Transformer calibrators are a kind of equipment used to test the transformer error in the power system. With the development of technology, the transformer calibrator is also constantly innovating, from manual, and automatic to intelligent development, which has become a research hot spot. Two types of calibrators according to the usage method, namely the difference measurement method and the direct comparison method were introduced and the advantages and disadvantages of each method and related products were analyzed. Currently, digital calibrators had became a research hotspot because of their high degree of automation and multiple functions. The digital calibrator could be used for both conventional and non-conventional transformers, with a wide range of applications. Three key technologies that affect the accuracy of the digital calibrator are focused on by the paper. And a new technology based on small-signal on-site calibration were introduced, which had significant advantages over the current commonly used on-site calibration methods, with strong compatibility and high security, making the transformer calibration device smaller and more portable, and suitable for a wide range of occasions. Finally, it was pointed out that the transformer calibrator should continuously develop towards digitalization, intelligence, portability, accuracy improvement, and comprehensive performance improvement.

The boundaries of underground geological bodies are effectively highlighted through gravity inversion based on a typical focusing stabilizer, but this process is significantly affected by the focusing factor. The focusing characteristics are possessed by the exponential focusing stabilizer. To a certain extent, the issue of selecting the focusing factor can be circumvented by it, and it has the potential to have improved the effectiveness of three-dimensional gravity inversion.Furthermore, the multiplicity of solutions in inversion can be improved by the constraint imposed by the penalty function, which confine the inverted physical property values within a certain range. Based on this, in order to explore the improvement effects on three-dimensional gravity inversion by the exponential focusing stabilizer and penalty function constraint, the exponential focusing stabilizer and penalty function were incorporated into the three-dimensional gravity regularization inversion objective function. Comparisons were made of the effects resulting from three-dimensional gravity inversion, both with and without the involvement of the exponential focusing stabilizer, as well as with and without the application of the penalty function constraint. Model experiments have demonstrated that: the physical properties and spatial distribution of anomalous bodies can be accurately restored by the exponential focusing stabilizer, but there exist instances where false anomalies arise and physical property values surpass the true values. Situations like these can be improved by the exponential focusing inversion that is based on penalty function constraints. Furthermore, the accuracy of the solution can be enhanced by the zonal processing of penalty function constraints. The above situation indicates that the inversion method based on the exponential-type focusing stabilizer and constrained by penalty functions has certain potential to be generalized.

The influencing factors on the reservoir development of Upper Taiyuan Formation in the eastern Ordos Basin were investigated. Experimental methods such as casting thin sections, high-pressure mercury intrusion, and constant-rate mercury intrusion were employed to examine the pore structure characteristics of Upper Taiyuan Formation, Tai 2 Member. Results show that the average porosity of Tai 2 Member reservoir is 7.84%, with an average permeability of 0.396 mD, primarily characterized by ultra-low porosity and permeability. The pore structure is complex, with strong heterogeneity. Various types of pores were developed in the reservoir, including intragranular dissolution pores, intergranular dissolution pores, intercrystalline pores, and rock fragment dissolution pores. Based on the frequency of pore development, porosity, and permeability in each region, the pore combinations are classified into three types: intragranular dissolution pores, intragranular dissolution pores combined with intercrystalline pores, and intragranular dissolution pores combined with intergranular dissolution pores. The experimental methods of high-pressure mercury intrusion and constant-rate mercury intrusion could effectively characterize the reservoir characteristics of these three types of pore combinations, among which the combination of intragranular dissolution pores and intercrystalline pores represents a favorable reservoir pore type. Based on the laws of sedimentary differentiation and pore differentiation, a set of criteria for evaluating high-quality reservoirs is established on the basis of experimental results. Upper Taiyuan Formation reservoir was classified into Class Ⅰ, Ⅱ, and Ⅲ from good to poor, and predictions were made for favorable areas of high-quality reservoirs.

The Yakela region is located in the northern part of the Tarim Basin. The review of old wells in 2021 shows that the new proven geological reserves of oil in the Paleogene Kumugeliemu Formation in the YK6H block of Yakela are 86.7×10⁴ t, and the structural amplitude of the oil and gas reservoirs that have been discovered so far is low, and it is difficult to identify similar low-amplitude structural traps, and the matching relationship between the accumulation conditions is not clear. In order to find new favorable zones for oil and gas development and strengthen the development of remaining oil reservoirs, based on the high-precision 3D seismic data of the Yakela area and guided by the theory of high-precision sequence stratigraphy, the high-precision stratigraphic division and comparative analysis of the Yakela area were carried out. Through ant body extraction, automatic layer tracking, and variable velocity mapping technology, 105 micro-faults were identified, the identification accuracy of low-amplitude structures was improved, and the distribution of low-amplitude structural traps with a minimum closure height of 2 meters was implemented. Based on the reservoir control factors such as structural location, trap characteristics, sedimentary reservoirs and oil and gas migration channels, the newly implemented low-amplitude structural traps were analyzed and evaluated, and favorable targets were selected, and then the favorable reservoir zones were comprehensively analyzed. The “three-element reservoir control” favorable target optimization method suitable for low-amplitude structural traps was summarizes, which is suitable for low-amplitude structural traps, and provides a reference for the evaluation of favorable targets in areas with similar geological conditions.

Under the condition of heavy rainfall, the rock and soil saturation of fully weathered granite slope increases, and the shear strength decreases, which is easy to cause slope instability. In this process, the change of matrix suction is the key factor leading to the change of shear strength. Taking Laoshan fully weathered granite slope in Qingdao as the research object, the soil and water characteristic curve (SWCC) of fully weathered granite based on Van Genuchten model was obtained by means of centrifuge test, undrained direct shear test, X-ray diffraction analysis, conventional silicate chemical total analysis test and scanning electron microscope test. The effect of matrix suction on the shear strength of fully weathered granite was studied systematically. The results show these as follows. The saturation of fully weathered granite soil is negatively correlated with matrix suction, and the soil samples with uneven gradation have stronger drainage capacity. The shear strength index is affected by matrix suction differently. Cohesion is more sensitive to the change of matrix suction than the angle of internal friction. There is a positive correlation between matrix suction and shear strength in fully weathered granite soil. The research results can provide theoretical guidance for slope prevention in fully weathered granite area.

In order to study the disaster susceptibility of debris flow in Yongsheng County, the research area was Yongsheng County of Lijiang City, Yunnan Province, and it was divided into 475 sub-watershed units. Grey correlation analysis method was used to calculate the correlation degree of each factor, and the factor with the lowest correlation degree was eliminated. The independence of factors was tested by collinearity diagnosis. In the end, eight factors including average slope, average annual maximum rainfall, average vegetation coverage, average elevation, average melton ratio, average water system density, average landslide core density and average road density were retained. The information volume of the factors was calculated by the information volume method, and the correlation degree value was taken as the weight value of the superposition of each factor. The grey correlation analysis-information volume model was further constructed to carry out the evaluation research on the vulnerability of debris flow in Yongsheng County. The results show this as follows. The requency ratio of debris flow disaster points in the extremely vulnerable area is as high as 4.06, and the area under the ROC (receiver operating characteristic) curve is 0.818, indicating that the selected eight factors and the grey correlation analysation-information volume method have good forecasting ability for the evaluation of debris flow disaster vulnerability. The results can also be used as reference for the prevention and control of debris flow disaster in Yongsheng County.

