Gaseous detonation is a method to obtain nanomaterials in a short time by gas explosion, which has been successfully applied to the preparation of carbon nanomaterials and oxides. Compared with other nanomaterials preparation methods, gaseous detonation method has the advantages of high efficiency, convenience, high yield and green environmental protection. The instrumentation and operation procedures required for the preparation of nanomaterials by gaseous detonation were described. Secondly, the morphology, structure, and performance characteristics of carbonaceous nanomaterials and metal oxide nanomaterials prepared by gaseous detonation were presented. At the same time, the current status of the growth mechanism of nanomaterials was analysed and summarized. Moreover, the progress of the research on nanomaterials prepared by gaseous detonation in the areas of photocatalysis, electromagnetic wave absorption, and friction resistance was summarized. Finally, the application potential and technological prospect of the gaseous detonation method and the nanomaterials prepared by the method were discussed, which can provide a useful reference for the industrialised large-scale synthesis of nanomaterials by the gaseous detonation method.

In recent years, digital class D power amplifiers have attracted widespread attention in the audio electronics field due to their high efficiency and seamless integration with digital audio sources. As one of the crucial digital signal processing modules in digital class D amplifiers, the Sigma-Delta modulator plays a pivotal role for digital audio signal processing. The noise-shaping characteristic of the Sigma-Delta modulator can reduce the implementation cost of the power amplifier system while maintaining or even improving the output signal-to-noise ratio of the system, and can suppress the noise introduced by some signal transmission paths. Firstly, the working principle and mainstream architecture of digital D-class power amplifiers were summarized. Then, based on the basic principle of Sigma-Delta modulators, the design schemes of Sigma-Delta modulators used in digital D-class power amplifiers in recent years were discussed, with a focus on the architecture design and noise transfer function design of Sigma-Delta modulators. Finally, the research and development of Sigma-Delta modulators for digital D-class power amplifiers were summarized.

The tension string system with concentrated viscous damping belongs to a hybrid dynamic system in mechanical models. Approximate methods are typically used to solve its inherent problems for engineering applications. In order to further clarify the vibration characteristics of the system, two centrally damped symmetrical damping string systems were taken as the basic research object, and their complex eigenvalues were solved analytically. The complex frequency equation and the eigenvalue expression of the system were derived, and the transformation of the complex frequency equation beyond the function form was treated as algebraic form, and the explicit solution of the complex eigenvalue of the system was given by the algebraic equation. The structure and properties of the complex eigenvalues of the system were analyzed, and the variation of vibration characteristics with damping coefficient was discussed. The results show that the eigenvalue solution of the system can be divided into three branches, in which the real part of the eigenvalue(the inverse is the decay rate) does not change with the order of the system motion, but the imaginary part of the eigenvalue(the frequency) increases with the order of the motion. The decay rate curves corresponding to each solution branch increase first and then decrease with the damping coefficient, and in the damping range of the decay rate curve, the frequencies of each order of the system are equal.

Addressing the challenge of insufficient accuracy in building regional cultural heritage 3D models using single-image modeling techniques, a method for optimizing regional ancient architectural three-dimensional models through the fusion of laser and imagery was proposed. Initially, imagery data of the target area was acquired through drone-based cross-flight aerial photography combined with close-range photography. Subsequently, laser scanning data was obtained using a 3D laser scanner to cover blind spots from drone aerial photography. Then, the laser scanning data was fused and registered with the imagery data to generate a complete point cloud model of the target area, which is then used to reconstruct a refined 3D model of the regional cultural heritage. Finally, the superiority of the proposed method was validated through error analysis of the fused heterogeneous data and comparative analysis of accuracy and texture completeness with single-image modeling results. The results indicate that the fused heterogeneous data achieves high fitting accuracy, and the resulting regional ancient architectural 3D model exhibits high accuracy and texture completeness, thereby providing valuable technical reference for the detailed modeling of ancient architectural complexes within the target scope and holding broad application prospects in enhancing the digital archive storage of ancient architectural three-dimensional models.

The scientific extraction of urban built-up area information and the exploration of the spatial-temporal characteristics of urban expansion have significant relevance for urban planning and management. The local-optimal thresholding method was refined for the quantitative extraction of urban built-up area information within the Baiyangdian Basin, and the extraction process utilized PANNDA nighttime light data and Landsat series data from four periods: 1990, 2000, 2010, and 2020. Subsequently, an analysis of the spatial-temporal characteristics of urban built-up area expansion in the basin over the past 30 years was conducted using the urban expansion index and landscape index. The results show the optimized local-optimal thresholding method is successfully used to extract the data of the built-up areas in the basin for all phases, and it is confirmed that the method exhibits enhanced applicability compared to its pre-optimization state. The urban built-up area in the Baiyangdian Basin experienced significant expansion throughout the study period, with a growth rate of 154.48%. The sizes of the built-up areas across the 35 cities in the basin exhibited high heterogeneity. Temporally, the expansion of urban built-up areas predominantly exhibited an accelerating trend, with a widening disparity in the pace of expansion among the cities within the basin. Spatially, the built-up area to the left of the Zhengding-Zhuozhou line was less developed than that to the right. Notable expansion trends were observed in municipal districts or county-level cities such as Lianchi District, Jingxiu District, and Gaobeidian City. Based on the results of the landscape index, the expansion of urban built-up areas in Baiyangdian Basin shows the spatial characteristics of “dispersion-fusion” during the study period, and the boundary of built-up areas showed the evolution characteristics of “regular-complex-regular”.

The Loess Plateau, as a natural ecological barrier in the western region of China, has made positive contributions to the sustainable development of the nation. The governance and restoration of the ecological environment on the Loess Plateau (Gansu region) plays a critical role in the implementation of China’s ecological civilization construction strategy. To monitor the changes in forest resources on the Loess Plateau (Gansu region) from 2008 to 2018, based on cloud platform, Landsat, PALSAR, and terrain data were integrated to explore the advantages of spectral index, backscatter, texture, and terrain features in obtaining forest resource information. The random forest feature selection algorithm was utilized to obtain the spatiotemporal distribution of forest cover in the study area for 10 years, and factor detection was conducted using geographic detectors. The results indicate that the random forest feature selection algorithm can effectively screen important feature information, with an overall accuracy of 91.88% and a Kappa coefficient of 0.91. The experimental scheme that integrates Landsat, PALSAR, and terrain data presents significantly higher accuracy compared to the forest classification results using a single data source. The overall accuracy of the four classification results is 86.65%, 88.23%, 90.15%, and 89.86% respectively. Over the past 10 years, the net increase in forest area in the study area is 0.60×10⁴ km². The areas with increased forests are primarily distributed in the central and eastern parts of Qingyang City, Pingliang City, Tianshui City, and the western region of Linxia Hui Autonomous Prefecture, while forest degradation primarily occurs in the southwestern part of Dingxi City and the central and eastern areas of Linxia Hui Autonomous Prefecture. In single-factor detection, land use type is the dominant factor in forest cover change, and the spatial distribution of suitable soil type and the auxiliary effect of rainfall provide favorable natural conditions for the survival rate of afforestation and the healthy growth of forests.

