• Earthquakes and Structures
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• v.9 no.3
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• pp.563-576
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• 2015

Over the past few decades, seismic retrofitting of structural systems has been significantly improved by the adoption of various methods such as FRP composite wraps, base isolation systems, and passive/active damper control systems. In parallel with this trend, probabilistic risk assessment (PRA) for structural and nonstructural components has become necessary for risk mitigation and the achievement of reliable designs in performance-based earthquake engineering. The primary objective of the present study was to evaluate the effect on piping fragility at T-joints due to seismic retrofitting of structural systems with passive energy-dissipation devices (i.e., linear viscous dampers). Three mid-rise building types were considered: without any seismic retrofitting; with distributed damper systems; with optimal placement of dampers. The results showed that the probability of piping system failure was considerably reduced in a Multi Degree of Freedom (MDOF) building retrofitted with optimal passive damper systems at lower floor levels. This effect of damper systems on piping fragility became insignificant as the floor level increased.

• Nuclear Engineering and Technology
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• v.49 no.7
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• pp.1414-1422
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• 2017

Remote response technology has advanced to the extent that a robot system, if properly designed and deployed, may greatly help respond to beyond-design-basis accidents at nuclear power plants. Particularly in the aftermath of the Fukushima accident, there is increasing interest in developing disaster robots that can be deployed in lieu of a human operator to the field to perform mitigating actions in the harsh environment caused by extreme natural hazards. The nuclear robotics team of the Korea Atomic Energy Research Institute (KAERI) is also endeavoring to construct disaster robots and, first of all, is interested in finding out to what extent safety benefits can be achieved by such a disaster robotic system. This paper discusses a new approach based on the probabilistic risk assessment (PRA) technique, which can be used to quantify safety benefits associated with disaster robots, along with a case study for seismic-induced station blackout condition. The results indicate that to avoid core damage in this special case a robot system with reliability > 0.65 is needed because otherwise core damage is inevitable. Therefore, considerable efforts are needed to improve the reliability of disaster robots, because without assurance of high reliability, remote response techniques will not be practically used.

• 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.

• Nuclear Engineering and Technology
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• v.19 no.4
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• pp.279-291
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• 1987

The event tree/fault tree techniques used in the current probabilistic risk assessment (PRA) of nuclear power plants are based on the binary and static description of the components and the system. While these techniques Bay be adequate in most of the safety studies, more advanced techniques, e.g., the Markov reliability analysis, are required to accurately study such problems as the plant availability assessments and technical specifications evaluations that are becoming increasingly important. This paper describes a Markov model for the Reactor Protection System of a pressurized water reactor and presents results of model evaluations for two testing policies in technical specifications.

• Journal of Korean Society for Quality Management
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• v.19 no.2
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• pp.96-107
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• 1991

At the design stage of a plant, the plausible causes and pathways of release of hazardous materials are not clearly known. Thus there exist large amount of uncertainties on the consequences resulting from the operation of a fusion plant. In order to better handle such uncertain circumstances, we utilize the Probabilistic Risk Assessment(PRA) for the safety analyses on fusion power plant. In this paper, we concentrate on the tritium release accident. We develop a simple model that describes the process and flow of tritium, by which we figure out the locations of tritium inventory and their vulnerability. We construct event tree models that lead to various levels of tritium release from abnormal initiating events. Branch parameters on the event tree are assessed from the fault tree analysis. Based on the event tree models we construct influence diagram models which are more useful for the parameter updating and analysis. We briefly discuss the parameter updating scheme, and finally develop the methodology to obtain the predictive distribution of consequences resulting from the operating a fusion power plant. We also discuss the way to utilize the results of testing on sub-systems to reduce the uncertain ties on over all system.

