• Title/Summary/Keyword: 위상최적설계

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Preliminary Study on Nonlinear Static Response Topology Optimization Using Equivalent Load (등가하중을 이용한 비선형 정적 응답 위상최적설계의 기초연구)

  • Lee, Hyun-Ah;Zeshan, Ahmad;Park, Gyung-Jin
    • Transactions of the Korean Society of Mechanical Engineers A
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    • v.34 no.12
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    • pp.1811-1820
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    • 2010
  • Most components in the real world show nonlinear response. The nonlinearity may arise because of contact between the parts, nonlinear material, or large deformation of the components. Structural optimization considering nonlinearities is fairly expensive because sensitivity information is difficult to calculate. To overcome this difficulty, the equivalent load method was proposed for nonlinear response optimization. This method was originally developed for size and shape optimization. In this study, the equivalent load method is modified to perform topology optimization considering all kinds of nonlinearities. Equivalent load is defined as the load for linear analysis that generates the same response field as that for nonlinear analysis. A simple example demonstrates that results of the topology optimization using equivalent load are very similar to the numerical results. Nonlinear response topology optimization is performed with a practical example and the results are compared with those of conventional linear response topology optimization.

Particle-Structure Collision Modeling for Topology Optimization (위상최적설계를 위한 입자-구조 충돌 모델)

  • Young Hun Choi;Gil Ho Yoon
    • 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.

Material Topology Optimization Design of Structures using SIMP Approach Part II : Initial Design Domain with Topology of Partial Solids (SIMP를 이용한 구조물의 재료 위상 최적설계 Part II : 부분적인 솔리드 위상을 가지는 초기 설계영역)

  • Lee, Dong-Kyu;Park, Sung-Soo;Shin, Soo-Mi
    • Journal of the Computational Structural Engineering Institute of Korea
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    • v.20 no.1
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    • pp.19-28
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    • 2007
  • Discrete topology optimization processes of structures start from an initial design domain which is described by the topology of constant material densities. During optimization procedures, the structural topology changes in order to satisfy optimization problems in the fixed design domain, and finally, the optimization produces material density distributions with optimal topology. An introduction of initial holes in a design domain presented by Eschenauer et at. has been utilized in order to improve the optimization convergence of boundary-based shape optimization methods by generating finite changes of design variables. This means that an optimal topology depends on an initial topology with respect to topology optimization problems. In this study, it is investigated that various optimal topologies can be yielded under constraints of usable material, when partial solid phases are deposited in an initial design domain and thus initial topology is finitely changed. As a numerical application, structural topology optimization of a simple MBB-Beam is carried out, applying partial circular solid phases with varying sizes to an initial design domain.

Topology Design of Rigid-String Mechanism Using Constraint Force Design Method (구속조건 힘 설계기법을 이용한 강체와 스트링의 위상 최적설계)

  • Heo, Jae-Chung;Yoon, Gil-Ho
    • Transactions of the Korean Society of Mechanical Engineers A
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    • v.36 no.7
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    • pp.745-750
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    • 2012
  • This study extends the constraint force design method allowing topology optimization for planar rigid-link and string mechanisms. To our best knowledge, by applying conventional machine and mechanism design theories, it is likely that it is possible to find out optimal locations of joints and lengths of rigid-links but somewhat difficult to find out optimal topology of rigid-links. To achieve optimal topology of rigid links, there is our previous contribution so called the new constraint force design method with the binary design variables determining the existence of the auxiliary forces imposing apparent lengths among unit masses. By adding new binary design variables, this research extends the constraint force design method to find out optimal mechanism consisting of stringy links as well as rigid links that seems impossible in the conventional machine and mechanism design theories.

Topology Optimization of Element Removal Method Using Stress Density (응력량을 이용한 요소제거법의 위상최적화)

  • 임오강;이진식;김창식
    • Journal of the Computational Structural Engineering Institute of Korea
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    • v.16 no.1
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    • pp.1-8
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    • 2003
  • Topology optimization has been evolved into a very efficient conceptual design tool and has been utilized into design engineering processes. Traditional topology optimization has been using homogenization method and optimality criteria method. homogenization method provides relationship equation between structure which includes many holes and stiffness matrix in FEM. Optimality criteria method is used to update design variables while maintaining that volume fraction is uniform. Traditional topology optimization has advantage of good convergence but has disadvantage of too much convergency time. In one way to solve this problem, element removal method using the criterion of an average stress is presented. As the result of examples, it is certified that convergency time is very reduced.

Lightweight Crane Design by Using Topology and Shape Optimization (위상최적설계와 형상최적설계를 이용한 크레인의 경량설계)

  • Kim, Young-Chul;Hong, Jung-Kie;Jang, Gang-Won
    • Transactions of the Korean Society of Mechanical Engineers A
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    • v.35 no.7
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    • pp.821-826
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    • 2011
  • CAE-based structural optimization techniques are applied for the design of a lightweight crane. The boom of the crane is designed by shape optimization with the shape of the cross section of the boom as the design variable. The design objective is mass minimization, and the static strength and dynamic stiffness of the system are set as the design constraints. Hyperworks, a commercial analysis and optimization software, is used for shape and topology optimization. In order to consistently change the shape of the elements of the boom with respect to the change in the shape of its cross section, the morphing function in Hyperworks is used. The support of the boom of the original model is simplified to model the design domain for topology optimization, which is discretized by using three-dimensional solid elements. The final result after shape and topology optimization is 19% and 17% reduction in the masses of the boom and support, respectively, without a deterioration in the system stiffness.

Topology Design Optimization using Projection Method (프로젝션 기법을 활용한 위상 최적설계)

  • Ha, Seung-Hyun
    • Journal of the Computational Structural Engineering Institute of Korea
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    • v.29 no.4
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    • pp.293-299
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    • 2016
  • In this paper, a projection method is introduced which is used in topology design optimization. In the projection method, each active design variable is projected onto the design domain depending on the shape and size of the projection functions, and the finite element under this projection receives a solid material. Furthermore, the size of the projection function defines the minimum length scale of the structural members. Therefore, a designer can easily apply design constraints without complicated post-processing procedure. In addition, the projection method can be combined with the homogenization theory, and applied to material design problem for composite materials. Topology design optimization for the unit-cell of the periodic structures can maximize the effective material properties, which yields the optimal material distribution with maximum bulk or shear moduli under a given volume fraction.

Stress Constraint Topology Optimization using Backpropagation Method in Design Sensitivity Analysis (설계민감도 해석에서 역전파 방법을 사용한 응력제한조건 위상최적설계)

  • Min-Geun, Kim;Seok-Chan, Kim;Jaeseung, Kim;Jai-Kyung, Lee;Geun-Ho, Lee
    • 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.