Henan Province has abundant geothermal resources, with the northern and central regions having undergone extensive exploration and large-scale development. However, the southern region of Henan has been subject to limited exploration efforts, resulting in a scarcity of drilling data. Consequently, research on its structural characteristics, stratigraphic distribution, geothermal geological characteristics and resource potential is relatively underdeveloped. This knowledge gap poses challenges in meeting the demands for industrialization and large-scale development. Based on regional geological characteristics and two-dimensional seismic interpretation results, the research on geothermal geological characteristics, resource evaluation and favorable area prediction in Zhumadian area were carried out on the basis of previous studies. The results show that Zhumadian structure is located in five secondary structural units: Wuyang Depression, Zhumadian-Huaibin Depression, Pingyu Uplift and Changshan uplift in the southwest of Zhoukou Depression and Biyang Depression in the east of Nanxiang Basin. In Zhumadian area, the geothermal geological conditions are poor in Zhengyang and Chishan, which are located in the uplift area of Changshan Mountain. There are three sets of stratified heat reservoirs in Neogene, Paleogene sandstone and Cambrian-Ordovician carbonate rocks in this area, and the total static resources are about 115×10¹⁵ kJ. It is predicted that Biyang County urban area, Xincai County urban area and the west of Yicheng District are the most favorable areas for geothermal resources development, with moderate depth of heat storage, large water inflow and high temperature.

The current seismic toughness assessment is mainly aimed at the impact of a single earthquake on a single building, it is difficult to consider the seismic toughness assessment of different buildings in the same area. The research area was divided into grids according to 500 m×500 m, and seismic risk analysis was carried out. Six indexes, including the cost of building defense, damaged area of different degrees, direct economic loss of buildings, repair time, repair cost and casualties, were taken as the evaluation indexes of earthquake resilience. Analytic hierarchy process (AHP) was used to determine the weights of each index, and an earthquake resilience evaluation model based on grid and radar map was established and applied to Chengdu City. The results show that the earthquake toughness of Chengdu City is normal when the fortification is not upgraded. After upgrading the fortification, the cost of fortification increases by 45.95%, and the damaged area, the direct economic loss of the house, the repair time, the repair cost and the number of casualties decreases by 26.25%, 37.75%, 45.1%, 44.24% and 48.18%, respectively. Through comparative analysis of the model data, it is found that after upgrading the fortification, the comprehensive benefit of earthquake resilience of Chengdu City buildings is increased by 40.8%, the disaster loss is greatly reduced, and the improvement effect is obvious.

The Box-Behnken experimental design and response surface methodology were employed to optimize the preparation of the aspirin micro-porous osmotic pump tablets. The core of the tablet was prepared with aspirin and β-CD inclusion, then osmotic pump tablets were obtained by coating a layer of cellulose acetate containing PEG 4000 as porogenic agent. The in vitro release test shows that the aspirin inclusion complex microporous osmotic pump tablets prepared by this process has a cumulative release rate of 1.5% and 1.6% within 0~2 h in artificial gastric juice compared to commercially available aspirin enteric coated tablets. After adjusting the release medium to pH 6.8, there is no significant difference in the cumulative drug release between the two formulations at 10 h. And the inclusion complex microporous osmotic pump tablet shows zero order release and complete release within 12 h(cumulative release rate > 90%), indicating the possibility of reducing drug damage to the gastric mucosa.

To explore the effects of weak mineralized water and straw separation treatment on soil water and salt transport, through indoor soil column infiltration and evaporation test, the distribution of water and salt in soil under the irrigation condition of fresh water and slightly mineralized water with different salinity (1, 2, 3 g/L) at the buried depth of 0, 10 and 20 cm of straw interlayer was studied. The results show that there is a power function relationship between the wetting front and the infiltration time at the infiltration stage. The water infiltration rate increases with the increase of salinity, and the cumulative infiltration decreases with the increase of salinity. Kostiakov model and Philip model are used to fit the cumulative infiltration amount and infiltration time respectively, and the fitting results are good. During the evaporation stage, the straw interlayer has a significant water retention effect on the soil below the buried depth, and the vertical distribution of soil salinity shows a significant low desalination effect, and salt accumulates in the straw interlayer. When the salinity of irrigation water is 2 g/L and the depth of straw layer is 10 cm, it is conducive to soil bottom desalting, and has a better effect of promoting soil water infiltration and water retention. The research can provide basis and reference for weak mineralized water irrigation and the exploitation and utilization of straw resources.

In order to investigate the properties of seawater mixing alkali-activated materials, the development law of hydration reaction, mechanics and corrosion resistance of seawater alkali-activated materials based on multi-component composite cementitious materials was studied. The results show that seawater mixing has a certain inhibitory effect on the hydration reaction of alkali-activated slag, and the compressive strength of SLCM at different ages also shows a decreasing trend to a certain extent, which is not conducive to the development of strength. Fly ash and silica fume can reduce the hydration reaction rate, early strength and toughness of the seawater alkali-activated materials, but their strength and toughness increase potential is significant in the later period, in which the strength and toughness growth rate of the silica-fly ash-slag terpolymer system from 7 days to 28 days reaches 50.9% and 86.7%, respectively. Compared with alkali-activated slag, adding fly ash and silica fume can improve the electric flux permeability and chloride ion mobility coefficient of alkali excited materials in seawater to a certain extent, which is consistent with their microstructure, but the three still belong to the same chloride ion permeability grade, i.e., medium permeability grade (electric flux method).

In order to study the prevention and control of power disaster induced by coal mining process, Brazilian splitting test of raw coal specimen was carried out to study the energy evolution law in the process of coal body tensile damage destruction, and the precursor information of coal body destabilization and destruction was identified. The results show that the coal body tensile damage process has significant nonlinear evolution characteristics, and it is possible to identify the critical point, destabilization point, and damage point of coal body damage. The energy evolution characteristics of coal body tensile damage in each stage are significantly different. In the elastic deformation stage, the input energy is mainly converted into elastic energy, and the dissipation energy remains stable, while in the destabilization stage, the dissipation-elasticity ratio shows a jumping growth. By calculating the energy release rate and energy dissipation rate, it is found that the index has abnormal response characteristics at the critical point, destabilization point and damage point of the coal body tensile process, and the appearance of the characteristic points all have significant precursor information. The nature of coal destabilization is the result of energy accumulation and dissipation, and the energy index of coal body can reveal the abnormal characteristics of energy evolution in the process of damage and destruction of the specimen, and identify the precursor information of coal body catastrophe, which is conducive to the over-warning, and escort for the safe mining of coal.

