4.6 Article

Algorithm-Aided Design for Composite Bridges

期刊

BUILDINGS
卷 13, 期 4, 页码 -

出版社

MDPI
DOI: 10.3390/buildings13040865

关键词

parametric design; building information modelling; structural optimization; composite bridge; generative design

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This document proposes a generative approach to enhance the efficiency of bridge design by reducing computational costs and modeling efforts. It introduces a workflow that creates flexible geometric models by modifying parameter settings, and aims to define a modeling and analysis strategy for multi-girder composite bridge projects. The results integrate building information modeling (BIM) to explore complex geometries and find cost-effective solutions.
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.

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