TY - INPR A1 - Abbas, Tajammal A1 - Kavrakov, Igor A1 - Morgenthal, Guido A1 - Lahmer, Tom T1 - Prediction of aeroelastic response of bridge decks using artificial neural networks N2 - The assessment of wind-induced vibrations is considered vital for the design of long-span bridges. The aim of this research is to develop a methodological framework for robust and efficient prediction strategies for complex aerodynamic phenomena using hybrid models that employ numerical analyses as well as meta-models. Here, an approach to predict motion-induced aerodynamic forces is developed using artificial neural network (ANN). The ANN is implemented in the classical formulation and trained with a comprehensive dataset which is obtained from computational fluid dynamics forced vibration simulations. The input to the ANN is the response time histories of a bridge section, whereas the output is the motion-induced forces. The developed ANN has been tested for training and test data of different cross section geometries which provide promising predictions. The prediction is also performed for an ambient response input with multiple frequencies. Moreover, the trained ANN for aerodynamic forcing is coupled with the structural model to perform fully-coupled fluid--structure interaction analysis to determine the aeroelastic instability limit. The sensitivity of the ANN parameters to the model prediction quality and the efficiency has also been highlighted. The proposed methodology has wide application in the analysis and design of long-span bridges. KW - Aerodynamik KW - Artificial neural network KW - Ingenieurwissenschaften KW - Bridge KW - Bridge aerodynamics KW - Aerodynamic derivatives KW - Motion-induced forces KW - Bridges Y1 - 2020 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:gbv:wim2-20200225-40974 N1 - This is the pre-peer reviewed version of the following article: https://www.sciencedirect.com/science/article/abs/pii/S0045794920300018?via%3Dihub, https://doi.org/10.1016/j.compstruc.2020.106198 ER - TY - THES A1 - Abbas, Tajammal T1 - Assessment of Numerical Prediction Models for Aeroelastic Instabilities of Bridges N2 - The phenomenon of aerodynamic instability caused by the wind is usually a major design criterion for long-span cable-supported bridges. 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. The complexity and uncertainty of models for such engineering problems demand strategies for model assessment. This study is an attempt to use the concepts of sensitivity and uncertainty analyses to assess the aeroelastic instability prediction models for long-span bridges. The state-of-the-art theory concerning the determination of the flutter stability limit is presented. Since flutter is a coupling of aerodynamic forcing with a structural dynamics problem, different types and classes of structural and aerodynamic 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 coupled model. T3 - Schriftenreihe des DFG Graduiertenkollegs 1462 Modellqualitäten // Graduiertenkolleg Modellqualitäten - 16 KW - Brücke KW - Flattern KW - Unsicherheit KW - Flutter KW - Bridges KW - Sensitivity KW - Uncertainty KW - Model assessment Y1 - 2016 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:gbv:wim2-20180515-27161 UR - https://asw-verlage.de/katalog/assessment_of_numerical_prediction_models_for_aeroelastic_instabilities_of_bridges-1897.html PB - Jonas Verlag CY - Weimar ER -