• 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.

• 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.

• 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.

• 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 Institute of Building Construction Conference
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• 2017.11a
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• pp.195-196
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• 2017

The number of human accidents in the construction industry is increasing every year, and it constitute the highest percentage among industry. This means that activities performed to prevent safety accidents in the country are not efficient to reduce the rate of accidents in the construction industry. In order to solve this issue, research has been conducted from various perspectives. But, research regarding to quantification model of human accidents is insufficient. the objective of this study is to conduct a basic study on quantification model development of human accidents. To achieve the objective, first, Cause of accident is defined the through literature review. Second, a basic statistic analysis is conducted to determine the characteristics of the accident causes. Third, the analysis is conducted after dividing into four categories : accumulate rate, season, total construction cost, and location. In the future, this study can be used as a reference for developing the safety management checklist for safety management in construction site and development of prediction models of human accident.

• Journal of Information Technology Applications and Management
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• v.22 no.2
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• pp.201-217
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• 2015

In this paper, we report computational testing result to examine the validity of firm's bankruptcy risk estimation through quantification of supply chain risk. Supply chain risk in this study refers to upstream supply risk and downstream demand risk, To assess the firm's risk affected by supply chain risk, we adopt unit of analysis as industry level. since supply and demand relationships of the firm could be generalized by the industry input-output table and the availability of various valid economic indicators which are chronologically calculated. The research model to estimate firm's risk level is the linear regression model to assess the industry bankruptcy risk estimation of the focal firm's industry with the independent variables which could quantitatively reflect demand and supply risk of the industry. The publicly announced macro economic indicators are selected as the candidate independent variables and validated through empirical testing. To validate our approach, in this paper, we confined our research scope to steel industry sector and its related industry sectors, and implemented the research model. The empirical testing results provide useful insights to further refine the research model as the valid forecasting mechanism to capture firm's future risk estimation more accurately by adopting supply chain industry risk aspect, in conjunction with firm's financial and other managerial factors.

• Proceedings of the Korean Institute of Building Construction Conference
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• 2018.11a
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• pp.132-133
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• 2018

Many studies regarding construction safety management have been conducted. However, it is insufficient to research on external construction site. As a result, ordinary people around the construction site have injured and have a negative view when they think construction industrial since it has regarded having an overfull industrial accidents on media. To break the stereotype and prevention of accident on construction industry have been emphasized at this point in time, it is necessary to establish a comprehensive safety management system which is considered not only internal safety management but also external safety management. Therefore, the objective of this study is to develop the human accident risk quantification model by utilizing the third party payout data which occurred by incomplete safety management on external construction site. This study is conducted as a basic study for developing safety management manuals on internal·external construct site. In the future, it is expected to be used as a reference.

• Proceedings of the KSR Conference
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• 2006.11b
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• pp.1132-1139
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• 2006

Railway risk is evaluated by a method of linking event trees and fault trees as the general PSA(Probabilistic Safety Assessment) model for the risk assessment of complex systems. Accident scenarios causing undesirable events are modeled by event trees comprised of several accident sequences. Each branch located in the accident progression of the event tree is modeled by an fault tree or can be represented by some value too simply. We usually evaluate the frequency of the whole sequence by adding them after calculating the frequency of each sequence at a time. However, since there are quite a number of event trees and fault trees in the railway risk assessment model, the number of sequence to evaluate increases and preparation for the risk assessment costs much time all the more. Also, it may induce errors when analysts perform the work of quantification. Therefore, the systematic maintenance and control of event trees and fault trees will be essential for the railway risk assessment. In this paper we introduce an integrated assessment method using one-top model and develop a risk assessment tool for the maintenance and control of the railway risk model.

• Wind and Structures
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• v.13 no.2
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• pp.207-220
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• 2010

The 'chain reaction' effect of the interaction between wind pressure and windborne debris is likely to be a major cause of damage to residential buildings during severe wind events. The current paper (Part II) concerns the quantification of such pressure-debris interaction in an advanced vulnerability model that integrates the debris risk model developed in Part I and a component-based wind-pressure damage model. This vulnerability model may be applied to predict the cumulative wind damage during the passage of particular hurricanes, to estimate annual hurricane losses, or to conduct system reliability analysis for residential developments, with the effect of windborne debris fully considered.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.13 no.21
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• pp.29-41
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• 1990

An assessment of risk in industrial and urban environments is essential in the prevention of accident and in the analysis of situations which are hazardous to public health and safety. The risk imposed by a particular hazard increases with the likelihood of occurence of the event, the exposure and the possible consequence of that event. In a traditional approach, the calculation of a quantitative value of risk is usually based on an assignment of numerical values of each of the risk factors. Then the product of the values of likelihood, exposure and consequences called risk score is derived. However vagueness and imprecision in mathematical quantification of risk are equated with fuzziness rather than randomness. In this paper, a fuzzy set theoretic approach to risk analysis is proposed as an alternative to the techniques currently used in the area of systems safety. Then the concept of risk evaluation using linguistic representation of the likelihood, exposure and consequences is introduced. A risk assessment model using approximate reasoning technique based on fuzzy logic is presented to drive fuzzy values of risk and numerical example for risk analysis is also presented to illustrate the results.