted on them. The results show that the content of the main element${\mathrm{{SiO}}}_{2}$in the black shale of the Shengping Formation at Xishuiyuan section is the highest (${62.37}\%\sim {91.65}\%$, average${78.04}\%$), followed by${\mathrm{{Al}}}_{2}{\mathrm{O}}_{3}({2.88}\%\sim$16.92%, average 9.15%). Compared with the North American shale (NASC), the content of trace elements in the study area shows a loss for all elements. The value of the sample${\left(\mathrm{{La}}/\mathrm{{Yb}}\right)}_{\mathrm{N}}$is${7.185}\sim {15.858}$, with an average of 10.678. The light rare earth elements (LREE)/ heavy rare earth elements (HREE) values are${8.165}\sim {15.440}$, with an average of 11.029. It indicates that the differentiation phenomenon of light and heavy rare earth elements is more obvious, and LREE are relatively enriched compared to HREE. The δEu value exhibits negative anomalies$\left({{0.589}\sim {0.950}}\right)$, with an average value of 0.758 ; The$\delta \mathrm{{Ce}}$value exhibits positive anomalies$\left({{1.165}\sim {1.412}}\right.$, with an average of 1.259). The geochemical characteristics show that the structural background of the black shale source area in the Shengping Formation of the Xishuiyuan profile is passive continental margin, and the source rock type is sedimentary rock. The source area has undergone moderate to strong chemical weathering, which is greatly affected by chemical weathering, with a predominantly warm and humid climate. The sedimentary environment is mainly a deoxidizing environment with oxygen deficiency.

To explore the impact of the spatial distribution of material sources within a watershed on the susceptibility to debris flows. The nearest neighbor index was adopted, based on the principles of mathematical statistics, to quantify the spatial clustering of material sources. Using 2243 small watersheds as evaluation units, the longitudinal gradient, area-elevation integral, topographic wetness index, peak ground acceleration of earthquakes, and rock hardness were taken as disaster-prone indicators, and the aggregation index of material sources, connectivity index, and material reserves were taken as the core material source indicators. The LightGBM model was relied on to investigate the susceptibility to debris flows in the Shigu-Gangtuo section of the upper reaches of the Jinsha River. The research process calculated the index system of material source factors and the index system without material source factors. Both results indicate that the high and very high susceptibility areas are mainly concentrated in the Benzilan-Batang section. The receiver operating characteristic curve (ROC) curve analysis shows that after incorporating the material source characteristic indicators, the area under the curve (AUC) value increases by 6% compared to the AUC value without material source characteristics, indicating that the model performs well and has high predictive accuracy after the inclusion of material source indicators. It also proves that the material source characteristic indicators are highly correlated with the probability of debris flow occurrence.

In order to explore the efficient heat transfer characteristics of medium-deep coaxial buried pipe heat exchangers, a heat transfer model was constructed between the medium-deep coaxial buried pipe heat exchanger and surrounding rock and soil based on the fluid flow heat transfer equation. COMSOL software was used for numerical analysis and calculation of heat transfer, and the nominal heat transfer of the model was studied under different burial depths, inner pipe thermal conductivity, circulating water flow rate, and cementing material thermal conductivity conditions. The research results indicate that the thermal conductivity of the inner pipe, the flow rate of circulating water, and the thermal conductivity of the cementing material have a significant impact on the nominal heat extraction. The thermal conductivity of the inner tube decreases from${0.5}\mathrm{\;W}/\left({\mathrm{m}\cdot \mathrm{K}}\right)$to${0.002}\mathrm{\;W}/\left({\mathrm{m}\cdot \mathrm{K}}\right)$, with a nominal increase in nominal heat extraction of${289.4}\%$. The circulating water flow rate from${20}{\mathrm{\;m}}^{2}/\mathrm{h}$rises to${45}{\mathrm{\;m}}^{2}/\mathrm{h}$, with a nominal increase in nominal heat extraction of${124}\%$. The thermal conductivity of cementing materials increases from${0.8}\mathrm{\;W}/\left({\mathrm{m}\cdot \mathrm{K}}\right)$to${1.8}\mathrm{\;W}/\left({\mathrm{m}\cdot \mathrm{K}}\right)$, with a nominal increase in heat extraction of$2\%$. Finally, relying on a Pilot Demonstration Project of Medium and Deep Geothermal Energy for Building Heating at CCTEG Xi’an Research Institute (Group) Co., Ltd., differential analysis was conducted on experimental and simulation data under continuous operation for${168}\mathrm{\;h}$of the project. The research results have certain guiding significance for the optimization design of medium-deep coaxial buried pipe heat exchangers and the efficient development and utilization of medium-deep geothermal wells.

Based on the Wnt/β-catenin pathway, to investigate the anti-tumor effect of Gegen Qinlian Decoction (GQD) on colorectal cancer and its effect on nuclear translocation of protein regulator of cytokinesis 1 (PRC1). BALB/c nude mice were subcutaneously inoculated with the CT26 colorectal cancer cell line and divided into GQD low (L-GQD), medium (M-GQD), and high (H-GQD) dose groups, with the model group serving as the control. The mice were administered the drug daily for 25 days, and the growth of the tumors was recorded. Following the conclusion of the previous administration, the tumor was surgically excised and subjected to subsequent observation. The proliferation and apoptosis of the tumor were assessed using hematoxylin-eosin staining(HE), immuohistochemistry (IHC), and terminal deoxynucleotidyl transferase-mediated dUTP nick end labeling (TUNEL) staining techniques, while the Wnt/B-catenin pathway was examined through qRT-PCR and western blot (WB) analysis. Furthermore, alterations in the expression of catenin signals and downstream factors were investigated. In addition, WB was used to detect the effects of GQD on the phosphorylation level of PRC1 and its subcellular localization. Compared with the model group, GQD inhibited the growth and increased the apoptosis level of colorectal tumors in vivo in a dose-dependent manner. IHC results show that GQD down-regulated the expressions of proliferation-related proteins cyclind1 , marker of proliferation Ki-67 (Ki67), and platelet endothelial cell adhesion molecule-1 (CD31)$\left({P <{0.05}}\right)$, and promoted the expressions of approbation-related proteins Caspase 3 and Caspase 9$\left({P <{0.05}}\right)$. GQD is further found to inhibit the activation of Wnt/β-catenin signaling, which may be related to the reduction of PRC1 phosphorylation level and the alteration of its nuclear retention ratio. This inhibition of Wnt/β-catenin signaling by GQD is closely associated with the suppression of colorectal tumor proliferation and the promotion of apoptosis. Moreover, GQD may involve in mediating nuclear translocation of PRC1.

