Although many attempts have been made to solve the atmospheric diffusion equation, there are many limits that prevent both solving it and its application. The causes of these impediments are primarily due to both the partial differentiation term and the turbulence diffusion coefficient. In consideration of this dilemma, this study aims to discuss the methodology and cases of utilizing a passive air sampler to increase the applicability of atmospheric dispersion modeling. Passive air samplers do not require pumps or electric power, allowing us to achieve a high resolution of spatial distribution data at a low cost and with minimal effort. They are also used to validate and calibrate the results of dispersion modeling. Currently, passive air samplers are able to measure air pollutants, including SO2, NO2, O3, dust, asbestos, heavy metals, indoor HCHO, and CO2. Additionally, they can measure odorous substances such as NH3, H2S, and VOCs. In this paper, many cases for application were introduced for several purposes, such as classifying the VOCs’ emission characteristics, surveying spatial distribution, identifying sources of airborne or odorous pollutants, and so on. In conclusion, the validation and calibration cases for modeling results were discussed, which will be very beneficial for increasing the accuracy and reliability of modeling results.

In this study, the performances of H2S, NH3, and HCl sensors for real-time monitoring in small emission facilities (4, 5 grades in Korea) were evaluated at high concentration conditions of those gases. And the proper approach for the collection of reliable measurement data by sensors was suggested through finding out the effect on sensor performances according to changes in temperature and humidity (relative humidity, RH) settings. In addition, an assessment on sensor data correction considering the effects produced by environmental settings was conducted. The effects were tested in four different conditions of temperature and humidity. The sensor performances (reproducibility, precision, lower detection limit (LDL), and linearity) were good for all three sensors. The intercept (ADC0) values for all three sensors were good for the changes of temperature and humidity conditions. The variation in the slope value of the NH3 sensor showed the highest value, and this was followed by the HCl, H2S sensors. The results of this study can be helpful for data collection by enabling the more reliable and precise measurements of concentrations measured by sensors.

Particulate matter is known to have adverse effects on health, making it crucial to accurately gauge its concentration levels. While the recent advent of low-cost air sensors has enabled real-time measurement of particulate matter, discrepancies in concentrations can arise depending on the sensor used, the measuring environment, and the manufacturer. In light of this, we aimed to propose a method to calibrate measurements between low-cost air sensor devices. In our study, we introduced decision tree techniques, commonly used in machine learning for classification and regression problems, to categorize particulate matter concentration intervals. For each interval, both univariate and multivariate multiple linear regression analyses were conducted to derive calibration equations. The concentrations of PM10 and PM2.5 measured indoors and outdoors with two types of LCS equipment and the GRIMM 11-A device were compared and analyzed, confirming the necessity for distinguishing between indoor and outdoor spaces and categorizing concentration intervals. Furthermore, the decision tree calibration method showed greater accuracy than traditional methods. On the other hand, during univariate regression analysis, the proportion exceeding a PM2.5/PM10 ratio of 1 was significantly high. However, using multivariate regression analysis, the exceedance rate decreased to 79.1% for IAQ-C7 and 89.3% for PMM-130, demonstrating that calibration through multivariate regression analysis considering both PM10 and PM2.5 is more effective. The results of this study are expected to contribute to the accurate calibration of particulate matter measurements and have showcased the potential for scientifically and rationally calibrating data using machine learning.

The dismantling nuclear power plant is expected to continue to change the radiation working environment compared to the operating nuclear power plant. Contamination monitors and survey meters currently in use have limitations in accurate analysis source term and dose rates for continuous changes in radiation fields at dismantling sites. Due to these limitations, the use of semiconductor detectors such as HPGe and CZT detectors with excellent energy resolution and portability is increasing. The CZT detector performs as well as the HPGe detector, but there is no proven calibration procedure yet. Therefore, in this study, the HPGe calibration method was reviewed to derive implications for the CZT detector calibration method. The operating principle of a semiconductor detector that measures gamma emission energy converts them into electrical signals is the same. Two calibrations of HPGe detectors are performed according to the standard calibration procedure for semiconductor detectors for gamma-ray measurement issued by the Korea Association of Standards & Testing Organizations. The first is an energy calibration that calculates gamma-ray peak position measurements and relational expressions using standard source term that emit gamma-rays. The channel values for energy are measured using certified reference source term to determine radionuclides by identifying channels corresponding to the measured peak energy values. The second is the measurement efficiency of measuring the coefficient calibration device, which measures gamma rays emitted from the standard source term. The detector efficiency by sample or distance is measured in consideration of the shape, size, volume, and density of the calibration device. The HPGe detector performs calibration once every six months through a verified calibration method and is being used as a source term analyzer at the power plant. The CZT detector may also establish a procedure for identifying peak positions through energy calibration and calculating radioactivity through efficiency calibration. This will be a way to expand the usability of semiconductor detectors and further monitor radiation in a more effective way.

