• Journal of Electrical Engineering and Technology
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• v.9 no.5
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• pp.1686-1693
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• 2014

In this paper, oil-paper samples composed of transformer windings were used to investigate the insulation degradation process subjected to partial discharge (PD), with artificial defects inside to simulate the PD induced insulation degradation. To determine appropriate test voltages, the breakdown time obtained through a group of accelerated electrical degradation tests under high voltages was firstly fitted by two-parameter Weibull model to acquire the average breakdown time, which was then applied to establish the inverse power law life model to choose advisable test voltages. During the electrical degradation process, PD signals were synchronously detected by an ultra-high frequency (UHF) sensor from inception to breakdown. For PD analysis, the whole degradation process was divided into ten stages, and chaos theory was introduced to analyze the variation of three chaotic parameters with the development of electrical degradation, namely the largest Lyapunov exponent, correlation dimension and Komogorov entropy of PD amplitude time series. It is shown that deterministic chaos of PD is confirmed during the oil-paper degradation process, and the obtained results provide a new effective tool for the diagnosis of degradation of oil-paper insulation subjected to PD.

• Tunnel and Underground Space
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• v.30 no.1
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• pp.15-28
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• 2020

In this study, a procedure was introduced to estimate strength and deformation modulus of the 3-D discrete fracture network(DFN) systems using the distinct element method(DEM). Fracture entities were treated as non-persistent square planes in the DFN systems. Systematically generated fictitious fractures having similar mechanical characteristics of intact rock were combined with non-persistent real fractures to create polyhedral blocks in the analysis domain. Strength and deformation modulus for 10 m cube domain of various deterministic and stochastic 3-D DFN systems were estimated using the DEM to explore the applicability of suggested method and to examine the effect of fracture geometry on strength and deformability of DFN systems. The suggested procedures were found to effective in estimating anisotropic strength and deformability of the 3-D DFN systems.

• Nuclear Engineering and Technology
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• v.48 no.6
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• pp.1423-1432
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• 2016

The integrity of a reactor pressure vessel (RPV) related to pressurized thermal shocks (PTSs) has been extensively studied. This paper introduces an integrity assessment of an RPV subjected to a PTS transient based on the French codes. In the USA, the "screening criterion" for maximum allowable embrittlement of RPV material is developed based on the probabilistic fracture mechanics. However, in the French RCC-M and RSE-M codes, which are developed based on the deterministic fracture mechanics, there is no "screening criterion". In this paper, the methodology in the RCC-M and RSE-M codes, which are used for PTS analysis, are firstly discussed. The bases of the French codes are compared with ASME and FAVOR codes. A case study is also presented. The results show that the method in the RCC-M code that accounts for the influence of cladding on the stress intensity factor (SIF) may be nonconservative. The SIF almost doubles if the weld residual stress is considered. The approaches included in the codes differ in many aspects, which may result in significant differences in the assessment results. Therefore, homogenization of the codes in the long time operation of nuclear power plants is needed.

• Nuclear Engineering and Technology
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• v.50 no.5
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• pp.627-638
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• 2018

This article describes an integrated Level 1-Level 2 probabilistic risk assessment (PRA) methodology to evaluate the radiological risk during postulated accident scenarios initiated during the decommissioning phase of a typical Mark I containment boiling water reactor. The fuel damage scenarios include those initiated while the reactor is permanently shut down, defueled, and the spent fuel is located into the spent fuel storage pool. This article focuses on the integrated Level 1-Level 2 PRA aspects of the analysis, from the beginning of the accident to the radiological release into the environment. The integrated Level 1-Level 2 decommissioning PRA uses event trees and fault trees that assess the accident progression until and after fuel damage. Detailed deterministic severe accident analyses are performed to support the fault tree/event tree development and to provide source term information for the various pieces of the Level 1-Level 2 model. Source terms information is collected from accidents occurring in both the reactor pressure vessel and the spent fuel pool, including simultaneous accidents. The Level 1-Level 2 PRA model evaluates the temporal and physical changes in plant conditions including consideration of major uncertainties. The goal of this article is to provide a methodology framework to perform a decommissioning Probabilistic Risk Assessment (PRA), and an application to a real case study is provided to show the use of the methodology. Results will be derived from the integrated Level 1-Level 2 decommissioning PSA event tree in terms of fuel damage frequency, large release frequency, and large early release frequency, including uncertainties.

• Journal of Korea Water Resources Association
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• v.50 no.11
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• pp.735-743
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• 2017

With growing concerns about ever-increasing anthropogenic greenhouse gas emissions, it is crucial to enhance preparedness for unprecedented extreme weathers that can bring catastrophic consequences. In this study, we proposed a stochastic framework that considers uncertainty in weather forecasts for flood analyses. First, we calibrated a simple rainfall-runoff model against observed hourly hydrographs. Then, using probability density functions of rainfall depths conditioned by 6-hourly weather forecasts, we generated many stochastic rainfall depths for upcoming 48 hours. We disaggregated the stochastic 6-hour rainfalls into an hourly scale, and input them into the runoff model to quantify a probabilistic range of runoff during upcoming 48 hours. Under this framework, we assessed two rainfall events occurred in Bocheong River Basin, South Korea in 2017. It is indicated actual flood events could be greater than expectations from weather forecasts in some cases; however, the probabilistic runoff range could be intuitive information for managing flood risks before events. This study suggests combining deterministic and stochastic methods for forecast-based flood analyses to consider uncertainty in weather forecasts.

