• Journal of the Korean Institute of Gas
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• v.25 no.2
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• pp.13-21
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• 2021

Because of the recent expansion of hydrogen vehicle supply, the installation of hydrogen filling station is expected to gradually expand. This study attempts to predict the damage scale and propose a safer design form based on the scenario that assumes the worst case of a hydrogen station. A Flacs solver using computational fluid dynamics (CFD) was used to predict the damage scale, and the accuracy was verified by comparing it with the experimental results of previous researchers. The damage scale prediction was conducted for hydrogen leakage and explosion, and the prediction target was the KR model based on the measured values. And as a comparative review model, a roofless model was selected without a ceiling. As a result of analyzing the two models, it was possible to confirm the accumulation and retention of hydrogen gas up to 60 vol% or more in the KR model, whereas in the case of the Roofless model, the phenomenon of discharge and diffusion to the outside of the charging station by riding the wall after leakage. I was able to check. In conclusion, it was reviewed that the type of hydrogen charging station without ceiling is more advantageous for safety than the hydrogen filling station model.

• Journal of Internet Computing and Services
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• v.22 no.2
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• pp.59-68
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• 2021

As artificial intelligence(AI) technologies, which have made rapid growth recently, began to be applied to the marine environment such as ships, there have been active researches on the application of CNN-based models specialized for digital videos. In E-Navigation service, which is combined with various technologies to detect floating objects of clash risk to reduce human errors and prevent fires inside ships, real-time processing is of huge importance. More functions added, however, mean a need for high-performance processes, which raises prices and poses a cost burden on shipowners. This study thus set out to propose a method capable of processing information at a high rate while maintaining the accuracy by applying Quantization techniques of a deep learning model. First, videos were pre-processed fit for the detection of floating matters in the sea to ensure the efficient transmission of video data to the deep learning entry. Secondly, the quantization technique, one of lightweight techniques for a deep learning model, was applied to reduce the usage rate of memory and increase the processing speed. Finally, the proposed deep learning model to which video pre-processing and quantization were applied was applied to various embedded boards to measure its accuracy and processing speed and test its performance. The proposed method was able to reduce the usage of memory capacity four times and improve the processing speed about four to five times while maintaining the old accuracy of recognition.

• Land and Housing Review
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• v.12 no.2
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• pp.109-120
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• 2021

Global warming due to increased carbon dioxide is perceived as one of the factors threatening the future. Efforts are being made to reduce carbon dioxide emissions in each industry around the world. In particular, environmental loads and impacts during the life cycle of SOC structures and buildings have been quantitatively assessed through a quantitative method called Life Cycle Assessment (LCA). However, the construction sector has gone through difficulty in quantitative assessment for several reasons: 1) LCI DB is not fully established; 2) the life cycle is very long; 3) the building structures are unique. Therefore, it takes enormous effort and time to carry out LCA. Rather than estimating carbon emissions with accuracy, this study aims to present a simplified estimation model that allows owners or designers to easily estimate carbon dioxide emissions with little effort, given that rapid and rough decisions regarding environmental load reduction are to be made. This study performs the LCA using data from 25 road construction projects across the country, followed by multiple regression analyses to derive a simplified carbon estimation model (SLCA). The study also carries out a comparative analysis with values estimated by performing a typical LCA. The comparison analysis shows an error rate of less than 5% for 16 road projects.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.20 no.2
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• pp.346-357
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• 2019

The purpose of this study was to examine the effects of flipped learning and explore the learners' experiences. Data were collected from 64 students who participated in flipped learning for 7 weeks at N university. The results were as follows. First, after applying flipped learning, learners feel more comfortable learning together and prefer collaborative learning. Second, flipped learning had no significant effects on learner's overall metacognition, but it had positive effects on the awareness and cognitive strategies. Third, flipped learning had no significant effects on academic self-efficacy, but it positively affected the task difficulty preference and confidence of learners who had a lower level of collaborative tendencies. Fourth, flipped learning had no significant effects on SDL ability, but it positively affected the learning plan of learners who had a higher level of collaborative tendencies. Fifth, learners' class satisfaction of flipped learning was generally very high. We suggested a policy, instructional design and strategies for effective implementation of flipped learning.

• Journal of Energy Engineering
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• v.27 no.4
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• pp.27-35
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• 2018

The passive containment cooling system (PCCS) has been designed to remove the released decay heat during the accident by means of the condensation heat transfer phenomenon to guarantee the safety of the nuclear power plant. The heat removal performance of the PCCS is mainly governed by the condensation heat transfer of the steam-air mixture. In this study, the heat removal performance of the PCCS was evaluated by using the MARS-KS code with a new empirical correlation for steam condensation in the presence of a noncondensable gas. A new empirical correlation implemented into the MARS-KS code was developed as a function of parameters that affect the condensation heat transfer coefficient, such as the pressure, the wall subcooling, the noncondensable gas mass fraction and the aspect ratio of the condenser tube. The empirical correlation was applied to the MARS-KS code to replace the default Colburn-Hougen model. The various thermal-hydraulic parameters during the operation of the PCCS follonwing a large-break loss-of-coolant-accident were analyzed. The transient pressure behavior inside the containment from the MARS-KS with the empirical correlation was compared with calculated with the Colburn-Hougen model.

