• Nuclear Engineering and Technology
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• v.36 no.5
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• pp.420-429
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• 2004

The local power density should be estimated accurately to prevent fuel rod melting. The local power density at the hottest part of a hot fuel rod, which is described by the power peaking factor, is more important information than the local power density at any other position in a reactor core. Therefore, in this work, the power peaking factor, which is defined as the highest local power density to the average power density in a reactor core, is estimated by fuzzy neural networks using numerous measured signals of the reactor coolant system. The fuzzy neural networks are trained using a training data set and are verified with another test data set. They are then applied to the first fuel cycle of Yonggwang nuclear power plant unit 3. The estimation accuracy of the power peaking factor is 0.45% based on the relative $2_{\sigma}$ error by using the fuzzy neural networks without the in-core neutron flux sensors signals input. A value of 0.23% is obtained with the in-core neutron flux sensors signals, which is sufficiently accurate for use in local power density monitoring.

• Journal of Information Technology Services
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• v.20 no.3
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• pp.1-12
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• 2021

Reactor Coolant Pump (RCP) is core part of nuclear power plant to provide the forced circulation of reactor coolant for the removal of core heat. Properly monitoring vibration of RCP is a key activity of a successful predictive maintenance and can lead to a decrease in failure, optimization of machine performance, and a reduction of repair and maintenance costs. Here, we developed real-time RCP Vibration Analysis System (VAS) that web based platform using NoSQL DB (Mongo DB) to handle vibration data of RCP. In this paper, we explain how to implement digital signal process of vibration data from time domain to frequency domain using Fast Fourier transform and how to design NoSQL DB structure, how to implement web service using Java spring framework, JavaScript, High-Chart. We have implement various plot according to standard of the American Society of Mechanical Engineers (ASME) and it can show on web browser based on HTML 5. This data analysis platform shows a upgraded method to real-time analyze vibration data and easily uses without specialist. Furthermore to get better precision we have plan apply to additional machine learning technology.

• Nuclear Engineering and Technology
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• v.53 no.2
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• pp.532-548
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• 2021

Nuclear power plants contain several monitoring systems that can identify the in-vessel phenomena of a severe accident (SA). Though a lot of analysis and research is carried out on SA, right from the development of the nuclear industry, not all the possible circumstances are taken into consideration. Therefore, to improve the efficacy of the safety of nuclear power plants, additional analytical studies are needed that can directly monitor severe accident phenomena. This paper presents an interacting multiple model (IMM) based fault detection and diagnosis (FDD) approach for the identification of in-vessel phenomena to provide the accident propagation information using reactor vessel (RV) out-wall temperature distribution during severe accidents in a nuclear power plant. The estimation of wall temperature is treated as a state estimation problem where the time-varying wall temperature is estimated using IMM employing three multiple models for temperature evolution. From the estimated RV out-wall temperature and rate of temperature, the in-vessel phenomena are identified such as core meltdown, corium relocation, reactor vessel damage, reflooding, etc. We tested the proposed method with five different types of SA scenarios and the results show that the proposed method has estimated the outer wall temperature with good accuracy.

• Nuclear Engineering and Technology
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• v.55 no.4
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• pp.1528-1539
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• 2023

Since the leakage of sodium in an SFR (sodium-cooled fast reactor) causes an explosion upon reaction with air and water, sodium leakages represent an important safety issue. In this study, a novel technique for improving the reliability of sodium leakage detection applying DDVR (dynamic data validation and reconciliation) is proposed and verified to resolve this technical issue. DDVR is an approach that aims to improve the accuracy of a target system in a dynamic state by minimizing random errors, such as from the uncertainty of instruments and the surrounding environment, and by eliminating gross errors, such as instrument failure, miscalibration, or aging, using the spatial redundancy of measurements in a physical model and the reliability information of the instruments. DDVR also makes it possible to estimate the state of unmeasured points. To validate this approach for supporting sodium leakage detection, this study applies experimental data from a sodium leakage detection experiment performed by the Korea Atomic Energy Research Institute. The validation results show that the reliability of sodium leakage detection is improved by cooperation between DDVR and hardware measurements. Based on these findings, technology integrating software and hardware approaches is suggested to improve the reliability of sodium leakage detection by presenting the expected true state of the system.

