• Journal of Ocean Engineering and Technology
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• v.27 no.2
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• pp.47-52
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• 2013

A subsea chemical injection system treats blockage problems in a subsea production system. It is important to treat problems quickly, because production delays cause fatal profit losses in a subsea production system. Therefore, the subsea industry requires a relatively higher reliability level for a production system compared to other industries. In this study, a subsea chemical injection system (linked to a control system) to inject chemicals into a subsea X-mas tree was analyzed. By using FSA (Formal Safety Assessment), the risk factors were defined and a quantitative risk analysis utilizing FTA (Fault Tree Analysis) and ETA (Event Tree Analysis) was performed. As a result, the effectiveness of a risk reduction option was evaluated.

• Journal of the Korean Society of Safety
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• v.31 no.5
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• pp.187-194
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• 2016

A single fire event within a fire area can cause multiple initiating events considered in internal events probabilistic safety assessment (PSA). For an example, a fire event in turbine building fire area can cause a loss of the main feed-water and loss of off-site power initiating events. This fire initiating event could result in special plant responses beyond the scope of the internal events PSA model. One approach to address a fire initiating event is to develop a specific fire event tree. However, the development of a specific fire event tree is difficult since the number of fire event trees may be several hundreds or more. Thus, internal fire events PSA model has been generally constructed by modifications of the pre-developed internal events PSA model. New accident sequence logics not covered in the internal events PSA model are separately developed to incorporate them into the fire PSA model. Recently, many fire PSA models have fire induced initiating event fault trees not shown in an internal event PSA model. Up to now, there has been no analytical comparative study on the constructions of fire events PSA model using internal events PSA model with and without fault trees of initiating events. In this study, the changing process of internal events PSA model to fire events PSA model is analytically presented and discussed.

• Proceedings of the Korea Society for Simulation Conference
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• 2003.11a
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• pp.51-57
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• 2003

In operating distributed systems, proactive management is one of the major concerns for better quality of service and future capacity planning. In order to handle this management problem effectively, it is necessary to analyze performances of the distributed system and events generated by components in the system. This paper provides a rule-based event parsing engine for proactive management. Our event parsing engine uses object hooking-based and event-token approaches. The object hooking-based approach prepares new conditions and actions in Java classes and allows dynamically exchange them as hook objects in run time. The event-token approach allows the event parsing engine consider a proper sequence and relationship among events as an event token to trigger an action. We analyze the performance of our event parsing engine with two different implementations of rule structure; one is table-based and the other is tree-based.

• 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.

• Nuclear Engineering and Technology
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• v.53 no.2
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• pp.498-508
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• 2021

Micro reactors are increasingly being considered for utilization as distributed power sources. Hence, the probabilistic safety assessment (PSA) of a direct supercritical-CO₂-cooled fast reactor, called micro modular reactor (MMR), was performed in this study; this reactor was developed using innovative design concepts. It adopted a modular design and passive safety systems to minimize site constraints. As the MMR is in its conceptual design phase, design weaknesses and valuable safety insights could be identified during PSA. Level 1 internal event PSA was carried out involving literature survey, system characterization, identification of initiating events, transient analyses, development of event trees and fault trees, and quantification. The initiating events and scenarios significantly contributing to core damage frequency (CDF) were determined to identify design weaknesses in MMR. The most significant initiating event category contributing to CDF was the transients with the power conversion system initially available category, owing to its relatively high occurrence frequency. Further, an importance analysis revealed that the safety of MMR can be significantly improved by improving the reliability of reactor trip and passive decay heat removal system operation. The findings presented in this paper are expected to contribute toward future applications of PSA for assessing unconventional nuclear reactors in their conceptual design phases.

• Journal of the Korean Society of Safety
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• v.15 no.2
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• pp.126-135
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• 2000

Probabilistic Safety Assessment (PSA) is an engineering analysis method to identify possible contributors to the risk from a nuclear power plant and now it has become a standard tool in safety evaluation of nuclear power plants. PSA consists of three phases named as Level 1, 2 and 3. Level 2 PSA, mainly focused in this paper, uses a step-wise approach. At first, plant damage states (PDSs) are defined from the Level 1 PSA results and they are quantified. Containment event tree (CET) is then constructed considering the physico-chemical phenomena in the containment. The quantification of CET can be assisted by a decomposition event tree (DET). Finally, source terms are quantitatively characterized by the containment failure mode. As the main benefit of PSA is to provide insights into plant design, performance and environmental impacts, including the identification of the dominant risk contributors and the comparison of options for reducing risk, this technique is expected to be applied to the industrial safety area.

• The Journal of Information Systems
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• v.17 no.3
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• pp.25-37
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• 2008

In a fault tree analysis, an uncertainty importance measure is often used to assess how much uncertainty of the top event probability (Q) is attributable to the uncertainty of a basic event probability ($q_i$), and thus, to identify those basic events whose uncertainties need to be reduced to effectively reduce the uncertainty of Q. For evaluating the measures suggested by many authors which assess a percentage change in the variance V of Q with respect to unit percentage change in the variance $v_i$ of $q_i$, V and ${\partial}V/{\partial}v_i$ need to be estimated analytically or by Monte Carlo simulation. However, it is very complicated to analytically compute V and ${\partial}V/{\partial}v_i$ for large-sized fault trees, and difficult to estimate them in a robust manner by Monte Carlo simulation. In this paper, we propose a method for evaluating the measure using discretization technique and Monte Carlo simulation. The proposed method provides a stable uncertainty importance of each basic event.

• Korean Journal of Computational Design and Engineering
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• v.18 no.2
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• pp.138-147
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• 2013

The liquefaction process system is regarded as primary among all topside systems in LNG FPSO. This liquefaction process system is composed of many types of equipment. LNG equipment on offshore plants has quite different demands on the equipment compared to traditional onshore LNG plants, so the reliability analysis of this process system needs to be performed. This study investigates how DEVS formalism for discrete event simulation can be used to reliability analysis of the liquefaction cycle for LNG FPSO. The reliability analysis method based on DEVS formalism could be better model for reflecting the system configuration than the conventional reliability analysis methods, such as fault tree analysis and event tree analysis.

• Proceedings of the KIEE Conference
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• 1999.07b
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• pp.838-840
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• 1999

In this paper, modeling and analysis of discrete event systems by temporal logic frame works and petri net is considered. The reachability tree of the petri net can be used to solve the safeness, boundedness, conservation and coverability problems of discrete event systems. But the reachability tree of the petri net do not solve reachability and liveness problems in general. We proposed a method that synthesised the petri net and the temporal logic frameworks. This method slove some problems of petri net by logical representation of temporal logic frameworks.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.30 no.3
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• pp.37-43
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• 2007

We use influence diagrams to describe event trees used in safety analyses of low-probability high-risk incidents. This paper shows how the branch parameters used in the event tree models can be updated by a bayesian method based on the observed counts of certain well-defined subsets of accident sequences. We focus on the analysis of the shared branch parameters, which may frequently often in the real accident initiation and propagation to more severe accident. We also suggest the way to utilize different levels of accident data to forecast low-probability high-risk accidents.