• Journal of Integrative Natural Science
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• v.17 no.1
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• pp.1-12
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• 2024

Many abnormal climate events are occurring around the world. The cause of abnormal climate is related to temperature. Factors that affect temperature include excessive emissions of carbon and greenhouse gases from a global perspective, and air circulation from a local perspective. Due to the air circulation, many abnormal climate phenomena such as abnormally high temperature and abnormally low temperature are occurring in certain areas, which can cause very serious human damage. Therefore, the problem of abnormal temperature should not be approached only as a case of climate change, but should be studied as a new category of climate crisis. In this study, we proposed a model for the classification of abnormal temperature using random forests based on various meteorological data such as longitudinal observations, yellow dust, ultraviolet radiation from 2018 to 2022 for each region in Korea. Here, the meteorological data had an imbalance problem, so the imbalance problem was solved by oversampling. As a result, we found that the variables affecting abnormal temperature are different in different regions. In particular, the central and southern regions are influenced by high pressure (Mainland China, Siberian high pressure, and North Pacific high pressure) due to their regional characteristics, so pressure-related variables had a significant impact on the classification of abnormal temperature. This suggests that a regional approach can be taken to predict abnormal temperatures from the surrounding meteorological environment. In addition, in the event of an abnormal temperature, it seems that it is possible to take preventive measures in advance according to regional characteristics.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.18 no.8
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• pp.34-40
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• 2017

In recent years, global warming has caused abnormal weather phenomena. Unusually cold climates have occurred all around the world, including cold waves in the Northeastern United States, Beijing, China, Southern India, and Pakistan, as well as floods in Chile, Kazakhstan, and Vietnam. China has been experiencing a nationwide heat wave annually since the year 2013, especially in the southern region. In this study, we used Landsat 8 OLI TIRS sensor images from four periods to analyze the characteristics of abnormal high temperature phenomena in Cixi-si, China. Land cover classification was performed using 10 bands of satellite imagery, and the surface temperature was extracted using the 10th thermal band. The results of the land cover classification of the fourth period show the changes of the time series quantitatively. The results of the surface temperature calculation provided both the average overall temperature and the average temperature of individual items. The temperature was found to be highest for buildings, followed by grassland, forest, agricultural land, water systems, and tidal flats in the same period.

• Proceedings of the Korean Institute of Electrical and Electronic Material Engineers Conference
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• 2002.07a
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• pp.466-469
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• 2002

In the sintering of YIG, abnormal grain growth phenomena was observed. This abnormal grain growth is related to the sintering temperature in this experiment. In the sintering below 145$0^{\circ}C$., the sintered body showed narrow size distribution. However, in the sintering at 145$0^{\circ}C$, a few grains grew rapidly with respect to other grains, and bimodal size distribution was appeared. Liquid phase was not observed far from the abnormally grown large grains, but only near the large grains. This means that the abnormal grain growth was caused by the nonuniform distribution of liquid phase which promote the grains growth. This nonuniform distribution of liquid phase was thought to be due to the nonuniform mixing of the starting materials. This abnormal grain growth was suppressed by enhance the compositional uniformity by multiple calcination.

• Proceedings of the Korean Institute of Building Construction Conference
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• 2010.05a
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• pp.95-97
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• 2010

This study revealed unusual weather phenomena by comparing and analyzing monthly average temperature and amount of snowfall for the past 10 years, and, based on the weather phenomena, analyzed damage cases of concrete structures in winter. As a result, the temperature for the recent one year became greatly low compared with the monthly average for the past 10 years, and the snowfall increased by 4-5 times compared with the past, so that the frost damage of concrete structures also greatly occurred. Accordingly, in case of concrete construction, because there may occur various variables owing to abnormal weather conditions, it is required that thorough quality control should be performed even from the stage of construction plan, execution and maintenance.

• Journal of the Korean Institute of Electrical and Electronic Material Engineers
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• v.16 no.12
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• pp.1131-1135
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• 2003

In the sintering of YIG, abnormal grain growth phenomena were observed. This abnormal grain growth is related to the sintering temperature in this experiment. In the sintering below 1450$^{\circ}C$, the sintered body showed narrow size distribution. However, in the sintering at 1450$^{\circ}C$, a few grains grew rapidly with respect to other grains, and bimodal size distribution was appeared. From the observation of the microstructure, liquid phase was not observed far from the abnormally grown large grains, but only near the large grains. This means that the abnormal grain growth was caused by the nonuniform distribution of liquid phase which promote the grains growth. Because the growth rate of grains near the liquid phase is much higher than that of the other grains, a few grains grow rapidly. This nonuniform distribution of liquid phase was thought to be due to the nonuniform mixing of the calcined powders. This abnormal grain growth was suppressed by enhancement of the compositional uniformity by multiple calcination.

