• Journal of information and communication convergence engineering
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• v.20 no.2
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• pp.79-89
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• 2022

To compute the mean and variance of component-based reliability software, we focused on path-based reliability analysis. System reliability depends on the transition probabilities of components within a system and reliability of the individual components as basic input parameters. The uncertainty in these parameters is estimated from the test data of the corresponding components and arises from the software architecture, failure behaviors, software growth models etc. Typically, researchers perform Monte Carlo simulations to study uncertainty. Thus, we considered a Markov chain Monte Carlo (MCMC) simulation to calculate uncertainty, as it generates random samples through sequential methods. The MCMC approach determines the input parameters from the probability distribution, and then calculates the average approximate expectations for a reliability estimation. The comparison of different techniques for uncertainty analysis helps in selecting the most suitable technique based on data requirements and reliability measures related to the number of components.

• Nuclear Engineering and Technology
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• v.54 no.12
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• pp.4412-4421
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• 2022

The pressure measurement in the high-temperature liquid metal system, such as Sodium-cooled Fast Reactor(SFR), is important and yet it is very challenging due to its nature. The measuring pressure is relatively at low range and the applied temperature varies in wide range. Moreover, the pressure transfer material in impulse line needs to considered the high temperature condition. The conventional diaphragm-based approach cannot be used for it is impossible to remove the effect of thermal expansion. In this paper, the Fiber Bragg Grating(FBG) sensor-based pressure measuring concept is suggested that it is free of problems induced by the thermal expansion. To verify this concept, a prototype was fabricated and tested in an appropriate conditions. The uncertainty analysis result of the experiment is also included. The final result of this study clearly showed that the FBG-based pressure transmitter system is applicable to the extreme environment, such as SFR and any other high-temperature liquid metal system and the measurement uncertainty is within reasonable range.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2010.05a
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• pp.783-784
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• 2010

• The Transactions of The Korean Institute of Electrical Engineers
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• v.62 no.9
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• pp.1264-1269
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• 2013

In this paper, we study a disturbance observer (DOB) based controller for an EMS(Electro-Magnetic Suspension) system in presence of mass uncertainty and input disturbance. The DOB based controller is employed in order to compensate the modeling uncertainty and attenuate disturbance signals. For the design of DOB based controller, the Jacobain linearization of nonlinear system model equation is used. Computer simulation is carried out for nonlinear model in order to compare the performance of the proposed DOB controller with that of the conventional PID controller. The simulation results show that the substantial improvement in the performance can be achieved by the proposed DOB controller.

• Proceedings of the KIEE Conference
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• 2006.07c
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• pp.1509-1510
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• 2006

ERA PD measuring system has been using for partial discharge evaluation of power appratus in test laboratories. So, the measurement uncertainty of PD measuring system (ERA), such as PD pulse calibrator rise and fall time, sacle factor(k) and linearity, transfer impedance etc, is very important factor of test result in test laboratory. In this paper, we describe tracebility and uncertainty improvement of PD measuring system in test laboratory based on IEC 60270.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.58 no.11
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• pp.2136-2141
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• 2009

Transmission planning is an important part of power system planning to meet an increasing demand for electricity. The objective of transmission expansion is to minimize operational and construction costs subject to system constraints. There is inherent uncertainty in transmission planning due to errors in forecasted demand and fuel costs. Therefore, transmission planning process is not reliable if the uncertainty is not taken into account. The paper presents a systematic method to find the optimal location and amount of transmission expansion using Cross-Entropy (CE) incorporating uncertainties about future power system conditions. Numerical results are presented to demonstrate the performance of the proposed method.

• Journal of the Korean Society of Safety
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• v.29 no.6
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• pp.166-171
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• 2014

Nuclear power plants are equipped with the reactor trip system (RTS) and the engineered safety features actuation system (ESFAS) to improve safety on the normal operation. In the event of the design basis accident (DBA), a various of post accident monitor(PAM)systems support to provide important details (e.g. Containment pressure, temperature and pressure of reactor cooling system and core exit temperature) to determine action of main control room (MCR). Operator should be immediately activated for the accident mitigation with the information. Especially, core exit temperature is a critical parameter because the operating mode converts from normal mode to emergency mode when the temperature of core exit reaches $649^{\circ}C$. In this study, uncertainty which was caused by exterior environment, characteristic of thermocouple/connector and accuracy of calibrator/indicator was evaluated in accordance with ANSI-ISA 67.04. The square root of the sum of square (SRSS) methodology for combining uncertainty terms that are random and independent was used in the synthesis. Every uncertainty that may exist in the hardware which is used to measure the core exit temperature was conservatively applied and the associative relation between the elements of uncertainty was considered simultaneously. As a result of uncertainty evaluation, the channel statistical allowance (CSA) of single channel of core exit temperature was +1.042%Span. The range of uncertainty, -0.35%Span ($-4.05^{\circ}C$) ~ +2.08%Span($24.25^{\circ}C$), was obtained as the operating criteria of core exit temperature.

