Machine learning technology is a hot research topic at present. It is widely used in various prediction, recognition and classification tasks with its strong learning ability and high versatility. The application of machine learning in computational structural mechanics was discussed, with emphasis on its role in material property prediction, structural damage analysis, improvement of traditional methods, constitutive equation establishment and differential equation solving. Through literature review, the advantages of machine learning algorithms such as neural networks, support vector machines and random forests in improving computational efficiency and design process optimization were summarized. It is pointed out that the combination of machine learning and classical computing methods provides a new way to solve engineering problems. Future research will focus on algorithm optimization, model improvement and interdisciplinary technology integration.

Long-term stockpiling of coal fly ash releases a large amount of toxic and hazardous substances, posing a threat to the soil and water environment. In order to have a comprehensive understanding of the research progress in this field, a bibliometric method was conducted to systematically and deeply visualize and analyze the relevant literature in CNKI and Web of Science databases from the period of database construction to 2023. The results show that the annual total number of publications in this field is generally on the rise. Among them, Chinese scientists have conducted a substantial amount of research in this field, accounting for the highest publication volume, which makes up 18.87% of the total, providing important scientific foundation for subsequent studies. The betweenness centrality of publications from the United States (0.51) is significantly higher than that of other countries, and its research results have greater international influence. The research hotspots focus on contaminants like heavy metals in coal fly ash, investigating their leaching and release patterns under various conditions, and revealing the environmental impacts of contaminants migration from coal fly ash landfills. Based on high-frequency keyword analysis, the composition of contaminants in coal fly ash and the types of contaminants potentially released into the water environment were examined. A systematic review and analysis of contaminants release mechanisms, release regularity, key influencing factors, and the migration regularity of mechanisms in environmental media were conducted. Future research should further focus on the release of heavy metals such as Pb, Cr, and Hg, trace elements like As, Se, and Mo, and specific mechanisms such as F^-, Cl^-, and $\mathrm{SO^{2-}_{4}}$, $\mathrm{PO^{3-}_{4}}$ during the coal fly ash stockpiling. Studies should explore the release characteristics of these mechanisms under complex environmental conditions, investigate whether synergistic or inhibitory mechanisms exist between various factors, and establish quantitative relationships between mechanisms indicators in the solid phase of coal fly ash and their release into water environment. This will provide a theoretical basis for scientifically evaluating the environmental impacts of coal fly ash and effectively preventing potential threats to water environment.

In order to investigate the vortex characteristics and wave propulsion generated by the undulating pectoral fins of the flatworm, a simplified model of the flatworm's pectoral fin was re-established using the linear interpolation method in MATLAB. The relationship between thrust and kinetic energy, during the flatworm's swimming was derived, and the undulating posture of the flatworm was simulated using Fluent software. The results show that compared to similar MPF propulsion fish species such as rays and cownose rays, the flatworm, due to its narrow and elongated body structure, exhibits better stability, adaptability, and flexibility in water. When the Reynolds number is set to 1.05×10⁵, the pectoral fins of the flatworm demonstrates more stable thrust, effectively reducing flow separation and turbulence effects. At a frequency of 0.6 Hz and a wavelength of 2.5 m, the pectoral fins displays optimal undulating parameters, enhancing fluid mixing and energy transfer efficiency, thereby improving the flatworm's propulsion performance. It is concluded that, during the mid-phase of an undulation cycle, the pressure distribution on the pectoral fins changes significantly, with the lift efficiency being highest at the peak of the undulation.

On December 18, 2023, a M_S6.2 earthquake occurred in Jishishan County, Gansu Province, marking the largest earthquake recorded in the area since seismic observations began. To investigate the practical application of interferometry synthetic aperture radar(InSAR) technology in monitoring surface deformation in Jishishan County and its surrounding areas before and after the earthquake, 13 C-band Sentinel-1A SAR images covering the earthquake event and study area were utilized. D-InSAR and SBAS-InSAR techniques were employed to process the data, obtaining surface deformation information along the radar line of sight before and after the earthquake, and a comparative analysis of the deformation rates before and after the event was conducted. The results show that the monitoring results of the two techniques show a bulge phenomenon centered in Liugou Township (the epicenter), which gradually expands outward in an elliptical shape, and then evolves into irregular subsidence. The maximum line-in-line shape variables before and after the earthquake are 41 mm and 16 mm, respectively. The overall deformation of the whole region after the earthquake is relatively stable, which is consistent with the relevant data. The D-InSAR and SBAS-InSAR technologies can be used to monitor the long-term surface deformation process and abnormal conditions before and after earthquakes, and provide effective support for quickly obtaining the distribution range of coseismic geological disasters and guiding post-earthquake emergency rescue and post-disaster recovery and reconstruction.

Seasonal deltas are deltaic sedimentary systems controlled by seasonal rivers in continental basins. Modern seasonal deltas are mainly developed in arid and semi-arid climate with gentle topography. However, the study on the sedimentary model of seasonal deltas in ancient sedimentary records is still insufficient. Suweiyi Formation in Tabei area, Tarim Basin was selected as the research object. Based on 63 logging data and 215.52 m core data in the study area, logging facies templates of different sedimentary microfacies and lithofacies type combination templates were established, and the vertical evolution law of sedimentary facies plane characteristics was analyzed and summarized, and the overall sedimentary model of the study area was established. The results show that the Suweiyi Formation in Tabei area developed 4 categories and 17 subtypes of rock facies. During the depositional period of the lower Suweiyi Member, seasonal shallow water braided river deltas were developed in the study area. A seasonal shallow meandering river delta with multiple flood events and retrograde accumulation developed in the north of the study area during the sedimentary period of the upper Suweiyi Member. Finally, the profile and single well sedimentary model of seasonal shallow water delta affected by factors such as accommodable space, frequent change of sedimentary base level and sudden events were established. The results provide a reference for further understanding of the seasonal shallow water delta depositional model under the background of arid climate, and also provide geological basis for lithologic trap exploration.

