• Journal of Korea Water Resources Association
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• v.55 no.8
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• pp.623-634
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• 2022

Due to river maintenance projects such as the creation of hydrophilic areas around rivers and the Four Rivers Project, the flow characteristics of rivers are continuously changing, and the risk of water quality accidents due to the inflow of various pollutants is increasing. In the event of a water quality accident, it is necessary to minimize the effect on the downstream side by predicting the concentration and arrival time of pollutants in consideration of the flow characteristics of the river. In order to track the behavior of these pollutants, it is necessary to calculate the diffusion coefficient and dispersion coefficient for each section of the river. Among them, the dispersion coefficient is used to analyze the diffusion range of soluble pollutants. Existing experimental research cases for tracking the behavior of pollutants require a lot of manpower and cost, and it is difficult to obtain spatially high-resolution data due to limited equipment operation. Recently, research on tracking contaminants using RGB drones has been conducted, but RGB images also have a limitation in that spectral information is limitedly collected. In this study, to supplement the limitations of existing studies, a hyperspectral sensor was mounted on a remote sensing platform using a drone to collect temporally and spatially higher-resolution data than conventional contact measurement. Using the collected spatio-temporal hyperspectral images, the tracer concentration was calculated and the transverse dispersion coefficient was derived. It is expected that by overcoming the limitations of the drone platform through future research and upgrading the dispersion coefficient calculation technology, it will be possible to detect various pollutants leaking into the water system, and to detect changes in various water quality items and river factors.

• Tunnel and Underground Space
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• v.32 no.5
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• pp.285-297
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• 2022

We report results of Extended Leak-Off Test (XLOT) conducted in a large diameter borehole, which is drilled for installation of deep borehole geophysical monitoring system to monitor micro-earthquakes and fault behavior of major fault zones in the southeastern Korean Peninsula. The borehole was planned to secure a final diameter of 200 mm (or more) at a depth of ~1 km, with 12" diameter wellbore to intermediate depths, and 7-7/8" (~200 mm) to the bottom hole depth. We drilled first the 12" borehole to approximately 504 m deep and installed American Petroleum Institute standard 8-5/8" casing, then annulus between the casing and bedrock was fully cemented. XLOT was carried out for several purposes such as confirming casing and cementing integrity, measuring rock stress states. To that end, we drilled additional 4 m long open hole interval to directly inject water and pressurize into the rock mass using the upper API casings. During the XLOT, flow rates and interval pressures were recorded in real time. Based on the logs we tried to analyze hydraulic conductivity of the test interval.

• Journal of the Korea institute for structural maintenance and inspection
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• v.27 no.3
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• pp.21-29
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• 2023

In this study, the stress characteristics of temporary fixed steel rods were analyzed in the "temporary fixing system using internal prestressing tension", which is mainly applied to the construction of superstructures by FCM. It was difficult to confirm the changes in initial tensile force in this system because the steel rod was internally connected to the pier and the PSC BOX. Therefore, measurement was performed before and after the completion of each segment using an FBG sensor to measure the change in the micro length of the steel rod. The results of the analysis showed that 75% to 90% of the maximum vertical contraction of the steel rod that occurred until the completion of the cantilever segment occurred in the fixing ~ 1segment, and the maximum loss of initial prestressing force was 39%. Such excessive loss of tension force to 1 segment means that tension is needed to improve the precision of construction during the fixation, and re-tension is needed to secure stability for conduction of cantilever segments after the completion of 1segment. In the 2 ~ last segment, the stress of the steel rod decreased gradually, and in the summer, the decrease in stress tended to partially recover due to the increase in the length of the steel rod corresponding to the increase in the vertical volume of PSC BOX. The dominant factor in the stress change in 2~ last segment in this phenomenon is judged to be the change in the length of the steel rod according to the temperature. Unlike the change in length, the relaxation was 1.2-2.7%, which was mostly offset by the opposite stress corresponding to the temperature stress. Therefore, a plan was proposed to improve the internal stress, such as adjusting the fixation time.

