• Journal of the Korean Society of Hazard Mitigation
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• v.3 no.4 s.11
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• pp.119-129
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• 2003

Concrete and steel are essential structural materials in the construction. But, concrete, different from steel, consists of many materials and is affected by many factors such as properties of materials, site environmental situations, and skill of constructors. Concrete have two kinds of properties, immediately knowing properties such as slump, air contents and time dependent one like strength. Therefore, concrete mixes depend on experiences of experts. However, at point of time using High Performance Concrete, new method is wanted because of more ingredients like mineral and chemical admixtures and lack of data. Artificial Neural Networks(ANN) are a mimic models of human brain to solve a complex nonlinear problem. They are powerful pattern recognizers and classifiers, also their computing abilities have been proven in the fields of prediction, estimation and pattern recognition. Here, among them, the back propagation network and radial basis function network ate used. Compositions of high-performance concrete mixes are eight components(water, cement, fine aggregate, coarse aggregate, fly ash, silica fume, superplasticizer and air-entrainer). Compressive strength, slump, and air contents are measured. The results show that neural networks are proper tools to minimize the uncertainties of the design of concrete mixtures.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.42 no.3
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• pp.199-212
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• 2014

This paper describes an autonomous air combat guidance law using a Virtual Pursuit Point (VPP) in one-on-one close engagement for Unmanned Combat Aerial Vehicle (UCAV). The VPPs that consist of virtual lag and lead points are introduced to carry out tactical combat maneuvers. The VPPs are generated based on fighter's aerodynamic performance and Basic Fighter Maneuver (BFM)'s turn circle, total energy and weapon characteristics. The UCAV determines a single VPP and executes pursuit maneuvers based on a smoothing function which evaluates probabilities of the pursuit types for switching maneuvers with given combat states. The proposed law is demonstrated by high-fidelity real-time combat simulation using commercial fighter model and X-Plane simulator.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.35 no.7
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• pp.759-766
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• 2011

Recently, noise reduction in room air conditioners has been one of the important issues as well as cooling efficiency. The rotary compressor is the dominant noise source in an air conditioner. A number of studies have been conducted on reducing compressor noise through improving muffler and resonator design. However the noise from the accumulator, a noise delivering path between compressor and air conditioner, is not fully taken into consideration. The accumulator contains a large inner cavity, and usually generates additional resonance noise during operation. This paper aims to conduct an optimal design for reducing accumulator noise by maximizing the transmission loss within the target frequency range that represents high-order nonlinearity. Design of experiments and radial basis function neural network are used in the context of approximate meta-models, and genetic algorithm is used as an optimization tool.

• Transactions of the Korean Society of Mechanical Engineers B
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• v.33 no.7
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• pp.486-494
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• 2009

One-dimensional modeling of $CH_4$/air premixed flame was conducted to validate the heat loss model and investigate NOx formation characteristics in the postflame region. The predicted temperature and NO concentration were compared to experimental data and previous heat loss model results using a constant gradient of temperature (100 K/cm). The following conclusions were drawn. In the heat loss model using steady-state heat transfer equation, the numerical results using the effective heat loss coefficient ($h_{eff}$) of $1.0\;W/m^2K$ were in very good agreement with the experiments in terms of temperature and NO concentration. On the other hand, the calculated values using the constant gradient of temperature (100 K/cm) were lower than that in the experiments. Although the effects of heat loss suppress NO production near the flame region, a significant difference in NO concentration was not found compared to that under adiabatic conditions. In the postflame region, however, there were considerable differences in NO emission index as well as the contribution of NO formation mechanisms. In particular, in the range of ${\phi}\;{\geq}\;0.8$, the prompt NO mechanism plays an important role in the NO reduction under the adiabatic condition. On the other hand, the mechanism contributes to the NO production under the heat loss conditions.

