• Journal of Radiation Protection and Research
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• 제48권1호
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• pp.28-43
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• 2023

Background: High-fidelity meteorological data is a prerequisite for the realistic simulation of atmospheric dispersion of radioactive materials near nuclear power plants (NPPs). However, many meteorological models frequently overestimate near-surface wind speeds, failing to represent local meteorological conditions near NPPs. This study presents a new high-resolution (approximately 1 km) meteorological downscaling method for modeling short-range (< 100 km) atmospheric dispersion of accidental NPP plumes. Materials and Methods: Six considerations from literature reviews have been suggested for a new dynamic downscaling method. The dynamic downscaling method is developed based on the Weather Research and Forecasting (WRF) model version 3.6.1, applying high-resolution land-use and topography data. In addition, a new subgrid-scale topographic drag parameterization has been implemented for a realistic representation of the atmospheric surface-layer momentum transfer. Finally, a year-long simulation for the Kori and Wolsong NPPs, located in southeastern coastal areas, has been made for 2016 and evaluated against operational surface meteorological measurements and the NPPs' on-site weather stations. Results and Discussion: The new dynamic downscaling method can represent multiscale atmospheric motions from the synoptic to the boundary-layer scales and produce three-dimensional local meteorological fields near the NPPs with a 1.2 km grid resolution. Comparing the year-long simulation against the measurements showed a salient improvement in simulating near-surface wind fields by reducing the root mean square error of approximately 1 m/s. Furthermore, the improved wind field simulation led to a better agreement in the Eulerian estimate of the local atmospheric dispersion. The new subgrid-scale topographic drag parameterization was essential for improved performance, suggesting the importance of the subgrid-scale momentum interactions in the atmospheric surface layer. Conclusion: A new dynamic downscaling method has been developed to produce high-resolution local meteorological fields around the Kori and Wolsong NPPs, which can be used in short-range atmospheric dispersion modeling near the NPPs.

• 한국압력기기공학회 논문집
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• 제10권1호
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• pp.70-74
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• 2014

An Operating Experience Report(OER) has written about events and accidents happened at a Nuclear Power Plant(NPP). The purpose of publishing the OER is to prevent the similar event or accident repeatedly by spreading the experience of a single plant to other plants personnel. In this paper, it is analyses that the foreign NPPs' OERs on JIT published by the International Nuclear Agency(WANO, INPO, COG, BE). The analysis introduced in this paper is performed along with the various factors such as type of work, root-cause, and equipment. The root-cause analysis about the OERs shows that the Human-error is the major factor in foreign NPPs, but on the other hand equipment problem is the main part of the Domestic NPPs. The ratio of the foreign NPP's OERs on JIT according to the type of work was applied to KHNP-JIT developed nowadays for the first time in KOREA.

• 한국압력기기공학회 논문집
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• 제9권1호
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• pp.35-39
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• 2013

The Operating Experience Report(OER) has written about the event and accident happened at a Nuclear Power Plant(NPP). The purpose of publishing the OER is to prevent the similar event or accident repeatedly by spreading the experience of a single plant to other plants personnel. Before initiating the analysis mentioned in this paper, 2,298 review reports for the same number of OER published from 2007 to June 2012 have been written to achieve the correct and objective statistics. The analysis introduced in this paper is performed with the various factors such as year, plant type, equipment, type of work, root-cause. The root-cause analysis is showed that the equipment problem is the major factor in domestic NPPs, but on the other hand human-error is the main part of the foreign NPPs. Moreover, while the number of the man-made event is decreasing, the equipment-made event is rapidly increasing in domestic NPPs.

• Nuclear Engineering and Technology
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• 제31권6호
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• pp.8-22
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• 1999

This study was performed to comparatively evaluate selected Human Reliability Analysis (HRA) methods which mainly focus on cognitive error analysis, and to derive the requirement of a new human error analysis (HEA) framework for Accident Management (AM) in Nuclear Power Plants (NPPs). In order to achieve this goal, we carried out a case study of human error analysis on an AM task in NPPs. In the study we evaluated three cognitive HEA methods, HRMS, CREAM and PHECA, which were selected through the review of the currently available seven cognitive HEA methods. The task of reactor cavity flooding was chosen for the application study as one of typical tasks of AM in NPPs. From the study, we derived seven requirement items for a new HEA method of AM in NPPs. We could also evaluate the applicability of three cognitive HEA methods to AM tasks. CREAM is considered to be more appropriate than others for the analysis of AM tasks, HRMS is also applicable to the error analysis of AM tasks. But, PHECA is regarded less appropriate for the predictive HEA technique as well as for the analysis of AM tasks. In addition to these, the advantages and disadvantagesofeachmethodaredescribed.

• Nuclear Engineering and Technology
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• 제50권1호
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• pp.88-96
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• 2018

Concerns over reliability assessments of the main components in nuclear power plants (NPPs) related to aging and continuous operation have increased. The conventional reliability assessment for main components uses experimental correlations under general conditions. Most NPPs have been operating in Korea for a long time, and it is predictable that NPPs operating for the same number of years would show varying extent of aging and degradation. The conventional reliability assessment does not adequately reflect the characteristics of an individual plant. Therefore, the reliability of individual components and an individual plant was estimated according to operating data and conditions. It is essential to reflect aging as a characteristic of individual NPPs, and this is performed through prognostics. To handle this difficulty, in this paper, the general path model/Bayes, a data-based prognostic method, was used to update the reliability estimated from the generic database. As a case study, the authors consider the aging for steam generator tubes in NPPs and demonstrate the suggested methodology with data obtained from the probabilistic algorithm for the steam generator tube assessment program.