NFDC (Nuclear Fuel and materials Data Center) is designated as a one of the data center of National Standard Reference Center from Ministry of Trade Industry and Energy at Dec. 30 2008. The fields of designation were nuclear fuel and energy materials. NFDC produces standard reference data of nuclear fuel and materials. To ensure reliability of experimental data uncertainty should be estimated. There are two kinds of uncertainty: A-type uncertainty from tester and B-type uncertainty from experimental equipments. To reduce the former, the measurement should be repeated for sufficient amount of times, and to reduce the latter type uncertainty all equipment have to be calibrated. In this study self calibration process of thermo-mechanical analyzer (TMA) was established to ensure the B-type uncertainty. The self calibration was performed using the standard reference material and correction factor was obtained. The correction factor was defined as the ratio of the thermal expansion value of the standard reference material reported in the certificate and the thermal expansion value measured using TMA. It is believed that the uncertainty evaluation process of TGA data developed in this study will be helpful for increasing reliability and stability evaluation of nuclear fuel and spent fuel.

The Wide-Angle Polarimetric Camera (PolCam) is installed on the Korea’s lunar orbiter, Danuri, which launched on August 5, 2022. The mission objectives of PolCam are to construct photometric maps at a wavelength of 336 nm and polarization maps at 461 and 748 nm, with a phase angle range of 0◦–135◦ and a spatial resolution of less than 100 m. PolCam is an imager using the push-broom method and has two cameras, Cam 1 and Cam 2, with a viewing angle of 45◦ to the right and left of the spacecraft’s direction of orbit. We conducted performance tests in a laboratory setting before installing PolCam’s flight model on the spacecraft. We analyzed the CCD’s dark current, flat-field frame, spot size, and light flux. The dark current was obtained during thermal / vacuum test with various temperatures and the flat-field frame data was also obtained with an integrating sphere and tungsten light bulb. We describe the calibration method and results in this study.

Detectors used for nuclear material safeguards activities are using scintillator detectors to quickly calculate the uranium enrichment at various nuclear material handling facilities. In order to measure the uranium enrichment, a region of interest is set around 185.7 keV which is the main gamma emission energy of uranium-235 in which the proportional relationship between the amount of uranium-235 and the net count is used. It is necessary to perform channel/energy calibration that a specific channel of the multi-channel analyzer is set to 185.7 keV. Most detector manufacturers have a built-in calibration source so that it is automatically performed when the detector starts to operate. In addition, the scintillator detector requires attention because the channel/energy gain may change depending on the ambient temperature so that a calibration source is used to compensate for this. In this paper, the spectral features are examined from among the scintillator detectors seeded with calibration sources used for safeguards activities. For this purpose, FLIR’s Identifinder-2 R400 T2 model and Canberra’s NAID model were used. HM-5 contains about 15nCi of Cs-137 and a photoelectric peak occurs at 662.1 keV. NAID contains about Am-241 of 55 nCi which alpha decays and subsequently emits gamma rays of 59.5 keV and 26.3 keV. The major difference among the detectors occurs in the background spectrum due to the difference in the source. From that kind of spectral features, it can be confirmed that the equipment is operating properly only when the spectrum by the corresponding calibration source is accurately known. The results of this study will enable a better understanding of the characteristics of scintillator detectors used for uranium enrichment analysis. Therefore, it is expected to be used as basic research for related software utilization as well as development in the future.

In order to permanently dispose of radioactive waste drums generated from nuclear power plants, disposal suitability must be demonstrated and the nuclides and radioactivity contained in the waste drums, including those in the shielding drums, must be identified. At present, reliable measurements of the nuclide concentration are performed using drum nuclide analysis devices at power plants and disposal facilities during acceptance inspection. The essential functions required to perform nuclide analysis using the non-destructive assay system are the correction for self-attenuation and the dead time correction. Until now, measurements have mainly been performed for drums containing solid waste such as DAW drums using SGS calibration drums with ordinary iron drums. However, for drums containing non-uniform radioactive waste, such as waste filters embedded in cement within shielding drums, a separate calibration drum needs to be produced. In order to produce calibration drums for shielded and embedded waste drums, the design considered the placement of calibration sources, setting of shielding thickness, correction for medium density, and cement mixing ratio. Based on these considerations, three calibration drums were produced. First, a shielding drum with an empty interior was produced. Second, a density correction drum filled with cement was produced to create apparent density on the surface of the shielding drum. Third, a physical model drum was produced containing a mock waste filter and cement filled in the shielding drum.

PURPOSES : The initial smoothness of concrete pavement surfaces must be secured to ensure better driving performance and user comfort. The roughness was measured after hardening the concrete pavement in Korea. When the initial roughness is poor, relatively large-scale repair works, such as milling or reconstruction must be performed. Hence, a method to measure the roughness of the concrete pavements in realtime during construction and immediately correct the abnormal roughness was developed in this study. METHODS : The profile of a concrete pavement section was measured at a construction site using sensors that were attached to the tinning equipment of the paver. The measured data included outliers and noise caused by the sensor and vibration of the paving equipment, respectively, which were further calibrated. Consequently, the calibrated data were input into the ProVAL program to calculate the roughness based on the international roughness index (IRI). Additionally, the profile of the section was re-measured using another method to verify the reliability of the calculated IRI. RESULTS : The profile data measured at the concrete pavement construction site were calibrated using methods, such as overlapped boxplot outlier removal and low-pass filtering. The outlier data from the global positioning system (GPS), which was installed to identify the construction distance, was also calibrated. The IRI was calculated using the ProVAL program by matching the measured profile and GPS data, and applying the moving average method. The calculated IRI was compared to that measured using another method, and the difference was within the tolerance. CONCLUSIONS : A method to measure the roughness of the concrete pavements in real time during construction was developed in this study. Hence, the performance of concrete pavements can be improved by enhancing the roughness of the pavement considerably using the aforementioned method.