Myocardial ischemia is caused by the incoordination between myocardial oxygen consumption and oxygen delivery in coronary artery disease, and due to its high morbidity and mortality rate, the number of patients who die from ischemic heart disease in China is increasing year by year. In order to verify that the active ingredients of Jinlume have anti-myocardial ischemic efficacy. The maximum tolerated concentration (MTC) was determined to be 15.63 μg/mL by the pre-test, and the high school and low dose groups were divided into 7.81 μg/mL (1/2 MTC), 2.60 μg/mL (1/6 MTC) based on the MTC, respectively, 0.868 μg/mL (1/18 MTC), and the positive drug group was N-acetylcysteine (125 μg/mL). With the help of network pharmacology and molecular docking technology, the possible mechanism of action of the active ingredients of Jinlume in inhibiting cardiomyocyte apoptosis and slowing down myocardial ischemia was investigated. The results showed that the aqueous extract of Jinlume had significant effects against myocardial ischemia in comparison with the positive drug group by means of zebrafish cardiac fluorescence intensity phenotyping, and its mechanism of action was related to five pathways, namely, Rap1 signaling pathway, cancer pathway, proteoglycans in cancer, PI3K-Akt signaling pathway, lipids, and atherosclerosis. It can be seen that exploring the anti-myocardial ischemic mechanism of the active ingredients of Jinlume has certain theoretical significance for the prevention and treatment of myocardial ischemia.

In order to study the task-based functional connectivity of the whole brain in schizophrenia patients and healthy controls during task switching, the NSP(nested-spectral partition) method was used to quantify the degree of integration and segregation of the whole brain network and explain differential remodeling patterns of brain networks in schizophrenia patients and healthy controls. Results show that changes in whole-brain functional connectivity patterns in schizophrenia are driven by lower network integration and higher segregation, suggesting global and network-wide local information transfer during task switching in schizophrenia patients efficiency was lower than that of healthy controls. Furthermore, the association between task switching costs (reaction time and switching costs) and task state modularity was analyzed using simple linear correlation. Lower whole-brain modularity and lower salience network modularity in schizophrenia were found to be associated with larger switch costs but not with mean reaction times across the task. In contrast, higher cortical network modularity in healthy control patients was associated with faster task reaction times but not with shorter switch costs. Taken together, the results suggest that quantifying functional network configurations across different task states can provide information about cognitive control performance.

Traditional retinal vessel segmentation methods often face challenges such as missegmentation caused by optic disc confusion, lack of continuity in segmentation results, and imprecise segmentation in detailed regions. To address these issues, a retinal vessel segmentation algorithm was proposed based on UNet. The algorithm replaced traditional square convolutions with a fusion of horizontal and vertical one-dimensional convolutions and two-dimensional square convolutions, enhancing the representation capability of the eye region. A multi-scale branch approach was adopted to increase feature space diversity, thereby improving the network’s feature learning and expression capabilities. Additionally, to further enhance segmentation performance, multi-layer dilated convolutions was introduced into the deep structure of the autoencoder, replacing traditional simple pooling operations. This approach enlarged the convolution kernel size and expanded the receptive field, achieving a fusion of multi-scale shallow and deep feature information. The proposed algorithm was evaluated on the public DRIVE and CHASE_DB1 datasets. Experimental results demonstrates that the algorithm achieves precision (0.956 8 and 0.959 8) and F₁ scores (0.832 6 and 0.830 4), respectively. Compared with traditional UNet and recent UNet-based retinal vessel segmentation methods, the proposed algorithm shows advantages in accuracy, sensitivity, specificity, and F₁ metrics, these validation results fully demonstrate the proposed model’s strong capability in precise segmentation tasks.

During the production of monocrystalline silicon, defects generated during the crystal pulling process are recognized to severely impact product quality. Traditional visual-based defect detection methods, when applied to the detection of small protrusions in crystal pulling images, are confronted with challenges such as slow detection speeds, large parameter volumes, and difficulties in deployment on embedded terminals. In response to these challenges, an improved YOLOv8 object detection model was proposed incorporating a ContextGuided module to enhance the inference efficiency of the model. An efficient DySample was introduced into the feature fusion network to optimize the efficiency and depth of feature fusion. A lightweight network structure was adopted to reduce the complexity and computational demands of the model, making it suitable for devices with limited computing resources. The model has been trained and tested on an industrial dataset, demonstrating a more accurate detection of small protrusions with a mean average precision (mAP) of 97.7%. Compared to YOLOv8n, it exhibits an increase of 11.6% in precision and a reduction in parameter volume by 31.9%, facilitating its deployment on embedded terminals.

In order to reasonably evaluate, screen, and optimize the exterior design schemes of suspended monorail train with regional cultural characteristics, an optimization method for exterior design of suspended monorail train based on fuzzy analytic hierarchy process was proposed. Firstly, the characteristics and trends of the exterior design of suspended monorail trains both domestically and internationally were analyzed, and an evaluation index system which focusing on cultural factors for the exterior design of suspended monorail train was constructed. Then, estimate matrix based on experts scores and gained weights of each individual index by calculation was established. Finally, taking the design case of a suspended monorail train with regional cultural characteristics of Guangzhou as an example, the integration of typical regional culture and design idea, as well as the evaluation and optimization of design schemes were explained. The results show that the method can be used to screen and obtain suspension monorail train design schemes with high comprehensive satisfaction in terms of exterior form, painting, and cultural relevance. It can quantitatively evaluate design schemes from multiple dimensions and provide a basis and direction for the screening and iterative optimization of design schemes.

The vibration excitation transmission of the platform should be suppressed while ensuring the safe and reliable operation of equipment. Currently, most research on vibration reduction focuses on individual pedestals or pedestal-platform plate structures, with few studies comprehensively considering the relationship between equipment, pedestal, and platform bottom plate vibrations. ultra-deep water semi-submersible drilling platform equipment’s long base was taken as the research object and impedance analysis and optimization design technology was utilized to control input power flow of the platform bottom plate in key frequency bands. Design variables such as mass and stiffness were optimized to improve base plate thickness while maintaining support strength and stiffness. A coupling vibration control model for “equipment-pedestal-platform” was established, using a particle swarm optimization algorithm with linear weight decline for optimization. Finite element method verification results show that this technical process is feasible, reducing optimized input power flow by 95.43% in low frequencies below 300 Hz and decreasing total response level of vibration acceleration by 18.1 dB.

