This article made a temperature field analysis in a nearshore waters of a nuclear power plant in Fujian Province，and uses Landsat-8/9 TIRS thermal infrared satellite remote sensing data was used to study the temperature field distribution characteristics in different seasons before and after nuclear power operation. The research results show that the temperature inversion results of Landsat-8/9 TIRS data based on the radiative transfer equation algorithm have high reliability. Before the operation of nuclear power plants，there were significant differences in temperature field characteristics in different seasons in the sea area near the nuclear power plant site. In winter，the temperature field was generally more uniform，slightly higher in the south than in the north and slightly higher in the east than in the west. The water temperature near the water intake was slightly higher than that near the drainage outlet. The maximum temperature difference within 4 km of the plant site was about 1.5 ℃，and within 2 km was about 1.0 ℃. In summer，there was a large temperature difference in the region，showing the characteristics of being higher in the north and lower in the south，and higher in the west and lower in the east. The maximum temperature difference within 4 km of the plant site was about 5.5 ℃，and within 2km was about 2.5 ℃，and some parts were distributed in a disorderly manner. The water temperature near the drainage.After the operation of the nuclear power plant，the characteristics of the regional temperature field are basically the same as before，but there are obvious high-temperature bright spots at the drainage outlet，with a maximum temperature exceeding the surrounding area by 3.0 ℃. The intensity and area of the high-temperature bright spots in winter are greater than those in summer，indicating that the impact of thermal drainage discharge on the temperature field in the nearby sea area is stronger in winter than in summer.The flow direction of the current affects the local distribution of the temperature field，and the diffusion direction of the warm water discharge is related to the flow direction of the current. The Landsat-8/9 TIRS data basically meet the needs of regional temperature field distribution research，but it is difficult to realize the monitoring of full tidal temperature and drainage.

Delingha depression in the eastern Qaidam basin is believed a potential area for sandstone type uranium deposit in the target stata of the Neogene Shizigou formation and the Shangyoushashan formation. The in-depth investigation on the sedimentary facies characteristics and evolution of strata will provide valuable guidance for uranium exploration. Detailed observations of lithofacies assemblages and sedimentary formation in field outcrops，drilling cores, and well logging analyses have identified that the alluvial fan-braided river delta-lake are the dominant sedimentary facies type in the study area. Among these，the distributary channels in the braided river delta plain and subaqueous distributary channels in the braided river delta front are well-developed with significant scale and good connectivity，providing a favorable sedimentary environment for uranium enrichment. This new understanding has contributed to the knowledge of the spatial and temporal distribution of sand bodies in the Shizigou formation and the Shangyoushashan formations in the eastern Qaidam basin，and provided key information in guiding the future prospecting and exploration.

Underground Research Laboratories (URLs) play a crucial role in the siting process of high-level radioactive waste disposal. A study of evaluating the structural stability of Beishan URLs site was carried out, considering regional seismic and geological environment. After over a decade of site stability evaluations，techniques were developed to identify weakly active faults in stable crustal areas and assess their seismic potential. A method for determining design seismic motions was proposed，accounting for the source，propagation path，and local site characteristics. An efficient，high-precision time-domain analysis method for deeply buried，complex URL systems was proposed，along with a rock-structure numerical model to reveal seismic performance and its impact on the structural stability of the Beishan URL. The research determined the seismic fortification intensity for the Beishan URL，provided key seismic input parameters for structural design，and presented the seismic response results, supporting the construction of a site descriptive model (SDM) and site suitability assessment for the disposal repository.

A year-long investigation of air radon concentration at Beishan URL site and its surrounding areas was carried out using solid-state nuclear track detectors at 24 points，with quarterly sampling and measurements conducted. The results indicated that the annual radon concentration in the region ranged from 10 to 64 Bq·m^-3，with a geometric mean (GM) of 27 Bq·m^-3. The overall radon levels exhibited distinct seasonal variations, with the highest concentrations occurring from April to June and the lowest from January to March. The differences in radon concentrations between different areas were small and remained relatively stable. Construction disturbances in the active construction zones had a localized impact on radon concentrations，but due to favorable air diffusion conditions，this effect did not result in a widespread increase in radon levels. This suggests that the direct impact of human activities on regional radon concentrations is limited. According to the Pearson correlation coefficient analysis，a significant positive correlation was observed between temperature and radon concentrations，with radon levels increasing as temperatures rose at most measurement points. In contrast，the influence of wind speed on radon concentrations was more complex，with considerable variability in correlation across different points，likely influenced by other factors，warranting further investigation. This study provides data support and practical insights for long-term radon monitoring and health risk assessment at the Beishan URL.

