• 한국태양에너지학회:학술대회논문집
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• 2008.11a
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• pp.280-287
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• 2008

In case of low pressure steam turbine used in power plant, it was operated in wet steam and high stress condition. Therefore, it is possible that the corrosion damage of low pressure was induced by this condition. According to previous study, about 30% of total blade failure correspond to corrosion fatigue or SCC(stress corrosion cracking) in low pressure turbine. Especially, LSB(last stage bucket) of low pressure turbine has a higher hardness to prevent erosion damage due to water droplet however, generally this is more dangerous for SCC damage. Therefore, to improve reliability of turbine blade. various methods for SCC evaluation has been developed. In this study, the crack found in LSB during in-service inspection was evaluated using microstructure analysis and stress analysis. From the stress analysis, the optimum size of fillet to remove the crack was proposed. And also, the reliability was evaluated for modified LSB using GOODMAN diagram.

• Corrosion Science and Technology
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• v.17 no.3
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• pp.116-122
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• 2018

The secondary coolant of a nuclear power plant has small amounts of various impurities (S, Pb, and Cl, etc.) introduced during the initial construction, maintenance, and normal operation. While the concentration of impurities in the feed water is very low, the flow of the cooling water is restricted, so impurities can accumulate on the Top of Tubesheet (TTS). This environment is chemically very complicated and has a very wide range of pH from acidic to alkaline. In this study, the characteristics of the oxide and the mechanism of stress corrosion cracking (SCC) are investigated for Alloy 690 TT in alkaline solution containing Pb, Cl, and S. Reverse U-bend (RUB) specimens were used to evaluate the SCC resistance. The test solution comprises 3m NaCl + 500ppm Pb + 0.31m $Na_2SO_4$ + 0.45m NaOH. Experimental results show that Alloy 690 TT of the crevice environment containing Pb, S, and Cl has significant cracks, indicating that Alloy 690 is vulnerable to stress corrosion cracking under this environment.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2003.11a
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• pp.361-364
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• 2003

The safe operation and reliable maintenance of nuclear power plants is one of the most fundamental and important tasks. It is known that a loose part such as a disengaged and drifting metal inside of reactor coolant systems might lead to a serious damage because of their impact on the components of the coolant system. In order to estimate the impact position of a loose par, three accelerometers attached to the wall of the coolant system have been used. These accelerometers measure the vibration of the coolant system induced by loose part impact. In the conventional analysis system, the low pass filtered version of the vibration data was used for the estimation of the position of a loose part. It is often difficult to identify the initial point of the impact signal by using just a low passed time signal because the impact wave is dispersed during propagation into the sensor. In this paper, the impact signal is analysed by use of various time frequency methods including the short time Fourier transform(STFT), the wavelet transform, and the Wigner-Vill distribution for finding a convenient way to identify the starting point of a impact signal and their advantages and limits are discussed.

• KSBB Journal
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• v.18 no.3
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• pp.234-238
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• 2003

Biofilm process is preferred to activated sludge process in small domestic wastewater treatment plant because of its simplicity in operation and maintenance. Column reactor filled with waste ceramics and with waste plastics was used to remove pollutants in restaurant wastewater. COD removal at 18 hours of hydraulic retention time (HRT) gave 93.7%, COD removal during the experimental period, where maximum COD removal was observed. Under same condition, average removal of total nitrogen and total phosphorus were 82.3% and 25.9%, respectively Organic and nitrogen were efficiently removed with the HRT of 18 hours or more.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.43 no.1
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• pp.123-131
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• 2020

There have been a lot of studies in the past for the method of predicting the failure of a machine, and recently, a lot of researches and applications have been generated to diagnose the physical condition of the machine and the parts and to calculate the remaining life through various methods. Survival models are also used to predict plant failures based on past anomaly cycles. In particular, special machine that reflect the fluid flow and process characteristics of chemical plants are connected to hundreds or thousands of sensors, so there are not many factors that need to be considered, such as process and material data as well as application of derivative variables. In this paper, the data were preprocessed through time series anomaly detection based on unsupervised learning to predict the abnormalities of these special machine. Next, clustering results reflecting clustering-based data characteristics were applied to produce additional variables, and a learning data set was created based on the history of past facility abnormalities. Finally, the prediction methodology based on the supervised learning algorithm was applied, and the model update was confirmed to improve the accuracy of the prediction of facility failure. Through this, it is expected to improve the efficiency of facility operation by flexibly replacing the maintenance time and parts supply and demand by predicting abnormalities of machine and extracting key factors.