• Journal of the Earthquake Engineering Society of Korea
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• v.23 no.6
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• pp.289-299
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• 2019

The tendency to use a probabilistic design method rather than a deterministic design method for the design of nuclear power plants (NPPs) will increase because their safety should be considered and strictly controlled in relation to various causes of damage. The distance between a seismically isolated NPP structure and a moat wall is called the clearance to stop. The clearance to stop is obtained from the 90th percentile displacement response of a seismically isolated NPP subject to a beyond design basis earthquake (BDBE) in the probabilistic design method. The purpose of this study is to analyze the effects of heating and buckling effects on the 90th percentile displacement response of a lead-rubber bearing (LRB) subject to a BDBE. The analysis results show that considering the heating and buckling effects to estimate the clearance to stop is conservative in the evaluation of the 90th percentile displacement response. If these two effects are not taken into account in the calculation of the clearance to stop, the underestimation of the clearance to stop causes unexpected damage because of an increase in the collision probability between the moat wall and the seismically isolated NPP.

• Earthquakes and Structures
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• v.3 no.3_4
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• pp.581-609
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• 2012

In this paper a novel non-iterative approach is proposed to address the problem of deriving non-stationary stochastic processes which are compatible in the mean sense with a given (target) response (uniform hazard) spectrum (UHS) as commonly desired in the aseismic structural design regulated by contemporary codes of practice. This is accomplished by solving a standard over-determined minimization problem in conjunction with appropriate median peak factors. These factors are determined by a plethora of reported new Monte Carlo studies which on their own possess considerable stochastic dynamics merit. In the proposed approach, generation and treatment of samples of the processes individually on a deterministic basis is not required as is the case with the various approaches found in the literature addressing the herein considered task. The applicability and usefulness of the approach is demonstrated by furnishing extensive numerical data associated with the elastic design UHS of the current European (EC8) and the Chinese (GB 50011) aseismic code provisions. Purposely, simple and thus attractive from a practical viewpoint, uniformly modulated processes assuming either the Kanai-Tajimi (K-T) or the Clough-Penzien (C-P) spectral form are employed. The Monte Carlo studies yield damping and duration dependent median peak factor spectra, given in a polynomial form, associated with the first passage problem for UHS compatible K-T and C-P uniformly modulated stochastic processes. Hopefully, the herein derived stochastic processes and median peak factor spectra can be used to facilitate the aseismic design of structures regulated by contemporary code provisions in a Monte Carlo simulation-based or stochastic dynamics-based context of analysis.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.17 no.4
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• pp.103-113
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• 2007

In this paper, we present a security analysis of Lightweight RFID Mutual Authentication Protocols-LMAP[10], $M^2AP$[11], EMAP[12]. Based on simple logic operations, the protocols were designed to be suitable for lightweight environments such as RFID systems. In [8,9], it is shown that these protocols are vulnerable to do-synchronization attacks with a high probability. The authors also presented an active attack that partially reveals a tag's secret values including its ID. In this paper, we point out an error from [9] and show that their do-synchronization attack would always succeed. We also improve the active attack in [9] to show an adversary can compute a tag's ID as well as certain secret keys in a deterministic way. As for $M^2AP$ and EMAP, we show that eavesdropping $2{\sim}3$ consecutive sessions is sufficient to reveal a tag's essential secret values including its ID that allows for tracing, do-synchronization and/or subsequent impersonations.

• The Korean Journal of Applied Statistics
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• v.34 no.3
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• pp.477-489
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• 2021

COVID-19 has spread seriously around the world in 2020 and it is still significantly affecting our whole daily life. Currently, the whole world is still undergoing the pandemic and South Korea is no exception to it. During the pandemic, South Korea had several events that prevented or accelerated its spread. To establish the prevention policies for infectious diseases, it is very important to evaluate the intervention effect of such events. The susceptible-infected-removed (SIR) model is often used to describe the dynamic behavior of the spread of infectious diseases through ordinary differential equations. However, the SIR model is a deterministic model without considering the uncertainty of observed data. To consider the uncertainty in the SIR model, the Bayesian approach can be employed, and this approach allows us to evaluate the intervention effects by time-varying functions of the infection rate in the SIR model. In this study, we describe the time trend of the spread of COVID-19 in South Korea and investigate the intervention effects for the events using the stochastic SIR model based on the Bayesian approach.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.31 no.3
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• pp.401-410
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• 2021

Recently, as cyber attacks targeting industrial control systems increase, various studies are being conducted on the detection of abnormalities in industrial processes. Considering that the industrial process is deterministic and regular, It is appropriate to determine abnormality by comparing the predicted value of the detection model from which normal data is trained and the actual value. In this paper, HAI Datasets 20.07 and 21.03 are used. In addition, an ensemble model is created by combining models that have applied different time steps to Gated Recurrent Units. Then, the detection performance of the single model and the ensemble recurrent neural networks model were compared through various performance evaluation analysis, and It was confirmed that the proposed model is more suitable for abnormal detection in industrial control systems.