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Design Optimisation for Cable Dome Structures Based on Progressive Collapse Resistance

Auteur(s):




ORCID


Médium: article de revue
Langue(s): anglais
Publié dans: Buildings, , n. 9, v. 13
Page(s): 2353
DOI: 10.3390/buildings13092353
Abstrait:

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:

Cette oeuvre a été publiée sous la license Creative Commons Attribution 4.0 (CC-BY 4.0). Il est autorisé de partager et adapter l'oeuvre tant que l'auteur est crédité et la license est indiquée (avec le lien ci-dessus). Vous devez aussi indiquer si des changements on été fait vis-à-vis de l'original.

  • Informations
    sur cette fiche
  • Reference-ID
    10744645
  • Publié(e) le:
    28.10.2023
  • Modifié(e) le:
    07.02.2024
 
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