• Economic and Environmental Geology
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• v.51 no.2
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• pp.203-211
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• 2018

Issues with past practice in seismic hazard analysis of nuclear power plant sites in Korea are addressed. Brief review on both deterministic and probabilistic methods in seismic hazard analysis is given, and most of the continuing discussion is focussed on the probabilistic seismic hazard analysis. Causes of uncertainty are traced on the basis of the cases that the assessment methodology was applied to the nuclear power plant sites. Considerations on the assessment include the role of experts, a representative seismic catalog, seismic source zonation, earthquake ground-motion relationship, and evaluation process. Factors increasing uncertainty in each item are analyzed and some feasible solutions are discussed.

• 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

• Nuclear Engineering and Technology
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• v.28 no.6
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• pp.507-521
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• 1996

Quantification of uncertainties in the source term estimations by a large computer code, such as MELCOR and MAAP, is an essential process of the current Probabilistic safety assessment. The main objective of the present study is to investigate the applicability of a combined procedure of the response surface method (RSM) based on input determined from a statistical design and the Latin hypercube sampling (LHS) technique for the uncertainty analysis of CsI release fractions under a Hypothetical severe accident sequence of a station blackout at Younggwang nuclear power plant using MAAP3. OB code as a benchmark problem. On the basis of the results obtained in the present work, the RSM is recommended to be used as a principal tool for an overall uncertainty analysis in source term quantifications, while using the LHS in the calculations of standardized regression coefficients (SRC) and standardized rank regression coefficient (SRRC) to determine the subset of the most important input parameters in the final screening step and to check the cumulative distribution functions obtained by RSM. Verification of the response surface model for its sufficient accuracy is a prerequisite for the reliability of the final results that can be obtained by the combined procedure proposed in the present work.

• Journal of the Korea Management Engineers Society
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• v.23 no.4
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• pp.87-103
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• 2018

This paper introduces the method to develop two main types of the fuzzy OEE (Overall Equipment Effectiveness) models via triangular membership function for measuring uncertainty. The fuzzy OEE includes model type 1 and model type 2. The model type 1 is used when the theoretical machine speed only reflects the time loss whereas model type 2 is used when the actual machine speed reflects both time and speed loss. Model type 2 has shown to perform a lower availability rate and a higher performance rate compared to model type 1. In addition, the fuzzy UPH (Unit Per Hour) which is derived from using the fuzzy OEE is presented to satisfy demand uncertainty. The fuzzy UPH can easily measure the fuzzy tact time and cycle time by reciprocating itself. Finally, this study demonstrates the fuzzy OEE models using IVIFS (Interval-Valued Intuitionistic Fuzzy Set) based on the characterization via membership function, non-membership function and hesitant function. For the purpose of analyzing the fuzzy system OEE, the OEE for each machine of plant structure is considered triangular interval-valued intuitionistic fuzzy number. Regardless of plant structure, the validity degree of fuzzy membership function of system OEE decreases when the number of machine with worst value of the validity degree increases. Corresponding examples are presented in this paper for practitioner to understand the applicability and practicability of the proposed fuzzy OEE methods.

• Nuclear Engineering and Technology
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• v.21 no.1
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• pp.18-31
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• 1989

To analyze the impact of air pollution control on electricity generation cost, a computer program was developed. POGEN calculates levelized discounted power generation cost including additional air pollution control cost for coal power plant. Pollution subprogram calculates total capital and variable costs using governing equations for flue gas control. The costs are used as additional input for levelized discounted power generation cost subprogram. Pollution output for Rue Gas Desulphurization direct cost was verified using published cost data of well experienced industrialized countries. The power generation costs for the year 2001 were estimated by POGEN for three different regulatory scenarios imposed on coal power plant, and by levelized discounted power generation cost subprogram for nuclear power. Because of uncertainty expected in input variables for future plants, sensitivity and uncertainty analysis were made to check the importance and uncertainty propagation of the input variables using Latin Hypercube Sampling and Multiple Least Square method. Most sensitive parameter for levelized discounted power generation cost is discount rate for both nuclear and coal. The control cost for flue gas alone reaches additional 9-11 mills/kWh with standard deviation less than 1.3 mills/kWh. This cost will be nearly 20% of power generation cost and 40% of one GW capacity coal power plant investment cost. With 90% confidence, the generation cost of nuclear power plant will be 32.6-51.9 mills/kWh, and for the coal power plant it will be 45.5-50.5 mills/kWh. Nuclear is favorable with 95% confidence under stringent future regulatory requirement in Korea.

• 제어로봇시스템학회:학술대회논문집
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• 1997.10a
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• pp.856-859
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• 1997

In this paper we treat the application of fault detection method in DC motor having both model mismatch and noise problems. A fault detection method presented by Kwon et al. (1994) for SISO systems has been here experimented. The model mismatch includes here linearization error as well as undermodelling. Comparisons are made with the real plant, DC motor. The experimental result of robust fault detection method is shown to have good performance via with the alternative fault detection method which do not account noise.

• Journal of the Korean Institute of Telematics and Electronics B
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• v.31B no.5
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• pp.58-64
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• 1994

In this paper, a robust control scheme of a nonlinear system with norm bounded uncertainty is studied. The proposed algorithm is based on variable structure systems (VSS) theory. the sliding mode which is robust to plant uncertainty and disturbances is obtained by regulating a sliding surface equation. This VSS control law can improve the robustness of control systems by adjusting the minimum reaching velocity in a reaching phase. A numerical example is given to verify the effectiveness of the control law.

• 제어로봇시스템학회:학술대회논문집
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• 1992.10b
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• pp.586-591
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• 1992

In this paper a robust stabilization problem is discussed for plant with both time-varying parameter perturbations and unstructured uncertainty. It is shown that, a robust L$_{2}$-stabilizing controller can be obtained by solving an H$_{\infty}$ standard problem with a scaling parameter. Using an H$_{\infty}$ design method, a robust L$_{2}$-stabilizing controller is derived. Finally, a numerical example is given.n.

• 제어로봇시스템학회:학술대회논문집
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• 2000.10a
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• pp.237-237
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• 2000

In this paper, The modified dead-time compensator for plants with an integrator and long dead time is proposed. The design procedure takes account of the closed-loop performance and robustness. The tuning of the controller can be done using some information about the plant and its uncertainties. The proposed controller is compared to others recently presented in the literature. Some simulation results verify good closed-performance and robustness of the proposed DTC.

• Nuclear Engineering and Technology
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• v.46 no.4
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• pp.481-488
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• 2014

An analysis of the uncertainty quantification related to LBLOCA using the Monte-Carlo calculation has been performed and compared with the tolerance level determined by the Wilks' formula. The uncertainty range and distribution of each input parameter associated with the LOCA phenomena were determined based on previous PIRT results and documentation during the BEMUSE project. Calulations were conducted on 3,500 cases within a 2-week CPU time on a 14-PC cluster system. The Monte-Carlo exercise shows that the 95% upper limit PCT value can be obtained well, with a 95% confidence level using the Wilks' formula, although we have to endure a 5% risk of PCT under-prediction. The results also show that the statistical fluctuation of the limit value using Wilks' first-order is as large as the uncertainty value itself. It is therefore desirable to increase the order of the Wilks' formula to be higher than the second-order to estimate the reliable safety margin of the design features. It is also shown that, with its ever increasing computational capability, the Monte-Carlo method is accessible for a nuclear power plant safety analysis within a realistic time frame.