• The Transactions of the Korean Institute of Electrical Engineers
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• v.36 no.6
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• pp.418-423
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• 1987

In the course of the investigation to the field dependent electrical conducation mechanism in polypropylene, an abnormal conduction phenomena such as voltage controlled negative resistance charateristics has been observed at the junction of two regions charateriged by schottky effect and space charge effect respectively. This abnormal characteristics was observed initially about 110MV / m of the field strength and at 25 , however, the field strength where it observed was decreased and the apparent feature of negative charateristics was less pronounced as increasing ambient temperature. Although the observations of analogous characteristics in other materials such as polyethylene, polymethylemethactylate, and polystyrene have already been reported together with plausible explanation by Toureille and others, however, it was found that the proposed concept by those authors was little use to the present observations for quantitative discussions. Accordingly we tried to adapt another conceptual discussion based on Gibbons's formulation pertaing to the saturatio trend of the field dependent drift velocity of carriers towards the thermal velocity corresponding to the ambient temperature so that the quantitative explanatio on the observed facts has been succeeded to some estent of reasonable acceptance.

• Korean Journal of Remote Sensing
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• v.38 no.3
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• pp.265-282
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• 2022

Sea surface temperature (SST) is a factor that greatly influences ocean circulation and ecosystems in the Earth system. As global warming causes changes in the SST near the Korean Peninsula, abnormal water temperature phenomena (high water temperature, low water temperature) occurs, causing continuous damage to the marine ecosystem and the fishery industry. Therefore, this study proposes a methodology to predict the SST near the Korean Peninsula and prevent damage by predicting abnormal water temperature phenomena. The study area was set near the Korean Peninsula, and ERA5 data from the European Center for Medium-Range Weather Forecasts (ECMWF) was used to utilize SST data at the same time period. As a research method, Long Short-Term Memory (LSTM) algorithm specialized for time series data prediction among deep learning models was used in consideration of the time series characteristics of SST data. The prediction model predicts the SST near the Korean Peninsula after 1- to 7-days and predicts the high water temperature or low water temperature phenomenon. To evaluate the accuracy of SST prediction, Coefficient of determination (R²), Root Mean Squared Error (RMSE), and Mean Absolute Percentage Error (MAPE) indicators were used. The summer (JAS) 1-day prediction result of the prediction model, R²=0.996, RMSE=0.119℃, MAPE=0.352% and the winter (JFM) 1-day prediction result is R²=0.999, RMSE=0.063℃, MAPE=0.646%. Using the predicted SST, the accuracy of abnormal sea surface temperature prediction was evaluated with an F1 Score (F1 Score=0.98 for high water temperature prediction in summer (2021/08/05), F1 Score=1.0 for low water temperature prediction in winter (2021/02/19)). As the prediction period increased, the prediction model showed a tendency to underestimate the SST, which also reduced the accuracy of the abnormal water temperature prediction. Therefore, it is judged that it is necessary to analyze the cause of underestimation of the predictive model in the future and study to improve the prediction accuracy.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.35 no.4
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• pp.313-318
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• 2017

Land surface temperature is essential for monitoring abnormal climate phenomena such as UHI (Urban Heat Islands), and for modeling weather patterns. However, the quality of surface temperature obtained from the optical space imagery is affected by many factors such as, revisit period of the satellite, instance of capture, spatial resolution, and cloud coverage. Landsat 8 imagery, often used to obtain surface temperatures, has a high resolution of 30 meters (100 meters rearranged to 30 meters) and a revisit frequency of 16 days. On the contrary, MODIS imagery can be acquired daily with a spatial resolution of about 1 kilometer. Many past attempts have been made using both Landsat and MODIS imagery to complement each other to produce an imagery of improved temporal and spatial resolution. This paper applied machine learning methods and performed downscaling which can obtain daily based land surface temperature imagery of 30 meters.

• Nuclear Engineering and Technology
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• v.29 no.3
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• pp.186-195
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• 1997

When asymmetric thermal-hydraulic conditions occur between cold legs, the core inlet temperature will be nonuniform if the coolant is not mixed perfectly in the lower plenum. These uneven core inlet conditions may induce the change in core power distribution. Thus realistic prediction of thermal mixing is important in such abnormal conditions. In this study, reactor internals, which are scaled down as to conserve the flow area ratio, are set up in the model of KORI Unit 1 with the scaling factor of 1/710 by volume and coolant temperatures are measured beneath the lower core plate. Based on experimental results, the ability of COMMIX-1B code to simulate the coolant mixing phenomena in the lower plenum is estimated. The results show that complete mixing never occurs in any conditions and the mixing pattern is characterized according to the plant type.

• Proceedings of the Korean Society of Propulsion Engineers Conference
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• 2011.11a
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• pp.218-222
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• 2011

During the development of the iridium catalyst for domestic production, the catalyst failure, loss, sintering phenomena are observed by high pressure and temperature. By these abnormal failure of catalyst bed, the performance of thruster is degraded. To figure out the detail phenomena on the damaged catalyst bed, a numerical analysis code is developed by assuming the catalyst bed as an one dimensional porous media. The numerical analysis code is validated with experiment data. Thereby, resulting physical phenomena are examined by considering the variation of catalyst bed characteristics incurred by catalyst granule failure. Through these numerical analyses we figure out the effect of the catalyst loss on the decomposition of hydrazine and ammonia.