• Journal of the Korea Academia-Industrial cooperation Society
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• v.22 no.3
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• pp.587-596
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• 2021

Naval battleships have systems to perform special purposes, such as the Command and Fire Control System (CFCS). Some of the this equipment should be equipped with an Uninterruptible Power System (UPS ) to ensure operational continuity and the backup of important data, even during unexpected power outages caused by problems with the ship's power generator. Heavy combat losses can occur if the equipment cannot satisfy the function. Therefore, it is important to design a stable UPS. The battery and Battery Management System (BMS) are two of the most important factors for designing a stable UPS. A power outage will be encountered if the battery and BMS are not stable. The customer will be exposed to abnormal situations, loss of important tactical data, and inability to operate some of the CFCS. As a result, an enhanced safety system should be designed. Thus, this study implemented and verified the improved system in terms of three methods, such as comparative analysis of the batteries, improvement about leakage current of the circuit, and tests of the aggressive environmental resistance to improve the UPS for CFCS.

• Journal of the Korean Society of Marine Environment & Safety
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• v.28 no.1
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• pp.184-192
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• 2022

Valve internal leakage is caused by damage to the internal parts of the valve, resulting in accidents and shutdowns of the piping system. This study investigated the possibility of a real-time leak detection method using the acoustic emission (AE) signal generated from the piping system during the internal leakage of a butterfly valve. Datasets of raw time-domain AE signals were collected and postprocessed for each operation mode of the valve in a systematic manner to develop a data-driven model for the detection and classification of internal leakage, by applying machine learning algorithms. The aim of this study was to determine whether it is possible to treat leak detection as a classification problem by applying two classification algorithms: support vector machine (SVM) and convolutional neural network (CNN). The results showed different performances for the algorithms and datasets used. The SVM-based binary classification models, based on feature extraction of data, achieved an overall accuracy of 83% to 90%, while in the case of a multiple classification model, the accuracy was reduced to 66%. By contrast, the CNN-based classification model achieved an accuracy of 99.85%, which is superior to those of any other models based on the SVM algorithm. The results revealed that the SVM classification model requires effective feature extraction of the AE signals to improve the accuracy of multi-class classification. Moreover, the CNN-based classification can be a promising approach to detect both leakage and valve opening as long as the performance of the processor does not degrade.

• Nuclear Engineering and Technology
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• v.54 no.7
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• pp.2728-2735
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• 2022

The research on the flow and heat transfer characteristics of lead bismuth(LBE) is significant for the thermal-hydraulic calculation, safety analysis and practical application of lead-based fast reactors(LFR). In this paper, a new CFD model is proposed to solve the thermal-hydraulic analysis of LBE. The model includes two parts: turbulent model and turbulent Prandtl, which are the important factors for LBE. In order to find the best model, the experiment data and design of 19-pin hexagonal rod bundle with spacer grid, undertaken at the Karlsruhe Liquid Metal Laboratory (KALLA) are used for CFD calculation. Furthermore, the turbulent model includes SST k - 𝜔 and k - 𝜀; the turbulent Prandtl includes Cheng-Tak and constant (Pr_t =1.5,2.0,2.5,3.0). Among them, the combination between SST k - 𝜔 and Cheng-Tak is more suitable for the experiment. But in the low Pe region, the deviation between the experiment data and CFD result is too much. The reason may be the inlet-effect and when Pe is in a low level, the number of molecular thermal diffusion occupies an absolute advantage, and the buoyancy will enhance. In order to test and verify versatility of the model, the NCCL performed by the Nuclear Thermal-hydraulic Laboratory (Nuthel) of Xi'an Jiao tong University is used for CFD to calculate. This paper provides two verification examples for the new universal model.

• Korean Journal of Remote Sensing
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• v.38 no.6_1
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• pp.1541-1555
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• 2022

Red tide has potential to harm marine ecology and aquaculture. Research on detecting red tide using various optical remote sensors has been conducted, but most of existing algorithms for detecting red tide has limitations, especially in shallow coastal waters with high levels of suspended sediment. For enhanced understanding of the optical behavior of red tide waters, analysis on remote sensing reflectance and water constituent is becoming increasingly important. This study analyzed the optical remote sensing data and water quality variables(Chl-a_(Spec), SPM, a_ph, a_d, Turbidity, Chl-a_(HPLC), Dominant species) of red tide waters. The data were collected from ship-based campaigns. In addition to the research on detecting red tide, the remote sensing reflectance and extinction coefficients for mesodinium and cochlodinium species were also analyzed. Through the analysis, it was possible to estimate the red tide chlorophyll concentration based on a specific wavelength of the remote sensing reflectance. The study found that chlorophyll concentration and phytoplankton absorption coefficient were highly correlated(R²=0.9), and that the RE_diff formula provided a more accurate estimate of red tide concentration than the B-G ratio.

• Journal of the Institute of Convergence Signal Processing
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• v.23 no.2
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• pp.76-83
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• 2022

With the recent development of IT technology, research and interest in various biosignal measuring devices is increasing. As an aging society is in full swing, research on the elderly population using IT-related technologies is continuously developing. This study is about the development of life pattern detection and fall detection algorithm, which is one of the medical service areas for the elderly, who are rapidly developing as they enter a super-aged society. This study consisted of a system using a 3-axis accelerometer and an electrocardiogram sensor, collected data, and then analyzed the data. It was confirmed that behavioral patterns could be classified from the actual research results. In order to evaluate the usefulness of the human activity monitoring system implemented in this study, experiments were performed under various conditions, such as changes in posture and walking speed, and signal magnitude range and signal vector magnitude parameters reflecting the acceleration of gravity of the human body and the degree of human activity. was extracted. And the possibility of discrimination according to the condition of the subject was examined by these parameter values.

