Landslide geological hazard susceptibility assessment is an important means of hazard prevention and reduction. The selection and optimization of susceptibility assessment model is very important. Sinan County was selected as the study area, and 16 assessment factors such as elevation, slope, curvature, lithology, land use, and average annual precipitation were selected. Frequency ratio (FR) model was coupled with support vector machine (SVM) model and random forest (RF) model. Grid search method was introduced to obtain the optimal parameter combination of SVM model, RF model and their coupling model for model training. Finally, SVM, RF, FR-SVM and FR-RF models were constructed to predict landslide susceptibility in the whole study area, and receiver operating characteristics (ROC) curve was performed verification. The results show that compared with the single machine learning model, the coupled machine learning model has more landslide hazard samples fall in the high zone and the very high zone, and has higher accuracy. In the single model, more landslide hazard samples in the RF model fall in the high zone and the extremely high zone. In the coupled model, more landslide hazard samples in the FR-RF model fall in the high zone and the very high zone, and no hazard samples points in the FR model and the FR-RF model fall in the very low zone, indicating that no matter the single model or the coupled model, The performance of RF model is better than that of SVM model. The AUC values of ROC prediction curves of the four models are 0.831 6, 0.843 9, 0.864 4 and 0.910 4, indicating that the coupling model combined with FR model and RF model has a higher accuracy, and this model is more suitable for the assessment of landslide susceptibility in Sinan County. The assessment results can provide some reference for hazard prevention and reduction of local landslide geological hazards.

Dafuling(DFL) deposit is a part of the Mingyuefeng ore field in eastern Hunan Province, China, is a typical perigranitic uranium deposit discovered recently. The characteristics of the ore minerals and the features of rare earth elements in this deposit have not been previously documented. In order to further elucidate the characteristics of ore minerals and rare earth elements (REE), as well as explore their indicative significance for uranium metallogenesis. Herein, uraninite, the primary ore mineral in the deposit, was investigated via scanning electron microscopy and electron probe microanalysis. Additionally, laser ablation-inductively coupled plasma-mass spectrometry(LA-ICP-MS) was used for the first time to determine the in situ the REE characteristics of uraninite. Uraninite exhibits a distinct fractionation between light rare earth elements(LREE) and heavy rare earth elements(HREE), while displaying a negative Eu anomaly. The (La/Yb)_N ratio exceeds 1, indicating a significant enrichment of LREE. Both major elements and REE in uraninite suggest its formation within a hydrothermal environment at temperatures ranging from moderate to low, below 350 °C. Consequently, DFL deposit can be classified as a typical hydrothermal vein-type uranium deposit. The REE serve as indicators of the transition of ore-bearing hydrothermal fluids from high salinity to low salinity, and the hydrothermal environment gradually shifts from a reducing state to a weakly oxidizing state. These observations suggest that the ore-bearing hydrothermal fluid responsible for metallogenesis originating from the deep crust or lithospheric mantle, ascended along regional deep faults, and subsequently underwent a series of physical and chemical transformations, eventually accumulated mineralization in suitable locations within DFL deposit.

As an innovative new method of natural gas hydrate extraction, the recovery of hydrate particles determines the efficiency of this method and is one of the key technical links. However, due to the limited hydraulic suction, the recovery rate of hydrate particles is low. Therefore, in order to improve the recovery performance of hydrate particles, a double jet recovery scheme was innovatively proposed. In order to explore the efficiency of solid particle recovery under different working conditions, experimental research was carried out, and the recovery flow field and particle recovery rate were studied by numerical simulation. The results show that with the increase in the distance between the front-end jetting and the recovery hole (l₁) and the distance between the back-end jetting and the recovery hole (l₂), the flow field effect between the double jets weakens, resulting in the particle deposition phenomenon becoming more obvious and the number of sand piles changing from 2 to 3. When the distance between the back-end jetting and the recovery hole (l₂) is 300 mm, the particle recovery increases first and then decreases with the increase in the distance between the front-end jetting and the recovery hole (l₁). When l₁ = 300 mm, the recovery increases first and then decreases with the increase of l₂. The results further enrich the mechanism of hydrate mining and help optimize the design of mining tools.

In order to solve the problems of excessively long droplet break time and excessively large droplet length to diameter ratio in the production of high-temperature and high-viscosity temporary plugging agent, the minimum velocity of droplet forming of temporary plugging agent was obtained by theoretical calculation, and the formula for calculating the optimal disturbance period was derived. The numerical simulation method was used to analyze the droplet forming process of temporary plugging agent, and the changes of the flow field of the droplet forming under the action of no disturbance and external square wave disturbance were explored. The simulation results show that without disturbance, the jet is difficult to break into droplets within 300 mm, the jet temperature is basically unchanged within 0.5 s, and the jet velocity increases to 2.13 times of the initial velocity. When square wave disturbance is added to the outside, too short disturbance period is not conducive to uniform droplet forming, and too long disturbance period will lead to excessive elongation of liquid column before fracture. When the disturbance period is about 0.11 s, the droplet forming efficiency is the highest, the fracture frequency is stable at 0.11 s, and the final droplet length-diameter ratio is stable at about 2. The research results provide a basis for the selection of process parameters for droplet forming of high viscosity temporary plugging agent.

