The optimization and operational control of ventilation systems on the offshore platforms is of great significance for improving cabin environmental quality and ensuring occupant health. In response to the current lack of a comprehensive design standard system for offshore platform ventilation, domestic and international specifications for shipboard and land-based ventilation systems were systematically classified and summarized to establish a dedicated design standard framework tailored to offshore platforms. Ventilation rate models, indoor dynamic models, air quality models, and energy consumption models were analyzed. Furthermore, an overview of ventilation optimization methods was provided for three critical areas: living areas, equipment areas, and storage areas. Current challenges and technical difficulties in system design and operation were analyzed, and feasible future development strategies for ventilation system design and optimization were proposed. The research results provide scientific basis and technical guidance for the design, operation, and energy-saving measures of offshore platform ventilation systems.

With the emergence of deep learning technologies, speech enhancement methods based on deep learning have seen widespread application and generally surpass traditional approaches in performance. The fundamental framework of noise reduction signal processing in speech enhancement was outlined and progressively delved into the latest advancements in deep learning-driven speech enhancement models. A comprehensive organization of deep learning-based speech enhancement algorithms was provided, detailing the principles, characteristics, evaluation metrics, and representative studies of various neural network-based methods. The advantages and limitations of these approaches were thoroughly assessed. Finally, in light of the current developmental landscape, the core challenges encountered in the speech enhancement process were analyzed, and future developmental trajectories were discussed and predicted.

The application of building information modeling(BIM) technology in the construction industry in China has developed rapidly, and its further development is inseparable from the support of BIM standards. In view of the importance of BIM standards, it is necessary to review the existing researches on BIM standards. Firstly, three key research topics, namely theoretical research, technical research and application research of BIM standards, were determined by keyword cluster analysis method. Secondly, for each research topic, the methods and results of existing research were explained and summarized through critical review, with typical cases being enumerated. Then, the evolution trend of BIM standard research was analyzed by using the timeline map generated by keywords. The results indicate that the extension of industry foundation classes(IFC) standard and the technical and application research based on IFC will still be the research hotspots. At the same time, research on BIM standard framework will continue. Furthermore, future research on BIM standards should also focus on three cutting-edge areas: technological integration, expansion of application scenarios, and cross-disciplinary collaboration. The research results will help further develop BIM standards and improve the formulation and application level of BIM standards.

Due to the high calorific value of energetic materials combined with their flammable and explosive nature. The propagation in the tube will affect the shape and geometric dimensions of the tube, resulting in the propagation of detonations is affected. In order to deeply investigate the influence of annular perturbation on the propagation of detonation waves, accurately and clearly observe the propagation dynamics of the detonation wave in annular tube, and better reflect the influence of boundary layer effect and curvature tube wall on detonation waves.An annular disturbance detonation experimental device was built up. Annular disturbance was realized by adding disturbance tubes with different diameters to the end of the smooth circular tube. The detonation wave velocity, triple-point trajectory, and cell structure were observed by using a data acquisition system composed of pressure sensors and smoke films. The experimental system of annular disturbance detonation was constructed successfully. It was able to obtain the ideal propagation data with remarkable regularity and high reliability. After verification, the detonation experimental device built has excellent data acquisition capabilities, and the obtained data confirms that the device is scientific and effective. The experimental system built contributes to providing theoretical support for accident prevention and control, allowing scientific instruments to play a more significant role in supporting technological innovation and societal development.

In order to identify the characteristics of the geothermal field in Longmuwan, including its temperature field, hydrochemistry, and recharge sources, and to analyse its genetic model. The hydrogeochemistry, isotopes, and geothermal temperature measurement methods were employed, integrated with regional geological characteristics, the hydrochemical characteristics, heat reservoir temperature and recharge sources of the geothermal field were systematically analysed, and a conceptual genetic model was preliminarily constructed. The results indicate that the geothermal gradient of porous stratified reservoir is 5.23~8.25 ℃/100 m, while the fracture zoned reservoir has a gradient of 1.47~4.50 ℃/100 m, the deep heat reservoir temperature range is 87~115 ℃, with geothermal fluid circulation depths reaching 960~2 298 m in Longmuwan geothermal field. The hydrochemical types of geothermal fluid are HCO₃-Na·Ca type and Cl·HCO₃-Na type, primarily recharged by atmospheric precipitation. The calculated recharge elevation is 421~597 m, suggesting the recharge area is the hinterland of Jianfeng Ridge. Isotopic age results show that the formation age of geothermal water exceeds 6 000 a, and it has the characteristics of a long recharge pathway and slow groundwater flow.

To improve the accuracy of precipitation forecasts and address the limitations of traditional numerical weather prediction models in forecast precision and computational efficiency, a meteorological large model was combined with a deep learning post-processing approach was combined. A case study was conducted for precipitation forecasts over Shaanxi Province during 2008—2018. Based on meteorological variable fields output by the FourCastNet model, a pre-trained model mapping meteorological fields to regional precipitation was constructed using Bayesian-optimized convolutional neural networks (CNN)/long short-term memory (LSTM) networks. The results indicate that this method outperforms traditional numerical weather prediction models in terms of spatial resolution and forecast accuracy. The regionally fine-tuned forecasts more accurately capture the spatiotemporal distribution of precipitation. Furthermore, the Bayesian-optimized deep learning post-processing algorithm effectively mitigates the impact of initial field biases on forecast results. These findings demonstrate the significant potential of integrating meteorological large models with deep learning post-processing algorithms for accurate precipitation forecasting, providing scientific support for disaster prevention, agricultural production, and water resource management.

