• Corrosion Science and Technology
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• v.12 no.6
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• pp.274-279
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• 2013

Flow accelerated corrosion (FAC) of the carbon steel piping in nuclear power plants (NPPs) has been major issue in nuclear industry. During the FAC, a protective oxide layer on carbon steel dissolves into flowing water leading to a thinning of the oxide layer and accelerating corrosion of base material. As a result, severe failures may occur in the piping and equipment of NPPs. Effect of alloying elements on FAC of pipe materials was studied with rotating cylinder FAC test facility at $150^{\circ}C$ and at flow velocity of 4m/s. The facility is equipped with on line monitoring of pH, conductivity, dissolved oxygen(DO) and temperature. Test solution was the demineralized water, and DO concentration was less than 1 ppb. Surface appearance of A 106 Gr. B which is used widely in secondary pipe in NPPs showed orange peel appearance, typical appearance of FAC. The materials with Cr content higher than 0.17wt.% showed pit. The pit is thought to early degradation mode of FAC. The corrosion product within the pit was enriched with Cr, Mo, Cu, Ni and S. But S was not detected in SA336 F22V with 2.25wt.% Cr. The enrichment of Cr and Mo seemed to be related with low, solubility of Cr and Mo compared to Fe. Measured FAC rate was compared with Ducreaux's relationship and showed slightly lower FAC rate than Ducreaux's relationship.

• Nuclear Engineering and Technology
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• v.41 no.3
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• pp.247-270
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• 2009

This paper reviews studies on information searching behavior in process control systems and discusses some implications learned from previous studies for use in human factors studies on nuclear power plants (NPPs) main control rooms (MCRs). Information searching behavior in NPPs depends on expectancy, value, salience, and effort. The first quantitative scanning model developed by Senders for instrument panel monitoring considered bandwidth (change rate) of instruments as a determining factor in scanning behavior. Senders' model was subsequently elaborated by other researchers to account for value in addition to bandwidth. There is also another type of model based on the operator's situation awareness (SA) which has been developed for NPP application. In these SA-based models, situation-event relations or rules on system dynamics are considered the most significant factor forming expectancy. From the review of previous studies it is recommended that, for NPP application, (1) a set of symptomatic information sources including both changed and unchanged symptoms should be considered along with bandwidth as determining factors governing information searching (or visual sampling) behavior; (2) both data-driven monitoring and knowledge-driven monitoring should be considered and balanced in a systematic way; (3) sound models describing mechanisms of cognitive activities during information searching tasks should be developed so as to bridge studies on information searching behavior and design improvement in HMI; (4) the attention-situation awareness (A-SA) modeling approach should be recognized as a promising approach to be examined further; and (5) information displays should be expected to have totally different characteristics in advanced control rooms. Hence much attention should be devoted to information searching behavior including human-machine interface (HMI) design and human cognitive processes.

• Nuclear Engineering and Technology
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• v.53 no.1
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• pp.234-243
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• 2021

In the research or project planning for the decommissioning of a nuclear power plant, one of several preparations will be the establishment of a list of potential radionuclides to be considered at the time of characterization or final status surveys. Reliable data for selection of potential radionuclides during the transition period to prepare for decommissioning will depend heavily on historical data at the site or, where possible, sampling analysis. However, during the transition period, direct sampling can be challenging, depending on the circumstances of the site or national regulation. A methodology of selecting potential radionuclides for nuclear facility sites which largely consists of three major processes: production of initial list of radionuclides, selection of the insignificant radionuclide that will be eliminated, and consideration of site characterization or sampling. For developing a preliminary list of potential radionuclides for Kori Unit 1 decommissioning, the list of initial radionuclides was made referring to the technical documents applied at decommissioned NPPs in the U.S and additional reference materials applied until the operation of NPPs in Korea. For the screening of insignificant radionuclides, we applied criterion of less than 0.1% of the amount of radioactivity inventory and confirmed the dose fraction using the RESRAD code. The final suit of radionuclides was established, which should be supplemented by reflecting site characterization and sampling process in the future. Thus, the methodology and results for the selection of potential radionuclides suggested in this paper can give an insight as a future reference to deriving DCGLs in relation to site remediation of decommissioning nuclear plants.

• Nuclear Engineering and Technology
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• v.55 no.9
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• pp.3409-3416
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• 2023

Licensing the next-generation of nuclear reactor designs requires extensive use of Modeling and Simulation (M&S) to investigate system response to many operational conditions, identify possible accidental scenarios and predict their evolution to undesirable consequences that are to be prevented or mitigated via the deployment of adequate safety barriers. Deep Learning (DL) and Artificial Intelligence (AI) can support M&S computationally by providing surrogates of the complex multi-physics high-fidelity models used for design. However, DL and AI are, generally, low-fidelity 'black-box' models that do not assure any structure based on physical laws and constraints, and may, thus, lack interpretability and accuracy of the results. This poses limitations on their credibility and doubts about their adoption for the safety assessment and licensing of novel reactor designs. In this regard, Physics Informed Neural Networks (PINNs) are receiving growing attention for their ability to integrate fundamental physics laws and domain knowledge in the neural networks, thus assuring credible generalization capabilities and credible predictions. This paper presents the use of PINNs as surrogate models for accidental scenarios simulation in Nuclear Power Plants (NPPs). A case study of a Loss of Heat Sink (LOHS) accidental scenario in a Nuclear Battery (NB), a unique class of transportable, plug-and-play microreactors, is considered. A PINN is developed and compared with a Deep Neural Network (DNN). The results show the advantages of PINNs in providing accurate solutions, avoiding overfitting, underfitting and intrinsically ensuring physics-consistent results.

