• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2022.05a
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• pp.322-323
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• 2022

The most necessary thing for the optimal operation of a water purification plant is to accurately predict the pattern and amount of tap water used by consumers. The required amount of tap water should be delivered to the drain using a pump and stored, and the required flow rate should be supplied in a timely manner using the minimum amount of electrical energy. The short-term demand forecasting required from the point of view of energy optimization operation among water purification plant volume predictions has been made in consideration of seasons, major periods, and regional characteristics using time series analysis, regression analysis, and neural network algorithms. In this paper, we analyzed energy management methods through AI-based complex sensor applicability analysis such as LSTM (Long Short-Term Memory) and GRU (Gated Recurrent Units), which are types of cyclic neural networks.

• Nuclear Engineering and Technology
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• v.54 no.11
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• pp.4134-4145
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• 2022

The collimator is one of the high-heat-flux components used to avoid a series of vacuum and thermal problems. In this paper, the heat load distribution throughout the collimator is first calculated through experimental data, and a transient thermodynamic simulation analysis of the original model is carried out. The error of the pipe outlet temperature between the simulated and experimental values is 1.632%, indicating that the simulation result is reliable. Second, the model is optimized to improve the heat transfer performance of the collimator, including the contact mode between the pipe and the flange, the pipe material and the addition of a twisted tape in the pipe. It is concluded that the convective heat transfer coefficient of the optimized model is increased by 15.381% and the maximum wall temperature is reduced by 16.415%; thus, the heat transfer capacity of the optimized model is effectively improved. Third, to adapt the long-pulse steady-state operation of the experimental advanced superconducting Tokamak (EAST) in the future, steady-state simulations of the original and optimized collimators are carried out. The results show that the maximum temperature of the optimized model is reduced by 37.864% compared with that of the original model. The optimized model was changed as little as possible to obtain a better heat exchange structure on the premise of ensuring the consumption of the same mass flow rate of water so that the collimator can adapt to operational environments with higher heat fluxes and long pulses in the future. These research methods also provide a reference for the future design of components under high-energy and long-pulse operational conditions.

• Korean Journal of Materials Research
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• v.33 no.3
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• pp.106-114
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• 2023

The carbon concentration in the carburized steels was measured by electron probe microanalysis (EPMA) for a range of soluted carbon content in austenite from 0.1 to 1.2 wt%. This study demonstrates the problems in carbon quantitative analysis using the existing calibration curve derived from pure iron (0.008 wt%C) and graphite (99.98 wt%C) as standard specimens. In order to derive an improved calibration curve, carbon homogenization treatment was performed to produce a uniform Kα intensity in selected standard samples (AISI 8620, AISI 4140, AISI 1065, AISI 52100 steel). The trend of detection intensity was identified according to the analysis condition, such as accelerating voltage (10, 15, 30 keV), and beam current (20, 50 nA). The appropriate analysis conditions (15 keV, 20 nA) were derived. When the carbon concentration depth profile of the carburized specimen was measured for a short carburizing time using the improved calibration curve, it proved to be a more reliable and accurate analysis method compared to the conventional analysis method.

• Journal of Internet of Things and Convergence
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• v.9 no.3
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• pp.61-67
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• 2023

In order to optimize the pulse electroforming copper process, a double hidden layer BP (Back Propagation) neural network is constructed. Through sample training, the mapping relationship between electroforming copper process conditions and target properties is accurately established, and the prediction of microhardness and tensile strength of the electroforming layer in the pulse electroforming copper process is realized. The predicted results are verified by electrodeposition copper test in copper pyrophosphate solution system with pulse power supply. The results show that the microhardness and tensile strength of copper layer predicted by "3-4-3-2" structure double hidden layer neural network are very close to the experimental values, and the relative error is less than 2.32%. In the parameter range, the microhardness of copper layer is between 100.3~205.6MPa and the tensile strength is between 112~485MPa.When the microhardness and tensile strength are optimal,the corresponding process conditions are as follows: current density is 2A-dm-2, pulse frequency is 2KHz and pulse duty cycle is 10%.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2021.05a
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• pp.260-262
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• 2021

In recent years, many studies are being conducted to reduce the damage to humans in the event of a fire. In case of fire in large cities, evacuation route guidance services are provided using Mobile GIS (geographic information system). However, among the algorithms used in the existing evacuation route system, Dijkstra Algorithm has a problem that when the cost is negative, it cannot obtain an infinite loop or an accurate result value, and does not help to select an appropriate shortest route by searching all routes. For this reason, in this paper, we propose the shortest route guidance system based on A^* Algorithm. In case of fire, the shortest route is searched and the shortest route is visualized and provided using a map service on a mobile device using mobile GIS.

