• Journal of the Computational Structural Engineering Institute of Korea
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• v.12 no.1
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• pp.95-102
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• 1999

본 연구에서는 중복되지 않는 고유치를 갖는 비비례 감쇠계의 고유치와 고유벡터의 민감도를 계산하는 새로운 방법을 제시하였다. 제안 방법에서는 (n+1)차의 대칭 행렬로 이루어진 대수방정식을 해석함으로써 n개의 자유도를 갖는 감쇠계의 고유치와 고유벡터의 설계변수에 대한 미분을 구한다. 제안 방법은 매우 간단하면서도 수치적 안정성이 보장되고 정확한 해를 주는 방법이다. 제안 방법의 검증을 위해 7자유도를 갖는 차량모델의 민감도해석을 예제에서 다루고 있다. 예제에서의 설계변수는 콘테이너의 질량으로 하였다.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.12 no.1
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• pp.103-109
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• 1999

본 연구에서는 중복 고유치를 갖는 비비례 감쇠 진동계의 고유치와 고유벡터의 민감도를 계산하는 새로운 방법을 제시하였다. 제안 방법은 매우 간단하면서도 수치적 안정성이 보장되고 정확한 해를 주는 방법이다. 제안 방법에서는 (n+m)차의 대칭 행렬로 이루어진 대수방정식을 해석함으로써 n개의 자유도를 갖는 감쇠계에 있어서 m차의 중복도를 갖는 고유치와 고유벡터의 설계변수에 대한 미분을 구한다. 제안 방법의 검증을 위해 5자유도를 갖는 단순구조물의 민감도해석을 예제에서 다루고 있다. 예제에서의 설계변수는 모델의 부분강성으로 하였다.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.18 no.3
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• pp.255-263
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• 2005

This paper proposes an efficient boundary-based technique for the shape design sensitivity analysis in various disciplines. An analytical sensitivity formula in the form of a boundary integral is derived based on the continuum formulation for a general functional defined in the problems. The formula can be conveniently used for gradient computation in a variety of shape design problems. The advantage of using a boundary-based method is that the shape variation vectors are needed only on the boundary, not over the whole domain. The boundary shape variation vectors are conveniently computed by using finite. Perturbations of the shape geometry instead of complex analytical differentiation of the geometry functions. The potential flow problems and fillet problem are chosen to illustrate the efficiency of the proposed methodology.

• Transactions of the Korean Society of Mechanical Engineers
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• v.17 no.1
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• pp.141-152
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• 1993

A generalized method is presented for shape design sensitivity analysis of axisymmetric thermal conducting solids. The shape sensitivity formula of a general performance functional arising in shape optimal design problem is derived using the material derivative concept and the adjoint variable method. The method for deriving the formula is based on standard axisymmetric boundary integral equation formulation. It is then applied to obtain the sensitivity formulas for temperature and heat flux constraints imposed over a small segment of the boundary. To show the accuracy of the sensitivity analysis, numerical implementations are done for three examples. Sensitivities calculated by the presented method are compared with analytic sensitivities for two examples with analytic solutions, and compared with sensitivies by finite difference for a cooling fin example.

• 한국정보통신설비학회:학술대회논문집
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• 2003.08a
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• pp.70-72
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• 2003

본 논문에서는 설계민감도 해석법과 위상최적화 기법을 사용하여 산란체의 물질상수 분포를 알기위한 수치해석 알고리즘을 제안하였다. 설계민감도 해석법과 보조변수법을 사용하여 복소 유전율에대한 목적함수의 미분정보를 계산하였고 이 민감도 정보를 통해 물질정보를 최적화 하였다. 최적화 기법으로 최대경사법(Steepest descent Method)을 사용하였으며 이 제안한 해석 기법을 2차원 TMz 모델에 적용함으로써 검증하였다.

• Computational Structural Engineering
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• v.7 no.3
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• pp.115-122
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• 1994

Design sensitivity analysis of the second order perturbed eigenproblems for random structural system is presented. Dynamic response of random system including uncertainties for the design variable is calculated with the first order and second order perturbation method to original governing equation. In optimal design methods, there is fundamental requirement for design gradients. A method for calculating the sensitivity coefficients is developed using the direct differentiation method for the governing equation and first order and second order perturbed equation.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.31 no.3
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• pp.155-163
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• 2018

One of the major disadvantages of isogeometric analysis(IGA) is that local refinement is nearly impossible in a conventional manner because of the tensor product nature in NURBS. In this research, we investigate a local refinement scheme for isogeometric analysis, named multi-resolution approach where different resolutions are employed at each subdomain, using h-refinement relation to endow displacement compatibility on an interface of subdomains. Then, we develop shape sensitivity analysis possessing same compatibility condition as in the analysis. Numerical examples are shown to demonstrate the computational efficiency of the method in analysis especially stress concentration problem and accurate sensitivity results which is also compatible on the interface.

• Proceedings of the KSME Conference
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• 2005.11a
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• pp.158.2-158.2
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• 2005

• Proceedings of the KIEE Conference
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• 1999.07a
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• pp.43-45
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• 1999

지금까지 사용된 2차원 유한요소해석은 자계의 프린징(Fringing) 및 누설 자계 등을 무시하기 때문에 정확한 특성을 파악하기 위해서는 3차원 모델을 사용하여야 한다. BLDC 모터의 회전자(자석)의 높이를 고정시킨 상태에서 고정자(Core) 높이의 변화에 따른 코깅(Cogging) 토크의 해석을 통해 높이 비에 대한 2차원과 3차원 유한요소해석 결과 사이에의 상관 오차에 대한 연구를 수행하였다 또한. 정자기의 3차원 형상 설계 민감도 해석 기법을 개발하였다. 개발된 정자기 민감도 프로그램(MAGSEN-magnetic sensitivity)은 유용성과 실용성을 보이기 위하여 BLDC 모터의 코깅토크를 줄이는 형상 최적설계에 적용되었다.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.35 no.6
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• pp.367-374
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• 2022

This papter presents the use of the automatic differential method based on the backpropagation method to obtain the design sensitivity and its application to topology optimization considering the stress constraints. Solving topology optimization problems with stress constraints is difficult owing to singularities, the local nature of stress constraints, and nonlinearity with respect to design variables. To solve the singularity problem, the stress relaxation technique is used, and p-norm for stress constraints is applied instead of local stresses for global stress measures. To overcome the nonlinearity of the design variables in stress constraint problems, it is important to analytically obtain the exact design sensitivity. In conventional topology optimization, design sensitivity is obtained efficiently and accurately using the adjoint variable method; however, obtaining the design sensitivity analytically and additionally solving the adjoint equation is difficult. To address this problem, the design sensitivity is obtained using a backpropagation technique that is used to determine optimal weights and biases in the artificial neural network, and it is applied to the topology optimization with the stress constraints. The backpropagation technique is used in automatic differentiation and can simplify the calculation of the design sensitivity for the objectives or constraint functions without complicated analytical derivations. In addition, the backpropagation process is more computationally efficient than solving adjoint equations in sensitivity calculations.