In order to explore the application of carbon fiber composite in portable weapons, the technical research on the structural properties of the launcher and the method of composite laminating was carried out. The working pressure of a certain type of launcher was obtained through experiments, and different carbon fiber composite layering models were established by using finite element numerical simulation method. Then the mechanical properties of the launcher under working load were studied. The results show that the layering method of carbon fiber has a great influence on the stiffness and damage failure of the launcher. Under the condition of the same working pressure, the same number of layers and the total thickness, the maximum deformation of the launcher structure is 2.41 mm in the layering mode Ⅰ. The maximun deformation of mode Ⅱ is 7.66 mm, and the latter is more than 3 times of the former. According to the Hashin failure criterion, there is no damage in the carbon fiber cylinder of the mode Ⅰ, except for the 6th to 12th fiber layers in the middle of the cylinder according to the mode Ⅱ, a large range of initial damage points are found in other layers. The research results can provide reference for the stucture design of the launcher and the carbon fiber composite layering scheme.

In order to avoid wellbore failure caused by abnormal annulus band pressure and resulting safety accidents, the annulus band pressure value is accurately predicted, and preventive measures are taken in advance when it exceeds the control value. An autoregressive integrated moving average-long short term memory (ARMI-LSTM) model was proposed. The model was trained to predict the annular band pressure of example wells based on actual annular band pressure time series data and feature capture data sets, and compared with a single model and recurrent neural network (RNN) model. The results show that the model has a good performance in error, fitting accuracy and overall performance after training with actual data, which can provide a reference for improving the prediction accuracy and efficiency of annular band pressure value, and is helpful to well integrity design.

Particle profile control and blockage is recognized as an important method for enhancing oil recovery. The migration and deposition characteristics of particles in porous media are understood to facilitate the optimization of particle preparation, thereby improving compatibility with reservoir pore throats and blocking efficiency. Factors such as particle concentration, particle size, porous medium structure, particle size ratio, and fluid parameters within the medium were reviewed for their effects on migration and deposition. Research results from various simulation methods, including simplified geometry, mesoscopic simulation, lattice Boltzmann method-discrete element method (LB-DEM) and computational fluid dynamics-discrete element method(CFD-DEM) were summarized. It is indicated that the critical value of the particle size ratio influences the deposition location and blockage degree in porous media. Different particle sizes are subjected to significant differences in forces, with larger particles being notably affected by hydrodynamics, gravity, and fluid flow rates. The fluid flow model within porous media is not yet fully unified. However, the Brinkman-Forchheimer-Darcy model is noted for its strong applicability. The CFD-DEM method, approached from a microscopic perspective, has validated the flow-solid coupling of migration and deposition within the medium, providing a basis for profile control schemes in heterogeneous reservoirs.

In order to better protect the safety of bridge piers and ships, a step-by-step progressive high energy consumption anti-collision magnetorheological damper for bridge piers was designed for the problems of passive energy dissipation, poor dynamic response and anti-collision energy dissipation, and limited adaptability of the device. The structural parameters of the damper were established through the establishment of a mechanical model. The structural strength and magnetic circuit were analyzed using finite elements. The results show that the strength of the structural components meets the requirements, the magnetic induction strength at the gap under 2 A current can reach about 1.2 T, three pistons are set up in the cylinder barrel, which can work together under different crash depth displacements to divide the energy dissipation of the damper into three stages, the minimum damping force under no current is 15 kN, the maximum damping force is 496 kN, and the damping force improves with displacement by 481 kN. The damping force under 2.5 A current increases with displacement from 78 kN to 1 204 kN, which is an improvement of about 15 times. It effectively improve the force of the damper and achieve the excellent effect of graded progressive impact energy dissipation. The application in the bridge pier collision avoidance device can achieve semi-active collision avoidance energy dissipation. The theoretical and finite element simulation results basically coincide with each other, proving the rationality of the damper design.

With the acceleration of the transition to new energy systems, it is urgent to carry out in-depth research on the complex energy characteristics of multi-load users. A technology of constructing user energy characteristic label library and a user portrait method were proposed, which comprehensively considered the coupling characteristics of electric, cold and thermal multiple loads. Firstly, the high redundancy and low correlation features were eliminated by the fast correlation filtering algorithm, and the features with strong distinguishing ability were selected by the random forest and recursive feature elimination algorithm. In the clustering stage, the improved three-way adaptive density peak clustering (3W-ADPC) algorithm improved the load clustering effect by combining the adaptive neighbor search and the three-branch clustering algorithm. The empirical results show that the proposed method has dual advantages in computational efficiency and clustering accuracy, and can accurately reveal the comprehensive energy use characteristics and deep information of multi-load users, which confirms the practical value of the proposed method in the study of multi-load users’ behavior.

The role of gas storage in regulating natural gas peaks is crucial. Improper allocation of gas injection schemes during the injection process not only results in excessive energy consumption by compressors, but also leads to excessive pressure changes in certain individual wells and convergence of salt karst cavities, thereby affecting the long-term stable operation of gas storage. By combining the simulated annealing algorithm with actual field conditions, a multi-objective optimization function was established considering both compressor energy consumption and dispersion degree of wellhead pressures across all gas storage wells within the same block. The variable for this optimization was set as the gas injection volume during the task period for each gas storage well, while variables such as maximum design pressure of pipelines, minimum operating pressure, and maximum operating pressure of gas storage wells were taken into account. Additionally, constraints were imposed based on the maximum design flow rate measured by target flowmeters for multi-objective optimization purposes. Results indicate that compressor power consumption can be reduced by over 40% and formation pressure differences can be decreased by more than 90%. It is evident that this scheme provides assurance for ensuring long-term stable operation of gas storage through effective guidance on actual production operations.