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Long-span cable supported bridges are prone to aerodynamic instabilities caused by wind and this phenomenon is usually a major design criterion. If the wind speed exceeds the critical flutter speed of the bridge, this constitutes an Ultimate Limit State. The prediction of the flutter boundary therefore requires accurate and robust models. This paper aims at studying various combinations of models to predict the flutter phenomenon.
Since flutter is a coupling of aerodynamic forcing with a structural dynamics problem, different types and classes of models can be combined to study the interaction. Here, both numerical approaches and analytical models are utilised and coupled in different ways to assess the prediction quality of the hybrid model. Models for aerodynamic forces employed are the analytical Theodorsen expressions for the motion-enduced aerodynamic forces of a flat plate and Scanlan derivatives as a Meta model. Further, Computational Fluid Dynamics (CFD) simulations using the Vortex Particle Method (VPM) were used to cover numerical models.
The structural representations were dimensionally reduced to two degree of freedom section models calibrated from global models as well as a fully three-dimensional Finite Element (FE) model. A two degree of freedom system was analysed analytically as well as numerically.
Generally, all models were able to predict the flutter phenomenon and relatively close agreement was found for the particular bridge. In conclusion, the model choice for a given practical analysis scenario will be discussed in the context of the analysis findings.
Reinforced concrete walls are commonly selected as the lateral resisting systems in seismic design of buildings. The design procedure requires reliable/robust models to predict the wall response. Many researchers, thus, have focused on using the available experimental data to be able to comment on the quality of models at hand. What is missing though is an uncertain attitude towards the experimental data since such data can be affected by different sources of uncertainty. In this paper, we introduce the database created for model quality evaluation purposes considering the uncertainties in the experimental data. This is the first step of a larger study on experience-based model quality evaluation of reinforced concrete walls. Here, we briefly present the database as well as six sample validations of the developed numerical model (the quality of which is to be assessed). The database contains the information on nearly 300 wall specimens from about 50 sources. Both the database and the numerical model, built for uncertainty/sensitivity analysis purposes, are mainly based on ten parameters. These include geometry, material, reinforcement layout and loading properties. The validation results prove that the model is able to predict the wall response satisfactorily. Consequently, the validated numerical model could be used in further quality evaluation studies.