The accumulation of aerosols in the downstream eddy caused by the complex hilly terrain underlying surface is still the main obstacle to accurately predicting the aerosol’s dispersion concentration distribution of atmospheric emissions from nuclear power plants. In particular, the asymmetric distribution of downstream aerosols has not attracted widespread attention in previous numerical simulations and experimental studies. This paper focuses on the dispersion concentration distribution of aerosol downstream of a two-dimensional hill model under neutral atmospheric conditions. The downstream aerosol dispersion concentration was obtained through CFD numerical simulation and laser measurement wind tunnel experiments. Considering the accumulation of aerosols in the eddy on the leeward side of the hill and the rebound effect on the ground, a dispersion concentration distribution model combining Gaussian distribution and Gumbel distribution is proposed. The concentration distributions fitted by the Mixed-Gaussian-Gumbel model and the Gaussian model are compared with the numerical simulation and experimental results. The results show that in contrast to the Gaussian model, the Mixed-Gaussian-Gumbel model has better consistency with the asymmetric distribution of aerosols behind the hill, and the fractional bias is less than 0.135. This study can provide an accurate assessment of the atmospheric dispersion of aerosols in complex hilly terrain underlying surface.

Uranium ore concentrate (UOC) is a group of intermediate products widely used in the nuclear fuel cycle. Following the recent characterisation and classification of UOC industrial product powders for nuclear forensic analysis, this paper presents an experimental study of the hygroscopic properties of these UOC stockpile samples for long-term storage and the inhalation risk assessment of uranium particles. Two independent techniques, the density balance and Attenuated Total Reflectance-Fourier Transform Infrared Spectroscopy (ATR-FTIR), were utilised to measure increases in sample weight and the infrared absorption peak of ten UOC samples, respectively, due to hygroscopic growth. Taking (NH4)4((UO2)2(SO4)O2)2(H2O) powder as an example, the hygroscopicity mechanism was investigated experimentally by monitoring hydration and dehydration processes using Diffuse Reflectance Infrared Fourier Transform Spectroscopy (DRIFTS) and Thermogravimetric-Differential Thermal Analysis (TG-DTA), respectively. The hygroscopic growth factor of (NH4)4((UO2)2(SO4)O2)2(H2O) sample was determined using the above two techniques under precisely controlled temperature and humidity conditions. Screening results show significant differences in the hygroscopicity of sodium- and ammonium-containing UOC powders, despite their similar elemental composition, infrared functional groups, and crystal structures. The porous surface and hygroscopic component are beneficial for hygroscopic growth. Observation of the hydration and dehydration process confirms that the physical adsorption of water is the dominant mechanism. The hygroscopic growth factors of sample mass and infrared absorption peak increase with rising relative humidity above 80% RH. The hygroscopic growth curve of (NH4)4((UO2)2(SO4)O2)2(H2O) powder could be described using a simplified κ-Köhler equation. A dense surface, low RH (<80%) and an inert buffer gas are recommended for material processing and stable storage. For (NH4)4((UO2)2(SO4)O2)2(H2O) particles possibly inhaled in the respiratory tract, the effect of hygroscopic growth on the deposition profile is also discussed.

This numerical study investigates the inaccuracy and instability of equivalent ring-source determination in dual-detector Improved Segmented Gamma Scanning (ISGS) for 400 L low and intermediate level radioactive solid waste drums. The effects of three key geometric parameters—detector eccentricity, collimator aperture radius, and measurement distance—on the full energy peak efficiency ratio function were systematically evaluated using a numerical efficiency-transfer method. Analyses were performed for 0.662 MeV γ rays from 137Cs decay and 1.333 MeV γ rays from 60Co, considering representative single point and multi point source distributions at different radial locations. A quantitative criterion was employed to identify measurement configurations that provide a sufficiently near-linear and well-conditioned efficiency-ratio mapping for stable equivalent-radius inversion. Under the recommended configuration, the reconstruction error of the equivalent ring source radius remained below 8%, and the activity reconstruction error was within 20%, outperforming Segmented Gamma Scanning (SGS) in drums with non-uniform source distributions. The proposed geometry selection strategy provides practical guidance for reducing source location induced errors and improving activity quantification in waste-drum measurements with complex source distributions.