The high-altitude & dense-vegetation landslide is difficult to investigate and lack of data, its appearance and subsurface information also difficult to get. Therefore it is difficult to identify and threat the road greatly. A case study of the Xiaojiapo landslide was presented. Detailed on-site geological surveys were performed, and drone-based oblique and orthophoto imaging techniques were employed to get the landslide's characteristics. Historical deformation of the landslide was analyzed using satellite image, airborne LiDAR was used to collect point cloud and digital imagery data of the landslide surface. A digital elevation model and centimeter-level three-dimensional model of the landslide surface were created following vegetation removal to assess the surface characteristics. The combined investigations reveal that the Xiaojiapo landslide is situated at an elevation of 3 030 m with a vegetation coverage reaching up to 90%. It is a typical landslide with high-altitude and dense vegetation. The key internal factors contributing to the landslide including the unique alpine valley topography, the slope structure with advantageous free faces, and easily erodible geological layers. Precipitation induces internal water infiltration, which reduces the strength of the rock and soil mass. Additionally, freeze-thaw cycles further diminish slope strength, while earthquakes and road constructions disturb the internal structure, weakening it further. These combined internal and external factors drive the landslide deformation. This study offers technical insights for the landslide identifying, early-warning, and mitigation of road landslides in high-altitude regions with dense vegetation.

The terrain in western Sichuan is complex and varied, and the geological structure is active, which makes the construction and maintenance of the traffic trunk line face the challenge of frequent geological disasters. Ensemble learning algorithm can optimize the shortcomings of the algorithm in geological hazard susceptibility assessment and improve the accuracy of the model, which has significant advantages in geological hazard susceptibility assessment. Taking the riverside high-speed as an example, 12 feature variables such as slope and relief were selected to construct the geological hazard susceptibility evaluation system. The forecasting performance of the modeling of the integrated algorithm and a single algorithm was compared and analyzed. The main control factors of the geological disasters along the riverside high-speed were discussed and the practicability of the model was verified. The results show that the proportion of high and extremely high geological hazard prone areas along the Yangtze River high speed is 18.21% and 9.85%, respectively, which are concentrated in the Leibo section and Jinyang section. The area under curve (AUC) of the receiver operating characteristics (ROC) curve and the precision-recall (P-R) curve in the integrated model. The AUC of ROC curve (0.84~0.86), the AUC of P-R curve (0.81~0.85) and the F₁ score (0.78~0.79) of the three single machine learning models are significantly higher, and the prediction performance is better than that of a single machine learning algorithm. The development of high-speed geological hazards along the Yangtze River is controlled by topographic and geomorphic factors. The new damage points are located in the highly prone areas of the model, which verifies the accuracy and reliability of the Stacking model.

Recently, the vessel-shaped aquacultural farm has received much attention from the academia and industry because of its importance in promotion and sustainability of marine fishery. Polluted surroundings unsuitable for fish growth are always introduced by traditional multiple point mooring system. Therefore, single point mooring system is more suitable for the aquacultural farm. In recent years, mooring scheme optimization and performance assessment was frequently investigated in most existing literature, while studies on design of the single point mooring system are rare. Based on the requirement of reducing hull reconstruction, an external turret single point mooring system was proposed, which is composed of the turret device, the mooring anchor, the truss structure and the bearings. And their working principle were also clearly illustrated. Then, three dimensional potential theory was applied to obtain the hydrodynamic coefficients of the ship by use of the software AQWA. Finally, in order to verify the positioning ability of the mooring system under both operational and survival conditions, the direction of wind, wave and current was combined according to the rules, and time-domain coupling analysis of the farm-mooring system was carried out. From the numerical results, it can be seen that yaw, relatively large sway and roll motions will be induced due to different direction of the wind, current and wave. The mooring line tension is adequate and safe under all conditions, indicating that this proposed single point mooring system exhibits good positioning performance.

Soil seed banks serve as the foundation for plant restoration and succession, playing a crucial role in sustaining biodiversity and ecological balance. The effect of short-term enclosure and grazing ban on soil seed bank was studied in the marsh meadow of Napahai Lake in northwest Yunnan Plateau. Through field sampling and seed germination identification, the effects of grazing and short-term confinement (3 years) on species composition, diversity and functional group structure of topsoil seed bank were compared. The findings show that short-term grazing exclusion significantly alters the diversity of the soil seed bank, reducing the Shannon-Wiener and Pielou indices (P<0.05) and increasing the density of sedge seeds (P<0.05). Weeds dominate in both enclosed and grazed conditions, with grasses and sedges following, and legumes being minimal. The percentage of weed species decreases, while that of sedge species increases under grazing exclusion, with no significant change observed in grasses and legumes. Weed importance values are significantly negatively correlated with grass and sedge importance values (P<0.05), and grass density is significantly positively correlated with sedge density (P<0.05). These results indicate that while short-term grazing exclusion reduces the diversity of the soil seed bank in swamp meadows, it also enhances the replenishment and recovery of sedge seeds, offering new insights for the restoration management of wetland ecosystems.

The laminectomy robot is an auxiliary surgical robot developed for laminectomy in recent years. In order to explore the differences in reducing orthopedic surgeons' mental workload between laminectomy robot techniques and traditional laminectomy methods, a multimodal evaluation incorporating an electrocardiogram, eye tracking, and the NASA-TLX scale was utilized to assess the mental workload of orthopedic surgeons undergoing both surgical procedures. Through simulated surgical trials, 12 orthopedic surgeons performed laminectomies employing both the robot-assisted and the conventional techniques, collecting multimodal data for both variance and correlation analyses. The findings indicate significant differences in subjective mental workload between the laminectomy robot and traditional techniques (P<0.05). However, in terms of electrocardiogram indicators such as average heart rate, the low frequency/high frequency ratio (LF/HF), and the standard deviation of NN intervals (SDNN), no significant differences are noted. Significant differences are observed in eye movement indicators, including pupil diameter (P<0.05), fixation rate (P<0.05), and saccade rate (P<0.01). Further correlation analysis underscored a notably significant relationship between pupil diameter and levels of subjective mental workload in both surgery techniques. In conclusion, compared to traditional laminectomy methods, the use of laminectomy robots can alleviate the mental workload on orthopedic surgeons, with both pupil diameter and subjective mental workload levels providing effective reflections of the orthopedic surgeons’mental workload.

