• Nuclear Engineering and Technology
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• 제54권12호
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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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• 제54권1호
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• pp.269-274
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• 2022

An artificial neural network (ANN) that identifies radionuclides from low-count gamma spectra of a NaI scintillator is proposed. The ANN was trained and tested using simulated spectra. 14 target nuclides were considered corresponding to the requisite radionuclide library of a radionuclide identification device mentioned in IEC 62327-2017. The network shows an average identification accuracy of 98.63% on the validation dataset, with the gross counts in each spectrum N_c = 100~10000 and the signal to noise ratio SNR = 0.05-1. Most of the false predictions come from nuclides with low branching ratio and/or similar decay energies. If the N_c>1000 and SNR>0.3, which is defined as the minimum identifiable condition, the averaged identification accuracy is 99.87%. Even when the source and the detector are covered with lead bricks and the response function of the detector thus varies, the ANN which was trained using non-shielding spectra still shows high accuracy as long as the minimum identifiable condition is satisfied. Among all the considered nuclides, only the identification accuracy of ²³⁵U is seriously affected by the shielding. Identification of other nuclides shows high accuracy even the shielding condition is changed, which indicates that the ANN has good generalization performance.

• Nuclear Engineering and Technology
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• 제53권1호
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• pp.253-257
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• 2021

This work demonstrates the use of baromembrane method based on reverse osmosis (RO) process. The method is realized on mobile complex, which allows to concentrate and determine ultra-low activity of radionuclides in water cooling ponds of Russian nuclear fuel cycle enterprises. The existence level of radionuclide background creates difficult conditions for identification the contribution of liquid discharges enterprise, as standard monitoring methods have a very high detection level for radionuclides. Traditional methods for determining the background radionuclides concentrations require the selection of at least 500 liters (l) of water, followed by their evaporation to form a dry residue. This procedure with RO membranes requires at least 5 days. It is possible to reduce the time and energy spent on evaporation of hundreds of water liters by pre-concentrating radionuclides in a smaller sample volume with baromembrane method. This approach allows preliminary concentration of water samples from 500 l volume till 20 l volume during several hours. This approach is universal for the concentration of dissolved salts of any heavy metals, other organic compounds and allows the preparation of water countable samples in much shorter time compared to the traditional evaporation method.

• Nuclear Engineering and Technology
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• 제55권10호
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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.

• Nuclear Engineering and Technology
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• 제44권7호
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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.

• Nuclear Engineering and Technology
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• 제53권4호
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• pp.1311-1317
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• 2021

In this study, an airborne alpha detection system, which consists of a passivated implanted planar silicon (PIPS) detector and an air filter, was developed. A collimator applied to the alpha detection system showed an enhancement in resolution and a degradation in detection efficiency. The resolution and detection efficiency were compared and analyzed to evaluate the performance of the collimator. Thus, the resolution was found to be more important than the efficiency as a determining factor of the detection system performance, from the viewpoint of radionuclide identification. The performance was evaluated on three properties of the collimator: hole shape, hole length, and the ratio between the hole and frame pitches. From the hole shape performance evaluation, a hexagonal collimator showed the highest resolution. Further, the collimator with a hole pitch of 14 mm was found to have the highest resolution while that with a frame pitch of 4-6 mm (i.e., 1.2-1.4 times longer than the hole pitch) showed the highest resolution.

• Nuclear Engineering and Technology
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• 제54권11호
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• pp.4220-4225
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• 2022

Monte Carlo (MC) simulations are increasingly being used as an alternative or supplement to the gamma spectrometric method in determining the full energy peak efficiency (FEPE) necessary for radionuclide identification and quantification. The MC method is more advantageous than the experimental method in terms of both cost and time. Experimental calibration with standard sources is difficult, especially for specimens with unusually shaped geometries. However, with MC, efficiency values can be obtained by modeling the geometry as desired without using any calibration source. Modeling the detector with the correct parameters is critical in the MC method. These parameters given to the user by the manufacturer are especially the dimensions of the crystal and its front edge, the thickness of the dead layer, dimensions, and materials of the detector components. This study aimed to investigate the effect of the front edge geometry of the detector crystal on efficiency, so the effect of rounded and sharp modeled front edges on the FEPE was investigated for <300 keV with three different HPGe detectors in point and volume source geometries using PHITS MC code. All results showed that the crystal should be modeled as a rounded edge, especially for gamma-ray energies below 100 keV.

• Nuclear Medicine and Molecular Imaging
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• 제40권3호
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• pp.148-154
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• 2006

