• Journal of Korea Water Resources Association
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• v.47 no.4
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• pp.371-384
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• 2014

This study developed a new algorithm of extreme rainfall extraction based on the Communication, Ocean and Meteorological Satellite (COMS) and the Tropical Rainfall Measurement Mission (TRMM) Satellite image data and evaluated its applicability for the heavy rainfall event in July-2011 in Seoul, South Korea. The power-series-regression-based Z-R relationship was employed for taking into account for empirical relationships between TRMM/PR, TRMM/VIRS, COMS, and Automatic Weather System(AWS) at each elevation. The estimated Z-R relationship ($Z=303R^{0.72}$) agreed well with observation from AWS (correlation coefficient=0.57). The estimated 10-minute rainfall intensities from the COMS satellite using the Z-R relationship generated underestimated rainfall intensities. For a small rainfall event the Z-R relationship tended to overestimated rainfall intensities. However, the overall patterns of estimated rainfall were very comparable with the observed data. The correlation coefficients and the Root Mean Square Error (RMSE) of 10-minute rainfall series from COMS and AWS gave 0.517, and 3.146, respectively. In addition, the averaged error value of the spatial correlation matrix ranged from -0.530 to -0.228, indicating negative correlation. To reduce the error by extreme rainfall estimation using satellite datasets it is required to take into more extreme factors and improve the algorithm through further study. This study showed the potential utility of multi-geostationary satellite data for building up sub-daily rainfall and establishing the real-time flood alert system in ungauged watersheds.

• Journal of the Korea institute for structural maintenance and inspection
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• v.27 no.2
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• pp.17-24
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• 2023

A post-processing technique for the measurement signal of a solenoid-type sensor is introduced. The solenoid-type sensor nondestructively evaluates an external tendon of prestressed concrete using the total flux leakage (TFL) method. The TFL solenoid sensor consists of primary and secondary coils. AC electricity, with the shape of a sinusoidal function, is input in the primary coil. The signal proportional to the differential of the input is induced in the secondary coil. Because the amplitude of the induced signal is proportional to the cross-sectional area of the tendon, sectional loss of the tendon caused by ruptures or corrosion can be identified by the induced signal. Therefore, it is important to extract amplitude information from the measurement signal of the TFL sensor. Previously, the amplitude was extracted using local maxima, which is the simplest way to obtain amplitude information. However, because the sampling rate is dramatically decreased by amplitude extraction using the local maxima, the previous method places many restrictions on the direction of TFL sensor development, such as applying additional signal processing and/or artificial intelligence. Meanwhile, the proposed method uses amplitude demodulation to obtain the signal amplitude from the TFL sensor, and the sampling rate of the amplitude information is same to the raw TFL sensor data. The proposed method using amplitude demodulation provides ample freedom for development by eliminating restrictions on the first coil input frequency of the TFL sensor and the speed of applying the sensor to external tension. It also maintains a high measurement sampling rate, providing advantages for utilizing additional signal processing or artificial intelligence. The proposed method was validated through experiments, and the advantages were verified through comparison with the previous method. For example, in this study the amplitudes extracted by amplitude demodulation provided a sampling rate 100 times greater than those of the previous method. There may be differences depending on the given situation and specific equipment settings; however, in most cases, extracting amplitude information using amplitude demodulation yields more satisfactory results than previous methods.

• Korean Journal of Mineralogy and Petrology
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• v.37 no.1
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• pp.1-11
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• 2024

World stone production in 2021 stood at 162.5 million tons, up by 7.5 million tons, or 4.8 percent, compared to the previous year when the production came in at 155 million tons. Six top countries with the most of stone production were China, India, Turkey, Brazil, Iran and Italy and these six countries accounted for 72.8 percent of total production in the world. Stone exports stood at $21.68 billion in 2021, up by $2.3 billion from the previous year. Exports of raw materials and processed stones stood at 54.4 million tons, up by 2.98 million tons from the previous year. In terms of aggregate exports, exports of natural stones increased by $2.3 billion to $21.7 billion while exports of artificial stones rose $2.6 billion to $13.6 billion in 2021 compared to the previous year. The average price of stone (Code: 68.02) was up by $65.2 per ton to $794.82. The price of board, processed stone, an ingredient for building materials, increased by $3.52 per square meter to $42.96 per square meter. Recycling was always the problem as the volume of the total quarry was 333.5 million tons, of which only 28.8 percent were finished products and the remaining 71.2 percent were waste generated from stone extraction and processing. Korea's stone exports stood at $1.97 million in 2021, down 38.3 percent on year, while imports were up 8.6 percent to $758.9 million. Stone exports are expected to grow to 66.1 million tons in 2025, while usage is expected to reach 108.92 million tons, or 2 billion square meters.