양방향 진화적 구조최적화를 이용한 신뢰성기반 위상최적화Reliability-Based Topology Optimization Based on Bidirectional Evolutionary Structural Optimization
- Other Titles
- Reliability-Based Topology Optimization Based on Bidirectional Evolutionary Structural Optimization
- Authors
- 유진식; 김상락; 박재용; 한석영
- Issue Date
- Aug-2010
- Publisher
- 한국생산제조학회
- Keywords
- 신뢰성기반 위상최적화; 신뢰성 지수 접근법; 목표성능치 접근법; 양방향 진화적 구조최적화; 민감도수; 신뢰성지수; Reliability-Based Topology Optimization; Reliability Index Approach; Performance Measure Approach; Bidirectional Evolutionary Structural Optimization; Sensitivity number; Reliability Index
- Citation
- 한국생산제조학회지, v.19, no.4, pp.529 - 538
- Indexed
- KCI
- Journal Title
- 한국생산제조학회지
- Volume
- 19
- Number
- 4
- Start Page
- 529
- End Page
- 538
- URI
- https://scholarworks.bwise.kr/hanyang/handle/2021.sw.hanyang/174290
- ISSN
- 2508-5093
- Abstract
- 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.
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