• 한국태양에너지학회:학술대회논문집
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• 2011.11a
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• pp.348-353
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• 2011

Recently the renewable energy has been used widely and the importance of renewable sources is bigger than before. So the government enforced a law to the public buildings to install the renewable energy facilities. The capacity of facilities is 5% of total construction cost until April 13, 2011. Since then, the government changed the law from 5% of total construction cost to 10% of predicted energy usage because of the practical use of the renewable energy facilities. So, in this study, the comparative analysis is conducted according to the law to the building installed PV system through the EnergyPlus simulation.

• Journal of the Korean Society for Geothermal and Hydrothermal Energy
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• v.10 no.2
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• pp.19-23
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• 2014

In the capital of Mongolia where the air quality is getting worse due to the coal consumption used for electricity generation and district heating, the application of geothermal systems in the housing sector is recently designed for high class resort. In this study, the case of applying a geothermal system in a house in Mongolia is examined. The effects of passive house design on the needed heat pump capacity, as well as the annual energy consumption are analyzed. Moreover, as the initial costs, except labor fee, are assumed similar to Korea, cost analysis for several cases is examined, too. From the results, if a house is designed according to passive house standard instead of ASHRAE standard, the heat pump capacity can be expected to be reduced from 16 to 5~6 RT. Furthermore, although the initial cost of architectural cost might increased by 29 M\, the total initial cost is reduced by 14 M\, while the annual energy consumption is reduced by 14%. This is mainly driven by the fact that the geothermal system which serves as the main system to cover the building needs, with a high initial cost for fulfilling the peak requirements.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.15 no.1
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• pp.35-57
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• 2021

Fog computing aims to provide the solution of bandwidth, network latency and energy consumption problems of cloud computing. Likewise, management of data generated by healthcare IoT devices is one of the significant applications of fog computing. Huge amount of data is being generated by healthcare IoT devices and such types of data is required to be managed efficiently, with low latency, without failure, and with minimum energy consumption and low cost. Failures of task or node can cause more latency, maximum energy consumption and high cost. Thus, a failure free, cost efficient, and energy aware management and scheduling scheme for data generated by healthcare IoT devices not only improves the performance of the system but also saves the precious lives of patients because of due to minimum latency and provision of fault tolerance. Therefore, to address all such challenges with regard to data management and fault tolerance, we have presented a Fault Tolerant Data management (FTDM) scheme for healthcare IoT in fog computing. In FTDM, the data generated by healthcare IoT devices is efficiently organized and managed through well-defined components and steps. A two way fault-tolerant mechanism i.e., task-based fault-tolerance and node-based fault-tolerance, is provided in FTDM through which failure of tasks and nodes are managed. The paper considers energy consumption, execution cost, network usage, latency, and execution time as performance evaluation parameters. The simulation results show significantly improvements which are performed using iFogSim. Further, the simulation results show that the proposed FTDM strategy reduces energy consumption 3.97%, execution cost 5.09%, network usage 25.88%, latency 44.15% and execution time 48.89% as compared with existing Greedy Knapsack Scheduling (GKS) strategy. Moreover, it is worthwhile to mention that sometimes the patients are required to be treated remotely due to non-availability of facilities or due to some infectious diseases such as COVID-19. Thus, in such circumstances, the proposed strategy is significantly efficient.

• Progress in Superconductivity
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• v.13 no.2
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• pp.133-138
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• 2011

To reduce the processing cost of the single grain REBCO (RE: Rare-earth elements) bulk superconductors, a cost-effective process should be developed. One possible way of developing the cost-effective process is the use of low-cost precursor powders. In this study, the single grain YBCO superconductors were fabricated using a home made powder. $YBa_2Cu_3O_{7-y}$ (Y123) powders were synthesized at $850-900^{\circ}C$ in air by the powder calcination method with repeated crushing and heat treatment steps. The processing parameters for the fabrication of single grain Y123 bulk superconductors, $T_{max}$ (maximum temperature), $T_p$ (peritectic temperature) and a cooling rate through $T_p$ were optimized. To enhance the flux pinning capacity of the single grain Y123 samples, $Y_2BaCuO_5$ (Y211) particles were dispersed in the Y123 matrix by adding $Y_2O_3$ powder to the calcined Y123 powder. Applying the optimized processing condition, the single grain Y123 superconductors with $T_c=91\;K$ and $J_c=1.5{\times}10^4\;A/cm^2$ at 2 T were successfully fabricated using a home made powder. The levitation forces and trapped magnetic field at 77 K measured using a Nd-B-Fe permanent magnet of 5300 G were 47 N and 3000 G, respectively, which are comparable to those obtained for the samples fabricated using a commercial grade Y123 powders.

