• Proceedings of the Korea Committee for Ocean Resources and Engineering Conference
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• 2001.05a
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• pp.186-195
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• 2001

The purpose of this study is to develop the time-dependent, one-dimensional numerical model on the interaction between irregular waves and two-layer permeable coastal structures, by extending and modifying the numerical model PBREAK(Wurjanto and Kobayashi, 1992) which is applicable only to one-layer permeable coastal structures. The two-layer permeable coastal structure consists of two permeable underlayers with different permeable media resting on an impermeable slope and an armor layer covering the permeable underlayer. The numerical model of this study simulates the wave over rough permeable underlayer of arbitrary geometry as well as the waves inside two-permeable underlayers of arbitrary thickness for specified normally-incident irregular waves. The utility of the numerical model is founded from comparing with PBREAK and the four hydraulic model tests under irregular waves. The sensitivities of computed results according to typical parameters(porosity, stone diameter, horizontal width of the permeable underlayer) and major factors(friction factor of primary armor layer etc.) discussed.

• Korean Chemical Engineering Research
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• v.43 no.2
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• pp.278-285
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• 2005

In the present work, a reaction of sulfur removal and simulation of desulfurization based on the grain model and two-phase theory were studied using natural manganese ore (NMO) as a sorbent in a continuous fluidized bed reactor. The effect of desulfurization was investigated through the grain model considered the change of pore structure as a function of desulfurization time, particle size of NMO, and diffusion velocity of $SO_2$ in the pores. Among these parameters, the diffusion of $SO_2$ in the pores of NMO was the most important factor. Moreover, the reaction of sulfur removal and desulfurization in a continuous fluidized bed reactor using NMO as a sorbent could be well predict through the grain model and two-phase theory, respectively.

• Journal of Electrical Engineering and Technology
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• v.13 no.4
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• pp.1759-1768
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• 2018

The energy density, power density and ohm resistance of battery change significantly as results of battery aging, which lead to decrease in the accuracy of the equivalent model. A parameter identification method of the equivale6nt circuit model with 3 R-C branches based on the test database of battery life cycle is proposed in this paper. This database is built on the basis of experiments such as updating of available capacity, charging and discharging tests at different rates and relaxation characteristics tests. It can realize regular update and calibration of key parameters like SOH, so as to ensure the reliability of parameters identified. Taking SOH, SOC and T as independent variables, lookup table method is adopted to set initial value for the parameter matrix. Meanwhile, in order to ensure the validity of the model, the least square method based on variable forgetting factor is adopted for optimizing to complete the identification of equivalent model parameters. By comparing the simulation data with measured data for charging and discharging experiments of Li-ion battery, the effectiveness of the full life cycle database and the model are verified.

• Journal of Korean Society of Water and Wastewater
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• v.20 no.2
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• pp.187-196
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• 2006

Forecasting the long-term water demand is important in the plan of water supply system because the location and capacity of water facilities are decided according to it. To forecast the long-term water demand, the existing method based on lpcd and population has been usually used. But, these days the trend among the variation of water demand has been disappeared, so expressing other variation of it is needed to forecast correct water demand. To accomplish it, we introduced the System Dynamics method to consider total connections of water demand factor. Firstly, the factors connected with water demand were divided into three sectors(water demand, industry, and population sectors), and the connections of factors were set with multiple regression model. And it was compared to existing method. The results are as followings. The correlation efficients are 0.330 in existing model and 0.960 in SD model and MAE are 3.96% in existing model and 1.68% in SD model. So, it is proved that SD model is superior to the existing model. To forecast the long-term water demand, scenarios were made with variations of employment condition, economic condition and consumer price indexes and forecasted water demands in 2012. After all scenarios were performed, the results showed that it was not needed to increase the water supply ability in Seoul.

• Smart Structures and Systems
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• v.7 no.4
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• pp.263-274
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• 2011

A reliability-based slope stability assessment method considering fluctuations in the monitored matric suction was proposed for real-time identification of slope risk. The assessment model was based on the limit equilibrium model for infinite slope failure. The first-order reliability method (FORM) was adopted to calculate the probability of slope failure, and results of the model were compared with Monte-Carlo Simulation (MCS) results to validate the accuracy and efficiency of the model. The analysis shows that a model based on Advanced First-Order Reliability Method (AFORM) generates results that are in relatively good agreement with those of the MCS, using a relatively small number of function calls. The contribution of random variables to the slope reliability index was also examined using sensitivity analysis. The results of sensitivity analysis indicate that the effective cohesion c' is a significant variable at low values of mean matric suction, whereas matric suction ($u_a-u_w$) is the most influential factor at high mean suction values. Finally, the reliability indices of an unsaturated model soil slope, which was monitored by a wireless matric suction measurement system, were illustrated as 2D images using the suggested probabilistic model.

