• Tunnel and Underground Space
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• v.27 no.1
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• pp.12-25
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• 2017

In local underground mines heavily depending on the natural ventilation, ducted fan auxiliary ventilation system is strongly recommended instead of the total mine ventilation system requiring large capital and operating costs. Optimizing the installation of ducted fans in series in long large-opening mines is required to assure the economy and efficiency of the ventilation system. The two most critical design parameters for optimization are the wall separation distance and gap length between adjoining ducts. This study aims at deriving the optimal values for those two parameters concerning the economic and environmental aspects through the extensive CFD analysis, which minimizes pressure loss, leakage and entrainment of the contaminated air in the gap space. The ranges of the wall separation distance and gap length for study are selected by taking into consideration the existing recommendations and guidelines. The ultimate goal is to optimize the auxiliary ventilation system using ducted fans in series to provide a reliable and efficient solution to maintain clean and safe workplace environment in local long underground mines.

• Journal of Biomedical Engineering Research
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• v.25 no.4
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• pp.253-259
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• 2004

in this study, we developed a Monte Carlo imaging simulation code written by the visual C$\^$++/ programing language for design optimization of a digital X-ray imaging system. As a digital X-ray imaging system, we considered a Gd$_2$O$_2$S(Tb) scintillator and a photosensor array, and included a 2D parallel grid to simulate general test renditions. The interactions between X-ray beams and the system structure, the behavior of lights generated in the scintillator, and their collection in the photosensor array were simulated by using the Monte Carlo method. The scintillator thickness and the photosensor array pitch were assumed to 66$\mu\textrm{m}$ and 48$\mu\textrm{m}$, respertively, and the pixel format was set to 256 x 256. Using the code, we obtained X-ray images under various simulation conditions, and evaluated their image qualities through the calculations of SNR (signal-to-noise ratio), MTF (modulation transfer function), NPS (noise power spectrum), DQE (detective quantum efficiency). The image simulation code developed in this study can be applied effectively for a variety of digital X-ray imaging systems for their design optimization on various design parameters.

• Journal of Energy Engineering
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• v.28 no.2
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• pp.18-35
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• 2019

The Korea District Heating Corporation operates a gas engine generator with a capacity of $4500m^3 /day$ of biogas generated from the sewage treatment plant of the Nanji Water Recycling Center and 1,500 kW. However, the actual operation experience of the biogas power plant is insufficient, and due to lack of accumulated technology and know-how, frequent breakdown and stoppage of the gas engine causes a lot of economic loss. Therefore, it is necessary to prepare technical fundamental measures for stable operation of the power plant In this study, a series of process problems of the gas engine plant using the biogas generated in the sewage treatment plant of the Nanji Water Recovery Center were identified and the optimization of the actual operation was made by minimizing the problems in each step. In order to purify the gas, which is the main cause of the failure stop, the conditions for establishing the quality standard of the adsorption capacity of the activated carbon were established through the analysis of the components and the adsorption test for the active carbon being used at present. In addition, the system was applied to actual operation by applying standards for replacement cycle of activated carbon to minimize impurities, strengthening measurement period of hydrogen sulfide, localization of activated carbon, and strengthening and improving the operation standards of the plant. As a result, the operating performance of gas engine # 1 was increased by 530% and the operation of the second engine was increased by 250%. In addition, improvement of vent line equipment has reduced work process and increased normal operation time and operation rate. In terms of economic efficiency, it also showed a sales increase of KRW 77,000 / year. By applying the strengthening and improvement measures of operating standards, it is possible to reduce the stoppage of the biogas plant, increase the utilization rate, It is judged to be an operational plan.