In order to accurately predict the water richness of the weathered bedrock aquifer, 28 groups of weathered bedrock pumping test borehole data in Zhangjimao minefield were used as training and verification samples, and the lithology combination index, weathering index, thickness, core recovery rate and burial depth of the weathered bedrock were selected as evaluation indexes. Based on whale optimization algorithm-support vector machines (WOA-SVM), a water-rich identification model for weathering bedrock aquifers was proposed. This model can predict the water-rich grade of the weathered bedrock in the area without pumping test data, and realize water-rich zoning of the weathered bedrock in the well field by comprehensive use of the geological information of 249 exploration boreholes. The study shows that the weathered bedrock of Zhangjiamao minefield is weakly water-rich as a whole, and its spatial distribution is uneven. There are strong water-rich areas in the central part of the field and the local area along Wulanbula Gully, but their distribution range is small, there are some moderately water-rich areas in the central-western and southeastern parts, and the northeastern and southwestern areas are weakly and very weakly water-rich almost all the time. The results predicted are more in line with the actual situation, and the research results can provide a reference for the safe production of the mine and a new way of thinking for the prediction of the water-richness of the weathered bedrock.

The pore structure of deep tight sandstone reservoir is complex and heterogeneous, and it is difficult to determine the influencing factors of pore microscopic parameters on the characteristics of gas-water phase permeability. Based on the fractal geometry theory, combined with the core mercury intrusion porosimetry (MIP) method, nuclear magnetic resonance (NMR) T₂ spectroscopy test and micron CT scanning results, the micro-pore throat parameters and various scale fractal dimensions of the reservoir were obtained. Through the mobile gas porosity and the maximum atmospheric phase relative permeability, the control mechanism of the fractal dimension and micro-pore throat structure parameters on the gas-water phase permeability characteristics was discussed. The results show that mercury injection and NMR fractal curves have obvious “three-stage” characteristics, and the total shape dimension of the reservoir describes the distribution of seepage and movable fluid more accurately when gas and water coexist. The maximum mercury saturation, average pore throat radius, total reservoir shape dimension and displacement pressure have significant effects on the mobile gas porosity during gas seepage. The average pore throat radius has a significant influence on the maximum effective gas phase relative permeability in gas seepage. The control mechanism of the micro-pore structure on the gas-water phase permeability can provide a powerful guide for the efficient development of water-producing gas reservoirs.

The effect of water flooding development in low permeability reservoir is generally poor, and CO₂ flooding can effectively improve the degree of crude oil recovery. In order to analyze various factors affecting the effect of CO₂-assisted gravity flooding, based on the research mechanism of gas-injection-assisted gravity flooding, a mechanism model of one injection and one production was established to analyze the influence law of geological factors and development factors, and the orthogonal experimental design method and Shapley value method were used for multi-factor analysis. The results show that the positive rhythm reservoir is more suitable for CO₂-assisted gravity flooding. Reservoir dip angle, average permeability and gas injection velocity are positively correlated with development effect. The ratio of vertical permeability to horizontal permeability and the difference of permeability stage were negatively correlated with the development effect. If the ratio of gas injection and dimensionless horizontal well section length is set to 0.8, the CO₂-assisted gravity flooding effect can be effectively improved. The ratio of vertical permeability to horizontal permeability has the highest influence on CO₂-assisted gravity flooding. The research results provide technical guidance and theoretical support for improving the development effect of CO₂-assisted gravity flooding in low permeability reservoirs.

In order to clarify the reservoir applicability of different acid systems, understand the influence of reservoir acid rock etching morphology on fracture conductivity, and give the optimal slug combination method for different horizons, acid erosion fracture conductivity experiments were carried out in the carbonate reservoirs of Sichuan and Chongqing, the results show that the conductivity of slug combinations between different acid systems to the dolomite of the Maokou Formation after acid etching is higher than that of the limestone. The morphology of acid-etched fractures after acid-etching is different between different single-acid systems, in which steering acid has extremely deep grooves after etching, and the grooves of authigenic acid are the shallowest. For Maokou Formation, when the alternation between gelling acid and fracturing fluid and the alternation between gelling acid and authigenic acid is tertiary, the conductivity is the highest, and the conductivity reaches 4.53 μm²·cm at 60 MPa after tertiary alternation between gelling acid and authigenic acid. The conductivity of Qixia Formation and Dengying Formation is the highest when secondary alternation of fracturing fluid and gelling acid was selected, and the conductivity of Qixia Formation and Dengying formation are 6.72 μm²·cm and 7.47 μm²·cm at 60 MPa, respectively. In the Sichuan Chongqing exploration area, on-site application and in-depth investigation were conducted to verify the acid corrosion fracture conductivity of the acid solution. The results show that the acid corrosion effect is good after the acid solution entered the well, and the gas testing effect after the transformation is 208×10⁴ m³/d, achieving the expected increase in production. It provides theoretical and experimental guidance for acid fracturing technology of carbonate reservoirs in Sichuan and Chongqing.

In order to study the solution properties of polyacrylamide at high temperatures at the molecular-atomic scale, the molecular models of partially hydrolyzed polyacrylamide(HPAM) and AM/AANa/AMPSNa copolymer [P(AM/AANa/AMPSNa)] have been established through a combination of experimental methods and molecular dynamics simulations. The solution properties of the two polymers at elevated temperatures were systematically investigated in terms of polymer chain rigidity and flexibility, hydrogen bonding, hydration layer, interaction energy and the effect of salt cation, and the micro-mechanism of temperature resistance of P(AM/AANa/AMPSNa) was explained. The results show that the introduction of side chains containing methyl and sulfonated groups into the molecular chain of P(AM/AANa/AMPSNa) could increase the rigidity of the molecular chain, more hydrogen bonds are formed between sulfonated groups and water and has longer lifetime. At the same time, the strong polar sulfonic acid group makes the hydration layer denser, which results in the weaker static shielding effect of the cations on the P(AM/AANa/AMPSNa). Under different temperature conditions, P(AM/AANa/AMPSNa) has stronger intermolecular non-bonding interactions, stronger water retention effect of the molecular chain at the microscopic level, and higher viscosity at the macroscopic level.