• Journal of Internet Computing and Services
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• v.13 no.5
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• pp.21-31
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• 2012

Threat Evaluation(TE) which has air intelligence attained by identifying friend or foe evaluates the target's threat degree, so it provides information to Weapon Assignment(WA) step. Most of TE data are passed by sensor measured values, but existing techniques(fuzzy, bayesian network, and so on) have many weaknesses that erroneous linkages and missing data may fall into confusion in decision making. Therefore we need to efficient Threat Evaluation system that can refine various sensor data's linkages and calculate reliable threat values under unpredictable war situations. In this paper, we suggest new threat evaluation system based on information fusion JDL model, and it is principle that combine fuzzy which is favorable to refine ambiguous relationships with bayesian network useful to inference battled situation having insufficient evidence and to use learning algorithm. Finally, the system's performance by getting threat evaluation on an air defense scenario is presented.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.48 no.11
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• pp.837-847
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• 2020

A velocity profile for flapping flight is optimized to increase the power efficiency of 20g weighted flapping wing micro air vehicle in hover. The experimental optimization of flapping velocity profile is carried out with a real sized flapper, and various velocity profiles are realized by non-circular gear. Kriging with noise is adopted as a meta model of the profile optimization to reflect the data noise by uncertainty. The optimization results confirm that the flapping efficiency (thrust-to-power ratio) is substantially improved (11.3%) through the elastic deformation that carries the angular kinetic energy from previous stroke.

• Journal of Energy Engineering
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• v.10 no.3
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• pp.188-194
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• 2001

The process simulations are made on the IGCC power plant using heavy residue oil from refinery process. In order to model combined power block of IGCC, the present study employs the gas turbine of MS7001FA model integrated with ASU (Air Separation Unit), and considers the air extraction from gas turbine and the combustor dilution by returned nitrogen from ASU. The exhaust gas energy of gas turbine is recovered through the bottoming cycle with triple pressure HRSG (Heat Recovery Steam Generator). Clean syngas fuel of the gas turbine is assumed to be produced through Shell gasification of Visbreaker residue oil and Sulfinol-SCOT-Claus gas cleanup processes. The process optimization results show that the best efficiency of IGCC plant is achieved at 20% air extraction condition in the case without nitrogen dilution of gas turbine combustor find at the 40% with nitrogen dilution. Nitrogen dilution of combustor has very favorable and remarkable effect in reducing NOx emission level, while shifting the operation point of gas turbine to near surge point.

• Journal of the Korea Society for Simulation
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• v.22 no.2
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• pp.1-10
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• 2013

Modeling and simulation techniques construct experimental environment considering battlefields and are able to analyze performance of components of weapon system that closely resemble reality. However, developed model has low scalability and not cared reusability because it has been used only in a limited range of domain. In this paper, we develop a verification tool to verify reusability of developed component for dynamic reconfiguration and to judge scalability of it and a management tool to control data of it effectively. In addition, dynamic reconfiguration architecture of guided weapon systems designed in the previous study has been applied to SAM(Surface to Air Missile) System Simulator, and we study effectiveness of the developed component. Thus the user can configure various guided weapon systems through simulation application of dynamic reconfiguration architecture of component.

• Transactions of the Korean Society of Mechanical Engineers B
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• v.35 no.10
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• pp.1025-1031
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• 2011

Autoignition characteristic is an important parameter for designing diesel or PCCI engines. In particular, diesel spray flames are lifted from the nozzle and the initial flame is formed by an autoignition phenomenon. The lifted nature of diesel spray flames influences soot formation, since air will be entrained into the spray core by the entrainment of air between the nozzle region and the lifted flame base. The objective of the present study was to identify the effect of heat loss on the ignition delay time by adopting a coflow jet as a model problem. Methane ($CH_4$), ethylene ($C_2H_4$), ethane ($C_2H_6$), propene ($C_3H_6$), propane ($C_3H_8$), and normal butane (n-$C_4H_{10}$) fuels were injected into high temperature air, and the liftoff height was measured experimentally. As the result, a correlation was determined between the liftoff height of the autoignited lifted flame and the ignition delay time considering the heat loss to the atmosphere.

• Journal of the Korean Association of Geographic Information Studies
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• v.14 no.2
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• pp.109-127
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• 2011

Atmospheric aerosols, small particles in the atmosphere, are one of the important parameters in climate change and human health. Additionally, accurate estimates of aerosol species are increasingly important in environmental impact assessment studies. Recent advances in global satellite remote sensing provide powerful tool for air quality monitoring. This study explores the potential usage of satellite derived data such as atmospheric aerosols for air quality monitoring as well as climate change study. The objectives of this study is to understand the general features of the global distribution of type dependent aerosols. A detailed spatio-temporal variability of the each different satellite dataset shows the variation of the global zonal average and specific geographical regions where the strong emission sources are located. Especially, significantly large aerosol amounts are observed in Asia and Africa because of the desert dust storm, anthropogenic and biomass burning emissions.