The continental shale oil in the Da’anzhai section of the Ziliujing Formation in the Sichuan Basin has great exploration and development prospects. The sedimentary facies are diverse, the lithology is complex, and the vertical changes are fast. The understanding of the lithological differentiation combination mode and reservoir characteristics is unclear, which restricts the optimal selection of favorable shale oil reservoirs in the Da’anzhai section. Based on observations, thin section analysis, X-ray diffraction (XRD), vitrinite reflectance Ro testing, total organic carbon (TOC) content testing, physical property testing, rock pyrolysis, fluorescence analysis, and other experiments of four actual drilling cores in the central Sichuan Basin. By comprehensively analyzing mineral composition characteristics, as well as considering the content, occurrence, thickness of the shell layer, and its superimposed relationship with shale, seven lithological combination models for the Da’anzhai member in the central Sichuan basin were established (pure shale type, shale interbedded with floating shell limestone type, shale interbedded with millimeter scale shell limestone type, shale interbedded with centimeter scale shell limestone type, shale interbedded with centimeter scale shell limestone type, shale interbedded with shell limestone type, and pure shell limestone type). By integrating reservoir characteristic parameters such as TOC content, physical properties, oil content, and brittleness index, the reservoir characteristics of different lithological combinations were clarified. Based on the exploration and development practices of the Da’anzhai section and reservoir characteristics, a classification evaluation standard for reservoirs was established. It is believed that the lithological combination of shale interbedded with millimeter scale shell limestone and shale interbedded with centimeter scale shell limestone is the key layer for exploration and development, which has most favorable source reservoir combination, best physical properties, the highest oil saturation index(OSI) index, strong mobility, and good brittleness. The thick dark shale interval has the highest TOC content, good physical and oil properties, which is a potential interval for further exploration.

Based on the detailed process mineralogy of gold ore from Jierwushake gold deposit in west Junggar, the selectability test was carried out. The results show that the valuable element in the ore is Au with a grade of 3.61 g/t. The types of gold minerals are natural gold, silver-gold, gold-tellurium and gold-selenium-silver ore, and the embedded states are encapsulated gold, fracture gold and intergranular gold. The particle size is mainly microparticle gold (0.2~10.0 μm), accounting for 96.96%, and the number of fine and above gold particles (>10 μm) account for 3.04%.The flotation-leaching combined process is recommended for mineral processing test: the Au grade of flotation-flotation concentrate is 53.14 g/t, and the recovery rate is 31.69%. After leaching the whole sludge of flotation tailings for 24 hours, the gold content in tailings is 0.20 g/t, and the leaching rate of gold operation is 89.56%, the Au total recovery rate of combined process is 93.31%, and the instructions are ideal.

In order to find out the uranium metallogenic potential of the Lower Cretaceous in Kelulun Sag of Hailar Basin, the spatial distribution of sequence stratigraphy, types and distribution characteristics of sedimentary facies and favorable spatial location of uranium enrichment in the area were studied by using sequence stratigraphy and sedimentary facies analysis methods based on core, logging and seismic data. The results show that the third-order and fourth-order sequence stratigraphic division marks of the target strata in the Kelulun Sag are determined. The target strata are divided into one super sequence, two three-order sequences and four fourth-order sequences, and the distribution characteristics of sequence stratigraphy are clarified. The sedimentary system of fan delta-lacustrine facies is mainly developed in the target layer in the area. The sedimentary facies plane has the characteristics of near source, fast phase change and small distribution range. The braided channel sand bodies of the fan delta plain and the underwater distributary channel sand bodies of the fan delta front have good uranium metallogenic potential.

To address the issue of inaccuracies in groundwater level predictions due to the insufficient consideration of groundwater-related factors, clustering methods for observation wells based on spatial distance, hydrogeological attributes, and a hybrid of distance and attributes were proposed. The significance of inter-well connectivity in groundwater level prediction was validated. Four models were designed, which were applied to simulate and predict groundwater levels in the karst water region of Jinan and compared with actual observations. The prediction results indicate that the combined model incorporating the connectivity characteristics of karst aquifers, known as convolution-long short-term memory(ConvLSTM), outperforms the traditional long short-term memory(LSTM) model. Among the models, the mix-multivariate-convolution-long short-term memory(M-MV-ConvLSTM) model, which accounts for wells of the same category based on the hybrid distance-attribute clustering results (characterized by strong connectivity), achieves the highest prediction accuracy and the smallest error. The average root mean square error is approximately 0.457, and the Nash-Sutcliffe efficiency is approximately 0.216, demonstrating a higher prediction accuracy than the traditional LSTM model. The research results is positioned to serve as a reference for real-time groundwater level prediction in karst regions.

In order to explore the medication characteristics of expectorants in the Huatan prescriptions commonly used in treating ischemic stroke recently. “Huatan/Qutan/Ditan/Huotan/Daotan/Guntan/Banxia Baizhu Tianma Decoction/Xinglou Chengqi Decoction/Wendan Decoction/Erchen Decoction/Xiao xianxiong Decoction/Lingjiao Gouteng Decoction/Jieyu Dan” + “ischemic stroke/cerebral ischemia/cerebral infarction/cerebral embolism/cerebral thrombus” + “clinical” as the main topic on the China National Knowledge Network (from May 1, 1986 to April 1, 2024) was used to investigate the medication characteristics of expectorants, and selected literature meeting the criteria. Statistical analysis of the data was performed using Excel and IBM SPSS Modeler 18.0 software. The results show that Banxia and Tian nan-xing are the most frequently used expectorants in different stages of ischemic stroke, followed by Fuling, Shi chang-pu, Chenpi, and Gancao. The dosages of most expectorants are 10~15 g. In the analysis of Siqi and five flavors, Wen, Ping, Xin, Ku, and Gan have the highest frequency of occurrence in different stages of ischemic stroke. In the analysis of meridian tropism, the lung and spleen meridian have the highest frequency of occurrence. Most Huatan prescriptions are composed of 8~14 herbs in both the acute and rehabilitation stages, accounting for 82.51% and 78.05% of the total frequency, respectively. In the analysis of association rules, 25 traditional Chinese medicine combinations with strong correlation strength are obtained, and the most combinations of herbs are Huatan-Xifeng-Tongluo and Huatan-Huoxue-Qufeng. Most Huatan prescriptions are administered through the traditional decoction method and generally used in combination with Western medicine. It is concluded that the commonly used expectorants in Huatan prescriptions for treating ischemic stroke are mainly Banxia and Tian nan-xing, and the dosage ranges of most expectorants are 10~15 g. The number of herbs in Huatan prescriptions is mainly 8~14. The research results provide references and clinical data support for the application of expectorant Chinese medicine and Huatan prescriptions in the treatment of ischemic stroke and the development of research on treating ischemic stroke from the perspective of phlegm.

