• 전기의세계
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• v.26 no.2
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• pp.95-98
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• 1977

Commercially available fuel oil for power plant contains relatively much sulphur, which means accordingly high content sulphur deoxide in exhaust gas. Sulphur deoxide has been identified as the worst-pollutant caused by thermal power generation. This paper primarily deals with the stack gas diffusion effects of various parameters, namely vertical stability, wind velocity, exhaust gas velocity, stack height, etc., on the ground concentration. thereof the relation between stack height and maximum plant capacity is analyzed from the standpoint of air pollution prevention. The limit capacity is calculated by means of mean concentration introducing Mead and Lowry coefficient respectively.

• The Transactions of the Korean Institute of Electrical Engineers
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• v.38 no.4
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• pp.316-325
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• 1989

This paper is concerned with robust stabilization of single input or single output systems. Based on the region of non-destabilizing perturbations some approaches to design which allow the given of structured perturbation of plant parameters and their gradient optimization are given. These algorithms iteratively enlarge the stability hypershere in plant parameter space and can be used to design a controller to stabilize a plant subject to given ranges of parameter excursions.

• Proceedings of the Korean Society of Marine Engineers Conference
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• 2001.05a
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• pp.112-116
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• 2001

In the paper, desalination technology for a barge mounted plant is presented. Desalination system on a barge needs high efficiency, smaller space, and stability. Therfore 4-effect distillation system (capacity of 50ton/day) is designed and constructed. During operation, detailed investigation of different opereation parameters is carried. This paper discusses about product water flowrate and recover ratio with different steam flow rate and feed water rate.

• 제어로봇시스템학회:학술대회논문집
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• 1987.10a
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• pp.817-826
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• 1987

An offset-free self-tuning control with pole placement (STCPP) and a recursive parameter estimation with multiple and variable forgetting factors (REWF), together with their application to a real plant, are described. There are two different types of offset-free STCPP; their features are analysed and discussed. REMVF employs as many forgetting factors as parameter estimates. It is suitable when parameters to be estimated are changing at different rates. The offset-free STCPP and REMVF have been successfully applied to a real plant, giving excellent results.

• 제어로봇시스템학회:학술대회논문집
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• 1996.10b
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• pp.164-167
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• 1996

This paper presents an off-line P.I.D parameter estimation method during normal operation in power plant. The process parameters are estimated using the recursive least square method. The controller parameters are estimated on the basis of desired characteristics of the dynamic model of the closed-loop control.

• 제어로봇시스템학회:학술대회논문집
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• 1989.10a
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• pp.489-493
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• 1989

In this paper a new approach to adaptive control using a combination of both direct and indirect methods has been proposed. Based on the estimates of the plant parameters and the current values of the control parameters, closed-loop estimation errors .epsilon.$_{\theta}$(t) and .epsilon.$_{k}$(t) are defined. These in turn are used in the adaptive laws for updating both identification as well as control parameters. The global uniform stability of the overall system is shown by constructing a Lyapunov function.n.

• The Transactions of the Korean Institute of Electrical Engineers
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• v.38 no.5
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• pp.337-342
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• 1989

Since the late 1960s, the selection of the parameters of power system stabilizer (PSS) to damp out sustained low frequency oscillation of power generators in the steady state has been an active research area. This paper presents a new approach to select the optimal PSS parameters using the sensitivity of the quadratic performance with respect to the PSS parameters. The proposed algorithm has been applied to Seo-Cheon fossil power plant.

• Journal of the Earthquake Engineering Society of Korea
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• v.19 no.6
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• pp.265-271
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• 2015

The tsunami hazard analysis is performed for testing the application of probabilistic tsunami hazard analysis to nuclear power plant sites in the Korean Peninsula. Tsunami hazard analysis is based on the seismic hazard analysis. Probabilistic method is adopted for considering the uncertainties caused by insufficient information of tsunamigenic fault sources. Logic tree approach is used. Uljin nuclear power plant (NPP) site is selected for this study. The tsunamigenic fault sources in the western part of Japan (East Sea) are used for this study because those are well known fault sources in the East Sea and had several records of tsunami hazards. We have performed numerical simulations of tsunami propagation for those fault sources in the previous study. Therefore we use the wave parameters obtained from the previous study. We follow the method of probabilistic tsunami hazard analysis (PTHA) suggested by the atomic energy society of Japan (AESJ). Annual exceedance probabilities for wave height level are calculated for the site by using the information about the recurrence interval, the magnitude range, the wave parameters, the truncation of lognormal distribution of wave height, and the deviation based on the difference between simulation and record. Effects of each parameters on tsunami hazard are tested by the sensitivity analysis, which shows that the recurrence interval and the deviation dominantly affects the annual exceedance probability and the wave heigh level, respectively.

• Journal of the Korean Institute of Gas
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• v.20 no.3
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• pp.52-58
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• 2016

In this study, evaluation method for LNG plant FEED is suggested and its validity is confirmed using a well-known decision making technique of Analytic Hierarchy Process (AHP). It is a pairwise comparison technique which can be used when multiple options must be considered for a single decision making problem. In order to develop an objective decision methodology, various decision parameters, sub-parameters as well as the concept of scale of assessment were introduced, and its consistency among these parameters was also checked by calculating the consistency index (C.I.). The methodology suggested in this article will contribute in evaluation of LNG plant FEED with less bias and subjectivity associated with the decision making procedure.

• Journal of Korean Society of Water and Wastewater
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• v.21 no.5
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• pp.601-607
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• 2007

In order to maintain constant residual chlorine in sedimentation basin, It is necessary to develop real time prediction model of residual chlorine considering water treatment plant data such as water qualities, weather, and plant operation conditions. Based on the operation data acquired from K water treatment plant, prediction models of residual chlorine in sediment basin were accomplished. The input parameters applied in the models were water temperature, turbidity, pH, conductivity, flow rate, alkalinity and pre-chlorination dosage. The multiple regression models were established with linear and non-linear model with 5,448 data set. The corelation coefficient (R) for the linear and non-linear model were 0.39 and 0.374, respectively. It shows low correlation coefficient, that is, these multiple regression models can not represent the residual chlorine with the input parameters which varies independently with time changes related to weather condition. Artificial neural network models are applied with three different conditions. Input parameters are consisted of water quality data observed in water treatment process based on the structure of auto-regressive model type, considering a time lag. The artificial neural network models have better ability to predict residual chlorine at sediment basin than conventional linear and nonlinear multi-regression models. The determination coefficients of each model in verification process were shown as 0.742, 0.754, and 0.869, respectively. Consequently, comparing the results of each model, neural network can simulate the residual chlorine in sedimentation basin better than mathematical regression models in terms of prediction performance. This results are expected to contribute into automation control of water treatment processes.