The objective of this experiment was to investigate the effect of drip irrigation volume on tomatoes (Solanum lycopersicum L.) grown in a greenhouse using perlite medium. Plants were treated by three different irrigation treatment I0, I25, and I50 (where irrigation volume of I25 and I50 was 25% and 50% higher than I0, having limited or no leaching). Growth characteristics of plants, yield and water use efficiency were measured. The result showed that plant height, leaf length and leaf width were lowest in the I0 treated plants. However, these parameters were not statistically significant differences between the plants that were grown in the I25 and I50 treatment. Soluble solids content, acidity and dry matter of 111th, 132nd, and 143rd days harvested tomato were higher in the plants irrigated with lowest volume (I0) than the higher volume (I25 or I50). In addition, water content was lower in the 111th and 132nd days of harvested tomatoes from the I0 treatment. The number of big-size tomatoes (>180 g) was significantly higher in the I25 irrigated plants. There was no significant difference in the total number of harvested fruits among the treatments. The average fruit weight and total yield of harvested tomatoes were lowest in the I0 treated plants. The water consumption of tomato was not significantly different amongst the treatments but water use efficiency was lowest in the I0 treatment. Principal component analysis revealed that total soluble solid and acidity of tomato showed a positive correlation between each other. These results suggest that I25 was the optimum irrigation treatment for tomato based on its measured growth characteristics, yield and water use efficiency.

Since radon was detected in mattresses of famous bed furniture brands in 2018, the nuclear safety and security commission (NSSC) announced the radiation safety management act in April 2021 to protect the public health and environment. This act stipulates the safety management of radiation that can be encountered in the natural environment such as the notification of radioactivity concentration of source materials, process by-products, the installation and operation of radioactive monitors. In this study, a model was established to predict radioactive exposure dose from radioactive materials such as radon and uranium detected in consumer products such as bed mattresses, pillows, shower, bracelets and masks in order to identify major radioactive substances that largely affect the exposure dose. A period of seven years from 2014 to 2020 was investigated for the source materials and exposure doses of consumer products containing naturally occurring radioactive materials (NORMs). We analyzed these using machine learning models such as classification and regression tree (CART), Random Forest and TreeNet. Index development and verification were performed to evaluate the predictive performance of the models. Overall, predictive performance was highest when Random Forest or TreeNet was used for each consumer product. Thoron had a great influence on the internal exposure dose of bedding, clothing and mats. Uranium had a great influence on the internal exposure dose of other consumer products except whetstones. When the number of data is very small or the missing value rate is high, it is difficult to expect accurate predictive performance even with machine learning techniques. If we significantly reduce the missing value rate of data or use the limit of detection value instead of missing values, we can build a model with more accurate predictive performance.

Republic of Korea (ROK) is operating the Integrated Environmental Radiation Monitoring Network (IERNet) in preparation for a radioactive emergency based on Article 105 of the Nuclear Safety Act (Monitoring of Nationwide Radioactive Environment). 215 radiation monitoring posts are monitoring a wide area, but their location is fixed, so they can’t cover areas where the post is not equipped around the Nuclear Power Plants (NPPs). For this, a mobile radiation monitoring system was developed using a drone or vehicle. However, there are disadvantages: it is performed only at a specific cycle, and an additional workforce is required. In this study, a radiation monitoring system using public transportation was developed to solve the above problems. Considering the range of dose rates from environmental radiation to high radiation doses in accidents, the detector was designed by combining NaI (TI) (in the low-dose area) and GM detector (in the high-dose area). Field test was conducted by installed on a city bus operated by Yeonggwang-gun to confirm the performance of the radiation monitoring system. As a result of the field test, it was confirmed that data is transmitted from the module to the server program in both directions. Based on this study, it will be possible to improve the radiation monitoring capability near nuclear facilities.

Waste containers for packaging, transportation and disposal of NPP (Nuclear Power Plant) decommissioning wastes are being developed. In this study, drop tests were conducted to prove the safety of containers for packaging of the wastes and to verify the reliability of the analysis results by comparing the test and analysis results. The drop height of the waste containers was considered to be 30 mm, which is the maximum lifting speed of a 50 tons crane in the waste treatment facility converted to the drop height. Drop orientation of the containers was considered for bottom-end on drop. The impact acceleration and strain data were obtained to verify the reliability of the analysis results. Before and after the drop tests, measurement of the dose rate and the radiographic testing for concrete wall, and measurement of the wall thickness of steel plate were conducted to evaluate the radiation shielding integrity. Also, measurement of bolt torque, and visual inspection were conducted to evaluate the loss or dispersion of radioactive contents. After the drop tests, the radiation dose rate on the container surface did not increase by more than 20%, and there was no crack in the concrete. In addition, the thickness of the steel plate did not change within the measurement error. Therefore, the radiation shielding integrity of the container was maintained. After the drop tests, the lid bolts were not damaged and there was no loss of pretension in the lid bolts. In addition, there was no loss or dispersion of the contents as a result of visual inspection. In order to prove the reliability of the drop analysis results, safety verifications were performed using the drop test results, and the appropriate conservatism for the analysis results and the validity of the analysis model were confirmed. Therefore, the structural integrity of the waste containers was maintained under the drop test conditions.