• Structural Engineering and Mechanics
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• v.59 no.4
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• pp.621-652
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• 2016

A new cable-supported bridge model consisting of suspension parts, self-anchored cable-stayed parts and earth-anchored cable-stayed parts is presented. The new bridge model can be used for suspension bridges, cable-stayed bridges, cable-stayed suspension bridges, and partially earth-anchored cable-stayed bridges by varying parameters. Based on the assumption that each structural member is in either an axial compressive or tensile state, and the stress in each member is equal to the allowable stress of the material, the material quantity for each component is calculated. By introducing the unit cost of each type of material, the estimation formula for the cost of the new bridge model is developed. Numerical examples show that the results from the estimation formula agree well with that from the real projects. The span limit of cable supported bridge depends on the span-to-height ratio and the density-to-strength ratio of cables. Finally, a parametric study is illustrated aiming at the relations between three key geometrical parameters and the cost of the bridge model. The optimization of the new bridge model indicates that the self-anchored cable-stayed part is always the dominant part with the consideration of either the lowest total cost or the lowest unit cost. It is advisable to combine all three mentioned structural parts in super long span cable supported bridges to achieve the most excellent economic performance.

• Advances in aircraft and spacecraft science
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• v.7 no.4
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• pp.353-369
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• 2020

This paper presents the flutter analysis and optimum design of axially functionally graded box beam cantilever wing section by considering various geometric and material parameters. The coupled dynamic equations of the continuous model of wing system in terms of material and cross-sectional properties are formulated based on extended Hamilton's principle. By expressing the lift and pitching moment in terms of plunge and pitch displacements, the resultant two continuous equations are simplified using Galerkin's reduced order model. The flutter velocity is predicted from the solution of resultant damped eigenvalue problem. Parametric studies are conducted to know the effects of geometric factors such as taper ratio, thickness, sweep angle as well as material volume fractions and functional grading index on the flutter velocity. A generalized surrogate model is constructed by training the radial basis function network with the parametric data. The optimized material and geometric parameters of the section are predicted by solving the constrained optimal problem using firefly metaheuristics algorithm that employs the developed surrogate model for the function evaluations. The trapezoidal hollow box beam section design with axial functional grading concept is illustrated with combination of aluminium alloy and aluminium with silicon carbide particulates. A good improvement in flutter velocity is noticed by the optimization.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.29 no.4 s.235
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• pp.570-577
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• 2005

In this study a complete 3D surface reconstruction method is proposed based on the concept that the vertices of surface model can be completely matched to the unstructured point cloud. In order to generate the initial mesh model from the point cloud, the mesh subdivision of bounding box and shrink-wrapping algorithm are introduced. The control mesh model for well representing the topology of point cloud is derived from the initial mesh model by using the mesh simplification technique based on the original QEM algorithm, and the parametric surface model for approximately representing the geometry of point cloud is derived by applying the local subdivision surface fitting scheme on the control mesh model. And, to reconstruct the complete matching surface model, the insertion of isolated points on the parametric surface model and the mesh optimization are carried out Especially, the fast 3D surface reconstruction is realized by introducing the voxel-based nearest-point search algorithm, and the simulation results reveal the availability of the proposed surface reconstruction method.

• The Journal of Korean Association of Computer Education
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• v.11 no.5
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• pp.57-66
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• 2008

An adaptive optimization of parametric cubic convolution for image interpolation is derived in this paper. The proposed technique is based on optimizing the standard cubic convolution interpolation formula at each interpolated pixel. Conventional parametric cubic convolution methods use a fixed parameter in an image, so properties of each pixel cannot be incorporated into the interpolation. The proposed method optimizes the interpolation kernel by obtaining parameters adaptively on each pixel. A new cost function is introduced to reflect frequency properties of the original data. The proposed technique produces noticeably sharper edges than traditional techniques and exhibits an average PSNR improvement of traditional techniques.

