• Journal of the Korean Society of Safety
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• v.31 no.4
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• pp.55-63
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• 2016

A dust explosion is a phenomenon of strong blast wave propagation involving destruction which results from dust pyrolysis and rapid oxidation in a confined space. There has been some research done to find individual explosion characteristics and common physical laws for various dust types. However, there has been insufficient number of studies related to the heat of combustion of materials and the oxygen consumption energy about materials in respect of dust explosion characteristics. The present study focuses on the relationship between dust explosion characteristics of wood dust samples and oxygen consumption energy. Since it is difficult to estimate the weight of suspended dust participating in explosions in dust explosion and mixtures are in fuel-rich conditions concentrations with equivalent ratios exceeding 1, methods for estimating explosion overpressure by applying oxygen consumption energy based on unit volume air at standard atmospheric pressure and temperature are proposed. In this study an oxygen consumption energy model for dust explosion is developed, and by applying this model to TNT equivalent model, initial explosion efficiency was calculated by comparing the results of standardized dust explosion experiments.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.4 no.2
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• pp.135-140
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• 2011

Currently, studies have show that the network related energy consumption are increasing. and part of overall energy consumption of our society are too. So, that is important to look for energy-efficient network applications and protocols. A most of network energy consumption are due to network edge devices. in this paper, in order to cut down the emissions of carbon dioxide from ICT business, which contributes 2% of the global energy consumption, it is necessary to understand energy consumption in peer-to-peer system. In this paper, in this paper we propose a architecture based on the introduction of a p2p proxy. The model is analyzed analytically and numerically to reveal how these factors influence the overall power consumption in both steady state and flash crowd information exchange scenarios. Specifically, our results show that the proxy-based solution can provide up to 50% reduction in the energy consumption and, at the same time, a significant reduction in the average file download time.

• 제어로봇시스템학회:학술대회논문집
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• 1987.10b
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• pp.63-68
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• 1987

In this study, a pantograph leg of the four legged walking vehicle is analysed with regard to mechanical energy consumption. Energy efficiency of the vehicle is estimated in terms of specific resistance varying body height, stride length and walking speed. The interaction between specific resistance and the parameters is investigated.

• International Journal of Computer Science & Network Security
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• v.22 no.7
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• pp.301-307
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• 2022

Energy consumption has grown alongside dramatic population increases. Statistics show that buildings in particular utilize a significant amount of energy, worldwide. Because of this, building energy prediction is crucial to best optimize utilities' energy plans and also create a predictive model for consumers. To improve energy prediction performance, this paper proposes a ResNet-LSTM model that combines residual networks (ResNets) and long short-term memory (LSTM) for energy consumption prediction. ResNets are utilized to extract complex and rich features, while LSTM has the ability to learn temporal correlation; the dense layer is used as a regression to forecast energy consumption. To make our model more robust, we employed Huber loss during the optimization process. Huber loss obtains high efficiency by handling minor errors quadratically. It also takes the absolute error for large errors to increase robustness. This makes our model less sensitive to outlier data. Our proposed system was trained on historical data to forecast energy consumption for different time series. To evaluate our proposed model, we compared our model's performance with several popular machine learning and deep learning methods such as linear regression, neural networks, decision tree, and convolutional neural networks, etc. The results show that our proposed model predicted energy consumption most accurately.

• Transactions of Materials Processing
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• v.32 no.3
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• pp.153-159
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• 2023

This paper presents the optimal design of a heating system using radiant heating elements for application in smart farms. Smart farming, an advanced agricultural technology, is based on artificial intelligence and the internet of things and promotes crop production. Temperature and humidity regulation is critical in smart farms, and thus, a heating system is essential. Radiant heating elements are devices that generate heat using electrical energy. Among other applications, radiant heating elements are used for environmental control and heating in smart farm greenhouses. The performance of these elements is directly related to their electrical energy consumption. Therefore, achieving a balance between efficient electrical energy consumption and maximum heating performance in smart farms is crucial for the optimal design of radiant heating elements. In this study, the size, electrical energy supply, heat generation efficiency, and heating performance of radiant heating elements used in these heating systems were investigated. The effects of the size and electrical energy supply of radiant heating elements on the heating performance were experimentally analyzed. As the radiant heating element size increased, the heat generation efficiency improved, but the electrical energy consumption also increased. In addition, increasing the electrical energy supply improved both the heat generation efficiency and heating performance of the radiant heating elements. Based on these results, a method for determining the optimal size and electrical energy supply of radiant heating elements was proposed, and it reduced the electrical energy consumption while maintaining an appropriate heating performance in smart farms. These research findings are expected to contribute to energy conservation and performance improvement in smart farming.