In order to accurately calculate the hydrodynamic parameters of the slope rill at any point during the erosion process, and to avoid errors caused by using the average flow rate to calculate the hydrodynamic parameters in the traditional method. Based on the variability and complexity of the development process of slope rills, as well as the characteristics of water sand two-phase flow, the Euler-Euler two-phase flow model was used to calculate and analyze the morphological evolution characteristics and erosion mechanisms of slope rills at different stages of expansion erosion. The results show that the Euler-Euler two-phase flow model can accurately describe the morphology evolution process of slope rill in expanded erosion. Based on the morphology evolution characteristics of slope rill at different stages of expanded erosion, the expanded erosion of slope rill is divided into the period when the rill sidewall is slightly spreading and eroding (the early stage), the period when the expanded erosion become severe with a significant increase in the number and area of amalgamated arcs (the middle stage), and the period when the expanded erosion basically ceased and the rill morphology stabilized (the late stage). The influential factors of slope gradient, initial flow rate, and preset rill width on the Darcy-Weisbach resistance coefficient, Reynolds number, and real-time flow rate are significant. Optimal characterization parameters for different stages of slope rill development, such as erosion arc length and hydraulic radius, are proposed, aiding in determining the specific period of slope rill development and predicting the development trend of rill morphology through changes in these parameters. The research results provide a theoretical basis for soil erosion control measures and are of great significance for soil and water conservation.

In practical production processes, equipment performance gradually degrades over time, leading to extended processing durations. To address this issue, an improved nondominated sorting genetic algorithm II (NSGA-II) was proposed for a re-entrant hybrid flow-shop scheduling problem that considers deterioration effects. Firstly, a mathematical model was formulated with the optimization objectives of minimizing makespan and reducing processing energy consumption. Secondly, a job-sequence-based encoding method was employed, and an energy-efficient scheduling decoding method that accounts for deterioration effects was designed. Additionally, to enhance population diversity, various mutation operators were introduced, and algorithm parameters were adaptively adjusted to prevent convergence to local optima. A variable neighborhood search strategy was also integrated to reinforce the local search capability of the algorithm. Finally, comparative experiments with other algorithms on ten different scale test instances demonstrated that the proposed algorithm delivers superior solution quality, along with better diversity and convergence properties.

In response to the issues of parameter homogenization and insufficient rationality in the support design of the mining roadway in the Lingtai mining area, it is highly significant to conduct classification research on the mining roadway and propose differentiated support strategies. Firstly, based on a systematic analysis of the geological conditions of the surrounding rock and the matching relationship with the support system in the mining roadway of the Lingtai mining area, six classification indicators were determined. Secondly, a mining roadway classification method based on mixed data clustering was proposed, extracting the informational characteristics of numerical and categorical indicators and introducing a penalty competition mechanism to dynamically optimize the number of clusters during the classification process. Subsequently, the proposed method was applied to classify 37 segments of the Lingtai mining area's mining roadways into four categories, validating the feasibility of the method. Finally, a field test was conducted in the D segment of the 2502 transport roadway in Shaozhai Coal Mine. The results indicate that the maximum convergence of the roof and floor of the test roadway segment is 109 mm, and the maximum convergence of the two sides is 113 mm, with a small range of surrounding rock damage. The dynamic classification and differentiated support method for mining roadways can achieve stable control of the surrounding rock in the roadways.

As a critical unconventional oil and gas resource within the global energy framework, heavy oil has garnered significant attention for its development efficiency. Although steam flooding technology has improved the efficiency of heavy oil production, the phenomenon of steam breakthrough negatively impacts thermal efficiency and reservoir development. Traditional prediction methods have shown inadequate precision and delayed response when dealing with long-term oilfield time series data. Data from 13 steam flooding well groups in the Shengli oilfield heavy oil block were utilized. An innovative approach was adopted, using the instantaneous temperature ratio between production and injection wells as an indicator of steam breakthrough time. Pearson correlation coefficient analysis was employed to select key factors related to steam breakthrough time. Based on these factors, a deep learning model built on the Transformer architecture was developed, achieving accurate predictions of the instantaneous temperature ratio. The predictions closely aligned with oilfield observation data, demonstrating higher prediction accuracy and stability compared to traditional long short-term memory (LSTM) models. The research results not only provide a new perspective for the precise prediction of steam breakthrough time in heavy oil reservoirs but also further validate the extensive potential of deep learning technology in oilfield development applications, supporting the construction of intelligent oilfield management and decision support systems.

To clarify the mechanism of water injection damage in low-permeability reservoirs of the Longdong Oilfield, the Chang 3 reservoir was selected as the research subject. A comprehensive analysis method was developed, starting from the intrinsic factors of the reservoir to the external engineering factors, to analyze the mechanism of reservoir water injection damage. X-ray diffraction (XRD), cast thin sections, and scanning electron microscopy (SEM) were used to analyze the reservoir’s rock physical properties and pore structure. Experimental methods combining visual microfluidics with nuclear magnetic resonance(NMR) were employed to analyze the damage patterns of externally injected water on low-permeability reservoirs. The results show that the intrinsic factors causing blockage in the Chang 3 reservoir are related to its low porosity and low permeability, with pore throat diameters all less than${20\mu }\mathrm{m}$, leading to poor reservoir properties and high liquid flow resistance in the reservoir. The composition of clay minerals mainly includes kaolinite and illite, which are velocity-sensitive minerals prone to fine particle migration and reservoir blockage. The external engineering factors causing blockage are the incompatibility of injected water with formation water, resulting in the formation of scale particle. These scale particles and clay particles can undergo a blockage-breakthrough process at the pore throat passages, causing fluctuating increases in injection pressure. Moreover, the injected water can carry scale and clay particles into the deep parts of the reservoir, where they accumulate and exacerbate blockage, significantly reducing the sweep efficiency of water flooding. The research results have clarified the pattern of water injection damage in the Chang 3 reservoir, providing theoretical guidance for water flooding development in oil fields.

