• Proceedings of the Korean Information Science Society Conference
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• 1998.10b
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• pp.487-489
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• 1998

원자력 발전소와 같이 환경적으로 큰 재난을 가져 올 수 있는 시스템에서는 전체 시스템을 구축하기 전에 구축하고자 하는 시스템의 안전성을 보장할 수 있는지의 여부와 그러한 시스템의 조작자들의 훈련을 위해 실시간 시뮬레이션이 반드시 필요하다. 본 논문에서는 원자력 발전소의 SIS(Safety Injection System)를 실시간 객체 TMO(Time-triggered Message Triggered Model)를 이용 모델링하는 기법과, 분산 실시간 객체 플랫폼인 WTMOS위에서 구현된 SIS 시뮬레이션 시스템에 대해 기술하였다.

• Proceedings of the Korean Nuclear Society Conference
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• 1996.11a
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• pp.395-400
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• 1996

Scoping analyses for the Safety Injection System (SIS) configuration for Korean Next Generation Reactor (KNGR) are peformed in this study. The KNGR SIS consists of four mechanically separated hydraulic trains. Each hydraulic train consisting of a High Pressure Safety Injection (HPSI) pump and a Safety Injection Tank (SIT) is connected to the Direct Vessel Injection (DVI) nozzle located above the elevation of cold leg and thus injects water into the upper portion of reactor vessel annulus. Also, the KNGR is going to adopt the advanced design feature of passive fluidic device which will be installed in the discharge line of SIT to allow more effective use of borated water during the transient of large break LOCA. To determine the feasible configuration and capacity of SIT and HPSI pump with the elimination of the Low Pressure Safety Injection (LPSI) pump for KNGR, licensing design basis evaluations are performed for the limiting large break LOCA. The study shows that the DVI injection with the fluidic device SIT enhances the SIS performance by allowing more effective use of borated water for an extended period of time during the large break LOCA.

• Journal of Mechanical Science and Technology
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• v.19 no.5
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• pp.1206-1215
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• 2005

The thermal stratification phenomena, frequently occurring in the component of nuclear power plant system such as pressurizer surge line, steam generator inlet nozzle, safety injection system (SIS), and chemical and volume control system (CVCS), can cause through-wall cracks, thermal fatigue, unexpected piping displacement and dislocation, and pipe support damage. The phenomenon is one of the unaccounted load in the design stage. However, the load have been found to be serious as nuclear power plant operation experience accumulates. In particular, the thermal stratification by the turbulent penetration or valve leak in the SIS and SCS pipe line can lead these safety systems to failure by the thermal fatigue. Therefore in this study an 1/10 scaledowned experimental rig had been designed and installed. And a series of experimental works had been executed to measure the temperature distribution (thermal stratification) in these systems by the turbulent penetration, valve leak, and heat transfer through valve. The results provide very valuable informations such as turbulent penetration depth, the possibility of thermal stratification by the heat transfer through valve, etc. Also the results are expected to be useful to understand the thermal stratification in these systems, establish the thermal strati­fication criteria and validate the calculation results by CFD Codes such as Fluent, Phenix, CFX.

• Nuclear Engineering and Technology
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• v.53 no.12
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• pp.4014-4021
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• 2021

If safety injection systems (SISs) do not work in the event of a loss-of-coolant accident (LOCA), the accident can progress to a severe accident in which the reactor core is exposed and the reactor vessel fails. Therefore, it is considered that a technology that provides recoverable maximum time for SIS actuation is necessary to prevent this progression. In this study, the corresponding time was defined as the golden time. To achieve the objective of accurately predicting the golden time, the prediction was performed using the deep fuzzy neural network (DFNN) with rule-dropout. The DFNN with rule-dropout has an architecture in which many of the fuzzy neural networks (FNNs) are connected and is a method in which the fuzzy rule numbers, which are directly related to the number of nodes in the FNN that affect inference performance, are properly adjusted by a genetic algorithm. The golden time prediction performance of the DFNN model with rule-dropout was better than that of the support vector regression model. By using the prediction result through the proposed DFNN with rule-dropout, it is expected to prevent the aggravation of the accidents by providing the maximum remaining time for SIS recovery, which failed in the LOCA situation.

• Nuclear Engineering and Technology
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• v.23 no.2
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• pp.174-182
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• 1991

Effects of human error relevant to the periodic test are incorporated in the evaluations of the unavailability and optimal test interval of a safety system. Two types of possible human error with respect to the test and maintenance are considered. One is the possibility that a good safety system is inadvertently left in a bad state after test（Type A human error) and the other is the possibility that a bad safety system is undetected upon the test（Type B human error). An event tree model is developed for the steady-state unavailability of a safety system in order to determine the effects of human errors on the system unavailability and the optimal test interval. A reliability analysis of the Safety Injection System (SIS) was peformed to evaluate the effects of human error on the SIS unavailability. Results of various sensitivity analyses show that ; (1) the steady-state unavailability of the safety system increases as the probabilities of both types of human error increase and it is far more sensitive to Type A human error, (2) the optimal test interval increases slightly as the probability of Type A human error increases but it decreases as the probability of Type B human error increases, and (3) provided that the test interval of the safety injction pump is kept unchanged, the unavailability of SIS increases significantly as the probability of Type A human error increases but slightly as the probability of Type B human error increases. Therefore, to obtain the realistic result of reliability analysis, one should take shorter test interval (not optimal test interval) so that the unavailability of SIS can be maintained at the same level irrespective of human error. Since Type A human error during test & maintenance influeces greatly on the system unavailability, special efforts to reduce the possibility of Type A human error are essential in the course of test & maintenance.

• Transactions of the Korean Society of Mechanical Engineers B
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• v.40 no.3
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• pp.165-172
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• 2016

An experimental study of the thermal-hydraulic characteristics of passive safety systems (PSSs) was conducted using a system-integrated modular advanced reactor-integral test loop (SMART-ITL). The present passive safety injection system for the SMART-ITL consists of one train with the core makeup tank (CMT), the safety injection tank, and the automatic depressurization system. The objective of this study is to investigate the injection effect of the PSS on the small-break loss-of-coolant accident (SBLOCA) scenario for a 0.4 inch line break in the safety-injection system (SIS). The steady-state condition was maintained for 746 seconds before the break. When the major parameters of the target value and test results were compared, most of the thermal-hydraulic parameters agreed closely with each other. The water level of the reactor pressure vessel (RPV) was maintained higher than that of the fuel assembly plate during the transient, for the present CMT and safety injection tank (SIT) flow rate conditions. It can be seen that the capability of an emergency core cooling system is sufficient during the transient with SMART passive SISs.