The dispersion uplift of the aerosol plume due to the complex mountain subsurface and the residence of the plume in the clockwise turnaround flow behind the hill are still a major obstacle in accurately predicting the dispersion concentration distributions of aerosols in the atmospheric emissions from nuclear power plants, despite the use of complex numerical models. In particular, the effect of hill combination on dispersion trajectories and concentration distributions has not received widely attention in previous experimental studies. The focus of this study is on the effect of the distance between two identical parallel aligned hills on the dispersion trajectory and concentration distribution of the aerosol plume under neutral atmospheric conditions. A combination of planar particle laser concentration measurement method and CFD simulation was used to characterize the flow reattachment and plume trajectories as well as the dispersion distribution. The results show that when the interval between the two hills is less than 4H, the total reattachment length remains at 9H as in the case of a single hill, and the dispersion trajectory is basically consistent with that of a single hill. The concentration accumulates on the windward side of the second hill between valleys. When the distance between the two hills is greater than 12H, the reattachment length of the first hill recovers to 9H as in the case of a single hill, and the second hill begins to move away from the influence area of the first hill.

Rapid source term estimation is a key element of nuclear accident emergency response, and its accuracy largely depends on the data source: the spatiotemporal configuration of monitoring sites. This study uses similarity-validated boundary-layer wind-tunnel laser measurements to systematically investigate aerosol dispersion and concentration distributions for releases at different heights (0-2 & times;hill height ) over a two-dimensional Gaussian hill. By extracting virtual-source heights and characteristic concentrations and normalizing measurements at multiple monitoring locations across downwind distances and heights, key terrain-dependent influence scales on aerosol transport are revealed: when /less than or similar to 0.85, pronounced compression and near-surface accumulation occur on the windward slope; when /less than or similar to 1.69, significant accumulation appears in the leeward recirculation zone; when /greater than or similar to 1.69, dispersion approaches flat-terrain behavior. Based on spatial features of the normalized curves, monitoring-site layout recommendations are proposed (downwind distances /= -0.5, -0.1, 0.5, 7.4; measurement heights /= 0.5 on the hill and /= 0.1 on the downwind plain). An empirical inversion-initialization form = + (/)3.2 and the parameter relation ) = 7.5 & times; 10-6 exp ( / + 3.5 & times; 10-4 are provided to improve initial estimates for source-term inversion. The 0.2373 limitations of the 2D wind-tunnel experiments are discussed, and further validation and generalization via 3D numerical simulations and field observations are recommended.

Traditional Segmented Gamma Scanning (SGS) and Tomographic Gamma Scanning (TGS) reconstruct activities in low- and intermediate-level radioactive waste drums by assuming radionuclide distributions, which often differ from actual source distributions and lead to inaccurate detection efficiencies and large activity reconstruction errors in practical nondestructive measurement applications. This paper proposes a Compton scattering-based method for direct radioactive-source localization and activity reconstruction in a waste drum with unknown source number and positions. Valid events consisting of one Compton scattering interaction and one photoelectric absorption interaction in the first two layers of a CZT detector were used for source localization, followed by efficiency calculation and activity reconstruction. For single sources emitting 0.662 and 1.333 MeV gamma rays, the localization error was less than 1 cm. For multiple sources, distinguishability depended on source spacing. When the spacing was 6 cm or larger, individual sources were resolved, with localization errors generally below 1 cm. When the spacing was less than 6 cm, multiple sources were reconstructed as one broadened peak; the resulting localization deviations ranged from 1 to 2.3 cm, with a maximum of 2.26 cm. For distinguishable sources, the reconstructed activity error was within ±5%, whereas unresolved multi-source cases showed a maximum error of -15.96%.

To improve the sampling accuracy of micron-sized aerosols in gaseous effluent monitoring systems of nuclear facilities, this study conducts experimental investigations on aerosol deposition behavior in horizontal sampling pipelines. A comprehensive deposition velocity model is developed by incorporating the effects of surface roughness, turbulent diffusion, and gravitational settling. Based on this model, an engineering-oriented analytical method is developed to predict aerosol penetration efficiency in horizontal circular pipes. Experimental results indicate that pipe surface roughness significantly affects the near-wall flow structure and axial flow resistance. Even micron-level variations in roughness can lead to an order-of-magnitude change in aerosol deposition rates. In horizontal configurations, aerosol settling is jointly governed by gravitational and Brownian mechanisms, resulting in relatively low net deposition velocities. Further analysis reveals that aerosol penetration is influenced by the combined effects of gravity, turbulent eddies, and particle residence time. Notably, an optimal sampling velocity exists that maximizes penetration efficiency. The model predictions are validated against experimental results and compared with existing models, showing good agreement with the present data under the tested roughness conditions. The proposed method provides an engineering-oriented framework for predicting aerosol penetration in horizontal circular sampling pipes under the tested particle, flow, and roughness conditions, and may support the design and assessment of nuclear-facility sampling systems.

