• Journal of Environmental Impact Assessment
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• v.20 no.3
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• pp.397-409
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• 2011

This study was carried out for improving the effectiveness of water resources development project through local resident opinions in the environmental impact assessment(EIA). The EIA reports of seven dams were examined. Four dams -Youngju Dam, Seongduck Dam, Buhang Dam and Hantangang Dam- which included many local opinions including 470 opinions of 341 local residents were selected to be analyzed. Local residents submitted their opinions in the six fields which are meteorological phenomena, water quality, land use, fauna and flora, noise and vibration, and residence, and the major opinions of those opinions came from the atmosphere environment field which is 32% of total opinions and social and economic field which is 38% of total opinions, respectively. In submerged area, opinions of the measure for migration and compensation were 91% and in non-submerged area, opinions of the measure for meteorological phenomena was 86%. Those percentages were maximum in each area. Opinions concerned meteorological phenomena were 86% and 53% in Youngju Dam and Seongduck Dam where area is surrounded by existing dam, but there was only 9% and 0% of opinions in Buhang Dam and Hantangang Dam where area is without existing dam nearby. The reformation methods which reflected the resident's opinions were suggested on EIA in dam development projects. First of all, reliability and objectivity of the field of meteorological phenoma should be enhanced by scientific prediction of the phenomenon days. Secondly, techniques reducing uncertainty of various water quality prediction models ought to be developed and effectiveness of the reduction strategies in environmental impact should be quantified. Finally, the draft of EIA report should involve the detailed plans of migration and compensation's procedures, criteria and measures to support.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.30 no.6A
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• pp.543-560
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• 2010

Safety-related concrete structures in a nuclear power plant must be protected against the impact of flying objects, referred to in the profession as missiles. In practice, the structural verification is usually carried out by means of empirical formulas, which relate the velocity of the impinging missile to the wall thickness needed to prevent scabbing or perforation. The purpose of this study is to reevaluate the predictability of the local effect prediction formulas for the penetration and scabbing depths and perforation thickness. Therefore, available formulas for predicting the penetration depth, scabbing thickness, and perforation thickness of concrete structures impacted by solid missiles are summarized, reviewed, and compared. A series of impact analyses is performed to predict the local effects of the projectile at impact velocities varing from 95 to 215 m/s. The results obtained from the numerical simulations have been compared with tests that were carried out at Kojima to validate numerical modelling. The simulation results show reasonable agreement with the Kojima test results for the overall impact response of the RC slabs. From these results, it seems that the Degen equation give a very good estimate of perforation thickness against a tornado projectile for test data. Finally, the results obtained from the impact analysis have been compared with Degen formula to determine the perforation thickness of the RC slab.

• Journal of information and communication convergence engineering
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• v.21 no.4
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• pp.346-350
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• 2023

Trajectory prediction is an essential element for driving autonomous vehicles, and various trajectory prediction models have emerged with the development of deep learning technology. Convolutional neural network (CNN) is the most commonly used neural network architecture for extracting the features of visual images, and the latest models exhibit high performances. This study was conducted to identify an efficient CNN backbone model among the components of deep learning models for trajectory prediction. We changed the existing CNN backbone network of multiple-trajectory prediction models used as feature extractors to various state-of-the-art CNN models. The experiment was conducted using nuScenes, which is a dataset used for the development of autonomous vehicles. The results of each model were compared using frequently used evaluation metrics for trajectory prediction. Analyzing the impact of the backbone can improve the performance of the trajectory prediction task. Investigating the influence of the backbone on multiple deep learning models can be a future challenge.

• Ocean Systems Engineering
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• v.11 no.1
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• pp.43-58
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• 2021

In the present work, a 3D numerical model is proposed to study local scouring around single vertical piers with different cross-section shapes under steady-current flow. The model solves the flow field and sediment transport processes using a coupled approach. The flow field is obtained by solving the Unsteady Reynolds Averaged Navier-Stokes (URANS) equations in combination with the k-ω SST turbulence closure model and the sediment transport is considered using both bedload and suspended load models. The proposed model is validated against the empirical measurements of local scour around single vertical piers with circular, square, and diamond cross-section shapes obtained from the literature. The measurement of scour depth in equilibrium condition for the simulations reveal the differences of 4.6%, 6.7% and 13.1% from the experimental measurements for the circular, square, and diamond pier cases, respectively. The model displayed a remarkable performance in the prediction of scour around circular and square piers where horseshoe vortices (HSVs) have a leading impact on scour progression. On the other hand, the maximum deviation was found in the case of the diamond pier where HSVs are weak and have minimum impact on the formation of local scour. Overall, the results confirm that the prediction capability of the present model is almost independent of the strength of the formed HSVs and pier cross-section shapes.

