• Journal of Teachers' Pension
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• v.1
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• pp.157-185
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• 2016

본 연구에서는 비정상적 사건을 정의하고 이에 따른 비정상적 위험의 구체적인 유형을 파악하며, 이와 관련된 사학연금의 위험관리 체계에 대한 검토와 함께 비정상적 위험에 효과적으로 대응할 수 있는 자산운용방안을 제시하였다. 우선 비정상적 사건을 '과거 자료를 이용한 발생확률의 추정이나 발생여부에 대한 예측이 불가능하며 따라서 이의 발생 가능성을 사전에 고려하고 대비하는 사전적인 대처가 어려운 사건으로서 자산운용과 위험관리에 무시할 수 없는 영향을 미치는 사건'으로 정의하였으며, 이의 구체적인 형태로서 금융위기를 포함하는 9가지 사건 유형을 파악하였다. 동비정상적 사건들은 포트폴리오 투자를 통한 자산운용에서 개별자산군의 기대수익률과 위험 및 자산군 사이의 상관관계에 영향을 미쳐, 기존의 자산배분안의 최적성을 상실시키고 위험수준의 측정치인 VaR값을 과소 또는 과대추정하게 할 수 있는 것으로 분석되었다. 한편 비정상적 사건의 해외 사례에 대한 분석에서는 비정상적 사건의 영향이 개별 사건마다 다양한 양태로 발현되는 것이 관측되었다. 본 연구에서는 사학연금의 현행 자산배분 체계가 이와 같은 비정상적 사건의 영향에 적절하게 대응하기 어려운 상황이라고 진단하였으며, 비정상적 사건에 적절히 대응하기 위한 자산관리방안의 일환으로서 일별 수익률 자료를 사용한 비정상적 사건의 영향 평가방안을 제시하였다. 한편, 사학연금의 현행 위험관리 체계는 비정상적 사건의 발생에 적절하게 대응할 수 있는 것으로 평가되었다

• Journal of the Korean Society for Railway
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• v.12 no.2
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• pp.190-198
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• 2009

This study shows the developing process of the risk assessment models for railway casualty accidents. To evaluate the risks of these accidents, the hazardous events and the hazardous factors were identified by the review of the accident history and engineering interpretation of the accident behavior. The frequency of each hazardous event was evaluated from the historical accident data and structured expert judgments by using the Fault Tree Analysis (FTA) technique. In addition, to assess the severity of each hazardous event, the ETA (Event Tree Analysis) technique and other safety techniques were applied. The risk assessment models developed can be effectively utilized in defining the risk reduction measures in connection with the option analysis.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 2015.10a
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• pp.256-257
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• 2015

The trend of globalization and the development of the communication-Information technology not only complexified the supply chain, but also, led to the needs of the high quality of logistics service for customers. I t defines risks that can occur in truck transport under unexpected situation with Fault Tree Analysis(FTA) and calculates failure rate concerning relationship between each risks. Based on the 4 kinds of middle failure events that defined in FTA, Reliability function which is regarded about risks sequentiality and time flow is resulted in. I t is meaningful that it calculates reliability of logistics and transportation system with engineering methodology.

• Korean Journal of Construction Engineering and Management
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• v.23 no.3
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• pp.25-35
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• 2022

The purpose of this study is to derive risk events that occurred during aircraft runway construction and analyze loss costs for project participants. For this purpose, design change data, contracted statement and completed statement were investigated. The results of this study are as follows: There were 12 risk events in the process of construction, 5 design errors and 7 construction errors. The increased construction costs due to such risk events were calculated as KRW 726 million. Of the KRW 726 million that was increased due to risk events, about 52.57% was spent by the ordering agency, and about 47.43% contractors. The increased construction costs due to such risk events are about 4.86% of the direct construction costs of KRW 14.9 billion. Based on the results derived from these case studies, a method for estimating reserve costs and construction costs considering risk events is presented.

