• Nuclear Engineering and Technology
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• v.53 no.1
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• pp.148-163
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• 2021

Timely fault identification is important for safe and reliable operation of the electric valve system. Many research works have utilized different data-driven approach for fault diagnosis in complex systems. However, they do not consider specific characteristics of critical control components such as electric valves. This work presents an integrated shallow-deep fault diagnostic model, developed based on signals extracted from DN50 electric valve. First, the local optimal issue of particle swarm optimization algorithm is solved by optimizing the weight search capability, the particle speed, and position update strategy. Then, to develop a shallow diagnostic model, the modified particle swarm algorithm is combined with support vector machine to form a hybrid improved particle swarm-support vector machine (IPs-SVM). To decouple the influence of the background noise, the wavelet packet transform method is used to reconstruct the vibration signal. Thereafter, the IPs-SVM is used to classify phase imbalance and damaged valve faults, and the performance was evaluated against other models developed using the conventional SVM and particle swarm optimized SVM. Secondly, three different deep belief network (DBN) models are developed, using different acoustic signal structures: raw signal, wavelet transformed signal and time-series (sequential) signal. The models are developed to estimate internal leakage sizes in the electric valve. The predictive performance of the DBN and the evaluation results of the proposed IPs-SVM are also presented in this paper.

• Journal of the Korean Society of Systems Engineering
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• v.18 no.2
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• pp.94-107
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• 2022

Accidents prevention and mitigation is the highest priority of nuclear power plant (NPP) operation, particularly in the aftermath of the Fukushima Daiichi accident, which has reignited public anxieties and skepticism regarding nuclear energy usage. To deal with accident scenarios more effectively, operators must have ample and precise information about key safety parameters as well as their future trajectories. This work investigates the potential of machine learning in forecasting NPP response in real-time to provide an additional validation method and help reduce human error, especially in accident situations where operators are under a lot of stress. First, a base-case SGTR simulation is carried out by the best-estimate code RELAP5/MOD3.4 to confirm the validity of the model against results reported in the APR1400 Design Control Document (DCD). Then, uncertainty quantification is performed by coupling RELAP5/MOD3.4 and the statistical tool DAKOTA to generate a large enough dataset for the construction and training of neural-based machine learning (ML) models, namely LSTM, GRU, and hybrid CNN-LSTM. Finally, the accuracy and reliability of these models in forecasting system response are tested by their performance on fresh data. To facilitate and oversee the process of developing the ML models, a Systems Engineering (SE) methodology is used to ensure that the work is consistently in line with the originating mission statement and that the findings obtained at each subsequent phase are valid.

• Journal of the Korean Electrochemical Society
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• v.25 no.3
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• pp.119-124
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• 2022

Because high power with large size cell is used for the battery pack of hybrid electric vehicles and electric vehicles (HEV and EV), average temperature in a battery cell is the important criteria of the thermal management of the battery pack. Furthermore, fast charging technology is required to reduce battery charging time. Since battery pack performance and lifespan are deteriorated due to the heat of cells and electronic components caused by fast charging, an effective cooling system is required to reduce performance deterioration. In this study, a cooling system and module design applied to a pouch-type for fast charging battery cell are investigated, and the cooling performance that can maximize the efficiency of the battery was analyzed. The result shows that the vapor chamber cooling system has better cooling performance, the temperature drop in the module was 5.82 ℃ compared with aluminum cooling plates.

• Wind and Structures
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• v.35 no.4
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• pp.269-285
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• 2022

The pressure-mitigating effects of a high-speed train passing through a tunnel with a partially reduced cross-section are investigated via the numerical approach. A compressible, three-dimensional RNG k-ε turbulence model and a hybrid mesh strategy are adopted to reproduce that event, which is validated by the moving model test. Three step-like tunnel forms and two additional transitions at the tunnel junction are proposed and their aerodynamic performance is compared and scrutinized with a constant cross-sectional tunnel as the benchmark. The results show that the tunnel step is unrelated to the pressure mitigation effects since the case of a double-step tunnel has no advantage in comparison to a single-step tunnel, but the excavated volume is an essential matter. The pressure peaks are reduced at different levels along with the increase of the excavated earth volume and the peaks are either fitted with power or logarithmic function relationships. In addition, the Arc and Oblique-transitions have very limited gaps, and their pressure curves are identical to each other, whereas the Rec-transition leads to relatively lower pressure peaks in C_Pmax, C_Pmin, and ΔC_P, with 5.2%, 4.0%, and 4.1% relieved compared with Oblique-transition. This study could provide guidance for the design of the novel railway tunnel.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2021.10a
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• pp.243-245
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• 2021

Existing beacons are suitable for providing untact services, but they have the disadvantage of difficulty in accurate indoor positioning because the deviation in signal strength increases depending on the environment. In general, trilateration technique can reduce deviation, but if the distance between beacons is quite irregular, it becomes difficult to apply the algorithm. Therefore, in this paper, we studied how to reduce the signal power measurement error between beacons. First, we transformed the distance measurement formula using RSSI, assuming that the TX values were the same. In addition, we compared measurement errors with existing beacons by searching beacons with beacons scanner applications implemented with Android. As a result, it was confirmed that if a certain distance was further away, the measurement was measured more accurately than the non-changing beacon. Through this, accurate indoor positioning will be possible even in various disability situations. It is also expected that there will be more cases of establishing services that combine beacon with non-face-to-face services.