• Atmosphere
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• v.33 no.5
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• pp.457-475
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• 2023

Accurately predicting localized heavy rainfall is challenging without high-resolution mesoscale cloud information in the numerical model's initial field, as precipitation intensity and amount vary significantly across regions. In the Korean Peninsula, the radar observation network covers the entire country, providing high-resolution data on hydrometeors which is suitable for data assimilation (DA). During the pre-processing stage, radar reflectivity is classified into hydrometeors (e.g., rain, snow, graupel) using the background temperature field. The mixing ratio of each hydrometeor is converted and inputted into a numerical model. Moreover, assimilating saturated water vapor mixing ratio and decomposing radar radial velocity into a three-dimensional wind vector improves the atmospheric dynamic field. This study presents radar DA experiments using a numerical prediction model to enhance the wind, water vapor, and hydrometeor mixing ratio information. The impact of radar DA on precipitation prediction is analyzed separately for each radar component. Assimilating radial velocity improves the dynamic field, while assimilating hydrometeor mixing ratio reduces the spin-up period in cloud microphysical processes, simulating initial precipitation growth. Assimilating water vapor mixing ratio further captures a moist atmospheric environment, maintaining continuous growth of hydrometeors, resulting in concentrated heavy rainfall. Overall, the radar DA experiment showed a 32.78% improvement in precipitation forecast accuracy compared to experiments without DA across four cases. Further research in related fields is necessary to improve predictions of mesoscale heavy rainfall in South Korea, mitigating its impact on human life and property.

• Journal of the Society of Naval Architects of Korea
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• v.42 no.4 s.142
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• pp.350-356
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• 2005

Prediction of green water loads acting on the bow deck is au essential part for the design of bow structures against the green water impact. Proper technique of the green water simulation is highly required for the prediction of green water loads. in this paper, the green water flow on bow deck is simulated by FDM(finite difference method). Using the results of green water simulation, impact load on bow deck is calculated. Also, experiments are carried out to compare with the numerical calculation. Through the comparisons between experimental results and numerical results, it is verified that the present numerical tool is adequate as a practical calculation tool for the green water problem.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2002.11b
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• pp.541-546
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• 2002

Railway noise is one of the main causes of environmental impact. Whenever a new railway line is planned or a housing project near an existing railway is proposed, an estimate of the relevant levels is usually required. For this, it is necessary to quantify those parameters that affect the railway noise. Therefore we investigated the noise and vibration level which 107 high speed trains generated passing through the block of test railway track between Chunan and Chungwon. This paper presents the status and characteristics of the high speed railway noise and an accurate prediction of the high speed railway noise.

• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.14 no.11
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• pp.1161-1165
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• 2004

Railway noise Is one of the main causes of environmental impact. Whenever a new railway line is planned or a housing project near an existing railway is proposed, an estimate of the relevant noise levels is usually required. For this, it is necessary to quantify those parameters that affect the railway noise. Therefore we investigated the noise level which 107 high speed trains generated passing through the block of test railway track between Chunan and Chungwon. This paper shows the status and characteristics of the high speed rallway noise and an accurate prediction of the high speed railway noise.

• Journal of Environmental Impact Assessment
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• v.19 no.6
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• pp.553-561
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• 2010

Railway noise barrier is generally used with welding of joint rail for railway noise reduction in our country. In this study, method for performance evaluation of railway noise barrier using insertion loss was suggested in case of without having noise measurement results before barrier installation. For this, railway noise measurements were performed in commercial high-speed railway site which has railway noise barrier. As a noise level before noise barrier installation, predicted noise level were used. From this method the performance evaluation for railway noise barrier were performed accurately and efficiently.

• Journal of Environmental Impact Assessment
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• v.20 no.4
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• pp.435-442
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• 2011

In this study, a regression model was developed for prediction of inflow temperature to support an effective thermal stratification simulation of Yongdam Reservoir, using the relationship between gaged inflow temperature and air temperature. The effect of reproductability for thermal stratification was evaluated using EFDC model by gaged vertical profile data of water temperature(from June to December in 2005) and ex-developed regression models. Therefore, in the development process, the coefficient of correlation and determination are 0.96 and 0.922, respectively. Moreover, the developed model showed good performance in reproducing the reservoir thermal stratification. Results of this research can be a role to provide a base for building of prediction model for water quality management in near future.