• Journal of the Computational Structural Engineering Institute of Korea
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• v.36 no.6
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• pp.365-370
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• 2023

This paper presents a particle-structure collision model for topology optimization, which requires sensitivity analysis. Therefore, a new model that incorporates sensitivity analysis is needed. The proposed particle-structure collision model conducts sensitivity analysis for topology optimization. To evaluate the accuracy of the proposed model, it was applied to a simplified one-dimensional collision problem. Optimization of the final positions of particles using topology optimization through this model confirmed the suitability of the proposed approach. These results demonstrate that it is possible to consider particle-structure collision in topology optimization.

• Journal of the Korea institute for structural maintenance and inspection
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• v.12 no.6
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• pp.241-248
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• 2008

The objective of sensitivity analyses is to identify critical variables of structural models and how their variability impacts mechanical response results. The sensitivity analyses have been used as significant basis data for practical applications of measuring and reinforcing fragile building structures. This study presents several sensitivity analysis methods for topological optimum designs of linear elastostatic structural systems. Numerical examples for structural analyses and topological optimum modeling demonstrate the reliability of sensitivities formulated in the present study.

• 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.

• Proceedings of the KSME Conference
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• 2005.11a
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• pp.214.2-214.2
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• 2005

• Journal of the Computational Structural Engineering Institute of Korea
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• v.19 no.2 s.72
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• pp.213-219
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• 2006

Topology optimization problem requires numerous repeated evaluations of objective function and design sensitivity for elements within design domain with various density distributions. The recently proposed two-level condensation scheme(TLCS) is very promising for the construction of reduced system and for an accurate and efficient analysis concerned about eigenvalue and dynamic problems. We used the two-level dynamic condensation scheme for the analysis and sensitivity computation part in the structural topology optimization problem. The results of the topology optimization for the reduced system show the TLCS provides high accuracy and computation efficiency compared to the full scale system within engineering accuracy.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.25 no.6
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• pp.559-567
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• 2012

A level set based topological shape optimization method for nonlinear structure considering hyper-elastic problems is developed. To relieve significant convergence difficulty in topology optimization of nonlinear structure due to inaccurate tangent stiffness which comes from material penalization of whole domain, explicit boundary for exact tangent stiffness is used by taking advantage of level set function for arbitrary boundary shape. For given arbitrary boundary which is represented by level set function, a Delaunay triangulation scheme is used for current structure discretization instead of using implicit fixed grid. The required velocity field in the actual domain to update the level set equation is determined from the descent direction of Lagrangian derived from optimality conditions. The velocity field outside the actual domain is determined through a velocity extension scheme based on the method suggested by Adalsteinsson and Sethian(1999). The topological derivatives are incorporated into the level set based framework to enable to create holes whenever and wherever necessary during the optimization.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.27 no.1
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• pp.9-16
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• 2014

Using a level set method and topological derivatives, a topological shape optimization method that is independent of an initial design is developed for linearly elastic structures. In the level set method, the initial domain is kept fixed and its boundary is represented by an implicit moving boundary embedded in the level set function, which facilitates to handle complicated topological shape changes. The "Hamilton-Jacobi(H-J)" equation and computationally robust numerical technique of "up-wind scheme" lead the initial implicit boundary to an optimal one according to the normal velocity field while minimizing the objective function of compliance and satisfying the constraint of allowable volume. Based on the asymptotic regularization concept, the topological derivative is considered as the limit of shape derivative as the radius of hole approaches to zero. The required velocity field to update the H-J equation is determined from the descent direction of Lagrangian derived from optimality conditions. It turns out that the initial holes are not required to get the optimal result since the developed method can create holes whenever and wherever necessary using indicators obtained from the topological derivatives. It is demonstrated that the proper choice of control parameters for nucleation is crucial for efficient optimization process.

• Proceedings of the Korean Society For Composite Materials Conference
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• 2003.04a
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• pp.22-26
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• 2003

EFPI (extrinsic Fabry-Perot interferometer) 센서를 이용해 복합재료의 파손 신호를 취득하기 위해서는 파손 신호에 비해 상대적으로 낮은 주파수의 열적, 기계적 정적 변형에 의해 발생하는 위상 변화를 보상해 주는 기술이 필요하다. 또한 센서의 민감도를 최적화하기 위해 출력 신호의 위상을 Quadrature 지점에 유지시켜야 한다. 본 논문에서는 EFPI 센서 시스템의 출력 신호위상을 일정하게 유지시킬 수 있는 안정화 제어 시스템을 개발하였다. 안정화 제어 시스템은 광대역 파장 레이저 광원, 가변 F-P (Fabry-Perot) 필터 그리고 필터를 제어한 수 있는 전자 회로시스템으로 구성하였다. 개발된 시스템의 위상 제어 성능을 평가하기 위해 복합재료 시편의 인장 실험을 수행하여 인장 변형에 의해 발생하는 위상 변화를 개발된 시스템을 이용해 Quadrature 지점에 일정하게 유지할 수 있음을 보였다. 또한 연필심 파손 실험을 통해 개발된 시스템이 파손 신호를 잘 취득할 수 있음을 확인하였다.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.21 no.3
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• pp.239-245
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• 2008

A level set based topological shape optimization using extended B-spline basis functions is developed for steady-state heat conduction problems. The only inside of complicated domain identified by the level set functions is taken into account in computation, so we can remove the effects of domain outside parts in heat conduction problem. The solution of Hamilton-Jacobi equation leads to an optimal shape according to the normal velocity field determined from the sensitivity analysis, minimizing a thermal compliance while satisfying a volume constraint. To obtain exact shape sensitivity, the precise normal and curvature of geometry need to be determined using the level set and B-spline basis functions. Using topological derivative concept, the nucleation of holes for topological changes can be made whenever and wherever necessary during the optimization.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.23 no.5
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• pp.535-541
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• 2010

In this paper, we have derived a continuum-based adjoint design sensitivity of general performance functionals with respect to Young' modulus and heat conduction coefficient for steady-state nonlinear thermoelastic problems. An adjoint equation for temperature and displacement fields is defined for the efficient computation of the coupled field design sensitivity. Through numerical examples, we investigated the mesh dependency of the topology optimization method in the thermoelastic problems. Also, comparing the dominant loading cases of thermal and mechanical ones, the loading dependency of topology design optimization in coupled multi-physics problems is investigated.