• Korean Journal of Remote Sensing
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• v.39 no.2
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• pp.207-221
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• 2023

This study suggests deep neural network models for estimating air temperature with Level 1B (L1B) datasets of GEO-KOMPSAT-2A (GK-2A). The temperature at 1.5 m above the ground impact not only daily life but also weather warnings such as cold and heat waves. There are many studies to assume the air temperature from the land surface temperature (LST) retrieved from satellites because the air temperature has a strong relationship with the LST. However, an algorithm of the LST, Level 2 output of GK-2A, works only clear sky pixels. To overcome the cloud effects, we apply a deep neural network (DNN) model to assume the air temperature with L1B calibrated for radiometric and geometrics from raw satellite data and compare the model with a linear regression model between LST and air temperature. The root mean square errors (RMSE) of the air temperature for model outputs are used to evaluate the model. The number of 95 in-situ air temperature data was 2,496,634 and the ratio of datasets paired with LST and L1B show 42.1% and 98.4%. The training years are 2020 and 2021 and 2022 is used to validate. The DNN model is designed with an input layer taking 16 channels and four hidden fully connected layers to assume an air temperature. As a result of the model using 16 bands of L1B, the DNN with RMSE 2.22℃ showed great performance than the baseline model with RMSE 3.55℃ on clear sky conditions and the total RMSE including overcast samples was 3.33℃. It is suggested that the DNN is able to overcome cloud effects. However, it showed different characteristics in seasonal and hourly analysis and needed to append solar information as inputs to make a general DNN model because the summer and winter seasons showed a low coefficient of determinations with high standard deviations.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.29 no.5A
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• pp.557-564
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• 2009

In recent years, there have been numerous explosion-related accidents due to military and terrorist activities. Such incidents caused not only damages to structures but also human casualties, especially in urban areas. To protect structures and save human lives against explosion accidents, better understanding of the explosion effect on structures is needed. In an explosion, the blast overpressure is applied to concrete structures as an impulsive load of extremely short duration with very high pressure and heat. Generally, concrete is known to have a relatively high blast resistance compared to other construction materials. However, information and test results related to the blast experiment of internal and external have been limited due to military and national security reasons. Therefore, in this paper, to evaluate blast effect on reinforced have concrete structure and its protective performance, blast tests are carried out with $1.0m{\times}1.0m{\times}150mm$ reinforce concrete slab structure at the Agency for Defence Development. The standoff blast distance is 1.5 m and the preliminary tests consists with TNT 9 lbs and TNT 35 lbs and the main tests used ANFO 35 lbs. It is the first ever blast experiment for nonmilitary purposes domestically. In this paper, based on the basic experiment procedure and measurement details for acquiring structural behavior data, the blast experimental measurement system and procedure are established details. The procedure of blast experiments are based on the established measurement system which consists of sensor, signal conditioner, DAQ system, software. It can be used as basic research references for related research areas, which include protective design and effective behavior measurements of structure under blast loading.

• Journal of the Korea institute for structural maintenance and inspection
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• v.27 no.6
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• pp.120-129
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• 2023

To evaluate the vertical loads on railway bridges, conventional load tests are typically conducted. However, these tests often entail significant costs and procedural challenges. Railway conditions involve nearly identical load profiles due to standardized rail systems, which may appear straightforward in terms of load conditions. Nevertheless, this study aims to validate load tests conducted under operational train conditions by comparing the results with those obtained from conventional load tests. Additionally, static and dynamic structural behaviors are extracted from the measurement data for evaluation. To ensure the reliability of load testing, this research demonstrates feasibility through comparisons of existing measurement data with sensor attachment locations, train speeds, responses between different rail lines, tendency analysis, selection of impact coefficients, and analysis of natural frequencies. This study applies to the Dongho Railway Bridge and verifies the applicability of the proposed method. Ten operational trains and 44 sensors were deployed on the bridge to measure deformations and deflections during load test intervals, which were then compared with theoretical values. The analysis results indicate good symmetry and overlap of loads, as well as a favorable comparison between static and dynamic load test results. The maximum measured impact coefficient (0.092) was found to be lower than the theoretical impact coefficient (0.327), and the impact influence from live loads was deemed acceptable. The measured natural frequencies approximated the theoretical values, with an average of 2.393Hz compared to the calculated value of 2.415Hz. Based on these results, this paper demonstrates that for evaluating vertical loads, it is possible to measure deformations and deflections of truss railway bridges through load tests under operational train conditions without traffic control, enabling the calculation of response factors for stress adjustments.