• Journal of Navigation and Port Research
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• v.47 no.3
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• pp.167-173
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• 2023

The manufacturing industry is the backbone of the Korean economy. Among them, the petrochemical industry is a strategic growth industry, which makes a profit through reexports based on eminent technology in South Korea which imports all of its crude oil. South Korea imports whole amount of crude oil, which is the raw material for many manufacturing industries, by sea transportation. Therefore, it must respond swiftly to a highly volatile tanker freight market. This study aimed to make an early warning model of crude oil shipping market using a signal approach. The crisis of crude oil shipping market is defined by BDTI. The overall leading index is made of 38 factors from macro economy, financial data, and shipping market data. Only leading correlation factors were chosen to be used for the overall leading index. The overall leading index had the highest correlation coefficient factor of 0.499 two months ago. It showed a significant correlation coefficient five months ago. The QPS value was 0.13, which was found to have high accuracy for crisis prediction. Furthermore, unlike other previous time series forecasting model studies, this study quantitatively approached the time lag between economic crisis and the crisis of the tanker ship market, providing workers and policy makers in the shipping industry with an framework for strategies that could effectively deal with the crisis.

• Journal of Korea Port Economic Association
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• v.39 no.2
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• pp.1-13
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• 2023

This study forecasted the manpower demand of eco-friendly smart shipbuilding, whose importance and weight are increasing according to the environmental regulations of the IMO and the spread of the 4th industrial revolution technology. It predicted the shipbuilding industry manpower by applying various models of trend analysis and time series analysis based on data from 2000 to 2020 of Statistics Korea. It was found that the prediction applying geometric mean had the smallest gap among the trend and time series analysis methods in comparing between forecast results and actual data for the past 5 years. Therefore, the demand for manpower in the shipbuilding industry was predicted by using the geometric mean method. In addition, the manpower demand of smart eco-friendly ships wast forecasted by using the 2018 and 2020 manpower survey results of the Ministry of Trade, Industry and Energy and reflecting the trend of manpower increase in the shipbuilding industry. The result of forecasting showed that 62,001 person in 2025 and 85,035 people in 2030. This study is expected to contribute to the adjustment of manpower supply and demand and the training professional manpower in the future by increasing the accuracy of forecasting for high value-added eco-friendly smart ships.

• Journal of the Korean Society of Marine Environment & Safety
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• v.29 no.7
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• pp.910-914
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• 2023

With the technological innovation owing to the 4th industrial revolution, the maritime transportation is rapidly being developed with autonomous ships and systems. Particularly, autonomous ships will partially replace the manned ships and navigation among them remotely upon the degree of autonomy suggested by IMO. Accordingly, the remote operator and related research have increased as well. However, the data on the minimum required manpower for remote operators are lacking such as considering engage required situations and their co-occurrence probability. Therefore, this study proposes a simulation model that calculates the number of remote engage required situations by defining restricted water area and remote engage required situation as close-quarter situations based on accumulated trajectory data of actual ships. The findings are expected to be used as background materials to establish the appropriate manpower distribution of remote operators in remote operation centers.

• Applied Chemistry for Engineering
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• v.34 no.6
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• pp.603-607
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• 2023

Aqueous film forming foam (AFFF) is a critical fire suppression agent used in combating hydrocarbon fires. This type of fire suppressant is highly effective due to its ability to form a protective film, dissipate heat, inhibit combustion, and utilize a blend of chemical substances to extinguish fires. While these properties offer significant advantages in responding to hydrocarbon fires, AFFF is distinct in its deployment as it is dispensed in the form of foam. Therefore, the rheological analysis of AFFF foam using a rheometer plays a crucial role in predicting the spray characteristics of AFFF for combating hydrocarbon fires, and this is closely associated with effective fire suppression. In this study, we conducted rheometer experiments to confirm the non-Newtonian behavior (shear-thinning) of AFFF foam and obtained data on the form's stability. These experimental data are expected to contribute to enhancing the efficiency of fire suppression systems utilizing AFFF.

• The Sea:JOURNAL OF THE KOREAN SOCIETY OF OCEANOGRAPHY
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• v.14 no.4
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• pp.195-204
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• 2009

In order to estimate sea surface current fields in the East Sea, we examined characteristics of mean dynamic topography (MDT) fields (or mean surface current field, MSC) generated from three different methods. This preliminary investigation evaluates the accuracy of surface currents estimated from satellite-derived sea level anomaly (SLA) data and three MDT fields in the East Sea. AVISO (Archiving, Validation and Interpretation of Satellite Oceanographic data) provides a MDT field derived from satellite observation and numerical models with $0.25^{\circ}$ horizontal resolution. Steric height field relative to 500 dbar from temperature and salinity profiles in the East Sea supplies another MDT field. Trajectory data of surface drifters (ARGOS) in the East Sea for 14 years provide another MSC field. Absolute dynamic topography (ADT) field is calculated by adding SLA to each MDT. Application of geostrophic equation to three different ADT fields yields three surface geostrophic current fields. Comparisons were made between the estimated surface currents from the three different methods and in-situ current measurements from a ship-mounted ADCP (Acoustic Doppler Current Profiler) in the southwestern East Sea in 2005. For offshore areas more than 50 km away from the land, the correlation coefficients (R) between the estimated versus the measured currents range from 0.58 to 0.73, with 17.1 to $21.7\;cm\;s^{-1}$ root mean square deviation (RMSD). For coastal ocean within 50 km from the land, however, R ranges from 0.06 to 0.46 and RMSD ranges from 15.5 to $28.0\;cm\;s^{-1}$. Results from this study reveal that a new approach in producing MDT and SLA is required to improve the accuracy of surface current estimations for the shallow costal zones of the East Sea.