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변요셉(Byun Yoseph),김현기(Kim Hyungi),이상수(Lee Sangsu),천병식(Chun Byungsik) 한국지반환경공학회 2010 한국지반환경공학회논문집 Vol.11 No.8
병렬터널의 이격거리가 근접할수록 응력집중으로 인하여 필라(pillar)의 파괴 위험이 큰 만큼 필라의 응력 검토 및 필라의 강도를 고려한 필라의 안정성 평가는 병렬터널의 이격거리 검토 시 매우 중요한 사항이다. 본 연구에서는 필라의 안정성을 구하는 방법 중 하나인 수치해석의 요소크기를 검토하여 필라부 안정성 검토에 대한 체계적인 분석을 제안하였다. 그 결과, 강도응력비는 요소크기에 따른 영향이 크게 없었고, 강도강소법에 의한 안전율은 요소가 작을수록 안전율이 작게 나왔다. 특히 지반이 풍화암인 경우 요소크기에 대한 안전율 값 차이가 크므로 지반이 불량한 경우 요소의 크기를 작게하는 것이 안정적인 결과를 나타냈다. Safety estimation of the pillar between parallel tunnels are very important considering stress concentration in case the piller width is not enough to secure the stability. Pillar width needs to be determined properly because of the progressive failure-risk of pillar due to stress-concentration. In this research, the effect of element size in numerical analysis was evaluated based on that yield pillar’s stability and proposed systematic analysis about pilar’s stability examination. In consequence of it, element size does not give any effect on intensity stress ratio. On the other hand, the analysis using the smaller element size results in lower safety factor in strength reduction technique. In case of the weathered re.k on the main ground layer, the analysis of result was not reliable. In conclusion, the smaller element size is, the more stable factor is.
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Jaewon Park,Juyub Kim,Hyungi Byun 한국방사성폐기물학회 2022 한국방사성폐기물학회 학술논문요약집 Vol.20 No.2
Decommissioning of a nuclear power plant (NPP) generate large amounts of various types of wastes. In accordance with the Nuclear Safety and Security Commission Notice of Korea (No. 2020- 6), they are classified as High Level Waste (HLW), Intermediate Level Waste (ILW), Low Level Waste (LLW), Very Low Level Waste (VLLW) and Exempt Waste (EW) according to specific activities. More than 90% of the wastes are at exempt level, mostly metal and concrete wastes with low radioactivity, of which the concentrations of nuclides is less than the allowable concentration of self-disposal. The self-disposal or recycling of these wastes is widely used worldwide. More than 10,000 drums, based on 200 L drum, are expected to be produced in the decommissioning process of a unit of nuclear power plant. Due to the limited storage capacity of the intermediate & low level waste disposal facility in Gyeongju, recycling and self-disposal of EW are actively recommended in Korea. A variety of scenarios were proposed for recycling and self-disposal of decommissioning metal/ concrete wastes, and a computational program called REDISA was developed to perform the dose evaluation for each recycling and self-disposal scenario. The REDISA computer program can calculate external and internal exposure doses by simulating the exposure pathways from waste generation, thru transport, processing, manufacture, to the final destination of recycling or self-disposal. In this study, the self-disposal scenario was only considered for the dose evaluation. Many studies have been conducted to evaluate the exposure doses of the radioactive waste disposal sites. However, there have been few researches on dose evaluation for self-disposal landfills. In particular, the dose evaluation is important not only during the operation period, but also for a long period after the facility is closed. To this end, we developed a conceptual model for dose evaluation for post-closure scenarios of the self-disposal landfill of decommissioning metal/concrete wastes with reference to the methodology of IAEA-TECDOC-1380. The model incorporates three exposure pathways, including external exposure from contaminated soil, internal exposure by inhalation, and internal exposure by ingestion of water and food grown in contaminated soil. The duration of the dose evaluation is set to 100,000 years after the closure of landfill facility. Co-60 was selected as dominant nuclide, and dose evaluation was performed based on unit specific activity of 1 Bq/g. Exposure doses shall be verified for their application in accordance with the annual dose limit of 10 ?Sv/yr for self-disposal. As a result, the post-closure scenario of selfdisposal landfills have shown negligible effects on public health, which means that the exposures doses from transportation and operational processes should be considered more carefully for selfdisposal of decommissioning metal/concrete wastes.
