• 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.

• Nuclear Engineering and Technology
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• v.40 no.5
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• pp.349-364
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• 2008

Over the years, probabilistic risk assessment (PRA) research activities conducted at the U.S. Nuclear Regulatory Commission (NRC) have played an essential role in support of the agency's move towards risk-informed regulation. These research activities have provided the technical basis for NRC's regulatory activities in key areas; provided PRA methods, tools, and data enabling the agency to meet future challenges; supported the implementation of NRC's 1995 PRA Policy Statement by assessing key sources of risk; and supported the development of necessary technical and human resources supporting NRC's risk-informed activities. PRA research aimed at improving the NRC's understanding of risk can positively affect the agency's regulatory activities, as evidenced by three case studies involving research on fire PRA, human reliability analysis (HRA), and pressurized thermal shock (PTS) PRA. These case studies also show that such research can take a considerable amount of time, and that the incorporation of research results into regulatory practice can take even longer. The need for sustained effort and appropriate lead time is an important consideration in the development of a PRA research program aimed at helping the agency address key sources of risk for current and potential future facilities.

• Nuclear Engineering and Technology
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• v.50 no.5
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• pp.627-638
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• 2018

This article describes an integrated Level 1-Level 2 probabilistic risk assessment (PRA) methodology to evaluate the radiological risk during postulated accident scenarios initiated during the decommissioning phase of a typical Mark I containment boiling water reactor. The fuel damage scenarios include those initiated while the reactor is permanently shut down, defueled, and the spent fuel is located into the spent fuel storage pool. This article focuses on the integrated Level 1-Level 2 PRA aspects of the analysis, from the beginning of the accident to the radiological release into the environment. The integrated Level 1-Level 2 decommissioning PRA uses event trees and fault trees that assess the accident progression until and after fuel damage. Detailed deterministic severe accident analyses are performed to support the fault tree/event tree development and to provide source term information for the various pieces of the Level 1-Level 2 model. Source terms information is collected from accidents occurring in both the reactor pressure vessel and the spent fuel pool, including simultaneous accidents. The Level 1-Level 2 PRA model evaluates the temporal and physical changes in plant conditions including consideration of major uncertainties. The goal of this article is to provide a methodology framework to perform a decommissioning Probabilistic Risk Assessment (PRA), and an application to a real case study is provided to show the use of the methodology. Results will be derived from the integrated Level 1-Level 2 decommissioning PSA event tree in terms of fuel damage frequency, large release frequency, and large early release frequency, including uncertainties.

• Journal of the Korean Society of Safety
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• v.18 no.2
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• pp.98-103
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• 2003

Based on ASME probabilistic risk assessment (PRA) and NEI PRA peer review guidance, we evaluate a human reliability analysis (HRA) in probabilistic safety assessment (PSA) for Korea standard nuclear power plants, Ulchin Unit 3&4, to improve it performed at under design. The HRA for Ulchin Unit 3&4 is assessed as higher than Grade I based on ASME PRA standard and as higher than Grade 2 based on NEI PRA peer review guidance. The major items to be improved identified through the evaluation process are the documentation, the systematic human reliability analysis, the participitation of operators in the works and review of HRA. We suggest the guidance on the identification and qualitative screening analysis for pre-accident human errors and solve some items to be improved using the suggested guidance.

• Journal of Korean Society of Transportation
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• v.23 no.3 s.81
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• pp.95-108
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• 2005

The purpose of this study is to develop the ITS evaluation model using the Probabilistic Risk Analysis (PRA) methodology and to demonstrate the goodness-of-fit of the large ITS projects through the comparative analysis between DEA and PRA model. The results of this study are summarized below. First, the evaluation mode] using PRA with Monte-Carlo Simulation(MCS) and Latin-Hypercube Sampling(LHS) is developed and applied to one of ITS projects initiated by local government. The risk factors are categorized with cost, benefit and social-economic factors. Then, PDF(Probability Density Function) parameters of these factors are estimated. The log-normal distribution, beta distribution and triangular distribution are well fitted with the market and delivered price. The triangular and uniform distributions are valid in benefit data from the simulation analysis based on the several deployment scenarios. Second, the decision making rules for the risk analysis of projects for cost and economic feasibility study are suggested. The developed PRA model is applied for the Daejeon metropolitan ITS model deployment project to validate the model. The results of cost analysis shows that Deterministic Project Cost(DPC), Deterministic Total Project Cost(DTPC) is the biased percentile values of CDF produced by PRA model and this project need Contingency Budget(CB) because these values are turned out to be less than Target Value(TV;85% value), Also, this project has high risk of DTPC and DPC because the coefficient of variation(C.V) of DTPC and DPC are 4 and 15 which are less than that of DTPC(19-28) and DPC(22-107) in construction and transportation projects. The results of economic analysis shows that total system and subsystem of this project is in type II, which means the project is economically feasible with high risk. Third, the goodness-of-fit of PRA model is verified by comparing the differences of the results between PRA and DEA model. The difference of evaluation indices is up to 68% in maximum. Because of this, the deployment priority of ITS subsystems are changed in each mode1. In results. ITS evaluation model using PRA considering the project risk with the probability distribution is superior to DEA. It makes proper decision making and the risk factors estimated by PRA model can be controlled by risk management program suggested in this paper. Further research not only to build the database of deployment data but also to develop the methodologies estimating the ITS effects with PRA model is needed to broaden the usage of PRA model for the evaluation of ITS projects.