The rod of a fire drive production well in Xinjiang oilfield is seriously corroded, and there are many corrosion pits on the surface. In order to find out the cause of rod corrosion failure, the metallographic structure and physical and chemical properties of the failed rod were tested and analyzed, and the corrosion characteristics were analyzed by scanning electron microscope, energy spectrometer and X-ray diffraction analysis, and the failure causes were found out combined with the service conditions of the rod. The results show that the chemical composition, metalloid structure and inclusions of the D-class rod meet the standard requirements of the rod. The rod has only been in service for 1 year and 8 months and its diameter has decreased from 19 mm to 16 mm, the average corrosion rate is 1.796 mm /a, and the maximum surface corrosion pit depth is 2.1 mm. The surface of the rod is mainly attached with FeCO₃, FeS and CaCO₃. It is judged that the rod is corroded by CO₂/H₂S and underscale corrosion caused by high salinity produced water. At the same time, a large amount of Cl^- in the produced liquid promotes the development of pitting pits. It is recommended to inject corrosion and scale inhibitor into production wells with temperature lower than 50 ℃, pH value between 6 and 8, and formation water belonging to high calcium and high chlorine to protect the D-class rod and extend the service life of the rod.

Considering the characteristics of poor permeability, mixed particle sizes, and complex pore structures of conglomerates, a study was conducted on the pore structure characteristics and connectivity of the Mahu Urho Formation conglomerates using CT(computed tomography)scanning and 3D reconstruction techniques. By establishing a pore structure extraction method combining conventional threshold segmentation and top-hat algorithm, the challenge of extracting microcracks was overcome. The study reveals that the main types of pores in the Urho Group conglomerates are intergranular pores, dissolved pores, and microfractures, with the 3D pore types are mainly lamellar pore structures and isolated pore structures. Although pores with equivalent radii of conglomerate samples smaller than 30 μm account for a high proportion, their contribution to the total pore volume is relatively low. Pores larger than 60 μm, while fewer in number, occupy over 50% of the total pore volume, serving as the primary storage space. Experimental samples are predominantly characterized by level III connected domains, exhibiting good connectivity conducive to the accumulation and extraction of oil and gas. The investigation into the pore structure characteristics of strongly inhomogeneous conglomerates holds significant theoretical and practical value for an in-depth understanding of such characteristics and for the exploration and development of oil and gas reservoirs in sand conglomerates.

In order to comprehend the scale and connectivity of sandbodies in late oilfield development, it is imperative to conduct a detailed characterization of fluvial sandbodies in the upper Guantao Formation of Gudong oilfield. Through comprehensive analysis of core, well logging, and seismic data, the sedimentary characteristics of braided river and meandering river were determined under the control of dense well array. The results indicate that the upper Guantao Formation has undergone a sedimentary evolution process from braided river to meandering river. The lower Guantao Formation exhibits braided fluvial reservoir with braid bar, braid channel, and overbank sand microfacies, while the upper Guantao Formation features meandering fluvial reservoir with microfacies types such as point bar, abandoned channel, crevasse splay, and floodplain. By conducting core-log calibration analysis, the logging response characteristics and sandbody development laws of braided and meandering rivers were determined. The channel sandbody of a braided river is cut and overlapped in multiple stages while being distributed across multiple branches on a plane. On the other hand, the meandering fluvial channel sandbody develops in isolation but forms strips on a plane. Under the control of dense well array, we have quantitatively determined the scale of sandbody development for both braided and meandering rivers. Additionally, the relationship between sandbody thickness and width for different river types were established which holds significant guiding significance for identifying sandbody connectivity and 3D geological modeling.

A significant number of subsalt oil and gas fields are distributed worldwide. Due to the high costs associated with coring operations in salt formations, conducting creep experiments on specific salt rock cores is challenging. To address this issue, a method for creating artificial salt rock cores was developed wherein the degree of recrystallization was controlled by adjusting the preparation temperature and pressure. By testing the acoustic velocity, density, and uniaxial peak strength of salt rock cores under different preparation conditions, the optimal preparation conditions were identified. Creep experiments verified that the artificial salt rock cores exhibit similar creep characteristics to natural salt rock cores, indicating the feasibility of using artificial cores as substitutes for natural ones. Based on indoor creep experiments, a viscoelastic constitutive model of salt rock was constructed. The result showed that the rheological characteristics of the decelerating creep stage conform to the Kelvin model, while the steady-state creep stage aligns with the Heard model. A UMAT subroutine was compiled to describe the creep characteristics of the decelerating and steady-state stages, demonstrating a good fit and indicating the applicability of the viscoelastic model constructed in this study. Creep experiments on composite salt rocks with different contents of anhydrite showed that the presence of anhydrite inhibits the creep of salt rock. The higher the anhydrite content in the salt rock, the lower the creep rate of the rock. Therefore, in salt layers containing anhydrite, the density of drilling fluid used during drilling can be appropriately reduced.

Based on the reservoir conditions of tight conglomerate reservoirs in the Mahu area of the Junggar Basin, an experiment was conducted to study the interaction between tight conglomerates, CO₂, and water. The results indicate that after CO₂ dissolves in water to form carbonic acid, it primarily reacts chemically with feldspar and calcite in the cement between the conglomerate grains. This leads to significant around-grain dissolution, with dissolution being the main process and precipitation being secondary. Ultimately, this increases the porosity and permeability of the rock, enhancing the reservoir fluid seepage capacity. The maximum increases in porosity and permeability are 3.65% and 87.36%, respectively. Additionally, the surface roughness of the rock increases after the interaction, with hydrophilic mineral quartz exposed on the surface. The water-phase wetting contact angle of the rock decreases by 7.4°, enhancing hydrophilicity. The CO₂ huff and puff process has a positive effect on improving oil recovery, with the main oil-increasing mechanisms being the enlargement of pore space to enhance fluid seepage capacity and the improvement of rock water-phase wettability, which increases reservoir water-phase imbibition capacity and crude oil mobility, thereby improving oil recovery.

Due to the similarity in site selection between underground pipelines and power facilities such as high-voltage power lines and urban rail transit power supply systems, underground pipelines are increasingly affected by stray currents generated by power facilities. The impact of AC stray currents on the corrosion rate of pipeline coating defects were simulated and analyzed. The effects of parameters such as AC current magnitude, soil conductivity, internal pressure of the pipeline, stress, distance to grounding electrode, and pipeline radius on corrosion were investigated in the study. The results indicate that when the stress on the pipeline is less than the yield strength, the effect of stress on the corrosion caused by AC stray currents is relatively small. However, after the deformation of the pipeline increases, serious corrosion will be induced by stress. The greater the AC current, the greater the corrosion at the defects of the pipeline coating. The lower the AC frequency, the greater the corrosion at the defects of the pipeline coating. The closer the distance to the grounding electrode, the greater the corrosion at the defects of the pipeline coating. The higher the soil conductivity, the greater the corrosion at the defects of the pipeline coating. The smaller the pipeline radius, the greater the corrosion at the defects of the pipeline coating. These research findings are of significant importance for ensuring the safe operation of oil and gas transportation pipelines under the influence of AC stray currents.

