• Nuclear Engineering and Technology
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• v.54 no.12
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• pp.4671-4678
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• 2022

The purpose of this comprehensive research is to observe the impact of scintillator crystal type on entire detection process. For this aim, MCNPX (version 2.6.0) is used for designing of a physical plastic scintillation detector available in our laboratory. The modelled detector structure is validated using previous studies in the literature. Next, different types of plastic scintillation crystals were assessed in the same geometry. Several fundamental detector properties are determined for six different plastic scintillation crystals. Additionally, the deposited energy quantities were computed using the MCNPX code. Although six scintillation crystals have comparable compositions, the findings clearly indicate that the crystal composed of PVT 80% + PPO 20% has superior counting and detecting characteristics when compared to the other crystals investigated. Moreover, it is observed that the highest deposited energy amount, which is a result of the highest collision number in the crystal volume, corresponds to a PVT 80% + PPO 20% crystal. Despite the fact that plastic detector crystals have similar chemical structures, this study found that performing advanced Monte Carlo simulations on the detection discrepancies within the structures can aid in the development of the most effective spectroscopy procedures by ensuring maximum efficiency prior to and during use.

• Nuclear Engineering and Technology
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• v.54 no.9
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• pp.3398-3402
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• 2022

We fabricated a 15 m long position-sensitive plastic scintillation optical fiber (PSOF) detector consisting of a PSOF, two photomultiplier tubes, four fast amplifiers, and a digitizer. A single PSOF was used as a sensing part to estimate the gamma-ray source position, and ¹³⁷Cs, an uncollimated solid-disk-type radioactive isotope, was used as a gamma-ray emitter. To improve the sensitivity, accuracy, and measurement time of a PSOF detector compared to those of previous studies, the performance of the amplifier was optimized, and the digital signal processing (DSP) was newly designed in this study. Moreover, we could measure very low dose rates of gamma-rays with high sensitivity and accuracy in a very short time using our proposed PSOF detector. The results of this study indicate that it is possible to accurately and quickly locate the position of a very low dose rate gamma-ray source in a wide range of contaminated areas using the proposed position-sensitive PSOF detector.

• Journal of Radiation Protection and Research
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• v.46 no.4
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• pp.204-212
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• 2021

Background: Identification of radioisotopes for plastic scintillation detectors is challenging because their spectra have poor energy resolutions and lack photo peaks. To overcome this weakness, many researchers have conducted radioisotope identification studies using machine learning algorithms; however, the effect of data normalization on radioisotope identification has not been addressed yet. Furthermore, studies on machine learning-based radioisotope identifiers for plastic scintillation detectors are limited. Materials and Methods: In this study, machine learning-based radioisotope identifiers were implemented, and their performances according to data normalization methods were compared. Eight classes of radioisotopes consisting of combinations of ²²Na, ⁶⁰Co, and ¹³⁷Cs, and the background, were defined. The training set was generated by the random sampling technique based on probabilistic density functions acquired by experiments and simulations, and test set was acquired by experiments. Support vector machine (SVM), artificial neural network (ANN), and convolutional neural network (CNN) were implemented as radioisotope identifiers with six data normalization methods, and trained using the generated training set. Results and Discussion: The implemented identifiers were evaluated by test sets acquired by experiments with and without gain shifts to confirm the robustness of the identifiers against the gain shift effect. Among the three machine learning-based radioisotope identifiers, prediction accuracy followed the order SVM > ANN > CNN, while the training time followed the order SVM > ANN > CNN. Conclusion: The prediction accuracy for the combined test sets was highest with the SVM. The CNN exhibited a minimum variation in prediction accuracy for each class, even though it had the lowest prediction accuracy for the combined test sets among three identifiers. The SVM exhibited the highest prediction accuracy for the combined test sets, and its training time was the shortest among three identifiers.

• Nuclear Engineering and Technology
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• v.56 no.5
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• pp.1667-1671
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• 2024

This paper presents a neutron/gamma detector based on a micropixel avalanche photodiode and a plastic scintillator that monitors the status of the accelerator-driven intense resonance neutron source (IREN) facility by measuring the neutron/gamma intensity in the target hall. The electronics of the neutron/gamma detector has been designed and developed. The size of the plastic scintillator was selected to be 3.7 × 3.7 × 30 mm³ due to the sensitive area of the MAPD. The experimental results demonstrated a dependence between the count rate of the detector and the frequency of the accelerator. The detector is sensitive to intermediate and fast neutrons. The minimum detectable energy was determined to be 200 keV using Cs-137 point gamma source. The maximum counting rate of the detector from TTL out is about 2.2⋅10⁶ counts/sec, but for analogue output it is about 2⋅10⁷ counts/sec. The detector can not allow discriminating neutrons and gamma rays by charge integration method.