• Nuclear Engineering and Technology
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• v.55 no.5
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• pp.1587-1592
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• 2023

Time-encoded imagers (TEI) are important class of instruments to search for potential radioactive sources to prevent illicit transportation and trafficking of nuclear materials and other radioactive sources. The energy of the radiation cannot be known in advance due to the type and shielding of source is unknown in practice. However, the response function of the time-encoded imagers is related to the energy of neutrons or gamma-rays. An improved image reconstruction method based on MLEM was proposed to correct for the energy induced response difference. In this method, the count vector versus time was first smoothed. Then, the preset response function was adaptively corrected according to the measured counts. Finally, the smoothed count vector and corrected response were used in MLEM to reconstruct the source distribution. A one-dimensional dual-particle time-encode imager was developed and used to verify the improved method through imaging an Am-Be neutron source. The improvement of this method was demonstrated by the image reconstruction results. For gamma-ray and neutron images, the angular resolution improved by 17.2% and 7.0%; the contrast-to-noise ratio improved by 58.7% and 14.9%; the signal-to-noise ratio improved by 36.3% and 11.7%, respectively.

• 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.55 no.7
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• pp.2628-2641
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• 2023

Nuclear safety is the lifeline for the development and application of nuclear energy. In severe accidents of pressurized water reactor (PWR), aerosols, as the main carrier of fission products, are suspended in the containment vessel, posing a potential threat of radioactive contamination caused by leakage into the environment. The gas-phase aerosols suspended in the containment will settle onto the wall or sump water through the natural deposition mechanism, thereby reducing atmospheric radioactivity. Aiming at the low accuracy of the aerosol model in the ISAA code, this paper improves the natural deposition model of aerosol in the containment. The aerosol dynamic shape factor was introduced to correct the natural deposition rate of non-spherical aerosols. Moreover, the gravity, Brownian diffusion, thermophoresis and diffusiophoresis deposition models were improved. In addition, ABCOVE, AHMED and LACE experiments were selected to validate and evaluate the improved ISAA code. According to the calculation results, the improved model can more accurately simulate the peak aerosol mass and respond to the influence of the containment pressure and temperature on the natural deposition rate of aerosols. At the same time, it can significantly improve the calculation accuracy of the residual mass of aerosols in the containment. The performance of improved ISAA can meet the requirements for analyzing the natural deposition behavior of aerosol in containment of advanced PWRs in severe accident. In the future, further optimization will be made to address the problems found in the current aerosol model.

• Nuclear Engineering and Technology
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• v.55 no.7
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• pp.2621-2627
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• 2023

In Experimental Advanced Superconducting Tokamak (EAST) experiments, to achieve long pulse and high-power ICRH system operation, a new kind of ICRH antenna has been designed. One of the most critical factors in limiting the operation of long pulse and high power is the intense heat load in the front face of the ICRH antenna, especially the Faraday Screen (FS). Therefore, the cooling channels of FS need to be designed. According to thermal-hydraulic analysis, the FS tubes are divided into several groups to achieve more excellent water cooling capability. The number of series and parallel tubes in one group is chosen as six. This antenna went into service in the spring of 2021, and it is delightful that the temperature distribution of the FS tube is below 400 ℃ in 14.5 s and 1.8 MW ICRH system operation. However, the active water-cooling design was not carried out on the upper and lower plates of FS, which led to severe ablations on that region under long pulse and high power operation, and the temperature is up to 800. Therefore, the upper and lower side plates of the FS were designed with water cooling based on thermal-hydraulic analysis. During the 2022 winter experiments, the temperature of ICRH antenna FS was lower than 400 in the pulse of 200s and the power of 1 MW operation.

• The Journal of the Acoustical Society of Korea
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• v.42 no.4
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• pp.357-363
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• 2023

In underwater signal processing, separating individual signals from mixed signals has long been a challenge due to low signal quality. The common method using Short-time Fourier transform for spectrogram analysis has faced criticism for its complex parameter optimization and loss of phase data. We propose a Triple-path Recurrent Neural Network, based on the Dual-path Recurrent Neural Network's success in long time series signal processing, to handle three-dimensional tensors from multi-channel sensor input signals. By dividing input signals into short chunks and creating a 3D tensor, the method accounts for relationships within and between chunks and channels, enabling local and global feature learning. The proposed technique demonstrates improved Root Mean Square Error and Scale Invariant Signal to Noise Ratio compared to the existing method.