• Tribology and Lubricants
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• v.35 no.1
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• pp.16-23
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• 2019

In this study, we aim to analyze the effects of both contact layer properties and surface roughness on contact resistance. The contact has a great influence on performance in terms of electrical conduction and heat transfer. The two biggest factors determining contact resistance are the presence of surface roughness and the surface layer. For this reason we calculated the contact resistance by considering both factors simultaneously. The model of this study to calculate contact resistance is as follows. First, the three representative surface parameters for the GW model are obtained by Nayak's random process. Then, the apparent contact area, real contact area, and contact number of asperities are calculated using the GW model with the surface parameters. The contact resistance of a single surface layer is calculated using Mikic's constriction equation. The total contact resistance is approximated by the parallel connection between the same asperity contact resistances. The results of this study are as follows. The appropriate thickness with reduction effect for contact resistance is determined according to the difference in conductivity between the base layer and surface layer. It was confirmed that the standard deviation of surface roughness has the greatest influence on surface roughness parameters. The results of this study will be useful for selecting the surface material and surface roughness when the design considering the contact resistance is needed.

• Proceedings of the Korean Magnestics Society Conference
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• 2015.11a
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• pp.155-155
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• 2015

• KOREAN JOURNAL OF CROP SCIENCE
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• v.55 no.4
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• pp.275-283
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• 2010

This experiment was conducted to construct process models to estimate grain weight (GW) and grain nitrogen content (GN) in rice. A model was developed to describe the dynamic pattern of GW and GN during grain-filling period considering their relationships with temperature, solar radiation and growth traits such as LAI, shoot dry-weight, shoot nitrogen content, grain number during grain filling. Firstly, maximum grain weight (GWmax) and maximum grain nitrogen content (GNmax) equation was formulated in relation to Accumulated effective temperature (AET) ${\times}$ Accumulated radiation (AR) using boundary line analysis. Secondly, GW and GN equation were created by relating the difference between GW and GWmax and the difference between GN and GNmax, respectively, with growth traits. Considering the statistics such as coefficient of determination and relative root mean square of error and number of predictor variables, appropriate models for GW and GN were selected. Model for GW includes GWmax determined by AET ${\times}$ AR, shoot dry weight and grain number per unit land area as predictor variables while model for GN includes GNmax determined by AET ${\times}$ AR, shoot N content and grain number per unit land area. These models could explain the variations of GW and GN caused not only by variations of temperature and solar radiation but also by variations of growth traits due to different sowing date, nitrogen fertilization amount and row spacing with relatively high accuracy.

• Journal of Korea Port Economic Association
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• v.33 no.2
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• pp.83-96
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• 2017

As a way to address global warming, among the renewable energy sources, there have been heavy investments worldwide for the development of offshore wind farms. However, such development has a drawback: investment costs are higher than those for onshore wind farms due to required operations such as offshore transportation and installation. In particular, delays in installation due to adverse maritime weather conditions are factors that affect the economics of offshore wind farms' operation. Therefore, in this study, we analyze the optimal schedule of the construction of an offshore wind farm from a macro perspective by considering the weather conditions in Korea. For this purpose, we develop a mathematical model and apply it to a 2.5 GW offshore wind farm project on the southwestern coast of the country. We use data from the Korea Meteorological Agency for maritime weather conditions and attempt to reflect the actual input data based on precedent cases overseas. The results show that it takes 6 months to install 35 offshore wind turbines. More specifically, it is pointed out that it is possible to minimize costs by not working in winter.

• Journal of Korean Society on Water Environment
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• v.28 no.4
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• pp.595-600
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• 2012

This study is to assess the application of SWAT-CUP(Soil and Water Assessment Tool-Calibration Uncertainty Programs) and to extend daily flow data from 8-day interval flow data which has been measured by Korean Ministry of Environment(MOE). Model sensitivity analysis and calibration were performed with sequential uncertainty fitting(SUIF-2), which is one of the programs interfaced with SWAT, in the package SWAT-CUP. The most sensitive parameters were SOL_K.sol, CH_N2.rte, CN2.mgt, SOL_BD.sol, ALPHA_BF.gw, ALPHA_BNK.rte, SOL_AWC.sol, CH_K2.rte, SFTMP.bsn, GW_DELAY.gw. Following the sensitivity analysis, SWAT-CUP calibration was carried out using 8-day interval flow data from January 2008 to December 2010. The results were then assessed based on the visual agreement and simulated flow plots and the performance statistics generated $R^2$ and NSE which are 0.71 and 0.61 respectively. Results of these statistics indicated that there was a good agreement between the observed and simulated flow. To extend daily flow data from 8-day interval flow data, parameters, which were estimated by SWAT-CUP, re-entered for SWAT model. As a result, the observed flow data were found to reflect the trend of simulated flow data. From these results, it is thought that this method could be used to provide daily flow data using 8-day interval flow data.