Rainfall is one of the main factors affecting landslide stability. To explore the deformation and stability laws of unsaturated soil landslides under different rainfall conditions, based on the theory of saturation-unsaturation and the intensity reduction method, focused on a traction landslide in eastern Jiangxi. The rock and soil parameters of the landslide hazard body were determined through field investigations and laboratory tests. AutoCAD software was used to restore the terrain and geological conditions of the Tongshan landslide in Xishan Village, Zhengfang Town, as accurately as possible. A three-dimensional mathematical model of seepage-deformation coupling for the landslide was established. The dynamic process of seepage deformation and stability of the unsaturated soil landslide under various rainfall conditions (different intensities, durations, and post-rain stoppage) was simulated. The results indicate that the pore water pressure at the slope surface increases gradually with rainfall intensity and duration. The drainage velocity increases, the saturated zone gradually transforms into the unsaturated zone, and the displacement and deformation increase progressively. After the rainfall stops, leakage in the landslide hazard body exhibits a delayed response. The displacement deformation after continuous rainfall first increases and then decreases, while the displacement following intermittent rainfall shows periodicity during the short-term post-rain stoppage period. In terms of landslide stability, the reduction trend of the stability coefficient of the slope body strength under different rainfall intensities and durations is similar, but the stability coefficient under the same intensity varies, with the overall trend showing a gradual decrease with increased duration. After the rain stopped, the stability coefficient of the uniform rainfall slope body decreases initially and then increases, whereas the stability of the intermittent rainfall slope body exhibits periodic variations.

In order to study the problem that the processing of 7075 aluminum alloy rings was affected by the large value of initial residual stress, the effect of reducing the residual stress was investigated by using the method of compression of 7075 aluminum alloy rings along the ring direction. ABAQUS simulation software was used to simulate the quenching and compression of 7075 aluminum alloy rings to obtain the initial residual stress field and the residual stress field after compression. The results show that the initial residual stresses generated by quenching can be effectively reduced by the method of compression in the ring direction. After the data before and after compression is compared, it is found that when the compression deformation amount is 1.312 5%, the amplitude of quenching residual stress decreases by 57% of the original residual stress value as a whole, and the amplitude of radial residual stress and circumferential residual stress decreases by about 58%. It is concluded that the method of circumferential compression can effectively reduce the residual stresses of aluminum alloy ring parts.

Addressing the lack of clarity regarding spontaneous imbibition displacement mechanisms and production management strategies for shale oil in the Cangdong Sag, a model was established that considered the “synergy of imbibition, flowback, and productivity”. The model was designed to dynamically reflect the mutual constraints and synergies between spontaneous imbibition displacement and engineering parameters such as flowback rates and soaking durations. Through comprehensive numerical simulations integrating geology and engineering across the entire lifecycle, the spontaneous imbibition displacement patterns and optimal flowback regimes for the C1 and C3 sweet spots in the Kong-2 Member, which served as the main development interval in the Cangdong Sag, were elucidated. The results indicate that spontaneous imbibition displacement continues to occur during the flowback process. The optimal soaking durations for the C1 and C3 sweet spots are determined to be between 37 and 42 days, with a reasonable flowback rate ranging from 20 to 40 tons per day. The research findings provide a theoretical foundation for studies on spontaneous imbibition mechanisms and reasonable production management strategies for deep shale oil and gas reservoirs.

Due to factors such as temperature, pressure, and production rate, integrity issues like annular leakage in gas well tubing frequently occur frequently. In order to study the influence of working conditions on the process of downhole oil pipe leakage, a high temperature and high pressure oil pipe leakage simulation model was established based on field parameters and compared with the existing mathematical model of small hole leakage. Based on the simulation model, the influence of flow field change, leakage aperture, casing pressure difference and leakage environment on the leakage process was analyzed. The results show that the changes of flow field mainly focus on the inside of the leak hole and the inlet and outlet of the leak hole. With the increase of the leak aperture, the leakage quantity, leakage velocity, pressure and density inside the leak hole increase. The greater the pressure difference between tubing and oil jacket annulus, the greater the leakage amount and leakage velocity, and the more drastic the change of pressure and density. The gas velocity and pressure in the upper part of the annular protective fluid are greater than that in the annular protective fluid section.

To mitigate the risk of annular pressure buildup caused by solid-phase deposition in the B and C annuli of deep-water wells, experimental tests were conducted on sedimentation behavior using common deep-water drilling fluid systems. The sedimentation height and post-settling solid-phase permeability of various drilling fluids were measured. Based on the parameters of solid phase percolation characteristics, and considering the impact of annular fluid solid deposition, a predictive analytical method was established for annular pressure under percolation conditions. Case analysis was conducted to validate the approach. Results show that the sedimentation height follows the order: oil-based drilling fluid > EZFLOW drilling fluid > HEM drilling fluid. In contrast, the post-settling solid-phase permeability is ranked as EZFLOW drilling fluid > HEM drilling fluid > oil-based drilling fluid, with a maximum permeability of 2.216 μm². Under annular fluid solid-phase deposition conditions, reductions in annular fluid viscosity, increases in formation permeability, and longer open-hole cement sheath sections reduce fluid viscous resistance, enlarge the seepage contact area with the formation, and enhance fluid flow. Therefore, reducing drilling fluid viscosity and extending the open-hole cement sheath length can improve the pressure release capacity in the B and C annuli of deep-water wells. However, the presence of solid-phase deposition significantly restricts seepage flow rates compared to conditions without deposition, leading to a potential risk of incomplete pressure relief following solid-phase sedimentation.