As China’s mountainous regions host more and more gas pipelines, incidents involving natural gas leaks that cause harm to the environment or injure people are growing increasingly common. To investigate the diffusion behavior and vertical hazard distance of leakage gas in mountainous regions, a three-dimensional model of pipeline-soil-air was created with CFD software. The impacts of various obstructions, soil types, burial depths, leak hole shapes, and leak directions on the propagation of natural gas pipeline leaks and hazard distances were studied separately. The results show that in proportion to the direction angle between the buoyant force and the leakage hole, the vertical hazard distance and the rate of gas diffusion to the ground decrease. Diffusion rates and hazard ranges are larger for square and triangle leaking holes compared to circular ones. As soil porosity and granularity increase, the rate at which escaping gases diffuse into the soil increases steadily. The time it takes for the gas leak to release will vary depending on the burial depth, and as soil burial depth increases, so will the vertical hazard distance. Obstructions will alter the diffusion path of the leaking gas and accelerate the vertical hazard distance. Culverts will allow the gas to accumulate in the ditch to form an area of high concentration.

Aiming at the problem of effective extraction and identification of rolling bearing fault information in complex environments, a fault diagnosis method for rolling bearings based on feature mode decomposition (FMD) combined with multiscale fuzzy dispersion entropy (MFDE) and zebra optimization algorithm (ZOA) optimization support vector machine was proposed. In order to solve the problem that the key parameters in FMD are not adaptive, the minimum envelope entropy was used as the objective function, and the beluga whale optimization (BWO) was used to optimize FMD to find the optimal parameter combination to achieve the optimal decomposition of fault signals. Multiscale fuzzy dispersion entropy was introduced to construct the eigenvectors under different modes after decomposition. Finally, the feature vectors were input into the support vector machine for training and recognition. The effectiveness of the proposed method was verified by the public dataset and the self-made experimental platform dataset.

The drilling process requires real-time measurement of drill string vibration, which is crucial for drilling and downhole safety. However, the traditional power supply mode used for downhole vibration sensors has been found to increase drilling costs and reduce drilling efficiency. Therefore, sensors with self-powered capabilities are considered more suitable for practical conditions. A downhole arrayed self-powered deformable vibration sensor was proposed based on the principle of triboelectric nanogenerators. Experimental results demonstrate that the sensor synchronized measurements of amplitude and frequency. The vibration frequency is measured within a range of 0 Hz to 11 Hz, with a measurement error of less than ±4%. Additionally, the sensor is able to measure three discrete amplitude values (10, 25, 40 mm) with a measurement error of ±3 mm. The sensor can working normally within a temperature range of 0 ℃ to 85 ℃. Furthermore, the sensor has power generation capabilities, with experiments revealing a maximum output power of 8.3×10^-7 W. Notably, when multiple sensors are used in parallel, the power generation capacity is significantly enhanced. These research findings provide new insights for the development of downhole sensors and downhole generators.

The magnetic flux leakage detection technology has been widely used in the field of ferromagnetic material defect detection, in which the magnetic dipole method is currently the most widely used mathematical method for predicting magnetic flux leakage from structural defects. The magnetic dipole method is primarily employed for predicting the magnetic flux leakage signal of regular defects. The unit magnetic dipole band superposition model can be used to predict the magnetic flux leakage signal of complex defects. The magnetic charge density of complex defects needs to be calculated when the model is used for prediction. However, the magnetic charge density distribution of complex defects is inhomogeneous, and the calculation is complex. Therefore, a calculation method of discrete magnetic charge density field was proposed for calculating the magnetic charge density of three-dimensional irregular defects. The computational complexity of the model was reduced by using this method and the magnetic flux leakage signal of three-dimensional irregular defects can be quickly and exactly obtained. Comparison between the signal predicted by the unit magnetic dipole band superposition model based on discrete magnetic charge density field and the signal simulated by COMSOL software demonstrates the feasibility of the method. Experimental results show that the prediction performance of the model has been significantly improved by using this method, the maximum prediction error is reduced by 90.08%, and the calculation time is reduced by 97.43%, thus a fast and effective solution for the calculation of the magnetic charge distribution of three-dimensional irregular defects is provided.

A geomagnetic storm is a periodic natural disaster in which the changing geomagnetic field can induce an induced geoelectric field. A geomagnetic induced current (GIC) loop is formed between the transmission line and the earth conductor through the neutral points of grounding transformers. GIC seriously threatens the safe and stable operation of extra-high and ultra-high voltage AC transmission systems. There are many types of terrain and complex structures in our country, which makes the influence of geological landforms on induced geoelectric fields very significant. A finite element calculation method for GIC was proposed based on a three-dimensional earth conductivity model to address the difficulties in modeling and calculating GIC. Firstly, a three-dimensional earth conductivity model was established considering the anisotropy of geological structures. Meanwhile, a calculation model for electromagnetic field penetration depth under multi-layer geological conditions was given. Secondly, a mathematical model based on time-varying electromagnetic fields was established. Combined with the topology of the power grid, an equivalent calculation model for the power grid GIC was derived. Finally, taking the Shache-Turpan 750 kV transmission line in Xinjiang area as an example, a corresponding physical model was built in COMSOL Multiphysics finite element simulation software. The three-dimensional distribution of the induced ground electric field in the power grid was obtained through geometric modeling, boundary condition setting, grid division, and iterative solution. Furthermore, the GIC flowing through the neutral point of the 750 kV transformer was obtained. The research results indicatethat the overall level of GIC obtained by the 3D model is higher than that of the 2D model. Besides, the 3D model considers the geometric angle between the transmission line and different terrains, which can provide a more detailed distribution of induced geoelectric fields. The research results verify the effectiveness of the method proposed, which provides a reference basis for scientific planning of ultra-high and ultra-high voltage transmission corridors.

In order to solve the influence of intermittent and fluctuating wind energy on the economy and reliability of the system, a day-ahead and real-time energy management strategy for islanded wind power hydrogen production system with energy storage battery was proposed. In the day-ahead energy management stage, the energy management strategy of alkaline electrolytic cell power classification was adopted, and the economic energy management model of isolated wind power hydrogen production system was established with the maximum daily profit of the system as the objective function. An improved grey wolf optimization algorithm was proposed to solve the system energy management model, optimize the system energy flow and improve the system economy. In the real-time energy management stage, in order to ensure that the system can maintain stable operation when unplanned power fluctuations occur, a real-time energy management strategy for island wind power hydrogen production system based on condition identification was designed, which can adjust the system operation status in time according to the real-time operating conditions of the system. The experimental results show that the day-ahead energy management based on the improved grey wolf optimization algorithm effectively increases the daily revenue of the system and improves the economy of the system. The real-time stage energy management based on condition identification can maintain the system power balance when the wind power fluctuates under the day-ahead plan, and realize the stable hydrogen production of the electrolytic cell throughout the day.

