Assessment of the potential for efficient frame bridges through refined analysis and design methods

Sarah Aumayr

This thesis addresses the modelling, calculation, and design of skew and straight frame bridges constructed in an integral structural system. The objective is to investigate, in the context of resource-efficient construction, to what extent reinforcement can be reduced by modelling the structure as a plate model instead of the more commonly used bar model. Furthermore, the influence of linear-elastic and nonlinear internal force determination on the resulting design is analysed.
Through the collaboration between the engineering office Schimetta and the Institute of Concrete Structures at Graz University of Technology, an in-depth study of frame bridges was conducted as part of the FFG research project “Agile structural design for resource-responsible concrete construction.”
The bar model reaches its limits of application as soon as a certain degree of skew is exceeded and is, moreover, no longer state-of-the-art. By modeling the structure as a plate model, a holistic representation of the frame structure can be created, enabling targeted reinforcement distribution and placement - particularly in the area of the frame corner. In this way, approximately 12% of the total reinforcement quantity can be saved compared to the bar model, which represents a significant contribution considering that around 80% of all bridges in German-speaking countries are frame bridges.
When using a plate model with nonlinear internal force determination, a further reduction of about 4% in total reinforcement can be achieved. However, this approach requires a more complex and extensive workflow and is therefore only of limited suitability for practical application. Significant potential also lies in both linear-elastic and nonlinear plate models for the reassessment of bridges in need of reconstruction.
This thesis shows that engineers enable resource-efficient construction not only by using sustainable materials, but also applying them efficiently through advanced modeling approaches.

Sarah Aumayr AT

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