In order to explore the relationship between the ratio of non-high-density lipoprotein cholesterol to high-density lipoprotein cholesterol (NHHR) and the risk of rapid decline in kidney function, data from the China health and retirement longitudinal study (CHARLS) conducted in 2011 and 2015 was utilized. It includes 4 055 participants aged 40 and above with a baseline estimated glomerular filtration rate (eGFR) of at least 60 mL/(min·1.73m²), calculated using serum creatinine and cystatin C levels. Rapid kidney function decline is defined as a decrease in eGFR of 3 mL/(min·1.73m²·a). A multivariable logistic regression model was used to investigate the association between NHHR and the risk of rapid kidney function decline. Additionally, restricted cubic spline and threshold effect analyses were used to evaluate the dose-response relationship. The results show that over the 4-year follow-up, 447 participants (11.02%) experienced rapid decline in kidney function. In the fully adjusted multivariable logistic regression model, those in the highest NHHR group (T3) faced a 1.94-fold increased risk of rapid kidney function decline compared to the lowest NHHR group (T1) (OR=1.94,95%CI:1.46~2.61). As a continuous variable, each unit increase in NHHR is associated with a 1.21-fold increase in risk (OR=1.21, 95%CI:1.08~1.36). The restricted cubic spline analysis demonstrates a near logarithmic curve saturation effect between NHHR and rapid kidney function decline (P_nonlinearity<0.05). It is concluded that with NHHR ≤3.52, the risk increases as NHHR rises, while NHHR >3.52 marks a saturation point. In conclusion, among middle-aged and elderly individuals, a higher NHHR is linked to a greater risk of rapid decline in kidney function, displaying a nonlinear relationship.

To address the current situation of low flatness, poor cutting quality and cane bud damage at the cane cutter due to insufficient optimization of the structure and motion parameters and installation coordination of the cutting tool of the cane seed cutter. Finite element cutting simulation tests were conducted using single-factor tests on the distance between the cutting edge and the pivot point of the transport roller, tool drop speed, tool installation offset angle, tool front angle and tool back angle of the cane seed cutter to determine the evaluation indexes affecting the cane seed cutting quality and the trend of the influence of each factor on this index. The significant interaction effect of each factor on the evaluation index was analyzed based on the rotating orthogonal test, and the quadratic polynomial regression model of the orthogonal test results was obtained. Combining the agronomic requirements with the cutting characteristics of the tool, the optimal evaluation index was established, the optimized optimal combination of parameters was obtained, and the cutting section simulation test and bench validation test were conducted. The final selection results are as follows: the distance between the incision and the fulcrum is 177.944 mm, the tool landing speed is 1.569 m/s, the tool installation offset angle is 5.923°, the tool front angle is 10.899°, and the tool back angle is 8.637°. The equivalent stress at the incision site and the sugarcane shoot site are 5.053 mm and 1.592 MPa, respectively. The comprehensive analysis error rate is 4.97%. This study can provide a research basis for the optimization of the structure parameters and installation parameters of sugarcane seed cutting knife and its motion parameters, so as to improve the seed cutting quality of cane.

Buried pipeline is an important part of oil and gas transportation. The subsidence of gob area will cause the corresponding subsidence of the pipeline passing through the gob area, resulting in pipeline deformation, fracture and other accidents. Taking Puxian-Hejin pipeline crossing coal mining subsidence area as the research background, 3D printing technology was used to make up for the mismatch in mechanical similarity between pipeline simulation materials and geotechnical simulation materials, and the coupling simulation experiment between pipeline and rock and soil was constructed. The mining response of buried pipeline caused by coal mining was analyzed, and the correlation between pipeline movement deformation and stratum movement deformation was established. The research shows that the buried pipeline and the underlying rock strata do not synchronously settlement, resulting in delamination between the overlying rock strata and the underlying rock strata. The pipeline bends and deforms under the overlying rock load and its own weight. When the delamination span is large enough, the bending tensile stress on the bottom of the pipeline exceeds the allowable stress, resulting in tensile failure. The subsidence value of the buried pipeline is about 1.21 times of the formation subsidence value, and only 18% of the horizontal deformation of the formation is transmitted to the pipeline. The research results have guiding significance for the safe laying and daily maintenance of pipelines in subsidence area.

Oil-based drilling fluids, favored for their superior stability and inhibitive properties in complex deep oil and gas strata, is constrained by a scarcity of efficient materials for leak prevention and plugging, thereby limiting their utilization. In response to this challenge, a homogenous and stable polymer, SMHDVD, was synthesized via solution polymerization, using acrylate monomers as the primary chain and incorporating functional monomers that offer resistance to high temperatures and enhanced bonding with the formation. The impact of different concentrations (0.1%, 0.3%, and 0.5%) of the crosslinking agent divinylbenzene on the polymer SMHDVD was also investigated. In-house plugging experiments have shown that SMHDVD significantly contributes to the plugging efficacy of oil-based drilling fluid systems, with a maximum reduction in cumulative drilling fluid loss of up to 68.7%, surpassing the performance of conventional plugging materials. It was observed through comparative studies that the incorporation of a crosslinking agent diminishes the sealing capacity of SMHDVD, and an increase in the crosslinking agent's concentration leads to a decline in the polymer's plugging performance. The polymeric plugging agent developed in this research offers a novel perspective for the prevention of oil-based drilling fluid leakage, with promising prospects for practical field application.

In China's shale gas exploration and development, skid-mounted equipment is typically used due to its ease of disassembly, transportation, and reassembly. This equipment is often operated in high-pressure and high-temperature environments. As a result, faults are more likely to occur. To prevent production accidents and eliminate safety hazards, regular monitoring and fault diagnosis of skid-mounted gathering and transportation equipment are essential. Only relatively independent and discrete fault information is typically provided by conventional fault diagnosis methods. The relationships between faults are not uncovered. In response, a two-stage association analysis technique was proposed to analyze fault data from shale gas gathering and transportation skid-mounted equipment. The relationships between faults and defect type distributions were identified, providing valuable guidance for equipment maintenance and process optimization. It has been demonstrated through experiments on real data that the method proposed accurately identifies the relationships between defect locations and the distribution of defect types in skid-mounted equipment. A new solution is provided for the preventive detection and optimized design of gathering and transportation skid-mounted systems.