The application of intense current transient pulse radiation fields encompasses a wide range of fields, from scientific research to industrial application. The generation and application of this radiation have become an important direction of current research. Ray detection technology (such as neutron detection, gamma ray detection, etc.) plays a key role in understanding the working state, physical mechanism, and process of different pulse radiation devices. With a new energy-selective gamma-ray imaging technique based on a magnetic lens, the energy and spatial information of pulsed gamma rays can be obtained simultaneously. However, due to the limitations of angle and energy dispersion, the detection efficiency and spatial resolution of the system cannot be simultaneously optimized, which limits its practical application. To overcome this limitation, a method combining system optimization and imaging restoration is proposed to improve the performance of energy-selective gamma-ray imaging. In this article, the effect of beam-limiting hole size on detection efficiency and spatial resolution in an energy-selective gamma-ray imaging system is analyzed. The imaging dataset of the energy-selective gamma-ray imaging system is constructed using a Geant4 simulation, and a deblurring generative adversarial network (GAN) based on a weighted bidirectional feature pyramid is developed. The results demonstrate that by selecting Dx =60 mm and Dy =30 mm as the new beam-limiting hole size parameters, the detection efficiency of the imaging system can be improved by approximately four times, and the spatial resolution performance of 1.2 mm in the x-direction and 2 mm in the y-direction can be achieved by the proposed algorithm. Furthermore, the reliability of the proposed algorithm is substantiated by experimental verification.

LBB (Leak-before-break) radioactive aerosol monitor in the nuclear power plant requires knowledge of the source term to build the relationship between monitored radiation activity and the leak flow rate. The leak flow rate could be used to evaluate the risk of LOCA (Loss of Coolant Accident). The source term, including initial diameter distribution, and initial concentration, comes from the break of the liquid phase in the critical flow existing in the crack. The relationship between the source term and the critical flow is complicated and requires dimensional analysis to be built. Experiments of water and R134a under lower stagnant pressure and lower stagnant temperature than the primary loop are conducted to measure the critical flow pattern, spray shape, and droplet diameter distribution near the outlet of the slit (simplified crack). Non-dimensional numbers based on the outlet physical variables are calculated by TFM-DEM (Two-fluid Model-Delayed Equilibrium Model), and the relation between diameter distribution coefficients and non-dimensional numbers is built by regression analysis. It is found that the critical flow patterns are similar and have no relationship with the break, while the spray shapes could be split into three groups, and the break relationships are different among them. Linear discriminant analysis is used to classify different spray shapes and different breaking modes. The relations are effective as long as the range of major non-dimensional numbers related to the breaking process covers those of actual industrial cases. The initial concentration is researched using random sampling and regression analysis so that it can be calculated using the gas phase volume fraction at the outlet. The source term equations, non-dimensional analysis, and random sampling process would be of great help in the development of more accurate model for the source term of LBB aerosol monitor with more complete source term measurement results in the future.

核设施气态流出物监测系统需要对放射性物质进行连续取样和测量，气溶胶受到布朗扩散、重力、湍流等作用会在取样管道内产生沉积。本文针对水平取样管道微米级气溶胶穿透效率开展实验，并与国内外现有的经验公式和发表数据进行了对比验证。考虑有效粗糙度、湍流扩散、重力沉降的共同影响，提出了适用于扩散区与扩散-碰撞区的沉降速率预测修正公式，预测值与实验结果较为吻合。实验结果表明：由于粗糙度会改变近壁处流场和沿程阻力，所以不同粗糙度对沉降速率有显著影响，微米级的粗糙度改变也可能会使湍流沉降速率变化一个数量级。水平管中处于扩散区的气溶胶，其沉降受重力和布朗扩散机制共同控制，具有较低的沉降速率。位于扩散-碰撞区的气溶胶，穿透率受重力、湍流涡和管道内滞留时间的共同影响，会存在最佳取样风速点，使得穿透率达到最大值。