The blowout preventer (BOP) is a key well control equipment, in which the shear ram BOP is the last line of defense against blowout accidents. Therefore, its shear performance under extreme working conditions is crucial for the safety of drilling operations. A super shear ram BOP was taken as the research object, and the numerical analysis was carried out by using the dynamics module. The simulation results were compared with experimental and theoretical values to verify the accuracy and applicability of the model. In order to investigate the influence of extreme working conditions on the shear capacity of the ram BOP, the shearing performance of the drill pipe joints was evaluated under high pressure working conditions, eccentric working conditions and moving conditions. The response surface method was applied to develop a shear force prediction model under extreme working conditions. Based on the prediction model and the actual shearing capacity provided by the ram BOP, the shearing failure scenarios under extreme working conditions were determined. The results show that the relative errors between the theoretical values and the simulation results are less than 3%. In the shearing process, the larger the axial tension and compression load, the more unfavorable the shearing. While the certain deviation distance is conducive to the shearing. The research results can provide technical guidance for preventing the shearing failure of ram BOP.

In order to reduce the vibration of fracturing branch pipe during fracturing operation, the fluid-structure coupling analysis method was used to carry out the modal analysis and harmonious response analysis of fracturing branch pipe, considering the impact of fracturing pump vibration and high-pressure fracturing fluid on fracturing branch pipe. The influence of angle of bend and number of fracturing branch pipe supports on fracturing branch pipe vibration was studied. The results show that under the current layout, the main vibration positions of the first six modal modes of the manifold appear at double elbows 2, 3, and 4, indicating that the main vibration deformation of the fracturing branch pipe occurs at its lower end, that is, at the double elbows far away from the fracturing truck. Considering the weak points at double elbows 2, 3, and 4, the smaller displacement response amplitudes of each double elbow at each connection angle are obtained based on the maximum displacement response amplitude. Indicating that each connection angle is the best choice for the actual fracturing operation. When four elastic supports are used, the maximum amplitude is much smaller than that of two or three elastic supports, indicating that adding elastic supports at the lower end of the fracturing branch pipe can weaken the vibration amplitude, and the optimal scheme can be obtained under the specific working range. The research results can provide theoretical guidance for the vibration characteristics and vibration reduction of fracturing branch pipe.

Fault diagnosis of industrial motor bearings is crucial for equipment performance and lifespan. Traditional diagnostic methods aggregate data from multiple factories, leading to issues with data privacy and high annotation costs. To address these problems, a fault diagnosis strategy based on adaptive local collaboration (ALC) federated learning was proposed. In this approach, bearing data under different working conditions was stored across multiple clients, with a central server collaborating with each client to build a federated learning diagnostic model. An improved ResNet-18 network was used as the classifier, which was trained within the personalized federated learning framework. The ALC federated learning method enables each client to effectively integrate global and local models, extracting global information to optimize local training results. Experiments demonstrate that this method enhances fault diagnosis accuracy while protecting data privacy, showing higher fault classification precision compared to other methods, especially in multi-factory environments.

With the depletion of fossil fuels and the emergence of biofuels, ethanol-hydrogen fuel as a new generation of clean renewable fuel has attracted widespread attention. It is necessary to study the effects of ethanol-hydrogen air premixed flame combustion characteristics. Based on the constant volume combustion system, the laminar combustion characteristics of ethanol/hydrogen/air premixed flame were studied under the conditions of initial temperature of${400}\mathrm{\;K}$, hydrogen ratio of${20}\%$, equivalent ratio of${0.7}\sim {1.4}$and initial pressure of$2 \times {10}^{5},3 \times {10}^{5}$and$4 \times {10}^{5}\mathrm{\;{Pa}}$. Based on the mechanism of ethanol oxidation of Marinov and experimental data, the laminar combustion rate of Marinov was studied and the influencing factors were analyzed. Based on Chemkin-Pro software, the chemical reaction kinetics and numerical study were carried out. The results show that the laminar combustion rate of mixed fuel slows down with the increase of pressure.$\mathrm{H}$group is the main pathway of ethanol consumption, and$\mathrm{H},\mathrm{O}$, and$\mathrm{{OH}}$radicals play a leading role in the reaction of${\mathrm{{SC}}}_{2}{\mathrm{H}}_{4}\mathrm{{OH}}$and${\mathrm{{PC}}}_{2}{\mathrm{H}}_{4}\mathrm{{OH}}$from$\mathrm{H}$extracted by ethanol.$\mathrm{R}1 :\mathrm{H}+ {\mathrm{O}}_{2}\rightleftharpoons \mathrm{O}+ \mathrm{{OH}}$has the most positive effect on laminar combustion speed. The peak molar fraction of the active radical pool composed of active free radicals(H, OandOH) has a good correlation with the laminar combustion rate of ethanol in the whole equivalent ratio range, and the influence is huge. Further exploring this correlation, it is found that there is an approximate linear relationship, and the expression of laminar combustion rate with the peak molar fraction of$\mathrm{H}+ \mathrm{{OH}}+{\mathrm{{CH}}}_{3}$and$\mathrm{H}+\mathrm{{OH}}$is fitted.

At present, China's offshore floating photovoltaic is in its exploratory stage, which ensures the dynamic stability of floating photovoltaic foundation under varying environmental loads becoming a key research priority. In order to more effectively solve the above-mentioned difficulties and the shortage of land resources in the photovoltaic industry, a floating photovoltaic PE floating block foundation structure design, hydrodynamic calculation and optimization were completed through numerical simulation calculation based on the environmental conditions of a sea area in Rushan City, Weihai. The results indicate that wave height, wave period, and wave incidence angle have varying degrees of influence on the motion response and internal force values of the structure. Based on the analysis, practical applications of the new floating foundation in specific projects are guided, showing promising results that verify the feasibility and stability of this foundation structure's application.

With the construction of a new type of power system with new energy as the main body under the "double carbon" target, the challenges of natural disasters such as wildfires, icing and typhoons in the production, transmission and distribution of electric energy are more severe. Therefore, a fire point identification algorithm based on the world's first operational dawn-dusk orbit meteorological satellite Fengyun-3E satellite (FY-3E) was proposed, which was suitable for mountain fire monitoring in transmission line corridors, the adverse effects of large solar zenith angle observation conditions and satellite perspective differences on the accurate acquisition of infrared channel detection data were eliminated. Cloud information extraction and cloud pixel fire point extraction under complex atmospheric observation conditions were realized, which reduced fire point false alarms and missed alarms. The analysis of mixed pixel linear spectrum separation method shows that the fire point detection sensitivity of FY-3E mid-infrared channel is 4 times higher than that of geostationary meteorological satellite. The effectiveness of the proposed algorithm and the superiority of FY-3E in fire detection sensitivity, spatial range accuracy and positioning accuracy were verified. Compared with geostationary meteorological satellites, the fire location accuracy can be increased by more than one time, and it can effectively detect the fire time in advance by the transmission line operation and maintenance department, and guide the relevant departments to take timely measures to reduce the impact of wildfires on power grid operation.

