• The Sea:JOURNAL OF THE KOREAN SOCIETY OF OCEANOGRAPHY
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• v.5 no.3
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• pp.177-185
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• 2000

The adjoint method is a method of data assimilation to improve the model results by seeking for model parameters that minimize the cost function and satisfy the governing equations of a model simultaneously. An adjoint package was set up for the two-dimensional linear tidal model and was applied to an idealized domain for an optimal estimation of the open boundary conditions. The assimilating data were selected from the results of forward modeling. Attention is paid on the response of the adjoint package to weighting parameters, the importance of initial estimates of model parameters and the applicability of the adjoint package to the case with varying depth. A procedure to determine optimal weight is presented based on the relationships between weights and other factors.

• Proceedings of the KSME Conference
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• 2008.11a
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• pp.418-423
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• 2008

Among various sensitivity evaluation techniques, semi-analytical method is quite popular since this method is more advantageous than analytical method and global finite difference method. However, SAM reveals severe inaccuracy problem when relatively large rigid body motions are identified for individual elements. Such errors result from the numerical differentiation of the pseudo load vector calculated by the finite difference scheme. In the present study, the adjoint variable method combined with complex variable is proposed to obtain the shape and size sensitivity for structural optimization. The complex variable can present accurate results regardless of the perturbation size as well as easy to be implemented. Through a few numerical examples of the static problem for the structural sensitivity, the efficiency and reliability of the adjoint variable method combined with complex variable is demonstrated.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.33 no.3
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• pp.243-250
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• 2009

The adjoint variable method can reduce computation time and save computer resources because it can selectively provide the sensitivity information for the positions that designers wish to measure. However, the adjoint variable method commonly employs exact analytical differentiation with respect to the design variables. It can be cumbersome to precisely differentiate every given type of finite element. This trouble can be overcome only if the numerical differentiation scheme can replace this exact manner of differentiation. But, the numerical differentiation scheme causes of severe inaccuracy due to the perturbation size dilemma. For assuring the accurate sensitivity without any dependency of perturbation size, this paper employs a complex variable that has been mainly used for computational fluid dynamics problems. The adjoint variable method combined with complex variables is applied to obtain the shape and size sensitivity for structural optimization. Numerical examples demonstrate that the proposed method can predict stable sensitivity results and that its accuracy is remarkably superior to traditional sensitivity evaluation methods.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.36 no.2
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• pp.99-104
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• 2008

This study performed robust design optimization of fighter wing planform, considering uncertainty based on neural network model. To construct uncertainty model, aerodynamic performance and their sensitivity were evaluated by 3-dimensional Euler equations and adjoint variable method at experimental points selected from central composite design. In addition, because a neural network model has the advantage of capturing non-linear characteristic, it was possible to predict sensitivity of the aerodynamic performance efficiently and accurately . From the results of robust design optimization, it could be confirmed that the robustness of the objective function and constraints were improved if the variation of uncertainty and sigma level were increased.

• 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.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.23 no.1
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• pp.37-43
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• 2010

In this paper, a reliability-based design optimization is developed for the topology design of linear structures using a performance measure approach. Spatial domain is discretized using three dimensional Reissner-Mindlin plate elements and design variable is taken as the material property of each element. A continuum based adjoint variable method is employed for the efficient computation of sensitivity with respect to the design and random variables. The performance measure approach of RBDO is employed to evaluate the probabilistic constraints. The topology optimizationproblem is formulated to have probabilistic displacement constraints. The uncertainties such as material property and external loads are considered. Numerical examples show that the developed topology optimization method could effectively yield a reliable design, comparing with the other methods such as deterministic, safety factor, and worst case approaches.

