• Nuclear Engineering and Technology
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• v.49 no.2
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• pp.360-372
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• 2017

Many advanced reactor designs rely on passive systems to fulfill safety functions during accident sequences. These systems depend heavily on boundary conditions to induce a motive force, meaning the system can fail to operate as intended because of deviations in boundary conditions, rather than as the result of physical failures. Furthermore, passive systems may operate in intermediate or degraded modes. These factors make passive system operation difficult to characterize within a traditional probabilistic framework that only recognizes discrete operating modes and does not allow for the explicit consideration of time-dependent boundary conditions. Argonne National Laboratory has been examining various methodologies for assessing passive system reliability within a probabilistic risk assessment for a station blackout event at an advanced small modular reactor. This paper provides an overview of a passive system reliability demonstration analysis for an external event. Considering an earthquake with the possibility of site flooding, the analysis focuses on the behavior of the passive Reactor Cavity Cooling System following potential physical damage and system flooding. The assessment approach seeks to combine mechanistic and simulation-based methods to leverage the benefits of the simulation-based approach without the need to substantially deviate from conventional probabilistic risk assessment techniques. Although this study is presented as only an example analysis, the results appear to demonstrate a high level of reliability of the Reactor Cavity Cooling System (and the reactor system in general) for the postulated transient event.

• Nuclear Engineering and Technology
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• v.37 no.3
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• pp.245-258
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• 2005

This paper addresses two types of uncertainty: stochastic uncertainty and subjective uncertainty in probabilistic accident consequence assessments. The off-site consequence assessment code OSCAAR has been applied to uncertainty and sensitivity analyses on the individual risks of early fatality and latent cancer fatality in the population outside the plant boundary due to a severe accident. A new stratified meteorological sampling scheme was successfully implemented into the trajectory model for atmospheric dispersion and the statistical variability of the probability distributions of the consequence was examined. A total of 65 uncertain input parameters was considered and 128 runs of OSCAAR with 144 meteorological sequences were performed in the parameter uncertainty analysis. The study provided the range of uncertainty for the expected values of individual risks of early and latent cancer fatality close to the site. In the sensitivity analyses, the correlation/regression measures were useful for identifying those input parameters whose uncertainty makes an important contribution to the overall uncertainty for the consequence. This could provide valuable insights into areas for further research aiming at reducing the uncertainties.

• Nuclear Engineering and Technology
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• v.52 no.10
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• pp.2238-2249
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• 2020

In a seismic PSA, dependency among seismic failures of components has not been explicitly modeled in the fault tree or event tree. This dependency is separately identified and assigned with numbers that range from zero to unity that reflect the level of the mutual correlation among seismic failures. Because of complexity and difficulty in calculating combination probabilities of correlated seismic failures in complex seismic event tree and fault tree, there has been a great need of development to explicitly model seismic correlation in terms of seismic common cause failures (CCFs). If seismic correlations are converted into seismic CCFs, it is possible to calculate an accurate value of a top event probability or frequency of a complex seismic fault tree by using the same procedure as for internal, fire, and flooding PSA. This study first proposes a methodology to explicitly model seismic dependency by converting correlated seismic failures into seismic CCFs. As a result, this methodology will allow systems analysts to quantify seismic risk as what they have done with the CCF method in internal, fire, and flooding PSA.

• Nuclear Engineering and Technology
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• v.44 no.5
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• pp.471-482
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• 2012

To assess the risk of nuclear power plant operation and to determine the risk impact of digital systems, there is a need to quantitatively assess the reliability of the digital systems in a justifiable manner. The Probabilistic Risk Analysis (PRA) is a tool which can reveal shortcomings of the NPP design in general and PRA analysts have not had sufficient guiding principles in modelling particular digital components malfunctions. Currently digital I&C systems are mostly analyzed simply and conventionally in PRA, based on failure mode and effects analysis and fault tree modelling. More dynamic approaches are still in the trial stage and can be difficult to apply in full scale PRA-models. As basic events CPU failures, application software failures and common cause failures (CCF) between identical components are modelled.The primary goal is to model dependencies. However, it is not clear which failure modes or system parts CCF:s should be postulated for. A clear distinction can be made between the treatment of protection and control systems. There is a general consensus that protection systems shall be included in PRA, while control systems can be treated in a limited manner. OECD/NEA CSNI Working Group on Risk Assessment (WGRisk) has set up a task group, called DIGREL, to develop taxonomy of failure modes of digital components for the purposes of PRA. The taxonomy is aimed to be the basis of future modelling and quantification efforts. It will also help to define a structure for data collection and to review PRA studies.

• Proceedings of the KSME Conference
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• 2007.05b
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• pp.3464-3466
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• 2007

Power uprate is the process of increasing the maximum power level at which a commercial nuclear power plant may operate. Power uprate applications(113 units) for NPPs(Nuclear Power Plants) were recently approved in the United States. Utilities have been using power uprates since the 1970s as a way of increasing the power output of their nuclear plants. To increase the power output of a reactor, typically more highly enriched uranium fuel and/or more fresh fuel is used. This enables the reactor to produce more thermal energy and therefore more steam, driving a turbine generator to produce electricity. In this paper, the propriety of power uprate is explained through the review on the power uprate method and the changes of the physical parameters due to power uprate. The analysis results showed that the CDF(Core Damage Frequency) and LERF(Large Early Release Frequency) are affected in the current probabilistic safety assessment (PSA) model.

