With the growing global demand for nuclear energy, the evaluation of the quality of uranium resource distribution and the precise measurement of reserves have become increasingly important. The uranium fission prompt neutron logging technology, as a critical tool for uranium ore logging exploration, offers the advantage of providing quantitative results unaffected by radioactive equilibrium. However, the measurement accuracy is influenced by the pulse width and yield of the neutron source. This study utilizes a uranium logging instrument equipped with an associated particle sealed-tube neutron generator, which enables time and spatial statistics of the companion α particles emitted by the outgoing neutrons. This approach helps to eliminate interference from the source neutrons and enhances the accuracy of the logging results. In the simulation process, to obtain information on neutron emissions during logging and the timing signal responses of both the companion α detector and the epithermal neutron detector, we propose a response time simulation method that combines Monte Carlo simulation software with MATLAB. By appropriately setting the pre-delay time and gate width, a relationship curve between the count rate and uranium content in formations with uranium levels ranging from 0 to 1.00% was established. The results from validation samples indicate that the calculated uranium content show a deviation of less than 0.1% from the actual values. When the uranium content in the formation exceeds 0.5%, the relative deviation is within 10%. This method meets the exploration requirements and demonstrates significant application value for uranium ore logging.

Machine learning algorithms can automatically learn and extract features from a large amount of geological data to achieve fast and accurate lithology identification. In this paper, the logging data of several wells in a sandstone-type uranium deposit in Inner Mongolia were randomly divided into training sets and verification sets according to the ratio of 7∶2. The model structure was adjusted and the hyperparameters were optimized for training. BC1401, BC2802, BC4603 and BC7206 well were used for testing to realize the comparative analysis of 5 kinds of models, such as random forest, XGBoost, K value proximity algorithm, BP neural network and SMOTE-LSTM algorithm. The results show that SMOTE-LSTM model has the most superior stability and accuracy, with an accuracy of 84.6%.

In order to clarify the leaching effect of horizontal well technology on in-situ leaching of uranium, a numerical simulation method was used to study the influence of different parameters on "Horizontal Well Injection-Vertical Well Pumping" and conventional "Vertical Well Injection and Pumping". The results show that compared with "Vertical Well Injection and Pumping", the length of horizontal wells is proportional to the leaching range, the vertical leaching range of "Horizontal Well Injection-Vertical Well Pumping" is small, the plane sweep efficiency is high, the dead corner of leaching is small, and the effective utilization rate of leaching solution is high; it has a wide coverage in the horizontal direction and have significant advantages in the treatment of thin uranium ore deposits. The ratio of horizontal permeability to vertical permeability has a greater impact on the leaching of "Vertical Well Injection and Pumping". When the vertical permeability is low, the leaching effect of horizontal well sections is better than that of vertical well sections; the amount of pumping and injection fluid is positively correlated with the leaching range. As the amount of pumping and injection fluid increases, the dead corners of leaching of both "Horizontal Well Injection-Vertical Well Pumping" and "Vertical Well Injection and Pumping" decrease. The increase in the amount of pumping and injection fluid has a greater impact on the leaching effect of "Horizontal Well Injection-Vertical Well Pumping". When the flow rate reaches 210 m³/d, the leaching range of the ore layer of "Horizontal Well Injection-Vertical Well Pumping" is higher than that of generalized "Vertical Well Injection and Pumping".

In the in-situ leaching of uranium, uranium migration is influenced by both groundwater flow and solute diffusion, and this process can be effectively modeled using the advection-diffusion equation. Accurately modeling the variation of uranium concentration over time and space is crucial for predicting uranium migration in groundwater during in-situ leaching of uranium. Traditional numerical methods, such as the finite difference method, are computationally intensive and prone to errors while dealing with high-dimensional, complex problems. Therefore, this research aims to explore the applicability and accuracy of physics-informed neural networks (PINN) in solving the advection-diffusion equation. Through numerical simulations of the one-dimensional advection-diffusion equation, and by comparing the PINN solutions with numerical and analytical solutions. The results show that PINN provide higher accuracy and better alignment with the analytical solution over long-term simulations compared to numerical methods. Furthermore, PINN exhibit certain extrapolation capabilities. Additionally, the introduction of dropout enhances the generalization ability and convergence speed of the PINN model, confirming the potential of PINN in solving complex physical problems.