최근 원예작물의 지속가능한 생산을 위한 작물 생육환경 센 싱 기반 복합환경제어시스템 연구와 산업적 이용이 부각되면 서, 노지재배에 적용하기 적합한 토양센서 활용 방안 연구가 활발히 이루어지고 있다. 본 연구는 산업 및 연구 현장에서 많 이 사용되고 있는 TEROS 12 FDR 센서(frequency domain reflectometry sensor)를 노지 과수원의 토양에 알맞게 활용 하기 위하여 국내 세 지역 과수원 토양의 토성별 FDR 센서 활 용 방법을 제시하고자 수행하였다. 실제 과수가 재배되고 있 는 각 과수원에서 토양을 채취하여, 토성 및 토양수분보유곡 선을 조사하였으며, 토양별 TEROS 12 센서 Raw 값과 이에 대응하는 용적수분함량 값을 선형 회귀 분석, 3차 회귀 분석을 통해 보정식을 얻은 뒤 제조사에서 제공하는 광질 토양 보정 식과 비교 분석하였다. 채취한 세 과수원의 토양은 모두 토성 이 달랐으며, 토성에 따라 각 보수력에 따른 용적수분함량 수 치에 차이가 있었다. 또한, TEROS 12 센서 보정식에서는 모 든 토양에서 3차 회귀 분석 보정식이 결정계수 0.95 이상으로 가장 높게 나타났으며, RMSE도 가장 낮게 나타났다. 제조사 에서 제공하는 보정식을 사용하여 TEROS 12 센서의 용적수 분함량을 보정할 경우 토양에 따라 실제 수치에 비해 최대 0.09－0.17m3·m-3가량 낮게 나타나, FDR 센서 사용시 적용 토양에 알맞은 보정이 반드시 선행되어야 함을 확인하였다. 또한 토성에 따라 토양의 보수력 구간에 따른 용적수분함량 범위의 차이가 있었으며, 토양 용적수분함량의 수치 해석에 보수력 정보가 수반되어야 할 것으로 나타났다. 또한, 사질이 많은 토양에서는 관수 개시점 측정을 위해 FDR 센서를 활용 하는 데 있어 용적수분함량 측정 범위가 상대적으로 좁아 정 밀도가 떨어질 것으로 판단되었다. 결론적으로 토양에서 FDR 센서를 통해 토양수분의 변화를 알맞게 해석하고 노지 에서 알맞은 관수 시점을 선정하기 위해서는, 적용 토양의 수 분보유특성을 파악하고 FDR 센서 보정을 선행하여 올바른 토양 수분 정보 제공이 필요할 것이다.

A tensile test is performed to obtain the mechanical property data of the spent fuel cladding. In general, the elastic modulus, elongation, yield stress, tensile stress, etc. are obtained by axial tensile test of cladding attaching an extensometer. However, due to the limitation in the number of specimens for spent nuclear fuel that can be made, the ring tensile test (RTT) whose required length of the specimen is short is mainly performed. In the case of RTT, an extensometer or strain gauge cannot be attached because the gauge part of the specimen is formed around the cladding and is short. In addition, since a load is applied in the radial direction of the cladding, a curved portion of the circular cladding is spread out and becomes straight, and then the cladding is tensioned. For this reason, it is difficult to obtain the stress-strain curve directly from the RTT results. Isight, which is used to identify the optimization design parameters, was used to build an optimization process that minimizes the difference between the RTT and the analysis to estimate the material property. For this, the elastic modulus, plastic strain, and the radius of the RTT jig were taken as fixed variables. As variables, isotropic hardening data and plastic stress were taken. The objective function was taken as the minimization of the area difference of the load-displacement curve obtained from the tests and analysis, of the difference in the magnitude of the maximum reaction force, and of the difference in the location where the maximum reaction force occurred. Optimization workflow was configured in the following order. First, using the calculator component, plastic stress design variables were created. Next, ABAQUS was placed to perform analysis using design variables, and the reaction force or displacement was calculated. After that, the reaction force was calculated considering the 1/4 symmetry condition using the script component. After that, the data matching component performed quantitative comparison of test and analysis data. Finally, by utilizing the exploration component, the plastic stress design variable that minimizes the difference in the objective function was obtained by automatically changing six optimization algorithms. In this paper, the constructed optimization process and the obtained plastic stress by applying it to the SUS316 RTT results are briefly described. The established optimization process can be utilized to obtain mechanical property from the results of the cladding RTT of spent nuclear fuel or new material.