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Jinhong Kim,Siwon Song,Jae Hyung Park,Seunghyeon Kim,Taeseob Lim,Hyungi Byun,Sang-Hun Shin,Bongsoo Lee 한국방사성폐기물학회 2022 한국방사성폐기물학회 학술논문요약집 Vol.20 No.1
In this study, the positions of Cs-137 gamma ray source are estimated from the plastic scintillating fiber bundle sensor with length of 5 m, using machine learning data analysis. Seven strands of plastic scintillating fibers are bundled by black shrink tube and two photomultiplier tubes are used as a gamma ray sensing and light measuring devices, respectively. The dose rate of Cs-137 used in this study is 6 μSv·h?1. For the machine learning modeling, Keras framework in a Python environment is used. The algorithm chosen to construct machine learning model is regression with 15,000 number of nodes in each hidden layer. The pulse-shaped signals measured by photomultiplier tubes are saved as discrete digits and each pulse data consists of 1,024 number of them. Measurements are conducted separately to create machine learning data used in training and test processes. Measurement times were different for obtaining training and test data which were 1 minute and 5 seconds, respectively. It is because sufficient number of data are needed in case of training data, while the measurement time of test data implies the actual measuring time. The machine learning model is designated to estimate the source positions using the information about time difference of the pulses which are created simultaneously by the interaction of gamma ray and plastic scintillating fiber sensor. To evaluate whether the double-trained machine learning model shows enhancement in accuracy of source position estimation, the reference model is constructed using training data with one-time learning process. The double-trained machine learning model is designed to construct first model and create a second training data using the training error and predetermined coefficient. The second training data are used to construct a final model. Both reference model and double-trained models constructed with different coefficients are evaluated with test data. The evaluation result shows that the average values calculated for all measured position in each model are different from 7.21 to 1.44 cm. As a result, by constructing the double-trained machine learning model, the final accuracy shows 80% of improvement ratio. Further study will be conducted to evaluate whether the double-trained machine learning model is applicable to other data obtained from measurement of gamma ray sources with different energy and set a methodology to find optimal coefficient.
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Taeseob Lim,Siwon Song,Jae Hyung Park,Jinhong Kim,Seunghyeon Kim,Hyungi Byun,Seokhyeon Jegal,Bongsoo Lee 한국방사성폐기물학회 2022 한국방사성폐기물학회 학술논문요약집 Vol.20 No.2
Plastic scintillators can be used to find radioactive sources for portal monitoring due to their advantages such as faster decay time, non-hygroscopicity, relatively low manufacturing cost, robustness, and easy processing. However, plastic scintillators have too low density and effective atomic number, and they are not appropriate to be used to identify radionuclides directly. In this study, we devise the radiation sensor using a plastic scintillator with holes filled with bismuth nanoparticles to make up for the limitations of plastic materials. We use MCNP (Monte Carlo N-particle) simulating program to confirm the performance of bismuth nanoparticles in the plastic scintillators. The photoelectric peak is found in the bismuth-loaded plastic scintillator by subtracting the energy spectrum from that of the standard plastic scintillator. The height and diameter of the simulated plastic scintillator are 3 and 5 cm, respectively, and it has 19 holes whose depth and diameter are 2.5 and 0.2 cm, respectively. As a gamma-ray source, Cs-137 which emits 662 keV energy is used. The clear energy peak is observed in the subtracted spectrum, the full width at half maximum (FWHM) and the energy resolution are calculated to evaluate the performance of the proposed radiation sensor. The FWHM of the peak and the energy resolution are 61.18 keV and 9.242% at 662 keV, respectively.
