• Journal of the Korean Society of Safety
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• v.12 no.4
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• pp.241-248
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• 1997

This paper presents the development procedure and application of the generic component reliability data base considering the dependency among dependent generic compendia in NPPs (Nuclear Power Plants) PSA (Probabilistic Safety Assessment) under construction or without operating history. We use MPRDP (Multi-Purpose Reliability Data Processor) code developed in KAERI (Korea Atomic Energy Research Institute) based on a PEB (Parametric Empirical Bayesian) procedure to estimate the reliability. The employed model in this study accounts for the relative credibility as well as the dependency among generic estimates. Numerical examples and the part of summarized reliability data table are provided as the application.

• Journal of the Korean Society of Safety
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• v.14 no.2
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• pp.178-191
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• 1999

More than twenty methods were suggested for Human Reliability Analysis (HRA) in the field of safety analysis for Nuclear Power Plants (NPPs). However, there is still a high uncertainty on the analysis and a difficulty in performing HRA. New methods and approaches are under studying to overcome such limitations of current HRA. This paper presents some results of study to analysis limitations of current HRA in viewpoint of user, i.e., HRA analyst. The limitation analysis was based on 89 human error events modeled in a Probabilistic Safety Assessment (PSA) project for NPPs in Korea. Total 17 specific limitations were identified and categorized into seven groups. Important analysis has also been undertaken to assess the order of priority among those limitations. Finally, seven requirements with priority ranking were generated for an advanced framework and methodology of HRA.

• Journal of the Korean Society of Safety
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• v.30 no.3
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• pp.100-106
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• 2015

A module or independent subtree is a part of a fault tree whose child gates or basic events are not repeated in the remaining part of the fault tree. Modules are necessarily employed in order to reduce the computational costs of fault tree quantification. This quantification generates fault tree solutions such as minimal cut sets, minimal path sets, or binary decision diagrams (BDDs), and then, calculates top event probability and importance measures. This paper presents a new linear time algorithm to detect modules of large fault trees. It is shown through benchmark tests that the new method proposed in this study can very quickly detect the modules of a huge fault tree. It is recommended that this method be implemented into fault tree solvers for efficient probabilistic safety assessment (PSA) of nuclear power plants.

• Nuclear Engineering and Technology
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• v.53 no.2
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• pp.509-521
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• 2021

In this paper, from a review of the size distribution of the bubbles during pool scrubbing obtained from experiments by EPRI, we apply the bubble size distributions to analyses on the decontamination factors of pool scrubbing via I-COSTA (In-Containment Source Term Analysis). We perform sensitivity studies of the bubble size on the various mechanisms of deposition of aerosol particles in pool scrubbing. We also perform sensitivity studies on the size distributions of the bubbles depending on the diameters at the nozzle exit, the molecular weights of non-condensable gases in the carrier gases, and the steam fractions of the carrier gases. We then perform analyses of LACE-ESPANA experiments and compare the numerical ~ results to those from SPARC-90 and experimental results in order to show the effect of the bubble size distributions.

• Nuclear Engineering and Technology
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• v.56 no.9
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• pp.3851-3863
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• 2024

The speed of offsite consequence analysis is highly important due to the extensive calculations required to handle all the scenarios for a single-unit or multi-unit Level 3 PSA (probabilistic safety assessment). To perform an offsite consequence analysis as part of Level 3 PSA, various input parameters are considered, amongst which certain parameters, such as plume segments, spatial grids, and particle size distributions, have flexible input formats. This study describes the development of an effective optimization method to reduce the analysis time as much as possible while maintaining the accuracy of the offsite consequence analysis results. The effect of plume segmentation on offsite consequence analysis was investigated by observing deviations in analysis results and changes in the required analysis times following changes in plume release. Then a plume segmentation optimization method based on the cumulative release fraction slope was developed to intensively analyze the sections with rapid release and to simplify the analysis for the sections with nonsignificant release. As a result of applying this method, the analysis time was reduced by about 54.5 % compared to the base case, while the resulting health effects showed very small deviations of 0.03 % and 1.77 % for early fatality risk and cancer fatality risk, respectively.

