• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.25 no.1
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• pp.48-57
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• 2015

In a sodium-cooled fast reactor, which is a Generation-IV reactor, refueling is conducted by rotating, but not opening, the reactor head to prevent a reaction between the sodium, water and air. Therefore, an inspection technique that checks for the presence of any obstacles between the reactor core and the upper internal structure, which could disturb the rotation of the reactor head, is essential prior to the refueling of a sodium-cooled fast reactor. To this end, an ultrasound-based inspection technique should be employed because the opacity of the sodium prevents conventional optical inspection techniques from being applied to the monitoring of obstacles. In this study, a ranging inspection technique using a plate-type ultrasonic waveguide sensor was developed to monitor the presence of any obstacles between the reactor core and the upper internal structure in the opaque sodium. Because the waveguide sensor installs an ultrasonic transducer in a relatively cold region and transmits the ultrasonic waves into the hot radioactive liquid sodium through a long waveguide, it offers better reliability and is less susceptible to thermal or radiation damage. A 10 m horizontal beam waveguide sensor capable of radiating an ultrasonic wave horizontally was developed, and beam profile measurements and basic experiments were carried out to investigate the characteristics of the developed sensor. The beam width and propagation distance of the ultrasonic wave radiated from the sensor were assessed based on the experimental results. Finally, a feasibility test using cylindrical targets (corresponding to the shape of possible obstacles) was also conducted to evaluate the applicability of the developed ranging inspection technique to actual applications.

• Journal of the Korean Society of Radiology
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• v.15 no.2
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• pp.265-271
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• 2021

The pattern of the tree's internal swelling depends on many causes. Since it is difficult to detect these various causes of swelling with a general method, if the state of swelling for a long time cannot be confirmed, serious damage to the trees may occur due to enlargement of the swelling area. In the method of acquiring a tree tomography image, an impulse passing through the tree is generated by tapping the sensor with a rubber mallet, and the moving speed is recorded. In this paper, to measure cracks, cavities, and swelling due to physical damage, we developed a 3D viewer that can know the internal state of a tree using a tree cross-section image acquired from Arbotom to determine the degree of swelling inside the tree. Based on this, we tried to present data that can be referred to when surgical operation of trees is required. In order to acquire a tomographic image of a tree, 6 sensors were attached to the three Yangpala and Maple trees, and a 1 m-long tree was measured using the Arbotom program, and a 3D image was implemented through the 3D Viewer created using MATLAB. In addition to simply acquiring images, the cross-sectional length and volume of the tree were measured. In the actually produced 3D Viewer, the length of the part where the swelling of the maple tree occurred was 33.12 cm, and the swelling of the yangpala tree was measured as 21.41 cm. The volume of the maple tree was measured to be 78.832 ㎤. As a result of comparing the cross-sectional image of the Arbotom and the 3D image, the same result as the real aspect of the tree was obtained, so it can be judged that the reliability of the manufactured software is also secured, and data to be applied to the surgical tree operation through the created Viewer is provided. It is believed that the damage will be minimized.

• Korean Journal of Remote Sensing
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• v.34 no.6_1
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• pp.869-877
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• 2018

The area of desert in East Asia is increasing every year, and it cause a great cost of social damage. Because desert is widely distributed and it is difficult to approach people, remote sensing using satellites is commonly used. But the study of desert area comparison is insufficient which is calculated by satellite sensor. It is important to recognize the characteristics of the desert area data that are calculated for each sensor because the desert area calculated according to the selection of the sensor may be different and may affect the climate prediction and desertification prevention measures. In this study, the desert area of Northeast Asia in 2001-2013 was calculated and compared using Moderate Resolution Imaging Spectroradiometer (MODIS) and Vegetation. As a result of the comparison, the desert area of Vegetation increased by $3,020km^2/year$, while in the case of MODIS, it decreased by $20,911km^2/year$. We performed indirect validation because It is difficult to obtain actual data. We analyzed the correlation with the occurrence frequency of Asian dust affected by desert area change. As a result, MODIS showed a relatively low correlation with R = 0.2071 and Vegetation had a relatively high correlation with R = 0.4837. It is considered that Vegetation performed more accurate desert area calculation in Northeast Asian desert area.

• Korean Journal of Remote Sensing
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• v.39 no.5_1
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• pp.655-667
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• 2023

Algal bloom outbreaks are frequently reported around the world, and serious water pollution problems arise every year in Korea. It is necessary to protect the aquatic ecosystem through continuous management and rapid response. Many studies using satellite images are being conducted to estimate the concentration of chlorophyll-a (Chl-a), an indicator of algal bloom occurrence. However, machine learning models have recently been used because it is difficult to accurately calculate Chl-a due to the spectral characteristics and atmospheric correction errors that change depending on the water system. It is necessary to consider the factors affecting algal bloom as well as the satellite spectral index. Therefore, this study constructed a dataset by considering water quality, hydrological and meteorological factors, and sentinel-2 images in combination. Representative ensemble models random forest and extreme gradient boosting (XGBoost) were used to predict the concentration of Chl-a in eight weirs located on the Nakdong river over the past five years. R-squared score (R²), root mean square errors (RMSE), and mean absolute errors (MAE) were used as model evaluation indicators, and it was confirmed that R² of XGBoost was 0.80, RMSE was 6.612, and MAE was 4.457. Shapley additive expansion analysis showed that water quality factors, suspended solids, biochemical oxygen demand, dissolved oxygen, and the band ratio using red edge bands were of high importance in both models. Various input data were confirmed to help improve model performance, and it seems that it can be applied to domestic and international algal bloom detection.