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.

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.

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.

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.

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.

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.

In-situ leaching of uranium, as a green uranium mining technology, generates massive data in production operation, which are available for the big data analysis and trend prediction to improve the reliability of technicians in making production plans. In the current prediction algorithms, the attention mechanism in the temporal prediction model based on the encoder-decoder structure has the problems of computational complexity and high memory consumption. In this paper, we proposed a depthwise separable convolutional model, in which the semantic damage caused by fixed segmentation was reduced by the dynamic sequence segmentation module, and the depthwise separable convolutional mixer module was used to reduce the model running time and capture local features as well as global features. The results show that the Mean Square Error (MSE) and Mean Absolute Error (MAE) of the depthwise separable convolutional hybrid network model are reduced by 1.04% and 4.13% respectively, compared with Patch Time Series Transformer (PatchTST), and the proposed dynamic sequence segmentation module MSE and MAE are reduced by 7.32% and 5.03% respectively, compared to the original model; in the comparative performance analysis, the training speed of this model is 59.91% faster than the Trend Seasonal Decomposition Linear (Decomposition Linear, DLinear) model. The depthwise separable convolutional model can accurately predict the future trend of sulfuric acid injection volume in the production operation of the mining area, improve the existing prediction model for in-situ leaching data by solving the problem of long running time, large running memory, poor data fitting problems, which provide a theoretical and practical reference for the decision-making of in-situ leaching production.

The in-situ leaching of uranium is influenced by deposit conditions, leaching environments, and various other factors, resulting in a low utilization rate for certain resources. To facilitate the rational development of these resources, a device for preparing leaching agents was designed to enhance the leaching process by increasing the concentration of sulfuric acid in areas where the resources is difficult to leach. The results show that the relative deviation in concentration remains below 1.5%, allowing for precise and stable preparation of acid either regionally or at individual boreholes. By using a 15~20 g/L sulfuric acid solution as a leaching agent, the unit uranium leaching rate of the refractory leaching uranium resources can be increased from 24.8% to 53.7%. The amount of sulfuric acid used and the increase in residual acid are only 11.1% of those used for strengthening leaching results in the entire mining area. This device achieves the leaching of the refractory leaching uranium resources with low consumption of sulfuric acid and has little impact on subsequent hydrometallurgical processes.

This article studies the pretreatment methods of solutions with high iron content, high nitrate content, and low uranium content. The results show that under the pretreatment conditions of using 4% TOPO cyclohexane solution as the extractant, a volume ratio of organic phase to water phase of 1:6, an extraction time of 2 minutes, an extraction temperature of 25℃, and a mixed complexing agent as the counter extractant, the extraction efficiency reached 99.0%, and the counter extraction efficiency was 99.0%. The 5-Br-PADAP colorimetric method can accurately determine the uranium content in the pretreated solution after extraction reverse extraction of high iron, high nitrate, and low uranium content solutions. The relative standard deviation of this method is less than 8.11%, the recovery rate of spiking is 96.0%~99.5%, and the detection limit of this method is 0.013 mg/L.