• Transactions of the Korean Society of Mechanical Engineers
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• v.9 no.1
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• pp.119-126
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• 1985

형상은 3차원이지만 2차원 문제로 이상화하여 해석할 수 있는 탄성구조물의 최적설계를 내연기관 연결봉(Connecting Rod)을 예제로 사용하여 진행하였다. 연결봉은 각 부위에서의 두께는 다르나 평면응력상태에 있다고 가정하였다. 연결봉의 질량을 최소화하기 위해 두께의 분포 및 2차원 모델 경계의 모양을 설계변수로 채택하였고 설계변수 및 응력치에 대한 제한조건을 적용하였다. 설계감도계수 계산을 위해 Variational Formulation, Material Derivative, Adjoint Variable이론을 도입하였고 최적화 방법으로는 Gradient Projection Method를 사용하였다. 최적설계 결과 현재 사용중인 연결봉 무게의 20%를 줄일 수 있음이 밝혀졌다.

• Journal of computational fluids engineering
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• v.6 no.2
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• pp.9-21
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• 2001

초음속 여객기의 천음속 순항 성능을 개선하기 위하여 날개의 플랩 꺽임각을 최적화하였다. 이를 위하여 3차원 Euler 코드와 adjoint 코드를 이용한 최적설계기법을 적용하였다. 설계변수로서, 앞전플랩 5개, 뒷전 플랩 5개 등 총 10개의 플랩의 꺽임각이 사용되었다. 설계과정중에 격자계 내부격자점의 수정을 위해 타원형방정식법을 이용하였다. 계산 시간의 단축을 위해 내부격자의 민감도는 무시하였다. 또한 본 설계문제에 근사구배기법의 적용가능성 여부를 조사하였다. 충격파가 없는 경우 앞전 플렙에 한하여 근사구배기법을 적용할 수 있음을 알았다. 최적설계기법으로 BFGS기법을 적용하여 항력을 최소화하였으며, 양력 및 날개 표면 마하수에 대한 제약조건을 적용하였다. 앞전 플랩의 최적화 및 앞전과 뒷전 플랩의 최적화 등 두 개의 설계 문제를 고려하였다. 성공적인 결과를 얻음으로써 본 설계방법의 타당성 및 효율성을 확인하였다.

• Transactions of the Korean Society of Mechanical Engineers
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• v.18 no.1
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• pp.12-23
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• 1994

This paper proposes an optimal design software for the open-chain dynamic systems whose governing equations are expressed as differential equation. In this software, an input module and an automatic creation module of the equation of motion are developed to contrive the user's convenience. To analyze the equation of motion of the dynamic systems, variable-order and variable-stepsize Adams-Bashforth-Moulton predictor-corrector method is used to improve the efficiency. For the optimization and the design sensitivity analysis, ALM(augmented lagrange multiplier)method and adjoint variable method are adopted respectively. An output module with which the user can compare and investigate the analysis and the optimization results through tables and graphs is also provided. The developed software is applied to three typical dynamic response optimization problems, and the results compare very well with those available in the literature, demonstrating its effectiveness.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.14 no.2
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• pp.159-171
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• 2001

평면 아치 구조물에 대해 선형 탄성 변분방정식에 기반을 둔 설계민감도 해석을 위한 일반적 이론을 개발하였다. 아치 구조물내의 임의 마디에 정의된 응력범함수를 고려하였고 이에 대한 설계민감도 공식을 유도하기 위해 전미분(material derivative) 개념과 보조(adjoint) 변수 방법을 도입하였다. 얻어진 민감도 공식은 구조해석 결과를 얻고 나면 이들로부터 단순 대수연산을 통해 계산이 되므로 적용이 간편할 뿐 아니라 해의 정확도가 높은 잇점이 있다. 본 방법은 아치의 형상을 매개변수를 통해 표현하므로 얕은 아치에 국한하지 않고 어떠한 형상도 고려가 가능하며, 나아가서 아치의 형상변화를 형상에 대해 수직뿐 아니라 접선방향도 포함하여 일반적으로 고려하므로 다양한 형상설계가 가능하다. 몇 가지 예제에서 민감도 계산을 수행함으로써 본 방법의 정확도와 효율성을 입증하였으며, 두 가지의 설계최적화 문제를 대상으로 실제로 두께 및 형상최적설계를 수행하였다.