Optimization of orthotropic girders in cable supported bridges by parametric studies

Mads Jacob Baandrup, Peter Noe Poulsen, John Forbes Olesen, Henrik Polk

    Research output: Contribution to conferencePaperResearchpeer-review


    For the last six decades closed-box orthotropic steel girders have been widely used in cable supported bridges due to their simple but useful structural concepts. Several numerical parametric studies were previously carried out in order to investigate inherent fatigue stress problems and in general, to improve the bridge girder designs. However, often such studies have been carried out with over-simplified finite element models, especially where boundary conditions have been challenging. In the present work, an advanced multi-scale FE model of a suspension bridge is established with sophisticated boundary conditions applied to a local parametric sub-model of a bridge girder. Thus, the model accommodates realistic support conditions. With this sub-model, a parametric study of the usual design parameters is carried out with focus on fatigue and a Eurocode stiffness requirement. The study reveals trends and correlations for the varying design parameters. Finally, the parametric sub-model is utilized in an automatic gradient-based optimization of multiple design variables simultaneously with the goal of minimizing weight. The methods allow bridge engineers to push material utilization to its limits by giving new insight into the effect of changing design parameters.
    Original languageEnglish
    Publication date2019
    Number of pages6
    Publication statusPublished - 2019
    Event2019 IABSE Congress New York City: The Evolving Metropolis: Addressing Structural Affordability, Durability, and Safety - The Javits Center, New York City, United States
    Duration: 4 Sept 20196 Sept 2019


    Conference2019 IABSE Congress New York City
    LocationThe Javits Center
    Country/TerritoryUnited States
    CityNew York City


    • Orthotropic bridge girders
    • Cable supported bridges
    • Optimization
    • Parametric Study


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