• Journal of Energy Engineering
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• v.22 no.2
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• pp.83-89
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• 2013

Energy consumption is closely related to our lives. As Korea has four seasons, heating and cooling system is considered as essential facilities for the residential buildings. Accordingly, the government has continuously strengthened the design criteria to improve energy for new and existing building to save energy. The most important factor in the energy efficiency analysis for apartment is the heat transmission coefficient, and the value is significantly different as the heating energy amount is greatly different according to the window area ratio versus facade area ratio. Therefore, it is time to conduct continuous set-up for goal to enhance efficiency and restriction on window area ratio versus facade area ratio.

• KIEAE Journal
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• v.13 no.2
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• pp.39-46
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• 2013

Recently, the field of construction is putting a variety of effort into reducing CO2, since global warming is being accelerated due to climate changes and the increase of greenhouse gas. For reduction of CO2 in the field of construction, it is required to make plans to cut down heating energy of buildings and especially, it is urgently needed to cut down energy of residential buildings in rural area where occupies the majority of consumption of petroleum-based energy sources. Therefore, this research compared and analyzed the actual energy consumption, by evaluating energy performance of a detached house applying passive house design components for reduction of energy. As the result, energy consumption showed remarkable differences, according to the operation of a heat recovery ventilation unit which is one of passive house design components, and building energy consumption displayed remarkable differences, too, depending on the difference of airtightness performance during building energy simulation conducted in process of design. Based on these results, the importance of airtightness performance of passive house was verified. The result of the actual measurement of energy consumption demonstrated that LNG was most economical amongst several heat resources yielded, on the basis of LPG source energy consumption measured within a certain period of time, and it was followed by kerosene. LPG was analyzed to have a low economic efficiency, when used for heating.

• Journal of the Korean Society for Geothermal and Hydrothermal Energy
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• v.10 no.2
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• pp.7-12
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• 2014

Government has recently restricted heating and cooling set temperatures for the commercial and public buildings due to increasing national energy consumption. The goal of this paper is to visualize a future two way indoor set temperature control impact on building energy consumption by using TRNSYS simulation modeling. The building was modelled based on the twin test cell with the same dimension. Air source ground coupled heat pump performance data has been used for modeling by TRNSYS 17. Daejeon weather data has been used from Korea Solar Energy Society. The heating set temperature in the reference room is $24^{\circ}C$ as well as the target room set temperature are $23^{\circ}C$, $22^{\circ}C$, $21^{\circ}C$ and $20^{\circ}C$. The cooling set temperature of the reference room is also $24^{\circ}C$ as well as the target room set temperature of $25^{\circ}C$, $26^{\circ}C$, $27^{\circ}C$ and $28^{\circ}C$. For the air source heat pump system, heating season energy consumption is $35.52kWh/m^2y$ in the reference room. But the heating energy consumption in the target room is reduced to 7.5% whenever the set temperature decreased every $1^{\circ}C$. The cooling energy consumption in the reference room is $4.57kWh/m^2y$. On the other hand, the energy consumption in the target room is reduced to 22% whenever the set temperature increased every $1^{\circ}C$ by two way controller. For the geothermal heat pump system, heating energy consumption in the reference room is reduced to 20.7%. The target room heating energy consumption is reduced to 32.6% when the set temperature is $22^{\circ}C$. The energy consumption in the target room is reduced to 59.5% when the set temperature is $26^{\circ}C$.

• ETRI Journal
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• v.44 no.6
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• pp.885-902
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• 2022

The mmWave cell-free massive MIMO (CFmMIMO), combining the advantages of wide bandwidth in the mmWave frequency band and the high- and uniform-spectral efficiency of CFmMIMO, has recently emerged as one of the enabling technologies for 6G. In this paper, we propose a novel framework for energy-efficient mmWave CFmMIMO systems that uses low-resolution digital-analog converters (DACs) and phase shifters (PSs) to introduce lowcomplexity hybrid precoding. Additionally, we propose a heuristic pilot allocation scheme that makes the best effort to slash some interference from copilot users. The simulation results show that the proposed hybrid precoding and pilot allocation scheme outperforms the existing schemes. Furthermore, we reveal the relationship between the energy and spectral efficiencies for the proposed mmWave CFmMIMO system by modeling the whole network power consumption and observe that the introduction of low-resolution DACs and PSs is effective in increasing the energy efficiency by compromising the spectral efficiency and the network power consumption.

• International Commerce and Information Review
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• v.16 no.2
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• pp.199-218
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• 2014

The study was focused on the Energy Efficiency of Korea. Thus this study calculates Energy Intensity and Energy Dependence, Energy Independence rate using data Korea Energy Statistics. This study calculate 'Energy Intensity', 'Energy Dependence', 'Energy Independence rate', which is making use of the Gross Domestic product, Energy Consumption, Energy Export and Import, Energy Gross Input. The analysis of the pater suggests that this goal can be achieved throuth improved efficiency of Energy consumption and Energy Independence.