• KOREAN JOURNAL OF PACKAGING SCIENCE & TECHNOLOGY
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• v.28 no.2
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• pp.143-149
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• 2022

PCS needs to freely switch AC and DC to connect the battery, external AC loads and renewable energy in both directions for energy efficiency. Whenever converting happens, power loss inevitably occurs. Minimization of the power loss to save electricity and convert it for usage is a very critical function in PCS. PCS plays an important role in the ESS(Energy Storage System) but the importance of stabilizing semiconductors on PCB(Printed Circuit Board) should be empathized with a risk of failure such as a fire explosion. In this study, the temperature variation inside PCS was reviewed by cooling fan on top of PCS, and the vibration characteristics of PCS were analyzed during truck transportation for reliability of the product. In most cases, a cooling fan is mounted to control the inner temperature at the upper part of the PCS and components generating the heat placed on the internal aluminum cooling plate to apply the primary cooling and the secondary cooling system with inlet fans for the external air. Results of CFD showed slightly lack of circulating capacity but simulated temperatures were durable for components. The resonance points of PCS were various due to the complexity of components. Although they were less than 40 Hz which mostly occurs breakage, it was analyzed that the vibration displacement in the resonance frequency band was very insufficient. As a result of random-vibration simulation, the lower part was analyzed as the stress-concentrated point but no breakage was shown. The steel sheet could be stable for now, but for long-term domestic transportation, structural coupling may occur due to accumulation of fatigue strength. After the test completed, output voltage of the product had lost so that extra packaging such as bubble wrap should be considered.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.21 no.3
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• pp.42-52
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• 2022

Bus Information System (BIS) services are expanding nationwide to small and medium-sized cities, including large cities, and user satisfaction is continuously improving. In addition, technology development related to improving reliability of bus arrival time and improvement research to minimize errors continue, and above all, the importance of information accuracy is emerging. In this study, accuracy performance was evaluated using LSTM, a machine learning method, and compared with existing methodologies such as Kalman filter and neural network. As a result of analyzing the standard error for the actual travel time and predicted values, it was analyzed that the LSTM machine learning method has about 1% higher accuracy and the standard error is about 10 seconds lower than the existing algorithm. On the other hand, 109 out of 162 sections (67.3%) were analyzed to be excellent, indicating that the LSTM method was not entirely excellent. It is judged that further improved accuracy prediction will be possible when algorithms are fused through section characteristic analysis.

• Steel and Composite Structures
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• v.48 no.1
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• pp.27-41
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• 2023

Under the long-term effect of corrosive environment, many cold-formed steel (CFS) structures have serious corrosion problems. Corrosion leads to the change of surface morphology and the loss of section thickness, which results in the change of instability mode and failure mechanism of CFS structure. This paper mainly investigates the elastic local buckling behavior of corroded CFS columns. The surface morphology scanning test was carried out for eight CFS columns accelerated corrosion by the outdoor periodic spray test. The thin shell finite element (FE) eigen-buckling analysis was also carried out to reveal the influence of corrosion surface characteristics, corrosion depth, corrosion location and corrosion area on the elastic local buckling behaviour of the plates with four simply supported edges. The accuracy of the proposed formulas for calculating the elastic local buckling stress of the corroded plates and columns was assessed through extensive parameter studies. The results indicated that for the plates considering corrosion surface characteristics, the maximum deformation area of local buckling was located at the plates with the minimum average section area. For the plates with localized corrosion, the main buckling shape of the plates changed from one half-wave to two half-wave with the increase in corrosion area length. The elastic local buckling stress decreased gradually with the increase in corrosion area width and length. In addition, the elastic local buckling stress decreased slowly when corrosion area thickness was relatively large, and then tends to accelerate with the reduction in corrosion area thickness. The distance from the corrosion area to the transverse and longitudinal centerline of the plate had little effect on the elastic local buckling stress. Finally, the calculation formula of the elastic local buckling stress of the corroded plates and CFS columns was proposed.

• Journal of the Korean Society of Marine Environment & Safety
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• v.28 no.5
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• pp.780-790
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• 2022

Quantitative risk levels must be presented by analyzing the causes and consequences of accidents and predicting the occurrence patterns of the accidents. For the analysis of marine accidents related to vessel traffic, research on the traffic such as collision risk analysis and navigational path finding has been mainly conducted. The analysis of the occurrence pattern of marine accidents has been presented according to the traditional statistical analysis. This study intends to present a marine accident prediction model using the statistics on marine accidents related to vessel traffic. Statistical data from 1998 to 2021, which can be accumulated by month and hourly data among the Korean domestic marine accidents, were converted into structured time series data. The predictive model was built using a long short-term memory network, which is a representative artificial intelligence model. As a result of verifying the performance of the proposed model through the validation data, the RMSEs were noted to be 52.5471 and 126.5893 in the initial neural network model, and as a result of the updated model with observed datasets, the RMSEs were improved to 31.3680 and 36.3967, respectively. Based on the proposed model, the occurrence pattern of marine accidents could be predicted by learning the features of various marine accidents. In further research, a quantitative presentation of the risk of marine accidents and the development of region-based hazard maps are required.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.38 no.1
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• pp.57-67
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• 2020

Recently, smart cities are attracting attention as a solution for a plethora of urban problems, including transportation, environment, safety, and energy. However, despite a substantial body of research dealt with the concept, trends, policy, and legal institutions of smart cities, few researchers have examined how the smart city services influence the cities from the dynamic perspective that considers the entire cycle of a city, including its growth, stagnation, and decline. Thus, it is vital to understand how the city changes with time from the view that a city is a system of sub-elements-population, industry, transportation, environment, housing, and land-closely interacting together. Within this context, this study explores how the urban dynamics of Anyang-city develop for the long term using the System Dynamics method and analyzes the effect of smart city project investment on the dynamics of Anyang-city. According to the result, Anyang-city is a "mature and stable" type, and its population is expected to decrease slowly by 2040. Specifically, the Anyang-city population will be reduced to 553,000 by 2030. It was analyzed that the number will decrease to 543,000 by 2040. It was also found that the investment in smart city projects in Anyang, based on the Plan for Anyang Smart City, would have the following effects: easing population decline, increasing number of businesses, improving urban safety index, and increasing average driving speed. The population will grow by 4,000 and the number of businesses will increase by 761 than before budget investment. The result of this paper is expected to contribute to identifying and predicting the effect of smart city policies from a long-term perspective.

