• Journal of the Ergonomics Society of Korea
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• v.22 no.1
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• pp.81-94
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• 2003

The British railway safety research group has developed a risk assessment model for the railway infrastructure and major railway accidents. The major hazardous factors of the railway infrastructure were identified and classified in the model. The frequency rates of critical top events were predicted by the fault tree analysis method using failure data of the railway system components and ratings of railway maintenance experts, The consequences of critical top events were predicted by the event tree analysis method. They classified the Joss of accident due to railway system into personal. commercial and environmental damages. They also classified 110 hazardous event due to railway system into three categories. train accident. movement accident and non-movement accident. The risk assessment model of the British railway system has been designed to take full account of both the high frequency low consequence type events (events occurring routinely for which there is significant quantity of recorded data) and the low frequency high consequence events (events occurring rarely for which there is little recorded data). The results for each hazardous event were presented in terms of the frequency of occurrence (number of events/year) and the risk (number of equivalent fatalities per year).

• 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.

• Journal of the Society of Naval Architects of Korea
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• v.59 no.3
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• pp.164-172
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• 2022

A HAZID is a brainstorming workshop to identify hazards in an early phase of a project. It should be flexible to capture all probable accidents allowing experienced participants to exploit their expertise and experiences. A bowtie analysis is a graphical representation of major accident hazards elaborating safety measures i.e. barriers. The result of these workshops should be documented in an organized manner to share as good as possible details of the discussion through the lifetime of the project. Currently results are documented using a three-step representation of an accident; causes, top event and consequences, which cannot capture correctly sequence of events leading to various accidents and roles of barrier between two events. Another problem is that barriers would be shown repeatedly leading to a misunderstanding that there are an enough number of safety measures. A new bowtie analysis method is proposed to describe an accident in multiple steps showing relations among causes or consequences. With causes and consequences shown in a format of a tree, the frequencies of having the top event (Fault tree analysis) and various consequences (Event tree analysis) are evaluated automatically based on the frequency of initiating causes and the probabilities of failure of barriers. It will provide a good description of the accident scenario and help the risk to be assessed transparently.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.12 no.10
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• pp.4774-4796
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• 2018

Wireless sensor networks are composed of a large number of inexpensive and tiny sensors used in different areas including military, industry, agriculture, space, and environment. Fault tolerance, which is considered a challenging task in these networks, is defined as the ability of the system to offer an appropriate level of functionality in the event of failures. The present study proposed an intelligent throughput descent and distributed energy-efficient mechanism in order to improve fault tolerance of the system against soft and permanent faults. This mechanism includes determining the intelligent neighborhood radius threshold, the intelligent neighborhood nodes number threshold, customizing the base paper algorithm for distributed systems, redefining the base paper scenarios for failure detection procedure to predict network behavior when running into soft and permanent faults, and some cases have been described for handling failure exception procedures. The experimental results from simulation indicate that the proposed mechanism was able to improve network throughput, fault detection accuracy, reliability, and network lifetime with respect to the base paper.

• Proceedings of the IEEK Conference
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• 2003.11b
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• pp.231-234
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• 2003

This paper designs and implements fault-tolerant server of meta server for shared filesystem (SANfs) in SAN environment. SANfs is the filesystem that many clients can share data in Network-attached storage in SAN environment and meta server is the server that processes file operation in SANfs. The focus of this paper is the implementation of fault-tolerant server of meta server in SANfs. In the event of a meta server, meta server failovers to a fault-tolerant server where its processing continues seamlessly. If meta server doesn't restore, fault-tolerant server searches reliable client and makes another fault-tolerant server and work as meta server. Heartbeat monitors meta server and shadow server and controls them.

• Journal of the Korean Institute of Intelligent Systems
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• v.7 no.1
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• pp.5-15
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• 1997

This paper mentions a fault tree analysis using not probability but natural language and fuzzy theory, Reliability estimate of each basic event and dependence level estimate among subsystems are expressed by linguistic terms. Analysis results are also expressed by natural language. The meaning of linguistic terms is expressed by a fuzzy set. In the presented analysis approach parametrized operations of fuzzy sets are considered so that analyst's subjectivity can be introduced into the analysis. This paper gives the Chernobyl accident as an example of the fuzzy fault tree analysis using linguistic terms.

• Proceedings of the Korean Information Science Society Conference
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• 1998.10b
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• pp.582-584
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• 1998

객체 지향 설계 명세를 대상으로한 시스템의 안전성에 대한 검사를 하여, 표(Table)조작에 기초한 검증법을 제안하였다[4]. 제안한 검증법에서는 전문 분야별로 준비된 안정성 기준(Safety Standard)과 노우하우(Knowhow)를 이용하여, 안전성에 관한 이벤트(Event)와 액션(Action)의 관계표를 작성하였다. 그러나, 많은 실제 개발 현장에서는 실제 존재하는 안전성 기준의 부족 등으로 인하여, 이러한 검증법의 기용이 어렵다는 문제점이 있다. 이에 본 논문에서는 신뢰성 분석의 한 방법인 FTA(Fault Tree Analysis)의 FT(Fault Tree)도를 이용한 안정성 체크리스트(Check list)를 작성하여, 이를 바탕으로 관계표를 작성하는 새로운 방법을 제안하고자 한다.

• The Transactions of the Korean Institute of Electrical Engineers
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• v.43 no.4
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• pp.564-569
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• 1994

This paper presents an expert system for the fault section estimation and fault diagnosis in power transmission systems, which also has random event generation function for the purpose of operator training or educational experiment. The expert system is developed using an artificial intelligence language.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.39 no.2
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• pp.129-137
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• 2016

To identify the cause of the error and maintain the health of system, an administrator usually analyzes event log data since it contains useful information to infer the cause of the error. However, because today's systems are huge and complex, it is almost impossible for administrators to manually analyze event log files to identify the cause of an error. In particular, as OpenStack, which is being widely used as cloud management system, operates with various service modules being linked to multiple servers, it is hard to access each node and analyze event log messages for each service module in the case of an error. For this, in this paper, we propose a novel message-based log analysis method that enables the administrator to find the cause of an error quickly. Specifically, the proposed method 1) consolidates event log data generated from system level and application service level, 2) clusters the consolidated data based on messages, and 3) analyzes interrelations among message groups in order to promptly identify the cause of a system error. This study has great significance in the following three aspects. First, the root cause of the error can be identified by collecting event logs of both system level and application service level and analyzing interrelations among the logs. Second, administrators do not need to classify messages for training since unsupervised learning of event log messages is applied. Third, using Dynamic Time Warping, an algorithm for measuring similarity of dynamic patterns over time increases accuracy of analysis on patterns generated from distributed system in which time synchronization is not exactly consistent.

• Journal of the Korean Institute of Gas
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• v.1 no.1
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• pp.81-86
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• 1997

This study is to estimate the possibility of accident in chemical plants from the analysis of system component which affects the occurrence of top event. Among the various risk assessment techniques, the Fault Tree Analysis which approaches deductively on the route of accident development was used in this study. By gate-by-gate method and minimal cut set, the qualitative and quantitative risk assessment for hazards in plants was performed. The probability of occurrence and frequency of top event was calculated from failure or reliability data of system components at stage of the quantitative risk assessment. In conclusion, the probability of accident was estimated according to logic pattern based on the Fault Tree Analysis. And the failure path which mostly influences on the occurrence of top event was found from Importance Analysis.