• Nuclear Engineering and Technology
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• v.54 no.12
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• pp.4684-4692
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• 2022

Radionuclide identification is an important part of the nuclear material identification system. The development of artificial intelligence and machine learning has made nuclide identification rapid and automatic. However, many methods directly use existing deep learning models to analyze the gamma-ray spectrum, which lacks interpretability for researchers. This study proposes an explainable radionuclide identification algorithm based on the convolutional neural network and class activation mapping. This method shows the area of interest of the neural network on the gamma-ray spectrum by generating a class activation map. We analyzed the class activation map of the gamma-ray spectrum of different types, different gross counts, and different signal-to-noise ratios. The results show that the convolutional neural network attempted to learn the relationship between the input gamma-ray spectrum and the nuclide type, and could identify the nuclide based on the photoelectric peak and Compton edge. Furthermore, the results explain why the neural network could identify gamma-ray spectra with low counts and low signal-to-noise ratios. Thus, the findings improve researchers' confidence in the ability of neural networks to identify nuclides and promote the application of artificial intelligence methods in the field of nuclide identification.

• Nuclear Engineering and Technology
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• v.44 no.7
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• pp.781-790
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• 2012

The HyperGam program was developed for the analysis of complex HPGe ${\gamma}$-ray spectra. The previous version of HyperGam was mainly limited to the analysis of ${\gamma}$-ray peaks and the manual logging of the result. In this study, it is specifically developed into a tool for the isotopic analysis of spectra. The newly developed features include nuclide identification and activity determination. An algorithm for nuclide identification was developed to identify the peaks in the spectrum by considering the yield, efficiency, energy and peak area for the ${\gamma}$-ray lines emitted from the radionuclide. The detailed performance of nuclide identification and activity determination was accessed using the IAEA 2002 set of test spectra. By analyzing the test spectra, the numbers of radionuclides identified truly (true hit), falsely (false hit) or missed (misses) were counted and compared with the results from the IAEA 2002 tests. The determined activities of the radionuclides were also compared for four test spectra of several samples. The result of the performance test is promising in comparison with those of the well-known software packages for ${\gamma}$-ray spectrum analysis.

• Journal of Radiation Protection and Research
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• v.34 no.4
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• pp.170-175
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• 2009

For the emergency radiation monitoring using gamma spectrometry, we should sufficiently survey the background spectra as environmental samples with systematic nuclide identification method. In this study, we obtained the gamma ray energy spectrum using a HPGe gamma spectrometry system from an air sample. And we identified nuclide of the gamma ray energy peaks in the spectrum using two methods -1) Half life calculation and 2) survey for cascade coincidence summing peaks using nuclear data. As the results, we produced the nuclide identification results for the air sample.

• Journal of the Korean Chemical Society
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• v.6 no.2
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• pp.155-157
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• 1962

A tiny dust found at the balcony of the Institute indicated about 8,0000 counts per minute by T.G.C.-2 Geiger-Muller tube (1.8mg/$cm^2$ window-thickness) at the distance of 2cm from the window. The main fission fragments, as identified by the present analysis, are 12.5day Ba-140 and 33.1 day Ce-141. The gamma energies were determined using $2"{\times}2"$ NaI(Tl) scintillation detector connected to RCL-256 channel pulse heigt analyzer. The beta energies were evaluated by Feather plot.

• Journal of Nuclear Fuel Cycle and Waste Technology(JNFCWT)
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• v.6 no.2
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• pp.73-100
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• 2008

For the purpose of evaluating dose rate to individual due to long-term release of nuclides from the HLW repository, a biosphere assessment model and the implemented code, ACBIO, based on BIOMASS methodology have been developed by utilizing AMBER, a general compartment modeling tool. To show its practicability and usability as well as to see the sensitivity of compartment scheme or parametric variation to concentration and activity in compartments as well as annual flux between compartments at their peak values, some calculations are made and investigated: For each case when changing the structure of compartments and GBIs as well as varying selected input Kd values, all of which seem very important among others, dose rate per nuclide release rate is separately calculated and analyzed. From the maximum dose rates (Bq/y), flux-to-dose conversion factors (Sv/Bq) for each nuclide were derived, which are to be used for converting the nuclide release rate appearing from the geosphere through various GBIs to dose rate (Sv/y) for individual in critical group. It has been also observed that compartment scheme, identification of possible exposure group and GBIs could be all highly sensitive to the final consequences in biosphere modeling.