• Journal of the Korean Society of Safety
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• v.28 no.1
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• pp.158-163
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• 2013

While job stress evaluations are reported in the recent surveys upon the nuclear power plants(NPPs), any significant advance in the types of questionnaires is not currently found. There are limitations to their usefulness as analytic tools for the management of safety resources in NPPs. Data mining(DM) has emerged as one of the key features for data computing and analysis to conduct a survey analysis. There are still limitations to its capability such as dimensionality associated with many survey questions and quality of information. Even though some survey methods may have significant advantages, often these methods do not provide enough evidence of causal relationships and the statistical inferences among a large number of input factors and responses. In order to address these limitations on the data computing and analysis capabilities, we propose an advanced procedure of survey analysis incorporating the DM method into a statistical analysis. The DM method can reduce dimensionality of risk factors, but DM method may not discuss the robustness of solutions, either by considering data preprocesses for outliers and missing values, or by considering uncontrollable noise factors. We propose three steps to address these limitations. The first step shows data mining with response surface method(RSM), to deal with specific situations by creating a new method called response surface data mining(RSDM). The second step follows the RSDM with detailed statistical relationships between the risk factors and the response of interest, and shows the demonstration the proposed RSDM can effectively find significant physical, psycho-social, and environmental risk factors by reducing the dimensionality with the process providing detailed statistical inferences. The final step suggest a robust stress management system which effectively manage job stress of the workers in NPPs as a part of a safety resource management using the surrogate variable concept.

• Nuclear Engineering and Technology
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• v.50 no.8
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• pp.1234-1245
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• 2018

The risk of multi-unit nuclear power plants (NPPs) at a site has received considerable critical attention recently. However, current probabilistic safety assessment (PSA) procedures and computer code do not support multi-unit PSA because the traditional PSA structure is mostly used for the quantification of single-unit NPP risk. In this study, the main purpose is to develop a multi-unit Level 2 PSA method and apply it to full-power operating six-unit OPR1000. Multi-unit Level 2 PSA method consists of three steps: (1) development of single-unit Level 2 PSA; (2) extracting the mapping data from plant damage state to source term category; and (3) combining multi-unit Level 1 PSA results and mapping fractions. By applying developed multi-unit Level 2 PSA method into six-unit OPR1000, site containment failure probabilities in case of loss of ultimate heat sink, loss of off-site power, tsunami, and seismic event were quantified.

• Proceedings of the KSME Conference
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• 2008.11b
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• pp.2606-2611
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• 2008

The high energy fluid leakage from the high temperature and high differential pressure drop system of NPPs (Nuclear Power Plants) decreases efficiency and consequently leads to considerable economic loss due to less power production. Also, the leakage possibly damages critical parts of components such as valve and trim with the effect of cavitation, flashing, and erosion, etc. and deteriorates its performance. Thus, in this study, we diagnosed the as-is leakage for four (4) main steam drain valves and two (2) steam traps of Yonggwang 1,2 units during normal operation by using multi-measuring technique and observed the occurrence of fine leakage. In the course of measuring fluid leakage, the sign of fine leakage is estimated to be the leakage from orifice. By converting the leakage to energy loss, it is equivalent to the amount of several hundred thousand won per each unit, which supports the basis for the justification of fine leakage.

• Transactions of the Korean Society of Pressure Vessels and Piping
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• v.9 no.1
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• pp.1-7
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• 2013

In around 2000, the U.S. NPPs have developed the various advanced engineering processes based on the INPO AP-913(Equipment Reliability Process Description) and showed the high performance in availability. With these benchmarking cases, the Korean NPPs have introduced the advanced engineering technology since 2005. The first step of the advanced engineering is to analyze and determine component importance for all components of a plant. This process is called Functional Importance Determination(FID). These results are basically utilized to determine the priority with limited resources in various areas. However, because the consistency of FID results is insufficient despite applying the same criteria in the existing operating NPPs, the degree of application is low. Therefore, this paper presents the improved methodology for FID interfacing system functions of Maintenance Rule Program and results of Single Point Vulnerability(SPV). This improved methodology is expected to contribute to enhance the reliability of FID data.

• Journal of Energy Engineering
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• v.23 no.2
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• pp.183-190
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• 2014

A Commercial Grade Item Dedication(CGID) for Korean operating nuclear power plants has been implemented since 2012. The CGID implementation and strategies for Korea are established as follows: CGID policy establishment, R&D of a specific methodologies of CGID, enrollment of third party organizations for CGID work, CGID program establishment for enrolled suppliers, establishment of training courses for certification, and CGID process development for quality class Q and A. Consequently, it is expected that these activities are enable to enhance the reliability and the safety of components and/or parts in nuclear power plants.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.27 no.5
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• pp.385-392
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• 2014

The isolators have been generally used to reduce a seismic force. If the isolators apply to the nuclear power plants(NPPs), the durability and capacity for the structures and equipments should be ensured during the life time. In this study, the long-term behavior of isolated NPPs was analyzed for ensuring the seismic safety. The properties of isolator due to the age-related degradation were analyzed. And the seismic behavior of isolated buildings was analyzed by considering the aging of rubber bearings in different temperature environments. According to the analysis results, the natural frequency of structures was increased with time. But the maximum acceleration and maximum displacement of isolated structures have not changed significantly. Although the damaged of structure did not occurred by aging of isolators, it was presented that the spectral acceleration at the target frequency of isolated structure increased with the temperature. Therefore the isolators in the isolated buildings should be carefully designed and manufactured considering the temperature-dependancy of rubber material.