• Journal of Radiation Industry
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• v.11 no.3
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• pp.157-165
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• 2017

In this paper, we calculate the light photons collection efficiency of large-volume plastic scintillation detector mainly used for radiation portal monitor (RPM). A Monte Carlo light photon transport code, DETECT2000, were used to quantitatively evaluate light collection efficiency of plastic scintillation detector. DETECT2000 calculated the placement of light collection efficiency based on the energy spectrum. We calculated the light collection efficiency relative to the position of the energy spectrum that proportional to the placement of the source. The $850{\times}285{\times}65mm^3$ size of polyvinyl toluene (PVT) scintillator was used for measurements. Through DETECT2000 simulation, the light collection efficiency of $5{\times}5$ arrays were calculated and verification was performed by comparing with experimentally measured. And then, the corrected MCNP simulation by applying the light collection efficiency in $21{\times}13$ arrays was compared and analyzed. Comparing the Monte Carlo simulation with measured results, it shows an average difference of 10.1% in $5{\times}5$ arrays. Particularly, about twice of the difference was found in the edge of first column, which coupled with PMT. In whole $5{\times}5$ array, the overall ratio was the same except for the first column. And then comparing the energy spectra of the $21{\times}13$ array with and without the light collection efficiency, it shows a difference of 6.69% in Compton edge area. The DETECT2000 based light collection efficiency simulation showed well agreement with the point source experiment. And comparing with measured energy spectra, we could compare the differences according to whether or not the light collection efficiency was applied. As a results, it is possible to increase the accuracy and reliability of Monte Carlo simulation results by pre-calculating the light collection efficiency according to the PVT geometry by using the DETECT2000.

• Nuclear Engineering and Technology
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• v.54 no.3
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• pp.1037-1048
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• 2022

A radioactive isotope identification algorithm is a prerequisite for a low-resolution scintillation detector applied to an unmanned radiation monitoring system. In this paper, a sparse representation with dictionary learning approach is proposed and applied to plastic gamma-ray spectra. Label-consistent K-SVD was used to learn a discriminative dictionary for the spectra corresponding to a mixture of four isotopes (¹³³Ba, ²²Na, ¹³⁷Cs, and ⁶⁰Co). A Monte Carlo simulation was employed to produce the simulated data as learning samples. Experimental measurement was conducted to obtain practical spectra. After determining the hyper parameters, two dictionaries tailored to the learning samples were tested by varying with the source position and the measurement time. They achieved average accuracies of 97.6% and 98.0% for all testing spectra. The average accuracy of each dictionary was above 96% for spectra measured over 2 s. They also showed acceptable performance when the spectra were artificially shifted. Thus, the proposed method could be useful for identifying radioisotopes in gamma-ray spectra from a plastic scintillation detector even when a dictionary is adapted to only simulated data. Furthermore, owing to the outstanding properties of sparse representation, the proposed approach can easily be built into an insitu monitoring system.

• Journal of Radiation Industry
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• v.17 no.1
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• pp.69-73
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• 2023

Commercially used organic scintillation materials (1,4 di[2-(5phenyloxazolyl)] benzene) have low solubility in solvents and a wide emission energy range, which causes a decrease in detection efficiency. In this study, an organic liquid scintillator with improved detection efficiency was developed using 7-Diethylamino-4-methylcoumarin material to compensate for the disadvantages of existing organic scintillation detectors. And to evaluate the applicability of radiation measurement, the performance of a commercial plastic detector was compared. As a result of analyzing the ⁶⁰Co detection characteristics by applying 7-Diethylamino-4-methylcoumarin as an alternative to 1,4 di[2-(5phenyloxazolyl)] benzene, the detection efficiency was improved around 2% compared with commercial scintillator when the 7-Diethylamino-4-methylcoumarin content was 0.04 wt%. Based on the results of this study, the possibility of improving detection efficiency through scintillator material modification was confirmed. In addition, since it is possible to discriminate nuclide through the spectrum correction algorithm, it will be possible to inspect and classify various decommissioning wastes generated during the decommissioning process.

• The Bulletin of The Korean Astronomical Society
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• v.34 no.1
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• pp.188.2-188.2
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• 2009

• Journal of Nuclear Fuel Cycle and Waste Technology(JNFCWT)
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• v.7 no.2
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• pp.87-92
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• 2009

Remote detecting system for a radiation contamination using a plastic scintillator and an optical fiber was developed. Using a commercially available silica optical fiber and a plastic scintillator, we tested then for a real possibility as a remote monitoring detector. Also, a plastic scintillator was developed by itself, and evaluated as a radiation sensor. The plastic scintillator was made of epoxy resin, a hardener and an organic scintillation material. The mixture rate of the epoxy resin, hardener and organic scintillator was fixed by using their emission spectrum, transmittance, intensity etc. In this study, in order to decrease the light loss of an incomplete connection between an optical fiber and a scintillator, the optical fiber was inserted into the scintillator during the fabrication process. The senor used a plastic optical fiber and was estimated for its detection efficiency by an optic fiber's geometric factor.

• Analytical Science and Technology
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• v.18 no.6
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• pp.495-499
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• 2005

Notwithstanding antipathies against radiation, radiations are extensively used in various fields with development of the radiation technology. In order to safely manage such radiation it is necessary for development of the radiation measurement materials. In this paper a thin film type of plastic scintillator using in the contamination measurement devices was prepared. The plastic organic scintillator was prepared by simple solvent methods. It was possible to prepare in easy way and in various forms. The polysulfone which has high transparency and solubility was chosen. As the radiation measurement scintillator, the optical properties and radiation detection abilities were estimated.