• International conference on construction engineering and project management
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• 2022.06a
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• pp.823-830
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• 2022

The risk of project execution increases due to the enlargement and complexity of Engineering, Procurement, and Construction (EPC) plant projects. In the fourth industrial revolution era, there is an increasing need to utilize a large amount of data generated during project execution. The design is a key element for the success of the EPC plant project. Although the design cost is about 5% of the total EPC project cost, it is a critical process that affects the entire subsequent process, such as construction, installation, and operation & maintenance (O&M). This study aims to develop a system using machine-learning (ML) techniques to predict risks and support decision-making based on big data generated in an EPC project's design and construction stages. As a result, three main modules were developed: (M1) the design cost estimation module, (M2) the design error check module, and (M3) the change order forecasting module. M1 estimated design cost based on project data such as contract amount, construction period, total design cost, and man-hour (M/H). M2 and M3 are applications for predicting the severity of schedule delay and cost over-run due to design errors and change orders through unstructured text data extracted from engineering documents. A validation test was performed through a case study to verify the model applied to each module. It is expected to improve the risk response capability of EPC contractors in the design and construction stage through this study.

• Proceedings of the SAREK Conference
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• 2009.06a
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• pp.325-331
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• 2009

In this paper, a simulation approach for the optimum design of cogeneration system is described. For the purpose of the systematic analysis, a simulation tool is developed with which the prediction of the energy load, calculation of operation data according to prime mover or capacity of it, and estimation of economic gains can be carried out. As for the criterion of the optimum design, the economic gains by adopting cogeneration system is taken. Based on the capital, operation, and maintenance costs etc, LCC analysis is to be carried out for the scenarios respectively. In this study, the simulation for the apartment complex is performed and the analysis of the results are described in detail. The effects of the operation parameters such as capital cost, fuel cost, and unit cost for the purchase or sale of heat and electricity on overall economy are also be considered by sensitivity study.

• Current Optics and Photonics
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• v.1 no.4
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• pp.315-324
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• 2017

In recent years, multicast services such as high-definition television (HDTV), video conferencing, interactive distance learning, and distributed games have increased exponentially, and wavelength-division multiplexing (WDM) networks are considered to be a promising technology due to their support for multicast applications. Multicast survivability in WDM networks has been the focus of extensive attention since a single-link failure in an optical network may result in a massive loss of data. But the improvement of network survivability increases energy consumption due to more resource allocation for protection. In this paper, an energy-efficient multicast algorithm (EEMA) is proposed to reduce energy consumption in WDM networks. Two cost functions are defined based on the link state to determine both working and protection paths for a multicast request in WDM networks. To increase the number of sleeping links, the link cost function of the working path aims to integrate new working path into the links with more working paths. Sleeping links indicate the links in sleep mode, which do not have any working path. To increase bandwidth utilization by sharing spare capacity, the cost function of the protection path is defined to use sleeping fibers for establishing new protection paths. Finally, the performance of the proposed algorithm is evaluated in terms of energy consumption, and also the blocking probability is evaluated under various traffic environments through OPNET. Simulation results show that our algorithm reduces energy consumption while maintaining the quality of service.

• Korean Journal of Air-Conditioning and Refrigeration Engineering
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• v.21 no.2
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• pp.71-78
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• 2009

Up until recently, the energy and the economic analysis of a cogeneration system have been implemented by a manual calculation that is based on monthly thermal loads of buildings. In this study, a cogeneration system modeling validation with a detail building energy simulation, eQUEST, for a building energy and cost prediction has been implemented. By analyzing the hourly building electricity and thermal loads, it enables users to decide proper cogeneration system capacity and to estimate more accurate building energy consumption. eQUEST also verified the energy analysis when the heat pump system is integrated with the cogeneration system. The mechanical system configuration benefits from the high efficiency heat pump system while avoiding the building electricity demand increase. Economic analysis such as LCC (Life Cycle Cost) method is carried out to verify economical benefits of the system by applying actual utility rates of KEPCO(Korea Electricity Power COmpany) and KOGAS(KOrea GAS company).

• Korean Journal of Plant Resources
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• v.13 no.3
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• pp.249-254
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• 2000

Heating supply system using solar energy-collecting plate was examined for 20 farmers. Some problems, resolution, future energy system, and basic information were discussed, Installation cost was approximately 18 million won/20a. Main crops cultured were tomato(30%) and floricultural crop(40%). Minor crops cultured were grape, red pepper, cucumber, lettuce, and strawberry. Information was mostly obtained from agricultural service agents. 75% of farm house hold reported that energy reduction effect was below 20%, showing some different result compared with over 20% that was totalized from agricultural service agents. Cost of installation was excessive in considering energy reduction effect. Another problem was insufficient technical proficiency of solar energy company.

• Journal of applied mathematics & informatics
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• v.41 no.1
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• pp.95-105
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• 2023

To make the network energy efficient and to protect the network from malignant user's energy efficient grid based secret key sharing scheme is proposed. The cost function is evaluated to select the optimal nodes for carrying out the data transaction process. The network is split into equal number of grids and each grid is placed with certain number of nodes. The node cost function is estimated for all the nodes present in the network. Once the optimal energy proficient nodes are selected then the data transaction process is carried out in a secured way using malicious nodes filtration process. Therefore, the message is transmitted in a secret sharing method to the end user and this process makes the network more efficient. The proposed work is evaluated in network simulated and the performance of the work are analysed in terms of energy, delay, packet delivery ratio, and false detection ratio. From the result, we observed that the work outperforms the other works and achieves better energy and reduced packet rate.