• Korean Journal of Fisheries and Aquatic Sciences
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• v.24 no.1
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• pp.59-69
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• 1991

Two-level numerical models are formulated to predict the flow pattern, SS(suspended solids) distribution and the behavior of discharged fresh water in estuary, and are applied to the Suyoung River estuary in Pusan, Korea. To verify the application of the models, field observations of tidal current, salinity and 55 were performed during the period of spring tide. Computed upper level velocities by two-level model are in better agreement with observed values than single model. Apart from the magnitude of the velocities, the predicted flow fields at upper level are similar to those obtained at lower level. Upper level velocities in river channel during ebb spring tide are about 2 times stronger than those during flood spring tide due to the discharging flow rate from the Suyoung River. Two-level model results on the salinity and 55 distribution at upper level are compared with the observed ones at the surface. Computed salinity distributions are in good agreement with the observed values, but computed 55 distributions show $6{\~}10$ ppm higher values than the observed ones.

• Journal of the Korean Mathematical Society
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• v.57 no.4
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• pp.915-933
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• 2020

A two-level finite element method based on the Newton iterative method is proposed for solving the Navier-Stokes/Darcy model. The algorithm solves a nonlinear system on a coarse mesh H and two linearized problems of different loads on a fine mesh h = O(H^4-𝜖). Compared with the common two-grid finite element methods for the considered problem, the presented two-level method allows for larger scaling between the coarse and fine meshes. Moreover, we prove the stability and convergence of the considered two-level method. Finally, we provide numerical experiment to exhibit the effectiveness of the presented method.

• Journal of the Korean Society of Clothing and Textiles
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• v.21 no.5
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• pp.807-820
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• 1997

This exploratory research was intended to develop and test a slacks pattern based upon conic model. Data came from measurements of photograph of three subjects. Silhouette of slacks was close fit on waist and hip and loose under hip level. This three-dimensional form was modeled with truncated cones. This conic model was truncated by plane of the waist level, the abdomen level, the hip level, the crotch level and the ankle level parallel to the floor. Two models that have differences in back part of the model were tested. Drafted patterns from two models were taken for each subject. Drafted experimental pattern was operated for slacks pattern. The first step was to make sideseam. Parts over crotch level were moved to both sides. And then to make waistdarts. Experimental pattern had two darts each in front and back. Each experimental slacks was evaluated by sensory test to appearance and comfort by five judges. The results can be summarized as follows. 1) Appearance and comfort of experimental pattern were judged to be satisfactory. Especially these patterns were fitted we18 in waist darts front and back. So we evaluated that was proper pattern for slacks. 2) Model 2 was better in appearance than model 1. But Model 1 was more comfortable in non significant difference. This was supposed to be resulted from fit more closely of model 2. 3) considering preceding results, this geometric model based upon truncated cone was applicable for slacks pattern.

• Korean Journal of Cognitive Science
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• v.4 no.2
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• pp.115-143
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• 1994

In this paper,I present an extended two-level model using LR parsing techniques.The LR-based two-level model not only guarantees effcient morphological processing but also achieves a higher degree of descriptive adequacy than Koskenniemi's original model.The two-level model is augmented with an independent morphosyntactic module based on feature-based CF word grammar.By adopting a CF word grammar,our model is capable of dealing with complex words with discontinuous dependencies without having duplicate lexicons.It is shown how LR predictions manifested in the parsing table can help the morphological processor to minimize the dictionary lookup process.

• Nuclear Engineering and Technology
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• v.39 no.2
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• pp.133-142
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• 2007

The Electric Power Research Institute (EPRI) demonstrated a method for monitoring the performance of instrument channels in Topical Report (TR) 104965, 'On-Line Monitoring of Instrument Channel Performance.' This paper presents the results of several models originally developed by EPRI to monitor three nuclear plant sensor sets: Pressurizer Level, Reactor Protection System (RPS) Loop A, and Reactor Coolant System (RCS) Loop A Steam Generator (SG) Level. The sensor sets investigated include one redundant sensor model and two non-redundant sensor models. Each model employs an Auto-Associative Kernel Regression (AAKR) model architecture to predict correct sensor behavior. Performance of each of the developed models is evaluated using four metrics: accuracy, auto-sensitivity, cross-sensitivity, and newly developed Error Uncertainty Limit Monitoring (EULM) detectability. The uncertainty estimate for each model is also calculated through two methods: analytic formulas and Monte Carlo estimation. The uncertainty estimates are verified by calculating confidence interval coverages to assure that 95% of the measured data fall within the confidence intervals. The model performance evaluation identified the Pressurizer Level model as acceptable for on-line monitoring (OLM) implementation. The other two models, RPS Loop A and RCS Loop A SG Level, highlight two common problems that occur in model development and evaluation, namely faulty data and poor signal selection