Aiming at the problem that it is difficult to directly use external heat sink to dissipate heat for high-power electronic devices with short-time operation in external insulation condition, the phase-change material with low melting point and high volume enthalpy value was adopted to optimize the design of energy storage structure and realize temperature control for electronic devices. Firstly, based on the constraints of electronic device volume, weight, external environment, thermal power, working time, etc., combined with the thermal performance of phase change materials, an integrated design of heat dissipation structure was carried out. Secondly, according to the characteristics of phase change material(PCM), an equivalent specific heat capacity thermal analysis method based on temperature feedback was proposed. Finally, the thermal conductivity of three PCM including paraffin, carbon composite and liquid metal, was analyzed by numerical simulation, and the heat dissipation performance of the three PCM in specificenergy-storage structures was evaluated by using heat source temperature rise and temperature equalization as indicators, and an optimal phase-change energy-storage structure of the electronic devices was determined. The results show that the PCM can significantly control the temperature rise in a certain period of time, which meets the temperature control requirements of electronic devices in small volume and external adiabatic environment. The volume enthalpy of PCM represents the energy storage capacity per unit volume of PCM. The higher the volume enthalpy, the smaller the volume of PCM required. Liquid metal can obtain better thermal properties because of its large enthalpy and high thermal conductivity.

The non-lethal electric shock weapon is a research hotspot in the field of non-lethal weapons. In recent years, the research on wireless long-range electric shock bullets has become a key issue within this field. Therefore, aiming at the design of non-lethal long-range low-velocity electric shock bullet empennage, three airfoils of Clark Y, Eppler 387 and NACA-66 with good aerodynamic characteristics at low velocity were selected. The simulation results of NACA0012 airfoil at 30 m/s using CFD software were compared with the literature simulation results and wind tunnel test results to verify the algorithm's effectiveness. Subsequently, the aerodynamic characteristics of the three airfoils at low velocity were simulated, and the lift coefficient, drag coefficient and lift-drag ratio corresponding to different angles of attack at 30, 35 and 40 m/s were obtained respectively. The results show that at the same flight velocity, the lift coefficient and drag coefficient of the three airfoils gradually increase with the increase of the angle of attack, but the growth rate of the lift coefficient gradually decreases, and the growth rate of the drag coefficient gradually increases. The lift-to-drag ratio increases first and then decreases with the increase of the angle of attack. After comparison, it is found that the aerodynamic performance of the airfoil Eppler 387 is better than that of the other two airfoils. The velocity of 40 m/s and the angle of attack between 4° and 6° are the best working conditions, which can not only meet the structural design requirements of non-lethal long-range low-velocity electric shock bullets, but also produce less drag while providing as much rolling moment as possible.

To achieve the integration of renewable energy utilization and CO₂ emission reduction technology, high-temperature gas field geothermal resource extraction was conducted via the CO₂ plume geothermal system, which merges the benefits of CO₂ sequestration with deep geothermal resource development, facilitating the concurrent sequestration of CO₂ during thermal extraction. Taking a high-temperature gas field as the target thermal storage, a three-dimensional thermal flow coupling model of cap rock thermal storage bedrock was constructed using COMSOL software to analyze the thermal compensation effect of the rock mass on both sides of the thermal storage and the relationship between the number of production wells and the system's thermal recovery performance. The findings indicate that during the advanced phases of the plume geothermal system's operation, when thermal compensation is considered, the fluid's temperature decline rate diminishes, resulting in an enhanced heat extraction rate and a greater heat extraction resource, while the thermal storage extraction degree is reduced, thereby extending the system's operational lifespan. It was discovered that increasing the number of production wells resulted in a smaller production fluid temperature decline. The operation of a CO₂ plume geothermal system demonstrates that the thermal compensation effect of cap rock and bedrock on thermal storage, along with an increase in the number of production wells, can extend the system's lifespan, offering theoretical insights for the optimisation and practical implementation of CO₂ plume geothermal systems in the future.

Second order selective harmonic repetitive control(SOSHRC) strategy with good frequency adaptability and dynamic performance, is widely used in grid-connected inverter control. To address the problems of the traditional SOSHRC strategy, such as the difficulty of using the stability analysis method and the conservative stability criterion, a novel second order selective harmonic repetitive control and proportional control(SOSHRC-PC) was proposed. Firstly, the structure and principle of the novel SOSHRC were designed, the novel SOSHRC-PC control strategy was introduced. Then, the stability and parameter design methods of the novel SOSHRC-PC controller were analyzed. Finally, a three-phase grid-connected inverter based on the novel second-order (6k ± 1) harmonic repetitive control and proportional control was constructed, and the simulation results show that the proposed control strategy has great steady state and dynamic performance.

The reactive power optimization and reconfiguration of traditional distribution network are mostly studied separately, lacking the coordination and cooperation of different optimization techniques. A mathematical model of reactive power and reconfiguration collaborative optimization of active distribution network was established. Combined with the two optimization methods of reactive power optimization and reconfiguration of distribution network, the coordinated operation of the two was realized according to the actual situation of distribution network. Taking the minimum annual comprehensive cost as the objective function, the improved grey wolf algorithm was used to solve the problem under the constraints of network power balance, node voltage amplitude and network radial operation. Aiming at the problems of low population diversity, easy to fall into local optimal solution and slow running speed of traditional grey wolf algorithm, it is proposed to increase the explosion mechanism of fireworks algorithm on the basis of grey wolf update strategy. At the same time, in order to improve the computational efficiency and solution accuracy, the fireworks algorithm was used for integer solution optimization, and the nonlinear programming algorithm was introduced to optimize the continuous solution. The IEEE33 node distribution network was taken as an example to verify four different scenarios. The results show that the proposed collaborative optimization model can effectively reduce the network loss and annual comprehensive cost, suppress the node voltage fluctuation level, and show the superiority of the improved algorithm in convergence speed and calculation accuracy.

Aiming at the problem that the unordered charging of large-scale electric truck (ET) increases the peak load of the grid and affects the power quality, a cluster division and two-tier optimal scheduling strategy for peak load balancing scenarios were proposed. Firstly, the demand response model of ET participating in power grid peak regulation was established considering real-time road flow and multi-energy consumption factors. With logistics factors as characteristic quantities, ET was divided into day-ahead clusters by an improved fuzzy clustering algorithm. Secondly, based on the clustering results, combined with the different interests of power grid dispatching and enterprise users, a two-tier scheduling model was established under the framework of master-slave game considering the flexible time window to solve the charging and discharging power of pure electric heavy duty card in the cluster in real time. Finally, particle swarm optimization based on Kriging model was used to speed up the solving of the model. The simulation results of ET data in a logistics area show that the two-tier scheduling strategy based on cluster division and flexible time window can better smooth the load curve and reduce the scheduling deviation of clusters. At the same time, Kriging optimization algorithm is more fast in solving the two-tier optimization model.