• Nuclear Engineering and Technology
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• v.37 no.3
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• pp.259-264
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• 2005

This paper presents a vital area identification (VAI) method based on the current fault tree analysis (FTA) and probabilistic safety assessment (PSA) techniques for the physical protection of nuclear power plants. A structured framework of a top event prevention set analysis (TEPA) application to the VAI of nuclear power plants is also delineated. One of the important processes for physical protection in a nuclear power plant is VAI that is a process for identifying areas containing nuclear materials, structures, systems or components (SSCs) to be protected from sabotage, which could directly or indirectly lead to core damage and unacceptable radiological consequences. A software VIP (Vital area Identification Package based on the PSA method) is being developed by KAERI for the VAI of nuclear power plants. Furthermore, the KAERI fault tree solver FTREX (Fault Tree Reliability Evaluation eXpert) is specialized for the VIP to generate the candidates of the vital areas. FTREX can generate numerous MCSs for a huge fault tree with the lowest truncation limit and all possible prevention sets.

• Transactions of the Korean Society of Pressure Vessels and Piping
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• v.14 no.2
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• pp.49-58
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• 2018

The regulatory periodic inspection program (PSI) conducted at every overhaul period is the most important process for confirming the safety of nuclear power plants. The PSI for operating nuclear power plants in Korea mainly consist of component level performance check that had been developed based on deterministic approach putting the same degree of importance to all the inspection items. This inspection methodology is likely to be effective for preoperational inspection. However, once the plant is put into service, the PSI must be focused on whether to minimize the risk of accident using defense-in-depth concept and risk insight. The incorporation of defense-in-depth concept and risk insight into the deterministic based safety inspection has not been well studied so far. In this study, two track approaches are proposed to make sure that core damage be avoided: one is to secure success path and the other to block the failure path in a specific event tree of PSA. The investigation shows how to select safety important components and how to set up inspection group to ensure that core damage would not occur for a given initiating event, which results in strengthening defense-in-depth level 3.

• Nuclear Engineering and Technology
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• v.51 no.1
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• pp.104-115
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• 2019

Since the Fukushima Daiichi accident, there has been an emphasis on the risk resulting from multi-unit accidents. Human reliability analysis (HRA) is one of the important issues in multi-unit probabilistic safety assessment (MUPSA). Hence, there is a need to properly identify all the human and organizational factors relevant to a multi-unit incident scenario in a nuclear power plant (NPP). This study identifies and categorizes the human and organizational factors relevant to a multi-unit incident scenario of NPPs based on a review of relevant literature. These factors are then analyzed to ascertain all possible unit-to-unit interactions that need to be considered in the multi-unit HRA and the pattern of interactions. The human and organizational factors are classified into five categories: organization, work device, task, performance shaping factors, and environmental factors. The identification and classification of these factors will significantly contribute to the development of adequate strategies and guidelines for managing multi-unit accidents. This study is a necessary initial step in developing an effective HRA method for multiple NPP units in a site.

• Nuclear Engineering and Technology
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• v.50 no.8
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• pp.1199-1209
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• 2018

After the Fukushima-Daiichi accident in 2011, the multi-unit risk, i.e., the risk due to several nuclear power plants (NPPs) in a site has become an important issue in several countries such as Korea, Canada, and China. However, the multi-unit risk has been discussed for a long time in the nuclear community before the Fukushima-Daiichi nuclear accident occurred. The regulatory authorities around the world and the international organizations had proposed requirements or guidelines to reduce the multi-unit risk. The concerns regarding the multi-unit risk can be summarized in the following three questions: How much the accident of an NPP in a site affects the safety of other NPPs in the same site? What is the total risk of a site with many NPPs? Will the risk of the simultaneous accidents at several NPPs in a site such as the Fukushima Daiichi accident be low enough? The multi-unit risk assessment (MURA) in an integrated framework is a practical approach to obtain the answers for the above questions. Even though there were few studies to assess the multi-unit risk before the Fukushima-Daiichi nuclear accident, there are still several issues to be resolved to perform the complete MURA. This article aims to provide an overview of the multi-unit risk issues and its assessment. We discuss the several critical issues in the current MURA to get useful insights regarding the multi-unit risk with the current state art of probabilistic safety assessment (PSA) technologies. Also, the qualitative answers for the above questions are addressed.

• Journal of the Ergonomics Society of Korea
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• v.20 no.2
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• pp.1-28
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• 2001

This paper deals with the selection of the important Influencing Factors (IFs) under accident management situations in nuclear power plants for use in the assessment of human errors. In order to achieve this goal, we collected two types of IF taxonomies, one is the full set IF list mainly developed for human error analysis. and the other is the IFs for human reliability analysis (HRA) in probabilistic safety assessment (PSA). Five sets of IF taxonomy among the full set IF list and ten sets of IF taxonomy among HRA methodologies were collected in the study. From the review and analysis of BRA IFs, we could obtain some insights for the selection of HRA IFs. By considering the situational characteristics of the accident management domain, candidate IFs are chosen. Finally, those IFs are structured hierarchically to be appropriate for the use in the assessment of human error under accident management situation. Three nuclear accidents such as TMI. Chernobyl and JCO were analysed to validate the proposed taxonomy.