• Nuclear Engineering and Technology
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• v.55 no.4
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• pp.1420-1427
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• 2023

Seismic risk has received increased attention since the 2011 Fukushima accident in Japan. The seismic risk of a nuclear power plant is evaluated via seismic probabilistic safety assessment (PSA), for which several methods are available. Recently, the discrete approach has become widely used. This approximates the seismic risk by discretizing the ground motion level interval into a small number of subintervals with the expectation of providing a conservative result. The present study examines the effect of the number of subintervals upon the results of seismic risk quantification. It is demonstrated that a small number of subintervals may lead to either an underestimation or overestimation of the seismic risk depending on the ground motion level. The present paper also provides a method for finding the boundaries between overestimation and underestimation regions, and illustrates the effect of the number of subintervals upon the seismic risk evaluation with an example. By providing a method for determining the effect of a small number of subintervals upon the results of seismic risk quantification, the present study will assist seismic PSA analysts to determine the appropriate number of subintervals and to better understand seismic risk quantification.

• Proceedings of the KSR Conference
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• 2007.05a
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• pp.605-613
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• 2007

In order to overcome the difficulties of quantitative risk analysis such as complexity of model, we propose a systematic methodology for risk quantification of railway system which consists of 6 steps: The identification of risk factors, the determination of major scenarios for each risk factor by using event tree, the development of supplementary fault trees for evaluating branch probabilities, the evaluation of event probabilities, the quantification of risk, and the analysis in consideration of accident situation. In this study, in order to address the feasibility of the propose methodology, this framework is applied to the prototype risk model of nation-wide railway level crossings. And the quantification result based on the data of 2005 in Korea will also be presented.

• Nuclear Engineering and Technology
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• v.49 no.2
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• pp.306-312
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• 2017

The purpose of this research is to introduce the technical standard of accident sequence precursor (ASP) analysis, and to propose a case study using the dynamic-probabilistic safety assessment (D-PSA) approach. The D-PSA approach can aid in the determination of high-risk/low-frequency accident scenarios from all potential scenarios. It can also be used to investigate the dynamic interaction between the physical state and the actions of the operator in an accident situation for risk quantification. This approach lends significant potential for safety analysis. Furthermore, the D-PSA approach provides a more realistic risk assessment by minimizing assumptions used in the conventional PSA model so-called the static-PSA model, which are relatively static in comparison. We performed risk quantification of a steam generator tube rupture (SGTR) accident using the dynamic event tree (DET) methodology, which is the most widely used methodology in D-PSA. The risk quantification results of D-PSA and S-PSA are compared and evaluated. Suggestions and recommendations for using D-PSA are described in order to provide a technical perspective.

• Journal of the Korean Society of Safety
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• v.38 no.6
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• pp.72-78
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• 2023

The purpose of this paper is to derive a quantified approach for Operator Manual Actions (OMAs) based on the existing fire Human Reliability Analysis (HRA) methodology developed by the Korea Atomic Energy Research Institute (KAERI). The existing fire HRA method was reviewed, and supplementary considerations for OMA quantification were established through a comparative analysis with NUREG-1852 criteria and the review of the existing literature. The OMA quantification approach involves a timeline that considers the occurrence of Multiple Spurious Operations (MSOs) during a Main Control Room Abandonment (MCRA) determination and movement towards the Remote Shutdown Panel (RSP) in the event of a Main Control Room (MCR) fire. The derived failure probability of an OMA from the approach proposed in this paper is expected to enhance the understanding of its reliability. Therefore, it allows moving beyond the deterministic classification of "reliable" or "unreliable" in NUREG-1852. Also, in the event of a nuclear power plant fire where multiple OMAs are required within a critical time range, it is anticipated that the OMA failure probability could serve as a criterion for prioritizing OMAs and determining their order of importance.