With the transition from traditional centralized power systems to distributed energy systems, harmonics are produced due to the penetration of renewable energy, resulting in additional losses. Distribution network loss accounts for more than half of the total system loss and is the focus of network loss reduction. A network reconstruction method based on improved binary particle swarm optimization algorithm was proposed to reduce distribution network loss. Firstly, considering the influence of harmonic wave on network loss and the harmonic effect of the line under high frequency current, the line impedance was modified. Then, the total loss of the network was calculated using the corrected impedance, and a probabilistic reverse learning approach suitable for binary algorithms was creatively proposed, integrating the theory of the good point set to obtain uniform and diverse initial particles. Finally, taking the modified 33 node power system as an example, the optimization objective was to minimize the total loss and obtain the optimal topology structure of the distribution network. The experimental results show that the distribution network reconstruction considering harmonic factors has played a good role in reducing the loss of distribution network.

A method for optimizing the control parameters of the sample point distribution state within the framework of the unscented transform (UT) for the unscented Kalman filter (UKF) was introduced. The issue of abnormal filtering performance arising from the state of sample point distributions was addressed by this method. A multi-strategy improved sparrow search algorithm(ISSA) was employed to finely tune the control parameters. The goal is to enhance the distribution of Sigma points, thereby improving the effectiveness of nonlinear approximations and ultimately enhancing the accuracy of filtering estimations. To address the shortcomings of traditional sparrow search algorithms, several refinements were implemented. Initially, a Cubic chaotic mapping was applied to diversify the initial population. Furthermore, during the exploration phase, a nonlinear adaptive convergence factor was introduced to balance the algorithm’s capacity for global exploration and local exploitation. Additionally, a wavelet mutation strategy was integrated into the follower phase to prevent blind adherence to specific paths and mitigate the risk of becoming trapped in local optima. Lastly, an adaptive t-distribution perturbation capability was introduced to strengthen the algorithm’s ability to perform wide-ranging global searches. The efficacy of the proposed ISSA was demonstrated through simulation experiments conducted on various test functions. The results consistently show that ISSA outperforms other methods in terms of convergence and solution accuracy. Furthermore, the benefits of ISSA are extended to the optimization of parameters within the UKF algorithm. Experimental outcomes indicate that the ISSA-UKF algorithm reduces the root mean square error (RMSE) of position by 52.2% and the RMSE of velocity by 21.9%, thus affirming the viability and effectiveness of the proposed enhancements.

The path planning problem of electric vertical takeoff and landing (eVTOL) aircraft in urban scenarios was studied. Firstly, a three-dimensional urban space model was constructed using the hazard grid method. Considering the selected model of eVTOL, with range, operational risk, and altitude variation as objective functions, a path planning model for manned eVTOL with multiple constraints was developed, taking into account the characteristics of the aircraft and environmental limitations. Subsequently, an improved artificial electric field algorithm (IAEFA) was proposed, which enhances the traditional artificial electric field algorithm (AEFA) by introducing an adaptive Coulomb parameter and incorporating a decreasing coefficient in the Coulomb constant calculation for simulation-based solution. Experimental results demonstrate that the constructed model achieves the expected outcomes. The solution effectiveness of path planning using the improved algorithm surpasses that of traditional particle swarm optimization and artificial electric field methods, resulting in shorter range, minimal altitude variation, and enhanced safety during operations. Finally, based on comparative experiments, the value of the decreasing coefficient was determined. The optimal solution effectiveness of the improved algorithm is achieved when the decreasing coefficient is set to 1.5.

Continuum robots have been widely used in natural cavity intervention therapy, but the current flexible continuum robots have poor positioning accuracy and lack of accurate navigation means. In response, a multi-segment continuum robot shape reconstruction method based on electromagnetic positioning information was proposed, aimed at achieving accurate end navigation and positioning. An efficient two-stage active structure shape reconstruction method based on third-order Bessel curve was proposed. The solution of Bessel curve was optimized to nonlinear least squares problem, which was solved quickly and accurately by particle swarm algorithm with linear decreasing weights. The proposed method can accurately fit the shape of the two-segment continuum and has good real-time performance. The results show that within the bending angle process, the average root-mean-square error of shape reconstruction is 0.48 mm, which is 0.8% of the length of the continuum bending segment. The accuracy and reliability of the proposed shape reconstruction method for intracavitary interventions using micro-continuum robots are demonstrated through detailed modeling and validation results.

Multivariate time series classification is a key problem in many fields, but the current research on multivariate time series classification is faced with some problems, such as high dimensionality of original data, low accuracy, and lack of interpretability, which limits the performance improvement of models and makes it difficult to meet the actual requirements. Aiming at above problem, a multivariate time series classification method based on Shapelets was proposed. Firstly, unsupervised Shapelet learning of adaptive neighbors was used to automatically learn significant multivariate Shapelets by combining Shapelets transform and adaptive weights. Then, the method was combined with Shapelet similarity and class label constraint to enhance the interpretability and classification accuracy of the model. Finally, the optimization strategy of the model was proposed to obtain the best Shapelets to further improve the classification accuracy of the model. Three different types of 11 algorithms were compared on 11 public data sets, and the experimental results show that the proposed algorithm has high classification accuracy.

In order to improve the recognition accuracy of high-altitude nuts and reduce the false detection rate of bolts and nuts, a high-altitude nut recognition model based on improved YOLOv5 was proposed. Firstly, a new attention mechanism efficient multi-scale attention(EMA) was added to the backbone network to integrate more information. Secondly, in order to enhance the network’s feature extraction capability, bidirectional feature pyramid network(BiFPN) was used to replace the PANet of the neck network. Finally, structured intersection over union(SIoU) was used to replace the original loss function complete intersection-over-union(CIoU) to accelerate the convergence of the model and improve its classification accuracy. The results show that the improved model has better performance than the original YOLOv5 model. The accuracy of the improved model increases by 0.92%. The recall increases by 0.16%. The average precision 1 (mAP_0.5:0.5) increases by 0.53%. And the average precision 2 (mAP:0.95) increases by 2.26%. An actual recognition comparison experiment between the improved model and the original YOLOv5 model was carried out. The experimental results show that the improved model has better recognition performance, which reduces the missed detection rate and the false detection rate, and improves the actual recognition rate. The improved model can well meet the recognition and image data acquisition of high-altitude nuts. And it also provide a data foundation for subsequent nut maintenance.