• Nuclear Engineering and Technology
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• v.54 no.3
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• pp.896-908
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• 2022

As a part of probabilistic risk (or safety) assessment (PRA or PSA) of nuclear power plants (NPPs), the primary role of human reliability analysis (HRA) is to provide credible estimations of the human error probabilities (HEPs) of safety-critical tasks. In this regard, it is vital to provide credible HEPs based on firm technical underpinnings including (but not limited to): (1) how to collect HRA data from available sources of information, and (2) how to inform HRA practitioners with the collected HRA data. Because of these necessities, the U.S. Nuclear Regulatory Commission and the Korea Atomic Energy Research Institute independently developed two dedicated HRA data collection systems, SACADA (Scenario Authoring, Characterization, And Debriefing Application) and HuREX (Human Reliability data EXtraction), respectively. These systems provide unique frameworks that can be used to secure HRA data from full-scope training simulators of NPPs (i.e., simulator data). In order to investigate the applicability of these two systems, two papers have been prepared with distinct purposes. The first paper, entitled "SACADA and HuREX: Part 1. The Use of SACADA and HuREX Systems to Collect Human Reliability Data", deals with technical issues pertaining to the collection of HRA data. This second paper explains how the two systems are able to inform HRA practitioners. To this end, the process of estimating HEPs is demonstrated based on feed-and-bleed operations using HRA data from the two systems.

• Nuclear Engineering and Technology
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• v.54 no.5
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• pp.1686-1697
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• 2022

As a part of probabilistic risk (or safety) assessment (PRA or PSA) of nuclear power plants (NPPs), the primary role of human reliability analysis (HRA) is to provide credible estimations of the human error probabilities (HEPs) of safety-critical tasks. Accordingly, HRA community has emphasized the accumulation of HRA data to support HRA practitioners for many decades. To this end, it is critical to resolve practical problems including (but not limited to): (1) how to collect HRA data from available information sources, and (2) how to inform HRA practitioners with the collected HRA data. In this regard, the U.S. Nuclear Regulatory Commission (NRC) and Korea Atomic Energy Research Institute (KAERI) independently initiated two large projects to accumulate HRA data by using full-scale simulators (i.e., simulator data). In terms of resolving the first practical problem, the NRC and KAERI developed two dedicated HRA data collection systems, SACADA (Scenario Authoring, Characterization, And Debriefing Application) and HuREX (Human Reliability data EXtraction), respectively. In addition, to inform HRA practitioners, the NRC and KAERI proposed several ideas to extract useful information from simulator data. This paper is the first of two papers to discuss the technical underpinnings of the development of the SACADA and HuREX systems.

• Transactions of the Korean Society of Pressure Vessels and Piping
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• v.7 no.4
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• pp.31-37
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• 2011

Pressurized Water Reactor Owners Group(PWROG) proposed and applied a risk-informed inservice inspection(RI-ISI) program to alternate existing ASME Section XI periodic inspections. The RI-ISI programs enhance overall safety by focusing inspections of piping at high safety significant(HSS) and locations where failure mechanisms are likely to be present, and by improving the effectiveness on inspection of components because the examination methods are based on the postulated failure mode and the configuration of the piping structural element. The RI-ISI programs can reduce NDE, man-rem exposure, costs of engineering analysis, outage duration and chance of complicating plant operations etc. RI-ISI methods of piping inservice inspection were applied on 3 units(KSNP : Korea Standard Nuclear Power Plant) and are scheduled to apply on the other units. In this paper, we compared and showed the results of the 2 units and we concluded that the RI-ISI application could enhance and maintain plant safety and give unquantifiable benefits.

• Journal of Korean Society for Quality Management
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• v.39 no.2
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• pp.320-328
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• 2011

This research proposes comprehensive models for analyzing common cause failures (CCF) due to cumulative shocks and to assess system reliability under the CCF. The proposed cumulative shock models are based on the binomial failure rate (BFR) model. Six kinds of models are proposed so as to explain diverse cumulative shock phenomena. The models are composed of the initial failure probability, shape parameter, and the total shock number. Some parameters of the proposed models can not be explicitly estimated, so we adopt the Expectation-maximization (EM) algorithm in order to obtain the maximum likelihood estimator (MLE) for the parameters. By estimating the parameters for the cumulative shock models, the system reliability with CCF can be assessed sequentially according to the number of cumulative shocks. The result can be utilizes in dynamic probabilistic safety assessment (PSA), aging studies, or risk management for nuclear power plants. Replacement or maintenance policies can also be developed based on the proposed model.

• 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.