• International Journal of Aeronautical and Space Sciences
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• v.14 no.3
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• pp.229-236
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• 2013

This paper presents the experimental investigation of a biplane micro air vehicle. The effects of geometric parameters, gap, stagger, and decalage angle are investigated at low Reynolds number (~150,000) in a low-speed wind tunnel. A rigid flat plate with an aspect ratio of one and square planform shape is used to evaluate all three geometric parameters. The side dimension of the single flat plate is 0.15 m. The goal is to find an optimal biplane configuration that should exceed monoplane performance by generating high lift and flying as slow as possible, in order to capture high-quality visual recordings. This configuration will directly help to fly at a lower velocity and to make tighter turns that are advantageous in restricted environments. The results show that the aerodynamic performance of the biplane MAV is significantly enhanced through the combination of gap and stagger effects. A performance comparison demonstrates the superiority of the optimal biplane configuration compared to a monoplane in cruise and glide phases. Moreover, no significant compromise is found for the range, endurance, and climb performance.

• Journal of the Korean Institute of Intelligent Systems
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• v.20 no.6
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• pp.780-785
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• 2010

This paper introduces GP(Genetic Programming) based color detection model for an object detection and tracking. Existing color detection methods have used linear/nonlinear transformatin of RGB color-model and improved color model for illumination variation by optimization or learning techniques. However, most of cases have difficulties to classify various of colors because of interference of among color channels and are not robust for illumination variation. To solve these problems, we propose illumination robust and non-parametric multi-colors detection model using evolution of GP. The proposed method is compared to the existing color-models for various colors and images with different lighting conditions.

• Journal of the Korea Computer Graphics Society
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• v.17 no.3
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• pp.33-42
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• 2011

We present a new technique for removing interior knots of parametric B-spline curves. An initial curve is constructed by continuous $L_{\infty}$ approximation proposed by Eck and Hadenfeld. We employ Hausdorff distance to measure the shape difference between the original curve and the initial one. The final curve is obtained by minimizing their Hausdorff distance. We demonstrate the effectiveness of our technique with experimental results on various types of planar and spatial curves.

• Journal of Korea Water Resources Association
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• v.36 no.6
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• pp.1025-1033
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• 2003

In common with workers in hydrologic fields, scientists and engineers relate one variable to two or more other variables for purposes of predication, optimization, and control. Statistics methods have improved to establish such relationships. Regression, as it is called, is indeed the most commonly used statistics technique in hydrologic fields; relationship between the monitored variable stage and the corresponding discharges(rating curve). Regression methods expressed in the form of mathematical equations which has parameters, so called parametric methods. some times, the establishment of parameters is complicated and uncertain. Many non-parametric regression methods which have not parameters, have been proposed and studied. The most popular of these are kernel regression method. Kernel regression offer a way of estimation the regression function without the specification of a parametric model. This paper conducted comparisons of some bandwidth selection methods which are using the least squares and cross-validation.

• Journal of the Korean Society for Marine Environment & Energy
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• v.13 no.4
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• pp.241-248
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• 2010

This paper deals with the performance analysis and design of the Darrieus-type vertical axis turbine to evaluate the effect of key design parameters such as number of blade, blade chord, pitch and camber. The commercial CFD software FLUENT was employed as an unsteady Reynolds-Averaged Navier-Stokes (RANS) solver with k-e turbulent model. Grid system was modelled by GAMBIT. Basic numerical methodology of the present study is appeared in Jung et al. (2009). Two-dimensional analysis was mostly adopted to avoid the barrier of massive calculation required for parametric study. It was found that the highly efficient turbine model could be designed through the optimization of design parametrrs.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.30 no.1
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• pp.87-94
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• 2017

Reliability analysis(RA) and Reliability-based design optimization(RBDO) require statistical modeling of input random variables, which is parametrically or nonparametrically determined based on experimental data. For the parametric method, goodness-of-fit (GOF) test and model selection method are widely used, and a sequential statistical modeling method combining the merits of the two methods has been recently proposed. Kernel density estimation(KDE) is often used as a nonparametric method, and it well describes a distribution function when the number of data is small or a density function has multimodal distribution. Although accurate statistical models are needed to obtain accurate RA and RBDO results, accurate statistical modeling is difficult when the number of data is small. In this study, the accuracy of two statistical modeling methods, SSM and KDE, were compared according to the number of data. Through numerical examples, the RA results using the input models modeled by two methods were compared, and appropriate modeling method was proposed according to the number of data.