Given the prevalent issue of aging assets within power grid companies and the subpar management of aging equipment, a decision-making approach was introduced for optimizing the decommissioning of aging assets, taking into account the influence of transmission and distribution tariffs. Firstly, in accordance with the policy framework for reforming transmission and distribution tariffs, an accounting model for transmission and distribution tariffs for provincial power grids operating at varying voltage levels was developed. Secondly, the decommissioning planning model for over-age assets was established with the optimization objective of achieving the highest return throughout the investment cycle. The decision variables of time and scale for decommissioning were utilized in this model. Through a process of rolling optimization and feedback correction, the model ensured that the scale of decommissioning for overage assets in each stage aligns with the desired value, thereby meeting the premise of system reliability. Finally, the efficacy of the model and its ability to enhance investment efficiency were demonstrated through the examination of the${110}\mathrm{{kV}}$voltage level grid in a specific province.

Synthetic aperture radar (SAR) target recognition method based on deep networks requires a large amount of training data, and in practical applications, it is extremely difficult for SAR imaging systems to obtain sufficient and evenly distributed target data. One way to solve the small sample problem in SAR target recognition, is to use electromagnetic simulation technology to generate a large amount of SAR simulation data. However, there are still significant differences between simulated images and measured SAR images, so using simulation data directly cannot bring significant performance improvement for target recognition. A simulation data optimization method based on SAR target characteristic constraints was proposed to address the above issues. On the basis of analyzing the characteristics of SAR targets, a texture structure cycle-consistent generative adversarial network (TS-CycleGAN) based on texture structure and cycle consistency was constructed, in which the structural similarity measure was used to constrain the generation process of CycleGAN. This method can reduce the difference between simulation data and measured data, and can improve the usability of simulation data. The experimental results on the SAR SAMPLE dataset show that, compared to other simulation data optimization methods, the proposed method achieves significant improvements in image quality evaluation and classification performance.

Capsule networks can encode the properties and spatial relationships of skin cancer image features, thereby overcoming the disadvantage of information loss in the pooling process of convolutional neural networks. Aiming at the problem that only shallow features can be extracted and the convergence performance of the squash function in capsule networks, a ResNeXt cascaded with capsule networks was proposed for Rs-Capsnet networks. Firstly, the complex features of the image were learned using the ResNeXt network. The Inception module and the residual connection were used to extract the deep features, and the weights of the feature map were adjusted and delivered to the capsule module through the CBAM attention module. Then, an improved squash function capsule network was used to complete the classification. Finally, the improved network was compared with mainstream models. The results show that Rs-Capsnet exhibits better performance in skin cancer image classification.

Given the practical application background of installing underground pipelines in coal mine tunnels and the actual environmental conditions underground, a jointed tunnel pipeline installation robot was designed. The detailed design of the robotic arm structure was completed, along with its 3D modeling. The kinematic model of the robot was established, and MATLAB was employed to verify the forward and inverse kinematics of the robotic arm. Based on the established kinematic model, a trajectory planning algorithm for the Cartesian space of the robotic arm was designed, and MATLAB and ADAMS software were used to verify the robotic arm through simulation experiments. The simulation demonstrates that the structural design of the robotic arm is reasonable, and the trajectory planning scheme for the robotic arm is feasible.

In order to quickly identify the location of the leakage point and the leak aperture in the coal mine, a model was proposed for identifying and locating the leak aperture by using the pressure and flow signals generated when the water supply pipeline leaked. Modal energy entropy and genetic algorithm combined with envelope entropy were used to optimize the parameters of variational mode decomposition (VMD), and then VMD was used to denoise the pressure signal. Convolutional neural network (CNN) was used to extract the deep feature sequence of pressure and flow signal, and the long short-term memory network (LSTM) was used to extract the time sequence of deep feature sequence to identify and locate the leak aperture. The experimental results show that compared with Kalman filter, mean value filter and low-pass filter, the variational modal decomposition with optimized parameters has higher root-mean-square error (RMSE), mean absolute error (MAE), signal-to-noise ratio (SNR) and normalized cross correlation (NCC), which indicates that it can effectively reduce noise components and retain effective signals. Compared with LSTM, the MAE, mean absolute percentage error (MAPE) and RMSE of CNN-LSTM in leak location decrease by 65.97%, 61.22% and 59.11%. In the identification of leak aperture, MAE decreases by 12.04%, MAPE decreases by 22.45%, and RMSE decreases by 3.29%, which proves that CNN-LSTM can make full use of the spatial and temporal characteristics of pipeline pressure and flow signals to identify the leak location and aperture, and its detection effect is more accurate and stable than LSTM.

The bridge health monitoring system based on sensor data acquisition has become standard for new bridge construction. However, this scenario presents challenges due to the massive volume of monitoring data that is difficult to store. Therefore, focusing on the time-series characteristics of bridge monitoring data, compression schemes were explored for bridge monitoring data. Differential compression was investigated based on the arithmetic progression properties of bridge monitoring timestamps and floating-point exclusive OR(XOR) compression based on the low frequency of changes in monitoring value data. Compared to the Gorilla time series database algorithm, the XOR compression method added control bits to avoid degradation of compression results. Experimental analysis reveals that both algorithms exhibit varying degrees of superiority over common compressors. The differential compression of timestamp sequences demonstrates superior compression rates compared to common compressors, achieving a compression rate of 0.015 6 for timestamp sequences that conform to arithmetic progression characteristics, approaching the compression limit value. Compression and decompression speeds are above average, and the method is insensitive to monitoring type. On the other hand, the XOR compression method performs well on datasets with low frequency of change, achieving compression rates of 0. 302 8 for bridge data and 0. 662 8 for non-bridge data, indicating sensitivity of the XOR compression method to monitoring type. In practical applications of bridge monitoring, suitable compression storage schemes can be selected based on the characteristics of the bridge monitoring dataset.