With the development of global oil and gas exploration and development to deep and ultra-deep wells, the problems such as underground high temperature environment and unreasonable selection of drilling parameters in field operation make the bit wear increasingly serious. In order to prolong the bit life and improve the rock breaking efficiency, a 3D simulation model of polycrystalline diamond compact(PDC) cutters marble was established, and the effects of different cutting depth, cutting speed and bit caster on the PDC cutters surface temperature and rock breaking efficiency were analyzed. The results show that the temperature rise of the cutting gear can be divided into three stages: ascending period, transitional period and stable period, and the crushing form of the rock changes from plastic to brittle when the cutting depth increases to a certain extent. With the increase of cutting speed, both temperature and crushing work ratio increase. With the increase of cutting depth and bit caster, the crushing work ratio increases and the temperature increases first and then decreases. The response surface method was used to optimize the cutting speed, cutting depth and bit caster, and the optimal parameter combination was given. The research results can provide guidance for efficient rock breaking of PDC bit in field.

To enhance heat transfer efficiency and improve thermal exchange performance, a composite enhanced thermal exchange technology was explored that combined annular internal fins with protruding units, aiming to create an innovative thermal exchange structure. Through numerical simulation methods, the flow and heat transfer characteristics of this structure were studied within the Reynolds number Re range is 8 000~20 000. The analysis results indicate that the layout of the protruding units and four parameters (depth, radius, spacing, and quantity) have a significant impact on thermal performance. The mechanism of enhanced heat transfer was explained using field synergy theory. Under optimal parameters, with a depth of 2 mm, a radius of a specific value, a spacing of 20 mm, and six protruding units, the best thermal exchange performance is achieved, with an overall heat transfer performance improvement of 4.71%~23.59% compared to internal finned tubes. Increasing depth, radius, and quantity, while decreasing spacing, enhances heat transfer but also increases resistance, limiting the growth of overall thermal performance. Field synergy analysis shows that the structure promotes strong secondary vortices, significantly enhancing the synergy effect between the velocity field and the temperature field.

Medium-depth coaxial geothermal wells, as an efficient way to utilize geothermal energy, are now being vigorously promoted by many regions in China. In order to study its heat extraction performance and its influencing factors, COMSOL Multiphysics was used for modeling and orthogonal experimental analysis. The results show that the effects of all influencing factor on the heat extraction from geothermal wells are listed in the following order: ground temperature gradient, inlet flow rate, thermal conductivity of the backfill material, inlet temperature, and thermal conductivity of the inner tube. When designing geothermal wells, it is necessary to consider multiple factors to determine the optimal operating conditions. The radial temperature influence range of geothermal wells is about 10 m, which is a reference for the arrangement of multiple wells in the same area.

Serving as a clean and renewable energy source, wind energy plays a significant role in mitigating the increasingly severe energy crisis. However, the fluctuation and randomness of wind speed pose severe challenges to the stable operation of power systems. To address this issue, a combined short-term wind speed forecasting model named CEEMDAN-RIME-CNN-BiLSTM-AM was proposed, which was based on complete ensemble empirical mode decomposition with adaptive noise (CEEMDAN), rime optimization algorithm (RIME), convolutional neural network (CNN), bidirectional long short-term memory network (BiLSTM), and attention mechanism (AM). Initially, the CEEMDAN algorithm was applied to the original wind speed series to obtain a series of relatively stable sub-modes, thereby reducing the volatility of the wind speed series. Subsequently, the CNN hyperparameters were optimized using the RIME algorithm to establish the CNN-RIME model for adaptive extraction and mining of wind speed data. Then, the BiLSTM-AM model was employed to forecast the processed data. Finally, the forecasting results of each sub-series were superimposed to obtain the final forecasting result. A comparative experiment was conducted using an actual wind speed dataset from a certain location. The proposed model demonstrates good forecasting performance in both single-step and multi-step forecasting, providing a reference for scheduling plans to maximize energy utilization and power supply.

The dispatchable potential of charging stations represents the feasible solution space for optimizing their bidding strategies in the electricity market. However, the uncertainty in the access times of electric vehicles complicates the accurate assessment of this dispatchable potential. To address this issue, an uncertainty analysis method was proposed for evaluating the dispatchable potential of charging stations, taking into account the stochastic nature of electric vehicle charging times. Firstly, a generalized energy storage model for various types of electric vehicle clusters was established using Minkowski summation theory. Secondly, the impact of the randomness in electric vehicle arrival and departure times on the dispatchable potential of charging stations was analyzed. The discretized probability density functions of these times were mapped to the probability distributions of individual electric vehicle model parameters. By integrating these with the generalized energy storage model of electric vehicle clusters, the probabilistic characteristics of the dispatchable potential across various electric vehicle clusters were derived. Furthermore, the probability distribution characteristics of the dispatchable potential of charging stations were derived by aggregating the parameters of various electric vehicle clusters using convolution operations. Finally, simulations were conducted in MATLAB and compared with Monte Carlo simulations to validate the effectiveness of the proposed method.

In order to solve the fault line selection problem of single-phase high resistance grounding in resonant grounded distribution systems, a fault line selection scheme was proposed that utilized the disturbance characteristics of zero-sequence current before and after the neutral point parallel resistor was grounded. The zero-sequence fault model was established for the two conditions before and after the resistor paralleling with the arc suppression coil, and the zero-sequence current variation characteristics of sound and faulty lines were analyzed correspondingly. The amplitude of the zero-sequence current of any healthy line decreased after the neutral resistance was applied, while the current of the faulty line increased. Furthermore, a fault line selection criteria was constructed, which was used the amplitude disturbance characteristics of the zero-sequence currents. Simulations based on MATLAB verified the correctness and effectiveness of the proposed method. The results show that the proposed scheme is able to reliably detect single-phase ground fault with the resistance up to 5 kΩ.

The unmanned aerial vehicle (UAV) system, with its advantages of flexible deployment and line-of-sight propagation, has become an essential tool for assisting mobile communications in handling high-density data processing and emergency communications. However, the computational processing capabilities and endurance issues of UAVs under complex environments remain significant technological bottlenecks. The development of mobile edge computing (MEC) technology provides an effective solution to address UAVs’ computational and energy consumption challenges. A distributed task offloading strategy based on a multi-agent reinforcement learning algorithm was proposed for MEC-assisted UAV systems. The task offloading and resource allocation process of UAVs was modelled as a Markov game process (MGP) involving multiple MEC nodes. To solve the MGP problem, a distributed reinforcement learning algorithm for multi-agent collaboration was proposed. The algorithm enabled agents to find the optimal strategies through online collaborative learning based on local observation information. In comparative experiments, the convergence and system performance of the proposed scheme were evaluated. The results show that the proposed scheme outperforms the comparison schemes in terms of convergence speed, energy consumption, and unloading rate.