As the mining depth of a uranium mine continues to increase, the ore body shows a trend of decreasing thickness and increasing inclination angle. This paper focuses on the steeply inclined thin ore veins of the uranium mine, utilizing the AHP-TOPSIS method for comparative analysis of different mining methods, and proposes a high-segment continuous efficient collaborative mining method suitable for the thin ore veins in this mine. Based on this, the numerical analysis is conducted using FLAC3D to examine different structural parameter schemes of the stope, analyzing the stress field, displacement field, and distribution characteristics of the plastic zone during the mining process, ultimately acquiring the optimal stope structural parameters. The results indicate that: no tensile stress was observed in the top and intermediary pillars in scheme 1 to 4, while a small amount of tensile stress occurred in schemes 5 and 6; the proportion of the plastic zone varies from 22.52% to 27.98% across scheme 1 to 6, with scheme 3 demonstrating better stability. Considering both safety and economic factors, the optimal stope structural parameters are determined to be a top pillar height of 5 m and an intermediary pillar width of 8 m (scheme 3).

The accuracy of hydraulic conductivity holds great significance for the subsequnce research and exploitation of the in-situ leaching sandstone-type uranium deposit. Taking the in-situ leaching technology of sandstone-type uranium deposit as the research object, based on the current research status of hydrogeological well completion technology and hydraulic conductivity calculation methods at home and abroad, this paper analyzes the influencing factors of hydrogeological well completion quality on hydraulic conductivity calculation. Through VB visual programming software, the loopholes of human error in calculation and curve drawing are made up, and the calculation of hydrogeological parameters of deposit is more concise, efficient and accurate.

The "CO₂+O₂" leaching process is an artificially intensified water-rock interaction process that leads to the dissolution of non-uranium minerals, which enter the leaching solution system and cause changes in the dissolution and precipitation state of the minerals in the leachate. Geochemical simulation methods were used to simulate ion species in the leachate and the mineral leaching equilibrium studying the dissolution, migration, and precipitation of minerals during the in-situ leaching mining process. For the first time, the conditions and influencing factors for the precipitation of manganese minerals were studied, targeting the characteristics of strong groundwater reducibility and high carbonate content in the target deposit.The results show that under neutral leaching conditions, uranium in the leachate mainly exists in the form of UO₂(CO₃${)}_{3}^{4-}$ followed by UO₂(CO₃${)}_{2}^{2-}$, and the proportions of the two are affected by pH. The saturation indices of carbonate minerals in the neutral leaching leachate of the study area are all greater than zero, indicating a supersaturated state, and pH is the main factor controlling the precipitation of carbonates, with the critical pH for calcium carbonate precipitation being 6.7 and for calcium magnesium carbonate precipitation being 6.5. The saturation indices of sulfate minerals are all less than zero, and no precipitation of calcium sulfate will occur in the formation, and the precipitation of calcium sulfate is mainly controlled by the content of calcium ions and sulfate ions. Under neutral leaching conditions, iron mineral precipitation is likely to occur and is greatly affected by pH conditions; at the same time, manganese-containing minerals will precipitate in the leachate, and the redox conditions are the main factors affecting their dissolution and precipitation; some silicon-containing minerals in the leachate are in a supersaturated state, and their dissolution and precipitation are greatly affected by pH The research results are of great significance for the prevention of precipitation in in-situ leaching mining.

A sandstone-type uranium deposit in Xinjiang belongs to auspicious prospecting stage with exploration line of 200 m×200 m, low exploration degree, thin ore bed and low uranium content. In addition, there are complex hydrogeological conditions with poor permeability (permeability coefficient is only 0.045 m/d) and high pressure head. No leaching test work has been carried out in this deposit area. In order to study the leaching of uranium resources in the deposit, field leaching test was carried out by adopting neutral leaching and improving the pressure leaching technology, the results show that the average extraction volume of single hole is 1.7 m³/h, the average mass concentration of uranium in leaching solution is 40.37 mg/L, the maximum mass concentration of uranium in single hole is 390.22 mg/L, and the annual leaching recovery is 13.39%, it provides technical support for the exploitation of uranium resources in the deposit.