Aiming at the prominent problems of ignoring the unnatural connection relationship and interaction relationship between human bodies in two-person interaction recognition algorithm, a two-person interaction recognition network based on improved spatial temporal graph convolutional model was proposed. Firstly, the edge features of joint point data were aggregated by edge convolution to capture the unnatural connectivity relations inherent in the human body. Secondly, the interaction relationship graph between two people was constructed by using the improved relationship network. Furthermore, the branch of edge convolution and the interaction relationship graph were embedded into the spatial temporal graph convolutional network block, which were constructed as an edge-graph convolutional block and interaction relation graph convolutional block. Finally, an improved spatial temporal graph convolution algorithm was proposed to capture both the unnatural connection relationship and the interaction relationship, so as to realized the recognition of two-person interaction behavior. To verify the effectiveness of the network, it was tested on the international public large-scale standard dataset NTU RGB + D. The experimental results show that the network obtain a recognition accuracy of 97.77%, which is an improvement of 4. 28 percentage points compared to the baseline spatial temporal graph convolutional network. It improves the expressiveness of two-person interaction behavioral features, and achieves a better recognition effect than the existing state-of-the-art network models.

The accurate detection of coke overflow in high-dust environments is a pivotal challenge in achieving intelligent coke loading. A method was proposed to address this issue for the intelligent detection of coke loading overflow, which was based on dark channel prior knowledge and the ResNet network. Firstly, a video collector was used to obtain video information of the coke loading scene, and the original time-series video image frames were processed to obtain the region of interest between the discharge port and the loader. Secondly, the prior knowledge method of dark channels was employed to process the regions of interest. Enhancing the contrast between the target areas and irrelevant areas within the regions of interest, thereby mitigating the effects of dust on subsequent detection models. Moreover, the problem of overflow detection was transformed into a binary classification task by labeling the regions of interest based on the actual loading of coke. Finally, the ResNet network was utilized for modeling, enabling the completion of model training and experimentation during the loading process of newly acquired coke. The experimental results demonstrate that the proposed method exhibits promising performance on new data, achieving an overall accuracy of 86.81%. Specifically, the accuracy, recall, and F1 score for the overflow class are 84. 12%, 90.74%, and 0.8730, respectively. Furthermore, the application of the dark channel prior algorithm in data processing results in a notable increase in the recall rate of the overflow class by 3.31%.

Semantic segmentation of remote sensing images plays a crucial role in agriculture production, urban planning, and other fields. However, due to factors like imaging distance, lighting conditions, objects, and environment, there is a problem of semantic ambiguity in remote sensing images, which leads to uncertainty in segmentation. A multi-scale context attention (MSCA) method that combined pyramid pooling with attention mechanisms to better utilize contextual information was proposed for this problem. Additionally, this method significantly reduced the computational complexity and memory usage of attention methods. Experimental results on the ISPRS Potsdam dataset demonstrate that the MSCA method achieves superior segmentation performance for target classification with ambiguous semantic information in remote sensing images while almost not increasing memory consumption and maintaining consistent inference speed.

In order to promote the green, low-carbon and high-quality development of rural areas in western Inner Mongolia, the data collected from the survey and literature was combined, the energy consumption of farmhouses was jointly simulated through DeST and Trnsys software, single factor analysis was carried out, the orthogonal test method was used to obtain multiple schemes, and the gray fuzzy comprehensive evaluation method based on random forest algorithm was used to comprehensively optimize the enclosure structure and heating system, and selected the most suitable green and low-carbon farmhouse scheme in western Inner Mongolia. The results show that the optimal scheme of green and low-carbon farmhouses in western Inner Mongolia is as follows: the building is facing north and south, the floor height is${3.4}\mathrm{\;m}$, the ground is${20}\mathrm{\;{mm}}$polystyrene extruded polystyrene board (XPS) thermal insulation tile floor, the roof is${120}\mathrm{\;{mm}}$expanded polystyrene foam board (EPS) insulation board inverted concrete block roof, the external wall is${160}\mathrm{\;{mm}}$polystyrene extruded polystyrene board (XPS) insulation board external insulation concrete block wall, the external window is$6\mathrm{C}+ {12}\mathrm{{Ar}}+ 6\mathrm{C}6\mathrm{\;{mm}}$double-layer ordinary glass inert gas plastic steel window, the south-facing window-to-wall ratio is 0.5, the north-facing window-to-wall ratio is 0.5, and the sunlight depth is${1.2}\mathrm{\;m}$. The material of the sunshine room is$6\mathrm{C}+ {12}\mathrm{{Ar}}+ 6\mathrm{C}6\mathrm{\;{mm}}$double-layer inert gas ordinary glass + plastic steel window frame + thermal insulation curtains, and the wind power generation efficiency is${45}\%$. The heating energy consumption of the optimal scheme is${2661.15}\mathrm{\;{kW}}\cdot \mathrm{h}$,the average indoor temperature on the coldest day is${11.62}{}^{\circ }\mathrm{C}$, the carbon emission reduction is${10.02}\mathrm{\;t}/\mathrm{a}$, the solar heat gain is${67702.75}\mathrm{\;{kW}}$, and the net present value$> 0$, which is economical and has a certain degree of popularization in the rural areas of western Inner Mongolia, providing a development direction for the green and low-carbon transformation of rural houses in western Inner Mongolia.

In response to the common forms of specimens used for interface shear performance testing, these specimens fail to effectively reflect the actual situation of shear stress on the interface. An optimized improvement scheme for the traditional Z-type specimen was proposed. By employing the optimized Z-type specimen, experimental studies on the shear strength at the interface between ultra-high performance concrete (UHPC) and normal concrete (NC) were conducted, examining the influence of shear reinforcement ratio and interface roughness on the interface shear strength. The research results indicate that the failure occurs on the NC side or partially on the interface and partially on the NC side, which is characteristic of typical brittle failure. The shear strength of the interface increases with the increase of roughness, but when the roughness is larger than the value of 1.8, the effect of increasing interface roughness to enhance the interface shear strength is not very significant. Ribbed reinforcement as shear reinforcement can fully exert the anchoring effect and the effect of improving the interface shear strength is more evident than that of smooth-round reinforcement. A calculation formula for the interface shear capacity of UHPC and NC, which can consider the contribution of shear reinforcement and interface roughness, has been established. The theoretical calculation values are in good agreement with the experimental results, which can provide reference for the engineering design of composite components with UHPC and NC interfaces.