Shield tunnel construction impacts old buildings in urban areas. Extensive building deformation data was collected for Tianjin Metro Line 7’s shield tunnel passing beneath old buildings using automated measurement robots. Machine learning algorithms were applied to analyze the correlation between building instantaneous settlement and shield construction parameters such as average velocity, thrust, grouting volume, shield distance, and grouting pressure. A predictive model for building settlement was established. The results show that old buildings within -50~70 m are affected by shield construction. Differential settlement is significant, with noticeable differences on various facades. Grouting volume, thrust, and average velocity positively correlate with instantaneous settlement, with shield distance having the greatest impact. Reasonable construction parameters ensure building settlement and deformation remain within acceptable limits. The machine learning-based predictive model closely aligns with actual settlement curves, demonstrating robust predictive capabilities. This provides valuable insights for predicting and controlling surface settlement in future shield tunnel projects.

In order to solve the problems of missed detection and false detection in the current remote sensing image small target detection task, a SMCA+CSC+shape-aware intersection over union loss(SIoU)-you only look once(SCS-YOLO) remote sensing image small target detection algorithm was proposed. Firstly, in response to the problem of small and clustered targets in remote sensing images, a spatial multi-scale convolutional attention module(SMCA) was constructed to improve the model’s feature extraction ability of spatial and channel information. Secondly, in order to solve the problem that the semantic information of small targets was easy to be lost during deep network transmission, the aggregation subpixel convolution module concentrated sub-pixel convolution(CSC) was designed, and the multi-scale aggregation feature extraction method was used to enhance the ability of the network to extract semantic information. Finally, the SIoU loss function was used to replace the complete intersection over union loss(CIoU) loss function in the original model, which accelerated the convergence speed of the network. The average of the average precision(mAP)of the SCS-YOLO model reaches 97% and 90.9% on the RSOD and NWPU VHR-10 datasets, respectively, which is 2.2% and 2.7% higher than that of the original model, which shows the effectiveness of the method in the small target detection task of remote sensing images.

Due to the limitations of traditional ice force measurement methods in terms of stability and reliability, and the high sensitivity and anti-interference capabilities of fiber optic sensing technology was given, a fiber optic ice force sensor was developed. The effectiveness of this sensor was evaluated in the context of its application in marine structures. Based on the fundamental principles of fiber optic sensing technology and the design requirements of the ice force sensor, the research, design, and installation processes of the sensor were described in detail, including the design calculations of the elastic element, the selection and arrangement of the fiber optic sensors, and the construction of the data acquisition system to ensure that the precision requirements for ice force measurement were met. A winter field measurement of ice force was conducted at an observation station in the northern Bohai Sea. Field ice force data were successfully collected and analyzed, and the actual monitoring performance of the sensor was evaluated. The experimental results indicate that the system exhibits good stability and reliability in practical applications. The developed fiber optic ice force sensor provides a new reliable technical means for ice force measurement in marine engineering and lays a foundation for further research in structural health monitoring.

Modern air traffic management systems necessitate efficient and accurate identification and classification of hazard-related text data to ensure flight safety. Air traffic control hazard data encompasses information on potential factors, conditions, or events that may adversely impact aviation safety. Existing text classification methods face challenges due to the diversity of data categories and imbalances within classes. An enhanced ensemble model based on the Stacking framework, incorporating a dual-weighting mechanism was proposed for improved performance. A dual-protection strategy was implemented to categorize hazards and safety risks systematically. The methodology employed the term frequency-inverse document frequency(TF-IDF)algorithm to extract and vectorize features from preprocessed hazard texts. To address class imbalance, the synthetic minority over-sampling technique(SMOTE) and adaptive synthetic sampling approach(ADASYN)algorithms were utilized to generate synthetic samples for minority classes. The Stacking ensemble model was refined by dynamically weighting the F₁ scores derived from cross-validation of base learners and integrating a sensitivity assessment mechanism across the ensemble. Experimental results on the constructed dataset demonstrate that the ADASYN-enhanced ensemble model achieves notable improvements in precision, recall, and F₁ scores by 0.9%, 1.1%, and 1.0%, respectively, effectively mitigating overfitting in majority classes. The proposed algorithm significantly enhances the classification performance of imbalanced hazard text categories, contributing to the advancement of safety risk management in air traffic control.

Due to the complex underground environment, low lighting conditions, and the small size of hard hats, the detection results are not ideal. To address low-quality images in complex environments, an improved YOLOv7 for hard hat detection in low-quality images from underground coal mines was proposed. Firstly, addressing the limitation that image features were susceptible to noise interference under low-light conditions, a multi-scale MELAN module was introduced. By constructing a multi-scale attention mechanism, broader contextual information was captured, thereby enhancing feature extraction and effectively suppressing noise interference. Secondly, the OD-SMP module was constructed using soft pooling and full-dimensional dynamic convolution in the backbone network, which reduced information diffusion in feature mappings, retained more contextual information, and enhanced the detection capability for small targets. Finally, to address the varying quality of detection samples caused by the complex backgrounds and environments with different lighting and distances in underground coal mines, Wise-IoU was used as the loss function. Experimental results show that the average precision of the improved model is 94.9%, which is 13.5% higher than the original YOLOv7 model, demonstrating better detection performance.