• 한국신재생에너지학회:학술대회논문집
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• 2010.11a
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• pp.42.2-42.2
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• 2010

Transparent conducting oxides (TCOs) are of significant importance for their applications in various devices, such as light-emitting diodes, thin-film solar cells, organic light-emitting diodes, liquid crystal displays, and so on. In order for TCOs to contribute to the performance improvement of these devices, TCOs should have high transmittance and good electrical properties simultaneously. Sn-doped $In_2O_3$ (ITO) is the most commonly used TCO. However, indium is toxic and scarce in nature. Thus, ZnO has attracted a lot of attention because of the possibility for replacing ITO. In particular, group III impurity-doped ZnO showed the optoelectronic properties comparable to those of ITO electrodes. Al-doped ZnO exhibited the best performance among various doped ZnO films because of the high substitutional doping efficiency. However, in order for the Al-doped ZnO to replace ITO in electronic devices, their electrical and optical properties should further significantly be improved. In this connection, different ways such as a variation of deposition conditions, different deposition techniques, and post-deposition annealing processes have been investigated so far. Among the deposition methods, RF magnetron sputtering has been extensively used because of the easiness in controlling deposition parameters and its fast deposition rate. In addition, when combined with post-deposition annealing in a reducing ambient, the optoelectronic properties of Al-doped ZnO films were found to be further improved. In this presentation, we deposited Al-doped ZnO (ZnO:$Al_2O_3$ = 98:2 wt%) thin films on the glass and sapphire substrates using RF magnetron sputtering as a function of substrate temperature. In addition, the ZnO samples were annealed in different conditions, e.g., rapid thermal annealing (RTA) at $900^{\circ}C$ in $N_2$ ambient for 1 min, tube-furnace annealing at $500^{\circ}C$ in $N_2:H_2$=9:1 gas flow for 1 hour, or RTA combined with tube-furnace annealing. It is found that the mobilities and carrier concentrations of the samples are dependent on growth temperature followed by one of three subsequent post-deposition annealing conditions.

• Progress in Medical Physics
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• v.23 no.3
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• pp.162-168
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• 2012

In proton therapy, in vivo dose verification is one of the most important parts to fully utilize characteristics of proton dose distribution concentrating high dose with steep gradient and guarantee the patient safety. Currently, in order to image the proton dose distribution, a prompt gamma distribution detection system, which consists of an array of multiple CsI(Tl) scintillation detectors in the vertical direction, a collimator, and a multi-channel DAQ system is under development. In the present study, the optimal design of prompt gamma distribution detection system was studied by Monte Carlo simulations using the MCNPX code. For effective measurement of high-energy prompt gammas with enough imaging resolution, the dimensions of the CsI(Tl) scintillator was determined to be $6{\times}6{\times}50mm^3$. In order to maximize the detection efficiency for prompt gammas while minimizing the contribution of background gammas generated by neutron captures, the hole size and the length of the collimator were optimized as $6{\times}6mm^2$ and 150 mm, respectively. Finally, the performance of the detection system optimized in the present study was predicted by Monte Carlo simulations for a 150 MeV proton beam. Our result shows that the detection system in the optimal dimensions can effectively measure the 2D prompt gamma distribution and determine the beam range within 1 mm errors for 150 MeV proton beam.

• Applied Chemistry for Engineering
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• v.29 no.1
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• pp.10-17
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• 2018

POU (point of use) scrubbers were applied for the treatment of waste gases including PFCs (perfluorocompounds) exhausted from the CVD (chemical vapor deposition), etching, and cleaning processes of semiconductor and display manufacturing plant. The GWP (global warming potential) and atmosphere lifetime of PFCs are known to be a few thousands higher than that of $CO_2$, and extremely high temperature more than 3,000 K is required to thermally decompose PFCs. Therefore, POU gas scrubbers based on the thermal plasma technology were developed for the effective control of PFCs and industrial application of the technology. The thermal plasma technology encompasses the generation of powerful plasma via the optimization of the plasma torch, a highly stable power supply, and the matching technique between two components. In addition, the effective mixture of the high temperature plasma and waste gases was also necessary for the highly efficient abatement of PFCs. The purpose of this paper was to provide not only a useful technical information of the post-treatment process for the waste gas scrubbing but also a short perspective on R&D of POU plasma gas scrubbers.