• Nuclear Engineering and Technology
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• v.53 no.8
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• pp.2534-2546
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• 2021

Nuclear emergency preparedness and response is an essential part to ensure the safety of nuclear power plant (NPP). Key support technologies of nuclear emergency decision-making usually consist of accident diagnosis, source term estimation, accident consequence assessment, and protective action recommendation. Source term estimation is almost the most difficult part among them. For example, bad communication, incomplete information, as well as complicated accident scenario make it hard to determine the reactor status and estimate the source term timely in the Fukushima accident. Subsequently, it leads to the hard decision on how to take appropriate emergency response actions. Hence, this paper aims to develop a method for rapid source term estimation to support nuclear emergency decision making in pressurized water reactor NPP. The method aims to make our knowledge on NPP provide better support nuclear emergency. Firstly, this paper studies how to build a Bayesian network model for the NPP based on professional knowledge and engineering knowledge. This paper presents a method transforming the PRA model (event trees and fault trees) into a corresponding Bayesian network model. To solve the problem that some physical phenomena which are modeled as pivotal events in level 2 PRA, cannot find sensors associated directly with their occurrence, a weighted assignment approach based on expert assessment is proposed in this paper. Secondly, the monitoring data of NPP are provided to the Bayesian network model, the real-time status of pivotal events and initiating events can be determined based on the junction tree algorithm. Thirdly, since PRA knowledge can link the accident sequences to the possible release categories, the proposed method is capable to find the most likely release category for the candidate accidents scenarios, namely the source term. The probabilities of possible accident sequences and the source term are calculated. Finally, the prototype software is checked against several sets of accident scenario data which are generated by the simulator of AP1000-NPP, including large loss of coolant accident, loss of main feedwater, main steam line break, and steam generator tube rupture. The results show that the proposed method for rapid source term estimation under nuclear emergency decision making is promising.

• Journal of the Korean Society of Safety
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• v.35 no.1
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• pp.87-96
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• 2020

The purpose of this paper is to develop a fire HRA (Human Reliability Analysis) procedure for full power operation of domestic NPPs (Nuclear Power Plants). For the development of fire HRA procedure, the recent research results of NUREG-1921 in an effort to meet the requirements of the ASME/ANS PRA Standard were reviewed. The K-HRA method, a standard method for HRA of a domestic level 1 PSA (Probabilistic Safety Assessment) and fire related procedures in domestic NPPs were reviewed. Based on the review, a procedure for the fire HRA required for a domestic fire PSA based on the K-HRA method was developed. To this end, HRA issues such as new operator actions required in the event of a fire and complexity of fire situations were considered. Based on the four kinds of HFE (Human Failure Event) developed for a fire HRA in this research, a qualitative analysis such as feasibility evaluation was suggested. And also a quantitative analysis process which consists of screening analysis and detailed analysis was proposed. For the qualitative analysis, a screening analysis by NUREG-1921 was used. In this research, the screening criteria for the screening analysis was modified to reduce vague description and to reflect recent experimental results. For a detailed analysis, the K-HRA method and scoping analysis by NUREG-1921 were adopted. To apply K-HRA to fire HRA for quantification, efforts to modify PSFs (Performance Shaping Factors) of K-HRA to reflect fire situation and effects were made. For example, an absence of STA (Shift Technical Advisor) to command a fire brigade at a fire area is considered and the absence time should be reflected for a HEP (Human Error Probability) quantification. Based on the fire HRA procedure developed in this paper, a case study for HEP quantification such as a screening analysis and detailed analysis with the modified K-HRA was performed. It is expected that the HRA procedure suggested in this paper will be utilized for fire PSA for domestic NPPs as it is the first attempt to establish an HRA process considering fire effects.

• Journal of the Korean Society for Nondestructive Testing
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• v.18 no.5
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• pp.389-397
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• 1998

For an effective and efficient management of large amounts of preservice/inservice inspection(PSI/ISI) data in nuclear power plants, an intellegent Windows 95-based data management program was developed. This program enables the prompt extraction of previously conducted PSI/ISI conditions and results so that the time-consuming data management, painstaking data processing and analysis in the past are avoided. The program extracts, and the associated remedies. Furthermore, additional inspection data and comments can be easily added or deleted for subsequent PSI/ISI operation. Although the initial version of the program was applied to Kori nuclear power plant, this program can be equally applied to other nuclear power plant. And also this program can be used to offer the fundamental data for application of evaluation data related to fracture mechanics analysis(FMA), probabilistic reliability assessment(PRA) of PSI/ISI results, performance demonstration initiative(PDI) and risk-informed ISI based on probability of detection(POD) information of ultrasonic examination. Besides, the program can be further developed as a unique PSI/ISI data management expert system that can be apart of PSI/ISI data management expert system that can be a part of PSI/ISI Total Support System(TSS) for Korean nuclear power plants.