• KEPCO Journal on Electric Power and Energy
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• v.1 no.1
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• pp.33-38
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• 2015

Energy storage systems (ESSs) have been utilized widely in the world to optimize the power operation system and to improve the power quality. As lithium secondary batteries are the main power supplier for ESSs, it is very important to predict its cycle and power degradation behavior. In particular, the power, one of the hardest electrochemical properties to measure, needs lots of resources such as time and facilities. Due to these difficulties, computer modelling of lithium secondary batteries is applied to predict the DC-IR and power value during charging and discharging as a function of state of charge (SOC) by using pulse-based measurement methods. Moreover, based on the hybrid pulse power characteristics (HPPC) and J-Pulse (JEVS D 713, Japan Electric Vehicle Association Standards) methods, their electrochemical properties are also compared and discussed.

• Journal of Korean Society of Rural Planning
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• v.16 no.2
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• pp.47-55
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• 2010

Land cover and land use change data are important in many studies including climate change and hydrological studies. Although the various theories and models have been developed, it is difficult to identify the driving factors of the land use change because land use change is related to policy options and natural and socio-economic conditions. This study is to attempt to simulate the land cover change using the CLUE model based on a statistical analysis of land-use change. CLUE model has dynamic modeling tools from the competition among land use change in between driving force and land use, so that this model depends on statistical relations between land use change and driving factors. In this study, Yongin, Icheon and Anseong were selected for the study areas, and binary logistic regression and factor analysis were performed verifying with ROC curve. Land cover probability map was also prepared to compare with the land cover data and higher probability areas are well matched with the present land cover demonstrating CLUE model applicability.

• Proceedings of the Korean Vacuum Society Conference
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• 2010.02a
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• pp.464-464
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• 2010

A few years ago, for maintaining high stability and production yield of production equipment in a semiconductor fab, on-line monitoring of wafers is required, so that semiconductor manufacturers are investigating a software based process controlling scheme known as virtual metrology (VM). As semiconductor technology develops, the cost of fabrication tool/facility has reached its budget limit, and reducing metrology cost can obviously help to keep semiconductor manufacturing cost. By virtue of prediction, VM enables wafer-level control (or even down to site level), reduces within-lot variability, and increases process capability, $C_{pk}$. In this research, we have practiced VM on $SiO_2$ etch rate with optical emission spectroscopy(OES) data acquired in-situ while the process parameters are simultaneously correlated. To build process model of $SiO_2$ via, we first performed a series of etch runs according to the statistically designed experiment, called design of experiments (DOE). OES data are automatically logged with etch rate, and some OES spectra that correlated with $SiO_2$ etch rate is selected. Once the feature of OES data is selected, the preprocessed OES spectra is then used for in-situ sensor based VM modeling. ICP-RIE using 葰.56MHz, manufactured by Plasmart, Ltd. is employed in this experiment, and single fiber-optic attached for in-situ OES data acquisition. Before applying statistical feature selection, empirical feature selection of OES data is initially performed in order not to fall in a statistical misleading, which causes from random noise or large variation of insignificantly correlated responses with process itself. The accuracy of the proposed VM is still need to be developed in order to successfully replace the existing metrology, but it is no doubt that VM can support engineering decision of "go or not go" in the consecutive processing step.

• Transactions of Materials Processing
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• v.21 no.1
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• pp.49-57
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• 2012

It is difficult to estimate the properties of multilayered sheet because they are composed of one or more different materials. Plastic deformation behavior of the multilayered sheet is quite different as compared to each material individually. The deformation behavior of multilayered sheet should be investigated in order to prevent forming defects and to predict the properties of the formed part. In this study, the mechanical properties and formability of stainless steel-aluminum-magnesium multilayered sheet were investigated. The multilayered sheet needs to be deformed at an elevated temperature because of its poor formability at room temperature. Uniaxial tensile tests were performed at various temperatures and strain rates. Fracture patterns changed mainly at a temperature of $200^{\circ}C$. Uniform and total elongation of multilayered sheet increased to values greater than those of each material when deformed at $250^{\circ}C$. The limiting drawing ratio (LDR) was obtained using a circular cup deep drawing test to measure the formability of the multilayered sheet. A maximum value for the LDR of about 2 was achieved at $250^{\circ}C$, which is the appropriate forming temperature for the Mg alloy. Fracture patterns on a circular cup and thickness of formed part were predicted by a rigid-viscoplastic FEM analysis. Two kinds of modeling techniques were used to simulate deep drawing process of multilayered sheet. A single-layer FE-model, which combines the three different layers into a macroscopic single layer, predicted well the thickness distribution of the drawn cup. In contrast, the location and the time of fracture were estimated better with a multi-layer FE model, which used different material properties for each of the three layers.