• Nuclear Engineering and Technology
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• v.55 no.10
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• pp.3907-3912
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• 2023

Radiation portal monitors (RPMs) installed at airports and harbors to prevent illicit trafficking of radioactive materials generally use large plastic scintillators. However, their energy resolution is poor and radionuclide identification is nearly unfeasible. In this study, to improve isotope identification, a RPM system based on a multi-array plastic scintillator and convolutional neural network (CNN) was evaluated by measuring the spectra of radioactive sources. A multi-array plastic scintillator comprising an assembly of 14 hexagonal scintillators was fabricated within an area of 50 × 100 cm². The energy spectra of ¹³⁷Cs, ⁶⁰Co, ²²⁶Ra, and ⁴K (KCl) were measured at speeds of 10-30 km/h, respectively, and an energy-weighted algorithm was applied. For the CNN, 700 and 300 spectral images were used as training and testing images, respectively. Compared to the conventional plastic scintillator, the multi-arrayed detector showed a high collection probability of the optical photons generated inside. A Compton maximum peak was observed for four moving radiation sources, and the CNN-based classification results showed that at least 70% was discriminated. Under the speed condition, the spectral fluctuations were higher than those under dwelling condition. However, the machine learning results demonstrated that a considerably high level of nuclide discrimination was possible under source movement conditions.

• Journal of IKEEE
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• v.22 no.3
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• pp.638-644
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• 2018

In this paper, we develop a measurement system that uses 3D Scintillator and NaI(TI) Detector to 3-dimensionally identify the location of multiple radiation sources in moving vehicle loads. The radiation measurement system consists of radiation measurement (plastic scintillator), 2-channel Pulse Counter Board, nuclide analysis (NaI(TI) detector) and 1 channel MCA Board. The source locator algorithm calculates the coordinate value of the ratio of the CPS value($1/r^2$) of the source according to the angle(${\theta}$) in inverse proportion to the square of the distance(X, Y) through the SVM classification. The coordinate values are input every predetermined period of the spectrum, and after analyzing the spectrum per unit cycle, the position of the nuclide at the time is calculated by determining whether or not the nuclide is present in the remaining part except for the background area. As a result of the position discrimination test, the error within the international standard of ${\pm}1m$ was shown. Thus, the utility of the proposed system has been demonstrated.

• Proceedings of the Korean Radioactive Waste Society Conference
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• 2003.11a
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• pp.544-548
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• 2003

The Irradiation test of bar code label tagged on radioactive waste container was done to determine the effect of radiation. Low and medium radioactive waste is that below total activity of 4,000 Bq/g according to the Korean nuclear law. The irradiation amount to radiate bar code label tagged on radioactive waste container was calculated by MCNP-4b computer code. The nuclide such as Co-60 and Cs-137 was assumed to contribute 50% of total activity. Real irradiation amount for bar code label was finally calculated by the dimensions of the container and the bar code label. The Identification of post and the physical deflection of irradiated bar code label was tested by the bar code reader. The coated bar code label was suitable to use on low and medium radioactive waste container.

• Journal of Nuclear Fuel Cycle and Waste Technology(JNFCWT)
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• v.20 no.1
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• pp.99-110
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• 2022

In decommissioning a nuclear power plant, numerous concrete structures need to be demolished and decontaminated. Although concrete decontamination technologies have been developed globally, concrete cutting remains problematic due to the secondary waste production and dispersion risk from concrete scabbling. To minimize workers' radiation exposure and secondary waste in dismantling and decontaminating concrete structures, the following conceptual designs were developed. A micro-blast type scabbling technology using explosive materials and a multi-dimensional contamination measurement and artificial intelligence (AI) mapping technology capable of identifying the contamination status of concrete surfaces. Trials revealed that this technology has several merits, including nuclide identification of more than 5 nuclides, radioactivity measurement capability of 0.1-10⁷ Bq·g^-1, 1.5 kg robot weight for easy handling, 10 cm robot self-running capability, 100% detonator performance, decontamination factor (DF) of 100 and 8,000 cm²·hr^-1 decontamination speed, better than that of TWI (7,500 cm²·hr^-1). Hence, the micro-blast type scabbling technology is a suitable method for concrete decontamination. As the Korean explosives industry is well developed and robot and mapping systems are supported by government research and development, this scabbling technology can efficiently aid the Korean decommissioning industry.

• Journal of Radiation Protection and Research
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• v.41 no.2
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• pp.87-91
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• 2016

Background: A hand-held detector for an emergency response was developed for nuclide identification and to estimate the information of the ambient dose rate in the scene of an accident as well as the radioactivity of the contaminants. Materials and Methods: To achieve this, the most suitable sensor was first selected as a cadmium zinc telluride (CZT) semiconductor and the signal processing unit from a sensor and the signal discrimination and storage unit were successfully manufactured on a printed circuit board. Results and Discussion: The performance of the developed signal processing unit was then evaluated to have an energy resolution of about 14 keV at 662 keV. The system control unit was also designed to operate the CZT detector, monitor the detector, battery, and interface status, and check and transmit the measured results of the ambient dose rate and radioactivity. In addition, a collimator, which can control the inner radius, and the airborne dust sampler, which consists of an air filter and charcoal filter, were developed and mounted to the developed CZT detector for the quick and efficient response of a nuclear accident. Conclusion: The hand-held CZT detector was developed to make the in-situ gamma-ray spectrometry and its performance was checked to have a good energy resolution. In addition, the collimator and the airborne dust sampler were developed and mounted to the developed CZT detector for a quick and efficient response to a nuclear accident.