• Journal of the Korea institute for structural maintenance and inspection
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• v.17 no.6
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• pp.1-10
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• 2013

Probabilistic nonlinear first ply failure loads of flat composite panels and nonlinear buckling loads of curved composite panels with cutouts are estimated to provide the more reliable main load carrying structure in the renewable energy industry and offshore structures. The response surface method approximates limit state surface to a second order polynomial form of random variables with the results of deterministic finite element analyses at given sampling design points. Furthermore, the iterative linear interpolation scheme is used to obtain a more accurate approximation of the limit state surface near the most probable failure point (MPFP). The advanced first order second moment method and the Monte Carlo method are performed on an approximated limit state surface to evaluate the probability of failure. Finally, the sensitivity of the reliability index with respect to transformed random variables is investigated to figure out the main random variables that have an effect on failures.

• The Journal of the Korea institute of electronic communication sciences
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• v.15 no.4
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• pp.695-702
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• 2020

Recently, as research on smart farms has been actively conducted, indoor environment control, such as a green house, has reached a high level. However, In the field of forestry where cultivation is carried out in outdoor, the use of ICT is still insufficient. In this paper, we propose LPWA-based forest growth environment collection and big data analysis system using ICT technology. The proposed system collects and transmits the field cultivation environment data to the server using small solar power generation and LPWA technology based on the oneM2M architecture. The transmitted data is constructed as big data on the server and utilizes it to predict the production and quality of forest products. The proposed system is expected to contribute to the production of low-cost, high-quality crops through the fusion of renewable energy and smart farms. In addition, it can be applied to other industrial fields that utilize the oneM2M architecture and monitoring the growth environment of agricultural crops in the field.

• The Journal of the Korea institute of electronic communication sciences
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• v.18 no.6
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• pp.1143-1150
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• 2023

The global climate crisis and the implementation of low-carbon policies have led to a growing interest in renewable energy and a growing number of related industries. Among them, solar power is attracting attention as a representative eco-friendly energy that does not deplete and does not emit pollutants or greenhouse gases. As a result, the supplement of solar power facility is increasing all over the world. However, solar power is easily affected by the environment such as geography and weather, so accurate solar power forecast is important for stable operation and efficient management. However, it is very hard to predict the exact amount of solar power using statistical methods. In addition, the conventional prediction methods have focused on only short- or long-term prediction, which causes to take long time to obtain various prediction models with different prediction horizons. Therefore, this study utilizes a many-to-many structure of a recurrent neural network (RNN) to integrate short-term and long-term predictions of solar power generation. We compare various RNN-based very short- and long-term prediction methods for solar power in terms of MSE and R² values.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.17 no.6
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• pp.1-8
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• 2016

Current sensors are used widely in the fields of current control, monitoring, and measuring. They have become more popular with the increasing demand for smart grids in a power network, generation of renewable energy, electric cars, and hybrid cars. Although open loop Hall effect current sensors have merits, such as low cost, small size, and weight, they have low accuracy. This paper describes the design and fabrication of a 300A open loop current sensor that has high accuracy and temperature performance. The core of the current sensor was calculated numerically and the signal conditioning circuits were designed using circuit analysis software. The characteristics of the manufactured open loop current sensor of 300 A class was measured at currents up to 300 A. According to the test of the current sensor, the accuracy error and linearity error were 0.75% and 0.19%, respectively. When the temperature compensation was carried out with the relevant circuit, the temperature coefficients were less than $0.012%/^{\circ}C$ at temperatures between $-25^{\circ}C$ and $85^{\circ}C$.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.20 no.4
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• pp.590-596
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• 2019

Uses of fossil fuels like coal and oil increases with industrial development, and problems like abnormal climate come up as greenhouse gas increases. Accordingly, studies are actively conducted on eco-friendly renewable energy as a replacement for the main resources, and especially, wood pellets with high thermal efficiency are in the limelight as an alternative fuel in thermal power stations and gas boilers. However, despite a constant increase in their usage, few studies are conducted on their risks like fire and spontaneous combustion. Thus, this study found the auto-ignition temperature and critical ignition temperature of wood pellets with a change in flow rate in a thermostatic bath, using a sample vessel with 20 cm in length, 20 cm in height and 14 cm in thickness to predict their ignition characteristics. Consequently, at the flow rate of 0 NL/min, as the core temperature of the sample increased to higher than the ambient temperature, they ignited at $153^{\circ}C$, when the critical ignition temperature was $152.5^{\circ}C$. At the flow rates of 0.5 NL/min and 1.0 NL/min, it was $149.5^{\circ}C$, and at the flow rate of 1.5 NL/min, it was $147.5^{\circ}C$. Consequently, at the same storage, the more the flow rate, the lower the critical ignition temperature became.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.19 no.12
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• pp.523-531
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• 2018

The purpose of this paper is to derive priorities and implications for the organic resource conservation policy in the livestock sector. We conducted a survey on the importance-performance of the organic waste resource reclamation of livestock sector using a 5-point Likert scale. The importance average for the resource recycling of livestock organic waste was 3.63 and the average of performance was 3.04. As a result of the IPA on livestock manure recycling measures, it is necessary to improve feed quality, establish a local recycling system, increase demand for compost and liquid, enhance customer linkages, and develop cost reduction technologies. It requires intensive support for promoting the spread of odor reduction technologies and integrated management of biomass. It is necessary to introduce mid- and long-term measures such as the revival of feed in tariff, promote by-product feeding, establish solid fuel process management standards, create hygiene safety standards, develop eco-beads and promotion of feed conversion. It is required to strengthen support for the development of odor reduction technologies and prepare consultative organizations among related departments, develop eco-friendly solid fuel technology, and support policies for renewable energy certification.

