TY - INPR A1 - Kavrakov, Igor A1 - Morgenthal, Guido T1 - A synergistic study of a CFD and semi-analytical models for aeroelastic analysis of bridges in turbulent wind conditions N2 - Long-span bridges are prone to wind-induced vibrations. Therefore, a reliable representation of the aerodynamic forces acting on a bridge deck is of a major significance for the design of such structures. This paper presents a systematic study of the two-dimensional (2D) fluid-structure interaction of a bridge deck under smooth and turbulent wind conditions. Aerodynamic forces are modeled by two approaches: a computational fluid dynamics (CFD) model and six semi-analytical models. The vortex particle method is utilized for the CFD model and the free-stream turbulence is introduced by seeding vortex particles upstream of the deck with prescribed spectral characteristics. The employed semi-analytical models are based on the quasi-steady and linear unsteady assumptions and aerodynamic coefficients obtained from CFD analyses. The underlying assumptions of the semi-analytical aerodynamic models are used to interpret the results of buffeting forces and aeroelastic response due to a free-stream turbulence in comparison with the CFD model. Extensive discussions are provided to analyze the effect of linear fluid memory and quasi-steady nonlinearity from a CFD perspective. The outcome of the analyses indicates that the fluid memory is a governing effect in the buffeting forces and aeroelastic response, while the effect of the nonlinearity is overestimated by the quasi-steady models. Finally, flutter analyses are performed and the obtained critical velocities are further compared with wind tunnel results, followed by a brief examination of the post-flutter behavior. The results of this study provide a deeper understanding of the extent of which the applied models are able to replicate the physical processes for fluid-structure interaction phenomena in bridge aerodynamics and aeroelasticity. KW - Ingenieurwissenschaften KW - Aerodynamik KW - Bridge KW - Aerodynamic nonlinearity KW - Fluid memory KW - Vortex particle method KW - Buffeting KW - Flutter Y1 - 2018 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:gbv:wim2-20200206-40873 N1 - This is the pre-peer reviewed version of the following article: https://www.sciencedirect.com/science/article/abs/pii/S0889974617308423?via%3Dihub, which has been published in final form at https://doi.org/10.1016/j.jfluidstructs.2018.06.013 ER - TY - INPR A1 - Kavrakov, Igor A1 - Morgenthal, Guido T1 - Aeroelastic analyses of bridges using a Pseudo-3D vortex method and velocity-based synthetic turbulence generation N2 - The accurate representation of aerodynamic forces is essential for a safe, yet reasonable design of long-span bridges subjected to wind effects. In this paper, a novel extension of the Pseudo-three-dimensional Vortex Particle Method (Pseudo-3D VPM) is presented for Computational Fluid Dynamics (CFD) buffeting analysis of line-like structures. This extension entails an introduction of free-stream turbulent fluctuations, based on the velocity-based turbulence generation. The aerodynamic response of a long-span bridge is obtained by subjecting the 3D dynamic representation of the structure to correlated free-stream turbulence in two-dimensional (2D) fluid planes, which are positioned along the bridge deck. The span-wise correlation of the free-stream turbulence between the 2D fluid planes is established based on Taylor's hypothesis of frozen turbulence. Moreover, the application of the laminar Pseudo-3D VPM is extended to a multimode flutter analysis. Finally, the structural response from the Pseudo-3D flutter and buffeting analyses is verified with the response, computed using the semi-analytical linear unsteady model in the time-domain. Meaningful merits of the turbulent Pseudo-3D VPM with respect to the linear unsteady model are the consideration of the 2D aerodynamic nonlinearity, nonlinear fluid memory, vortex shedding and local non-stationary turbulence effects in the aerodynamic forces. The good agreement of the responses for the two models in the 3D analyses demonstrates the applicability of the Pseudo-3D VPM for aeroelastic analyses of line-like structures under turbulent and laminar free-stream conditions. KW - Bridge KW - Aerodynamik KW - Ingenieurwissenschaften KW - Computational Bridge Aerodynamics KW - Buffeting KW - Flutter KW - Long-span Bridges KW - Vortex Particle Method Y1 - 2018 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:gbv:wim2-20200206-40864 N1 - This is the pre-peer reviewed version of the following article: https://www.sciencedirect.com/science/article/pii/S0141029617322976?via%3Dihub, which has been published in final form at https://doi.org/10.1016/j.engstruct.2018.08.093 ER - TY - INPR A1 - Kavrakov, Igor A1 - Argentini, Tommaso A1 - Omarini, Simone A1 - Rocchi, Daniele A1 - Morgenthal, Guido T1 - Determination of complex aerodynamic admittance of