In order to reveal the characteristics and geological significance of the main micronutrient geochemistry in the Carboniferous-Permian Taiyuan Formation in Ningdong coalfield which deposited in marine-land transition coal-accumulating environment, the X-ray fluorescence(XRF) spectrometry, inductively coupled plasma-mass spectrometry(ICP-MS), macerals identification and industrial analysis were used to study the source, occurrence and environmental significance of trace elements in coals. The results show that the content of major and trace elements in Carboniferous coals of Ningdong coalfield are varies greatly, except the Fe₂O₃ content is lower than the mean content of China coals. The Rb(5.1) is enriched in Weierkuang while other elements are slightly enriched in different micronutrient. The major and trace elements in coal are mainly occurs in clay minerals, and come from the supply of terrigenous clasts and the combination with organic matter and authigenic minerals in water-soluble state and ion state. The ratio of TiO₂/Al₂O₃indicate that the minerals in the coal are mainly derived from felsic clastic rocks, and the positive correlation between CaO and MgO indicates that they coexist in the form of dolomite. The ratio of Sr/Cu and CaO/(MgO·Al₂O₃) and the other parameters indicate the coal-accumulating period is in a warm and humid environment, it is inferred that the temperature is between 15 ℃ and 30 ℃, the ratio of Sr/Ba indicates that the coal-forming marsh is a brackish water environment, which indicates that it is affected by seawater. The parameters of Cu/Zn, V/(V + Ni), Ni/Co and V/Cr revealed that the peat-formed bog was in an anaerobic redox environment.

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.

The Permian Wutonggou Formation in Dixi area of Junggar Basin has huge potential for oil and gas exploration. Based on the latest seismic data, combined with thin section data, drilling and logging data, rock physical properties and physical parameters, using seismic forward modeling, wave impedance attributes and waveform clustering attributes, the basic characteristics of the reservoir were characterized, the seismic waveform identification method of the upper and lower sand groups in the first member of Wutonggou Formation was clarified, the thickness distribution law of the upper and lower sand groups was described, and the sedimentary facies development characteristics of the upper and lower sand groups were clarified. The results display that the sandstone of Wutonggou Formation is mainly lithic sandstone and feldspar lithic sandstone, which belongs to low porosity and low permeability reservoir. The seismic waveform characteristics of sand bodies are significantly affected by seismic resolution, sand body thickness, mudstone interlayer thickness, sand body superposition relationship and underlying lithology. The sand body distribution regular pattern based on the interpretation of the sand body waveform characteristics of the forward model is highly consistent with the average wave impedance attribute distribution regular pattern. The study area develops delta front underwater distributary channel microfacies, estuary dam microfacies, underwater tributary bay microfacies and sheet sand microfacies. There are great differences in the development characteristics of sedimentary facies between the upper and lower sand groups.

Landslide disasters pose a serious threat to residents’ lives and socio-economic development. Taking Xinyuan County as the study area, 17 landslide influencing factors were selected as the initial factor set. Through multiple collinearity analysis, 10 landslide factors were screened and an evaluation index system for landslide susceptibility in the study area was constructed. The landslide susceptibility was then evaluated based on three typical models: logistic regression (LR), support vector machine (SVM), and random forest (RF). The evaluation results of the model were compared and validated using the area under curve (AUC), landslide ratio, and field investigation under the receiver operating characteristics(ROC) curve. The results show that low-susceptibility areas are mainly concentrated in the valley plain of the Kongnais River, where the terrain is flat and the landslide susceptibility is relatively low. High-susceptibility areas are mainly located in the northern part of the Kongnais River valley, the Awulale hilly area, and the watersheds on both sides of the southern Yishikelike Mountains and Nalati Mountains, as well as the area south of the Qiafu River, where the terrain is complex and varied, leading to a higher susceptibility to landslides. Among the three evaluation models, the SVM model performs the best, with an AUC value of up to 0.985, indicating its high accuracy in landslide susceptibility assessment. Furthermore, the high-susceptibility areas identified by the SVM model have a high density of landslide points, accounting for 86% of the total, further validating its effectiveness in landslide susceptibility assessment. Based on the above results, the SVM model is more reasonable than the other two alrorithms in assessing landslide susceptibility in Xinyuan County, providing a scientific theoretical basis and reference for landslide prevention and control in the region.