Explicit content features of webpages are often unavailable due to distractions such as commercials, insufficient permissions, privacy protection, or deceptive disguises. To address the challenge of classifying webpages with severe content feature deficiency, a method combining graph embedding and extreme gradient boosting(XGBoost) was proposed. This method leveraged implicit relational features in webpage hyperlink networks for multi-classification. Firstly, a hyperlink network was constructed using relationships between webpages. Then, node features were extracted using graph embedding models, and statistical structural features such as clustering coefficients and PageRank values were concatenated to form dense feature vectors. Finally, ensemble learning models, including XGBoost, were trained to classify webpages for prediction. Experiments on a real Wikipedia dataset show that the Struct2Vec*+XGBoost approach achieves excellent classification results, with accuracy, precision, recall, and F₁-score metrics reaching 0.987 5, 0.965 9, 0.971 3, and 0.964 1, respectively. These results are superior to those of comparison models. The findings demonstrate the effectiveness of using implicit link-based features for webpage classification in scenarios with content feature deficiency.

With the development of urbanization, the number and scale of sewage treatment plants are increasing, and the effective collection of odor generated by them is of great significance to prevent odor leakage, protect the environment and reduce energy consumption. The influence of structural parameters (different tube bundle positions, different tube bundle numbers, different pipe diameters) and operating parameters (suction flow) on the internal flow field of the odor collection hood of a sewage treatment plant was studied by numerical simulation. The results show that when the tube bundle is placed at the very edge of the air collecting hood, the number of suction pipes is three, the diameter of pipe is 150 mm, and the suction flow range is 3.63 kg/s to 5.71 kg/s, the airflow structure in the cavity is the best, the odor concentration is the lowest, and the suction effect is the best.

In order to study the displacement characteristics of pile and anchor supporting deep foundation pit in seasonal frozen loess area, the horizontal displacement of pile top and pile body and the surface settlement outside the pit under different working conditions were compared by indoor scale model test. The results show that water migration and redistribution occur in the freeze-thaw cycle, and the existence of external water replenishment conditions will accelerate the water migration rate, which makes the displacement of supporting structure and the surface settlement outside the pit much larger than that in the excavation stage. The maximum horizontal displacement of pile top and pile body in the freeze-thaw stage under closed conditions increase by 6~8 times compared with that in the excavation stage, and the surface settlement outside the pit increases by 3 times. Compared with the closed freeze-thaw condition, the horizontal displacement of pile top and pile body increases about 1.4 and 1.2 times, and the surface settlement outside the pit increases 1.5 times. The research results can provide reference for the risk prevention and control of pile and anchor support deep foundation pit construction in this kind of seasonal freezing loess area.

Large section tunnel in-situ expansion excavation is prone to induce ground settlement, posing a threat to the service safety of surrounding structures. However, the settlement evolution of the overlying strata during tunnel expansion excavation are not yet clear. A method combining theoretical analysis, physical model testing, and engineering practice was adopted to investigate the settlement evolution of the overlying strata during expansion excavation of tunnels. A theoretical model for tunnel expansion excavation settlement was established. The research findings indicate that the settlement of the overlying strata above the tunnel exhibits a sudden increase characteristic, with the expansion excavation settlement zone showing a parabolic distribution, which is primarily related to the cohesive force of the rock mass and its brittle fracture characteristics. The strata settlement shows a nonlinear increasing relationship with the distance from the tunnel, mainly influenced by the non-uniform attenuation of excavation unloading disturbance. The theoretical model curves can reflect the settlement evolution consistent with the physical model tests, with an average deviation of 4.8% between the experimental and theoretical values. Considering the influence of the correction coefficient α for tunnel support on the measured engineering values, the model with α=0.7 and α=0.4 can better predict the range of surface settlement after tunnel expansion excavation and support. The research results provide a theoretical method for calculating strata settlement during tunnel in-situ expansion excavation.

A large amount of dredged silt is produced in Taihu Lake every year. In order to realize the resource utilization of solid waste, the feasibility of preparing dredged mud and attapulgite into vertical cutoff wall material was explored, and its impermeability was studied. The permeability resistance and micro-pore structure of dredged mud-attapulgite engineering cutoff wall materials were studied by flexible wall infiltration, water centrifugation and low field nuclear magnetic resonance test. The results show that with the increase of consolidation pressure, the proportion of small holes increases, the proportion of mesoporous holes decreases, the content of free water decreases, and the content of bound water is basically unchanged, and the porosity and hydraulic conductivity of dredged silt-attapulgite decrease gradually with the increase of consolidation pressure. At the consolidation pressure of 100 kPa, the porosity and hydraulic conductivity of the dredging silt-attapulgite cutoff wall material using zinc chloride and butyric acid as the contaminated permeate increase compared with the test using water as the permeate. The reason is that the addition of the polluted permeate reduces the small hole proportion, increases the mesoporous proportion, increases the free water content, and basically keeps the bound water content unchanged.

A numerical simulation of groundwater dynamics in the Sugan Lake Basin was conducted by using MODFLOW, and 50-year predictions were made for four different water diversion schemes. The results from MODFLOW simulations fit well with the measured data, indicating that the established model can be used for predicting the groundwater dynamics in the Sugan Lake Basin. The MODFLOW simulation results under different water diversion schemes reveal that over a period of 50 years, as the amount of diverted water increases, the shrinkage rate of the large Sugan Lake’s area also increases, and the groundwater level in the Sugan Lake Basin shows a general declining trend. The impact of inter-basin water transfer exhibits certain time lags and spatial heterogeneity. Considering both the water diversion requirements and the effects of the water diversion project on the ecological environment of the Sugan Lake Basin, it is suggested that a water diversion scheme of 1.0×10⁸ m³/a is more appropriate. The research results provide important scientific theoretical support for assessing the impacts of inter-basin water transfer projects on the ecological environment of the Sugan Lake Basin and for determining suitable water diversion schemes.