목적 : 방사성동위원소 뇌조조영술은 자발성 두개강내 저뇌압증이 의심되는 환자에서 뇌척수액의 누출을 진단하는데 유용한 검사이지만, 뇌척수액의 누출 부위를 증명하지 못하는 경우가 있다. 본 연구의 목적은 방사성동위원소 뇌조조영술의 검사 방법을 변화함으로써 뇌척수액 누출 부위의 진단율을 향상시키고, 검사 소요시간을 단축할 수 있는지 알아 보고자 한다. 대상 및 방법 : 자발성 두개강내 저뇌압증으로 진단되어 방사성동위원소 뇌조조영술을 시행한 7명의 환자(평균 나이=$38{\pm}8$세, 남자 2명, 여자 5명), 8회 검사를 대상으로 하였다. 모든 환자들은 자주막하강에 $^{99m}Tc$-DTPA 185-222 MBq을 투여한 후 10분, 30분, 1시간, 2시간, 4시간 그리고 6시간에 방광을 포함하는 요추부부터 두부까지의 영상을 얻었다. 그리고 영상시간에 따라 뇌척수액의 누출과 방광의 방사능 조기 출현을 평가하였다. 결과: 방사성동위원소 뇌조조영술을 통해 8예 모두에서 뇌척수액의 누출 부위를 확인할 수 있었다. 뇌척수액의 누출 부위는 경흉추 경계부(cervico-thoracic junction)에서 3예, 경흉추 경계부와 C1-2에서 2예, 경흉추 경계부와 흉추부, 흉요추부 여러 곳 그리고 요추부가 각각 1예씩 이었다. 모든 예에서 1시간까지의 영상을 통해 모든 예에서 뇌척수액의 누출 부위를 발견할 수 있었으며, 모두 두 곳 이상에서 누출이 있었다. 이 중 경흉추 경계부를 포함하는 경우가 5예였다. 지연 영상에서 뇌척수액의 누출 부위가 추가로 발견된 경우는 단 1예 뿐 이었다. 조기 방광방사능 출현은 6예에서 관찰되었으며, 모두 뇌척수액 유출부위가 더 먼저 관찰되었다. 결론: 방사성동위원소 뇌조조영술은 자발성 두개강내 저뇌압증 환자에서 뇌척수액의 누출 부위를 확인하는데 매우 예민한 검사이며, 검사법을 변형함으로써 뇌척수액의 누출 부위를 발견하는 빈도를 향상시키고, 검사시간을 단축할 수 있을 것으로 기대된다.

• Journal of Radiation Protection and Research
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• 제34권1호
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• pp.37-42
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• 2009

국내 원전에서는 원전종사자의 내부피폭 방사능을 측정하기위해 전신계측기를 이용하고 있다. 이 전신계측기는 Sodium Iodide를 이용한 섬광검출기로서 짧은 시간에 종사자가 보유한 방사성핵종과 방사능을 측정하는 기능을 가지고 있다. 그런데 종사자의 신체표면에 부착된 오염과 내부에 침적된 오염을 구분하지 못하기 때문에 방사선계측 과정에서 종종 오류를 범할 가능성이 있으며, 이 경우 내부피폭선량은 매우 보수적으로 과대평가된다. 이러한 문제점을 개선하고자 종사자의 인체 내부와 외부 표면오염을 구분하고, 보다 체계적으로 오염부위를 확인할 수 있도록 전신계측기와 인체모형 팬텀을 이용한 방사능 계측실험을 수행하였다. 또한 원전에서 발생하는 주요 핵종의 신체내 침적위치를 고려하여 전신계측기의 최적 방사능 측정모드를 결정하는 실험을 수행하였다. 이러한 방사능 측정 실험결과를 근거로 원전종사자의 내부방사능 측정과 선량평가 절차를 개선하였다. 이에따라 보다 정확한 전신계측프로그램의 적용으로 내부피폭선량의 보수적 평가를 방지할 수 있을 것으로 기대된다.

• 핵의학기술
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• 제25권2호
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• pp.41-47
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• 2021

최근 사이클로트론 시설의 GMP 인증 및 핵의학과 검사 보험 미적용 등으로 인해 핵의학 검사 수가 감소함에 따라 사이클로트론도 조기에 해체될 가능성이 높다. 이에 본 연구에서는 사이클로트론 해체 시 방사성폐기물 발생량과 관련성이 높은 사이클로트론 차폐벽 내 방사성핵종을 확인하였다. 국내에는 해체가 진행중인 사이클로트론이 없으므로 사이클로트론 차폐벽 Coring이 불가능하고, 국내 모든 사이클로트론에 대한 실험을 수행하는 것은 현실적으로 불가능하다. 따라서, 대구 K대학교 병원 내 KIRAMS-13이 설치된 사이클로트론실에서 Target 진행 방향을 중심으로 총 30 곳에서 방사성핵종을 분석하였다. 본 연구에서 활용한 장비는 Thermo사의 RIIDEye이며, 측정 지점별 측정시간은 24시간으로 설정하였다. 측정 결과 일부 측정 지점에서 장반감기 방사성핵종인 Co-60과 Cs-137이 검출되었다. 또한, 가장 많은 측정 지점에서 검출된 Co-60의 방출에너지별 방사능을 확인한 결과, target 방향을 중심으로 우측 상부에서 좌측 하부로 이어지는 대각선 방향으로 방사능이 높은 것을 확인하였다. 따라서, 향후 사이클로트론 해체 전 차폐벽 coring 위치 선정 시 휴대용핵종분석기를 활용할 수 있을 것으로 예상된다. 하지만, 본 연구는 하나의 사이클로트론에 대한 실험 결과이므로 다수의 사이클로트론에 대한 추가 연구가 필요할 것으로 예상된다. 또한, 본 연구 결과는 휴대용핵종분석기를 사용한 연구결과로서 HPGe를 활용한 추가 연구를 수행하여 일치성을 확인하는 추가 연구가 필요할 것으로 판단된다. 최종적으로 다년간의 각 기관별 콘크리트 표면에서의 방사화 자료가 구축된다면, 사이클로트론 해체 준비 시 보다 정확한 방사성폐기물량을 예측할 수 있을 것으로 판단된다.