• Nuclear Engineering and Technology
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• v.27 no.4
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• pp.571-581
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• 1995

The generation, verification and validation of Emergency Procedures for Nuclear Power Plant is a difficult and complex process. Atomic Energy Control Board(AECB) requires that emergency procedure and plan be produced before obtaining the Operating License, that is, detailed plans and procedures to handle emergency situations for both on-site actions and off-site actions be developed. In this report Emergency Operating Procedures Standard for Canadian Nuclear Utilities which makes reference to U. S. practices and the current direction of emergency procedures for CAN-DU reactors are reviewed and compared based on scope(events covered), methodology (event-oriented or symptom-oriented or hybrid) and format(method of presentation) preponderantly, and an attempt is made to integrate these procedures and as a result the recommended strategy for Wolsong unit 2, 3, & 4 is presented as event-specific procedures, generic procedures(when event is not diagnosed) and whose format is combination of logic diagram and text.

• Journal of English Language & Literature
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• v.56 no.2
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• pp.187-217
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• 2010

By reading the main character, Rene Gallimard, in M. Butterfly as a spatial metaphor of America, this article examines how homogeneous American national identity of heterosexuality and white masculinity has been reinforced since the cold war and has constituted a crisis of hegemony with the decline of imperialism and how its pathological symptom is shown through the melancholic suicide of Gallimard. This article also argues how the feminine attributes implied in race, gender and sexuality in M. Butterfly are designated and allegorized as an impure, contaminated and ahistorical marker of national integrity in pthe social and material status of the heterosexual American white male. To develop my argument, I read M. Butterfly from a psychoanalytic point of view. Therefore I depend on Freud, Lacan, and Bhabha's psychoanalysis as the theoretical basis. In this paper, I also argue that the homogenized and fixed national identity is splitted and collapsed from within as shown in the Gallimard's melancholy and in the process of splitting the "Third Space" of hybrid subjects for the marginal and the emergent like Song Liling, a homosexual Asian man, can be built "from a space in-between." Therefore Hwang calls into questions conventions of fixed, essentialist identities through the shifting gender identities between Song and Gallimard in M. Butterfly and how identities in the plural are constructed variously in throughly historicized, politicized situations, and these constructions can be complicated by relations of power.

• Journal of Internet of Things and Convergence
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• v.10 no.2
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• pp.125-130
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• 2024

With the rapid growth of mobility technology, the industrial sector is demanding storage devices that can reliably process data from various equipment and sensors in vehicles. NAND flash memory is being utilized as a storage device in mobility environments because it has the advantages of low power and fast data processing speed as well as strong external shock resistance. However, flash memory is characterized by data corruption due to long-term exposure to high temperatures. Therefore, a dedicated system for temperature management is required in mobility environments where high temperature exposure due to weather or external heat sources such as solar radiation is frequent. This paper designs a dedicated temperature management system for managing storage device temperature in a mobility environment. The designed temperature management system is a hybrid of traditional air cooling and water cooling technologies. The cooling method is designed to operate adaptively according to the temperature of the storage device, and it is designed not to operate when the temperature step is low to improve energy efficiency. Finally, experiments were conducted to analyze the temperature difference between each cooling method and different heat dissipation materials, proving that the temperature management policy is effective in maintaining performance.

• Nuclear Engineering and Technology
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• v.56 no.7
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• pp.2718-2731
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• 2024

To ensure the operational safety of nuclear power plants, we present a Quadruped Inspection Robot that can be used for many types of steam generators. Since the Inspection Robot relies on the Holding Modules to grip the tube-sheet, it can be regarded as a hybrid robot with variable configurations, switching between 4-RRR-RR, 3-RRR-RR, and two types of 2-RRR-RR, and the variable configurations bring a great challenge to dimensional synthesis. In this paper, the kinematic model of the Inspection Robot in multiple configurations is established, and the analytical solution is given. The workspace mapping is analyzed by the solution-space, and the workspace of multiple configurations is decomposed into the workspace of 2-RRR to reduce the analysis complexity, and the workspace calculation is simplified by using the envelope rings. The optimization problem of the manipulator is transformed into the calculation of the shortest contraction length of the swing leg. The switching performance of the Inspection Robot is evaluated by stride-length, turning-angle, and workspace overlap-ratio. The performance indexes are classified and transformed based on the proportions and variation trends of dimensional parameters to reduce the number of optimization objective functions, and Pareto optimal solutions are obtained using an intelligent optimization algorithm.

• Journal of Electrochemical Science and Technology
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• v.15 no.3
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• pp.321-344
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• 2024

Transition metal compounds (TMCs) are being researched as promising electrode materials for electrochemical energy storage devices (supercapacitors). Among TMCs, transition metal phosphates (TMPs) have good, layered structures owing to open framework and protonic exchange capability among different layers, good surface area due to engrossed porosity, rich active redox reaction sites owing to octahedral structure and variable valance metallic ions. Hence TMPs become more ideal for supercapacitor electrode materials compared to other TMCs. However, TMPs have got some issues like low conductivity, rate performance, stability, energy, and power densities. But these problems can be addressed by making their composites with carbonaceous materials, e.g., carbon nanotubes (CNTs), graphene oxide (GO), graphitic carbon (GC), etc. A few factors like high surface area, excellent electrical conductivity of carbon materials and variable valence metal ions in TMPs caused great enhancement in their electrochemical performance. This article tries to discuss and compare the published data, majorly in last decade, regarding the electrochemical energy storage potential of pristine unary, binary, and ternary TMPs and their hybrid composites with carbonaceous materials (CNTs, GOs/rGOs, GC, etc.). The electrochemical performance of the hybrids has been reported to be higher than the pristine counterparts. It is hoped that the current review will open a new gateway to study and explore the high performance TMPs based supercapacitor materials.