• Journal of the Korean Society of Systems Engineering
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• v.18 no.1
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• pp.1-13
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• 2022

The Yongin Light Rail train was manufactured by Bombardier Transportation in Canada in 2008 and is a privately invested railway line that has been operating in Yongin-si, Gyeonggi-do, since 2013. When the frequency of train failure increases due to aging, and there is a delay in the delivery period of imported parts used in the Bombardier manufactured trains, timely vehicle maintenance may not be performed due to lack of parts. To solve this problem, it is necessary to build a 'vehicle parts maintenance demand forecasting system' that analyzes the accurate and actual maintenance demand annual based on the condition of vehicle parts. The full scope of analysis in this paper analyzes failure data from various angles after opening of Yongin light rail vehicle to analyze failure patterns for each part and identify replacement cycles according to possible failures and consumption of parts. Based on this study, it is expected that Yongin Light Rail's maintenance system will change from the existing time-based replacement (TBM) concept to the condition-based maintenance (CBM) concept. It is expected that this study will improve the efficiency of the Yongin Light Rail maintenance system and increase vehicle availability. This paper is a fundamental for establishing of a system for predicting the replacement timing of vehicle parts for Yongin Light Rail. It reports the results of data analysis on some vehicle parts.

• Journal of Advanced Navigation Technology
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• v.27 no.1
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• pp.63-70
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• 2023

In this work, a capacitive wireless power transfer (C-WPT) system is presented for wireless sensor system (WSS) applications in marine propulsion shafts. For a single Q factor on both sides of the coupling capacitor and reactive power removal from the circuit, a double-sided LCLC converter and transformers topology are designed to drive the rotary C-WPT system for WSS on the shaft. Parallel-connected parallel plate rotating capacitors with a capacitance of 170 pF are designed and implemented for the C-WPT system on a snow rotating shaft. In the experimental results, the C-WPT system achieved a transmission efficiency of 66.67% with 7.8 W output power at 3 mm distance and 1 MHz operating frequency. Therefore, it was proved that the fabricated C-WPT system can supply power to the WSS of the rotating shaft.

• Journal of the Semiconductor & Display Technology
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• v.22 no.1
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• pp.83-87
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• 2023

Y₂SiO₅ Powder based on silicon and yttrium is well known as powder phosphors due to their excellent sustainability and efficiency. A new electroluminescence device was fabricated with Y₂SiO₅:Eu³⁺ powder phosphors though a simple screen printing method. The powder-dispersed electroluminescence device consisted of the Y₂SiO₅:Eu³⁺ powder-dispersed phosphor layer and BaTiO₃-dispersed dielectric layer. The annealing temperature of the phosphor for the best powder electroluminescence performance was optimized to high temperature in ambient atmosphere though a solid-state reaction. The Eu³⁺ concentration for the best device performance was also investigated and furthermore, the thermal dependence of the electroluminescence intensity was investigated at the operating voltage at 100℃, which is the Curie temperature of the BaTiO₃ layer. And the intensity was exponentially increased with voltage and increased linearly with frequency.

• Journal of the Korean Applied Science and Technology
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• v.40 no.1
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• pp.71-80
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• 2023

Silver paste is a valuable electrode material for electronic device applications because it is easy to handle with relatively low heat treatment. This study treated the electrode surface using an atmospheric-pressure plasma jet on the silver-paste electrode. This plasma jet was generated in an argon atmosphere using a high voltage of 5.5 to 6.5 kV with an operating frequency of 11.5 kHz. Plasma-jet may be more beneficial to the printing process by performing it at atmospheric pressure. The electrode surface becomes hydrophilic quickly and contact angle variation is observed on the electrode surface as a function of plasma treatment time, applied voltage, and gas flow rate. Also, there was no deviation in the contact angle after the plasma treatment in the large-area sample, that means a uniform result could be obtained regardless of the substrate size. The outcomes of this study are expected to be very useful in forming a stacked structure in the manufacture of large-area electronic devices and future applications.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2022.05a
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• pp.306-309
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• 2022

Recently, the frequency of earthquakes is rapidly increasing in Korea. As a result, concerns about earthquakes are increasing. Response and recovery in the event of an earthquake are also important, but it is necessary to identify management vulnerabilities in advance and perform prevention and preparation activities. K-water collects real-time earthquake data by operating an earthquake accelerator to manage facilities safe from earthquakes. In addition, real-time data is transmitted to external organizations. Therefore, various efforts are being made to improve the quality of data. In order to reduce the management vulnerability of the earthquake monitoring system in advance, high-quality data can be produced by minimizing the delay time of data collection and establishing a real-time quality analysis system and base for earthquake data using big data. Accordingly, it is expected to protect the lives and property of the people from earthquake disasters by securing dam safety management and high-quality earthquake data and providing rapid data to external institutions.