An adaptive predefined-time prescribed performance backstepping fault-tolerant control strategy is presented based on radial basis function (RBF) neural networks, event-trigger mechanism and hysteresis quantizer for the attitude control problem of quadrotor unmanned aerial vehicle (UAV) with actuator faults. Firstly, the dynamic model of the quadrotor UAV system was constructed, and the attitude model was reconstructed by incorporating the actuator fault model. Secondly, by designing a class of time-varying functions, the error variables required for backstepping control were transformed. Thirdly, the nonlinear function approximation capability of RBF neural networks was utilized to estimate derivatives of virtual control laws and the actuator fault with unknown parameters. Finally, to reduce the update frequency of the actuator, a combination of event-trigger mechanism and hysteresis quantizer was used to design the control input. Stability of the closed-loop system was demonstrated through Lyapunov stability theory. The effectiveness of the proposed algorithm was verified through MATLAB. It is concluded that the designed event-triggered quantized controllers have a lower update frequency compared to controllers designed using only event-triggered techniques.

In the intersection scenario, the running state of social vehicles, the control state of traffic lights and the accurate identification of track components have become the technical bottlenecks restricting the promotion and application of track inspection robots. Aiming at the requirements of track health inspection, firstly, the vision inspection system of the track inspection robot and the technical scheme of the navigation system was presented based on “Beidou +5G”. Secondly, the vision detection system model was built based on YOLOv8 algorithm, and the web crawler technology was innovatively used to capture sample data about traffic lights and car taillights from open source video resources to train the vision detection model. Then, transfer learning method and early stop method were used to optimize the detection accuracy of the trained model. The research results show that after adopting YOLOv8 algorithm and optimizing the model with transfer learning method and early stop method, the inspection robot can effectively detect the track components, vehicles and traffic lights at the switch junction, and effectively improve the inspection efficiency and accuracy.

To solve the problem that the wire rope swing angle is too large during the load lifting and lowering process of the bridge crane, a fuzzy layered sliding mode control method was proposed with the single pendulum model of the bridge crane as the research object. The method firstly establishes the bridge crane single pendulum model system, designs the two-layer sliding mode surface joint control based on traditional sliding mode control, combines the layered sliding mode surface with fuzzy control to create the controller, proves the Lyapunov stability of the closed-loop system of the bridge crane under the method through theory and carries out simulation experiments. The simulation results show that compared with the LQR controller and the multi-sliding mode controller, the trolley arrives at the desired position in 68% less time, and the maximum swing angle of the load is reduced by 15%, which achieves a good anti-swing effect.

Aiming at the problems of nonlinearity, large delay, uncertain model parameters and weak anti-interference ability in the temperature control system of variable air volume air conditioning supply air, a closed-loop control system of supply air temperature based on active disturbance rejection control (ADRC) was designed. In order to overcome the difficulty in parameter adjustment of active disturbance rejection controller, an improved grey wolf optimization (IGWO) algorithm was proposed to optimize controller parameters. By introducing chaotic mapping, nonlinear convergence factors, dynamic weights and dimensional learning strategies into grey wolf optimization (GWO), the population diversity was increased and the balance between search and exploitation was taken into account. The advantages and feasibility of the proposed algorithm were verified by MATLAB simulation. The experiment further proves that compared with the traditional proportional integral derivative (PID) controller and the traditional gray wolf algorithm, the IGWO algorithm can shorten the supply air temperature overshoot by 45.3% and 8.9%. The adjustment time is reduced by 34.8% and 11.2%, the steady-state error is smaller, and the system is more energy efficient.

The Unmanned aerial vehicles three-dimensional path planning problem is a combinatorial optimization problem to find the optimal path between the starting point and the endpoint in complex three-dimensional environment, but most path planning algorithms struggle to find feasible paths within acceptable time and precision range, therefore, a dynamic multi-subswarm salp swarm algorithm based on K-means++ clustering optimization was proposed to address the aforementioned issue. Firstly, a new cost function incorporating height cost was proposed within the three-dimensional environment model. The path planning problem was converted into a multi-dimensional function optimization issue. Secondly, the population was clustered using the K-means++ clustering algorithm, and a dynamic multi-subswarm mechanism was designed to balance the algorithm's global search and local exploitation. Each subswarm collaborates with multiple strategies for improvement, avoiding the algorithm from being trapped in local optima while enhancing global optimization capability. Finally, after validating the algorithm against five algorithms ISSA, MSNSSA, IBSO, MBFPA, and SSA using 12 CEC2017 benchmark test functions, it was applied to solve the optimal path planning problem in three-dimensional environments. Simulation results under different environmental models demonstrate that the algorithm's average effective path rate is increased by 15.5%, 11%, 23%, 20.5% and 18% compared to the other five algorithms, confirming its excellent optimization capability in complex environments.

Existing voice-driven facial generation methods still face challenges in feature extraction and generation quality, and have yet to fully explore the deep correlation between audio and facial features. To address above mentioned issues, a research approach that combines Mel frequency cepstral coefficients (MFCC) was proposedfor audio feature extraction with the image generation capabilities of the second generation of style generative adversarial networks (StyleGAN2) was proposed. In terms of audio processing, MFCC was employed as the feature extraction method. To more effectively extract and transmit features from the audio, a ResNet18-based residual module was designed and integrated with the squeeze-and-excitation (SE) attention mechanism. Additionally, the activation function in the original residual blocks was optimized and improved by using the Mish activation function, aiming to mitigate the gradient vanishing problem in deep networks, maintain the integrity of feature information, and enhance the accuracy and generalization ability of the model. The StyleGAN2 model was then utilized as the facial image generation model. Experimental results demonstrate that the integration of the designed audio processing network with the StyleGAN2 facial generation model exhibits outstanding performance in the task of voice-driven facial generation. Through comprehensive evaluation using metrics such as Fréchet inception distance (FID) and path length, the proposed method shows a significant improvement in generation quality compared to existing methods, thus fully proving its effectiveness and superiority.

