Enhancing structural efficiency with robust evolutionary topology optimization for sustainable engineering
- Authors
- Rostami, Seyyed Ali Latifi; Kolahdooz, Amin; Lim, Hyoung Jun
- Issue Date
- Oct-2025
- Publisher
- Taylor & Francis
- Keywords
- Robust topology optimization; ETO method; finite element analysis (FEA); uncertainty quantification; sparse grid collocation
- Citation
- Engineering Optimization
- Indexed
- SCIE
SCOPUS
- Journal Title
- Engineering Optimization
- URI
- https://scholarworks.gnu.ac.kr/handle/sw.gnu/80683
- DOI
- 10.1080/0305215X.2025.2571668
- ISSN
- 0305-215X
1029-0273
- Abstract
- In this study, the evolutionary topology optimization (ETO) method is enhanced by incorporating robust topology optimization (RTO) techniques and used to improve structural efficiency and sustainability. By optimizing the material distribution within a given design space, this approach reduces material usage and promotes cost-effectiveness and environmentally conscious design. The integration of robust design principles ensures that optimized structures remain resilient to variations in environmental and loading conditions. A major challenge in RTO for achieving smooth boundaries and addressing the dimensionality in uncertainty problems is overcome by integrating ETO with sparse grid collocation, which significantly reduces computational time and post-processing work. The methodology is validated through numerical examples involving two-dimensional beams subjected to uncertain loads and materials, and outperforms traditional methods such as the RTO-extended finite element method and Monte Carlo. The results highlight the capability of ETO to lower the compliance mean values and standard deviations, attesting to its efficiency and robustness.
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