In order to estimate carbon storage and investigate its influencing factors in typical karst rocky desertification regions, Jianshui County, located in the upper reaches of the Yangtze River and within the Nanpan River Basin, was selected for study due to its significant ecological position. Data from Landsat 5 Collection 1 Tier 1 Surface Reflectance, Landsat 8 Collection 1 Tier 1 Surface Reflectance, and digital elevation model (DEM) were used to conduct the analysis. The google earth engine (GEE) platform and the integrated valuation of ecosystem services and trade-offs (InVEST) model was used to estimate and predict carbon storage, while the geodetector tool was employed to analyze influencing factors. The results show that, between 2000 and 2020, Jianshui County was predominantly classified as potential rocky desertification and non-desertification, with the rocky desertification area found to have decreased by 115 km² overall, and the non-desertification area increased by 21 km², reflecting an improvement in desertification conditions. Carbon storage displayed a spatial distribution pattern of “higher in the north and south, lower in the center,” with recorded values of 116.293 t, 113.310 t, and 118.363 t in 2000, 2010, and 2020, respectively, demonstrating an initial decrease followed by an increase. Projections suggest that carbon storage may reach 129.981 t by 2030. Temperature (q=0.672) was identified as the primary factor affecting changes in carbon storage, with the interactions between factors shown to have a stronger effect on carbon storage than individual factors, especially the interaction between slope and temperature (q=0.998), indicating a non-linear enhancement. It is concluded that carbon storage in Jianshui County exhibits a trend of initial decrease followed by increase, influenced by both natural and social factors, with a spatial pattern of “higher in the north and south, lower in the center.”

In the event of a public health emergency, the selection of the optimal distribution locations of daily necessities is crucial. Accordingly, the emergency distribution of daily necessities in Changchun City was taken as an example for empirical research and an optimization algorithm was proposed for the location of emergency supplies distribution. Initially, the virtual material warehouses, distribution candidate locations, and service coverage areas were determined by using K-means clustering and the Thiessen polygon method. Then, an optimization model was established with the goals of maximum coverage and minimum cost, and an improved genetic algorithm based on adaptive elite retention strategy was proposed to solve it. Empirical research had shown that the clustering algorithm could obtain 873 virtual material warehouses and distribution candidates, while Thiessen polygons could determine the reasonable coverage range of candidates, and improved genetic algorithms could obtain better 30 material warehouses and distribution locations. Data analysis had also found that there was a time lag between the distribution of supplies and effective control of infection. Therefore, once the rate of new additions exceeds the normal value, emergency supplies should be increased in advance to control further outbreaks of possible infections.The research results are beneficial for enhancing the ability of urban crisis management and emergency response, ensuring timely and efficient supply of daily necessities.

Caragana is the main wind-breaking and sand-fixing vegetation in Inner Mongolia, with a wide planting area and a large area. There is a great demand for harvesting machine in the stubble and harvesting of caragana. Aiming at the problems of high fuel consumption and heavy pollution of traditional caragana harvester, the maximum speed, maximum gradient and pure electric driving range of the extended range hybrid caragana harvester designed by our research group were used as the objective functions to design the dynamic parameters. Firstly, according to the design parameters and performance requirements of the whole machine, the parameters of the range extender, drive motor and battery of the harvester were designed. Combined with the actual working parameters, AVL/Cruise software was used to simulate and find the optimal solution of the overall performance index. Combined with the actual working parameters, AVL/Cruise software was used to simulate and find the optimal solution of the overall performance index. The reasonableness of the simulation results is verified by the field test of the whole machine. Comparing the two results, it is found that the error of the maximum speed is 9.012% and the climbing error is 6.404%. The error of the two results is within the allowable range. The results show that the simulation model is reasonable and can provide reference for the optimization of dynamic parameters of the extended range hybrid Caragana harvester.

To enhance the support for the nuclear safety review of domestic advanced pressurized water reactor (PWR), the reactor coolant pump (RCP) shaft seizure accident for this reactor type was conducted. The impact of the loss of offsite power (LOOP) assumption and moderator temperature feedback on the accident consequences was examined. The findings are as follows. The peak pressure in the reactor coolant system and the peak temperature of the hot spot cladding, recorded during the accident process, met the accident acceptance criteria, enabling the nuclear power plant to eventually stabilize. The LOOP assumption was found to be conservative. For this accident, however, the differences arising from this assumption manifested in the later stages and did not influence key outcome parameters such as system pressure peak, minimum departure from nucleate boiling ratio (DNBR), and peak temperature of hot spot cladding, which occurred early in the accident. Therefore, the inclusion or exclusion of the LOOP assumption was deemed acceptable. The introduction of moderator temperature feedback was considered an unconservative assumption. Nevertheless, even without this feedback, the peak pressure in the reactor coolant system and the peak temperature of the hot spot cladding still met the accident acceptance criteria, maintaining a substantial margin. Additionally, incorporating moderator temperature feedback brought the calculations closer to reality. Overall, the introduction of moderator temperature feedback in this accident was also judged to be acceptable.