Based on the sand-mud interlayer core of a block in Ordos Basin, denoising neural network based on wavelet transformation (DWTNet) was used to denoise the core image. The evaluation of this method was carried out by comparing the peak signal-to-noise ratio (PSNR) and the post-denoising image outcomes. The investigation reveals that by applying the DWTNet denoising algorithm to the test sets YX1 and YX2, and contrasting it with other denoising algorithms such as EGDNet, the PSNR values at noise levels of 25, 50, and 75 dB are respectively 0.527, 0.418, and 1.1 dB higher than those achieved by the EGDNet algorithm. The proposed algorithm surpasses others in terms of metrics including peak signal to noise ratio(PSNR), and visually, the resulting images processed by it exhibit enhanced clarity. The introduction of this method holds substantial significance for the calculation of parameters like porosity, mean specific surface area, mean curvature, among other rock properties, thereby advancing the capabilities in digital core technology, CT scanning analysis, and understanding of rock characteristics.

At present, the performance of the traditional centralized coil antenna used for radio frequency identification(RFID) detection and localization of underground cables is insufficient, which seriously restricts the improvement of its detection and localization distance. A new type of high field strength distributed RFID coil antenna structure was proposed. Based on the derivation of antenna related electrical parameters, the magnetic field strength of the coil antenna was taken as the objective function, and its quality factor was fixed as the constraint condition. Particle swarm optimization algorithm was employed to optimize the number of turns of the coil antenna and the turn spacing between adjacent two turns. Finally, an experimental test platform was built. The test results show that compared with the traditional centralized RFID coil antenna, the distributed RFID coil antenna increases the reading distance by 33.3%, significantly enhances the received signal strength indicator (RSSI) at the same distance, and helps to improve the accuracy of the underground RFID localization method based on RSSI, which provides an important reference for the application of RFID detection and localization of underground cables.

During growth, crop stalks are prone to bending deformation, posing challenges for computer visualization simulation. A differential analysis method was employed to investigate the physical stress-strain relationship of stalks, and a visualization simulation method was proposed for flexible stalks. Firstly, a mechanical model of the stalk under tensile, bending, shear, and torsional loads was established. Secondly, a geometric model based on a semi-structural approach and surface modeling was constructed. Finally, C++ and OpenGL were utilized to implement the visualization simulation. Experimental analysis of the bending stress-strain characteristics of stalks from different varieties was conducted. The results demonstrate that this method can relatively accurately simulate the deformation process of stalks. The physics-based model ensures the accuracy of bending simulation, providing a novel informatics analysis tool for selecting and breeding lodging-resistant crop varieties.

In order to study the effect of basalt fiber on the porosity of recycled concrete under salt erosion, the internal variation of concrete was analyzed by scanning electron microscopy, and a linear regression model was established between the porosity of concrete and the number of dry and wet cycles, the height of penetration, the compressive strength and the splitting tensile strength. A fully connected neural network (FCNN) model was established for the penetration height under different soaking ages and fiber content for predicting the corrosion resistance life of basalt fiber regenerated concrete under salt erosion conditions. The results show that the porosity of concrete increases gradually with the erosion age increasing, and the appropriate addition of basalt fiber can significantly reduce the porosity of concrete, and the improvement effect is most significant when the fiber content is 1.0%. With fiber content increasing, the salt permeability resistance of recycled concrete increases, and permeability height decreases. When the fiber content is 1.0%, the best compressive strength and splitting tensile strength are obtained. The fully connected neural network model has a good effect and provides a reliable reference for the life prediction of basalt fiber recycled concrete.

In order to study the mechanical properties of negative Poisson’s ratio(NPR) anchor cable under static tension and drop hammer impact load, the self-developed NPR anchor cable tension test system and NPR anchor cable drop hammer impact test system were used to conduct static tensile test and dynamic impact test for a certain batch of NPR anchor cables. Its resistance and absorption of slow deformation and instantaneous impact energy of surrounding rock were verified by the supporting force, elongation and expansion of anchor cable. Secondly, a 3D numerical model of NPR anchor cable was established, and relevant numerical parameters were calibrated according to laboratory test results. The static tensile test of NPR anchor cable and the drop hammer impact test were carried out. The results of the numerical test are in good agreement with those of the laboratory test, which verifies the reliability of the numerical model. The 3D numerical model of NPR anchor cable can be used as an auxiliary analysis tool for the improvement and upgrading of NPR anchor cable in the future.

1g shaking table test refers to the shaking table test carried out under conventional gravity conditions, which is the mainstream type of shaking table test at present. A distinction was made between strict similarity models and strain distortion models, primarily utilizing the control equation method with supplementary dimensional analysis. The similarity relationships between these models and the prototype during different deformation stages in rock slope 1g shaking table tests were theoretically derived, and the key parameters required to achieve similarity between the model and the prototype were established. Numerical tests were conducted to verify and evaluate the established similarity relationships for different deformation stages, considering the inherent vibration characteristics and dynamic response characteristics of rock slopes. The results indicate that both strict similarity models and strain distortion models can accurately calculate the natural vibration characteristics of the prototype slope and the dynamic response characteristics during the elastic deformation stage under seismic loads. However, for large deformation issues, it is recommended that the strain similarity ratio be close to or equal to 1. These research findings provide valuable references for the design of similarity relationships and the selection of similarity models in 1g shaking table tests for rock slopes.

In order to explore the impact of the number of bearing plates on the bearing capacity of the expanded pile and the soil around the pile, a small half face pile model test equipment developed was used to record the deformation of the soil around the pile in real-time using using digital image correlation (DIC) technology equipment, and to analyze the displacement and failure characteristics of the soil around the pile. Experimental research shows that during loading, the soil under the load-bearing plate is compressed to form a compression zone, and the influence range of this zone gradually increases with the increase of load, while squeezing towards the soil on both sides. The cracks above the bearing plate continue to develop until a free zone is formed, and this area expands with the increase of load. The bearing capacity of three plate piles has been significantly improved compared to single plate piles and two plate piles, but their load-settlement curve shapes are relatively similar. During the loading process, the displacement changes of the soil around the pile near and below the bearing plate are the most significant. Therefore, the study supplements the research on the impact of the number of bearing plates on the soil around piles and other related directions.