• Journal of the Korean Operations Research and Management Science Society
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• v.35 no.3
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• pp.25-43
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• 2010

We consider a multi-objective balancing and sequencing problem in mixed model assembly lines, which is important for an efficient use of the assembly lines. In this paper, we present a neighborhood symbiotic evolutionary algorithm to simultaneously solve the two problems of balancing and model sequencing under multiple objectives. We aim to find a set of well-distributed solutions close to the true Pareto optimal solutions for decision makers. The proposed algorithm has a two-leveled structure. At Level 1, two populations are operated : One consists of individuals each of which represents a partial solution to the balancing problem and the other consists of individuals for the sequencing problem. Level 2, which is an upper level, works one population whose individuals represent the combined entire solutions to the two problems. The process of Level 1 imitates a neighborhood symbiotic evolution and that of Level 2 simulates an endosymbiotic evolution together with an elitist strategy to promote the capability of solution search. The performance of the proposed algorithm is compared with those of the existing algorithms in convergence, diversity and computation time of nondominated solutions. The experimental results show that the proposed algorithm is superior to the compared algorithms in all the three performance measures.

• Structural Engineering and Mechanics
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• v.18 no.1
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• pp.91-112
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• 2004

Concrete is a composite material and at meso-level, may be assumed to be composed of three phases: aggregate, mortar-matrix and aggregate-matrix interface. It is postulated herein that although non-linear material parameters are generally used to model this composite structure by finite element method, linear elastic fracture mechanics principles can be used for modelling at the meso level, if the properties of all three phases are known. For this reason, a novel meso-mechanical approach for concrete fracture which uses the composite material model with distributed-phase for elastic properties of phases and considers the size effect according to linear elastic fracture mechanics for strength properties of phases is presented in this paper. Consequently, the developed model needs two parameters such as compressive strength and maximum grain size of concrete. The model is applied to three most popular fracture mechanics approaches for concrete namely the two-parameter model, the effective crack model and the size effect model. It is concluded that the developed model well agrees with considered approaches.

• Journal of Power Electronics
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• v.19 no.5
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• pp.1162-1170
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• 2019

Finite-control-set model predictive control (FCS-MPC) is a promising control scheme for two-level voltage-source inverters (TL-VSIs). However, two main issues arise in the classical FCS-MPC method: an exponentially-increasing computational time and a low steady-state performance. To solve these two issues, a novel FCS-MPC method has been proposed for n-phase TL-VSIs in this paper. The basic idea of the proposed method is to carry out the FCS-MPC scheme of TL-VSIs for one leg by one leg, like a "pipeline". Based on this idea, the calculations are reduced from exponential time to linear time and its current waveforms are improved by applying more switching states per sampling period. The cases of three-phase and five-phase TL-VSIs were tested to verify the effectiveness of proposed method.

• International Journal of Quality Innovation
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• v.8 no.1
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• pp.87-98
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• 2007

A COQ model plays an important role in the total quality cost survey. Based on the methodology of continuous quality improvement, a dynamic COQ model for different quality level is developed in this paper. A quality level is defined by Six Sigma level that can be measured by two indicators. The relationships among the four major quality costs are analyzed. Finally, the curves of total quality costs for different quality level are presented.

• Proceedings of the Korean Nuclear Society Conference
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• 1996.11a
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• pp.301-306
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• 1996

To predict the average liquid level under the condition of the countercurrent stratified two-phase flow in a pipe, an analytical model has been suggested. This is made by introducing the interfacial level gradient into the liquid-phase and the gas-phase momentum equations. The analytical method for the gas-phase pressure drop calculation with f$_i$ $\neq$ f$_G$ has also been described using the liquid level prediction model developed in the present study.