To investigate the adsorption characteristics of sodium dodecylbenzene sulfonate on scheelite surface, the water bath shaking method was used to study the adsorption capacity, kinetics, and thermodynamics. The effects of pH, reagent concentration, temperature on the adsorption characteristics were explored using kinetic and thermodynamic equation models. The results show that under pH=10, the adsorption capacity of sodium dodecylbenzene sulfonate on scheelite surface is the largest, while under pH=7, the adsorption rate is the fastest, which conforms to the pseudo-second-order kinetic equation. Within a certain range, the adsorption capacity of dodecyl benzene sulfonate on scheelite surface is positively correlated with the reagent concentration and temperature. The adsorption process conforms to the Freundlich equation, which is an endothermic reaction of heterogeneous multilayer adsorption.

In order to solve the problems of microwave plasma decomposition of ¹³CF₄, such as complex operation process, harsh decomposition conditions and easy corrosion of reaction tubes,the thermal catalytic decomposition of ¹³CF₄ to produce ¹³CO₂ was studied. Under the condition of anhydrous and high temperature, ¹³CF₄ was decomposed into ¹³CO₂ by gas-solid reaction between ¹³CF₄ and solid defluorination agent, using γ-Al₂O₃ as solid defluorination agent, meanwhile, the metal oxide in the defluorination agent is converted into metal fluoride. The results show that when the flow rate of reaction gas is 120 mL/min, the loading amount of catalyst is more than 60 g, the content of O₂ in feed gas mixture is more than 50%, and the temperature of high temperature tubular furnace is 900℃, the conversion of γ-Al₂${{\mathrm{O}}_{3}}_{}$ catalyst to ¹³CF₄ gas is over 90%, which has good catalytic decomposition performance and can realize continuous catalysis and decomposition. The catalytic decomposition process has the advantages of simple process, convenient operation and very high carbon yield, and can be used in industrial production.

In the process of uranium dioxide hydrofluorination in the uranium conversion workshop, the opening and feeding of uranium dioxide raw material drums need to be operated manually, in order to reduce the risk of radiation exposure of the operators, the design of the handwheel lid opening robot control system for uranium dioxide raw material drums. The system adopts STM32F407IG series as the main control chip, and uses USB communication module to communicate with the servo motor of the robot arm for the motion control of the robot arm; proposes and adopts the robot arm positioning method based on the combination of key point detection and robot inverse kinematics to realize the accurate positioning and smooth switching of the robot on the handwheel lid of the uranium dioxide raw material drum; at the same time, designs the monitoring and control interface of the upper computer. Experiments show that the robot can complete the identification and localization of the handwheel well, and the mechanical gripper can smoothly insert into the spokes of the handwheel and rotate as required.

The Husab Uranium Mine has complex ore body and issues of ore body displacement during production blasting, which leads to severe ore-waste mixing. Additionally, there is a lack of measurement methods for the truck after loading. To detect the grades after loading and distinguish the ore from the waste, further to control and measure the ore dilution and ore loss, Husab Mine designed and developed the radiomatric truck scanner. By determining the exact time points of entry and exit through infrared beam detection, and identifing the truck identities using radio frequency identification technology, the dynamic scanning is achieved. By using three sets of gamma spectrometers, the error caused by irregular ore loading and deviations in truck driving paths, is minimized. By integrating the on-site data collection system, the server-based data management system, and the client data management system, the management of multiple truck scanner become available. By connecting the truck scanner to the dispatch system, the scanner data can be used to guide trucks on where to unload at the stockpile. To assess the impact of the truck scanner on uranium mine production, both the shovel boundary model data and truck scanner data were compared against the grade control model data, which serve as a benchmark, to calculate the dilution rate and ore loss rate under each scenario, the dilution rate and ore loss rate dropped from 8.14% and 12.62% to -3.36% and 4.85%. The summary and Analysis of two months' production data revealed that, the scanner can effectively distinguish the ore with different grades and seperate the ore and waste. It’s found out that the ore transported reduced 8.4%, the recovered metal increased 4.7%, and the average grade on the stockpile increased 19.8%. These findings demonstrate the significant and positive impact of the truck scanner on production at Husab Uranium Mine.