Reinforcement and water sealing effect difficult to achieve by conventional stratum grouting method in strong seepage sandy soil stratum. In order to study the mechanical characteristics of freezing-grouting combination in water-rich sand stratum, the stress-strain relationship and its influencing factors of artificially frozen cement sand were studied by triaxial tests, and the variation law and strength mechanism of stress-strain relationship of samples under different freezing temperature, curing age and confining pressure were discussed. The results show that the stress-strain curve of frozen cement-sand has a certain strain-hardened nonlinear ductility stage including compaction stage linear elasticity stage nonlinear ductility stage and strain-hardening stage. The non-linear increase of cohesion and internal angle of frozen cement-sand due to the curing age of freezing temperature increases the shear strength of frozen cement-sand, and the non-linear ductility phase strain ratio enhances the brittleness of frozen cement-sand. The increase of confining pressure increases the shear strength of frozen cement-sand, and the proportion of strain in nonlinear ductility stage improves the ductility of frozen cement-sand. Based on Mohr-Coulomb strength criterion, a non-linear strength prediction model of frozen cement sand was established, which considered the influence of freezing temperature and curing age. The error between the predicted results and the measured values is less than 5% The research results can provide parameter support for the fine design of freezing-grouting combined reinforcement scheme for water-rich sandy soil stratum.

In order to explore the effect of dry-wet cycles in acidic environment on the physical and mechanical properties of limestone, and to evaluate the long-term stability of limestone rock mass in this environment, the limestone of the Jinfo Mountain of the Nanchuan District in Chongqing was selected as research subject. The limestone specimens were exposed to dry-wet cycles under neutral and acidic environments. The specimens were treated through mass loss test, hygroscopic property test, uniaxial compression test and tensile test. The results show that under the condition of the same pH of the soaking solution, with the increase of the times of dry-wet cycles, the mass loss rate and saturation water absorption rate of specimens increase; the tensile strength, uniaxial compressive strength and elastic modulus gradually decrease; with the same times of dry-wet cycles, the lower the pH of the soaking solution leads to the more serious the loss of physical and mechanical properties. Based on the experimental results, the damage theory, Weibull distribution, Lemaitre strain equivalence hypothesis and Mohr-Coulomb (M-C) strength criterion, the damage constitutive model of limestone by using a quadratic function to characterize the nonlinear features of the compaction stage of stress-strain curve was established and validated.

Based on the field pull destructive test of 9 anti-floating anchor of screw-thread steel bars in a foundation pit anti-float project in Qingdao, the load-displacement characteristics of anti-floating anchor of screw-thread steel bars under different anchoring lengths were studied, and the bearing performance of anti-floating anchor of screw-thread steel bars was determined. The results show that the ultimate uplift bearing capacity of the anti-floating anchor of screw-thread steel bars with the same diameter is 681 kN for the 3.0 m and 3.5 m anchors anchored in medium-weathered granite, and 1 004 kN for the 4.0 m anchors anchored in medium-weathered granite. At the initial stage of loading, the displacement of anchor head increase linearly, and with the increase of load, the displacement of anchor head increase abruptly, all of which exceed 50 mm. The agreement between the hyperbolic function and the power function load-displacement curve model and the measured value is good when the load level is low, but is relatively poor when the failure is near, and the predicted ultimate tensile strength is much different from the measured value. The exponential function load-displacement curve model can predict the ultimate uplift bearing capacity of the test anchors with high accuracy and good agreement with the measured curve.

To investigate the deformation mechanism of underground electrical conduits in soft soil considering the softening effect under traffic loads, a USDFLD subroutine was developed based on the dynamic modulus attenuation model. This subroutine was imported into ABAQUS software to establish a three-dimensional finite element model of electrical conduits buried in soft soil foundations. The finite element method was used to analyze the dynamic response of underground electrical conduits under traffic loads. The effects of different traffic load magnitudes (${50}\%$full load,100% full load,200% overload,300% overload) and burial depths (800,850,900,950mm)on the mechanical properties of electrical conduits were studied. The results show that the softening effect of soft soil has a significant impact on the dynamic response of electrical conduits under traffic loads. As the traffic load magnitude increases, the settlement of the electrical conduit gradually increases, and the strain at the bottom of the conduit shifts from symmetric to asymmetric distribution, with an increase in the strain concentration area. Increasing the burial depth of the electrical conduit can significantly reduce the impact of traffic loads on the conduit. When the burial depth increases from${800}\mathrm{\;{mm}}$to${950}\mathrm{\;{mm}}$, the vertical displacement decreases by${39}\%$. The research results provide a scientific basis for the design and construction of power pipes in soft soil areas, and help optimize the depth of pipe embedding and cope with the influence of different traffic loads.

The occurrence of natural gas leaks in buried gas pipelines is a serious safety event that can have significant economic and environmental impacts. For large-diameter high-pressure gas transmission pipelines, the computational fluid dynamics (CFD) method was used to establish a three-dimensional numerical model that included a${1.4}\mathrm{\;m}$diameter pipeline and the surrounding soil, to study the leakage characteristics of high-pressure gas through a pre-set leak hole in the soil. The CFD model considered the soil as a porous medium material, used the Redlich-Kwong equation of state to describe the temperature-pressure effects of high-pressure gas, and combined species transport and turbulence models to study the impact of leak hole diameter and internal pipeline pressure on leakage rate and temperature distribution. The results show that the leakage rate increases with the increase of hole diameter and pressure. When the leak hole diameter varies from 10 to${50}\mathrm{\;{mm}}$, the leakage rate increases by${77.78}\%$. Ambient temperature can cause the soil temperature field distribution to take different forms. When the ambient temperature is low, the temperature-pressure effect produced by the leakage of high-temperature gas inside the pipeline will be weakened. When the ambient temperature is close to the temperature of the gas inside the pipeline, a detectable temperature change area is produced in the buried range of 0.7 to 1.2 m above the leak hole. The research results help to understand the leakage characteristics and temperature change patterns of buried large-diameter high-pressure gas transmission pipelines, providing a theoretical basis for the layout of pipeline leak monitoring optical cables.

The piers of sea-crossing bridge are always subject to the scouring effect of flow and waves. The flow environment around the piers is complex. There is a risk of foundation erosion, endangering the safety of the bridge. Based on computational fluid dynamics (CFD) and the open-source software OpenFOAM, three-dimensional numerical simulations of the flow field around the inclined oblong pier were conducted with different inclination angles and length-to-width ratios$\left({L/D}\right)$. The results demonstrate that under the influence of wave and current, a symmetrically distributed vortex is formed behind the pier and undergoes periodic changes. The wake vortex constantly strengthens and moves backward as the trough approaches the pier. It reaches the maximum than gradually reduces and dissipates before the crest reaches the pier. With an increased downstream inclination angle, the pier tends to be streamlined, resulting the decreasing of wake vortex intensity and the horizontal load of pier. As the length-to-width ratio$\left({L/D}\right)$increases, the tail vortex area behind the bridge pier decreases and the horizontal load increases. Within the range of$L/D = 1$to 3 and a range of$-{30}^{\circ }$to${30}^{\circ }$, the minimal load on the pier is achieved when$L/D$is 1 and inclination angle is${10}^{\circ }$.

