• IE interfaces
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• v.6 no.2
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• pp.67-78
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• 1993

In this paper, we deal with the application of the fuzzy sets theory to evaluate and estimate the system reliability under the fault tree analysis. We formulate the uncertainty of component reliability to fuzzy sets, and propose a procedure for obtaining the system reliability in case the system structure is described by fault tree. An importance measure of each component is proposed. Computer program for fuzzy fault tree analysis(FFTA) is developed using C language to obtain the system reliability and the component‘s fuzzy importance.

• Journal of the Korean Society for Precision Engineering
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• v.10 no.4
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• pp.104-108
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• 1993

The linear length measurements are most frequently performed and should be most accurate among other parts in dimensional metrology. We developed the linear measuring system using a laser interferometer to improve the accuracy and to shorten the calibration time. The uncertainty of the system is 0.01 .mu. for 500mm steel gage block. The range of the measurement and resolution of the system are 1000mm and 0.01 .mu. m, respectively.

• Journal of the Korean Institute of Intelligent Systems
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• v.26 no.3
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• pp.208-217
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• 2016

This paper describes a simulation method to generate sensor measurements for location estimation of an underwater robot. Field trial of a navigation method of an underwater robot takes much time and expenses and it is difficult to change the environment of the field trial as desired to test the method in various situations. Therefore, test and verification of a navigation method through simulation is inevitable for underwater environment. This paper proposes a method to generate sensor measurements of range, depth, velocity, and attitude taking the uncertainties of measurements into account through simulation. The uncertainties are Gaussian noise, outlier, and correlation between the measurement noise. Also, the method implements uncertainty in sampling time of measurements. The method is tested and verified by comparing the uncertainty parameters calculated statistically from the generated measurements with the designed uncertainty parameters. The practical feasibility of the measurement data is shown by applying the measurement data for location estimation of an underwater robot.

• Journal of Electrical Engineering and Technology
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• v.8 no.6
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• pp.1269-1275
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• 2013

Recently, many studies have suggested that an electric vehicle (EV) is one of the means for increasing the reliability of power systems in new energy environments. EVs can make a contribution to improving reliability by providing frequency regulation in power systems in which the Vehicle-to-Grid (V2G) technology has been implemented and, if economically viable, can be helpful in increasing power system reliability. This paper presents a stochastic method for optimal coordination of charging and frequency regulation decisions for an EV aggregator using the Least Square Monte-Carlo (LSMC) with modeling of electricity price uncertainty. The LSMC can be used to assess the value of options based on electricity price uncertainty in order to simultaneously optimize the scheduling of EV charging and regulation service for the EV aggregator. The results of a numerical example show that the proposed method can significantly improve the expected profits of an EV aggregator.

• Nuclear Engineering and Technology
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• v.26 no.3
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• pp.389-400
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• 1994

The predictability of KAERI version of RELAP5/MOD3 on reflood peak cladding temperature during large break loss-of-coolant accident is assessed against 18 test runs in FLECHT SEASET test data. The associated uncertainty is statistically quantified. The selected test runs include a gravity feed test and several forced feed tests with wide range of the parameters such as flooding rate, system pressure, initial clad temperature, rod bundle power. The results show that the code under-predicts the peak cladding temperature by 7.56 K on average. The upper limit of the associated uncertainty at 95% confidence level is evaluated to be about 99 K, It including the bias due to the under-prediction.

• Nuclear Engineering and Technology
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• v.46 no.3
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• pp.343-352
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• 2014

Uncertainty and sensitivity analyses with respect to nuclear data are performed with depletion calculations for BWR and PWR fuel assemblies specified in the framework of the UAM-LWR Benchmark Phase II. For this, the GRS sampling based tool XSUSA is employed together with the TRITON depletion sequences from the SCALE 6.1 code system. Uncertainties for multiplication factors and nuclide inventories are determined, as well as the main contributors to these result uncertainties by calculating importance indicators. The corresponding neutron transport calculations are performed with the deterministic discrete-ordinates code NEWT. In addition, the Monte Carlo code KENO in multi-group mode is used to demonstrate a method with which the number of neutron histories per calculation run can be substantially reduced as compared to that in a calculation for the nominal case without uncertainties, while uncertainties and sensitivities are obtained with almost the same accuracy.