The electric control valve in the ⁷⁶Ge isotope production process is controlled by the PID module of the DCS (Distributed Control System) to regulate the internal pressure of the cascade pipeline. However, when the pressure of the process system fluctuates greatly, the existing control method of electric valve can not achieve the optimal control effect, which leads to the controlled process pressure exceeding the operating safety limit and has a serious adverse impact on the safe and stable operation of the process system. Aiming at the problem of weak control performance of electric valve under abnormal pressure, this paper put forward a control scheme to optimize DCS control configuration program of electric valve. Actual operation shows that the optimized control program avoids significant fluctuations in process pressure under abnormal conditions, effectively ensuring the safe and stable operation of the ⁷⁶Ge isotope production line.

This paper focuses on the abnormal fluctuation of yield during the electron beam welding process of fuel rods. Considering that the main defects leading to the rejection of fuel rods are surface scratches and out-of-tolerance straightness, through analysis and research, it is clarified that the direct causes of the abnormal yield of fuel rods are the excessively large aperture of the welding tooling baffle, the excessive use of the welding top, and the design of the top bearing. By taking measures such as reducing the aperture of the baffle, determining the reasonable number of uses for the welding top, and designing the top bearing, defects can be controlled in a timely manner, the yield can be improved, the manufacturing cost can be further reduced, and a foundation can be laid for the subsequent exploration of fuel rod manufacturing processes.

In order to promote the informationization construction of mining enterprises and enhance the safety informationization management capabilities, we explore the application of Python programming language and PyCharm editor to establish a basic database and big data analysis model for safety inspections in a certain mining enterprise. We construct a multi-dimensional analysis and evaluation system for historical safety inspection issues, new safety inspection issues, and other data, including time, space, problem categories, and causes. We explore the laws and development trends of intrinsic safety and safety inspection problems, and take targeted solutions accurately. The establishment of databases and analysis model can also be used for comprehensive evaluation of security inspection issues, visually displaying important information such as the time, place, category, and cause of the problem, providing objective data support for timely detection of repetitive problems and hidden danger investigation, avoiding the long-term existence of security problems that cannot be eradicated, and effectively reducing security risks. At present, the security big data model is mainly applied in security inspection work, and there is still room for exploration in the fields of security management system construction, "dual control" system operation, security education and training, accident prediction and warning in the future.

Dexing Copper Mine integrates the organization and management of the mining production process with modern mining technologies. Through the DIMINE 3D mining software, digital modeling and updates of the resources in certain mining areas have been completed. However, issues such as data silos in the existing CAD-based geological and surveying system, data integration challenges, and the absence of a database version in the early stages of the DIMINE software continue to constrain the mine's progress toward intelligent mining. To promote smart mining, enhance the efficiency and economic viability of mining processes, and address fundamental aspects of geology, surveying, and mining in intelligent mining construction, the functionalities of the original system were analyzed, researched and optimized. A customized development was carried out based on the DIMINE software system to achieve full coverage of the existing geological and surveying platform's functions and data at Dexing Copper Mine, ensuring the preservation of historical data and meeting the operational requirements of geological and surveying tasks.

Guyuan 460 associated uranium molybdenum resources belong to amorphous colloidal sulfur molybdenum ore, which has the characteristics of complex mineral properties, difficult beneficiation and metallurgy, and long process flow. After more than 20 years of experimental research and production practice, a process development technology system of "oxygen pressure acid leaching modified filtration extraction separation process water cycle" has been formed. This article summarizes the technological innovation process of Guyuan 460 uranium molybdenum mine, which comprehensively innovates and practices from multiple aspects such as efficient leaching of uranium molybdenum ore, solid-liquid separation of slurry, separation and purification of uranium molybdenum, product preparation, process water recycling, key equipment and material engineering applications. Finally, an oxygen pressure leaching demonstration mine with an annual processing capacity of 200 000 tons of uranium molybdenum ore was built, greatly improving the scientific and technological level of complex associated uranium molybdenum resource development in China. It is a typical embodiment of new quality productivity in the mineral field.

Uranium is an important raw material for the development of nuclear power, and radioactive wastewater is generated during the mining and processing of uranium resources. The treatment of radioactive wastewater has attracted much attention. This article introduces the research progress of radioactive wastewater treatment technology in uranium mines from the aspects of physical, chemical, and biological methods,and explores the interaction mechanisms, development status, advantages, and limitations of various methods for removing radioactive nuclides in the process of treating radioactive wastewater, such as oxidation-reduction, adsorption, and chelation precipitation. Reasonable suggestions and prospects are proposed for the application of radioactive wastewater treatment technology in uranium mining and metallurgy.