Macro-encapsulated phase change material (PCM) capsules are the core components that form the heat storage tank of the packed bed. In order to enhance the heat storage rate of the packed bed tank, it is necessary to optimize the heat storage and discharge rate of individual PCM capsules. Four different encapsulated shapes of PCM capsules were established while ensuring the uniform volume of individual PCM capsules. The capsules were placed in a flow field with an obstruction rate of 0.5, and the melting and solidification processes of PCM under different encapsulation shapes were analyzed with full consideration of gravity direction and heat transfer fluid flow direction in practical applications. The results show that the natural convection of liquid PCM inside the capsule can accelerate the melting and solidification process of PCM and increase the rate of charging and discharging; compared with the spherical encapsulation capsule, the heat transfer area per unit volume of cylindrical encapsulation capsule is increased by 14.47% and the melting time of PCM is shortened by 42.50%. Therefore, the cylindrical encapsulated capsule has the best thermal performance, and the cylindrical capsule can be applied to the packed-bed storage tank in future research to optimize its thermal storage performance.

In order to improve the control performance of a doubly-fed wind turbine grid-side converter under unbalanced and harmonic grid voltages, a direct power control algorithm with an improved super-helix fast terminal sliding mode was proposed. First, the mathematical model of the grid-side converter under unbalanced and harmonic grid voltages with power as the state variable was analyzed in a two-phase stationary coordinate system. Then, the power inner-loop design was carried out with a nonlinear expansion state observer for the negative sequence in the mathematical model as well as the disturbances due to each harmonic component. Secondly, to ensure that the system can reach the steady state in a shorter time, the non-singular fast terminal sliding mode surface was constructed and the sliding mode control law for the power inner loop was designed by combining with the improved super-helical sliding mode convergence law. Similarly the terminal sliding mode control rate was also designed for the voltage outer loop. The stability of the non-singular fast terminal sliding mode surface, the improved super-helix control algorithm and the nonlinear expanding state observer was also proved by using the Lyapunov function. Finally, the method was verified to have faster convergence and stronger robustness by comparing it with three different control schemes to perform simulations.

In order to improve the output performance of permanent magnet assisted synchronous reluctance motor (PMa-SynRM), a multi-objective optimization design method for external rotor PMa-SynRM based on kernel extreme learning machine (KELM) and fast non-dominated sorting genetic algorithm (NSGA-II) was proposed. Firstly, the preliminary design of the PMa-SynRM rotor magnetic barrier was carried out and the working principle of the PMa-SynRM was analyzed. Secondly, the influence of each design variable on the optimization goal was evaluated through comprehensive sensitivity analysis, and the main optimization parameters were selected. Thirdly, with high output torque, high efficiency and low torque ripple as the optimization goals, a surrogate model based on KELM was established. Finally, NSGA-II was used for global optimization, and the optimal solution was selected from the Pareto frontier generated by NSGA-II, which was verified by finite element analysis. The simulation results show that the average torque of the optimized motor is increased by 15.83%, the torque ripple is reduced by 60.27%, and the efficiency of the optimized motor is also improved compared with the initial motor, which verifies the effectiveness of the optimized design method proposed in this paper.

When the integrated energy system (IES) participates in electricity spot market transactions, the transaction price is uncertain due to changes in market supply and demand. In order to deal with this problem, a detailed analysis of the operating marginal cost of the integrated energy system was used to investigate the optimal dispatch strategy that fully utilizes the flexible resources of the integrated energy system to participate in the market. Firstly, the typical scenarios of market price uncertainty under the external spot market environment were analyzed, and the internal multiple source-load adjustable resources and operation cost structure of the integrated energy system were investigated. Secondly, a trading optimization model considering the marginal cost of the system under the condition of price uncertainty in the electric power market was established, and the sand cat swarm optimization algorithm was proposed to solve the problem. Finally, simulation verification was conducted based on actual cases. The result shows that this strategy can not only reduce the operating cost of IES, but also enhance its adaptability to market price uncertainty. The strategy provides new ideas for the operation of integrated energy systems in the power spot market environment, which is also helpful to realize the double optimization of economy and reliability of energy system participating in the market scheduling.

In order to solve the efficiency issues in distributed load responses to frequency regulation commands, an innovative strategy was introduced based on reinforcement learning for load aggregators’ pricing incentives in response to frequency commands. Within this strategy, a game-theoretic model between the load aggregators and load clusters was constructed, and the load aggregators adjust incentive prices based on frequency commands and their pricing strategies, while loads adjust their power consumption based on their own electricity costs to flexibly respond to the frequency commands. The multi-agent soft actor-critic (MASAC) algorithm was used to investigate the solution. The results show that the pricing incentive method enables effective load response to frequency commands, and the use of the MASAC algorithm not only optimizes the decision-making process but also significantly reduces computational complexity, achieving efficient dynamic adjustment. It is concluded that this method provides an effective solution for frequency regulation in power systems, offering significant theoretical significance and practical value.

Under the background that the accuracy of voltage amplitude detection is increasing year by year, a voltage amplitude detection method based on improved second-order generalized integrator was proposed to solve the problem that the existing voltage amplitude detection methods were susceptible to the interference of harmonic and DC components, which leaded to insufficient detection accuracy. First, the composition change of voltage after fault was analyzed, and the existence of harmonic component and DC component in fault voltage was proved. Then, the principle and performance of voltage amplitude detection by sine-cosine component method and traditional second-order generalized integral method were analyzed. Then, the output of traditional second-order generalized integrator without DC component was taken as the input of the improved second-order generalized integrator’s second module. In this way, the effective filtering of the DC component was realized, and the Bode diagram, zero pole and step response of the improved second-order generalized integrator under different gain coefficients were analyzed. The optimal gain coefficient was selected considering the influence of filtering effect, stability and response speed. Finally, the simulation results show that the method proposed in this chapter has stronger filtering ability and higher precision than the other two methods.

Laser ultrasonic detection technology possesses unique advantages combining ultrasonic and optical methods, enabling non-contact detection while enhancing temporal and spatial resolution. To enhance the excitation efficiency and defect detection accuracy of laser ultrasound, optimization of laser source parameters is necessary to improve energy exchange efficiency and reduce costs. Research has been conducted on the propagation characteristics of laser ultrasonic sound fields under various conditions. Numerical simulations of the process of laser ultrasonic action on X80 pipelines were performed using COMSOL Multiphysics finite element software, and the accuracy of the model was verified. The relationship between laser source parameters and ultrasonic field was studied by combining the set laser pulse width and laser spot radius, and further analysis of the relevant data was carried out using MATLAB. The analysis results indicate that when the pulse width is set to 20 ns and the spot radius is set to 300 μm, laser ultrasonics exhibit relatively optimal excitation efficiency in X80 pipelines. This provides important reference for improving the excitation efficiency of laser sources.

