• International Journal of Safety
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• 제5권1호
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• pp.29-32
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• 2006

There has been an increasing need for substitute energy development due to the dry up of the fossil fuel and environmental problems. Among the substitute energy under consideration, producing hydrogen from water without the accompanying release of carbon has become a promising technology. Also, Iodine-Sulfur (IS) thermochemical water decomposition is one of the promising processes that can produce hydrogen efficiently using the high temperature gas-cooled reactor (HTGR) as an energy source capable of supplying heat at over 1000. In this study, to effect an initiating events identification of the IS process, Master Logic Diagram (MLD) was used and 9 initiating events that cause a leakage of the chemical material were identified.

• Nuclear Engineering and Technology
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• 제47권2호
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• pp.187-195
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• 2015

Human-induced initiating events, also called Category B actions in human reliability analysis, are operator actions that may lead directly to initiating events. Most conventional probabilistic safety analyses typically assume that the frequency of initiating events also includes the probability of human-induced initiating events. However, some regulatory documents require Category B actions to be specifically analyzed and quantified in probabilistic safety analysis. An explicit modeling of Category B actions could also potentially lead to important insights into human performance in terms of safety. However, there is no standard procedure to identify Category B actions. This paper describes a systematic procedure to identify Category B actions for low power and shutdown conditions. The procedure includes several steps to determine operator actions that may lead to initiating events in the low power and shutdown stages. These steps are the selection of initiating events, the selection of systems or components, the screening of unlikely operating actions, and the quantification of initiating events. The procedure also provides the detailed instruction for each step, such as operator's action, information required, screening rules, and the outputs. Finally, the applicability of the suggested approach is also investigated by application to a plant example.

• Nuclear Engineering and Technology
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• 제51권4호
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• pp.1024-1031
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• 2019

The Molten Salt Fast Reactor (MSFR) with its liquid circulating fuel and its fast neutron spectrum calls for a new safety approach including technological neutral methodologies and analysis tools adapted to early design phases. In the frame of the Horizon2020 program SAMOFAR (Safety Assessment of the Molten Salt Fast Reactor) a safety approach suitable for Molten Salt Reactors is being developed and applied to the MSFR. After a description of the MSFR reference design, this paper focuses on the identification of the Postulated Initiating Events (PIEs), which is a core part of the global assessment methodology. To fulfil this task, the Functional Failure Mode and Effect Analysis (FFMEA) and the Master Logic Diagram (MLD) are selected and employed separately in order to be as exhaustive as possible in the identification of the initiating events of the system. Finally, an extract of the list of PIEs, selected as the most representative events resulting from the implementation of both methods, is presented to illustrate the methodology and some of the outcomes of the methods are compared in order to highlight symbioses and differences between the MLD and the FFMEA.

• 한국안전학회지
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• 제24권3호
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• pp.54-58
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• 2009

화석연료의 고갈과 환경문제로 인해 대체에너지 개발의 필요성이 대두되고 있다. 이에 거론되고 있는 대체에너지 중에서 물로부터 수소를 생산하는 기술은 탄소발생이 없는 매우 장래가 유망한 기술이다. IS 열화학적 물분해 공정은 거론되는 방법 중 매우 유망한 기술로 에너지원으로 900$^{\circ}C$ 이상의 열을 공급할 수 있는 고온가스냉각로(HTGR)를 시용하여 매우 능률적으로 수소를 생산할 수 있는 방법이다. 본 연구에서는 IS공정 의 초기사건을 도출하기 위해 주논리도(MLD)방법이 사용되어 화학물질의 유출을 야기할 수 있는 초기사건 9가지가 도출되었다. 또한 도출된 9가지 초기사건 중 6가지를 선정, 사건수목을 이용하여 정량화하였다.

• 한국원자력학회:학술대회논문집
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• 한국원자력학회 2005년도 춘계학술발표회
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• pp.55-56
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• 2005

• Nuclear Engineering and Technology
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• 제53권2호
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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.