CO₂ flooding is one of the most effective technical means to improve the recovery of low permeability reservoirs. However, the injected CO₂ will cause asphaltene precipitation in crude oil, resulting in the decrease of reservoir permeability and the change of reservoir heterogeneity. In order to clarify the effect of asphaltene differential precipitation on the heterogeneity of low permeability reservoirs under different pressure conditions, a low permeability reservoir in Jilin Oilfield was taken as the research object. Through the CO₂ long core displacement experiment, the CO₂ displacement characteristics under different pressures were clarified. At the same time, combined with the test results of crude oil and core properties, the changes of crude oil asphaltene content and reservoir properties before and after displacement under different pressure conditions were analyzed, and the distribution law of asphaltene precipitation was further clarified. The results show that under immiscible conditions, the degree of crude oil recovery is low, only 55.11%. The asphaltene precipitation increases first and then decreases with the increase of displacement distance. CO₂ mainly displaces the large pore throat crude oil, and the asphaltene precipitation also mainly occurs in the high permeability area, thus inhibiting the reservoir heterogeneity. Under miscible conditions, the degree of crude oil recovery is high, up to 81.84%. Asphaltene precipitation increases with the increase of displacement distance. CO₂ can displace small pore throat crude oil. Asphaltene precipitation occurs in high permeability and low permeability areas, but low permeability areas are greatly affected, and reservoir heterogeneity is further strengthened.

In order to analyze the instability and failure characteristics of earthquake landslides in the Loess Plateau, the Xinbaocun landslide induced by the 8.5-magnitude Haiyuan earthquake in 1920 was taken as an example. Based on satellite remote sensing interpretation and field investigation of landslides, the original terrain of the Xinbaocun landslide before sliding was restored using the numerical simulation function of MATLAB based on the principle that the volume of the landslide body before and after sliding is equal. On this basis, the numerical simulation method was used to analyze the instability, deformation and failure characteristics of the Xinbaocun landslide under the action of earthquakes and invert the minimum horizontal ground motion of the slope instability. The landslide restoration results show that after the restoration of the Xinbaocun landslide, the slope surface shape is generally concave, and the slope distribution range is 12°~18°.The numerical simulation results show that under natural conditions, the slope deformation of the restored landslide is small, there is no obvious plastic deformation zone,the stability is good, and the overall stability coefficient is 1.355. Under the action of earthquake, when the input earthquake motion is 0.4g, the stability coefficient is 0.887, the slope is in an unstable and damaged state, and the slope body has a large area of deformation. The maximum deformation area is located near the top of the slope,and gradually decreases from the top to the foot of the slope. It is speculated that the landslide is a push-type landslide. The inversion results show that the minimum horizontal earthquake motion for slope instability is 0.36g. The research results of this paper can provide certain basic data and reference for the prevention and control of earthquake disasters in the Loess Plateau.

The interporosity flow between matrix pores and fractures is the main cause of strong attenuation and dispersion of elastic wave in the seismic frequency band. A fractional equation for interporosity flow is developed. The constitutive relationship of double-porosity medium was improved in the frequency domain, in which three factors representing the effects of fractional interporosity flow were introduced. A wave equation considering fractional interporosity flow for a double-porosity medium was developed by substituting the improved constitutive relationship into the Lagrangian equation. The wave velocity and inverse quality factor was obtained and analyzed by plotting. Comparing to the traditional interporosity flow, the fractional interporosity flow provides a more flexible and accurate description for the dispersion and attenuation of elastic waves in the seismic frequency band.

Gas storage operations can be significantly impacted by abnormal wellbore temperatures at natural gas storage sites. Accurately predicting wellbore temperatures is of paramount importance for enhancing the safety and efficiency of these operations. Based on the analysis of operational parameter correlations, a gas storage wellbore temperature prediction method was proposed using advanced spatiotemporal graph convolutional neural network (A-SGCN). Both GCN and long short-term memory (LSTM) networks were employed by A-SGCN to capture spatial and temporal dependencies, respectively. Based on this framework, an adaptive residual attention mechanism was incorporated to effectively capture the intricate relationships between spatiotemporal data, ultimately enabling accurate temperature prediction. The effectiveness of the method is validated through its application at the Huangcaoxia gas storage No.2 injection-production station. Accurate prediction of wellhead temperature at Well No.1 is achieved through the association of monitoring parameters between Well No. 1 and Well No.6.

Landslides are significant geological hazard, with most events directly related to rainfall. Consequently, rainfall monitoring is critical for landslide forecasting and prediction. A self-powered rainfall sensor based on triboelectric nanogenerator (TENG) technology was developed for landslide monitoring. The sensor consists of a transmission unit and a sensing unit, which enable rainfall measurement and self-powering through rain-induced contact electrification of nanomaterials. Experimental results indicate that the sensor maintains a measurement error of 5% within the 0~300 mL/24 h range, with a linearity of 3.4%. It is capable of being operated in environments where the temperature is below 100 ℃ and the relative humidity is under 90%. Additionally, the output of the sensor can achieve a maximum power of 203.5 nW when an external load resistance of 7.8×10⁷ Ω is applied. The performance of the sensor can meet the practical requirements for field rainfall monitoring of landslides and also show potentials for the development of related rainfall monitoring technologies.

The double bottom blowing lead smelting is a representative kind of oxygen-enriched enhanced molten pool smelting process. Comparing with the traditional ore lead smelting,its production operation is more complex for coprocessing lead based solid waste. In order to ensure its production status in a stable and economic state, there are higher requirements for its process control. MetCal desk metallurgical computing platform was used to establish a calculation model for the double bottom blowing lead smelting process for coprocessing lead based solid waste through the principles of material balance, thermal balance and chemical balance in the smelting process. The process parameters of the double bottom blowing lead smelting process for coprocessing lead based solid waste were simulated and calculated. Meanwhile, the model was modified and controlled by the feedback control algorithm to make it more in line with the actual production situation, which can provide guidance for the actual production operation of the process engineers and realize the optimal control of the process.