• Journal of The Korean Society of Agricultural Engineers
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• v.61 no.1
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• pp.95-105
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• 2019

Evapotranpiration (ET) is one of the important factor in Hydrological cycle and irrigation planning. In this study, temperature-based artificial neural network (ANN) model for daily reference crop ET estimation was developed and compared with reference crop evapotranpiration ($ET_0$) from FAO-56 Penman-Monteith method (FAO-56 PM) and parameter regionalized Hargreaves method. The ANN model was trained and tested for 10 weather stations (5 inland stations and 5 costal stations) and two input climate factors, maximum temperature ($T_{max}$), minimum temperature ($T_{min}$), and extraterrestrial radiation (RA) were used for training and validation of temperature-based ANN model. Monthly reference ET by the ANN model also compared with parameter regionalized Hargreaves method for ANN model applicability evaluation. The ANN model evapotranspiration demonstrated more accordance to FAO-56 PM evapotranspiration than the $ET_0$ from parameter regionalized Hargreaves method(R-Hargreaves). The results of this study proposed that daily reference crop ET estimated by the ANN model could be used in the condition of no sufficient climate data.

• Structural Engineering and Mechanics
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• v.89 no.1
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• pp.77-91
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• 2024

During strong seismic events, inelastic shear deformation occurs in beam-column joints. To capture inelastic shear deformation, an analytical model for beam-column joint in reinforced concrete (RC) frame structures has been proposed in this study. The proposed model has been developed using a rotational spring and rigid links. The stiffness properties of the rotational spring element have been assigned in terms of a moment rotation curve developed from the shear stress-strain backbone curve. The inelastic rotation behavior of joint has been categorized in three stages viz. cracking, yielding and ultimate. The joint shear stress and strain values at these stages have been estimated using analytical models and experimental database respectively. The stiffness properties of joint rotational spring have been modified by incorporating a geometry factor based on dimensions of adjoining beam and column members. The hysteretic response of the joint rotational spring has been defined by a pivot hysteresis model. The response of the proposed analytical model has been verified initially at the component level and later at the structural level with the two actually tested RC frame structures. The proposed joint model effectively emulates the inelastic behavior precisely with the experimental results at component as well as at structural levels.

• Journal of Korea Water Resources Association
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• v.39 no.8 s.169
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• pp.677-690
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• 2006

The LH-OAT (Latin Hypercube One factor At a Time) method for sensitivity analysis and SCE-UA (Shuffled Complex Evolution at University of Arizona) optimization method were applied for the automatic calibration of SWAT model in Bocheong-cheon watershed. The LH-OAT method which combines the advantages of global and local sensitivity analysis effectively identified the sensitivity ranking for the parameters of SWAT model over feasible parameter space. Use of this information allows us to select the calibrated parameters for the automatic calibration process. The performance of the automatic calibration of SWAT model using SCE-UA method depends on the length of calibration period, the number of calibrated parameters, and the selection of statistical error criteria. The performance of SWAT model in terms of RMSE (Root Mean Square Error), NSEF (Nash-Sutcliffe Model Efficiency), RMAE (Relative Mean Absolute Error), and NMSE (Normalized Mean Square Error) becomes better as the calibration period and the number of parameters defined in the automatic calibration process increase. However, NAE (Normalized Average Error) and SDR (Standard Deviation Ratio) were not improved although the calibration period and the number of calibrated parameters are increased. The result suggests that there are complex interactions among the calibration data, the calibrated parameters, and the model error criteria and a need for further study to understand these complex interactions at various representative watersheds.

• Journal of Korea Water Resources Association
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• v.44 no.7
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• pp.553-563
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• 2011

According to the improvement of computer's performance, the development of Geographic Information System (GIS), and the activation of offering information, a distributed model for analyzing runoff has been studied a lot in recently years. The distribution model is a theoretical and physical model computing runoff as making target basin subdivided parted. In the distributed model developed by this study, the volume of runoff at the surface flow is calculated on the basis of the parameter determined by landcover data and a two-dimensional diffusion wave equation. Most of existing runoff models compute velocity and discharge of flow by applying Manning-Strickler's mean velocity equation and Manning's roughness coefficient. Manning's roughness coefficient is not matched with dimension and ambiguous at computation; Nevertheless, it is widely used in because of its convenience for use. In order to improve those problems, this study developed the runoff model by applying not only Manning-Strickler's equation but also Chezy's mean velocity equation. Furthermore, this study introduced a power law of exponential friction factor expressed by the function of roughness height. The distributed model developed in this study is applied to 6 events of fan-shape basin, oblong shape test basin and Anseongcheon basin as real field conditions. As a result the model is found to be excellent in comparison with the exiting runoff models using for practical engineering application.

• The Journal of the Korea Contents Association
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• v.16 no.10
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• pp.382-392
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• 2016

This study organize a self-directed learning in complex structures. And based on this, It was developed self-directed learning scale for university students. It was a analyzing literature and reviewing previous studies for developed scale. Therefore, Self-directed learning model was configured into motives, performance behaviors, and learning management behaviors. On the basis of this, the present study constructed 19 sub-factors and developed 114 scale items. First, a preliminary scale was developed and its reliability was assessed by administering the scale to 128 students attending A university. The result showed that the reliability of every sub-factor was good and, therefore, the scale was developed with no item removed. To verify the validity of the scale, this study evaluated reliability and construct validity by administering the scale to 674 students going to A university. The reliability and validity of all sub-factors were found to be good. A confirmatory factor analysis was performed to verify construct validity and the result revealed that the first model was not an appropriate model. For this reason, the first model was modified once by taking the model modification index into account and it was found that ${\chi}^2$ (563.254), CFI=.963, NFI=.951, RMSEA=.064. Thus, the model was verified as a valid model. The results of this study imply that it is possible to point out learners' weaknesses and strengths by measuring activities taking place in the learning process in detail.