• Transactions of Materials Processing
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• v.23 no.5
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• pp.289-296
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• 2014

Uniaxial tensile tests were conducted to accurately evaluate the in-plane mechanical properties of fiber metal laminates (FMLs). The FMLs in the current study are comprised of a layer of self-reinforced polypropylene (SRPP) sandwiched between two layers of aluminum alloy 5052-H34. The nonlinear tensile behavior of the FMLs under in-plane loading conditions was investigated using both numerical simulations and a theoretical analysis. The numerical simulation was based on finite element modeling using the ABAQUS/Explicit code and the theoretical constitutive model was based on the volume fraction approach using the rule of mixture and a modification of the classical lamination theory, which incorporates the elastic-plastic behavior of the aluminum alloy and the SRPP. The simulations and the model are used to predict the inplane mechanical properties such as stress-strain response and deformation behavior of the FMLs. In addition, a post-stretching process is used to reduce the thermal residual stresses before uniaxial tensile testing of the FMLs. Through comparison of both the numerical simulations and the theoretical analysis with the experimental results, it is concluded that the numerical simulation model and the theoretical approach can describe with sufficient accuracy the actual tensile stress-strain behavior of the FMLs.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.18 no.4
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• pp.260-266
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• 2017

The global economy, including Korea, has continuously searched for various market-friendly policies and new economic systems in pursuit of the forth industrial revolution. As a result, economic markets have grown, and factors affecting markets have diversified. Therefore, as for many company's decision makers, it has become an important issue to analyze and forecast markets accurately and effectively for rapid and appropriate decision making. In this study, we aim to improve the accuracy and validity of forecast models by applying extended information criteria in existing restricted information criteria to determine optimized modeling for the accurate analysis and prediction of complex market environments. In order to verify the practical use of the extended information criteria adopted in this study, we compare this study employing KOSPI data with previous studies. Experimental results show that applying extended information criteria is more accurate than using the existing information criteria.

• Journal of Korea Multimedia Society
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• v.3 no.2
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• pp.201-208
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• 2000

In this paper We describe an algorithm which is devised for 4he partition o# the input space and the generation of fuzzy rules by the fuzzy entropy and tested with the time series prediction problem using Mackey-Glass chaotic time series. This method divides the input space into several fuzzy regions and assigns a degree of each of the generated rules for the partitioned subspaces from the given data using the Shannon function and fuzzy entropy function generating the optimal knowledge base without the irrelevant rules. In this scheme the basic idea of the fuzzy neural network is to realize the fuzzy rules base and the process of reasoning by neural network and to make the corresponding parameters of the fuzzy control rules be adapted by the steepest descent algorithm. The Proposed algorithm has been naturally derived by means of the synergistic combination of the approximative approach and the descriptive approach. Each output of the rule's consequences has expressed with its connection weights in order to minimize the system parameters and reduce its complexities.

• Proceedings of the Korea Water Resources Association Conference
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• 2019.05a
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• pp.334-334
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• 2019

