• 한국방사성폐기물학회:학술대회논문집
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• 한국방사성폐기물학회 2018년도 추계학술논문요약집
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• pp.249-250
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• 2018

• 한국지진공학회논문집
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• 제22권3호
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• pp.113-119
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• 2018

The probabilistic seismic safety assessment is one of the methodology to evaluate the seismic safety of the nuclear power plants. The site characteristics of the nuclear power plant should be reflected when evaluating the seismic safety of the nuclear power plant. The Korea seismic characteristics are strong in high frequency region and may be different from NRC Regulatory Guide 1.60, which is the design spectrum of nuclear power plants. In this study, seismic response of a nuclear power plant structure by Pohang earthquake (2017.11.15. (KST)) is investigated. The Pohang earthquake measured at the Cheongsong seismic observation station (CHS) is scaled to the peak ground acceleration (PGA) of 0.2 g and the seismic acceleration time history curve corresponding to the design spectrum is created. A nuclear power plant of the containment building and the auxiliary buildings are modeled using OPENSEES to analyze the seismic response of the Pohang earthquake. The seismic behavior of the nuclear power plant due to the Pohang earthquake is investigated. And the seismic performances of the equipment of a nuclear power plant are evaluated by the HCLPF. As a result, the seismic safety evaluation of nuclear power plants should be evaluated based on site-specific characteristics of nuclear power plants.

• Nuclear Engineering and Technology
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• 제52권8호
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• pp.1661-1668
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• 2020

A physical protection system (PPS) is used for the protection of critical facilities. This paper proposes a structure analytic hierarchy approach (SAHA) for the hierarchical evaluation of the PPS effectiveness in critical infrastructure. SAHA is based on the traditional analysis methods "estimate of adversary sequence interruption, EASI". A community algorithm is used in the building of the SAHA model. SAHA is applied to cluster the associated protection elements for the topological design of complicated PPS with graphical vertexes equivalent to protection elements.

• Nuclear Engineering and Technology
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• 제50권4호
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• pp.562-569
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• 2018

Recently, human errors have very rarely occurred during power generation at nuclear power plants. For this reason, many countries are conducting research on smart support systems of nuclear power plants. Smart support systems can help with operator decisions in severe accident occurrences. In this study, a smart support system was developed by integrating accident prediction functions from previous research and enhancing their prediction capability. Through this system, operators can predict accident scenarios, accident locations, and accident information in advance. In addition, it is possible to decide on the integrity of instruments and predict the life of instruments. The data were obtained using Modular Accident Analysis Program code to simulate severe accident scenarios for the Optimized Power Reactor 1000. The prediction of the accident scenario, accident location, and accident information was conducted using artificial intelligence methods.

• Nuclear Engineering and Technology
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• 제56권6호
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• pp.1959-1974
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• 2024

Nuclear energy plays a crucial role in energy supply in the 21st century, and more and more Nuclear Power Plants (NPPs) will be in operation to contribute to the development of human society. However, as a typical complex system engineering, the operation and development of NPPs require efficient and stable control methods to ensure the safety and efficiency of nuclear power generation. Reinforcement learning (RL) aims at learning optimal control policies via maximizing discounted long-term rewards. The reward-oriented learning paradigm has witnessed remarkable success in many complex systems, such as wind power systems, electric power systems, coal fire power plants, robotics, etc. In this work, we try to present a systematic review of the applications of RL on these complex systems, from which we believe NPPs can borrow experience and insights. We then conduct a block-by-block investigation on the application scenarios of specific tasks in NPPs and carried out algorithmic research for different situations such as power startup, collaborative control, and emergency handling. Moreover, we discuss the possibilities of further application of RL methods on NPPs and detail the challenges when applying RL methods on NPPs. We hope this work can boost the realization of intelligent NPPs, and contribute to more and more research on how to better integrate RL algorithms into NPPs.