The microscopic pore structure is of great significance to the study of concrete materials. However，the traditional pore structure testing methods， such as nuclear magnetic resonance (NMR)，mercury intrusion porosimetry (MIP)，optical microscopy，X-ray tomography (X-CT)，and nitrogen adsorption，still have some limitations in terms of pore morphology and nanoscale pore characterization. In this study，we proposed to use argon ion polishing-scanning electron microscopy method to study the microscopic pore structure in concrete，prepared concrete samples with high-quality mechanically damage-free surfaces， and qualitatively investigated four types of pore structure in concrete. Large-area backscattered electron images were collected, and the pore porosity，pore diameter，pore shape factor，and graded porosity of the pore structure were quantified by ImageJ，Avizo，and other software. This method achieves the qualitative analysis and quantitative characterization of concrete microporous structure, which is of reference significance for the research and analysis of the microstructure of concrete materials.

In order to explore the uranium mineralization specific characteristics of granite， the geochemical characteristics of Mesozoic-producing and non-producing uranium granites in the Nanling region were analyzed on the base of systematic collection of previous research. The results show that both uranium deposit host and non deposit granites are mainly formed by partial melting of Precambrian metamorphic sedimentary rocks，but the uranium deposit host granites are mainly formed by partially melting U-rich mudstones, while the non-deposit granites are the partially melted products of uranium-depleted sandstone. Compared with uranium deposit host granites，the biotite crystallization temperature in uranium deposit host granites is relatively low，F-rich and Cl-poor，and the magmatic melt has lower oxygen fugacity values，suggesting that uranium deposit host granites formed at relatively low temperatures and low oxygen fugacity. The low temperature, low oxygen fugacity，and F-rich physical and chemical environment are favorable for U to continuously enter the melt during the magma crystallization and differentiation and combine with oxygen to form uranite that are liable to undergo secondary alteration. The formation of uranite provides a good material basis for uranium mineralization.

The Lianhua Mountain area in Yingjiang county，Yunnan province，is one of the several w regions in Yunnan that contains medium-high temperature geothermal resources. Previous geothermal research was more focused on meeting the actual production needs, lack of the in-depth exploration in aspects such as the sources of geothermal water chemical components，water-rock interactions，multi-method evaluations of reservoir temperatures，and the genetic mechanisms of geothermal systems. Based on hydro-geochemical methods，this paper aims to identify the circulation process of geothermal water and clarify the formation mechanism of the geothermal system. Through mathematical statistics and correlation analysis of hydrochemical indicators，Piper diagrams，Schoeller diagrams，diagrams of the relationships between anions and cations，hydrogen and oxygen isotope analysis，SiO₂ geothermal temperature scale，and the multi-mineral equilibrium method，a systematic study was carried out on the geothermal water chemical types，sources of major ionic components，recharge sources of geothermal water，reservoir temperatures，and circulation depths in the Yingjiang basin. Subsequently，the origin of geothermal water was inferred. The results show that the hydrochemical type of the geothermal fields in the Yingjiang basin is HCO₃-Na type. The major ionic components in the geothermal water originate from the dissolution of halide minerals，feldspars，fluorides，gypsum，and other minerals，and are influenced by cation-exchange reactions. The geothermal water is mainly recharged by mountainous atmospheric precipitation at an altitude between 1 348-1 571 m. The deep reservoir temperature is 168.2 °C. During the upwelling process，the geothermal water undergoes water-rock interactions and cation-exchange reactions with the surrounding rocks，resulting in the changes of its hydrochemical components. The heat source of the reservoir mainly comes from the magma chamber in the deep crust. Part of the heat is transferred upward in the form of heat convection through the connection of the Sudian-type fault zone，and the other part is transferred upward through rocks in the form of heat conduction. Atmospheric precipitation infiltrates and circulates along the water-conducting structure，absorbs the heat transferred upward by the magma chamber，and heated. Eventually，a convective-conductive composite hydrothermal system dominated by HCO₃-Na type water formed near the fault zone.