Aiming at the problem of frequent switching due to transient link changes in the heterogeneous network of indoor visible light communication (VLC) and radio frequency (RF) communication, a decision-making mechanism based on spatio-temporal characteristics for VLC/RF networks were proposed. Firstly, in the offline sampling stage, the database was constructed by processing and converting feature data such as spatial location, bandwidth, received signal strength, delay and signal-to-noise ratio of indoor grid points into proportional weights in the controller. Then, in the real-time decision-making phase, the terminal feeded the collected feature data back to the controller to determine the location of the user terminal by comparing it with the information in the database of the controller, and the prioritized link of the current location in the database was extracted and connected. Finally, the link decision model was used to derive the network communication index in real time, and the optimal link was solved by aggregating the proportional weights of the links in the database with the network communication index through the decision function, and the communication quality was improved using the resident timer. Simulation results show that the switching algorithm effectively reduces the average number of switching times and switching interruption probability compared with the traditional fuzzy logic switching algorithm and the vertical switching decision algorithm with equivalent signal-to-noise ratio (SNR). The algorithm can realize intelligent management of indoor heterogeneous networks and improve the quality of user experience.

A stepped-frequency radar transmission and reception system based on RF direct sampling technology was designed to address the issues of slow switching speed of sub pulses and incoherent phase of transmission and reception signals in stepped-frequency radar. This system performs RF direct acquisition of C-band radar signals, and all signal processing processes were carried out in the digital domain. It also had high integration and low power consumption. It was generated stepped-frequency signals by fast frequency hopping, frequency sweep of 1.8 GHz bandwidth within 7 ms was gotten. The system operates in the frequency range of 200~2 000 MHz with a frequency step of 2 MHz. At the same time, the parameters of the stepped-frequency signal in this system can be changed according to detection requirements. The test results show that the stepped-frequency radar system can achieve one-dimensional ranging function.

To solve the path planning problem of mobile robots in complex orchard environments such as irregular and rugged terrain in hilly and mountainous areas, an improved grey wolf algorithm based 3D path planning method for mobile robots was proposed. By simulating the actual geographical environment, a three-dimensional orchard terrain and obstacle model was established, and a path planning objective function model was structed. By introducing the sparrow search algorithm (SSA) the initialization method, convergence factor, local search ability, and global search ability of the standard grey wolf optimization (GWO) were improved. The simulation experimental results show that the proposed algorithm has the advantages of fast optimization speed, optimal path planning distance, and fast convergence speed compared to other algorithms, indicating the effectiveness and superiority of the proposed method.

In response to the tasks of detection and maintenance in small-diameter pipeline transportation, a small-scale soft pneumatic pipeline crawling robot was designed and developed. The robot employed the technique of analytical implicit triply periodic minimal surface offset to form a solid structure with thickness, and achieved the anisotropy of structural stiffness by adjusting the parameters of implicit equations. Based on this, the radial and linear actuators were designed to meet the flexible motion requirements of the robot inside the pipeline. To optimize the performance of the robot, a joint parameter optimization framework based on MATLAB, Rhino, and ABAQUS was proposed, and an automated parameter optimization process was implemented using Python scripts. Through this framework, the motion performance and adaptability of the robot could be effectively improved. Based on two types of deformation actuators, the overall structure of the pipeline crawling robot was designed, and the manufacturing method and motion control gait were elaborated in detail. Experimental results show that the designed pipeline robot can stably move along the pipeline in two different postures and under certain load conditions, verifying the feasibility of the joint parameter optimization framework. The research results provide valuable references for the parameterized design and optimization research of subsequent pipeline crawling robots, which contributes to the application development of soft robots in the field of small-diameter pipeline detection and maintenance.

The sigmoid iteration ACO(ant colony algorithm) was optimized for the problems of poor environmental adaptability, high number of inflection points and high computational complexity that exist in the traditional ACO(ant colony algorithm)in route planning. Firstly, the Sigmoid activation function distribution strategy was adopted to improve the initial pheromone spread through the position of the mesh nodes, and the initial concentration of the pheromone was assigned by the sigmoid, which reduced the blindness of the algorithm’s pre-search. Secondly, the adaptive factor was introduced to dynamically regulate the heuristic function, which increased the degree of expectation of the ants in choosing the globally optimal node, and reduces the convergence time of the algorithm. Lastly, a statistical analysis was carried out in each generation of the ant, and the three characteristic parameters of ant path optimal, worst and average were extracted in each generation, and the pheromone updating function was dynamically adjusted according to the number of iterations to give full play to the parallelism characteristics of the algorithm. The results prove that the improved algorithm shortens the optimal path length by 2.7%, 3.2%, and 5.4%, reduces the average number of iterations by 42%, 53%, and 62%, and shortens the worst path length by 49%, 62%, and 73%, respectively, when compared with the ant colony system, the elite ranking algorithm, and the traditional ACO. The study prove that the optimized algorithm has stronger global optimality seeking ability and better application value.

To enhance the synchronization performance of multiple clocks in robotic communication systems, a study was conducted on a distributed clock synchronization compensation scheme. Quantitative compensation and dynamic compensation algorithms for clock errors were designed. The synchronization compensation scheme, based on the IgH EtherCAT communication protocol stack, was implemented, and trajectory tracking and communication performance tests were conducted on a six-axis robotic arm. The results show that the application of this synchronization scheme improves the circular trajectory precision of the robotic arm’s end effector compared to non-IgH synchronization schemes. The clock synchronization error is reduced to 54 ns, with the error tolerance within ±200 ns. It is evident that the compensation scheme enhances clock synchronization performance and meets the application requirements of the robotic arm.

The background difference method and cross-correlation method used in the extraction of the bullet position in the images collected by the traditional CCD(charge coupled device) intersection stand-up target have the problems of poor versatility and long time-consuming. By analyzing the problems existing in CCD precision target image projectile extraction, a method for CCD precision target image projectile extraction based on IGWO(improved grey wolf optimizer) algorithm was proposed. The DLH (dimensional learning-based hunting) search strategy was used to update the position of each search factor through the neighborhood. Generate candid ate solutions, increase the diversity of search populations, and jump out of local optimal solutions. The bullet extraction problem was transformed into the problem of finding the minimum connected region of gray value under certain constraints. The minimization area gray value model, the vertical light spot area and the low gray area elimination model were established. Under the same parameter setting, the IGWO, GWO(grey wolf optimizer), MFO(moth-flame optimization) algorithm, cross-correlation algorithm, and background difference method were used to conduct comparative experiments. The experimental results show that the target detection success rate of the IGWO algorithm is much higher than other algorithms, reaching 95%, and the algorithm solution time is much lower than other algorithms, shortening to 12 ms.