To gain a deeper understanding of the interaction between surface water and groundwater in the water cycle of the inland basins of the Hexi region in Gansu Province, and thereby a scientific basis was provided for water resource management, the interaction and scheduling impacts of surface water and groundwater in the Taolai River Basin using long-term hydrological data combined with the WEAP-MODFLOW model were analyzed. The results indicate that the simulated groundwater extraction volume (2.461×10⁸ m³) closely aligns with the actual extraction volume (2.5×10⁸ m³), with an error of only about 1%, validating the model’s effectiveness in simulating groundwater extraction. Under the projected water use scenario for 2030, without reservoir regulation, the surface water and groundwater supply volumes would be 3.840×10⁸ m³ and 1.982×10⁸ m³ respectively, revealing a certain groundwater imbalance issue. Changes in the storage capacity of the Taolai Gorge Reservoir significantly affect the surface water supply capacity, with increased storage effectively enhancing the regulation and supply capacity of surface water, thereby alleviating the burden on the groundwater system. Adopting a scheduling rule that prioritizes surface water use has a positive impact on groundwater balance, helping to mitigate pressure on the groundwater system and protect groundwater resources. Evidently, the Taolai River Basin exhibits significant variability in its hydrological cycle, and there are distinct differences in the hydrological characteristics between the Hongshui River and the Taolai River, highlighting the necessity for implementing regionalized water resource management strategies.

With the rapid development of railway networks in cold regions, frequent subgrade diseases are observed. To investigate the freeze-thaw characteristics and mechanical properties of subgrade soils in cold regions, a series of laboratory tests were conducted. The effects of moisture content, freezing temperature, and freeze-thaw cycles on soil behavior were systematically investigated. The experimental results indicate that the frost heave ratio and thaw settlement coefficient increase consistently with higher moisture content, lower freezing temperatures, and more freeze-thaw cycles. More pronounced moisture migration is observed under conditions of higher initial moisture content and higher freezing temperatures. The upper part of soil samples shows gradual moisture reduction while the lower part exhibits moisture accumulation with increasing freeze-thaw cycles. The freezing temperatures are measured as -1.96, -1.89, -2.17, -2.06 ℃ for initial moisture contents of 8%, 10%, 12%, and 14% respectively, with the lowest freezing temperature occurring at 12% moisture content. The strength variation ranges are determined as 3.63~6.15 MPa with increasing moisture content, 3.26~6.05 MPa with decreasing freezing temperatures, and 4.49~3.68 MPa with increasing freeze-thaw cycles. These findings are considered significant for ensuring the stability and safety of transportation infrastructure in cold regions.

Due to the unclear constitutive relationship between the structure and performance of styrene-butadiene-styrene block copolymer(SBS) modified asphalt, the current way to improve the performance of SBS modified asphalt is still to simply increase its SBS content. However, early pavement diseases are still frequent. To explore the effect of swelling degree of SBS on the rheological properties of modified asphalt and its internal mechanism without increasing SBS content. The microstructure of SBS modified asphalt was observed by fluorescence microscope. The conventional properties and rheological properties of SBS modified asphalt were analyzed by dynamic shear rheometer. The internal mechanism of the influence of SBS swelling degree on the performance of SBS modified asphalt was revealed by molecular dynamics. The results show that the fully swollen star-line blended SBS modified asphalt has a higher swelling area, and has obvious performance advantages in terms of conventional performance, rheological properties and anti-aging properties. Molecular simulation shows that the complete swelling of SBS makes the radial distribution function peak of SBS modified asphalt higher, which improves the interaction between SBS molecules and light components in SBS modified asphalt. On the basis of maintaining the original stable asphalt colloid structure, SBS styrene ends are interconnected to form π-π conjugate, which improves the toughness of SBS network.

To investigate the stress characteristics of the primary support in the shallow buried biased section of the tunnel in fully weathered granite strata. Based on the Xiangsishan Tunnel, laboratory tests were conducted to determine the mechanical parameters including cohesion and internal friction angle of fully weathered granite. The construction process was simulated by FLAC 3D numerical software for the shallow buried bias section of the tunnel entrance. To study the effects of varying ground slopes, tunnel depths, and soil-rock interface locations on the stress characteristics of the primary support structure. The results indicate that, under various impact factors, the axial force and bending moment of the primary support exhibit the distribution characteristics of “upper large and lower small”, while the safety factor displays the opposite trend. The internal stresses of the primary support are distributed asymmetrically as the ground slope increases. The positive bending moment shifts toward the deeper-buried side and gradually increases, while the negative bending moment and axial force increase at the arch waist on the shallow-buried side. When the ground slope reaches 40°, the safety factor of the primary support falls below the standard allowable value. However, the stability of the primary support can be enhanced by implementing multi-stage variable slopes. As the depth of the tunnel increases, the asymmetric distribution of internal stresses in the primary support decreases, while the overall magnitude of internal stresses continuously increases. When the soil-rock interface crosses the tunnel at various locations, the magnitude of the internal stresses in the primary support is significantly affected, whereas the distribution pattern remains relatively stable. The reliability of the stress characteristics of the primary support under various impact factors was verified through on-site monitoring of the stress variations in the steel arch and concrete at various locations of the tunnel.

The evaluation of expressway network resilience has been emphasized due to significant global emergencies. Utilizing complex network theory and the resilience triangle model, a dynamic system was developed to assess the comprehensive performance of nodes, incorporating local, global, and social attributes. A method for evaluating the resilience of expressway networks was proposed, consisting of four stages: initial, disruption, recovery, and stabilization. Six disruption and recovery strategies (node degree, eigenvector, betweenness, accessibility, social attributes, and random selection) were applied to analyze the network’s performance using three key indicators: the number of independent paths, network efficiency, and network connectivity. A topological map of the expressway network spanning the provinces of Shanxi, Shandong, Henan, and Hebei were constructed, and the resilience changes under various disruption and recovery strategies were analyzed. The findings indicate that in the initial stage, the expressway network exhibits a relatively high number of independent paths, suggesting robust anti-risk capabilities. During the disruption stage, network efficiency, the number of independent paths, and network connectivity decrease by 94.32%, 98.18%, and 99.63%, respectively, demonstrating the network’s ability to absorb disruptions. In the recovery stage, the accessibility restoration strategy, which results in the smallest resilience triangle area, exhibits the strongest resilience, whereas the random restoration strategy shows the slowest recovery rate, indicating that it should be avoided whenever possible. In the stabilization stage, network efficiency resilience is found to be superior to that of network connectivity and independent path resilience in the expressway network of the four provinces. It is recommended that urban nodes with higher degree values, such as Xinxiang and Puyang, be prioritized for protection to enhance the overall resilience of the expressway network.

