Reliability-Based Topology Optimization Based on Bidirectional Evolutionary Structural Optimization

유진식,김상락,박재용,한석영,Yu, Jin-Shik,Kim, Sang-Rak,Park, Jae-Yong,Han, Seog-Young The Korean Society of Manufacturing Technology Eng 2010 한국공작기계학회지 Vol.19 No.4

This paper presents a reliability-based topology optimization (RBTO) based on bidirectional evolutionary structural optimization (BESO). In design of a structure, uncertain conditions such as material property, operational load and dimensional variation should be considered. Deterministic topology optimization (DTO) is performed without considering the uncertainties related to the design variables. However, the RBTO can consider the uncertainty variables because it can deal with the probabilistic constraints. The reliability index approach (RIA) and the performance measure approach (PMA) are adopted to evaluate the probabilistic constraints in this study. In order to apply the BESO to the RBTO, sensitivity number for each element is defined as the change in the reliability index of the structure due to removal of each element. Smoothing scheme is also used to eliminate checkerboard patterns in topology optimization. The limit state indicates the margin of safety between the resistance (constraints) and the load of structures. The limit State function expresses to evaluate reliability index from finite element analysis. Numerical examples are presented to compare each optimal topology obtained from RBTO and DTO each other. It is verified that the RBTO based on BESO can be effectively performed from the results.

Reliability-Based Topology Optimization Based on Bidirectional Evolutionary Structural Optimization

Jin-Shik Yu(유진식),Sang-Rak Kim(김상락),Jae-Yong Park(박재용),Seog-Young Han(한석영) 한국생산제조학회 2010 한국생산제조학회지 Vol.19 No.4

This paper presents a reliability-based topology optimization (RBTO) based on bidirectional evolutionary structural optimization (BESO). In design of a structure, uncertain conditions such as material property, operational load and dimensional variation should be considered. Deterministic topology optimization (DTO) is performed without considering the uncertainties related to the design variables. However, the RBTO can consider the uncertainty variables because it can deal with the probabilistic constraints. The reliability index approach (RIA) and the performance measure approach (PMA) are adopted to evaluate the probabilistic constraints in this study. In order to apply the BESO to the RBTO, sensitivity number for each element is defined as the change in the reliability index of the structure due to removal of each element. Smoothing scheme is also used to eliminate checkerboard patterns in topology optimization. The limit state indicates the margin of safety between the resistance (constraints) and the load of structures. The limit State function expresses to evaluate reliability index from finite element analysis. Numerical examples are presented to compare each optimal topology obtained from RBTO and DTO each other. It is verified that the RBTO based on BESO can be effectively performed from the results.

강성구속 조건을 갖는 구조물의 신뢰성기반 위상최적설계

김상락(Sang-Rak Kim),박재용(Jae-Yong Park),이원구(Won-Goo Lee),유진식(Jin-Shik Yu),한석영(Seog-Young Han) 한국생산제조학회 2008 한국생산제조학회지 Vol.17 No.6

This paper presents a Reliability-Based Topology Optimization(RBTO) using the Evolutionary Structural Optimization (ESO). An actual design involves some uncertain conditions such as material property, operational load and dimensional variation. The Deterministic Topology Optimization(DTO) is obtained without considering the uncertainties related to the uncertainty parameters. However, the RBTO can consider the uncertainty variables because it has the probabilistic constraints. In order to determine whether the probabilistic constraints are satisfied or not, simulation techniques and approximation methods are developed. In this paper, the reliability index approach(RIA) is adopted to evaluate the probabilistic constraints. In order to apply the ESO method to the RBTO, sensitivity number is defined as the change in the reliability index due to the removal of the ith element. Numerical examples are presented to compare the DTO with the RBTO.

양방향 요소제거법을 이용한 신뢰성 기반 최적설계

유진식,박재용,황승민,임민규,오영규,한석영 한국공작기계학회 2008 한국공작기계학회 추계학술대회논문집 Vol.2008 No.-

This research presents a Reliability-Based Topology Optimization (RBTO) using Bi-directional Evolutionary Structural Optimization (BESO). An actual design involves uncertain conditions such as material property, operational load and dimensional variation. Deterministic Topology Optimization (DTO) is obtained without considering of uncertainties related to the uncertainty parameters. However, RBTO involves evaluation of probabilistic constraints, which can be done in two different ways, the reliability index approach (RIA) and the performance measure approach (PMA). The reliability index approach (RIA) and the performance measure approach (PMA) are adopted to evaluate the probabilistic constraints. In order to apply the BESO method to the RBTO, sensitivity number is defined as the change in the reliability index due to the addition or the removal of the ith element. In the BESO, a mesh-independency filter using nodal variables is used to remove the checkerboard patterns. The optimal topologies of RIA and PMA are obtained very similarly. It is shown that RBTO based on BESO can be effectively applied from the presented examples.

ESO 기법을 이용한 외팔보의 신뢰성 기반 위상최적설계

김상락,박재용,이원구,유진식,한석영 한국공작기계학회 2008 한국공작기계학회 춘계학술대회논문집 Vol.2008 No.-

This paper presents a Reliability-Based Topology Optimization (RBTO) using the Evolutionary Structural Optimization (ESO). An actual design involves uncertain conditions such as material property, operational load and dimensional variation. The Deterministic Topology Optimization (DTO) is obtained without considering of uncertainties related to the uncertainty parameters. However, the RBTO can consider the uncertainty variables because it has the probabilistic constraints, In order to determine whether the probabilistic constraint is satisfied or not, simulation techniques and approximation methods are developed, In this paper, the reliability index approach (RIA) is adopted to evaluate the probabilistic constraint, In order to apply the ESO method to the RBTO, a sensitivity number is defined as the change in the reliability index due to the removal of ith element. Numerical examples are presented to compare the DTO with the RBTO.

ESO 기법을 이용한 컴플라이언트 메커니즘 설계

이원구,박재용,김상락,유진식,한석영 한국공작기계학회 2008 한국공작기계학회 춘계학술대회논문집 Vol.2008 No.-

A compliant mechanism is a mechanism that produces its motion by the flexibility of some or all of its members when the input forces are applied. Whereas the topology optimization based on homogenization and SIMP parameterization has been successfully applied for compliant mechanism design, an ESO approach has not been considered yet for the optimization of these types of systems. This work presents a modified version of the evolutionary structural optimization (ESO) Procedure for its application in topology optimization of compliant mechanisms, It will be shown that an additive version of this method must be adopted in order to achieve the optimum design, since the traditional ESO method's element removal technique is not efficient in this case. The methodology is based on a mutual energy concept for formulation of flexibility and the ESO method. A multi-objective optimization problem is formulated as an application of compliant mechanism design. The procedure has tested in several numerical applications and benchmark examples to illustrate and validate the approach.

ESO 기법을 이용한 신뢰성 기반 최적설계

김상락,박재용,이원구,유진식,한석영 한국공작기계학회 2007 한국공작기계학회 추계학술대회논문집 Vol.2007 No.-

This paper presents a Reliability-Based Topology Optimization (RBTO) using Evolutionary Structural Optimization (ESO). An actual design involves uncertain conditions such as material property, operational load and dimensional variation. Deterministic Topology Optimization (DTO) is obtained without considering of uncertainties related to the uncertainty parameters. However, RBTO involves evaluation of probabilistic constraints, which can be done in two different ways, the reliability index approach (RIA) and the performance measure approach (PMA). Limit state function is approximated using Monte Carlo Simulation and Central Composite Design for reliability analysis. ESO, one of the topology optimization techniques, is adopted for topology optimization. Numerical examples are presented to compare the DTO with RBTO.