• Journal of the Institute of Electronics and Information Engineers
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• v.53 no.5
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• pp.25-36
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• 2016

The goal of the SmartGrid is to maximize energy efficiency by exchanging bi-directional real-time power information with the help of ICT(Information and Communication Technology). In this paper, we propose a "JRS-MS" (Joint Routing and Scheduling for Multi-channel SmartGrid) algorithm that uses numerical modeling methods in IEEE 802.11s based STDMA multi-channel SmartGrid NAN networks. The proposed algorithm controls the amount of data transmission adaptively at the link layer and finds a high data-rate path which has the least interference between traffic flows in multi-channel SmartGrid NAN networks. The proposed algorithm improve transmission performance by enhancing network utilization. By comparing the results of performance analysis between the proposed algorithm and the JRS-SG algorithm in the previous paper, we showed that the JRS-MS algorithm can improve transmission performance by maximally utilizing given network resources when the number of flows are increasing in the multi-hop NAN wireless mesh networks.

• Applied Chemistry for Engineering
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• v.31 no.5
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• pp.575-580
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• 2020

In this study, we simulated an amine regeneration process with heat-stable salts removal unit. We derived the optimal operating conditions considering the flow rate of waste, the removal rate of heat-stable salts, and the loss rate of MDEA (methyl diethanolamine). In the amine regeneration process that absorbs and removes acid gas, heat-stable salt impairs the absorption efficiency of process equipment and amine solution. An ion exchange resin method is to remove heat-stable salts through neutralization by using a strong base solution such as NaOH. The acid gas removal process was established using the Radfrac model, and the equilibrium constant of the reaction was calculated using Gibbs free energy. The removed amine solution is separated and flows to the heat-stable salts remover which is modeled by using the Rstoic model with neutralization reaction. Actual operation data and simulation results were compared and verified, and also a case study was conducted by adjusting the inflow mass of removal unit followed by suggesting optimal conditions.

• KEPCO Journal on Electric Power and Energy
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• v.2 no.2
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• pp.311-316
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• 2016

Network intrusion detection system based on machine learning method such as artificial neural network is quite dependent on the selected features in terms of accuracy and efficiency. Nevertheless, choosing the optimal combination of features, which guarantees accuracy and efficienty, from generally used many features to detect network intrusion requires extensive computing resources. In this paper, we deal with a optimal feature selection problem to determine 6 denial service attacks and normal usage provided by NSL-KDD data. We propose a optimal feature selection algorithm. Proposed algorithm is based on the multi-start local search algorithm, one of representative meta-heuristic algorithm for solving optimization problem. In order to evaluate the performance of our proposed algorithm, comparison with a case of all 41 features used against NSL-KDD data is conducted. In addtion, comparisons between 3 well-known machine learning methods (multi-layer perceptron., Bayes classifier, and Support vector machine) are performed to find a machine learning method which shows the best performance combined with the proposed feature selection method.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.40 no.6
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• pp.613-622
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• 2020

The South Korean government plans for a 37 % reduction in CO2 emissions against business as usual by 2030. Subsequently, the Ministry of Land, Infrastructure and Transport declared a 26.9 % reduction target in greenhouse gas emissions from buildings by 2020 and established the Green Standard for Energy and Environmental Design (G-SEED) to help improve the environmental performance of buildings. Construction companies often work with consulting firms to prepare for G-SEED certification. In the process, owing to inefficient data sharing and work connections, it is difficult to achieve economic efficiency and obtain certification. The objective of this study was to develop an economic model to assist contractors in achieving the required G-SEED scores for materials and resources. To do this, we automated the process for material comparison and selection on the basis of an analysis of actual consulting data, and developed a model that selects material alternatives that can meet the required scores at a minimum cost. Information on materials is input by applying a genetic algorithm to the optimization of alternatives. When the model was applied to actual data, the construction cost could be lowered by 79.3 % compared with existing methods. The economical material selection model is expected to not only reduce construction costs for owners desiring G-SEED certification but also shorten the project design time.