An algorithm has been proposed to detect small targets in unmanned aerial vehicle(UAV) aerial images. The algorithm is based on an improved real-time detection Transformer (RT-DETR) and aims to address the challenges posed by complex backgrounds and a large number of small target samples. To enhance the feature fusion network, a dedicated feature fusion structure for small targets has been incorporated, utilizing rich location information from the shallow feature map to improve the network's ability to detect small targets. Furthermore, the last residual block in the BackBone has been removed to prevent an increase in additional parameters. Additionally, the MCP Block, a reconstructed BasicBlock structure in the backbone network, has been designed, which includes a multi-channel feature partial convolution module (MCPConv) to reduce redundancy in channel features and enhance the acquisition of multi-scale detail features. Moreover, a location encoding mechanism with learning ability has been introduced to obtain more accurate and expressive location information. The normalized weighted deviation(NWD) and mean precision-driven IoU(MPDIoU) positioning loss functions have been incorporated to accelerate the convergence speed of the model and reduce sensitivity to position deviation. Experimental results on the VisDrone2019-DET dataset demonstrate that the improved model reduces parameters by 62% compared to the original model, increases mAP50 by 3.9%, and improves FPS by 17%. The improved model exhibits superior detection performance compared to other mainstream detection models.

Aiming to address the issue of accurately measuring the slurry pH value during the operation of limestone-gypsum wet flue gas desulfurization (WFGD) system, which hinders the efficient operation of WFGD, a prediction model for FGD system pH based on bi-directional gated recirculation unit(BiGRU) has been developed. Firstly, the raw data were cleaned and normalized. Secondly, based on the maximum information coefficient analysis, 13 characteristic values were obtained as input variables and pH as output variables, and a slurry pH model was established. Finally, the model was run and the results were evaluated. Compared to LSTM and GRU, the results indicate that the mean absolute error of this mathematical model decreases by 11.95% and 24.92%, while the root mean square error decreases by 10.64% and 19.49%. Additionally, the coefficient of determination improves by 1.79% and 3.08% respectively. This demonstrates that the BiGRU-based pH predictive model exhibits high accuracy and stability, making it valuable for engineering applications and providing an important reference for predicting pH models in existing desulfurization tower systems.

Molecular dynamics method is adopted to investigate the effect of different NaCl solutions concentrations on the bonding properties of the calcium silicate hydrate/γ-FeOOH(C-S-H/γ-FeOOH) interface. The effect mechanism of NaCl solution concentration is revealed from the interface ion evolution, radial distribution function, particle strength distribution, interaction energy and mechanical properties. The results show that as the concentration of NaCl solution increases, interlayer {\mathrm{Ca}}_{\mathrm{h}}^{2+} ions separate from the surface of C-S-H and diffuse to the interlayer solution, Na⁺ ions enter the C-S-H layer. {\mathrm{Ca}}_{\mathrm{h}}^{2+} ions adsorb Cl^- ions in the solution, resulting in the ion clusters of {\mathrm{Ca}}_{\mathrm{h}}^{2+} and Cl^- on the surface of C-S-H. In addition, the γ-FeOOH surface hydroxyl oscillation provides adsorption points for {{\mathrm{Na}}^{+}}^{}ions, resulting in the increase of Na⁺ ions on the γ-FeOOH surface. When the NaCl solution concentration increased, the RDF peak of Ca_h—O_s gradually decreased and the radial distribution function(RDF) peak of Ca_h—O_w, Ca_h—Cl, and Na—O_s gradually increases, consistent with the ionic strength distribution. Where, O_s is the oxygen on the silicon chain in C-S-H, and O_w is the oxygen in the interlayer solution water. {\mathrm{Ca}}_{\mathrm{h}}^{2+} ions form ionic bonds with O_w in water, leading to a reduction of Ca_h—O_s ionic bonds on the C-S-H surface. Since the strength and stability of Ca_h—O_s ionic bond are better than that of Ca_h—O_w,therefore, the C-S-H/γ-FeOOH interfacial interaction energy and peak stress both show a decreasing trend with the increase of NaCl solution concentration.

In view of the deficiency of the research on the prevention and control of bolt anchoring in engineering rock mass, the method of cooperative prevention and control analysis based on bolt pre-tightening force was put forward, and the cooperative prevention and control test of bolt, anchor agent and surrounding rock based on bolt pre-tightening force was carried out, the variation law of pre-tightening force of bolt was obtained and the cooperative prevention and control state of bolt anchoring was identified. The results indicate that improving the synergy between anchoring agents and the surrounding rock of anchoring holes, as well as between anchor rods and anchoring agents, is beneficial for their synergistic evolution and can effectively enhance the prevention and control effect. A method for determining the collaborative state of anchor rod anchoring is provided, which can comprehensively determine the collaborative state of anchor rod anchoring through the relaxation process curve and relaxation degree of anchor rod pre-tightening force. Increasing the contact surface between the anchor rod pad and the surrounding rock on the free face is beneficial for their synergistic evolution. Based on the application and monitoring of pre-tightening force, a method for determining the overall coordination degree of anchor rod anchoring prevention and control has been developed, and strategies for improving the coordination degree of each part of anchor rod anchoring have been proposed. During design, special attention should be paid to the coordination of each part of anchor rod anchoring to ensure that they can perform at their best and be in their optimal state. The research results have good guidance and reference significance for the anchoring mechanism, monitoring, prediction and prevention of prestressed anchor rods in engineering rock masses.

“Large-difference annulus” is a common characteristic encountered in complex wellbore structures with “varying diameters” during (ultra-)deep well drilling. This characteristic leads to slow drilling fluid velocity in the upper large-diameter annulus, posing challenges for cuttings removal, while the higher velocity in the lower small-diameter annulus results in significant circulating pressure loss. To address these issues, a novel flow diverter tool was designed to carry cuttings in the upper section and the loss of circulating pressure in the lower section. However, the lack of a specific wellbore flow model tailored for this tool in current research has hindered its design and optimization. Based on the fundamental principles of fluid flow and hear transfer, a valid mathematical model was proposed to be compatible with the flow diverter tool. Then, via a case study on Well ZS102, the tool was proved to be effective and perform well in practice. The results show that with the installation of the flow diverter tool, the bottomhole pressure is lowered from 85.08 MPa to 80.30 MPa, the standpipe pressure is significantly reduced from 20.97 MPa to 7.22 MPa, and the annulus pressure loss is decreased from 7.16 MPa to 2.40 MPa. The research presents a novel approach for optimizing cuttings removal parameters and preventing leaks in complex wellbore structures during deep and ultra-deep well drilling operations, contributing significantly to the advancement of related drilling technologies.