To study the wind pressure distribution characteristics of long-span roofs of airport terminals at different mountain heights in mountainous areas, a rigid model wind tunnel pressure measurement test of airport terminals roofs at mountain heights of 0 m, 30 m, 60 m, and 90 m was conducted to compare and analyze the effects of the heights on the surface mean and pulsating wind pressure, non-Gaussian characteristics of pulsating wind pressure, peak factor, and extreme wind pressure of the roof surface. The results show that the increase in mountain height significantly increases the mean and fluctuating wind pressure coefficient at the windward leading edge of the roof, and also intensifies the degree of flow separation at the leading edge of the roof. This causes the skewness, kurtosis, and probability density function of the fluctuating wind pressure at the windward leading edge of the roof to deviate significantly from the standard Gaussian distribution, exhibiting strong non-Gaussian characteristics. At the same time, the Hermite moment model was used to calculate the peak factor, and it was found that the peak factor of most measuring points on the roof surface was mainly distributed in the range of 3.5~4, which was much higher than the recommended value of 2.5 in GB 50009—2012. The extreme wind pressure value at the front edge of the roof also increased with the increase of the mountain height, and there was a similar variation pattern at the edge of the roof under all wind directions. Among them, the most unfavorable extreme negative pressure on the roof surface at a mountain height of 90m decreased by 44.9% compared to the 0m mountain height. Research can provide useful suggestions and references for the design and construction of terminals in similar airports.

The creep of wood under the action of long-term load will increase the deformation of wooden beams or wooden columns, and bring hidden safety risks to the building structure. In order to improve the creep performance of wood components, an aluminum wood composite columns (AWC) was designed to make AWC with 0,2%, 3%, 3% and 4% respectively. The creep test of 0.25 stress ratio of the lower column lasted 30 days. The creep strain-time curve and creep coefficient-time curve were obtained and the AWC creep pattern was analyzed. Burgers model was used to fit the creep strain-time curve to explore the influence of aluminum alloy content on AWC creep, and analyze the causes of AWC int creep inhibition from AWC material characteristics and load transfer. The results show that, compared with AWC 1 with aluminum alloy content of 0, the creep deformation of AWC 2 ~ AWC 4 decreases to different degrees, that is, aluminum alloy can effectively enhance the creep deformation ability of wood; The four AWC creep strain-time curve correlation coefficient based on burgers model are greater than 0.95, and the creep prediction model constructed by this model can predict the AWC creep.

In order to improve the problem of easy cracking in the negative moment zone of the composite beam, the UHPC(ultra-high performance concrete)-narrow steel box composite beam structure was proposed, and the shear load capacity calculation method of UHPC-narrow steel box composite beam was obtained based on the ultimate equilibrium method and the sub-stacking method. In order to verify the accuracy of the calculation method, one normal concrete narrow steel box composite beam and three UHPC-narrow steel box composite beam specimens were designed with the thickness of UHPC layer and steel fiber as variables, and the test beams were subjected to mid-span reverse loading test to obtain the shear resistance of the composite beam under negative bending moment. The test results show that compared with the normal concrete narrow steel box composite beam, when the UHPC material is used in the wing slab, the crack distribution in the wing slab was more regular, and with the increase of the thickness of the UHPC slab, the crack distribution gradually shows the characteristic of vertical equidistant distribution, and when the thickness of the wing slab was kept constant and the thickness of the UHPC layer was increased by 50 mm, the yield load increases by 12.5% and the ultimate load increases by 8.3%, and the deflection value corresponding to the ultimate load is reduced by 22%. By analyzing the yield deflection as well as the ultimate deflection of each specimen, it can be seen that the yield deflection tends to increase gradually with the increase of UHPC airfoil thickness, and the proportion of the elastic phase of the combined beam keeps increasing. The comparison of the test data with the theoretical calculation results shows that the calculation results obtained by the sub-stacking method can more effectively reflect the contribution of UHPC layer, ordinary concrete layer, steel box, reinforcement and filled part of concrete to the shear load capacity, and the results are more accurate.

To investigate the impact of polymer polyvinyl alcohol (PVA) and polypropylene fiber on the composite enhancement of loosely piled sandy soil in Southeast Xizang, unconfined compressive strength tests and direct shear tests were conducted. The the effects of the improved sandy soil was understood and the optimal mixing ratio of the improved materials was determined. Additionally, the change in the strength of the improved sandy soil under water erosion after dry and wet cycles was analyzed, and the reinforcement mechanism was investigated. The results demonstrate that the dosage of PVA and polypropylene fibers has a significant effect on the unconfined compressive strength. The best improvement effect is achieved with a dosage ratio of 12% PVA + 0.25% polypropylene fibers, resulting in an unconfined compressive strength of 1 716 kPa. This is 67 times higher than that of sandy soil with an unconfined compressive strength of 25.46 kPa. The shear strength of the improved specimens with different fiber contents increased with the increase of PVA doping. After 10 dry and wet cycling processes, the 12% PVA + 0.25% polypropylene fiber specimen exhibited an unconfined compressive strength of about 748.66 kPa, which was still 91.8% of the strength at 7 days and 1.47 times that of the same age maintenance period of 28 days. Polyvinyl alcohol solution formed a polymer film that adhered to and wrapped the sandy soil, while polypropylene fiber wound and filled the sandy soil. The combination of these two materials improved the stability of the sandy soil, effectively enhancing the bonding strength between soil particles and increasing the compressive strength of the soil body.

The classical earth pressure theory only calculates the ultimate earth pressure in translational mode of the retaining wall. In order to get closer to the real engineering situation, it is necessary to develop the theory of non-ultimate earth pressure of the cohesive fill behind the wall under arbitrary load action and arbitrary displacement mode. The concept of equivalent uniform load was adopted to convert any type of load acting on the earth filling surface into uniform load. Based on the classical earth pressure theory, the rigid retaining wall was regarded as a combination of an ideal rigid plastic body and a series of springs, and the soil stiffness coefficient of the clay was obtained, which improved the Coulomb earth pressure theory and derives the general calculation method of the non-ultimate passive earth pressure of the soil in any displacement mode that can consider the arbitrary load.The research results indicate that the distribution and magnitude of passive soil pressure, the position of the resultant force point are closely related to the displacement mode of the retaining wall, the magnitude of cohesive force, and the load acting on the fill surface. When the equivalent uniform load and cohesive force are both 0, this method degenerates into Coulomb soil pressure theory.The model validation results show that the theoretical calculated values are in good agreement with the experimental measured values, proving that this calculation method has certain theoretical significance for calculating the passive soil pressure of cohesive soil under non limit states, and also has practical value for engineering practice.