• 대한인간공학회지
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• 제25권3호
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• pp.77-83
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• 2006

The purpose of this study is to assess the organizational types and the job stress factors that affect the procedure-based job performances in nuclear power plants(NPPs). We derived 24 organizational factors affecting to the job stress in NPPs from the job stress analysis models of NIOSH(1989), Cooper(1990), and Karasek(1990). onsidering the safety characteristic in operating tasks of NPPs, we individuate among the tasks in NPPs through the division of duty and the analysis of cost activity. Through the questionnaire survey, a structured interview with the responsible employees, and expert panels, we assess 70 tasks among 777 tasks managed officially under the procedures. They are the representative tasks to the duties of each division and are directly related to the safety. We utilize the OPTI(organizational personality type indicators) to characterize the personality type of each organization in NPPs.

• 전자공학회논문지SC
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• 제48권4호
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• pp.71-79
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• 2011

본 논문에서는 이더넷 파워링크의 마스터 이중화 기법의 실시간성 향상을 위해 PReq 신호를 이용한 원전용 실시간 제어망의 실시간성과 신뢰성을 고려한 마스터 이중화 기법을 제안하였다. 제안된 마스터 이중화 기법은 동기 구간에서 PReq 신호를 이용하여 마스터 고장을 감지하고 비동기 구간에서 AMNI 프레임을 전송하여 단위 사이클 구간 앞서서 전환이 가능하다. 이를 통해 실시간 주기 데이터의 손실 및 이로 인한 문제점들을 최소한으로 줄일 수 있다. 제안된 마스터 이중화 기법의 효용성을 증명하기 위하여 OPNET Modeler를 이용하여 성능분석 및 검증을 수행하였고 이를 통해 마스터 전환시간을 줄일 수 있음을 보였다.

• Nuclear Engineering and Technology
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• 제53권9호
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• pp.2888-2898
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• 2021

Vital area identification (VAI) is an essential procedure for the design of physical protection systems (PPSs) for nuclear power plants (NPPs). The purpose of PPS design is to protect vital areas. VAI has been improved continuously to overcome the shortcomings of previous VAI generations. In first-generation VAI, a sabotage fault tree was developed directly without reusing probabilistic safety assessment (PSA) results or information. In second-generation VAI, VAI model was constructed from all PSA event trees and fault trees. While in third-generation VAI, it was developed from the simplified PSA event trees and fault trees. While VAIs have been performed for NPPs in full-power operations, VAI for NPPs in low-power and shutdown (LPSD) operations has not been studied and performed, even though NPPs in LPSD operations are very vulnerable to sabotage due to the very crowded nature of NPP maintenance. This study is the first to research and apply VAI to LPSD operation of NPP. Here, the third-generation VAI method for full-power operation of NPP was adapted to the VAI of LPSD operation. In this study, LPSD VAI for a few plant operational states (POSs) was performed. Furthermore, the operation strategy of vital areas for both full-power and LPSD operations was discussed. The LPSD VAI method discussed in this paper can be easily applied to all POSs. The method and insights in this study can be important for future LPSD VAI that reflects various LPSD operational states. Regulatory bodies and electric utilities can take advantage of this LPSD VAI method.

• Nuclear Engineering and Technology
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• 제53권1호
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• pp.351-356
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• 2021

Korean nuclear power plants (NPPs) have various radiation protection programs to attain radiation exposure as low as reasonably achievable (ALARA). In terms of ALARA, this paper provides a comprehensive overview of administrative dose control for occupationally-exposed workers in Korean NPPs. In addition to dose limits, administrative dose constraints are implemented to resolve an inequity of radiation exposure in which some individuals in NPPs receive relatively higher doses than others. Occupational dose constraints in Korean NPPs are presented in this paper with the background of how those values were determined. For pressurized water reactors, 80% and 90% of the annual average limit for an effective dose, 20 mSv/y, are set as the primary and secondary dose constraints, respectively. Pressurized heavy water reactors (PHWRs) have also established the primary and secondary dose constraints corresponding to 70% and 80% of the effective dose limit, and additional constraints for tritium concentration are provided to control internal exposure in PHWRs. Follow-up measures for exceeding these administrative dose constraints are also introduced compared to exceeding the dose limits. Finally, analysis results of dose distributions show how the implementation of administrative dose constraints impacted the occupational dose distributions in Korean NPPs during the years 2009-2018.

• Nuclear Engineering and Technology
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• 제55권2호
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• pp.603-622
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• 2023

Human error (HE) is an important concern in safety-critical systems such as nuclear power plants (NPPs). HE has played a role in many accidents and outage incidents in NPPs. Despite the increased automation in NPPs, HE remains unavoidable. Hence, the need for HE detection is as important as HE prevention efforts. In NPPs, HE is rather rare. Hence, anomaly detection, a widely used machine learning technique for detecting rare anomalous instances, can be repurposed to detect potential HE. In this study, we develop an unsupervised anomaly detection technique based on generative adversarial networks (GANs) to detect anomalies in manually collected surveillance data in NPPs. More specifically, our GAN is trained to detect mismatches between automatically recorded sensor data and manually collected surveillance data, and hence, identify anomalous instances that can be attributed to HE. We test our GAN on both a real-world dataset and an external dataset obtained from a testbed, and we benchmark our results against state-of-the-art unsupervised anomaly detection algorithms, including one-class support vector machine and isolation forest. Our results show that the proposed GAN provides improved anomaly detection performance. Our study is promising for the future development of artificial intelligence based HE detection systems.