• Journal of Climate Change Research
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• v.2 no.4
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• pp.283-295
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• 2011

Many actions against climate change have been taken to reduce greenhouse gases (GHGs) emissions at home and abroad. As of 2007, the GHGs emitted from buildings accounted for about 23 % of Korea's total GHGs emission, which is the second largest GHG reduction potential following industry. In this study, we introduced Carbon Zero Building (CZB), which was constructed by the National Institute of Environmental Research to cut down GHGs from buildings in Korea, and evaluated the main applied technologies, the amount of energy load and reduced energy, and economic values for CZB to provide data that could be a basis in the future construction of this kind of carbon-neutral buildings. A total of 66 technologies were applied for this building in order to achieve carbon zero emissions. Applied technologies include 30 energy consumption reduction technologies, 18 energy efficiency technologies, and 5 eco-friendly technologies. Out of total annual energy load ($123.8kWh/m^2$), about 40% of energy load ($49kWh/m^2$) was reduced by using passive technologies such as super insulation and use of high efficiency equipments and the other 60% ($74.8kWh/m^2$) was reduced by using active technologies such as solar voltaic, solar thermal, and geothermal energy. The construction cost of CZB was 1.4 times higher than ordinary buildings. However, if active technologies are excluded, the construction cost is similar to that of ordinary buildings. It was estimated that we could save annually about 102 million won directly from energy saving and about 2.2 million won indirectly from additional saving by the reduction in GHGs and atmospheric pollutants. In terms of carbon, we could reduce 100 ton of $CO_2$ emissions per year. In our Life Cycle Cost (LCC) analysis, the Break Even Point (BEP) for the additional construction cost was estimated to be around 20.6 years.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.21 no.11
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• pp.672-682
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• 2020

The Korea Nowadays, which is research on digital twin technology for efficient operation in various industrial/manufacturing sites, is being actively conducted, and gradual depletion of fossil fuels and environmental pollution issues require new renewable/eco-friendly power generation methods, such as wave power plants. In wave power generation, however, which generates electricity from the energy of waves, it is very important to understand and predict the amount of power generation and operational efficiency factors, such as breakdown, because these are closely related by wave energy with high variability. Therefore, it is necessary to derive a meaningful correlation between highly volatile data, such as wave height data and sensor data in an oscillating water column (OWC) chamber. Secondly, the methodological study, which can predict the desired information, should be conducted by learning the prediction situation with the extracted data based on the derived correlation. This study designed a workflow-based training model using a machine learning framework to predict the pressure of the OWC. In addition, the validity of the pressure prediction analysis was verified through a verification and evaluation dataset using an IoT sensor data to enable smart operation and maintenance with the digital twin of the wave generation system.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.19 no.6
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• pp.80-87
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• 2018

In recent years, due to the spread of various renewable energy power sources and the pursuit of high efficiency and low-power consumption, not only trends in the electric power industry but also the consumption, control methods, and characteristics are diversified. However, in this diversified electric power industry, the fuse (which is the core part responsible for safety) has not developed significantly in classical operation mode, and thus, fires continue to occur. In this paper, the effects of low melting-point metal plating and high melting-point metal plating on operating characteristics and IT curve movement of the fuse are investigated in a cartridge fuse, which is a classic fuse manufacturing method. The effects of plating on the thickness of the fuse are investigated, and various operating characteristics of the fuse are implemented. In addition, it is suggested that the plating of the low melting-point metal moves the rated current line of the fuse to a low rating, and moves operating characteristics to characteristics of delay operation. It is possible to design various operating characteristics using this characteristic.

• Journal of Korea Port Economic Association
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• v.28 no.3
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• pp.27-44
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• 2012

The offshore wind farm is increasingly attractive as one of future energy sources all over the world. In addition, the capacity of an offshore wind turbine gets larger and its physical characteristics are big and heavy. In this regard, a special port is necessary to assemble, store, and transport the offshore wind systems, supporting to form the offshore wind farms. Thus, this study aims to provide a policy maker which evaluation factors can significantly affect to the optimal site selection of a offshore wind port. For this, Fuzzy-AHP method is applied to capture the relative weights. The results of this study can be summarized as follows. Five criteria in level I was defined such as the accumulation factor, the regional factor, the economic factor, the location factor, and the consortium factor. Of these, the accumulation factor(37.4%), the location factor(34.2%), and the economic factor( 24.5%) were analyzed by major factors. In level II, three assessment items of each factor were selected so that total fifteen items were formed. To sum up, the site selection of offshore wind port should consider the density of the wind industry, cargo volume of securing the economic operation of terminals, the development degree of offshore wind related industry, and the proximity to the offshore wind farms. In other words, the construction of offshore wind port should be paid attention to considering not only the proximity to offshore wind farms but also the preference of turbine manufacturing companies.