• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.43 no.7
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• pp.601-608
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• 2015

The static aeroelastic analysis and optimization of flexible wings are conducted for steady state conditions while both aerodynamic and structural parameters can be used as optimization variables. The system of multidisciplinary design optimization as a robust methodology to couple commercial codes for a static aeroelastic optimization purpose to yield a convenient adaptation to engineering applications is developed. Aspect ratio, taper ratio, sweepback angle are chosen as optimization variables and the skin thickness of the wing. The real-coded adaptive range multi-objective genetic algorithm code, which represents the global multi-objective optimization algorithm, was used to control the optimization process. The support vector regression(SVR) is applied for optimization, in order to reduce the time of computation. For this multi-objective design optimization problem, numerical results show that several useful Pareto optimal designs exist for the flexible wing.

• Aerospace Engineering and Technology
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• v.8 no.1
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• pp.49-57
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• 2009

The camera electronics in the KOMPSAT-3 payload provides the several control clocks in order to move the charges, which are converted from the light in the pixel, in the vertical and horizontal direction. Generally, the control clocks depend on the CCD internal design in the system. The KOMPSAT-3 payload uses the CCD controlled by 3-phase vertical clocks and 4-phase timing. The camera generates the various clocks such as the vertical clocks, the horizontal clocks, the summing clocks, the reset clocks and so on. The vertical clocks are deeply related to the camera performance and synchronized with satellite scan-rate even though they are relatively slow. Also, it gives the horizontal clocks without distortion under the very fast pixel-rate. This paper shows the design and simulation of the CCD clocks driver for the KOMPSAT-3 payload.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.30 no.1
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• pp.39-46
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• 2017

In this paper, a model updating procedure based on the response surface method combined with the multi-objective optimization was proposed and applied for updating of the FE models representing a low-rise reinforced concrete building before and after the seismic retrofit. The dynamic properties to be matched were obtained from vibration tests using a small shaker system. By varying the structural parameters according to the central composite design, analysis results from the initial FE model using a commercial software were collected and used to produce two regression functions each of which representing the errors in the natural frequencies and mode shapes. The two functions were used as the objective functions for multi-objective optimization. Final solution was determined by examining the Pareto solutions with one iteration. The parameters representing the stiffnesses of existing concrete, masonry, connection stiffness in expansion joint, new concrete, retrofitted members with steel section jacketing were selected and identified.

• Aerospace Engineering and Technology
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• v.8 no.2
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• pp.75-82
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• 2009

In order to help general users to analyze the KOMPSAT-2 data, an application of sensor modeling to commercial software was explained in this document. The sensor modeling is a basic step to extract the quantity and quality information from KOMPSAT-2 data. First, we introduced the contents and type of ancillary data offered with KOMPSAT-2 PAN image data, and explained how to use it with commercial software. And then, we applied the polynomial-base and refine RFM sensor modeling with ground control points. In the polynomial-base sensor modeling, the accuracy which is average RMSE of check points is highest when the satellite position was calculated by type of 1st order function and the satellite attitude was calculated by type of 1st order function for (Y axis), (Z axis) or constant for (X axis), (Y axis), (Z axis) in perspective center position and satellite attitude parameters. As a result of refine RFM sensor modeling, the accuracy is less than 1 pixel when we applied affine model..

• Journal of Advanced Marine Engineering and Technology
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• v.37 no.8
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• pp.893-904
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• 2013

In this paper, a Kriging metamodel-based multi-objective optimization strategy in conjunction with an NSGA-II(non-dominated sorted genetic algorithm-II) has been employed to optimize the valve-plate shape of the axial piston pump utilizing 3D CFD simulations. The optimization process for minimum pressure ripple and maximum pump efficiency is composed of two steps; (1) CFD simulation of the piston pump operation with various combination of six parameters selected based on the optimization principle, and (2) applying a multi-objective optimization approach based on the NSGA-II using the CFD data set to evaluate the Pareto front. Our exploration shows that we can choose an optimal trade-off solution combination to reach a target efficiency of the axial piston pump with minimum pressure ripple.