Based on Monte Carlo method, Python and Abaqus interface were used for secondary development, and an interfacial transition zone was generated to distinguish between natural coarse aggregates and new and old interfacial transition zone(ITZ) and recycled aggregate concrete (RAC) 2D meso-five phase model of new and old mortar. An improved moisture-chloride ion coupling model under dry-wet cycles was proposed, and the computational results of this model were compared and validated against physical experiments, with good agreement. This model was then applied to analyze the effects of dry-wet cycle periods, ITZ permeability, water-cement ratio, and natural aggregate volume fraction on chloride ion transport properties. The numerical results show that as the number of dry-wet cycles increases, the diffusion depth and concentration of chloride ions in RAC also increases. When the ratio of ITZ diffusion coefficient to the new mortar diffusion coefficient increases, the chloride ion concentration in the diffusion region increases significantly, especially at the front end of the diffusion zone. In addition, there is a positive correlation between RAC materials with different water-cement ratios and chloride ion transport capacity, with little variation in chloride ion transport performance within the high water-cement ratio range. Finally, the volume fraction of recycled aggregates has a significant impact on the chloride ion permeability of RAC, indicating that the ITZ and new and old mortar have an important influence on the transport of chloride ions.

Primary cracks and new cracks develop within the engineering rock mass, leading to the formation of macroscopic cracks. The hollow cylindrical discrete element simulation test enables the emulation of complex stress paths. In order to solve the problems existing in the simulation test of hollow cylindrical discrete element, such as numerous influencing factors and lengthy meso-parameter calibration, a method of mesoscale parameter calibration of hollow cylindrical sandstone discrete element based on machine learning algorithm was proposed. Through variations in input variables within the discrete element model, 210 sets of simulation data were obtained. A mesoscopic parameter calibration model based on random forest algorithm and extreme gradient boosting(XGBoost) algorithm was established, the prediction accuracy of the model was compared, the parameter sensitivity was analyzed, and the contribution of input parameters to the overall mechanical properties of the rock was quantified. Combined with the indoor triaxial test of hollow cylinder, the calibration results show that the XGBoost algorithm has the advantages of computing speed, and can quickly locate the range of discrete element mesoscopic parameters, which provides a new idea for the calibration of discrete element mesoscopic parameters of hollow cylinder, and has the value of engineering application.

The research on the factors affecting the convenience of urban integrated transportation transfer can provide scientific basis and guidance for urban transportation planning. Based on the comprehensive transportation theory and transfer convenience theory, the logic of the comprehensive transportation transfer system was sorted out, and the comprehensive transportation transfer system diagram was drawn. Then, from the two perspectives of the comprehensive transportation hub station and the transfer origin-destination(OD) pair of a single station, Pearson correlation analysis, geographic detector model and multiple linear regression model were used to study the factors affecting the convenience of integrated transportation transfer. The results show that the transfer convenience of a single hub station is mainly related to the location of the hub station. Geographical distance, travel mode and number of travel stations are the main factors of the shortest transfer time, and the number of travel stations is the most important factor. Geographical distance, shortest highway mileage, travel mode and number of travel stations are the main factors of the least transfer cost, among which the travel mode and number of travel stations are the most important factors.

In order to efficiently and accurately predict freight forwarders’ transportation modes preferences between China and Europe during major emergencies, as well as to uncover the relevant factors influencing freight forwarders’ choices, the stated preference method was employed to survey freight forwarders. Additionally, considering the influences of transportation and cargo attributes, decision trees, logistic regressions, and random forest prediction models were constructed to forecast the selection behavior of freight forwarders. The prediction results of the machine learning model and the discrete choice model were comprehensively compared through four evaluation metrics: accuracy, precision, recall, and F₁ score. Furthermore, the random forest algorithm was utilized to rank the importance of attributes influencing freight forwarders’ transportation mode choices during different stages of the pandemic. The study results demonstrate that the prediction accuracy of all three machine learning models is higher than that of the discrete choice model. Among them, the random forest model exhibits superior prediction accuracy compared to the decision tree and logistic regression models in addressing the choice of Sino-Europe container transport modes, making it more suitable for this problem. Regarding influencing factors, during stable periods, cargo attributes are identified as the most important factors. When major emergencies occur, freight forwarders place greater emphasis on the threshold delay time. Furthermore, the destination and value of the cargo are found to have significant impacts on the choice of Sino-Europe container transport modes. The study proposes an accurate analysis of the decision-making mechanisms guiding freight forwarders’ mode choice behavior during major global emergencies. Furthermore, it is utilized by shipping companies and operators of the China Railway Express to gain a deeper understanding of the preferences and decision-making factors influencing freight forwarders. The insights derived from this study are considered a solid basis for effectively responding to similar emergency situations.

In order to improve the efficiency of air transportation, reduce transportation costs and carbon emissions, the evolutionary game method was adopted to explore the influencing factors of the cargo alliance between the government and airlines. The system dynamics model (SD) was used to conduct simulation experiments on the game evolution process. The results indicate that the strategic choices between airlines are influenced by investment costs and alliance benefits, while the government’s strategic choices are influenced by factors such as the carbon emission penalty coefficient paid by airlines, carbon tax subsidy amounts, social benefits, and regulatory costs. In the long run, the government should establish a dynamic subsidy mechanism and increase the diversity of subsidies to enhance the innovation and core competitiveness of airlines.

In order to study the molecular weight and molecular structure changes of asphalt under ultraviolet aging and the mechanism of their effects on macro properties, gel permeation chromatography and nuclear magnetic resonance tests were carried out on four commonly used asphalt, respectively. The molecular weight composition changes, such as molecular weight and molecular relative mass distribution, and the molecular structure composition changes, such as hydrogen spectrum, carbon spectrum, hydrogen atom content and molecular structure parameters were studied. On the basis of macroscopic rheological tests, the molecular composition of asphalt rheological properties was characterized by correlation analysis, and the molecular mechanism of ultraviolet aging macroscopic properties was analyzed. The results show that ultraviolet aging causes the agglomeration of molecules in asphalt, small molecules decreases and aggregates into large molecules, and the molecular weight distribution boundary narrows gradually. From the changes of hydrogen atoms and molecular structure parameters, it can be seen that the alkyl substituents on the aromatic ring in the asphalt increase after ultraviolet aging, resulting in the increase of the volume and stability of the aromatic ring, and the increase of molecular backbone stiffness. On the macro level, the elastic properties of asphalt increase. The phase angle, rutting factor, irrecoverable compliance and recovery rate of asphalt before and after ultraviolet aging were obtained by macroscopic rheological tests. The correlation analysis shows that the rheological properties are most affected by condensation degree parameters, substitution rate of peripheral hydrogen, average molecular weight and branched degree of alkyl chain.