• Nuclear Engineering and Technology
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• v.46 no.3
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• pp.291-298
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• 2014

This paper concerns estimating uncertainties of the core neutronics design parameters of power reactors by direct sampling method (DSM) calculations based on the two-step McCARD/MASTER design system in which McCARD is used to generate the fuel assembly (FA) homogenized few group constants (FGCs) while MASTER is used to conduct the core neutronics design computation. It presents an extended application of the uncertainty propagation analysis method originally designed for uncertainty quantification of the FA FGCs as a way to produce the covariances between the FGCs of any pair of FAs comprising the core, or the covariance matrix of the FA FGCs required for random sampling of the FA FGCs input sets into direct sampling core calculations by MASTER. For illustrative purposes, the uncertainties of core design parameters such as the effective multiplication factor ($k_{eff}$), normalized FA power densities, power peaking factors, etc. for the beginning of life (BOL) core of Yonggwang nuclear unit 4 (YGN4) at the hot zero power and all rods out are estimated by the McCARD/MASTER-based DSM computations. The results are compared with those from the uncertainty propagation analysis method based on the McCARD-predicted sensitivity coefficients of nuclear design parameters and the cross section covariance data.

• Earthquakes and Structures
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• v.8 no.4
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• pp.915-934
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• 2015

Within the context of Structural Health Monitoring (SHM), it is often the case that structural systems are described by uncertainty, both with respect to their parameters and the characteristics of the input loads. For the purposes of system identification, efficient modeling procedures are of the essence for a fast and reliable computation of structural response while taking these uncertainties into account. In this work, a reduced order metamodeling framework is introduced for the challenging case of nonlinear structural systems subjected to earthquake excitation. The introduced metamodeling method is based on Nonlinear AutoRegressive models with eXogenous input (NARX), able to describe nonlinear dynamics, which are moreover characterized by random parameters utilized for the description of the uncertainty propagation. These random parameters, which include characteristics of the input excitation, are expanded onto a suitably defined finite-dimensional Polynomial Chaos (PC) basis and thus the resulting representation is fully described through a small number of deterministic coefficients of projection. The effectiveness of the proposed PC-NARX method is illustrated through its implementation on the metamodeling of a five-storey shear frame model paradigm for response in the region of plasticity, i.e., outside the commonly addressed linear elastic region. The added contribution of the introduced scheme is the ability of the proposed methodology to incorporate uncertainty into the simulation. The results demonstrate the efficiency of the proposed methodology for accurate prediction and simulation of the numerical model dynamics with a vast reduction of the required computational toll.

• Proceedings of the Korea Water Resources Association Conference
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• 2020.06a
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• pp.123-123
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• 2020

The present study is aimed to correcting radar-based mean areal precipitation forecasts to improve urban flood predictions and uncertainty analysis of water levels contributed at each stage in the process. For this reason, a long short-term memory (LSTM) network is used to reproduce three-hour mean areal precipitation (MAP) forecasts from the quantitative precipitation forecasts (QPFs) of the McGill Algorithm for Precipitation nowcasting by Lagrangian Extrapolation (MAPLE). The Gangnam urban catchment located in Seoul, South Korea, was selected as a case study for the purpose. A database was established based on 24 heavy rainfall events, 22 grid points from the MAPLE system and the observed MAP values estimated from five ground rain gauges of KMA Automatic Weather System. The corrected MAP forecasts were input into the developed coupled 1D/2D model to predict water levels and relevant inundation areas. The results indicate the viability of the proposed framework for generating three-hour MAP forecasts and urban flooding predictions. For the analysis uncertainty contributions of the source related to the process, the Bayesian Markov Chain Monte Carlo (MCMC) using delayed rejection and adaptive metropolis algorithm is applied. For this purpose, the uncertainty contributions of the stages such as QPE input, QPF MAP source LSTM-corrected source, and MAP input and the coupled model is discussed.