• Journal of KSNVE
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• v.8 no.4
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• pp.723-732
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• 1998

원자력 발전소에서 운전되고 있는 원자로 냉각재 펌프는 대형 수직 펌프로서 증기 발생기로부터 원자로에 냉각재를 순환시키는 중요한 역할을 담당하고 있다. 원자로 냉각재 펌프는 운전 조건 및 각종 결함에 따라 진동, 열적 변형, 마모 등의 비정상 상태에서 운전될 수 있으며, 이로 인한 발전소 신뢰성 저하의 원인이 된다. 따라서 이 펌프의 감시 및 진단에 대한 연구가 계속되어 왔으며 각종 시스템이 설치 운용되고 있다. 그러나 미국내의 거의 모든 냉각재 펌프 감시 시스템은 펌프의 고진동 여부만을 나타내며 진동의 원인을 진단하기 어렵다. 본 연구에서는 최근까지 주로 발생되었던 미국내 원자로 냉각재 펌프의 문제점을 분석하고 이들의 원인별 진동 특성을 지식베이스화 하였으며, 진단시스템 개발을 위한 알고리즘을 제안하였다.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2014.10a
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• pp.181-184
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• 2014

Loose Parts Monitoring System(LPMS) monitors loosened or detached parts and foreign parts inside the pressure boundary of a reactor coolant system (RCS). It is difficult to discriminate valid signal from LPMS alarms at full power since the signal pattern by thermal shocks and structure friction are similar to those by loose metal impacts. In addition, It is more difficult to discriminate the impact signals induced by the rod driving, sensor hard-line movement and loosened component since they have similar frequency characteristics with valid signals. This paper classifies the signal patterns by analyzing actual LPMS signal captured during nuclear power plant operation.

• Proceedings of the Korean Nuclear Society Conference
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• 1998.05a
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• pp.291-296
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• 1998

The DAta management and Communication NETworks (DACONET), Which it is designed as a subsystem for Man-Machine Interface System of Korea Advanced LIquid MEtal Reactor(KALIMER MMIS) and advanced design concept is approached, is described. The DACONET has its roles of providing the real-time data transmission and communication paths between MMIS systems, providing the quality data for protection, monitoring and control of KALIMER and logging the static and dynamic behavioral data during KALIMER operation. The DACONET is characterised as the distributed real-time system architecture with high performance, Future direction, in which advanced technology is being continually applied to Man-Machine interface System Development of Nuclear Power Plants, will be considered for designing data management and communication networks of KALIMER MMIS

• Journal of the Korean Society of Safety
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• v.16 no.3
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• pp.125-134
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• 2001

The Advanced Pressurized rater Reactor 1400(APR1400) system is advanced of the successful Korean Nuclear Power Plants(KSNP) design which meets functional needs for safety enhancement reliability improvement, and control in the human-computer monitoring system. Therefore this paper describes the scoring model in order to justify the reliability and safety in APR 1400 under uncertainty. The structure of this paper consists of the human engineering, risk safety, quality function, safety organization management factors of the qualitative factors in chapter 2, and the expectation results of the normalized scoring model in chapter 3. Finally, the proposed reliability model have provided the technical flexibility not only for functional control fields but also for accidents protection systems in APR 1400 under uncertainty.

• Transactions of the Korean Society of Pressure Vessels and Piping
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• v.19 no.1
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• pp.44-51
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• 2023

The RCP is one of the main components in nuclear power plants and plays an important role in circulating coolant to the RCS system. Currently, nuclear plants are monitored using various monitoring systems. However, since they operate independently according to their functional purpose, it is not able to analyze vibration and operation/performance information comprehensively, and thus failure diagnosis accuracy is limited. In addition, these systems do not provide some important information (such as fault type, parts and cause) necessary for emergency actions, but provide only alarm information. To improve these technical problems, this study proposes a diagnosis technique (M/L, Rule-based model, Data-driven model, Narrow band model) and methodology for comprehensive analysis.

• Nuclear Engineering and Technology
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• v.56 no.6
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• pp.2220-2238
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• 2024

As a typical active equipment, pump machinery is widely used in nuclear power plants. Although the mechanism of pump machinery in nuclear power plants is similar to that of conventional pumps, the safety and reliability requirements of nuclear pumps are higher in complex operating environments. Once there is significant performance degradation or failure, it may cause huge security risks and economic losses. There are many pumps mechanical parameters, and it is very important to explore the correlation between multi-dimensional variables and condition. Therefore, a condition monitoring model based on Deep Denoising Autoencoder (DDAE) is constructed in this paper. This model not only ensures low false positive rate, but also realizes early abnormal monitoring and location. In order to alleviate the influence of parameter time-varying effect on the model in long-term monitoring, this paper combined equidistant sampling strategy and DDAE model to enhance the monitoring efficiency. By using the simulation data of reactor coolant pump and the actual centrifugal pump data, the monitoring and positioning capabilities of the proposed scheme under normal and abnormal conditions were verified. This paper has important reference significance for improving the intelligent operation and maintenance efficiency of nuclear power plants.