SPH (smooth particle hydrodynamics) and MoorDyn numerical model were used to investigate systematically the dynamic behavior of moored floating bodies on stepped seabed. Based on the comparison with the experimental data, the influence of wave height and step height on the motion response and mooring force of moored box floating body on stepped seabed was discussed in detail. The results show that the motion response of the two floating bodies increases with the increase of wave height. The mooring power of the other three cables also show an increasing trend except for L3. As the height of the ladder continues to rise, the two floating bodies above and below the seabed ladder appear different change rules. In addition, it is found that the relationship between L2 mooring and L0 and L1 is about 3 times, and the relationship between L2 mooring and L3 is about 2 times.

To achieve rapid and reliable prediction of asphalt mixture performance, a method for predicting asphalt mixture performance by optimizing the back propagation (BP) neural network with a genetic algorithm (GA) from the perspective of material composition design was proposed. Initially, a grey relational analysis method was employed to reduce the dimensionality of multidimensional input variables, identifying the core influencing factors of asphalt mixture performance. Subsequently, integrating the GA, a GA-BP neural network prediction model was constructed with the core influencing factors as the input layer and asphalt mixture performance as the output layer. The model underwent training, validation analysis, and prediction generalization application. A comparison with the training effectiveness and prediction accuracy of the BP neural network was conducted to verify the accuracy of the GA-BP neural network model. The research results indicate that the grey relational degrees of eight performance characteristics, including air void, asphalt-aggregate ratio, nominal maximum aggregate size, 4.75 mm passing rate, asphalt type, softening point, penetration, and ductility, are all greater than 0.6, signifying their significant impact on asphalt mixture performance. Compared to the BP neural network model, the GA-BP neural network model reduces the root mean square error (RMSE) by 16% to 31%, decreases the mean absolute error (MAE) by 15% to 24%, and improves the R² value by 0.01 to 0.27, indicating that it has better learning and fitting capabilities. The prediction accuracy for dynamic modulus, dynamic stability, residual stability, splitting tensile strength ratio, and ultimate bending strain of the asphalt mixture is respectively enhanced by 35.26%, 47.78%, 23.13%, 31.92%, and 35.75%, revealing the superior generalization application capability of the GA-BP neural network model. The research findings provide essential references for the rapid prediction of asphalt mixture performance and guidance in the design of asphalt mixture material composition.

The dynamic modulus of asphalt mixture is an important parameter in the design of asphalt pavement. Extracting material characteristics, dynamic modulus, and phase angle information from a large amount of asphalt concrete datasets using integrated methods is of great significance for optimizing the performance of asphalt pavement. The extreme gradient boost (XGBoost) model aggregated a series of decision tree models through weighted summation to construct a powerful prediction model, while optimizing the loss function to minimize prediction errors. In order to further improve the accuracy of dynamic modulus and phase angle prediction, heuristic algorithms were used to optimize the model. Initially, the basic model was initialized based on samples and the gradient of the loss function of the training data was calculated. Subsequently, XGBoost utilized gradient details to construct a decision tree model, optimized leaf node weights, and updated the model’s predictions through weighted summation. During this process, heuristic algorithms are used to optimize the optimal parameters of the entire XGBoost model. The experimental results show that the improved XGBoost model outperforms the original model in all performance evaluation indicators, improving the accuracy of predicting the dynamic modulus and phase angle of asphalt mixtures.

In ultra-long-distance rock micro-shield pipe jacking, pipe wall friction is a key factor in determining the size of the jacking force and the arrangement of the intermediate jacking station, and the selection of a good bentonite mud is a key factor in controlling the pipe wall friction. In order to give full play to the polymer bentonite mud in the pipe jacking construction process of lubrication and support, the Chongqing Guanjingkou water conservancy hub project was used as the basis, through orthogonal tests and indoor straight shear test method on the basis of different types of bentonite mud ratio optimization, based on the performance parameters of the slurry, as well as the friction reduction mechanism to derive the optimal type of mud and its ratio. The results show these as follow. Sodium bentonite mud is the optimal type of mud, the ratio of bentonite to water is 14%, guar gum is 0.20%, soda ash is 0.40%, CMC(carboxymethyl cellulose) is 0.40%, PAM(polyacrylamide) is 0.10%, and its friction reduction effect is obvious, it can make the friction coefficient between concrete and gray rock reduced by 35%, which makes the friction between the pipe and the rock greatly reduced in the process of pipe jacking in the rock.

In order to reasonably and efficiently carry out the risk assessment of road tunnel construction collapse, the risk assessment model of road tunnel construction collapse was studied by rough set (RS), grid search method(GS) and support vector classification (SVC). Firstly, the index system of highway tunnel construction collapse risk evaluation was constructed by integrating advanced geological prediction. At the same time, the information of 100 tunnel collapse cases was collected and the index data was discretized. Secondly, attribute reduction was conducted based on the condition information entropy of rough set to obtain the reduced core index set. Then, grid search method was used to find the optimal parameters of the support vector classification training set, the risk assessment model of highway tunnel construction collapse based on rough set-grid search-support vector classification (RS-GS-SVC) was established. Finally, the model was used to predict the test samples. The results show that under the condition of the same learning sample, compared with rough set-genetic algorithm-support vector classification (RS-GA-SVC) model and Rough set-particle swarm optimization-support vector classification (RS-PSO-SVC) model, RS-GS-SVC model has higher classification accuracy; Under the same proportion of training set and test set, the prediction accuracy of RS-GS-SVC model is higher than that of GS-SVC model, with the accuracy rates of 93.33% and 90% respectively, and the operation time of RS-GS-SVC model is shorter. It can clearly be seen that the model complexity is effectively reduced and the classification accuracy is improved through the reduction of rough set conditional information entropy attributes.

Land use and traffic safety is a hot topic of mutual concern in the fields of urban geography and transportation. However, existing research on the impact of land use on pedestrian traffic accidents often incorporates a unified framework of built environment and mainly adopts measures such as land use mix or the proportion of land use types, lacking detailed analysis on land use types, thus making it difficult to translate their findings into actionable design strategies. Taking Yuzhong District, Chongqing City as an example, the land use types were finely characterized based on point of interest (POI) data, and the extreme gradient boosting (XGBoost) model was applied to explore the nonlinear relationships between land use types, pedestrian, road conditions, road environment, and the severity of pedestrian traffic accidents. The study finds these as follows. ①Land use types play an important role in the severity of pedestrian traffic accidents, with hospitals, residential areas, and educational land being the most influential. The presence of hospitals, residential areas, and educational land within a 300-meter buffer zone around accident sites reduces the severity of pedestrian traffic accidents. ②Road sections with curved and sloped road alignments are high-risk areas for severe pedestrian traffic accidents; entrances and exits of road sections, narrow road sections, and intersections have a mitigating effect on the severity of pedestrian traffic accidents. The findings provide policy insights for refined land use planning and governance to reduce the severity of pedestrian traffic accidents.