기후변화에 능동적으로 대처하기 위해서는 기후변화에 따른 수자원가용량의 변화를 정량적으로 평가할 수 있어야 한다. 평가결과의 신뢰도를 높이기 위해서 기후변화 시나리오는 지역기후 및 유역특성에 적합한 결과를 포함하여야 한다. 또한, 기후변화가 유역의 물순환계에 미치는 영향이 있다면, 물순환 개선 기술을 통해 지속가능한 유역 물환경을 구축하는 것이 필요하다. 유역 물순환 개선 기술은 기후변화가 진행 중에 있거나 예상되는 지역에 대하여 강우로부터 발생되는 유출을 지연, 저류, 침투시켜 지속가능한 물순환 체계를 유지하고 회복하도록 하는 기법이라 할 수 있다. 한국건설기술연구원에서는 기후변화에 따른 영향을 평가하고 적응 대책을 수립하기 위한 실무적인 유역 물순환 개선 및 평가 모형인 CAT3(Catchment hydrologic cycle Assessment Tool 3)을 개발하였으며 본 모형은 침투시설, 저류시설, 습지, 빗물저장시설과 같은 물순환 개선시설에 대한 효과를 정량적으로 평가할 수 있다. 본 연구에서는 팔당댐 상류의 경안천 유역을 대상으로 APCC 기후변화 시나리오 통계적 상세화 자료를 활용하여 물순환 개선 기술의 적용성을 평가하였다. 통계적 상세화 자료는 APCC에서 개발된 AIMS(APCC Integrated Modeling Solution) 플랫폼을 이용하였다. AIMS는 다양한 기후정보를 기반으로 사용자 관점에서 상세화를 수행할 수 있는 장점이 있다. 상세화 기법은 SDQDM(Spatial Disaggregation Quantile Delta Mapping) 방법을 이용하였다. 상세화된 기후자료는 과거자료의 재현성 및 미래 기간에 대한 왜곡도를 평가하기 위해 극한기후지수(Climate Index)를 이용하는데 본 연구에서는 장기간에 걸친 수자원가용량의 평가 및 예측을 위해 연강수량(PRCPTOT)을 사용하였으며 증발산량의 평가 및 예측에 영향을 미치는 온도 관련 극한기후지수는 평균기온 개념의 DTR(TMAX&TMIN)을 이용하였다. 통계적 상세화 과정을 통해 최종적으로 HadGEM2-CC, INMCM4, CanESM2 시나리오를 선택하였으며 각 시나리오별 물순환 개선 기술을 적용한 후 미래의 수문학적 변동성을 평가하였다.

• Journal of the Korean Society for Railway
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• v.16 no.3
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• pp.175-182
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• 2013

Rolling noise is an important source of noise from railways; it is caused by wheel and rail vibrations induced by acoustic roughness at the wheel/rail contact. To reduce rolling noise, it is necessary to have a reliable prediction model that can be used to investigate the effects of various parameters related to the rolling noise. This paper deals with modeling rolling noise from wheel and rail vibrations. In this study, the track is modeled as a discretely supported beam by regarding concrete slab tracks, and the wheel vibration is simulated by using the finite element method. The vertical and lateral wheel/rail contact forces are modeled using the linearized Hertzian contact theory, and then the vibration responses of the wheel and rail are calculated to predict the radiated noise. To validate the proposed model, a field measurement was carried out for a test vehicle. It was found that the predicted result agrees well with the measured one, showing similar behavior in the frequency range between 200 and 4000 Hz where the rolling noise is prominent.

• Nuclear Engineering and Technology
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• v.42 no.6
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• pp.656-661
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• 2010

Lead-alloys are very attractive nuclear coolants due to their thermo-hydraulic, chemical, and neutronic properties. By utilizing the HELIOS (Heavy Eutectic liquid metal Loop for Integral test of Operability and Safety of PEACER$^2$) facility, a thermal hydraulic benchmarking study has been conducted for the prediction of pressure loss in lead-alloy cooled advanced nuclear energy systems (LACANES). The loop has several complex components that cannot be readily characterized with available pressure loss correlations. Among these components is the core, composed of a vessel, a barrel, heaters separated by complex spacers, and the plenum. Due to the complex shape of the core, its pressure loss is comparable to that of the rest of the loop. Detailed CFD simulations employing different CFD codes are used to determine the pressure loss, and it is found that the spacers contribute to nearly 90 percent of the total pressure loss. In the system codes, spacers are usually accounted for; however, due to the lack of correlations for the exact spacer geometry, the accuracy of models relies strongly on assumptions used for modeling spacers. CFD can be used to determine an appropriate correlation. However, application of CFD also requires careful choice of turbulence models and numerical meshes, which are selected based on extensive experience with liquid metal flow simulations for the KALLA lab. In this paper consistent results of CFX and Star-CD are obtained and compared to measured data. Measured data of the pressure loss of the core are obtained with a differential pressure transducer located between the core inlet and outlet at a flow rate of 13.57kg/s.