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3축 가속도 센서와 족압 감지 시스템을 활용한 보행 모니터링 시스템 개발
유인환(In-Hwan Ryu),이선우(Sunwoo Lee),정현기(Hyungi Jeong),변기훈(Kihoon Byun),권장우(Jang-Woo Kwon) 한국재활복지공학회 2016 재활복지공학회논문지 Vol.10 No.3
대부분의 한국인은 오랜 좌식생활 때문에 팔자 걸음이나 안짱 걸음을 걷는 경우가 많고, 오늘날에는 보행 중 스마트폰 사용으로 인하여 올바른 자세의 보행이 더욱 어려워지고 있다. 본 연구는 현대 한국인의 걸음 실태를 쉽게 분석하고 사용자로 하여금 이를 알 수 있도록 하는 간편한 시스템을 구현하는 데 목적이 있다. 본 연구는 보행 유형을 분류하기 위하여 3축 가속도 센서와 족압 감지 시스템을 활용한 보행 모니터링 시스템을 개발하였다. 개발된 시스템은 걸을 때 발생하는 발의 압력(foot pressure)과, 상반신의 기울어진 정도를 각각 압력 센서(pressure sensor)와 3축 가속도계(3-axis accelerometer)를 통해 걷는 자세의 데이터를 취득할 수 있다. 이를 통해 몇 가지 보행 유형과 센서 데이터 간의 상관관계를 분석하였다. 그 결과 상체 자세 판별에는 통계적 모수인 제곱평균제곱근과 표준편차가, 보행 유행 판별에는 k-최근접 이웃 알고리즘이 적합하다는 사실을 확인하였다. 고안된 시스템은 저비용의 의학, 체육 분야에 응용될 수 있다. Most Koreans walk having their toes in or out, because of their sedentary lifestyles. In addition, using smartphone while walking makes having a desirable walking posture even more difficult. The goal of this study is to make a simple system which easily analyze and inform any person his or her personal walking habit. To discriminate gait patterns, we developed a gait monitoring system using a 3-axis accelerometer and a foot pressure monitoring system. The developed system, with an accelerometer and a few pressure sensors, can acquire subject’s foot pressure and how tilted his or her torso is. We analyzed the relationship between type of gate and sensor data using this information. As the result of analysis, we could find out that statistical parameters like standard deviation and root mean square are good for discriminating among torso postures, and k-nearest neighbor algorithm is good at clustering gait patterns. The developed system is expected to be applicable to medical or athletic fields at a low price.
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Seokhyeon Jegal,Siwon Song,Jae Hyung Park,Jinhong Kim,Seunghyeon Kim,Sangjun Lee,Hyungi Byun,Bongsoo Lee 한국방사성폐기물학회 2023 한국방사성폐기물학회 학술논문요약집 Vol.21 No.2
The inorganic scintillator used in gamma spectroscopy must have good efficiency in converting the kinetic energy of charged particles into light as well as high light output and high light detection efficiency. Accordingly, various studies have been conducted to enhance the net-efficiency. One way to improve the light yield has been studied by coating scintillators with various nanoparticles, so that the scintillation light can undergo resonance on surface between scintillators and nanoparticles resulting in higher light yield. In this study, an inorganic scintillator coated with CsPbBr3 perovskite nanocrystals using dip coating technique was proposed to improve scintillation light yield. The experiment was carried out by measuring scintillation light output, as the result of interaction between inorganic scintillator coated with CsPbBr3 perovskite nanocrystals and gamma-ray emitted from Cs-137 gamma source. The experimental results show that the channel corresponding to 662 keV full energy peak in the Cs-137 spectrum shifted to the right by 14.37%. Further study will be conducted to investigate the detailed relationships between the scintillation light yield and the characteristics of coated perovskite nanoparticles, such as diameter of nanoparticles, coated area ratio and width of coated region.
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