• Economic and Environmental Geology
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• v.54 no.4
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• pp.475-482
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• 2021

This study proposed a strategy with literature review on effective monitoring of dispersion of the particulate matters (PM) emitted from domestic open pit lime mines. The mines generally produced a large amount of PM through the mine processes such as crushing and transportation of raw or crushed ores. The PM emission from mine facilities or transportation can be assessed using empirical equations which was prepared through the experimental tests to produce PM from ores. For effective monitoring of mine PM dispersion, this study showed a preliminary application of the monitoring network with multiple low-cost sensors around a main PM emission source for each mine site. Therefore, two domestic limestone mine sites were selected for this study, and install the monitoring network with low-cost PM sensors and LTE (Long-term evolution) data communication. Then, preliminary resultant PM data plotted according to monitoring duration showed typical PM dispersion patterns. The quantification of the PM dispersion patterns should be roughly prepared by a PM size-dependent dispersion modeling.

• The Journal of the Korea Contents Association
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• v.21 no.4
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• pp.88-95
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• 2021

In Korea, which achieved economic growth due to export industries, the economic importance of the foreign port transportation industry is very great. The government took the initiative in fostering the foreign port transportation industry, and as a result, it developed into one of the top 10 foreign port transport countries in the world. However, due to the poor management of the small and medium-sized foreign port transport business and the trade dispute between countries, the foreign port transportation industry has faced a long-term invasion. Therefore, in order for these companies to recover again, they will, among other things, have to reorganize their operational inefficiency to carry out efficient production activities. In this study, we want to analyze the management efficiency of the top 10% companies in the unlisted domestic outbound shipping industry, present the project value of inefficient enterprises, and confirm the reference collection of companies that may be subject to benchmarking. For this purpose, a total of 10 foreign port transportation industry were analysed for efficiency and scale profitability (RTS) of the CCR and BCC models. The analysis showed that there were a total of six entities with BCC efficiency and five entities with CCR efficiency. In addition, there were a total of five entities with both BCC and CCR efficiency.

• Journal of Korean Society of Transportation
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• v.20 no.4
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• pp.151-162
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• 2002

The object of this study is to develop an operating time prediction model for expressways using toll collection data. A Prediction model based on modular neural network model was developed and tested using real data. Two toll collection system(TCS) data set. Seoul-Suwon section for short range and Seoul-Daejeon section for long range, in Kyongbu expressway line were collected and analyzed. A time series analysis on TCS data indicated that operating times on both ranges are in reasonable prediction ranges. It was also found that prediction for the long section was more complex than that for the short section. However, a long term prediction for the short section turned out to be more difficult than that for the long section because of the higher sensitivity to initial condition. An application of the suggested model produced accurate prediction time. The features of suggested prediction model are in the requirement of minimum (3) input layers and in the ability of stable operating time prediction.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.39 no.3
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• pp.149-156
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• 2021

This study collected and analyzed case studies related with the use of spatial information in North Korea to prioritize construction and required supporting processes in order to propose a short-term and long-term road map for the establishment of spatial information in North Korea. Recent research cases related to the prioritization of spatial information development were analyzed, and priority for the construction of infrastructure was derived based on the interconnectedness and relationship of national infrastructure. Due to the inaccessibility and remoteness of North Korea, all of the five studies determined priorities according to questionnaires and consulting of refugees and knowledgeable figures by expert groups. In summary, priority was given to unarmed and transborder areas, major cities, special zones, and development zones, while in terms of facilities, priority was given to power communication, railroads, water and sewage architectural buildings, roads, and dams. In the case of prioritizing the establishment of national infrastructure for the unified Korean Peninsula, the development of major areas, ports, and the related city-level spots to develop a line that promotes the sharing of routes such as transportation networks, water, and energy, thus leading to a scenario involving the development of cotton at an urban and national level.

• Journal of Korean Society of Transportation
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• v.26 no.5
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• pp.163-174
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• 2008

The conventional four-step travel demand model is still widely used as the state-of-practice in most transportation planning agencies even though it does not provide reliable estimates of travel demand. In order to improve the accuracy of travel demand estimation, implementing an alternative approach would be critical as much as acquiring reliable socioeconomic and travel data. Recently, the role of travel demand model is diverse to satisfy the needs of microscopic analysis regarding various policies of travel demand management and traffic operations. In this context, the activity-based approach for travel demand estimation is introduced and a case study of developing a spatial-temporal activity presence-based approach that estimates travel demand through forecasting number of people present at certain place and time is accomplished. Results show that the spatial-temporal activity presence-based approach provides reliable estimates of both number of people present and trips actually people made. It is expected that the proposed approach will provide better estimates and be used in not only long-term transport plans but short-term transport impact studies with respect to various transport policies. Finally, in order to introduce the spatial-temporal activity presence-based approach, the data such as activity-based travel diary and land use based on geographic information system are essential.