• International conference on construction engineering and project management
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• 2022.06a
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• pp.1242-1242
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• 2022

Annually, several construction workers fall ill, are injured, or die due to heat-related exposure. The prevalence of work-related heat illness may rise and become an issue for workers operating in temperate climates, given the increase in frequency and intensity of heatwaves in the US. An increase in temperature negatively impacts physical exertion levels and mental state, thereby increasing the potential of accidents on the job site. To reduce the impact of heat stress on workers, it is critical to develop and implement measures for monitoring physical exertion levels and mental state in hot conditions. For this, limited studies have evaluated the utility of wearable biosensors in measuring physical exertion and mental workload in hot conditions. In addition, most studies focus solely on male participants, with little to no reference to female workers who may be exposed to greater heat stress risk. Therefore, this study aims to develop a process for objective and continuous assessment of worker physical exertion and mental workload using wearable biosensors. Physiological data were collected from eight (four male and four female) participants performing a simulated drilling task at 92oF and about 50% humidity level. After removing signal artifacts from the data using multiple filtering processes, the data was compared to a perceived muscle exertion scale and mental workload scale. Results indicate that biosensors' features can effectively detect the change in worker physical and mental state in hot conditions. Therefore, wearable biosensors provide a feasible and effective opportunity to continuously assess worker physical exertion and mental workload.

• The Journal of the Korea institute of electronic communication sciences
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• v.18 no.3
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• pp.483-494
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• 2023

Recently, gas turbine generators are widely used for frequency control of power systems. Although the inlet temperature of a gas turbine is a key factor related to the performance and lifespan of the device, the inlet temperature is not measured directly for reasons such as the turbine structure and operating environment. In particular, the inlet temperature of the reheating gas turbine is very important for stable operation management, but field workers are experiencing a lot of difficulties because the manufacturer does not provide information on the calculation formula. Therefore, in this study, we propose a method for estimating the inlet temperature of a gas turbine using a machine learning-based linear regression analysis method based on a polytropic process equation. In addition, by proposing an inlet temperature calculation algorithm through the usefulness analysis and verification of the inlet temperature calculation model obtained through linear regression analysis, it is intended to help to improve the level of reheat gas turbine combustion tuning technology.

• Journal of IKEEE
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• v.26 no.1
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• pp.77-82
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• 2022

The effect of the bias network on the performance of the W-band power amplifier(PA) was investigated. The performances of the typical RC and radial stub networks were examined, and a hybrid network was proposed for W-band application and its performance was confirmed. To verify this, a W-band PA was designed using a 60-nm GaN pHEMT process. When hybrid networks were applied, the PA had improved stability in all frequency bands, secured about 9 dB of power gain at operating frequencies 87 GHz to 93 GHz, and the maximum PAE was found to be about 12.3% at output power of 26.7 dBm.

• Journal of The Korean Society of Agricultural Engineers
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• v.65 no.1
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• pp.41-49
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• 2023

To utilize the hydraulic and hydrological models when simulating floods in agricultural watersheds, it is necessary to consider agricultural reservoirs, farmland, and farmland drainage system, which are characteristics of agricultural watersheds. However, most of them are developed individually by different researchers, also, each model has a different simulation scope, so it is hard to use them integrally. As a result, there is a need to link each hydraulic and hydrological model. Therefore, this study established an integrated flood simulation system for the comprehensive flood simulation of agricultural reservoir watersheds. The system can be applied easily to various watersheds because historical weather data and the SSP (Shared Socio-economic Pathways) climate change scenario database of ninety weather stations were built-in. Individual hydraulic and hydrological models were coded and coupled through Python. The system consists of multiplicative random cascade model, Clark unit hydrograph model, frequency analysis model, HEC-5 (Hydrologic Engineering Center-5), HEC-RAS (Hydrologic Engineering Center-River Analysis System), and farmland drainage simulation model. In the case of external models with limitations in conceptualization, such as HEC-5 and HEC-RAS, the python interpreter approaches the operating system and gives commands to run the models. All models except two are built based on the logical concept.

• Journal of The Geomorphological Association of Korea
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• v.27 no.3
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• pp.87-103
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• 2020

The purpose of this study is to evaluate the risk of cropland and man-made infrastructures in a landslide-prone area using a GIS-based method. To achieve this goal, a landslide inventory map was prepared based on aerial photograph analysis as well as field observations. A total of 550 landslides have been counted in the entire study area. For model analysis and validation, extracted landslides were randomly selected and divided into two groups. The landslide causative factors such as slope, aspect, curvature, topographic wetness index, elevation, forest type, forest crown density, geology, land-use, soil drainage, and soil texture were used in the analysis. Moreover, to identify the correlation between landslides and causative factors, pixels were divided into several classes and frequency ratio was also extracted. A landslide susceptibility map was constructed using a bayesian predictive model (BPM) based on the entire events. In the cross validation process, the landslide susceptibility map as well as observation data were plotted with a receiver operating characteristic (ROC) curve then the area under the curve (AUC) was calculated and tried to extract a success rate curve. The results showed that, the BPM produced 85.8% accuracy. We believed that the model was acceptable for the landslide susceptibility analysis of the study area. In addition, for risk assessment, monetary value (local) and vulnerability scale were added for each social thematic data layers, which were then converted into US dollar considering landslide occurrence time. Moreover, the total number of the study area pixels and predictive landslide affected pixels were considered for making a probability table. Matching with the affected number, 5,000 landslide pixels were assumed to run for final calculation. Based on the result, cropland showed the estimated total risk as US $ 35.4 million and man-made infrastructure risk amounted to US $ 39.3 million.