To explore the impacts of various factors on the performance of concrete, the response surface methodology was adopted to optimize the concrete mix proportion. In the experiment, the water-binder ratio, the dosage of steel slag, and the content of desert sand were taken as variables, with a focus on analyzing the main performance indicators such as the slump of concrete, compressive strength, and splitting tensile strength. The experimental results indicate that the content of desert sand has the most significant influence on the slump of concrete, while the compressive strength and splitting tensile strength are mainly affected by the variation of the water-binder ratio. With the increase of the content of desert sand, the slump, compressive strength, and splitting tensile strength of concrete exhibit a trend of initially increasing and then decreasing. When the content of desert sand reaches 30%, the performance is optimal. The addition of steel slag can enhance the fluidity of desert sand concrete (DSC). As the amount of steel slag increases, the compressive strength of DSC shows a decreasing trend, and the tensile strength increases initially and then decreases. The addition of steel slag interacts with desert sand, particularly on the tensile strength of DSC. Through response analysis, the optimal mix proportion was obtained as a water-binder ratio of 0.39, a dosage of steel slag of 10%, and a content of desert sand of 30%, at which the comprehensive performance of DSC is the best. Finally, non-dominated sorting genetic algorithm Ⅱ(NSGA-Ⅱ) was utilized for multi-objective optimization, which yielded a more complete solution set, thereby providing certain technical support for the application of DSC.

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

On-line and efficient monitoring of leakage faults in district heating network can effectively increase the quality of heat transmission and reduce energy consumption. However, the data feature extraction ability of conventional leakage fault diagnosis method is limited, and it is difficult to deal with the high dimensional nonlinear pressure flow monitoring data for complex heating network, which makes its diagnostic performance weak. Therefore, a fault diagnosis model of heating network leakage based on convolutional neural network (CNN) and Transformer was proposed. The proposed CNN-Transformer diagnostic model combines CNN and Transformer network to realize joint learning of different time scales and spatial features. The CNN network was used to extract local features, and the Transformer network was used to capture global features. The validity of the model was verified by simulating the fault data set of the annular heating pipe network system. The results show that the proposed CNN-Transformer diagnosis model based on multi-stage feature extraction and fusion mechanism of fault features significantly improves the accuracy of leak diagnosis. The CNN-Transformer method has the highest accuracy on the test set, with an accuracy increase of 13.21%, 7.49%, 6.1% and 4.62%, respectively, compared to other fault diagnosis methods including long short-term memory network, gate recurrent network, CNN and Transformer.

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

When a large number of containers arrive at a node during coal intermodal transportation, it can lead to problems such as container congestion and transfer delays during the transshipment process. Based on this, the criteria importance through intercrieria correlation (CRITIC) objective weighting method was adopted to quantify the risk of transfer delay in coal rail-road intermodal transportation, and then the risk was incorporated into the path optimization factors. Meanwhile, the improved activity-share-intensity-factor (ASIF) equation was introduced to measure the carbon emissions of transportation and transshipment node exchange processes. A carbon emission and transfer delay risk model for the entire freight transportation time was established. Based on the above model, a coal rail-road intermodal transportation path optimization model was proposed, with the objectives of minimizing carbon emissions, transportation costs, transportation time, and transfer delay risk. Through a case study, MATLAB programming was introduced, and the non-dominated sorting genetic algorithm Ⅱ (NSGA-Ⅱ) algorithm was designed to solve the example. The optimization results under different transportation decision conditions were simulated, respectively. By comparing the single-objective optimization results of minimum carbon emissions, minimum transportation costs, shortest transportation time, and minimum transfer delay risk with the multi-objective optimization results that comprehensively consider the above objectives, the advantages of multi-objective optimization in handling low-carbon path optimization for coal rail-road intermodal transportation were explored. The research results show that compared with single-objective optimization, the multi-objective optimization scheme can effectively reduce transportation costs, shorten transportation time, reduce comprehensive energy consumption, and lower the risk of transfer delay, achieving a comprehensive optimal combination of economy and safety in coal rail-road intermodal transportation. At the same time, it also provides a certain reference for the path optimization of rail-road intermodal transportation under different transportation demands and scenarios.

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

In order to analyze the distortion effect of thin-walled box girder under lane load, the distribution law of stress amplification coefficient in thin-walled box girder was studied. The distortion angle and distortion generalized bending displacement were taken as node displacements. Based on the initial parameter solution of the homogeneous equation of the distortion control differential equation, the thin-walled box girder was divided into beam segment elements, and its element stiffness matrix and equivalent node load array were derived. Using Fortran language and referring to the calculation program FRAME2 for planar frame structures, a finite element program for beam segments that can be used to analyze the distortion effect of thin-walled box girders was obtained. The program was used to analyze the variation laws of the distortion internal forces and stress amplification factors of box girders under lane loads. The results show that the distortion warpage stress of three-span continuous box girder with variable cross-section under the action of lane load has a sudden change at the place of concentrated load, where the maximum and minimum values are obtained, the longitudinal distribution of stress amplification factor is similar to the longitudinal distribution of distortion warpage normal stress, both of which are symmetrically distributed along the span, the magnification factor of normal stress at the top and bottom of the section is 1.080 and 1.180 respectively. The points with smaller bending stress should not be considered when the magnification factor is taken into account.

During tunnel construction, the deformation of surrounding rock and the mechanical response of the supporting structures are significantly influenced by the lateral pressure coefficient λ. Accurate determination of the on-site lateral pressure coefficient is essential for guiding tunnel design and construction. Firstly, the impact of the lateral pressure coefficient on settlement displacement of the tunnel vault and horizontal displacement of the side walls was analyzed theoretically. Secondly, the ratio between horizontal displacement of the side walls and settlement displacement of the vault was monitored, and a numerical simulation was employed to establish a mathematical relationship between the horizontal-vertical displacement coefficient K and the lateral pressure coefficient λ, enabling the inversion of the lateral pressure coefficient. Finally, the inverted lateral pressure coefficient was applied to optimize tunnel cross-section design. The results indicate that, under the same geological conditions, an approximately linear relationship exists between K and λ. Regardless of changes in tunnel depth or surrounding rock conditions, a proportional relationship between horizontal and settlement displacements is maintained, which can be used to invert the lateral pressure coefficient at the tunnel site. By adjusting the tunnel axis ratio m to gradually approach λ^-1, deformation is effectively controlled and the proportion of lining damage is reduced.