• Nuclear Engineering and Technology
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• v.41 no.6
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• pp.849-858
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• 2009

Risk caused by safety-critical instrumentation and control (I&C) systems considerably affects overall plant risk. As digitalization of safety-critical systems in nuclear power plants progresses, a risk model of a digitalized safety system is required and must be included in a plant safety model in order to assess this risk effect on the plant. Unique features of a digital system cause some challenges in risk modeling. This article aims at providing an overview of the issues related to the development of a static fault-tree-based risk model. We categorize the complicated issues of digital system probabilistic risk assessment (PRA) into four groups based on their characteristics: hardware module issues, software issues, system issues, and safety function issues. Quantification of the effect of these issues dominates the quality of a developed risk model. Recent research activities for addressing various issues, such as the modeling framework of a software-based system, the software failure probability and the fault coverage of a self monitoring mechanism, are discussed. Although these issues are interrelated and affect each other, the categorized and systematic approach suggested here will provide a proper insight for analyzing risk from a digital system.

• Proceedings of the Korean Nuclear Society Conference
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• 2004.05a
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• pp.155.2-155.2
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• 2004

• KSCE Journal of Civil and Environmental Engineering Research
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• v.43 no.1
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• pp.109-117
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• 2023

Schedule delays present a major risk factor, as they can adversely affect construction projects, such as through increasing construction costs, claims from a client, and/or a decrease in construction quality due to trims to stages to catch up on lost time. Risk management has been conducted according to the importance and priority of schedule delay risk, but quantification of risk on the depth of schedule delay tends to be inadequate due to limitations in data collection. Therefore, this research used the BERT (Bidirectional Encoder Representations from Transformers) language model to convert the contents of aconstruction log, which comprised unstructured data, into WBS (Work Breakdown Structure)-based structured data, and to form a model of classification and quantification of risk. A process was applied to eight highway construction sites, and 75 cases of rain schedule delay risk were obtained from 8 out of 39 detailed work kinds. Through a K-S test, a significant probability distribution was derived for fourkinds of work, and the risk impact was compared. The process presented in this study can be used to derive various schedule delay risks in construction projects and to quantify their depth.

• Proceedings of the Korean Geotechical Society Conference
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• 2009.03a
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• pp.444-455
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• 2009

Great concerns on geotechnical risk & hazard assessment have been increased due to human and economic damage by natural disasters with recent global climate changes. In this paper, geotechnical problems in particular, landslides which is interested in European countries and North America, were mainly discussed. For these, 18 key topics on geotechnical risk and hazards which had been discussed at the LARAM 2008 workshop in Italy were analyzed after grouping by subjects. Main topic contents consisted of applications such as field measurement, early warning systems, uncertainty analysis of parameters using radar, optical data and statistical theory and so on. And the problems related to analysis of vulnerability and deformation due to earthquakes, investigation of gas zone using seismic reflection data in a landslide area, risk quantification and hazard assessment of landslide movements and multi-dimensional analysis for stability of complex slopes were attracted. Also, there were studies on risk matters of cultural heritage, the blockglide of clayey ground, simulations of debris flows based on GIS, quantification of the failure processes of rock slopes, a meshless method for 3D crack modelling, and finally risk assessment for cryological processes due to global warming.

• Nuclear Engineering and Technology
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• v.50 no.6
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• pp.854-859
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• 2018

Calculating minimal cut sets is a typical quantification method used to evaluate the top event probability for a fault tree. If minimal cut sets cannot be calculated or if the accuracy of the quantification result is in doubt, the Monte Carlo method can provide an alternative for fault tree quantification. The Monte Carlo method for fault tree quantification tends to take a long time because it repeats the calculation for a large number of samples. Herein, proposal is made to improve the quantification algorithm of a fault tree with circular logic. We developed a top-down iteration algorithm that combines the characteristics of the top-down approach and the iteration approach, thereby reducing the computation time of the Monte Carlo method.

• Proceedings of the Korean Institute Of Construction Engineering and Management
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• 2007.11a
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• pp.327-330
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• 2007

This paper verifies that the normality assumption that the simulation output data, Project Completion Times (PCTs), follow normal distribution is not always acceptable and the existing belief may lead to misleading results. A risk quantification method, which measures the effect caused by the assumption, relative to the probability distribution of PCTs is implemented as an algorithm in MATLAB. To validate the reliability of the quantification, several series of simulation experiments have been carried out to analyze a set of simulation output data which are obtained from different type of Probability Distribution Function (PDF) assigned to activities'duration in a network. The method facilitates to find the effect of PDF type and its parameters. The procedure necessary for performing the risk quantification method is described in detail along with the findings. This paper contributes to improving the reliability of simulation based scheduling method, as well as increasing the accuracy of analysis results.