• Journal of the Korean Society for Railway
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• v.12 no.6
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• pp.936-943
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• 2009

In this study, a risk assessment model based on the ETA (Event Tree Analysis) and FTA (Fault Tree Analysis) is developed according to the procedure of hazard analysis and risk assessment in order to estimate the risk quantitatively. The FTA technique is applied to estimate the branch probability (frequency) and the ETA technique is applied to estimate the consequence for each branch path on the ET (Event Tree). A risk assessment model is developed by the combination of those ETA and FTA. In addition, the reliability and the validity of the risk assessment model are verified by comparing the risk estimated through the developed model with the actual equivalent fatality.

• Proceedings of the Korean Institute of Industrial Safety Conference
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• 2003.05a
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• pp.114-119
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• 2003

원자력발전소를 비롯한 위험 시설물의 확률론적 안전성 평가(Probabilistic Safety Assessment: PSA)는 고장수목(Fault Tree) 및 사건수목(Event Tree) 분석으로 이루어지며, 분석 결과로 그 시설물의 위험도(Risk)는 최소단절집합(Minimal Cutsets)들의 합으로 구성 된다.(중략)

• Journal of Korean Tunnelling and Underground Space Association
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• v.18 no.1
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• pp.1-12
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• 2016

When utilizing a Tunnel Boring Machine (TBM) for tunnelling work, unexpected ground conditions can be encountered that are not predicted in the design stage. These include fractured zones or mixed ground conditions that are likely to reduce the stability of TBM excavation, and result in considerable economic losses such as construction delays or increases in costs. Minimizing these potential risks during tunnel construction is therefore a crucial issue in any mechanized tunneling project. This paper proposed the potential risk events that may occur due to risky ground conditions. A resistivity survey is utilized to predict the risky ground conditions ahead of the tunnel face during construction. The potential risk events are then evaluated based on their occurrence probability and impact. A TBM risk management system that can suggest proper solution methods (measures) for potential risk events is also developed. Multi-Criterion Decision Making (MCDM) is utilized to determine the optimal solution method (optimal measure) to handle risk events. Lastly, an actual construction site, at which there was a risk event during Earth Pressure-Balance (EPB) Shield TBM construction, is analyzed to verify the efficacy of the proposed system.

• The Korean Journal of Applied Statistics
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• v.33 no.4
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• pp.379-393
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• 2020

A terminal event such as death may censor an intermediate event such as relapse, but not vice versa in semi-competing risks data, which is often seen in medicine, public health, and epidemiology. We propose a Weibull regression model with a normal frailty to analyze semi-competing risks data when all three transition times of the illness-death model are possibly interval-censored. We construct the conditional likelihood separately depending on the types of subjects: still alive with or without the intermediate event, dead with or without the intermediate event, and dead with the intermediate event missing. Optimal parameter estimates are obtained from the iterative quasi-Newton algorithm after the marginalization of the full likelihood using the adaptive importance sampling. We illustrate the proposed method with extensive simulation studies and PAQUID (Personnes Agées Quid) data.

• 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.

• The Korean Journal of Applied Statistics
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• v.29 no.7
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• pp.1311-1327
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• 2016

We propose a multi-state model for analyzing semi-competing risks data with interval-censored or missing intermediate events. This model is an extension of the 'illness-death model', which composes three states, such as 'healthy', 'diseased', and 'dead'. The state of 'diseased' can be considered as an intermediate event. Two more states are added into the illness-death model to describe missing events caused by a loss of follow-up before the end of the study. One of them is a state of 'LTF', representing a lost-to-follow-up, and the other is an unobservable state that represents the intermediate event experienced after LTF occurred. Given covariates, we employ the Cox proportional hazards model with a normal frailty and construct a full likelihood to estimate transition intensities between states in the multi-state model. Marginalization of the full likelihood is completed using the adaptive Gaussian quadrature, and the optimal solution of the regression parameters is achieved through the iterative Newton-Raphson algorithm. Simulation studies are carried out to investigate the finite-sample performance of the proposed estimation procedure in terms of the empirical coverage probability of the true regression parameter. Our proposed method is also illustrated with the dataset adapted from Helmer et al. (2001).