Design Optimisation for Cable Dome Structures Based on Progressive Collapse Resistance
Author(s): |
Lian-Meng Chen
Sun-Kai Yan Zhi-Chao Jiang Kai-Yu Huang Ze-Bin Li Wei Li Yi-Yi Zhou Shi-Lin Dong |
---|---|
Medium: | journal article |
Language(s): | English |
Published in: | Buildings, 23 August 2023, n. 9, v. 13 |
Page(s): | 2353 |
DOI: | 10.3390/buildings13092353 |
Abstract: |
This study proposed a framework of optimal design for flexible cable dome structures based on progressive collapse resistance. First, a quantitative evaluation method for nonlinear robustness based on robustness control theory to reflect the structural progressive collapse resistance was proposed. Second, an actual engineering structure was used as a case study to evaluate the effects of design parameters on structural robustness. Finally, a genetic algorithm was used as an optimisation algorithm to further optimise the element cross-section and the structural shape and obtain a combined optimisation rate. The results indicated that increasing the element cross-sectional area, decreasing the structural span, and increasing the rise-to-span ratio effectively improved the structural robustness. The structural robustness was also effectively improved through the optimal design of element cross-sections by increasing element cross-sections sensitive to structural robustness and decreasing those insensitive to structural robustness. In this study, the combined optimisation rate was 38.27%, which was not only greater than the individual optimisation rates of 11.2% for element cross-sectional area optimisation and 22.5% for structural shape optimisation but also the sum of these two rates. |
Copyright: | © 2023 by the authors; licensee MDPI, Basel, Switzerland. |
License: | This creative work has been published under the Creative Commons Attribution 4.0 International (CC-BY 4.0) license which allows copying, and redistribution as well as adaptation of the original work provided appropriate credit is given to the original author and the conditions of the license are met. |
1.68 MB
- About this
data sheet - Reference-ID
10744645 - Published on:
28/10/2023 - Last updated on:
07/02/2024