• Nuclear Engineering and Technology
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• v.56 no.7
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• pp.2835-2841
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• 2024

Real-time analysis of metallic mineral grade and slurry concentration is significant for improving flotation efficiency and product quality. This study proposes an online detection method of ore slurry combining the Prompt Gamma Neutron Activation Analysis (PGNAA) technology and artificial neural network (ANN), which can provide mineral information rapidly and accurately. Firstly, a PGNAA analyzer based on a D-T neutron generator and a BGO detector was used to obtain a gamma-ray spectrum dataset of ore slurry samples, which was used to construct and optimize the ANN model for adaptive analysis. The evaluation metrics calculated by leave-one-out cross-validation indicated that, compared with the weighted library least squares (WLLS) approach, ANN obtained more precise and stable results, with mean absolute percentage errors of 4.66% and 2.80% for Fe grade and slurry concentration, respectively, and the highest average standard deviation of only 0.0119. Meanwhile, the analytical errors of the samples most affected by matrix effects was reduced to 0.61 times and 0.56 times of the WLLS method, respectively.

• Nuclear Engineering and Technology
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• v.55 no.5
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• pp.1708-1717
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• 2023

The grade analysis of lead-zinc ore is the basis for the optimal development and utilization of deposits. In this study, a method combining Prompt Gamma Neutron Activation Analysis (PGNAA) technology and machine learning is proposed for lead-zinc mine borehole logging, which can identify lead-zinc ores of different grades and gangue in the formation, providing real-time grade information qualitatively and semi-quantitatively. Firstly, Monte Carlo simulation is used to obtain a gamma-ray spectrum data set for training and testing machine learning classification algorithms. These spectra are broadened, normalized and separated into inelastic scattering and capture spectra, and then used to fit different classifier models. When the comprehensive grade boundary of high- and low-grade ores is set to 5%, the evaluation metrics calculated by the 5-fold cross-validation show that the SVM (Support Vector Machine), KNN (K-Nearest Neighbor), GNB (Gaussian Naive Bayes) and RF (Random Forest) models can effectively distinguish lead-zinc ore from gangue. At the same time, the GNB model has achieved the optimal accuracy of 91.45% when identifying high- and low-grade ores, and the F₁ score for both types of ores is greater than 0.9.

• Nuclear Engineering and Technology
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• v.54 no.11
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• pp.4231-4235
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• 2022

Considering the importance of deuterium in nuclear science including medical and industrial researches such as (BNCT) and nuclear reactors respectively, it is important to study various possible ways in addition to common methods for measuring its concentration. This study is an effort to measure deuterium concentration using PGNAA. The main idea is to calculate the area under 2.23 MeV gamma-rays photo peak resulting from neutron collision with Hydrogen atoms which are in mix with deuterium in samples. The study carried out by both simulation and experiment. Monte Carlo MCNPX2.6 code has been used for simulation and based on its acceptable results an experimental setup has been arranged. The coordination of results was in the range of R = 0.99 and R = 0.98 in simulation and experiment respectively. The accuracy of the study has been investigated by measuring the concentration of an unknown sample by both PGNAA and Fourier transform infrared spectroscopy (FT-IR) methods in which there were acceptable correlation between these two methods.

• Nuclear Engineering and Technology
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• v.54 no.6
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• pp.2221-2229
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• 2022

In this research, for improving the measurement performance of Prompt Gamma-ray Neutron Activation Analysis (PGNAA) set-up, a new optimization method for set-up design was proposed and investigated. At first, the calculation method for Signal-to-Noise Ratio (SNR) was proposed. Since the SNR could be calculated and quantified accurately, the SNR was chosen as the evaluation parameter in the new optimization method. For discussing the feasibility of the SNR optimization method, two kinds of PGNAA set-ups were designed in the MCNP code, based on the SNR optimization method and the previous signal optimization method, respectively. Meanwhile, the single element spectra analysis method was proposed, and the analysis effect of single element spectra as well as element sensitivity were used for comparing the measurement performance. Since the simulation results showed the better measurement performance of set-up designed by SNR optimization method, the experimental set-ups were built for the further testing, finally demonstrating the feasibility of the SNR optimization method for PGNAA setup design.

• Analytical Science and Technology
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• v.16 no.5
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• pp.391-398
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• 2003

Basic research for the determination of boron content in biological sample has been carried out using the PGAA facility of the 24MW research reactor(HANARO). For investigation of characteristics for the measurement condition, neutron flux and its homogeneity were measured at irradiating geometry. The size of thermal neutron beam collimated from beam guide is $2{\times}2cm^2$ at the sample position. The neutron flux measured was the range of $1.0{\sim}6.5{\times}10^7n{\cdot}cm^{-2}{\cdot}s^{-1}$, and flux distribution from center within the radius of 4.5 mm and 9.0 mm was $5.77{\pm}0.71{\times}10^7n{\cdot}cm^{-2}{\cdot}s^{-1}$ and $4.68{\pm}1.64{\times}10^7n{\cdot}cm^{-2}{\cdot}s^{-1}$, respectively. Accordingly, sample size is adjusted within 10 mm for a homogeneous irradiation of high quality. Measurement system is designed to reduce the background source by Compton scattering and to improve the analytical sensitivity. To investigate the energy calibration and Compton suppression effect of gamma-ray counting system, the background conditions on both of Compton and single-mode were measured using NaCl standard. On the other hand, degree of spectral interference for sodium 472 keV peak as a matrix effect in the sample is established for an accurate boron analysis, and then boron content in three certified reference materials (NIST SRM 1570a, 1547, 1573a) was measured by using two modes and the results were compared with each other.