• International Journal of Safety
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• v.2 no.1
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• pp.50-56
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• 2003

There are a lot of uncertainties in the severe accident phenomena and scenarios in nuclear power plants (NPPs) and one of the major issues for severe accident management is the reduction of these uncertainties. The severe accident management aid system using Probabilistic Safety Assessments (PSA) technology is developed for the management staff in order to reduce the uncertainties. The developed system includes the graphical display for plant and equipment status, previous research results by a knowledge-base technique, and the expected plant behavior using PSA. The plant model used in this paper is oriented to identify plant response and vulnerabilities via analyzing the quantified results, and to set up a framework for an accident management program based on these analysis results. Therefore the developed system may playa central role of information source for decision-making for severe accident management, and will be used as a training tool for severe accident management.

• Communications for Statistical Applications and Methods
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• v.8 no.2
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• pp.453-464
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• 2001

A commercial nuclear power station contains at least tow emergency diesel generators(EDG) to control the risk of severe core damage during station blackout accidents. Therefore, the reliability of the EDG's to start and load-run on demand must be maintained at a sufficiently high level. Probabilistic safety assessments(PSA) are increasingly being used to quantify the public risk of operating potentially hazardous systems such as nuclear power reactors. In this paper, to perform PSA, we will introduce three different types of data and use Bayes procedure to estimate the error rate of nuclear power plant EDG, and using practical examples, illustrate which method is more reasonable in our situation.

• Nuclear Engineering and Technology
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• v.53 no.11
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• pp.3465-3473
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• 2021

For a long time, research into integrated deterministic-probabilistic safety assessment has been continuously conducted to point out and overcome the limitations of classical ET (event tree)/FT (fault tree) based PSA (probabilistic safety assessment). The current paper also attempts to assert the reason why a technical transformation from classical PSA is necessary with a re-interpretation of the categories of risk. In this study, residual risk was classified into interpolating- and extrapolating-censored categories, which represent risks that are difficult to identify through an interpolation or extrapolation of representative scenarios due to potential nonlinearity between hardware and human behaviors intertwined in time and space. The authors hypothesize that such risk can be dealt with only if the classical ETs/FTs are freely relocated, entailing large-scale computation associated with physical models. The functional elements that are favorable to find residual risk were inferred from previous studies. The authors then introduce their under-development enabling techniques, namely DICE (Dynamic Integrated Consequence Evaluation) and DeBATE (Deep learning-Based Accident Trend Estimation). This work can be considered as a preliminary initiative to find the bridging points between deterministic and probabilistic assessments on the pillars of big data technology.

• Nuclear Engineering and Technology
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• v.50 no.8
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• pp.1246-1254
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• 2018

The importance of performing Level 3 probabilistic safety assessments (PSA) along with a general interest in assessing multi-unit risk has been sharply increasing after the Fukushima Daiichi nuclear power plant (NPP) accident. However, relatively few studies on multi-unit Level 3 PSA have been performed to date, reflecting limited scenarios of multi-unit accidents with higher priority. The major difficulty to carry out a multi-unit Level 3 PSA lies in the exponentially increasing number of multi-unit accident combinations, as different source terms can be released from each NPP unit; indeed, building consequence models for the astronomical number of accident scenarios is simply impractical. In this study, a new approach has been developed that employs the look-up table method to cover every multi-unit accident scenario. Consequence results for each scenario can be found on the table, established with a practical amount of effort, and can be matched to the frequency of the scenario. Preliminary application to a six-unit NPP site was carried out, where it was found that the difference between full-coverage and cut-off cases could be considerably high and therefore influence the total risk. Additional studies should be performed to fine tune the details and overcome the limitations of the approach.

• Nuclear Engineering and Technology
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• v.37 no.3
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• pp.207-220
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• 2005

Nuclear power plants (NPP) are complex socio-technological systems that rely on the success of both hardware and human components. Empirical studies of plant operating experience show that human errors are important contributors to accidents and incidents, and that organizational factors play an important role in creating contexts for human errors. Current probabilistic safety assessments (PSA) do not explicitly model the systematic contribution of organizational factors to safety. As some countries, like the United States, are moving towards increased use of risk information in the regulation and operation of nuclear facilities, PSA quality has been identified as an area for improvement. The modeling of human errors, and underlying organizational weaknesses at the root of these errors, are important sources of uncertainty in existing PSAs and areas of on-going research. This paper presents a review of research into the following questions: Is there evidence that organizational factors are important to NPP safety? How do organizations contribute to safety in NPP operations? And how can these organizational contributions be captured more explicitly in PSA? We present a few past incidents that illustrate the potential safety implications of organizational deficiencies, some mechanisms by which organizational factors contribute to NPP risk, and some of the methods proposed in the literature for performing root-cause analyses and including organizational factors in PSA.