• ETRI Journal
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• v.38 no.3
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• pp.510-517
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• 2016

Recent developments in the field of separation of mixed signals into music/voice components have attracted the attention of many researchers. Recently, iterative kernel back-fitting, also known as kernel additive modeling, was proposed to achieve good results for music/voice separation. To obtain minimum mean square error (MMSE) estimates of short-time Fourier transforms of sources, generalized spatial Wiener filtering (GW) is typically used. In this paper, we propose an advanced music/voice separation method that utilizes a generalized weighted ${\beta}$-order MMSE estimation (WbE) based on iterative kernel back-fitting (KBF). In the proposed method, WbE is used for the step of mixed music signal separation, while KBF permits kernel spectrogram model fitting at each iteration. Experimental results show that the proposed method achieves better separation performance than GW and existing Bayesian estimators.

• Korean Journal of Remote Sensing
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• v.38 no.6_1
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• pp.1527-1539
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• 2022

As coastal erosion of the east coast is accelerating, the need for scientific and quantitative coastal erosion monitoring technology for a wide area increases. The traditional method for observing changes in the coast was precision monitoring based on field surveys, but it can only be applied to a small area. The airborne bathymetric Light Detection And Ranging (LiDAR) system is a technology that enables economical surveying of coastal and seabed topography in a wide area. In particular, it has the advantage of constructing topographical data for the intertidal zone, which is a major area of interest for coastal erosion monitoring. In this study, time series analysis of coastal seabed topography acquired in Aug, 2021 and Mar. 2022 on the littoral cell GW36 in Gangwon was performed using the Seahawk Airborne Bathymetric LiDAR (ABL) system. We quantitatively monitored the topographical changes by measuring the baseline length, shoreline and Digital Terrain Model (DTM) changes. Through this, the effectiveness of the ABL surveying technique was confirmed in coastal erosion monitoring.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.12 no.4
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• pp.1553-1571
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• 2018

Currently, many of schemes for smart grid data aggregation are based on a one-level gateway (GW) topology. Since the data aggregation granularity in this topology is too single, the control center (CC) is unable to obtain more fine-grained data aggregation results for better monitoring smart grid. To improve this issue, Shen et al. propose an efficient privacy-preserving cube-data aggregation scheme in which the system model consists of two-level GW. However, a risk exists in their scheme that attacker could forge the signature by using leaked signing keys. In this paper, we propose a secure and fine-grained electricity consumption aggregation scheme for smart grid, which employs the homomorphic encryption to implement privacy-preserving aggregation of users' electricity consumption in the two-level GW smart grid. In our scheme, CC can achieve a flexible electricity regulation by obtaining data aggregation results of various granularities. In addition, our scheme uses the forward-secure signature with backward-secure detection (FSBD) technique to ensure the forward-backward secrecy of the signing keys. Security analysis and experimental results demonstrate that the proposed scheme can achieve forward-backward security of user's electricity consumption signature. Compared with related schemes, our scheme is more secure and efficient.

• Journal of Energy Engineering
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• v.24 no.3
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• pp.74-81
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• 2015

Currently, the government is encouraging the introduction of energy storage system to reduce carbon emissions and peak power demand. The government is planning the cumulative capacity of ESS of 2GW in 2020. By utilizing charge and discharge of the ESS, it is possible to sell the surplus power to utility and electricity market. This paper suggests the model that economic feasibility of energy storage system for planning the construction of power generation facilities in 2035. Our results of simulation indicate the energy storage plan of utility for constructing renewable energy facilities is need to incentives from the government to encourage power utilities and expansion of ESS.

• Tribology and Lubricants
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• v.34 no.1
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• pp.23-32
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• 2018

Coupling is a mechanical component that transmits rotational force by connecting two shafts. Curvic coupling is widely used in high-performance systems because of its excellent power transmission efficiency and easy machining. However, coupling applications change dynamic behavior by reducing the stiffness of an entire system. Contact surface stiffness is an important parameter that determines the dynamic behavior of a system. In addition, the roughness profile of a contact surface is the most important parameter for obtaining contact stiffness. In this study, we theoretically establish the process of contact and bending stiffness analysis by considering the rough surface contact at Curvic coupling. Surface roughness parameters are obtained from Nayak's random process, and the normal contact stiffness of a contact surface is calculated using the Greenwood and Williamson model in the elastic region and the Jackson and Green model in the elastic-plastic region. The shape of the Curvic coupling contact surface is obtained by modeling a machined shape through an actual machining tool. Based on this modeling, we find the maximum number of gear teeth that can be machined according to the contact angle. Curvic coupling stiffness is calculated by considering the contact angle, and the calculation process is divided into stick and slip conditions. Based on this process, we investigate the stiffness characteristics according to the contact angle.