Accurate prediction of aerosol atmospheric dispersion concentration distribution in airborne effluents from nuclear power plants is very important for environmental assessment and nuclear accident emergency response. This study focuses on the plume dispersion centerline trajectory and concentration distribution of aerosols in the atmospheric boundary layer over a two-dimensional hill model under neutral atmospheric conditions. Through laser measurements inactive atmospheric dispersion wind tunnel experiments, the flow field around the hill and the aerosol dispersion concentration distribution released at different heights were obtained. According to the streamlines and considering the lifting effect of hill on plumes, a modification algorithm for plume centerline trajectories and concentration distribution in hilly terrain based on Gaussian dispersion model was proposed. The plume centerline trajectory and concentration distribution simulated by the modification algorithm and Plume Path Coefficient Treatment are compared with the experimental results. The results showed that due to the influence of clockwise circulation on the leeside of the hill, the aerosol dispersion trajectory was separated from the shape of the hill. The modification algorithm has better agreement with the experimental results, with NMSE and FB in 0-0.025, in the simulation of the plume centerline trajectory. For the simulation of concentration distributions, the modification algorithm slightly underestimates, but is more stable than Plume Path Coefficient Treatment, which has the performance that goes from far overestimation to underestimation along the downwind direction. This study can provide an accurate evaluation of aerosols atmospheric dispersion over hilly terrain.

BackgroundDuring the reconstruction of radionuclide activity of waste by conventional tomography gamma scanning (TGS), the measurement time is long due to the division of a large number of invalid voxels, and the reconstruction accuracy is low due to the iterative solution of the pathology equation. The traditional division method of encrypting only circumferential voxels does not significantly improve the reconstruction accuracy.PurposeThis study aims to solve the problem of long measurement time and low accuracy of TGS by elaborating the influence law of voxel division method on reconstruction accuracy.MethodsFor a 400 L cement waste drum with a radius of 35 cm, a coaxial HPGe detector with a detection efficiency of 40% (crystal diameter 6.09 cm, length 5.18 cm) was used at a distance of 74 cm from the center of the drum to measure two types of nuclides, 60Co and 137Cs. The error situation of the optimized method of voxel partitioning and the traditional voxel partitioning method were compared by random point source activity reconstruction experiments. By calculating the condition number and count rate deviation of different voxel partitioning methods, the influence law of voxel partitioning methods on the reconstruction accuracy was investigated.ResultsComparison results show that the radial encryption method leads to an increase in the number of very small value points and a decrease in the value of very large value points in the count rate deviation curve, which improves the reconstruction accuracy. Compared with the conventional division method, the voxel division optimization method reduces the number of voxels and thus the measurement time by about 9/10; at the same time, it reduces the number of conditions and the count rate deviation, which reduces the maximum reconstruction error by about 2/3.ConclusionAn optimized voxel division method proposed in this study makes use of the influence law of different voxel divisions on the reconstruction error through theory and experiment, hence improves the measurement accuracy and reduce the measurement time.

R134a has the advantage of conducting visible critical flow experiments because of the lower temperature and pressure at the critical point than water. Whether the water critical flow model is suitable for predicting the flow rate and the pressure profile of R134a critical flow is unknown. An experiment on the critical flow rate and the pressure profile of R134a critical flow in a slit, mimicking the shape of a crack in the pipe, has been conducted. The dimension of the slit and the subcooling degree at the entrance are changed in the experiment. The Delayed Equilibrium Model (DEM), which is accurate for the water critical flow mass flux in a slit, is verified based on the experiment results. The empirical coefficients in the original DEM are adjusted according to the approximate saturated curve of R134a. The conservative and aggressive approaches to changing empirical coefficients are verified, respectively. For R134a, the ratio of boiling pressure to saturated inlet pressure is determined to minimize the relative error of volume flow rate and pressure profile in the slit with 0.3 mm width. It proves that the aggressive approach is lower in relative errors and differences in relative errors among different slit widths and different subcooling degrees. For the aggressive approach, the abstract value of the relative error of volume flow rate is lower than 20% in most cases. The abstract value of the mean relative error of pressure is lower than 15% in most cases. Besides, the differences in relative errors among different slit widths are not significant, and the differences in relative errors tend to be zero as the subcooling degree increases. DEM is adequate for predicting the volume flow rate and pressure profile for the R134a critical flow in a slit. Nevertheless, the relative error of the volume flow rate should disperse around zero at low subcooling degree, which is not achieved in this research. Further optimization requires more rigorous analytical methods and experiment data to find the best set of empirical coefficients, and the effect of velocity difference may be introduced.