bridge decks under deterministic gusts using the Vortex Particle Method N2 - Long-span bridges are prone to wind-induced vibrations. Therefore, a reliable representation of the aerodynamic forces acting on a bridge deck is of a major significance for the design of such structures. This paper presents a systematic study of the two-dimensional (2D) fluid-structure interaction of a bridge deck under smooth and turbulent wind conditions. Aerodynamic forces are modeled by two approaches: a computational fluid dynamics (CFD) model and six semi-analytical models. The vortex particle method is utilized for the CFD model and the free-stream turbulence is introduced by seeding vortex particles upstream of the deck with prescribed spectral characteristics. The employed semi-analytical models are based on the quasi-steady and linear unsteady assumptions and aerodynamic coefficients obtained from CFD analyses. The underlying assumptions of the semi-analytical aerodynamic models are used to interpret the results of buffeting forces and aeroelastic response due to a free-stream turbulence in comparison with the CFD model. Extensive discussions are provided to analyze the effect of linear fluid memory and quasi-steady nonlinearity from a CFD perspective. The outcome of the analyses indicates that the fluid memory is a governing effect in the buffeting forces and aeroelastic response, while the effect of the nonlinearity is overestimated by the quasi-steady models. Finally, flutter analyses are performed and the obtained critical velocities are further compared with wind tunnel results, followed by a brief examination of the post-flutter behavior. The results of this study provide a deeper understanding of the extent of which the applied models are able to replicate the physical processes for fluid-structure interaction phenomena in bridge aerodynamics and aeroelasticity. KW - Bridge KW - Aerodynamik KW - Ingenieurwissenschaften KW - Aerodynamic admittance KW - Computational fluid dynamics KW - Vortex particle method KW - Buffeting KW - Long-span bridges Y1 - 2019 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:gbv:wim2-20200206-40883 N1 - This is the pre-peer reviewed version of the following article: https://www.sciencedirect.com/science/article/pii/S0167610519305719?via%3Dihub, which has been published in final form at https://doi.org/10.1016/j.jweia.2019.103971 ER - TY - JOUR A1 - Kavrakov, Igor A1 - Kareem, Ahsan A1 - Morgenthal, Guido T1 - Comparison Metrics for Time-histories: Application to Bridge Aerodynamics N2 - Wind effects can be critical for the design of lifelines such as long-span bridges. The existence of a significant number of aerodynamic force models, used to assess the performance of bridges, poses an important question regarding their comparison and validation. This study utilizes a unified set of metrics for a quantitative comparison of time-histories in bridge aerodynamics with a host of characteristics. Accordingly, nine comparison metrics are included to quantify the discrepancies in local and global signal features such as phase, time-varying frequency and magnitude content, probability density, nonstationarity and nonlinearity. Among these, seven metrics available in the literature are introduced after recasting them for time-histories associated with bridge aerodynamics. Two additional metrics are established to overcome the shortcomings of the existing metrics. The performance of the comparison metrics is first assessed using generic signals with prescribed signal features. Subsequently, the metrics are applied to a practical example from bridge aerodynamics to quantify the discrepancies in the aerodynamic forces and response based on numerical and semi-analytical aerodynamic models. In this context, it is demonstrated how a discussion based on the set of comparison metrics presented here can aid a model evaluation by offering deeper insight. The outcome of the study is intended to provide a framework for quantitative comparison and validation of aerodynamic models based on the underlying physics of fluid-structure interaction. Immediate further applications are expected for the comparison of time-histories that are simulated by data-driven approaches. KW - Ingenieurwissenschaften KW - Aerodynamik KW - Brücke KW - Bridge Y1 - 2020 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:gbv:wim2-20200625-41863 UR - https://ascelibrary.org/doi/10.1061/%28ASCE%29EM.1943-7889.0001811 N1 - This material may be downloaded for personal use only. Any other use requires prior permission of the American Society of Civil Engineers. This material may be found at https://ascelibrary.org/doi/10.1061/%28ASCE%29EM.1943-7889.0001811. N1 - This is the final draft of the following article: https://ascelibrary.org/doi/10.1061/%28ASCE%29EM.1943-7889.0001811, which has been published in final form at https://doi.org/10.1061/(ASCE)EM.1943-7889.0001811 ER - 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 -