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Auteur(s):
ORCID


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ORCID
Médium: article de revue
Langue(s): anglais
Publié dans: Buildings, , n. 4, v. 13
Page(s): 865
DOI: 10.3390/buildings13040865
Abstrait:

Bridges are geometrically complex infrastructures, and their designs usually exhibit significant geometric variations between different structural solutions. The modelling complexity implies a low degree of model reuse in comparable projects; moreover, with the development of new technologies and design ways, the AEC industry often requires computational cost reduction, less time for model developments and analysis, and little-to-zero material waste in the face of the environmental emergency. The present document proposes a generative approach to enhance the bridge design process, increasing efficiency by reducing computational costs and modelling efforts, tackling the aforementioned objectives. The following methodology relies on a workflow to create flexible geometric models, introducing parameters and numerical relationships between all the design variables. Therefore, from a generative development, different geometric solutions of a bridge’s family are created by modifying the parameter settings within the same model. Then, the present work aims to define a modelling and analysis strategy for a multi-girder composite bridge project based on parametric development, structural analysis, and optimization. The results integrate building information modeling (BIM) to explore and create high-potential designs with complex geometries and find cost-effective solutions.

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
    10728088
  • Publié(e) le:
    30.05.2023
  • Modifié(e) le:
    01.06.2023
 
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