• 한국원자력학회:학술대회논문집
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• 한국원자력학회 2002년도 추계학술발표회요약집
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• pp.210.1-210
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• 2002

• 한국원자력학회:학술대회논문집
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• 한국원자력학회 2003년도 추계학술발표대회 요약집
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• pp.447-447
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• 2003

• 한국원자력학회:학술대회논문집
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• 한국원자력학회 2003년도 추계학술발표대회 요약집
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• pp.180-180
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• 2003

• 한국원자력학회:학술대회논문집
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• 한국원자력학회 1999년도 추계학술발표회요약집
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• pp.142-142
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• 1999

• Nuclear Engineering and Technology
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• 제53권3호
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• pp.812-824
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• 2021

In order to reduce risks from the Steam Generator Tube Rupture (SGTR) accident and to meet safety targets, various measures have been analyzed to minimize the amount of fission product (FP) release. In this paper, we propose an introduction of a Containment Filtered Venting System (CFVS) connected to the steam generator secondary side, which can reduce the amount of FP release while minimizing adverse effects identified in the previous studies. In order to compare the effect of new equipment with the existing strategy, accident simulations using MELCOR were performed. As a result of simulations, it is confirmed that CFVS operation lowers FP release into the environment, and the release fractions are lower (minimum 0.6% of the initial inventory for Cs) than that of the strategy which intends to depressurize the primary system directly (minimum 15.2% for Cs). The sensitivity analyses identify that refill of the CFVS vessel is a dominant contributor reducing the amount of FP released. As the new strategy has the possibility of hydrogen combustion and detonation in CFVS, the installation of an igniter inside the CFVS vessel may be considered in reducing such hydrogen risk.

• Nuclear Engineering and Technology
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• 제56권5호
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• pp.1725-1732
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• 2024

In nuclear power plants, reactor coolant leakage can occur due to various reasons. Early detection of leaks is crucial for maintaining the safety of nuclear power plants. Currently, a detection system is being developed in Korea to identify reactor coolant system (RCS) leakage of less than 0.5 gpm. Typically, RCS leaks are detected by monitoring temperature, humidity, and radioactivity in the containment, and a water level in the sump. However, detecting small leaks proves challenging because the resulting changes in the containment humidity and temperature, and the sump water level are minimal. To address these issues and improve leak detection speed, it is necessary to quantify the leaks and develop an artificial intelligence-based leak detection system. In this study, we employed bidirectional long short-term memory, which are types of neural networks used in artificial intelligence, to predict the relative humidity in the leakage area for leak quantification. Additionally, an optimization technique was implemented to reduce learning time and enhance prediction performance. Through evaluation of the developed artificial intelligence model's prediction accuracy, we expect it to be valuable for future leak detection systems by accurately predicting the relative humidity in a leakage area.

• 한국구조물진단유지관리공학회 논문집
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• 제5권2호
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• pp.147-154
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• 2001

The prestressed concrete containment is one of the most important structures in nuclear power plants, which is required to prevent release of radioactive or hazardous effluents to the environment even in the case of a severe accident. Numerical analyses are carried out by using the ABAQUS finite element program to assess the ultimate pressure capacity of the Y prestressed concrete containment with light water reactor at design criteria condition and aging condition considering varied properties of time-dependant materials respectively. From the results, it is verified that the structural capacity of the Y prestressed concrete containment building under the present, aging condition is still robust. In addition, the parameter studies for the reduction of the ultimate pressure capacity of containment building according to the degradation levels of the main structural materials are carried out. The results show that when the degradations of each materials are considered as individual and combined forms, the influence is large in the order of tendon, rebar and concrete degradation, and tendon-rebar, tendon-concrete and rebar-concrete degradation respectively.

• Nuclear Engineering and Technology
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• 제54권7호
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• pp.2748-2754
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• 2022

Because existing reactant coolant system (RCS) leakage detection mechanisms are insensitive to small leaks, a real-time, direct detection system with a detection threshold below 0.5 gpm·hr^-1 was studied. A beta-ray detection system using a silicon detector with good energy resolution for beta rays and a low gamma-ray response was proposed. The detection performance in the leakage condition was evaluated through experiments and simulations. The concentration of ¹⁶N in the coolant corresponding to a coolant leakage of 0.5 gpm was calculated using the analytic method and ORIGEN-ARP. Based on the concentration of ¹⁶N and the measurement of the silicon detector with ⁹⁰Sr/⁹⁰Y, the beta-ray count rate was estimated using MCNPX. To evaluate the effect of gamma rays inside the containment building, the signal-to-noise ratio (SNR) was calculated. To evaluate the count rate ratio, the radiation field inside the containment building was simulated using MCNPX, and response evaluation experiments were performed using beta and gamma rays on the silicon detector. The expected beta-ray count rate at 0.5 gpm leakage was 7.26 × 10⁵ counts/sec, and the signal-to-background count rate ratio exceeded 88 for a transport time of 10 s, demonstrating its suitability for operation inside a reactor containment building.

• Journal of international Conference on Electrical Machines and Systems
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• 제2권4호
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• pp.460-465
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• 2013

Electrical equipments of nuclear power plant are divided into class 1E and non-class 1E. Electrical equipment and systems that are essential to emergency reactor shutdown, containment isolation, reactor core cooling, and containment and reactor heat removal, are classified as class 1E. batteries of nuclear power plant are divided into four channels, which are physically and electrically separate and independent. The battery bank of class 1E DC power system of the nuclear power plant use lead-acid batteries in present. The lead acid battery, which has a high energy density, is the most popular form of energy storage. Kt factor of lead-acid battery is used to determine battery size and it is one of calculatiing coefficient for capacity. this paper analyzes Kt factor of lead-acid battery for the DC power system of nuclear power plant. In addition, correlation between Kt parameter and peukert's exponent of lead-acid battery for nuclear plant are discussed. The analytical results contribute to optimize of determining size Lead-acid battery bank.

• Nuclear Engineering and Technology
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• 제49권2호
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• pp.426-433
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• 2017

This paper describes the development process, the innovative techniques used and insights gained from the latest integrated, full scope, multistate Level 2 PSA analysis conducted at the Leibstadt Nuclear Power Plant (KKL), Switzerland. KKL is a modern single-unit General Electric Boiling Water Reactor (BWR/6) with Mark III Containment, and a power output of $3600MW_{th}/1200MW_e$, the highest among the five operating reactors in Switzerland. A Level 2 Probabilistic Safety Assessment (PSA) analyses accident phenomena in nuclear power plants, identifies ways in which radioactive releases from plants can occur and estimates release pathways, magnitude and frequency. This paper attempts to give an overview of the advanced modeling techniques that have been developed and implemented for the recent KKL Level 2 PSA update, with the aim of systematizing the analysis and modeling processes, as well as complying with the relatively prescriptive Swiss requirements for PSA. The analysis provides significant insights into the absolute and relative importances of risk contributors and accident prevention and mitigation measures. Thanks to several newly developed techniques and an integrated approach, the KKL Level 2 PSA report exhibits a high degree of reviewability and maintainability, and transparently highlights the most important risk contributors to Large Early Release Frequency (LERF) with respect to initiating events, components, operator actions or seismic component failure probabilities (fragilities).