• Nuclear Engineering and Technology
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• 제43권3호
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• pp.271-278
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• 2011

When performing fire PSA in a nuclear power plant, an event mapping method, using an internal event PSA model, is widely used to reduce the resources used by fire PSA model development. Feasible initiating events and component failure events due to fire are identified to transform the fault tree (FT) for an internal event PSA into one for a fire PSA using the event mapping method. A surrogate event or damage term method is used to condition the FT of the internal PSA. The surrogate event or the damage term plays the role of flagging whether the system/component in a fire compartment is damaged or not, depending on the fire being initiated from a specified compartment. These methods usually require explicit states of all compartments to be modeled in a fire area. Fire event scenarios, when using explicit identification, such as surrogate or damage terms, have two problems: (1) there is no consideration of multiple fire propagation beyond a single propagation to an adjacent compartment, and (2) there is no consideration of simultaneous fire propagations in which an initiating fire event is propagated to multiple paths simultaneously. The present paper suggests a fire propagation equation to identify all possible fire event scenarios for an explicitly treated fire event scenario in the fire PSA. Also, a method for separating fire events was developed to make all fire events a set of mutually exclusive events, which can facilitate arithmetic summation in fire risk quantification. A simple example is given to confirm the applicability of the present method for a $2{\times}3$ rectangular fire area. Also, a feasible asymptotic approach is discussed to reduce the computational burden for fire risk quantification.

• Nuclear Engineering and Technology
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• 제44권4호
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• pp.393-404
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• 2012

After the Fukushima nuclear accident in 2011, there has been increasing concern regarding severe accidents in nuclear facilities. Severe accident scenarios are difficult for operators to monitor and identify. Therefore, accurate prediction of a severe accident is important in order to manage it appropriately in the unfavorable conditions. In this study, artificial intelligence (AI) techniques, such as support vector classification (SVC), probabilistic neural network (PNN), group method of data handling (GMDH), and fuzzy neural network (FNN), were used to monitor the major transient scenarios of a severe accident caused by three different initiating events, the hot-leg loss of coolant accident (LOCA), the cold-leg LOCA, and the steam generator tube rupture in pressurized water reactors (PWRs). The SVC and PNN models were used for the event classification. The GMDH and FNN models were employed to accurately predict the important timing representing severe accident scenarios. In addition, in order to verify the proposed algorithm, data from a number of numerical simulations were required in order to train the AI techniques due to the shortage of real LOCA data. The data was acquired by performing simulations using the MAAP4 code. The prediction accuracy of the three types of initiating events was sufficiently high to predict severe accident scenarios. Therefore, the AI techniques can be applied successfully in the identification and monitoring of severe accident scenarios in real PWRs.

• 대한조선학회논문집
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• 제59권3호
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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.

• Journal of Radiation Protection and Research
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• 제41권2호
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• pp.117-121
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• 2016

Background: Definition and grouping of initiating events (IEs) are important basics for probabilistic safety assessment (PSA). An IE in a spent fuel reprocessing plant (SFRP) is an event that probably leads to the release of dangerous material to jeopardize workers, public and environment. The main difference between SFRPs and nuclear power plants (NPPs) is that hazard materials spread diffusely in a SFRP and radioactive material is just one kind of hazard material. Materials and Methods: Since the research on IEs for NPPs is in-depth around the world, there are several general methods to identify IEs: reference of lists in existence, review of experience feedback, qualitative analysis method, and deductive analysis method. While failure mode and effect analysis (FMEA) is an important qualitative analysis method, master logic diagram (MLD) method is the deductive analysis method. IE identification in SFRPs should be consulted with the experience of NPPs, however the differences between SFRPs and NPPs should be considered seriously. Results and Discussion: The plutonium uranium reduction extraction (Purex) process is adopted by the technics in a model reprocessing plant. The first extraction cycle (FEC) is the pivotal process in the Purex process. Whether the FEC can function safely and steadily would directly influence the production process of the whole plant-production quality. Important facilities of the FEC are installed in the equipment cells (ECs). In this work, IEs in the FEC process were identified and categorized by FMEA and MLD two methods, based on the fact that ECs are containments in the plant. Conclusion: The results show that only two ECs in the FEC do not need to be concerned particularly with safety problems, and criticality, fire and red oil explosion are IEs which should be emphatically analyzed. The results are accordant with the references.