Accurately predicting the mass flux, pressure profile, and velocity profile of the critical flow in a slit is essential for analyzing the breaking process of the liquid phase and calculating the aerosol source term for leak-beforebreak (LBB) monitoring and Loss of Coolant Accident (LOCA) risk analysis. A new critical flow model combining Two-fluid Model (TFM) and Delayed Equilibrium Model (DEM) is built to get accurate profiles while avoiding the same phase velocity in DEM and the arbitrary critical flow criterion in TFM. The new model is verified using past experiments of the critical flow in a slit. It proves to be accurate in mass flux but not in critical pressure, with maximum relative errors of around 25% in mass flux and around 80% in critical pressure. The new model is optimized for higher accuracy in critical pressure. The empirical equation of saturated phase mass flow rate fraction gradient is optimized by conducting approximate pressure profile calculation and regression analysis. The maximum relative error decreases little while the ratio of critical pressure relative errors lying in the range of +/- 40% increases after optimization. In contrast, the difference in the average abstract relative error of pressure between original TFM-DEM and DEM is much larger, for the maximum relative error of mass flux and critical pressure are around 25% and 110%. The comparison between the original and optimized TFM-DEM proves that the new critical flow model is accurate in mass flux and can be optimized to raise pressure calculation accuracy. The comparison between the original TFM-DEM and DEM proves that the phase velocity difference is the major source of accuracy improvement in the pressure profile.

The process of pulsed X-ray imaging generates noise and blurring that significantly degrade image quality, lead to loss of image information, and interfere with accurate diagnosis of X-ray spot size and objects. Traditional radiation image restoration methods lack flexibility and generalization. Furthermore, neural network methods based on supervised learning require many actual image data sets to be obtained in advance, which limits network training. In this paper, we propose an unsupervised radiation image restoration method based on a deep image prior. The classical DeepRED framework is extended by adding weight-adaptive variational regularization. Automatic strategies are employed to estimate local regularization parameters, resulting in better noise removal and preservation of image edges and texture structures. The proposed method is evaluated through numerical simulations and experimental studies of X-ray source images and flash radiographic images. The results indicate that the proposed method is effective in restoring pulsed radiation images, removing noise, and preserving boundary region information. Additionally, this method produces satisfactory results for the restoration of real neutron images, demonstrating its applicability in the field of radiation imaging.

In the field of low intensity radiation image diagnosis such as neutron radiographic non-destructive testing and low dose medical diagnosis, image quality is severely affected by blurring artifacts and Poisson noise under low-count conditions due to hardware limitations and imaging conditions. To solve these problems, within the Bayesian-MAP framework, the advantages of fractional order total variation and the overlapping group sparsity measure are combined as regularization term, and the overlapping group sparse fractal-order total variational Poisson image restoration (P-OGSFOTV) model is proposed. The model is optimized and solved using the alternating direction method of multiplier (ADMM) combined with majorize-minimize (MM) algorithm. The P-OGSFOTV model was compared with other algorithms (P-NLM, NLSPCA, TV, FOTV, and P-HONOGSTV) by simulating images and real low intensity radiation experiment images. The results show that the P-OGSFOTV model performs well in restoring low intensity radiation images destroyed by Poisson noise and blur.

The uncertainty of nuclide libraries in the analysis of the gamma spectra of low- and intermediate-level radioactive waste (LILW) using existing methods produces unstable results. To address this problem, a novel spectral analysis method is proposed in this study. In this method, overlapping peaks are located using a continuous wavelet transform. An improved quadratic convolution method is proposed to calculate the widths of the peaks and establish a fourth-order filter model to estimate the Compton edge baseline with the overlapping peaks. Combined with the adaptive sensitive nonlinear iterative peak, this method can effectively subtracts the background. Finally, a function describing the peak shape as a filter is used to deconvolve the energy spectrum to achieve accurate qualitative and quantitative analyses of the nuclide without the aid of a nuclide library. Gamma spectrum acquisition experiments for standard point sources of Cs-137 and Eu-152, a segmented gamma scanning experiment for a 200 L standard drum, and a Monte Carlo simulation experiment for triple overlapping peaks using the closest energy of three typical LILW nuclides (Sb-125, Sb-124, and Cs-134) are conducted. The results of the experiments indicate that (1) the novel method and gamma vision (GV) with an accurate nuclide library have the same spectral analysis capability, and the peak area calculation error is less than 4%; (2) compared with the GV, the analysis results of the novel method are more stable; (3) the novel method can be applied to the activity measurement of LILW, and the error of the activity reconstruction at the equivalent radius is 2.4%; and (4) The proposed novel method can quantitatively analyze all nuclides in LILW without a nuclide library. This novel method can improve the accuracy and precision of LILW measurements, provide key technical support for the reasonable disposal of LILW, and ensure the safety of humans and the environment.