In order to study the stability of the tunnel structure under the airport runway when the aircraft is running, the numerical calculation model of the runway, soil layer and tunnel structure co-deformation was constructed by establishing the six-degree-of-freedom dynamic equation of the “five-point contact” aircraft. The influence of the aircraft type, pavement type and buried depth on the stability of the tunnel structure was analyzed. The results show that the more concentrated the distribution position of the main landing gear wheel is, the greater the influence on the stability of the tunnel structure under different aircraft loads. The attenuation effect of stress diffusion on the flexible tunnel surface is obviously better than that on the rigid tunnel surface, and the deformation degree of the arch top is more significant than other locations. With the increase of the buried depth of the tunnel structure, the disturbance effect of aircraft load on the tunnel structure shows a decreasing trend. When the buried depth of the tunnel structure exceeds${64}\mathrm{\;m}$, the tunnel structure no longer bears the disturbance effect of aircraft load.

In order to address the issue of coordinate base inconsistency in the fusion display of road building information modeling (BIM) models and tilted reality models within existing large-scale 3D geographic information system (GIS) platforms, a high-precision matching method for geographic coordinates between road BIM models and tilted reality models was proposed. Taking into account the distribution characteristics of road bands and the requirements for road maintenance, the model was initially segmented. Subsequently, a spatial distance-weighted least-squares coordinate matching parameter fitting method was developed based on the distribution of characteristic points on the road pavement and asset facility model, with a focus on accurately joining edges of the road pavement in each segment. Real road data was selected for conducting experiments to validate this coordinate matching method. The method effectively resolves bias issues in matching between the road model and tilted reality model, achieving accuracy at millimeter level post-matching, thereby meeting digital maintenance needs as well as dynamic updating requirements for road traffic facilities.

low-temperature fracture is the normal distress of the thin-layer overlay asphalt mixture. To reveal the low-temperature cracking behavior, semicircular bending tests combined with crack observation, digital image correlation and a finite element numerical simulation based on the meso-structure cohesive zone model were carried out. The applicability of the model was verified by the load-displacement curve and crack paths. The results show that the low-temperature cracking behavior of asphalt mixture can be well demonstrated by digital image processing. The simulation of asphalt mixture meso-structure is suitable for analyzing the cracking behavior. Furthermore, the maximum tensile stress and neutral axis positions on the mid-span section are correlated with the properties of the materials.

Seismic soil liquefaction can lead to soil instability and slip, resulting in irreversible and severe damage to bridges. The seismic response of curved bridges in liquefied lateral extension sites is a major concern due to the complex stress state. Three representative far-field seismic waves were selected and applied to a four-span continuous curved bridge from 12 different directions. The maximum tilt angle of the site was set to be the same as the seismic input angle in order to investigate the seismic response behavior of the curved bridge in the liquefaction expansion site and conduct a comparative analysis. The results show that as the far site seismic input gradually changes from${0}^{\circ }$to${180}^{\circ }$, the pile top bending moment of the curved bridge decreases gradually, with the side piers experiencing larger bending moments compared to the secondary center piers and the center piers. When the seismic input wave changes gradually from${180}^{\circ }$to${360}^{\circ }$, the pile top bending moment gradually increases, with the middle pier and the second pier experiencing higher bending moments than the side piers. The maximum bending moment at the bottom of the pier alternates between the middle pier and the second pier as the seismic input angle changes, with the second pier experiencing a significantly higher number of occurrences of the largest bending moment compared to the middle pier. The relative displacement between the pier and beam and the ground shaking input angle exhibits a cyclic trend of initially increasing and then decreasing. Therefore, it is recommended that the location of a bridge project susceptible to ground vibration should be determined based on the type of ground vibration, and corresponding anti-liquefaction measures should be implemented accordingly.

Considering the technical issues related to the construction of extremely small radius and ultra large diameter shield tunnels in stratified strata, taking the shield tunnel project of the Pazhou Station to Beigang Park Station section of the Pearl River Delta intercity rail transit in Guangzhou as the research object, key construction technologies of shield excavation were elaborated in detail. Solutions to outward deviation of the excavation axis because of the small curve radius and strata disturbance caused by the excavation were provided. Built upon the analysis of on-site real-time monitoring data, variation patterns of vertical and horizontal displacements, pore water pressure and soil pressure during the construction of the small radius shield tunnel were revealed. Monitoring data shows that the shield excavation of the turning section in rock layers has little impact on surface settlements. The influence of shield tunneling on the surrounding soil decreases with the increasing distance, the maximum horizontal displacements occur in the area above the tunnel. There is a high similarity in the changing trend of pore pressure and soil pressure and the impact on the soil outside the turning is greater when the shield turns.

Charging infrastructure is essential for promoting the development of electric vehicles, and identifying charging behaviors of electric vehicles is the precondition of optimizing the layout of charging infrastructure. Using the charging data of the Kechuang Base Charging Station in Beijing in 2017, charging behaviors of electric vehicles were explored by descriptive analysis and statistical analysis. Based on the charging power, charging piles were divided into three categories: high(100kW), medium(40kW), and low (${10}\mathrm{\;{kW}}$and${15}\mathrm{\;{kW}}$). Firstly, a descriptive analysis was conducted. It is found that as the charging power decreases, the charging time significantly increases, but usually does not exceed 180 min. 86.5% of customers are company users, mainly consisted of taxi/ ride hailing drivers; electric vehicles are often charged when their state of charge (SOC) are still high. Then, an ordered Logistic model was built to identify the key factors influencing the charging pile choice. Company users, daytime, weekday, charging peak period, and the low starting SOC are found to be able to significantly lead users to adopt the high-power charging piles. The research findings could be used to help optimizing the charging station layout.