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.

In order to explore the effects of different internal fixation systems on the biomechanical characteristics of the spine after orthopedic idiopathic scoliosis, a theoretical basis for the improvement of the internal fixation system was provided from the perspective of biomechanics. Based on reverse engineering, topology optimization and finite element modeling techniques, the finite element model of idiopathic scoliosis was established by taking actual cases as examples. The personalized fusion device was designed. Two kinds of internal fixation systems were established, namely full fixation and interval fixation. To simulate idiopathic scoliosis surgery and compare the biomechanical differences between spine and internal fixation system under different physiological conditions. The results show that the average stress of cortical bone and cancellous bone is increased by 17.19% and 12.37%, respectively, compared with that of interlocking nails. The maximum equivalent stress of fibrous annulus matrix and nucleus pulposus is increased by 1.78% and 1.1%, respectively, compared with that of full nailing. The maximum equivalent stress of pedicle screws is 11.64% higher than that of interlocking screws. The average stress of interbody fusion is increased by 6.15% compared with that of interbody fusion. In conclusion, compared with the interspaced nailing scheme, the total nailing scheme is better in vertebrae safety, but the risk of screw slip and screw loss is higher. Compared with the total nailing scheme, the interstice nailing scheme has better spinal fusion effect and effectively alleviates stress occlusion, but the incidence of bone hyperplasia is increased.

With the rapid development of infrastructure projects in China, the use of anchor bolts in mining, geology, and tunnel engineering continues to increase. The non-destructive testing of anchor bolt quality is crucial for enhancing the stability and safety of engineering projects. Based on the stress wave detection method, wavelet threshold functions and STA/LTA algorithms were employed to comprehensively evaluate anchor bolt engineering. A software for non-destructive testing and intelligent analysis of anchor bolt anchorage was developed, integrating signal filtering and acquisition of anchorage parameters. Through numerical simulation analysis of anchor bolt anchorage, the lengths of anchor bolts were calculated using both manual picking and software-based arrival time extraction. The results show that the software-calculated anchor bolt lengths have an overall error controlled within 5%, offering higher precision than manual picking, which is significant for improving the safety and stability of project engineering.

In recent years, multiple exploration breakthroughs have been made in the Maokou Formation of the Sichuan Basin. Currently, the overall exploration level is low.The type and distribution of sedimentary facies are still unclear. The characteristics and formation mechanism of the reservoir are unclear. Techniques such as core observation, pore permeability testing, conventional and cast thin section identification were used to clarify the sedimentary and reservoir characteristics of the 2nd Member of the Maokou Formation in the front of the Longmen Mountains in western Sichuan and to explore the main controlling factors of high-quality reservoirs.Research shows that the 2nd Member of the Maokou Formation in the front of Longmen Mountain in western Sichuan develops in a northwest southeast direction. The southern and middle sections of Longmen Mountain are the development areas of high-energy shoals of the lower sub section of the second section of Maokou Formation. The middle and northern sections of the Longmen Mountain in the upper sub section of the second section of the Maokou Formation are the development areas of high-energy dolomitized platform edge sand debris shoals. The reservoir lithology of the upper sub section of the Maokou Formation is mainly composed of residual bioclastic sandstone dolomite, bioclastic grain dolomite, and residual grain dolomite.The reservoir lithology of the lower sub section of the second section of the Maokou Formation is mainly composed of residual sandstone dolomite and residual grain dolomite. The storage space consists of intergranular dissolution pores, intergranular dissolution pores, intragranular dissolution pores, and expansion fracture pores. The second section of the Maokou Formation is Ⅱ to Ⅲ porous reservoir. The reservoir foundation is composed of high-energy beach deposits. The leaching and dissolution of atmospheric fresh water during the contemporaneous period is the key to reservoir formation. The reservoir has been improved and maintained through shallow burial dolomitization.

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.

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.