• Radiation Oncology Journal
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• 제31권2호
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• pp.88-96
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• 2013

Purpose: This study identifies accident sequences from the past accidents in order to help the risk analysis application to the external radiotherapy. Materials and Methods: This study reviews 59 accidental cases in two retrospective safety analyses that have collected the incidents in the external radiotherapy extensively. Two accident analysis reports that accumulated past incidents are investigated to identify accident sequences including initiating events, failure of safety measures, and consequences. This study classifies the accidents by the treatments stages and sources of errors for initiating events, types of failures in the safety measures, and types of undesirable consequences and the number of affected patients. Then, the accident sequences are grouped into several categories on the basis of similarity of progression. As a result, these cases can be categorized into 14 groups of accident sequence. Results: The result indicates that risk analysis needs to pay attention to not only the planning stage, but also the calibration stage that is committed prior to the main treatment process. It also shows that human error is the largest contributor to initiating events as well as to the failure of safety measures. This study also illustrates an event tree analysis for an accident sequence initiated in the calibration. Conclusion: This study is expected to provide sights into the accident sequences for the prospective risk analysis through the review of experiences.

• 한국안전학회지
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• 제35권3호
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• pp.86-95
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• 2020

This paper describes the work and the results of the final Probabilistic Safety Assessment (PSA) for the Jordan Research and Training Reactor (JRTR). This final PSA was undertaken to assess the level of safety for the design of a research reactor and to evaluate whether it is probabilistically safe to operate and reliable to use. The scope of the PSA described here is a Level 1 PSA, which addresses the risks associated with core damage. After reviewing the documents and its conceptual design, nine typical initiating events were selected regarding internal events during the normal operation of the reactor. AIMS-PSA (Version 1.2c) was used for the accident quantification, and FTREX was used as the quantification engine. 1.0E-15/yr of the cutoff value was used to deliminate the non-effective Minimal Cut Sets (MCSs) when quantifying the JRTR PSA model. As a result, the final result indicates a point estimate of 2.02E-07/yr for the overall Core Damage Frequency (CDF) attributable to internal initiating events in the core damage state for the JRTR. A Loss of Primary Cooling System Flow (LOPCS) is the dominant contributor to the total CDF by a single initiating event (9.96E-08/yr), and provides 49.4% of the CDF. General Transients (GTRNs) are the second largest contributor, and provide 32.9% (6.65E-08/yr) of the CDF.

• Nuclear Engineering and Technology
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• 제53권2호
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• pp.498-508
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• 2021

Micro reactors are increasingly being considered for utilization as distributed power sources. Hence, the probabilistic safety assessment (PSA) of a direct supercritical-CO₂-cooled fast reactor, called micro modular reactor (MMR), was performed in this study; this reactor was developed using innovative design concepts. It adopted a modular design and passive safety systems to minimize site constraints. As the MMR is in its conceptual design phase, design weaknesses and valuable safety insights could be identified during PSA. Level 1 internal event PSA was carried out involving literature survey, system characterization, identification of initiating events, transient analyses, development of event trees and fault trees, and quantification. The initiating events and scenarios significantly contributing to core damage frequency (CDF) were determined to identify design weaknesses in MMR. The most significant initiating event category contributing to CDF was the transients with the power conversion system initially available category, owing to its relatively high occurrence frequency. Further, an importance analysis revealed that the safety of MMR can be significantly improved by improving the reliability of reactor trip and passive decay heat removal system operation. The findings presented in this paper are expected to contribute toward future applications of PSA for assessing unconventional nuclear reactors in their conceptual design phases.

• 한국원자력학회:학술대회논문집
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• 한국원자력학회 2004년도 요약집 춘계학술발표대회
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• pp.181.1-181.1
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• 2004

• Nuclear Engineering and Technology
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• 제52권1호
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• pp.211-221
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• 2020

One fundamental element of probabilistic safety assessment (PSA) is the initiating event (IE) analysis. Since IE frequencies can change over time, time-trend analysis is required to obtain optimized IE frequencies. Accordingly, such time-trend analyses have been employed to estimate industry-average IE frequencies for use in the PSAs of U.S. nuclear power plants (NPPs); existing PSAs of Korean NPPs, however, neglect such analysis in the estimation of IE frequencies. This article therefore provides the method for and results of estimating Korean industry-average IE frequencies using time-trend analysis. It also examines the effects of the IE frequencies obtained from this study on risk insights by applying them to recently updated internal events Level 1 PSA models (at-power and shutdown) for an OPR-1000 plant. As a result, at-power core damage frequency decreased while shutdown core damage frequency increased, with the related contributions from each IE category changing accordingly. These results imply that the incorporation of time-trend analysis leads to different IE frequencies and resulting risk insights. The IE frequency distributions presented in this study can be used in future PSA updates for Korean NPPs, and should be further updated themselves by adding more recent data.