• Survey Research
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• v.9 no.1
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• pp.69-85
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• 2008

Stratification is a feature of the majority of field sample design. This paper considers the multivariate stratification strategy for multipurpose sample survey with several auxiliary variables. In a multipurpose survey, stratification procedure is very complicated because we have to simultaneously consider the efficiencies of stratification for several variables of interest. We propose stratification strategy based on factor analysis and cluster analysis using several stratification variables. To improve the efficiency of stratification, we first select the stratification variables by factor analysis, and then apply the K-means clustering algorithm to the formation of strata. An application of the stratification strategy in the sampling design for the Fisher Production Survey is discussed, and it turns out that the variances of estimators are significantly less than those obtained by simple random sampling.

• Journal of the Korean Association of Geographic Information Studies
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• v.13 no.3
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• pp.91-101
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• 2010

As global warming has caused the number of abnormal changes in climate to increase throughout the world, much damage has occurred recently in Korean Peninsula which results from unexpected heavy rains, landslides, and floods from typhoons. To prevent and cope with these annually repeated natural hazards, the overall improvements are needed, including systematic management of the existing natural hazard information and improvement of hazard information. In this study, multi-purpose hazard information map based on digital image was constructed as an effective way to enhance hazard management considering regional characteristics and hazard response capabilities in the field. Multi-purpose hazard information map with a new concept by fusion of geospatial information and hazard attribute information is able to support quick decision for hazard management making and development of hazard information system.

• Journal of Korean Society of Transportation
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• v.25 no.5
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• pp.161-172
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• 2007

Vehicles transporting hazardous materials can make huge damage to people, properties and environment by traffic accidents. Therefore, transporting hazardous materials is a big issue with the cutting edge technology of communications in these days. However, despite this situation, Korean government gives limited efforts for systematic management, research and investment about hazardous materials. Accordingly, this research suggests the key path finding algorithm about management of real-time schedule and routes for vehicles transporting hazardous materials. Besides, the case study is progressed in transportation networks of Seoul in order to evaluate the reality of algorithm. Specifically, time-space network transformation is performed for time window attributes. In addition, this study proposes the techniques searching for non-dominated paths considering schedule by the multiobjective shortest path algorithm based on dynamic programming in dynamic transportation networks including multiobjective attributes.

• Journal of Korea Water Resources Association
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• v.41 no.12
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• pp.1211-1218
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• 2008

This study is for design of the detention system distributed in a watershed by the Multi-Objective Genetic Algorithms(MOGAs). A new model is developed to determine optimal size and location of detention. The developed model has two primary interfaced components such as a rainfall runoff model to simulate water surface elevation(or flowrate) and MOGAs to get the optimal solution. The objective functions used in this model depend on the peak flow and storage of detention. With various constraints such as structural limitations, capacities of storage and operational targets. The developed model is applied at Gwanyang basin within Anyang watershed. The simulation results show the maximum outlet reduction is occurred at detention facilities located in upper reach of watershed in the peak discharge rates. It is also reviewed the simultaneous construction of an off-line detention and an on-line detention. The methodologies obtained from this study will be used to control the flood discharges and to reduce flood damage in urbanized watershed.

• Journal of the Korea Society of Computer and Information
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• v.16 no.7
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• pp.13-23
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• 2011

Grid computing is a new generation computing technology which organizes virtual high-performance computing system by connecting and sharing geographically distributed heterogeneous resources, and performing large-scaled computing operations. In order to maximize the performance of grid computing, job scheduling is essential which allocates jobs to resources effectively. Many studies have been performed which minimize total completion times, etc. However, resource costs are also important, and through the minimization of resource costs, the overall performance of grid computing and economic efficiency will be improved. So in this paper, we propose a multi-objective job scheduling model considering both time and cost. This model derives from the optimal scheduling solution using NSGA-II, which is a multi objective genetic algorithm, and guarantees the effectiveness of the proposed model by executing experiments with those of existing scheduling models such as Min-Min and Max-Min models. Through experiments, we prove that the proposed scheduling model minimizes time and cost more efficiently than existing scheduling models.