In recent years, significant progress has been made in the exploration of sandstone type uranium deposits in the Subash area of the Turpan-Hami basin. Exploration shows that heterogeneity of sand bodies is one of the key factors controlling uranium mineralization. This article systematically analyzes the thickness, sand content, sedimentary facies, aquiclude numbers, ore bearing sandstone grain size, and organic matter content of the Xishanyao formation in the Subash area, identifies the spatial variation characteristics of sand heterogeneity, and explores its relationship with uranium mineralization. The research results show that the thickness of sand bodies in distributary channels is relatively large, with good connectivity and strong homogeneity. The heterogeneity is strong at the bay between the distributaries, with well-developed mudstone barriers and thin sand bodies. The variation of spatial heterogeneity in sand bodies causes the changes in the direction of oxygen and uranium water transport, resulting in a decrease in fluid transport velocity, leading to uranium unloading and precipitation for the mineralization. In the Subashi area, the favorable condition for uranium mineralization is that the thickness of the sand body is 19-54m, the sand content is 60 % -80 %, the number of aquiclude is 3-5, and the lithology is fine sandstone at the transition between the underwater distributary channel and the bay with high organic matter content.

In order to accurately measure ²³²Th in the waste residues of associated radioactive mines, especially for the measurement of slag samples under non-equilibrium conditions, and to provide data support for radiation environment supervision, a method for measuring ²³²Th in slag using a high-purity germanium γ spectrometer was established. The method involves indirect measurement by selecting the characteristic γ rays of the daughter nuclides in the decay chain of ²³²Th, and calculating its specific activity by the relative comparison method. The slag samples in a non-equilibrium state are sealed for 20 days to enable ²²⁸Ra and ²²⁸Ac to reach equilibrium, and ²²⁸Th, ²²⁴Ra and subsequent daughter nuclides to reach equilibrium. Then, the specific activity of the parent nuclide ²³²Th is obtained through conversion relationships. This method is accurate and efficient, with a detection limit of 1.1 Bq・kg^-1, a precision better than 5 %, and a relative error lower than 5 %. The method of measuring ²³²Th in slag using a high-purity germanium γ spectrometer does not require complex chemical treatment, which makes up for the deficiencies of inductively coupled plasma mass spectrometry. The calculation method under non-equilibrium conditions is also more reliable than using the average value of a single characteristic peak or multiple characteristic peaks.

The rapid identification of radionuclides is a critical component of nuclear material detection systems，essential for improving the performance and efficiency of radiation detection. Traditional nuclide spectrum recognition methods typically involve multiple complex steps，such as noise reduction，background subtraction，and feature extraction，which are computationally intensive，time-consuming，and inefficient，making them unsuitable for rapid response in practical applications. To address these issues，this paper proposed a rapid nuclide spectrum recognition algorithm based on the MobileNetV3 neural network，which achieved efficient nuclide recognition by optimizing data processing and model training methods. A series of simulated datasets were generated using Monte Carlo (MCNP) simulation software，including scenarios with different radioactive sources and particle counts，varying distances between NaI detectors and the sources，and mixed nuclide environments. These diverse datasets were used to train and validate the network model，enhancing its generalization capability. To better process the full-energy peak characteristics of gamma spectra，this study designs a preprocessing method based on a sliding window approach，which incrementally transforms one-dimensional spectral data. Subsequently，the transformed spectral data is mapped into two-dimensional grayscale images using Hilbert curves and input into the MobileNetV3 model for training and prediction. Experimental results demonstrate that the proposed neural network model performs exceptionally well in rapidly processing spectrum data handled by the sliding window method，achieving high-precision recognition of different nuclides while maintaining efficient learning. In terms of model performance，using sliding window sizes of 23 and 25 results in faster convergence and significantly improved recognition accuracy. This study highlights the effectiveness of integrating deep learning with nuclide spectral characteristics，providing a novel and efficient solution for nuclear material detection systems.