• Nuclear Engineering and Technology
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• 제43권2호
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• pp.105-132
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• 2011

The concept of improved performance indicators (PIs) for use in the KINS Safety Performance Indicator (SPI) program for reactor safety area is proposed in this paper. To achieve this, the recently developed PIs from the USNRC that use risk information were investigated, and a feasibility study for the application of these PIs in Korean NPPs was performed. The investigated PIs are Baseline Risk Index for Initiating Events (BRIIE), Unplanned Scrams with Complications (USwC), and Mitigating System Performance Index (MSPI). Moreover, the thresholds of the existing safety performance indicators of KINS were evaluated in consideration of the risk and regulatory response to different levels of licensee performance in the graded inspection program.

• 한국원자력학회:학술대회논문집
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• 한국원자력학회 2004년도 추계학술발표회 발표논문집
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• pp.353-354
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• 2004

• 한국원자력학회:학술대회논문집
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• 한국원자력학회 2005년도 춘계학술발표회
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• pp.55-56
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• 2005

• Nuclear Engineering and Technology
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• 제43권3호
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• pp.271-278
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• 2011

When performing fire PSA in a nuclear power plant, an event mapping method, using an internal event PSA model, is widely used to reduce the resources used by fire PSA model development. Feasible initiating events and component failure events due to fire are identified to transform the fault tree (FT) for an internal event PSA into one for a fire PSA using the event mapping method. A surrogate event or damage term method is used to condition the FT of the internal PSA. The surrogate event or the damage term plays the role of flagging whether the system/component in a fire compartment is damaged or not, depending on the fire being initiated from a specified compartment. These methods usually require explicit states of all compartments to be modeled in a fire area. Fire event scenarios, when using explicit identification, such as surrogate or damage terms, have two problems: (1) there is no consideration of multiple fire propagation beyond a single propagation to an adjacent compartment, and (2) there is no consideration of simultaneous fire propagations in which an initiating fire event is propagated to multiple paths simultaneously. The present paper suggests a fire propagation equation to identify all possible fire event scenarios for an explicitly treated fire event scenario in the fire PSA. Also, a method for separating fire events was developed to make all fire events a set of mutually exclusive events, which can facilitate arithmetic summation in fire risk quantification. A simple example is given to confirm the applicability of the present method for a $2{\times}3$ rectangular fire area. Also, a feasible asymptotic approach is discussed to reduce the computational burden for fire risk quantification.

• Nuclear Engineering and Technology
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• 제44권4호
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• pp.393-404
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• 2012

After the Fukushima nuclear accident in 2011, there has been increasing concern regarding severe accidents in nuclear facilities. Severe accident scenarios are difficult for operators to monitor and identify. Therefore, accurate prediction of a severe accident is important in order to manage it appropriately in the unfavorable conditions. In this study, artificial intelligence (AI) techniques, such as support vector classification (SVC), probabilistic neural network (PNN), group method of data handling (GMDH), and fuzzy neural network (FNN), were used to monitor the major transient scenarios of a severe accident caused by three different initiating events, the hot-leg loss of coolant accident (LOCA), the cold-leg LOCA, and the steam generator tube rupture in pressurized water reactors (PWRs). The SVC and PNN models were used for the event classification. The GMDH and FNN models were employed to accurately predict the important timing representing severe accident scenarios. In addition, in order to verify the proposed algorithm, data from a number of numerical simulations were required in order to train the AI techniques due to the shortage of real LOCA data. The data was acquired by performing simulations using the MAAP4 code. The prediction accuracy of the three types of initiating events was sufficiently high to predict severe accident scenarios. Therefore, the AI techniques can be applied successfully in the identification and monitoring of severe accident scenarios in real PWRs.