• Journal of Magnetics
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• v.18 no.3
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• pp.342-347
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• 2013

Local wall thinning in pipelines affects the structural integrity of industries, such as nuclear power plants (NPPs). In the present study, a development of pulsed eddy current (PEC) technology that detects the wall thinning of pipelines covered with insulation is reviewed. The methods and experimental results, which have two kinds of probe with a single and double core, were compared. For this purpose, the single and double core probes having one and two excitation coils have been devised, and the differential probe with two Hall sensors has been fabricated to measure the wall thinning in insulated pipelines. The test sample is a stainless steel having different thickness, laminated by plastic insulation to simulate the pipelines in NPPs. The excitation coils in the probe is driven by a rectangular current pulse, the difference of two Hall sensors has been measured as a resultant PEC signal. The peak value of the detected signal is used to describe the wall thinning. The double core probe has better performance to detect the wall thinning covered with insulation; the single core probe can detect the wall thinning up to an insulation thickness of 18 mm, whereas the double probe can detect up to 25 mm. The results show that the double core PEC probe has the potential to detect the wall thinning in an insulated pipeline of the NPPs.

• Nuclear Engineering and Technology
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• v.49 no.5
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• pp.989-995
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• 2017

Distributed Control System (DCS) communication networks, which use Fast Ethernet with redundant networks for the transmission of information, have been installed in digitalized nuclear power plants. Normally, failover tests are performed to verify the reliability of redundant networks during design and manufacturing phases; however, systematic integrity tests of DCS networks cannot be fully performed during these phases because all relevant equipment is not installed completely during these two phases. In additions, practical verification tests are insufficient, and there is a need to test the actual failover function of DCS redundant networks in the target environment. The purpose of this study is to verify that the failover functions works correctly in certain abnormal conditions during installation and commissioning phase and identify the influence of network failover on the entire DCS. To quantify the effects of network failover in the DCS, the packets (Protocol Data Units) must be collected and resource usage of the system has to be monitored and analyzed. This study introduces the use of a new methodology for verification of DCS network failover during the installation and commissioning phases. This study is expected to provide insight into verification methodology and the failover effects from DCS redundant networks. It also provides test results of network performance from DCS network failover in digitalized domestic nuclear power plants (NPPs).

• The Transactions of The Korean Institute of Electrical Engineers
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• v.61 no.3
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• pp.367-372
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• 2012

In nuclear plants, UVR (under voltage relay, 27r) of 1E bus, which protected and supplied power to essential loads, to safety trip of reactor and supplied to starting signal of EDG (emergency diesel generators) automatically. therefore UVR tolerances setting and calculation method has been important to nuclear facility. If calculation and tolerances values differ or ignore, may induced power loss and economical loss by protective failure. This paper show results for calculation methods, and whether dependant or independent methods for factors. included whether PT (potential transformer/voltage transformer) tolerance or not adapted, and based on UVR setting method within a difference minimum and maximum of rated voltage to safety operation in nuclear plants.

• Nuclear Engineering and Technology
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• v.42 no.4
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• pp.460-467
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• 2010

In this study, the parameters of the feedwater control system (FWCS) of the OPR1000 type nuclear power plant (NPP) are optimized by response surface methodology (RSM) in order to acquire better level control performance from the FWCS. The objective of the optimization is to minimize the steam generator (SG) water level deviation from the reference level during transients. The objective functions for this optimization are relationships between the SG level deviation and the parameters of the FWCS. However, in this case of FWCS parameter optimization, the objective functions are not available in the form of analytic equations and the responses (the SG level at plant transients) to inputs (FWCS parameters) can be evaluated by computer simulations only. Classical optimization methods cannot be used because the objective function value cannot be calculated directely. Therefore, the simulation optimization methodology is used and the RSM is adopted as the simulation optimization algorithm. Objective functions are evaluated with several typical transients in NPPs using a system simulation computer code that has been utilized for the system performance analysis of actual NPPs. The results show that the optimized parameters have better SG level control performance. The degree of the SG level deviation from the reference level during transients is minimized and consequently the control performance of the FWCS is remarkably improved.

• Nuclear Engineering and Technology
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• v.55 no.9
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• pp.3342-3351
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• 2023

High-density polyethylene (HDPE) pipelines in nuclear power plants (NPPs) have to meet high requirements for seismic performance. HDPE pipes have been proved to have good seismic performance, but joints are the weak links in the pipelines, and pipeline failures usually initiate from the defects inside the joints. Limited data are available on the seismic performance of butt-fusion joints of HDPE pipelines in NPPs, especially in terms of defects changes inside the joints after earthquakes. In this paper, full-scale shaking table tests were performed on a test section of suspended HDPE pipelines in an NPP, which included straight pipes, elbows, and 10 butt-fusion joints. During the tests, the seismic load-induced strain of the joints was analyzed by strain gauges, and it was much smaller than the internal pressure and self-weight-induced strain. Before and after the shaking table tests, phased array ultrasonic testing (PA-UT) was conducted to detect defects inside the joints. The locations, numbers, and dimensions of the defects were analyzed. It was found that defects were more likely to occur in elbows joints. No new defect was observed after the shaking table tests, and the defects showed no significant growth, indicating the satisfactory seismic performance of the butt-fusion joints.

