• 한국전산구조공학회:학술대회논문집
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• 한국전산구조공학회 2008년도 정기 학술대회
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• pp.216-221
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• 2008

Shape design optimization for linear elasticity problem is performed using isogeometric analysis method. In many design optimization problems for real engineering models, initial raw data usually comes from CAD modeler. Then designer should convert this CAD data into finite element mesh data because conventional design optimization tools are generally based on finite element analysis. During this conversion there is some numerical error due to a geometry approximation, which causes accuracy problems in not only response analysis but also design sensitivity analysis. As a remedy of this phenomenon, the isogeometric analysis method is one of the promising approaches of shape design optimization. The main idea of isogeometric analysis is that the basis functions used in analysis is exactly same as ones which represent the geometry, and this geometrically exact model can be used shape sensitivity analysis and design optimization as well. In shape design sensitivity point of view, precise shape sensitivity is very essential for gradient-based optimization. In conventional finite element based optimization, higher order information such as normal vector and curvature term is inaccurate or even missing due to the use of linear interpolation functions. On the other hands, B-spline basis functions have sufficient continuity and their derivatives are smooth enough. Therefore normal vector and curvature terms can be exactly evaluated, which eventually yields precise optimal shapes. In this article, isogeometric analysis method is utilized for the shape design optimization. By virtue of B-spline basis function, an exact geometry can be handled without finite element meshes. Moreover, initial CAD data are used throughout the optimization process, including response analysis, shape sensitivity analysis, design parameterization and shape optimization, without subsequent communication with CAD description.

• 전기학회논문지
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• 제58권3호
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• pp.548-558
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• 2009

This paper attempts to develop an algorithm which optimizes the electric field through the so-called NURB(Non-Uniform Rational B-spline) curve in order to improve the insulation capacity. In particular, the NURB curve is a kind of interpolation curve that can be expressed by a few variables. The electric field of a conductor is computed by Charge Simulation Method(CSM) while that of a spacer by Surface Charge Method(SCM); this mixed calculation method is adopted for the electric field optimization. For calculation of the initial and optimal shapes, the Gauss-Newton method, which is quite easy to formulate and has slightly faster convergence rate than other optimization techniques, was used. The tangential electric field, the total electric field, and the product of the tangential electric field and area (Area Effect) were chosen as the optimization objective function by the average value of electric field for the determined initial shape.