The complex nonlinear characteristics and dynamic friction properties of the integrated brake-by-wire system were recognized as challenges for precise hydraulic pressure control. To address these issues, a precise hydraulic force control strategy was proposed for the integrated brake-by-wire system. Firstly, the structure and control framework of the integrated brake-by-wire system were analyzed, and equivalent simplified models were established for each component to facilitate controller design. Secondly, a three-layer cascade pressure control method was introduced for active braking in the integrated brake-by-wire system. Specifically, the pressure control layer was designed based on the active disturbance rejection control method, which mitigates the effects of hysteresis nonlinearity in the hydraulic system. The position control layer employs a robust sliding mode variable structure control method and addresses the dynamic and static friction issues in the transmission mechanism. The current control layer was designed using the linear matrix inequality method to enhance the braking motor's dynamic following performance. Joint simulation tests using AMESim-Simulink demonstrate that the integrated brake-by-wire system achieves good pressure control performance across various operating conditions, maintaining the steady-state pressure tracking error within 0.1 MPa, compared to the traditional proportion-integration(PI) control method, the mean transient pressure tracking error is reduced by 0.14 MPa using the proposed method, the mean steady-state pressure tracking error decreases by 0.8 MPa, and the response lag time is lowered by 0.04 s, which verifies the effectiveness of the control strategy proposed.

In order to address the supply-demand imbalance in the increasingly complex and changing market environment, improving the accuracy of air cargo volume forecasting is of great significance for route planning and supply chain optimization. Firstly, based on monthly air cargo data from January 2000 to December 2022 as the training set, seasonal fluctuations and long-term trends were captured using seasonal and trend decomposition using loess (STL). Secondly, a deep learning time series prediction model (LSTM-SVR) was used to fit the nonlinear changes in cargo volume due to emergencies. Finally, the prediction model was tested based on monthly data for the entire year of 2023. The results indicate that the seasonal and combination prediction model (STL-SVR-LSTM) is more accurate in predicting air cargo volume during emergencies compared to traditional methods such as ARIMA, SVR, or LSTM. The data validation in 2023 shows that the root mean square error and average absolute percentage error of the seasonal and combination prediction models are 3.53 and 3.53%, respectively, with a goodness of fit score of 0.79. The LSTM model has the second best prediction results, with root mean square error and average absolute percentage error of 5.66 and 7.73%, respectively, and a goodness of fit score of 0.58, significantly better than the other two traditional models. It can be seen that this prediction model can adapt to the prediction of air cargo volume in complex environments, which is helpful in providing reference suggestions for enterprise operation and enhancing supply chain stability in case of emergencies.

In order to research the effect of rotation on the flow and heat transfer characteristics of heat convection system in a closed cavity, a series of numerical simulations were carried out on the air flow and heat transfer characteristics in a closed cavity. The distribution characteristics of velocity field and temperature field by different Rayleigh numbers and rotating Rayleigh numbers by horizontal and vertical temperature gradients were obtained, as well as the local and average Nusselt numbers on high temperature walls. The effect of rotation on the thermal convection system by two kinds of thermal boundary conditions was discussed. The results show that for the heat convection by horizontal temperature gradient, the gradual enhancement of rotation makes the flow characteristics change from single-cell to multi-cell, and enhances the heat transfer performance of heat convection. For heat convection by vertical temperature gradient, the enhancement of rotation makes the flow tend to the steady-state flow characteristics, that is, the flow stability is enhanced, and at a large Rayleigh number, the enhancement of rotational action will first inhibit and then strengthen the heat transfer performance. Given the same conditions, the convective heat transfer performance by horizontal temperature gradient is better than that by vertical temperature gradient, and the stronger the rotation effect is, the more obvious the feature is.

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

The application of green NH₃-fuel on board has been widely regarded as a feasible way to realize the green and low-carbon transformation of the global shipping industry. However, the N₂O emission problem of marine NH₃-fuel engines has become one of the key technical bottlenecks hindering the development of ammonia-powered ships. To solve this problem, a series of TiO₂-supported transition metal oxide catalysts were prepared by impregnation method. The effect of transition metal element types on the N₂O removal performance of the catalysts was investigated, and the N₂O removal performance of Cu_x/TiO₂ catalysts was optimized. The results show that compared with Fe₅/TiO₂, Mn₅/TiO₂, Co₅/TiO₂ and Ni₅/TiO₂ catalysts, Cu₅/TiO₂ catalyst shows excellent catalytic activity, the N₂O conversion efficiency can reach 100% at 350 ℃. In addition, Cu₅/TiO₂ catalyst also has good water resistance. The experimental results show that 5% is the best Cu loading amount. X-ray diffraction, N₂ adsorption-desorption, H₂ temperature programmed reduction, O₂ temperature programmed desorption, and in-situ diffuse reflectance infrared Fourier transform spectroscopy were used to characterize the physicochemical properties and surface reaction intermediates of Cu₅/TiO₂ catalyst, and the relevant catalytic reaction mechanisms were discussed in depth from multiple perspectives. The characterization results show that compared with other Cu_x/TiO₂ catalysts, Cu₅/TiO₂ catalyst has higher dispersion of active species, specific surface area, oxygen vacancy content and stronger redox performance, which is conducive to its better catalytic activity. The main active species on the surface of Cu₅/TiO₂ catalyst are Cu²⁺ and Cu⁺ species, and the adsorption and deionization of N₂O is a key step in the catalytic reaction.

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

In order to solve the problems of imperfect fire risk management system and subjective and one-sided risk assessment methods of civil aviation transport aircraft, a comprehensive risk assessment method based on random forest ensemble algorithm was proposed for the analysis and evaluation of risk factor indicators. Firstly, according to the man machine environment management(MMEM) theory, the risk index system was established based on the investigation of the causes of aircraft fire accidents in the past 20 years, and then the scores of scholars and experts in related fields on the correlation between the indicators were collected, and the subjective risk index weight results were obtained by using the analytic network process(ANP) method. The causes of major aircraft fire accidents in the database in the past 20 years were counted and their prior probabilities were calculated by classification, and the Bayesian network(BN) dynamic analysis method was used for reverse reasoning to obtain the probability distribution of each risk factor. The random forest regression model was established to obtain the predicted value and importance of the characteristic index, and put forward scientific and effective suggestions for the fire risk control of the operating unit. The results show that the five indicators of missing dangerous goods in security inspection, failure to eliminate hidden dangers in time, component failure, bird strike, and high surface temperature are the most critical risk factors in aircraft fire accidents.