• Nuclear Engineering and Technology
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• v.53 no.10
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• pp.3247-3255
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• 2021

As Probabilistic Safety Assessments (PSAs) are thoroughly conducted for the Site Operating States (SOSs) for a single unit, multi-unit Probabilistic Safety Assessments (MUPSAs) are ongoing worldwide to address new technical challenges or issues. In South Korea, the determination of the site operating states for a single site requires a logical approach with reasonable assumptions due to the fact that there are 4-8 operating units for each site. This paper suggests a simulation model that gives a reasonable expectation of the site operation states using the Monte-Carlo method as a stochastic approach and deterministic aspects such as operational policies. Statistical hypothesis tests were conducted so that the reliance of the simulation results can be guaranteed. In this study, 7 units of the Kori site were analysed as a case study. The result shows that the fraction of full power for all 7 units is nearly 0.45. For situations when more than two units are not in operation, the highest fraction combination was obtained for Plant Operation State (POS) 8, which is the stage of inspection and repairment. By entering various site operation scenarios, the simulation model can be used for the analysis of other site operation states.

• Nuclear Engineering and Technology
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• v.51 no.5
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• pp.1297-1306
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• 2019

Probabilistic safety assessments (PSA) have been used for several decades to visualize the risk level of commercial nuclear power plants (NPPs). Since the role of a human reliability analysis (HRA) is to provide human error probabilities for safety critical tasks to support PSA, PSA quality is strongly affected by HRA quality. Therefore, it is important to understand the underlying limitations or problems of HRA techniques. For this reason, this study conducted a survey among 14 subject matter experts who represent the HRA community of domestic Korean NPPs. As a result, five significant HRA issues were identified: (1) providing a technical basis for the K-HRA (Korean HRA) method, and developing dedicated HRA methods applicable to (2) diverse external events to support Level 1 PSA, (3) digital environments, (4) mobile equipment, and (5) severe accident management guideline tasks to support Level 2 PSA. In addition, an HRA method to support multi-unit PSA was emphasized because it plays an important role in the evaluation of site risk, which is one of the hottest current issues. It is believed that creating such a catalog of prioritized issues will be a good indication of research direction to improve HRA and therefore PSA quality.

• Nuclear Engineering and Technology
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• v.54 no.8
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• pp.2924-2932
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• 2022

Motivated by learning from experience and exploiting existing knowledge in civil nuclear operations, we have developed in-house generic Probabilistic Safety Assessment (PSA) models for pressurized and boiling water reactors. The models are computationally light, handy, transparent, user-friendly, and easily adaptable to account for major plant-specific differences. They cover the common internal initiating events, frontline and support systems reliability and dependencies, human-factors, common-cause failures, and account for new factors typically overlooked in many PSAs. For quantification, the models use generic US reliability data, precursor analysis reports, the ETHZ Curated Nuclear Events Database, and experts' opinions. Moreover, uncertainties in the most influential basic events are addressed. The generated results show good agreement with assessments available in the literature with detailed PSAs. We envision the models as an unbiased framework to measure nuclear operational risk with the same "ruler", and hence support inter-plant risk comparisons that are usually not possible due to differences in plant-specific PSA assumptions and scopes. The models can be used for initial risk screening, order-of-magnitude precursor analysis, and other research/pedagogic applications especially when no plant-specific PSAs are available. Finally, we are using the generic models for large-scale precursor analysis that will generate big picture trends, lessons, and insights.

• Nuclear Engineering and Technology
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• v.49 no.2
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• pp.295-305
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• 2017

This paper reviews current status of the unified approach known as integrated safety assessment (ISA), as well as the associated SCAIS (simulation codes system for ISA) computer platform. These constitute a proposal, which is the result of collaborative action among the Nuclear Safety Council (CSN), University of Madrid (UPM), and NFQ Solutions S.L, aiming to allow independent regulatory verification of industry quantitative risk assessments. The content elaborates on discussions of the classical treatment of time in conventional probabilistic safety assessment (PSA) sequences and states important conclusions that can be used to avoid systematic and unacceptable underestimation of the failure exceedance frequencies. The unified ISA method meets this challenge by coupling deterministic and probabilistic mutual influences. The feasibility of the approach is illustrated with some examples of its application to a real size plant.

• Proceedings of the Korean Nuclear Society Conference
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• 1996.05b
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• pp.493-498
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• 1996

A PC window-based computer code, CONPAS(CONtainment Performance Analysis System), has been developed to integrate the numerical, graphical and results-operation aspects of Level 2 probabilistic safety assessments (PSA) for nuclear power plants automatically. As a main logic for accident progression analysis, it employs a concept of the small containment phenomenological event tree(CPET) helpful to trace out visually individual accident progressions and of the large supporting event tree(LSET) for its detailed quantification. Compared with other existing computer codes for Level 2 PSA, the CONPAS code provides several advanced features: computational aspects including systematic uncertainty analysis, importance analysis, and sensitivity analysis, reporting aspects including tabling and graphic, and user-friend interface.