Two schemes, hollow shaft and solid shaft were proposed for the cantilever high-speed rotor of a turbofan engine during the structural design stage. Based on the beam element finite element method, rotor dynamic analysis models with hollow shaft and solid shaft were established, and critical speed and vibration mode calculations were carried out. The calculation results show that hollow shaft structure is suitable for the rotor. Then, an analysis was conducted on the sensitivity of the unbalance response of a rotor with a hollow shaft to the unbalance amount at the characteristic position, providing a basis for the selection of balance surfaces in high-speed dynamic balance test. Finally, the dynamic characteristics test of the simulated rotor with hollow shaft within the full speed range and the high-speed dynamic balance test research at the working speed were completed. The rotor smoothly crossed the two orders bending critical speed and safely operated to the working speed, verifying the rationality of the rotor’s hollow shaft structure and dynamic design. Compared with the experimental results, the calculation error of the established finite element model is not more than 4.08%, which well reflects the dynamic characteristics of the rotor. After high-speed dynamic balancing, the deflection of the rotor at the working speed is significantly reduced, not less than 33.33%. The research results provide reference and technical support for the structural, dynamic design, and experimental research of real low-pressure rotors, and has important engineering value.

The identification of aviation accident risk factors through the system-theoretic process analysis(STPA) method is a qualitative analysis process that does not allow for a quantitative assessment of the extent to which each factor contributes to an accident. To address the above problem, a qualitative and quantitative analysis method combining STPA and Bayesian network (BN) was proposed. Taking the JetBlue A320 aircraft flap accident as an example, the control structure model of the flap control system was constructed by STPA method, and the potential unsafe control behaviors and related causal scenarios were analyzed comprehensively. Then, the results of STPA qualitative analysis were transformed into a Bayesian network model that could be quantitatively analyzed, so as to identify the internal interaction logic and the highly influential factors in the accident, and put forward comprehensive safety recommendations. The analysis results show that the main factor leading to the accident is the failure of hydraulic source, while the failure of power transmission unit (PTU) and the leakage of hydraulic line are the main causes of hydraulic source failure, with a critical importance of 0.688 and 0.299, respectively.

In order to solve the safety problems encountered when aircraft land and taxi on runway surfaces with accumulated water, three-dimensional random uneven half-runway surfaces with different flatness grades were established. The distribution of accumulated water in the landing strip under the influence of runway unevenness was used to investigate the accumulated water distribution characteristic matrix. Moreover, a theoretical model for aircraft landing and taxiing on runways with accumulated water was established, and dynamic simulations were carried out using the Simulink tool to analyze the impact of runways on aircraft landing performance under different accumulated water distribution conditions. The results show that compared with “good” (international roughness index, IRI=1), the landing distance of the runway with “poor” (IRI=5) increases by about 29 m, and the landing distance of the runway with “poor” (IRI=1) increases by 3.7% compared with the ideal smooth road. Moreover, the decrease of road smoothness would aggravate the risk of tire water skiing. If the ground speed of the aircraft is increased from 62 m/s to 82 m/s, the landing distance will directly increase by about 520 m, an increase of about 87%. When the rainfall intensity of 1 mm/min increases from 1 mm/min to 3 mm/min, the landing distance increases by 6.5 m and 7.4 m for each increase in rainfall intensity of 1 mm/min. It is concluded that at the uneven position of the pavement, the greater the grounding speed, the greater the speed when reaching the same position, and the greater the reduction of the adhesion coefficient of the position, up to 11.3%. With the increase of rainfall intensity, the adhesion coefficient decreases gradually. When the rainfall intensity reaches 3 mm/min, the adhesion coefficient decreases by about 20% compared with the dry pavement.

With the rapid development of the global aviation industry, airport ground operations management is increasingly challenging. Ensuring safety, improving efficiency, and reducing environmental impacts constitute critical tasks. To address this, a mixed-integer linear programming model incorporating taxiway conflict prevention was developed. This model aimed to minimize taxi time and CO₂ emissions through dynamic optimization with the non-dominated sorting genetic algorithm II (NSGA-II). Implementation was conducted in Python for a major Chinese hub airport, with results compared against the commercial optimizer Gurobi. Computational findings reveal a 17.46% reduction in total taxi time and an 18.35% decrease in CO₂ emissions across 14 aircraft. The NSGA-II solution is found to be within 1.083% of Gurobi’s optimal solution, while a 95.0% faster computation time is achieved. The capability of NSGA-II in handling large-scale multi-objective taxi path optimization problems is demonstrated. Operational efficiency is enhanced, and CO₂ emissions are significantly reduced by the proposed approach.

In order to effectively evaluate and control the operational risks of unmanned aerial vehicle(UAV), based on the summary of various risk factors of UAV ground impact, the possible causes of UAV ground impact were analyzed, corresponding control measures were determined, and a safety barrier model combining risk analysis and control technology was established. It can clearly display the logical relationship between the causes of UAV operation safety, mitigation measures and accident consequences. Bow-tie (BT) model was mapped to Bayesian network (BN), each element of BT model was quantified, and the probability of unsafe events was calculated. The results show that the model can clearly show the risk control process and effectively reduce the operational risk of UAV. It provides an efficient and practical method for the operational risk assessment and control of UAV.

In order to alleviate the collision risk of non-intersecting runways simultaneous operation, it is necessary to apply a control strategy conforming to the operation characteristics. A collision risk assessment model was constructed by using event tree analysis and Monte Carlo method. Based on event tree analysis, the event to be solved was determined. The probability of related events was calculated by Monte Carlo method. By statistical and fitting the collision event data obtained by the experiment, the safety target level was standardized and the control strategy was put forward. Finally, taking the approach of 01L and the departure of 29R on the non-intersection runways of Daxing Airport as an example, the departure shielding window (0.41~7.39 km) was obtained. Using this strategy, the risk of aircraft collision can be controlled at an acceptable level. The proposed computational model of departure shielding window is of general applicability to the formulation of safe operation control strategies for non-intersecting converging runways.