• Journal of the Korean GEO-environmental Society
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• v.20 no.9
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• pp.5-11
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• 2019

Recently, ground collapse in urban area has been widely paid attention as it frequently happens. To investigate the causes and suggest the measurements, many researches such as ground exploration from GPR, mock test and numerical simulations have been conducted. The proposed risk evaluation chart recently focuses only on the current ground status and is not capable of forecasting the ground collapse. This paper presents the prediction method of ground collapse using the numerical simulations of 30 cases considering void size and ground height as variables. It finally provides the charts that can analyze quantitatively the ground collapse.

• International Journal of Naval Architecture and Ocean Engineering
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• v.11 no.1
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• pp.143-153
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• 2019

In this study, numerical simulations for the prediction of added resistance for KVLCC2 with varying wave steepness are performed using a Computational Fluid Dynamics (CFD) method and a 3-D linear potential method, and then the non-linearities of added resistance and ship motions are investigated in regular short and long waves. Firstly, grid convergence tests in short and long waves are carried out to establish an optimal mesh system for CFD simulations. Secondly, numerical simulations are performed to predict ship added resistance and vertical motion responses in short and long waves and the results are verified using the available experimental data. Finally, the non-linearities of added resistance and ship motions with unsteady wave patterns in the time domain are investigated with the increase in wave steepness in both short and long waves. The present systematic study demonstrates that the numerical results have a reasonable agreement with the experimental data and emphasizes the non-linearity in the prediction of the added resistance and the ship motions with the increasing wave steepness in short and long waves.

• Proceedings of the Korea Water Resources Association Conference
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• 2001.05b
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• pp.1224-1229
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• 2001

• Proceedings of the Korean Society of Fisheries Technology Conference
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• 1994.06c
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• pp.45-45
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• 1994

• 한국항공운항학회:학술대회논문집
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• 2007.06a
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• pp.13-17
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• 2007

• 한국전산유체공학회:학술대회논문집
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• 2008.03b
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• pp.80-83
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• 2008

The characteristics of the spread of a forest fire are generally related to the attributes of combustibles, geographical features, and meteorological conditions, such as wind conditions. The most common methodology used to create a prediction model for the spread of forest fires, based on the numerical analysis of the development stages of a forest fire, is an analysis of heat energy transmission by the stage of heat transmission. When a forest fire breaks out, the analysis of the transmission velocity of heat energy is quantifiable by the spread velocity of flame movement through a physical and chemical analysis at every stage of the fire development from flame production and heat transmission to its termination. In this study, the formula used for the 1-dimensional surface forest fire behavior prediction model, derived from a numerical analysis of the surface flame spread rate of solid combustibles, is introduced. The formula for the 1-dimensional surface forest fire behavior prediction model is the estimated equation of the flame spread velocity, depending on the condition of wind velocity on the ground. Experimental and theoretical equations on flame duration, flame height, flame temperature, ignition temperature of surface fuels, etc., has been applied to the device of this formula. As a result of a comparison between the ROS(rate of spread) from this formula and ROSs from various equations of other models or experimental values, a trend suggesting an increasing curved line of the exponent function under 3m/s or less wind velocity condition was identified. As a result of a comparison between experimental values and numerically analyzed values for fallen pine tree leaves, the flame spread velocity reveals has a error of less than 20%.

• Journal of Ocean Engineering and Technology
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• v.35 no.4
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• pp.273-286
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• 2021

In recent years, as human casualties and property damage caused by hazardous waves have increased in the East Sea, precise wave prediction skills have become necessary. In this study, the Simulating WAves Nearshore (SWAN) third-generation numerical wave model was calibrated and optimized to enhance the accuracy of winter storm wave prediction in the East Sea. We used Source Term 6 (ST6) and physical observations from a large-scale experiment conducted in Australia and compared its results to Komen's formula, a default in SWAN. As input wind data, we used Korean Meteorological Agency's (KMA's) operational meteorological model called Regional Data Assimilation and Prediction System (RDAPS), the European Centre for Medium Range Weather Forecasts' newest 5th generation re-analysis data (ERA5), and Japanese Meteorological Agency's (JMA's) meso-scale forecasting data. We analyzed the accuracy of each model's results by comparing them to observation data. For quantitative analysis and assessment, the observed wave data for 6 locations from KMA and Korea Hydrographic and Oceanographic Agency (KHOA) were used, and statistical analysis was conducted to assess model accuracy. As a result, ST6 models had a smaller root mean square error and higher correlation coefficient than the default model in significant wave height prediction. However, for peak wave period simulation, the results were incoherent among each model and location. In simulations with different wind data, the simulation using ERA5 for input wind datashowed the most accurate results overall but underestimated the wave height in predicting high wave events compared to the simulation using RDAPS and JMA meso-scale model. In addition, it showed that the spatial resolution of wind plays a more significant role in predicting high wave events. Nevertheless, the numerical model optimized in this study highlighted some limitations in predicting high waves that rise rapidly in time caused by meteorological events. This suggests that further research is necessary to enhance the accuracy of wave prediction in various climate conditions, such as extreme weather.

• Journal of the Korean Society of Manufacturing Technology Engineers
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• v.18 no.3
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• pp.315-320
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• 2009

The purpose of this study is to predict the roundness of Numerical Control Machining so that helps the operator to choose the right machining conditions to produce a product within the given error limits. Learning of neural network is Backpropagation theory. From this study, the base was set to setup the database to produce precisely machined product by predicting the rate of error in the fabrication facility which does not have the environment to analyze it.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.65 no.5
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• pp.851-856
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• 2016

Wind speed is heavily fluctuated and quite local than other weather elements. It is difficult to improve the accuracy of prediction only in a numerical prediction model. An MOS (Model Output Statistics) technique is used to correct the systematic errors of the model using a statistical data analysis. The Most of previous MOS has used a linear regression model for weather prediction, but it is hard to manage an irregular nature of prediction of wind speed. In order to solve the problem, a nonlinear regression method using SVR (Support Vector Regression) is introduced for a development of MOS for wind speed prediction. Experiments are performed for KLAPS (Korea Local Analysis and Prediction System) re-analysis data from 2007 to 2013 year for Jeju Island and Busan area in South Korea. The MLR and SVR based linear and nonlinear methods are compared to each other for prediction accuracy of wind speed. Also, the comparison experiments are executed for the variation in the number of UM elements.

• Ecology and Resilient Infrastructure
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• v.7 no.3
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• pp.218-226
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• 2020

This study investigated that the numerical experiment for analysis on free overtopping flow by a weir of levee type, as the first stage of the development of a numerical technique for prediction methodology based on a numerical model. Using 2-dimensional flow models, Nays2DH, we conducted numerical simulations based on existing experimental data to compare and verify the models. We firstly discussed the numerical reproducibility for the discontinued flow by weir shape, and calibrated the computational flow through preprocessing of channel bed. Further, we carried out and compared the simulations for prediction on the overtopping flow by the number of weir gates. As a result of simulations, we found that the maximum flow velocity of downstream of weir increases when the number of weir gates increases under the same cross sectional area of flow. Through such results, this study could present basic data for hydraulic research to consider the water flow and sediment transport depending on weir operation in the future work.