• Proceedings of the Earthquake Engineering Society of Korea Conference
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• 2000.04a
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• pp.226-232
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• 2000

Seismic probabilistic risk assessment(RA) rather than deterministic assessment provides more valuable information and insight for resolving seismic safety issues in nuclear power plant design. In the course of seismic PRA seismic fragility analysis is the most significant and essential phase especially for structural or mechanical engineers. Lately the seismic fragility analysis is taken as a useful tool in general structural engineering as well. A systemized and synthesized procedure or technology related to seismic fragility analysis of critical industrial facilities reflecting the unique experiences and database in Korea is urgently required. This paper gives a state-of-the-art reviews of PRA and briefly summarizes the technologies related to PRA and seismic fragility analysis before developing an unique technology considering characteristics of Korean database. Some key items to be resolved theoretically or technically are extracted and presented for the future research.

• Journal of Information Technology Applications and Management
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• v.16 no.3
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• pp.59-71
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• 2009

Hazard analysis identifies probability to hazard occurrence and its potential impact on business processes operated in organizations. This paper illustrates a quantitative approach of hazard analysis of information systems by measuring the degree of hazard to information systems using probabilistic risk analysis and activity based costing technique. Specifically the research model projects probability of occurrence by PRA and economic loss by ABC under each identified hazard. To verify the model, each computerized subsystem which is called a business process and hazards occurred on information systems are gathered through one private organization. The loss impact of a hazard occurrence is produced by multiplying probability by the economic loss.

• Proceedings of the KSR Conference
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• 2003.10b
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• pp.265-270
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• 2003

Though the probability of tunnel fire accident is very low, but critical fatalities are expected when it occurred. In this study the effect of critical safety parameters on tunnel fire accident are examined using probabilistic technique. Fire detection time, smoke spread velocity, passenger escape velocity, flash-over time, and emergency service arrival time are considered. In order to estimate the uncertainties of input parameters Monte Carlo simulation are used, and fatalities for each assumed accident scenarios are obtained as results. For the efficiency of iterative calculation PRA(Probabilistic Risk Analysis) code is developed in this study. As a result fire detection have large effect.

• Nuclear Engineering and Technology
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• v.49 no.2
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• pp.286-294
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• 2017

The events at the Fukushima Daiichi Nuclear Power Station in March 2011 point out, among other matters, that concurrent accidents at multiple units of a site can occur in reality. Although site risk has been deterministically considered to some extent in nuclear power plant siting and design, potential occurrence of multi-unit accident sequences at a site was not investigated in sufficient detail thus far in the nuclear power community. Therefore, there is considerable worldwide interest and research effort directed toward multi-unit site risk assessment, especially in the countries with high-density nuclear-power-plant sites such as Korea. As the technique of probabilistic safety assessment (PSA) has been successfully applied to evaluate the risk associated with operation of nuclear power plants in the past several decades, the PSA having primarily focused on single-unit risks is now being extended to the multi-unit PSA. In this paper we first characterize the site risk with explicit consideration of the risk associated with spent fuel pools as well as the reactor risks. The status of multi-unit risk assessment is discussed next, followed by a description of the emerging issues relevant to the multi-unit risk evaluation from a practical standpoint.

• Nuclear Engineering and Technology
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• v.53 no.2
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• pp.376-385
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• 2021

Probabilistic risk assessment (PRA) has improved its elemental technologies used for assessing external events since the Fukushima Daiichi Nuclear Power Station Accident in 2011. HRA needs to be improved for analyzing tasks performed under extreme conditions (e.g., different actors responding to external events or performing operations using portable mitigation equipment). To make these improvements, it is essential to understand plant-specific and scenario-specific conditions that affect human performance. The Nuclear Risk Research Center (NRRC) of the Central Research Institute of Electric Power Industry (CRIEPI) has developed an HRA guide that compiles qualitative analysis methods for collecting plant-specific and scenario-specific conditions that affect human performance into "narratives," reflecting the latest research trends, and models for analysis of tasks under extreme conditions.