• Journal of the Korean Society of Combustion
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• v.20 no.4
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• pp.10-18
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• 2015

Combustion instability is a major issue in design and maintenance of gas turbine combustors for efficient operation with low emissions. With the thermoacoustic view point the instability is induced by the interaction of the unsteady heat release of the combustion process and the change in the acoustic pressure in the combustion chamber. In an effort to study the combustion dynamics of gas turbine combustors, Morgans et al (2014) have developed OSCILOS (open source combustion instability low order simulator) code and it is currently available online. In this study the code has been utilized to predict the combustion instability of a reported case for lean premixed gas turbine combustion, and then its prediction results have been compared with the corresponding experimental data. It turned out that both the predicted and the experimental combustion instability results agree well. Further the effects of some typical inlet acoustic boundary conditions on the prediction have been investigated briefly. It is believed that the validity and effectiveness of the open source code is reconfirmed through this benchmark test.

• Corrosion Science and Technology
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• v.6 no.1
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• pp.29-32
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• 2007

The final goal of this study is to develop the core technologies applicable to the design, operation and maintenance of welds in nuclear structures. This study includes predicting microstructure changes and residual stress for welded parts of nuclear power plant components. Furthermore, researches are performed on evaluating fatigue, corrosion, and hydrogen induced cracking and finally constructs systematically integrated evaluation system for structural integrity of nuclear welded structures. In this study, metallurgical and mechanical approaches have been effectively coordinated considering real welding phenomena in the fields of welds properties such as microstructure, composition and residual stress, and in the fields of damage evaluations such as fatigue, corrosion, fatigue crack propagation, and stress corrosion cracking. Evaluation techniques tried in this study can be much economical and effective in that it uses theoretical/semi-empirical but includes many additional parameters that can be introduced in real phenomena such as phase transformation, strength mismatch and residual stress. It is clear that residual stress makes great contribution to fatigue and stress corrosion cracking. Therefore the mitigation techniques have been approached by reducing the residual stress of selected parts resulting in successful conclusions.

• Journal of Welding and Joining
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• v.16 no.1
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• pp.70-76
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• 1998

Most fossil power plants and many critical components will be approaching the end of their nominal design life. At the same time, utilities are finding it economically attractive to extend the use of these plants for several more years, Especially Main steam pipe that operated under high temperature and pressure, often under the more severe operating conditions associated with cycling duty, is most important pipe system and critical component in fossil power plant. To extend the viability of older pipe system and to improve the operation and maintenance reliability, some technologies of precise diagnosis and life management have evolved out of the necessity. The purpose of this study is to descrive the related technologies and show the example of one power plants. The purpose of this study is to descrive the related technologies and show the example of one power plants. The stress analysis was done using ANSYS FEM Code. The branch area from main steam to turbine was the high stressed zone. To evaluate the degradation of the pipe material, replica, visual check, magnetic test, hardness test were done at the welding spot. The degradation level of welding point was E/F, so the remaining life of the welded area was about 0-25%.

• Journal of the Korean Society of Safety
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• v.36 no.4
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• pp.1-11
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• 2021

Piping systems comprising pumps and valves are essential in the power plant, oil, and defense industry. Their purpose includes a stable supply of the working fluid or ensuring the target system's safe operation. However, piping system accidents due to leakage of toxic substances, explosions, and natural disasters are prevalent In addition, with the limited maintenance personnel, it becomes difficult to detect, isolate, and reconfigure the damage of the piping system and recover the unaffected area. An autonomous recovery piping system can play a vital role under such circumstances. The autonomous recovery algorithms for the piping system can be divided into low-pressure control algorithms, hydraulic resistance control algorithms, and flow inventory control algorithms. All three methods include autonomous opening/closing logic to isolate damaged areas and recovery the unaffected area of piping systems. However, because each algorithm has its strength and weakness, appropriate application considering the overall design, vital components, and operating conditions is crucial. In this regard, preliminary research on algorithm's working principle, its design procedures, and expected damage scenarios should be accomplished. This study examines the characteristics of algorithms, the design procedure, and working logic. Advantages and disadvantages are also analyzed through simulation results for a simplified piping system.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.46 no.3
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• pp.101-108
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• 2023

Although the proportion of coal-fired power generation is decreasing, efficient operating technology is needed to continuously invest in facilities and reduce maintenance costs until it is abolished. Boilers, one of the main facilities of power plants, operate for a long time in harsh environments of high temperature and high pressure. In addition, damage due to deterioration is likely to occur depending on the fuel and tube material used. It is very important to judge soundness because damage caused by deterioration adversely affects facility operation. Previously, replication method was used to analyze the progress of deterioration. In the replication method, pre-treatment such as chemical treatment is performed on the boiler tube in the field, the area is reproduced by attaching a film, and the replicated film is determined by an expert in the laboratory with an expensive microscope. However, this method involves substantial costs and time requirements, as well as the possibility of human errors. To address these issues, we developed a mobile health assessment system in this research. Since it is detachable and takes images in real time, this system enables swift evaluations across a broad range and facilitates the assessment of preprocessing quality. In addition, it was intended to reduce existing human mistakes by developing a degradation classification algorithm using the merger cluster method.