The narrow passageways and limited visibility in large underground parking lots often lead to vehicle collisions at blind intersections, posing significant dangers. In order analyze approach behavior at these intersections, a driving simulation experiment was designed. The experiment involved constructing a 3D model of the underground parking lot and integrating it with a connected vehicle warning information system. Four experimental scenarios were devised, considering variations in technical features (with or without warning information) and events (with or without vehicle conflicts at blind intersections). Using micro-driving behavior data from 31 participants, key metrics such as speed, acceleration, and braking position were selected to analyze approach behavior from the warning point to the blind intersection. Subsequently, correlation analysis was conducted, followed by the application of the k-means method to cluster driver types and examine the effects of warning information on the approach behavior of different drivers. Finally, the utility of the system was evaluated. The results indicate the following. ①When drivers approached blind intersections without warning information, the process typically involved three stages: speed maintenance, speed increase, and emergency braking. In contrast, when warning information was provided, speed decreased more uniformly and was 34.08% higher than without warning information. ②The warning information system reduced the average speed by 9.94 km/h compared to scenarios without warnings, and advanced the braking position by 4.49 meters, thereby effectively enhancing the safety of drivers passing through blind intersections in parking lots. ③The warning information system had discernible effects on conservative and general drivers, suggesting the need for additional training for radical drivers to help them understand the positive role of the warning system in improving driving efficiency and promoting safe driving practices. ④The warning information system significantly improved overall driver safety, with the greatest impact observed among conservative drivers, followed by ordinary and aggressive drivers. These research findings provide support for the application of connected vehicle warning information systems in parking lots and contribute to the enhancement of parking lot safety.

A comprehensive joint optimization solution was proposed to address the issue of traditional UAV(unmanned aerial vehicle)-assisted wireless sensor network data collection schemes, where only UAV energy consumption was optimized, while wireless sensor energy consumption is neglected. Firstly, clustering analysis was performed using the K-means algorithm and communication threshold between UAVs and wireless sensors to achieve effective clustering of wireless sensors. Secondly, a multi-objective optimization model was constructed to collaboratively optimize sensor energy consumption and UAV hovering energy consumption. The optimal UAV hovering position and wireless sensor transmission power were determined using a multi-objective particle swarm optimization algorithm. Finally, based on the optimal hovering positions of UAVs in each cluster, an ant colony algorithm was applied to compute the optimal flight path of UAVs, minimizing UAV’s flight energy consumption and thus minimizing the overall energy consumption of the entire data collection system. Simulation results indicate that the proposed solution achieves significant improvements in system energy consumption compared to traditional methods. Specifically, when the clustering radius is 120 meters, sensor energy consumption is reduced by 16.2%, and UAV energy consumption is reduced by 24.9%.

In order to analyze the effect of fan rotor blade leading edge erosion on the aerodynamic characteristics of the compression system for different internal and external culverting conditions, multilevel cascade calculations were used to investigate the changes in the aerodynamic characteristics of the compression system of a certain type of engine with large culverting ratio. The results show that the total pressure ratio, isentropic efficiency and channel flow rate of the engine compression system after leading edge erosion relatively decrease by 0.18%, 0.879% and 0.972%, respectively, under the peak efficiency point working condition. For fan rotor blades, leading edge erosion leads to a decrease in the slope of the surface static pressure coefficient curve in the axial 0~24% interval of the surface static pressure coefficient curve at the height of 95% of the blades under near-surge point conditions in the outer culvert channel, with a decrease in static pressure, and an increase in the slope in the axial 24%~40% interval, which reduces the loading of the blade, reduces the pressurizing capacity, and moves the surge wave forward.In addition, leading edge erosion increases the angle of attack of the overall fan blade at the near-surge point of the outer culvert by about 2°, resulting in changes in blade aerodynamic efficiency and stall margin, which deviates from the original blade design.

The accuracy and confidence level of the unmanned aerial vehicle(UAV) landing range are of great significance for objectively assessing the UAV’s ground risk. The uncertain wind field and complex electromagnetic environment are the main causes of uncertainty regarding UAV failure and landing range. Given the particle assumption in the case of complete failure of the UAV, firstly, a dynamic model of the UAV trajectory descent with the initial position and velocity as the boundary value and the wind speed vector and the initial position as random variables was constructed, and the failure and landing range of the UAV were determined by Monte Carlo simulation. Secondly, a geometric method for determining the envelope of the UAV ground risk buffer was proposed, and the quantitative determination of the ground risk buffer of the entire UAV track was realized. Finally, the method proposed was verified by taking an aerial inspection route as example and compared with the buffer protection area of the UAV in different wind fields and under various operating conditions, the effect of uncertain wind field and its operating conditions on the ground crash range of the UAV was studied, and the ground risk buffer zone under different operating conditions was established. The results show that falling at higher speed and higher altitudes under stronger winds yields a wider impacting area and a larger ground risk buffer.

ARGs(antibiotic resistance genes) as emerging environmental pollutants threaten human health, and studies show that secondary effluent from sewage treatment plants is an important source of ARGs in the environment. Ozone pre-oxidation combined with PAC(powdered activated carbon) and UF(ultrafiltration) was used to treat the secondary effluent from the wastewater treatment plant, and the factors and mechanisms of O₃ dosage, pH, and temperature on the removal of different forms of ARGs in the secondary effluent were investigated. The results show that ARGs could be more effectively removed by PAC adsorption and UF after oxidative inactivation by O₃; under the condition of optimal O₃ dosage (2.0 mg/L), the combined O₃-PAC-UF process could remove different types of ARGs (tetA, tetC, tetG, sulI, sulII) and other pollutants (intⅠ1, 16S rRNA) from the secondary effluent. The removal of different types of ARGs (tetA, tetC, tetG, sulI, sulII) and other pollutants (intⅠ1, 16S rRNA) by the combined process is 10^2.67~10^3.92 copies/mL, and the removal of cellular and free ARGs is significantly enhanced; the elevated pH and lower temperature facilitate the removal of ARGs; the direct oxidation of O₃ molecules dominate the removal of ARGs in the secondary effluent. In conclusion, ozone combined with PAC and UF can effectively remove antibiotic resistance genes from secondary effluent.

To evaluate the safety of navigation flight task scheduling schemes in forest fire rescue, safety evaluation indicators for navigation rescue task scheduling schemes were proposed by detecting the flight path conflicts of various general aircraft. Using an airspace grid model to model the rescue flight environment, and planning the rescue flight paths of aircraft with different performance constraints based on their respective task scheduling schemes, and conducting trajectory conflict detection to evaluate the safety of the task scheduling scheme. The simulation results show that this method has a 53.8% improvement in time efficiency compared to the direct conflict detection algorithm, and a 6.7% improvement in accuracy compared to the efficient spatiotemporal synchronous route conflict detection method. It can be seen that this method can efficiently and accurately predict track conflicts in rescue flights and evaluate the safety of task scheduling schemes, providing effective decision support for navigation rescue command and scheduling work.