• Korean Journal of Construction Engineering and Management
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• v.20 no.1
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• pp.114-123
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• 2019

Tracking ICT applications on construction business processes is critical to the success of ICT-applied construction projects. Existing IDEF0 is a representative modeling method for visualizing and analyzing business processes. It defines a construction production process into a visual information model, hence, encouraging the project participant to understand the activities, their deliverable, and control flow of the process. However, IDEF0 dose not lend itself to ICT-applied construction processes, because it does not provide a mean to define how, in what order, by which each and every activity that ICT applied implements. This paper presents a new business modeling method that improves the traceability of ICT application (IAMB: ICT Application tracking Model for Business process) for construction management. The IAMB contributes to handle the sophisticated features of construction management processes to which ICT are applied. The method categorizes the process into three types: management, construction, and information exchange. The validity of IAMB was confirmed by analyzing the performance when it is used for tracking each modeling step of lift reservation process which making use of ICT. The test case provides an admissible evidence that the method encourage to define who, what, how, which order, and by which ICT tools the construction process exchanges production information.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.39 no.1
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• pp.165-174
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• 2019

As a nonstationarity is observed in hydrological data, various studies on nonstationary frequency analysis for hydraulic structure design have been actively conducted. Although the inherent diversity in the atmosphere-ocean system is known to be related to the nonstationary phenomena, a nonstationary frequency analysis is generally performed based on the linear trend. In this study, a nonstationary frequency analysis was performed using climate indices as covariates to consider the climate variability and the long-term trend of the extreme rainfall. For 11 weather stations where the trend was detected, the long-term trend within the annual maximum rainfall data was extracted using the ensemble empirical mode decomposition. Then the correlation between the extracted data and various climate indices was analyzed. As a result, autumn-averaged AMM, autumn-averaged AMO, and summer-averaged NINO4 in the previous year significantly influenced the long-term trend of the annual maximum rainfall data at almost all stations. The selected seasonal climate indices were applied to the generalized extreme value (GEV) model and the best model was selected using the AIC. Using the model diagnosis for the selected model and the nonstationary GEV model with the linear trend, we identified that the selected model could compensate the underestimation of the rainfall quantiles.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.20 no.9
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• pp.175-181
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• 2019

In the case of a conventional single stage decompression regulator used for large depressurization in the hydrogen fuel cell system of a fuel cell electric vehicle (FCEV), problems can arise, such as pulsation, slow response, hydrogen brittleness, leakage, high weight, and high cost due to high decompression. Most of these problems can be overcome easily using two decompression mechanisms (two-stage structures). In addition, a wide outlet-pressure control range can be secured if an electronic solenoid is applied to the second decompression. Accordingly, it is necessary to improve the precision of the outlet pressure of a two-stage pressure-reducing regulator and develop techniques, such as leakage prevention, durability, light weight, and price reduction. Therefore, to improve the outlet pressure accuracy and prevent leakage, the structural part before and after decompression to improve the air tightness were divided and the analysis was carried out assuming that the valve part was closed (open ratio: 0%) after each initial internal pressure application.

• Asia-pacific Journal of Multimedia Services Convergent with Art, Humanities, and Sociology
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• v.9 no.6
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• pp.701-709
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• 2019

Recently, heart rate signal, which is one of biological signals, have been used in various fields related to healthcare. Conventionally, most of the proposed heart rate signal detection methods are contact type methods, but there is a problem of discomfort that the subject have to contact with the device. In order to solve the problem, detection study by non-contact method has been progressed recently. The detected heart rate signal can be used for finger vein liveness detection and various application using heart rate. In this paper, we propose a method to obtain heart rate signal by using finger vein imaging system. The proposed method detected the signal from the changes of the brightness value in the time domain of the infrared finger vein images and converted it into the frequency domain using the image processing algorithm. After the conversion, we removed the noise not related to the heart rate signal through band-pass filtering. In order to evaluate the accuracy of the signal, we analyzed the correlation with the signal obtained simultaneously with the finger vein acquisition device and contact type PPG sensor approved by KFDA. As a result, it was possible to confirm that the heart rate signal detected in non-contact method through the finger vein image coincides with the waveform of actual heart rate signal.

• Journal of Korean Society of Coastal and Ocean Engineers
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• v.32 no.6
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• pp.553-560
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• 2020

This paper presents an algorithm for identifying and eliminating errors by seagrasses in coastal bathymetry surveying using drone and HD camera. Survey errors due to seagrasses were identified, segmentated and eliminated using a L∗a∗b color space model. Bathymetry survey using a drone and HD camera has many advantages over conventional survey methods such as ship-board acoustic sounder or manual level survey which are time consuming and expensive. However, errors caused by sea bed reflectance due to seagrasses habitat hamper the development of new surveying tool. Seagrasses are the flowering plants which start to grow in November and flourish to maximum density until April in Korea. We developed a new algorithm for identifying seagrasses habitat locations and eliminating errors due to seagrasses to get the accurate depth survey data. We tested our algorithm at Wolpo beach. Bathymetry survey data which were obtained using a drone with HD camera and calibrated to eliminate errors due to seagrasses, were compared with depth survey data obtained using ship-board multi-beam acoustic sounder. The abnormal bathymetry data which are defined as the excess of 1.5 times of a standard deviation of random errors, are composed of 8.6% of the test site of area of 200 m by 300 m. By applying the developed algorithm, 92% of abnnormal bathymetry data were successfully eliminated and 33% of RMS errors were reduced.