The displacement response of a bridge is identified as a fundamental condition for the structural health monitoring and safety assessment of bridge structures. In order to fully leverage the advantages of machine vision for measuring structural displacements and to enhance its applicability, a structural displacement monitoring method based on the pinhole camera model was proposed. Sparse optical flow was employed to track structural feature points, achieving sub-pixel level image displacements. By employing the optical geometric relationships of camera imaging, an analytical solution was established between real-world displacements and image displacements. The image displacements were then substituted into algebraic relationships to obtain the true structural displacements. In the indoor experiments on dynamic load displacement identification of a simply supported bridge model, compared to the measurements obtained using a linear variable differential transformer displacement meter, the proposed method achieves a maximum error within 6% for pitch angles up to 30° and yaw angles up to 35°, thereby meeting the application requirements for monitoring the displacement deformations of bridge structures.

Shared bikes represent a crucial component of urban transportation. The randomness of user demand for shared bikes with fixed piles leads to unbalanced demand in time and space, and even the difficulty in renting a bike, which cannot meet the user demand during peak hours. Therefore, high-frequency users frequently travel to nearby stations to rent a bike for serving, which means that there are implicit demands. As for the hidden demand, firstly, the state changes of the site were described by the rental number and the return number, and the critical state of the reference site was determined by mining the user travel conditions of nearby sites. The hidden demand of the site was determined based on the site state change diagram and the demand judgment model. Then, according to the real needs of the site, the long short-term memory(LSTM) network prediction model was established, and the regional scheduling model of shared bicycles based on the real needs was established. The model takes the cost minimization as the goal, and obtains the path with minimum scheduling cost through genetic algorithm, which provides a reference for balanced scheduling based on real demand. The results demonstrate that, when transportation costs are similar, the scheduling method under real demand can alleviate the problem of users’ difficulty in renting a bike, thereby reducing the loss of high-frequency users.

Aiming at the problem of short effective prediction time for the movement history of amphibious aircraft in waves, the statistical values of amphibious aircraft movement over a period of time were proposed to predict, and a prediction model for the statistical characteristics of amphibious aircraft movement was constructed based on long short-term memory neural networks(LSTM). Taking the NACA TN 2929 amphibious aircraft as an example, based on its numerical simulation data, the statistical values of the three degrees of freedom motion of heave, roll, and pitch of amphibious aircraft under sea conditions of level 3, 4, and 5 were predicted, and their prediction effects were analyzed in detail. The results show that the LSTM neural network-based model for predicting the statistical characteristics of amphibious aircraft motion has good prediction accuracy. In practical engineering applications, this model can accurately predict the statistical values of amphibious aircraft motion in the future, providing auxiliary decision-making information for offshore operations.

With the increasingly serious problem of climate change, green and low-carbon operations have become an important principle for the sustainable development of the air transportation industry. Taking a single runway transport airport as the research object and green and low-carbon and passenger walking distance as the optimization objective, a green and low-carbon gate assignment model under multiple scenarios was constructed, and a genetic-tabu search combined optimization algorithm was designed to solve it. Finally, a transport airport in northeast China was taken as an example for simulation experiment. The experimental results are shown as follows. In the optimal assignment scheme, if considering green and low-carbon, the fuel consumption can be reduced by 3.1%, the taxiing distance of the aircraft by 3.1%, HC emission by 4.2%, CO emission by 3.6%, NO_X emission by 3.1%, and CO₂ emission by 3.1% comparatively. But passenger walking distance can be increased by 5.3% at the same time. If considering green and low-carbon as well as the interests of the passengers, the fuel consumption can be decreased by 2.1%, the taxiing distance of the aircraft by 2.2%, HC emission by 3.8%, CO emission by 2.7%, NO_X emission by 2.0%, CO₂ emission by 2.1%, and passenger walking distance by 2.1% comparatively. Thus, it is possible to strike a balance between green and low-carbon development and the interests of travelers.

The quantitative monitoring and evaluation of the terrestrial ecological environment status helps to understand the changes in ecosystems and their driving factors, and is of great significance for the government to guide regional ecological environment management, achieve ecological protection and socio-economic coordinated development. Based on long-term multi-source satellite remote sensing data, a land ecological environment status index (LESI) evaluation model was constructed by coupling five indicators including greenness, heat, humidity, dryness, and air pollution using covariance principal component analysis. Four strategies, including Augmented Dickey Fuller (ADF) test, Biplot biplot, correlation analysis, and cross validation, were used to demonstrate the good stationarity, rationality, comprehensive representativeness, and regional adaptability of the model. On this basis, the spatio-temporal characteristics and evolution patterns of the land eco-environment status (LES) in the the Taihu Lake Basin from 2001 to 2021 were assessed, the driving factors of LES changes were discussed, and the contributions of climate change and human activities were quantified. The results show that the eco-environment quality of the the Taihu Lake Basin is declining first and then stable. The average annual LESI decreases significantly from 0.639 in 2001 to 0.523 in 2009 (-18.2%), and then tends to be stable. The spatial-temporal variation of LESI in Taihu Lake Basin is obviously different. The area where the ecological environment quality remains stable or improved (68.8%) is significantly larger than the area where the ecological environment quality is declining (31.2%), of which Hangzhou and Huzhou have the best eco-environment quality and remain stable. Shanghai and Suzhou are relatively poor and have significant fluctuations. The contributions of temperature, precipitation and night light to LESI are 0.03, 0.19 and 0.78, respectively, indicating that the eco-environment changes in the the Taihu Lake basin in recent 21 years are mainly dominated by human activities, while only some forest mountain areas and wetland areas are affected by climate change. The LESI model established in the study can effectively monitor and quantitatively evaluate changes in the eco-environment, providing scientific support for the government to formulate ecological environment protection policies and promote high-quality development.

The problem of mine water pollution from abandoned mines after integration is becoming increasingly serious with the integration of coal resources and the merger and reorganisation of coal companies. An accurate understanding of the development mechanism of mine water quality in abandoned coal mines is an important prerequisite for the protection and use of mine water and the effective prevention and control of groundwater pollution. The leaching behaviour of Fe³⁺ and Mn²⁺ and the changes of related water quality indices were investigated by the long-term indoor water-coal immersion test based on the project practice of Shendong mining area. The results show that the solubility of Fe³⁺ is “wave-like”, and the solubility of both samples reaches the lowest value at the 84th day after immersion, while the solubility of Mn²⁺ remains relatively stable after a rapid reaction (the first day). The causes of solubility variations were further analysed by ion ratio coefficient method and Pearson correlation coefficient method, and it was found that mine water in goaf may be affected by mining activities, and the water quality of mine water is strongly influenced by the dissolution of silicate rocks and gypsum. The main water-rock interactions in mine water in the goaf area include the dissolution of silicate rocks and evaporative rocks and the alternating adsorption of cations. For the rational development and utilisation of mine water in China, it is of great importance to study the characteristic pollutant ion change law of mine water in the goaf area.