• FLOWER RESEARCH JOURNAL
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• v.18 no.3
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• pp.186-192
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• 2010

An infrared heating system, installed in a small venlo-type glasshouse ($280m^2$) in Gyeongsang National University, Jinju, Korea, was used to investigate its heating effect with potted Phalaenopsis, Schefflera arboricola 'Hongkong', Ficus elastica 'Variegata', and Rosa hybrida 'Yellow King' as the test plants. Temperature changes in test plants with the system turned 'On' and 'Off' were measured by using an infrared camera and the consumption of electricity by this infrared heating system was measured and analyzed. In potted Phalaenopsis, when the set air temperature of the greenhouse was $18^{\circ}C$, temperature of leaves and the growing medium were $22.8{\sim}27^{\circ}C$ and $21.3{\sim}24.3^{\circ}C$, respectively. In such tall plants as Schefflera arboricola 'Hongkong' and Ficus elastica 'Variegata', the upper part showed the highest temperature of 24.0 and $26.9^{\circ}C$, respectively. From the results of temperature change measurements, the plant temperatures were near or above the set point temperatures with some fluctuations depending on the position or distance from the infrared heating system. When air temperature between night and dawn dropped sharply, plant temperatures were maintained close to the set temperature ($18^{\circ}C$). There was a significant difference between 'On' and 'Off' states of the infrared heating system in average temperatures of root zone and leaf: 21.8 and $17.8^{\circ}C$ with the system 'On' and 20.4 and $15.5^{\circ}C$ with the system 'Off', respectively, in a cut rose Rosa hybrida 'Yellow King'. The heating load was about $24,850{\sim}35,830kcal{\cdot}h^{-1}$, which comes to about 27,000~40,000 won in Korean currency when calculated in terms of the cost of heating by a hot water heating system heated by petroleum. The cost for heating by the infrared heating system was about 35% of that of a hot water heating system. With the infrared heating system, the air temperature during the night was maintained slightly lower than the set point air temperature, probably due to the lack of air tightness of the glasshouse. Therefore, glasshouses with an infrared heating system requires further investigation including the installation space of the heat-emitting units, temperature sensor positions, and convection.

• Korean Journal of Agricultural and Forest Meteorology
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• v.23 no.4
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• pp.329-339
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• 2021

Soybeans (Glycine max), one of major upland crops, require precise management of environmental conditions, such as temperature, water, and soil, during cultivation since they are sensitive to environmental changes. Application of spectral technologies that measure the physiological state of crops remotely has great potential for improving quality and productivity of the soybean by estimating yields, physiological stresses, and diseases. In this study, we developed and validated a soybean growth prediction model using multispectral imagery. We conducted a linear regression analysis between vegetation indices and soybean growth data (fresh weight and LAI) obtained at Miryang fields. The linear regression model was validated at Goesan fields. It was found that the model based on green ratio vegetation index (GRVI) had the greatest performance in prediction of fresh weight at the calibration stage (R²=0.74, RMSE=246 g/m², RE=34.2%). In the validation stage, RMSE and RE of the model were 392 g/m² and 32%, respectively. The errors of the model differed by cropping system, For example, RMSE and RE of model in single crop fields were 315 g/m² and 26%, respectively. On the other hand, the model had greater values of RMSE (381 g/m²) and RE (31%) in double crop fields. As a result of developing models for predicting a fresh weight into two years (2018+2020) with similar accumulated temperature (AT) in three years and a single year (2019) that was different from that AT, the prediction performance of a single year model was better than a two years model. Consequently, compared with those models divided by AT and a three years model, RMSE of a single crop fields were improved by about 29.1%. However, those of double crop fields decreased by about 19.6%. When environmental factors are used along with, spectral data, the reliability of soybean growth prediction can be achieved various environmental conditions.