In the context of achieving carbon peak and carbon neutrality in transportation, high-precision, fine-grained, and highly feasible real-time prediction methods for motor vehicle energy consumption have become key components in reducing carbon emissions. Addressing the issue of limited universality in traditional regression-based vehicle energy consumption models, a prediction model based on the radial basis function neural network (RBFNN) has been developed. Firstly, the influencing factors of vehicle energy consumption were analyzed, and the influence factor matrix was normalized using the Min-Max standardization method. Then, the grey wolf optimization (GWO) algorithm was employed to optimize the training of the centers of the hidden layer, the width of the Gaussian function, and the weights connecting the hidden layer to the output layer in the RBFNN algorithm. Finally, a comprehensive analysis of the model's prediction accuracy was conducted through horizontal model comparisons and real-world vehicle measurements. The test results demonstrate that the RBFNN algorithm improves prediction accuracy by approximately 12% compared to traditional regression models, achieving an overall accuracy of over 90%. This makes it highly effective in accurately predicting the energy consumption of urban motor vehicles.

To solve the problems of multiple influencing factors, different focuses of participating parties, and inability to quantitatively describe the comparison and selection schemes in the current process of selecting routes for mountainous expressways, based on thorough research on the influencing factors of expressway and railway route selection at home and abroad, the influencing factors of expressway route selection in mountainous areas of China were systematically analyzed and summarized, and four aspects : economy, technology, safety and environment were summarized, totaling 16 specific influencing factors. Based on the Xihe to Tanchang Expressway project, a group of 164 experts from the local government, industry regulatory departments, owners, design, construction, supervision, third-party testing units, and research institutes in the project area were organized to form an expert group. The analytic hierarchy process (AHP) was used to evaluate the importance of 16 route selection influencing factors. The results show that the comprehensive weight average score of the three influencing factors in the environmental indicators is high, reflecting the further strengthening of environmental awareness in the field of engineering construction. To further establish a optimization model for scheme comparison, taking the scheme comparison of the route from the project Dengta Village to Haolin Village as an example, the technique for order preference by similarity to idea solution (TOPSIS) method based on the AHP was used to compare and select schemes. The superiority of the four comparison schemes is 2.84, 0.56, 0.72, and 2. 15, respectively, indicating that scheme 1 is optimal. Based on a comprehensive analysis of the factors affecting the selection of mountainous expressway routes, the research results adopt the AHP-TOPSIS comprehensive evaluation index system model. While fully utilizing expert experience, it can objectively and scientifically

In order to select advanced technologies applicable to civil aircraft, technical characteristics from various fields were integrated to develop an evaluation framework. Five key evaluation dimensions were identified: technology competitiveness, technology readiness assessment, economic impact, engineering methods, and technology standards. From practical case studies, these dimensions were derived and used as the basis for an evaluation index system. A technology application perspective was adopted, utilizing a cloud model and a reverse cloud generator to determine indicator weights. This approach incorporated technical standards from different industries, airworthiness standards, and the entire life cycle of civil aircraft to create comprehensive evaluation guidelines. The results show that this approach effectively compares advanced technologies across different industries, differentiates similar technologies at various levels, and eliminates those that offer no benefit or are unsuitable for civil aircraft. This evaluation approach successfully selects advanced technologies with a high degree of compatibility with civil aircraft.

To explore the process and evolution of large-scale flight delay propagation, and avoid previous research mainly focusing on observing real data and the distribution of delay propagation networks. Drawing inspiration from the classic susceptible-explored-infected-recovered(SEIR) model and taking into account the impact of node closure on large-scale flight delays. Based on this, the state of airport nodes was added to five categories, and a large-scale flight delay propagation model based on susceptible-explored-infected-death-recovered (SEIDR) was constructed and applied to air traffic networks. Using a combination of phase trajectory analysis and related parameter analysis, the propagation threshold and propagation law of large-scale flight delays were obtained, and the influence of propagation parameters between airport nodes on the propagation law of large-scale flight delays was further analyzed. Finally, a large-scale flight delay in 2022 was taken as an example for analysis and verification. The results show that the established model can more accurately describe the evolution process and propagation law of large-scale flight delays.

In order to study the reasonable sealing length of bedding gas drainage boreholes, based on the gas-air dual gas and the negative pressure attenuation effect of boreholes, a three-dimensional borehole drainage model was established by finite element simulation software to monitor and analyzed the gas pressure of coal seam in the sealing section. Through the field test of 20915 haulage roadway, the gas drainage effects of different sealing lengths were investigated. The results show that under the negative pressure attenuation effect, the negative pressure of borehole drainage is exponential function distribution, and the reduction of gas pressure in coal seams at different positions of borehole is different, and the closer to the sealing position, the smaller the reduction of gas pressure. The peak gas pressure in the sealing section is proportional to the sealing length. According to the field test, the gas drainage concentration decreases to about${10}\%$after 130 days when the sealing distance is${10}\mathrm{\;m}$. The sealing length of${20}\mathrm{\;m}$maintains at about${30}\%$, and the extraction concentration of the borehole with sealing length of${30}\mathrm{\;m}$maintains at above${60}\%$after 130 days.

In order to solve the problems of roof breakage, support difficulty, water and mud inrush encountered in underground space operations such as mining and tunnel excavation, polyester ammonia/water glass organic-inorganic hybrid grouting reinforcement material was taken as the research object. By establishing a similar simulation grouting model, the temperature and pressure of measuring points at different distances from the injection point during the model grouting process were studied, and the slurry diffusion law was analyzed. The mechanical properties of grouting reinforcement were analyzed to test the consolidation effect. The results show that the polyurethane(PU)/water glass double-liquid grouting material exhibits irregular diffusion in the broken rock test model, and the curing reaction is an exothermic reaction. It reaches a maximum of${83.2}\mathrm{C}$at 10 min after slurry injection, which is 6.6 times of room temperature. The maximum pressure is${5.7}\mathrm{{MPa}}$, which is 1.425 times of the test load. The temperature and pressure increase rapidly with time and then slowly decline and finally stabilize. The uniaxial compressive strength range of polyurethane/water glass double liquid grouting and solid is${15.32}\sim {32.57}\mathrm{{MPa}}$, the maximum bearing capacity of triaxial loading is${41.9}\mathrm{{MPa}}$, the residual strength is${25}\mathrm{{MPa}}$, the maximum load of creep failure is${25}\mathrm{{MPa}}$, and the strength of the injected material is greatly improved after consolidation. Through the microscopic analysis of grouting reinforcement, it can be seen that the rock and slurry are closely cemented at the junction, and the grouting reinforcement effect is good.