• Nuclear Engineering and Technology
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• 제54권10호
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• pp.3909-3918
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• 2022

In the event of a severe accident, the reactor core may melt due to insufficient cooling. the high-temperature core melt will have a strong interaction (FCI) with the coolant, which may lead to steam explosion. Steam explosion would pose a serious threat to the safety of the reactors. Therefore, the study of steam explosion is of great significance to the assessment of severe accidents in nuclear reactors. This research focuses on the development of a two-dimensional steam explosion integrated analysis code called SEINA. Based on the semi-implicit Euler scheme, the three-phase field was considered in this code. Besides, the influence of evaporation drag of melt and the influence of solidified shell during the process of melt droplet fragmentation were also considered. The code was simulated and validated by FARO L-14 and KROTOS KS-2 experiments. The calculation results of SEINA code are in good agreement with the experimental results, and the results show that if the effects of evaporation drag and melt solidification shell are considered, the FCI process can be described more accurately. Therefore, it is proved that SEINA has the potential to be a powerful and effective tool for the analysis of steam explosions in nuclear reactors.

• Nuclear Engineering and Technology
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• 제55권8호
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• pp.2997-3009
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• 2023

The Passive containment Air-cooling System (PAS) can effectively remove the decay heat of the modular small nuclear reactor after an accident. The details of natural convection around the dome, which is a key part of PAS, were investigated numerically in the present study. The thermal dynamics around the dome were studied through the temperature, pressure and velocity contours and the streamlines. Additionally, the formation of the buoyant plume at the top of the dome was investigated. The results show that with the increase of Ra, the lift-off point moves toward the bottom of the dome, and the eddy under the buoyant plume grows larger gradually, which enhances the heat transfer. And the heat transfer along the dome surface with different truncation angles was investigated. As the angle increases, the heat transfer coefficient becomes stronger as well. Consequently, a newly developed heat transfer correlation considering the influence of truncation angle for the dome is proposed based on the simulated results. This study could provide a better understanding of natural convection around the dome of PAS and the proposed correlation could also offer more predictive value in the improvement of nuclear safety.

• Journal of Mechanical Science and Technology
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• 제18권12호
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• pp.2080-2094
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• 2004

A model predictive controller is designed to control thermal power in a nuclear reactor. The basic concept of the model predictive control is to solve an optimization problem for finite future time steps at current time, to implement only the first optimal control input among the solved control inputs, and to repeat the procedure at each subsequent instant. A controller design model used for designing the model predictive controller is estimated every time step by applying a recursive parameter estimation algorithm. A 3-dimensional nuclear reactor analysis code, MASTER that was developed by Korea Atomic Energy Research Institute (KAERI), was used to verify the proposed controller for a nuclear reactor. It was known that the nuclear power controlled by the proposed controller well tracks the desired power level and the desired axial power distribution.

• Nuclear Engineering and Technology
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• 제53권1호
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• pp.103-110
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• 2021

In the development of a Risk Monitor probabilistic safety assessment (PSA) model from the basic PSA model of a nuclear power plant, the modeling of common-cause failure (CCF) is very important. At present, some approximate modeling methods are widely used, but there lacks criterion of modeling accuracy and error analysis. In this paper, aiming at ensuring the accuracy of risk assessment and minimizing the Risk Monitor PSA models size, we present three basic issues of CCF model resulted from the changes of a nuclear power plant configuration, put forward corresponding modeling methods, and derive accuracy criteria of CCF modeling based on minimum cut sets and risk indicators according to the requirements of risk monitoring. Finally, a nuclear power plant Risk Monitor PSA model is taken as an example to demonstrate the effectiveness of the proposed modeling method and accuracy criteria, and the application scope of the idea of this paper is also discussed.

• Nuclear Engineering and Technology
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• 제53권9호
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• pp.3035-3043
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• 2021

Epidemiological research has revealed that radiation exposure can cause cataracts. The Korean nuclear regulatory body has proposed the reduction of the occupational dose limit for the lens of the eye from 150 mSv/y to 100 mSv/5y, with an additional limitation of not exceeding 50 mSv/y for a specific year, taking into account the recommendations of the International Commission on Radiological Protection, and the International Atomic Energy Agency. This means that radiation workers should receive the same level of radiation safety for the lens of the eye as for whole-body protection. Korean nuclear power plants (NPPs) are conducting research to establish the radiation protection program for the lens of the eye. In terms of the preliminary results of the implementation of the radiation protection program for the lens of the eye dedicated to Korean NPPs, this review article summarizes the current state of understanding of the regulations, technical guidance, eye lens dosimeters, and radiation field conditions resulting in lens dose.