[Background]During the operation of nuclear power plants,a large amount of low and intermediate level waste(LILW)is generated,which is usually prepared into 200-L and 400-L waste drums.To ensure the safe disposal of these waste drums,they must be analyzed to determine the type and activity of the nuclides contained within them.Non-destructive assay(NDA)has been widely used in the detection of waste drums in nuclear power plants,along with segmented gamma scanning(SGS)and tomographic gamma scanning(TGS).However,the low measurement accuracy of SGS and the long measurement time of TGS limit the practical application of these methods.[Purpose]This sudy aims to shorten the measurement time while maintaining high measurement accuracy by proposing a new neural network-based method for measuring the activity of waste drum.[Methods]When the waste drum was filled with a uniform distribution of medium and rotated at a constant speed during measurement,the point source was equivalent to a ring source.The equivalent ring source in the waste drum possessed an activity equal to the total activity of all sources.The neural network model is established,the count rate of the detector at different positions is used as input,and the radius of the equivalent ring source is used as output.Finally,the total activity of the waste drum is calculated.The simulated measurement is carried out in a 400-L waste drum,the medium is concrete,the radioactive source is Co-60,and 50 groups of single-source and 10 groups of multi-source are generated randomly.Different methods are used to reconstruct the activity of the waste drum.[Results]When there is only one radioactive source in the waste drum,the mean relative error(MRE)of activity reconstruction by the new method is 4.26%,which is much lower than that of SGS(68.15%)and close to that of TGS with 60 grids(3.97%).When there are multiple radioactive sources in the waste drum,the MRE of activity reconstruction by the new method is 24.27%,which is lower than that of SGS(48.02%)and close to that of TGS with 60 grids(28.61%).This new method achieves the equal measurement accuracy of TGS but reduce the measurement time to 1/20 of TGS.[Conclusion]Compared to traditional measurement methods,the new method greatly shortens the measurement time while maintaining high precision,thereby providing technical support for the measurement of LILW.

BackgroundLow-level radioactive wastewater (LLW) is generated during the operation of nuclear facilities. Usually, LLW is discharged directly into the ocean in the form of liquid effluent after purification under the discharge management limits. However, discharging LLW into inland water bodies is difficult for inland nuclear facilities because of the poor dispersion and the lack of public acceptance. Thus, LLW disposal has become one of the challenges limiting the development of inland nuclear facilities. Liquid-to-gas discharge, which is based on high-pressure spray evaporation technology, is an alternative solution for LLW disposal for inland nuclear facilities.PurposeThis study aims to develop and validate a model for simulating spray flow and evaporation to assess the design feasibility.MethodsA numerical method coupling a two-phase flow model, mass transfer model, and heat transfer model were established to describe droplet evaporation during the flow process. To validate this numerical method, a sample high-pressure spray evaporation system was developed which included three key subsystems: carrier gas generation, source term generation, and measurement systems. Finally, considering evaporation and deposition factors, three experimental cases were designed for experimental comparison of the droplet diameter, number, and deposition rate among these cases.ResultsThe comparison results show that the numerical method is highly consistent with the experimental results, with a maximum uncertainty of 15%.ConclusionsThe numerical model developed in this study can be used for the technological design of liquid-to-gas LLW discharge based on high-pressure spray evaporation technology.

To achieve more efficient and accurate measurement of low- and intermediate-level radioactive waste (LILW), a room-temperature semiconductor detector CdZnTe (CZT) can be used to replace the high-purity germanium detector. The traditional method cannot identify nuclides since the energy resolution of CZT detectors is poor, and the spectrum have more overlapping peaks, compared with HPGe detectors. Therefore, in this study, we proposed a gamma spectrum analysis method based on an intelligent dynamic library. Simulation spectrum experiment and standard-source spectrum experiment achieved LILW all-nuclide quantitative analysis based on a CZT detector for the first time globally.