• Journal of the Computational Structural Engineering Institute of Korea
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• v.27 no.4
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• pp.297-303
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• 2014

Using the bond-based peridynamics and the parallel computation with binary decomposition, an adjoint shape design sensitivity analysis(DSA) method is developed for the dynamic crack propagation problems. The peridynamics includes the successive branching of cracks and employs the explicit scheme of time integration. The adjoint variable method is generally not suitable for path-dependent problems but employed since the path of response analysis is readily available. The accuracy of analytical design sensitivity is verified by comparing it with the finite difference one. The finite difference method is susceptible to the amount of design perturbations and could result in inaccurate design sensitivity for highly nonlinear peridynamics problems with respect to the design. It turns out that $C^1$-continuous volume fraction is necessary for the accurate evaluation of shape design sensitivity in peridynamic discretization.

• Proceedings of the Computational Structural Engineering Institute Conference
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• 2010.04a
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• pp.508-511
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• 2010

본 논문에서는 정상상태 유체-구조 연성문제를 연속체 기반으로 정식화하고 유한요소법을 이용하여 완전 연성된 해를 구하였다. 대 변형을 고려하기 위하여 토탈 라그란지안 정식화를 사용하였으며 유체 및 구조의 비선형성이 고려되었다. 유체와 구조 영역의 형상을 NURBS 곡면을 이용하여 매개화하여 표현하였으며, 형상 최적화를 위해 효율적인 설계민감도 해석법인 애조인 기법을 이용하여 압력, 속도, 변위 등에 대한 설계민감도를 구하였다. 이를 이용하여 최소 컴플라이언스를 갖게 하는 구조물 내부의 유체영역의 설계 등의 수치예제를 통하여 개발된 방법론의 타당성을 확인하였다.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.27 no.5
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• pp.337-343
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• 2014

This paper presents a continuum-based shape design sensitivity analysis(DSA) method for crack propagation problems using a reproducing kernel method(RKM), which facilitates the remeshing problem required for finite element analysis(FEA) and provides the higher order shape functions by increasing the continuity of the kernel functions. A linear elasticity is considered to obtain the required stress field around the crack tip for the evaluation of J-integral. The sensitivity of displacement field and stress intensity factor(SIF) with respect to shape design variables are derived using a material derivative approach. For efficient computation of design sensitivity, an adjoint variable method is employed tather than the direct differentiation method. Through numerical examples, The mesh-free and the DSA methods show excellent agreement with finite difference results. The DSA results are further extended to a shape optimization of crack propagation problems to control the propagation path.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.28 no.4
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• pp.425-431
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• 2015

Based on a bond-based peridynamics theory for dynamic crack propagation problems, this paper presents a design sensitivity analysis and optimization method. Peridynamics has a peculiar advantage over the existing continuum theory in the mathematical modelling of problems where discontinuities arise. For the design optimization of the crack propagation problems, a non-shape design sensitivity is derived using the adjoint variable method. The obtained adjoint sensitivity of displacement and strain energy turns out to be very accurate and efficient compared to the finite different sensitivity. The obtained design sensitivities are futher utilized to optimally control the position of bifurcation point in the design optimization of crack propagation in a plate under tension. A numerical experiment demonstrates that the optimal distribution of material density could delay the position of bifurcation.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.28 no.1
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• pp.9-18
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• 2015

In this paper, we verify the optimal topology design for heat conduction problems in steady stated which is obtained numerically using the adjoint design sensitivity analysis(DSA) method. In adjoint variable method(AVM), the already factorized system matrix is utilized to obtain the adjoint solution so that its computation cost is trivial for the sensitivity. For the topology optimization, the design variables are parameterized into normalized bulk material densities. The objective function and constraint are the thermal compliance of the structure and the allowable volume, respectively. For the experimental validation of the optimal topology design, we compare the results with those that have identical volume but designed intuitively using a thermal imaging camera. To manufacture the optimal design, we apply a simple numerical method to convert it into point cloud data and perform CAD modeling using commercial reverse engineering software. Based on the CAD model, we manufacture the optimal topology design by CNC.

• 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.