• Nuclear Engineering and Technology
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• v.42 no.2
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• pp.219-230
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• 2010

In nuclear power plants (NPPs), periodic sensor calibrations are required to assure that sensors are operating correctly. By checking the sensor's operating status at every fuel outage, faulty sensors may remain undetected for periods of up to 24 months. Moreover, typically, only a few faulty sensors are found to be calibrated. For the safe operation of NPP and the reduction of unnecessary calibration, on-line instrument calibration monitoring is needed. In this study, principal component-based auto-associative support vector regression (PCSVR) using response surface methodology (RSM) is proposed for the sensor signal validation of NPPs. This paper describes the design of a PCSVR-based sensor validation system for a power generation system. RSM is employed to determine the optimal values of SVR hyperparameters and is compared to the genetic algorithm (GA). The proposed PCSVR model is confirmed with the actual plant data of Kori Nuclear Power Plant Unit 3 and is compared with the Auto-Associative support vector regression (AASVR) and the auto-associative neural network (AANN) model. The auto-sensitivity of AASVR is improved by around six times by using a PCA, resulting in good detection of sensor drift. Compared to AANN, accuracy and cross-sensitivity are better while the auto-sensitivity is almost the same. Meanwhile, the proposed RSM for the optimization of the PCSVR algorithm performs even better in terms of accuracy, auto-sensitivity, and averaged maximum error, except in averaged RMS error, and this method is much more time efficient compared to the conventional GA method.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.25 no.2
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• pp.363-374
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• 2015

Instrumentation and control(I&C) system has been mainly designed and operated based on analog technologies in existing Nuclear Power Plants(NPPs). However, As the development of Information Technology(IT), digital technologies are gradually being adopted in newly built NPPs. I&C System based on digital technologies has many advantages but it is vulnerable to cyber threat. For this reason, cyber threat adversely affects on safety and reliability of I&C system as well as the entire NPPs. Therefore, the software equipped to NPPs should be developed with cyber security attributes from the initiation phase of software development life cycle. Moreover through cyber security assessment, the degree of confidence concerning cyber security should be measured and if managerial, technical and operational work measures are implemented as intended should be reviewed in order to protect the I&C systems and information. Currently the overall cyber security program, including cyber security assessment, is not established on I&C systems. In this paper, we propose cyber security assessment methods in the Software Development Life Cycle by drawing cyber security activities and assessment items based on regulatory guides and standard technologies concerned with NPPs.

• Nuclear Engineering and Technology
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• v.54 no.8
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• pp.2859-2870
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• 2022

Because nuclear power plants (NPPs) are safety-critical infrastructure, it is essential to increase their safety and minimize risk. To reduce human error and support decision-making by operators, several artificial-intelligence-based diagnosis methods have been proposed. However, because of the nature of data-driven methods, conventional artificial intelligence requires large amount of measurement values to train and achieve enough diagnosis resolution. We propose a graph neural network (GNN) based accident diagnosis algorithm to achieve high diagnosis resolution with limited measurements. The proposed algorithm is trained with both the knowledge about physical correlation between components and measurement values. To validate the proposed methodology has a sufficiently high diagnostic resolution with limited measurement values, the diagnosis of multiple accidents was performed with limited measurement values and also, the performance was compared with convolution neural network (CNN). In case of the experiment that requires low diagnostic resolution, both CNN and GNN showed good results. However, for the tests that requires high diagnostic resolution, GNN greatly outperformed the CNN.

• Journal of the Ergonomics Society of Korea
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• v.25 no.3
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• pp.85-96
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• 2006

Main control room(MCR) man-machine interface(MMI) design of advanced nuclear power plants(NPPs) such as APR(advanced power reactor)-1400 can be validated through performance-based tests to determine whether it acceptably supports safe operation of the plant. In this work, plant performance, personnel task, situation awareness, workload, teamwork, and anthropometric/physiological factor are considered as factors for the human performance evaluation. For development of measures in each of the factors, techniques generally used in various industries and empirically proven to be useful are adopted as main measures and some helpful techniques are developed in order to complement the main measures. Also the development of the measures is addressed based on the theoretical background. Finally we discuss the way in which the measures can be effectively integrated and then HUPESS(HUman Performance Evaluation Support System) which is in development based on the integrated way is briefly introduced.

• Proceedings of the Earthquake Engineering Society of Korea Conference
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• 1999.04a
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• pp.17-24
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• 1999

The porvision against earthquakes and aseismic design of nuclear power plants (NPPs) in Korea are composed of four stages: site-selection, design, construction, and operation stages, Since regulatory criteria are strictly applied in each stage, the NPPs in Korea are believed to have a sufficient safety against maximum potential earthquakes. However, it has been recognized that those regulatory criteria borrowed from U.S. should be replace by Korea-specific ones by using earthquake data obtained from earthquake observation at and around NPP sites. Also, the government made a plan after the Yongwol and th Kyongju earthquakes that the regulatory body operates an independent earthquake network in order to reinforce the earthquake preparedness of NPPs. In compliance with the government's plan, this project is aiming at deployment of an earthquake motoring network composed of four seismic stations at NPP sites to record earthquake ground motions at NPP sites, to derive attenuation formulas of various ground motions and site-specific response spectra, and to develop structural intergrity assesment program.