• Proceedings of the Korean Nuclear Society Conference
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• 1996.11a
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• pp.91-96
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• 1996

The Dynamic Safety System (DSS) is a compute. based reactor protection system that has fail-safe nature and perform dynamic self-testing. In this paper, the implementation of DSS in PLC is presented for PWR. In order to choose adequate PLC implementation model of DSS, the reliability analysis is performed. The KO-RI unit 2 Nuclear power plant is selected as the reference plant, and the verification is carried out using the KO-RI unit 2 simulator FISA-2.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2004.05a
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• pp.810-813
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• 2004

A study on the dynamic response of single-storey steel frames equipped with a rotational friction damper is presented. Extensive testing was carried out for assessing the friction pad material, damper unit performance and foaled model frame response to lateral harmonics excitation. Numerical simulations based on non-linear time history analysis were used to evaluate the seismic behaviour of steel frames with rotational frictional damper. It Is demonstrated that using discrete friction dampers of proper parameters to link steel frame can reduce dynamic response significantly.

• Communications for Statistical Applications and Methods
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• v.9 no.2
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• pp.473-478
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• 2002

A test for a single outlier in multivariate regression with linear constraints on regression coefficients using a mean shift model is derived. It is shown that influential observations based on case-deletions in testing linear hypotheses are determined by two types of outliers that are mean shift outliers with or without linear constraints, An illustrative example is given.

• Proceedings of the Korean Statistical Society Conference
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• 2005.11a
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• pp.43-48
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• 2005

We consider the problem of testing for parameter changes in time series models based on a cusum test. Although the test procedure is well-established for the mean and variance in time series models, a general parameter case has not been discussed in the literature. Therefore, here we develop a cusum test for parameter change in a more general framework. As an example, we consider the change of the parameters in an RCA(1) model and that of the autocovariances of a linear process. We also consider the variance change test for unstable models with unit roots and GARCH models.

• Communications for Statistical Applications and Methods
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• v.2 no.1
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• pp.48-54
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• 1995

A direct method for fitting analysis-of-variance models to unbalanced data is presented. This method exploits sparsity and rank deficiency of the matrix and is based on Gram-Schmidt orthogonalization of a set of sparse columns of the model matrix. The computational algorithm of the sum of squares for testing estmable hyphotheses is given.

• Proceedings of the KIEE Conference
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• 2003.07b
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• pp.1318-1320
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• 2003

According to the computerization of railway signalling system, necessity of communication protocol for interface between these equipments is increasing. Therefore the research on communication protocol structure that is required according to computerization trend of these signalling goes. In our research the existed protocol currently used was analyzed, and the simulation modeling for performance analysis is deduced. Based on this simulation model the performance analysis and comparison is carried out, and also validation test is executed about new designed protocol.

• Proceedings of the KIPE Conference
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• 2020.08a
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• pp.40-42
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• 2020

본 논문에서는 리튬이온 배터리의 전기적인 특성 실험을 통해 열 해석에 필요한 인자를 추출하고 이를 이용하여 열 해석의 상용 프로그램인 COMSOL과 ANSYS에서 서로 다른 방법으로 열 해석을 진행한다. 두 프로그램의 열 해석을 통해 얻은 데이터와 측정 데이터를 비교분석 한 결과 유사 경향성을 확인하였고, 이를 통해 전기적 열 해석 모델의 신뢰성을 확보한다.

• The Transactions of the Korean Institute of Electrical Engineers A
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• v.48 no.6
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• pp.789-799
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• 1999

In this paper, the optimization of fuzzy inference systems is proposed for fuzzy model of nonlinear systems. A fuzzy model needs to be identified and optimized by means of the definite and systematic methods, because a fuzzy model is primarily acquired by expert's experience. The proposed rule-based fuzzy model implements system structure and parameter identification using the HCM(Hard C-mean) clustering method, genetic algorithms and fuzzy inference method. Two types of inference methods of a fuzzy model are the simplified inference and linear inference. in this paper, nonlinear systems are expressed using the identification of structure such as input variables and the division of fuzzy input subspaces, and the identification of parameters of a fuzzy model. To identify premise parameters of fuzzy model, the genetic algorithms is used and the standard least square method with the gaussian elimination method is utilized for the identification of optimum consequence parameters of fuzzy model. Also, the performance index with weighting factor is proposed to achieve a balance between the performance results of fuzzy model produced for the training and testing data set, and it leads to enhance approximation and predictive performance of fuzzy system. Time series data for gas furnace and sewage treatment process are used to evaluate the performance of the proposed model.

• Structural Engineering and Mechanics
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• v.62 no.2
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• pp.225-236
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• 2017

The purpose of this work is to predict ductile fracture of structural steel under extremely low cyclic loading experienced in earthquake. A cumulative damage model is proposed on the basis of an existing damage model originally aiming to predict fracture under monotonic loading. The cumulative damage model assumes that damage does not grow when stress triaxiality is below a threshold and fracture occurs when accumulated damage reach unit. The model was implemented in ABAQUS software. The cumulative damage model parameters for steel base metal, weld metal and heat affected zone were calibrated, respectively, through testing and finite element analyses of notched coupon specimens. The damage evolution law in the notched coupon specimens under different loads was compared. Finally, in order to examine the engineering applicability of the proposed model, the fracture performance of beam-column welded joints reported by previous researches was analyzed based on the cumulative damage model. The analysis results show that the cumulative damage model is able to successfully predict the cracking location, fracture process, the crack initiation life, and the total fatigue life of the joints.

• Proceedings of the Korea Water Resources Association Conference
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• 2023.05a
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• pp.37-37
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• 2023

There is currently a high-accuracy modern forecasting method that uses machine learning algorithms or artificial neural network models to forecast river water levels or flowrate. As a result, this study aims to develop a mathematical model based on artificial neural networks to effectively forecast river water levels upstream of Tranh Culvert in North Vietnam's Bac Hung Hai irrigation system. The mathematical model was thoroughly studied and evaluated by using hydrological data from six gauge stations over a period of twenty-two years between 2000 and 2022. Furthermore, the results of the developed model were also compared to those of the long-short-term memory neural networks model. This study performs four predictions, with a forecast time ranging from 6 to 24 hours and a time step of 6 hours. To validate and test the model's performance, the Nash-Sutcliffe efficiency coefficient (NSE), mean absolute error, and root mean squared error were calculated. During the testing phase, the NSE of the model varies from 0.981 to 0.879, corresponding to forecast cases from one to four time steps ahead. The forecast results from the model are very reasonable, indicating that the model performed excellently. Therefore, the proposed model can be used to forecast water levels in North Vietnam's irrigation system or rivers impacted by tides.