• 전자공학회논문지 IE
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• v.46 no.4
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• pp.49-56
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• 2009

In this paper, stabilization inverse optimal control for nonlinear systems with structural uncertainty is considered. Based on the control Lyapunov function, a theorem for the globally asymptotic stability is presented. From this a less conservative condition for the inverse optimal control is derived. The result is used to design an inverse optimal controller for a class of nonlinear systems, that improves and extends the existing results. The class of nonlinear system considered is also enlarger. The simulation results show the effectiveness of the method.

• Nuclear Engineering and Technology
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• v.48 no.3
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• pp.684-701
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• 2016

The Gaussian process model (GPM) is a flexible surrogate model that can be used for nonparametric regression for multivariate problems. A unique feature of the GPM is that a prediction variance is automatically provided with the regression function. In this paper, we estimate the safety margin of a nuclear power plant by performing regression on the output of best-estimate simulations of a large-break loss-of-coolant accident with sampling of safety system configuration, sequence timing, technical specifications, and thermal hydraulic parameter uncertainties. The key aspect of our approach is that the GPM regression is only performed on the dominant input variables, the safety injection flow rate and the delay time for AC powered pumps to start representing sequence timing uncertainty, providing a predictive model for the peak clad temperature during a reflood phase. Other uncertainties are interpreted as contributors to the measurement noise of the code output and are implicitly treated in the GPM in the noise variance term, providing local uncertainty bounds for the peak clad temperature. We discuss the applicability of the foregoing method to reduce the use of conservative assumptions in best estimate plus uncertainty (BEPU) and Level 1 probabilistic safety assessment (PSA) success criteria definitions while dealing with a large number of uncertainties.

• Nuclear Engineering and Technology
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• v.45 no.6
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• pp.767-790
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• 2013

MAAP4 is a computer code that can simulate the response of a light water reactor power plant during severe accident sequences, including actions taken as part of accident management. The code quantitatively predicts the evolution of a severe accident starting from full power conditions given a set of system faults and initiating events through events such as core melt, reactor vessel failure, and containment failure. Furthermore, models are included in the code to represent the actions that could mitigate the accident by in-vessel cooling, external cooling of the reactor pressure vessel, or cooling the debris in containment. A key element tied to using a code like MAAP4 is an uncertainty analysis. The purpose of this paper is to present a MAAP4 based analysis to examine the sensitivity of a key parameter, in this case hydrogen production, to a set of model parameters that are related to a Level 2 PRA analysis. The Level 2 analysis examines those sequences that result in core melting and subsequent reactor pressure vessel failure and its impact on the containment. This paper identifies individual contributors and MAAP4 model parameters that statistically influence hydrogen production. Hydrogen generation was chosen because of its direct relationship to oxidation. With greater oxidation, more heat is added to the core region and relocation (core slump) should occur faster. This, in theory, would lead to shorter failure times and subsequent "hotter" debris pool on the containment floor.

• Korean Journal of Optics and Photonics
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• v.9 no.4
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• pp.258-263
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• 1998

Quasi-elastic light scattering is utilized to measure the mean diameter of the 0.3 $\mu\textrm{m}$-dimeter polystyrene sphere. The mean diameter of the polystyrene sphere is required to be known within the uncertainty of a few per centages. The systematic error has been considerably reduced by improving the system for the angle alignment and temperature measurement of cell. NIST SRM 1691 (0.269$\pm$0.007 $\mu\textrm{m}$: TEM; 0.275$\pm$0.007 $\mu\textrm{m}$: QELS) is measured to be 0.273 $\mu\textrm{m}$$\pm$0.006 $\mu\textrm{m}$ in mean diameter. Detailed description is given of the improved method and the resultant uncertainty, and the comparison of results with NIST is followed.