Identification of nonlinear aerodynamic damping of wind-excited flexible structures by curve-fitting non-Gaussian response probability density function

This study presents a new approach for identification of nonlinear aerodynamic damping of wind-excited flexible structures from stochastic response time history that can be modeled as the output of a single-degree-of-freedom system under a white noise excitation. The amplitude-dependent aerodynamic damping ratio is described as a polynomial function of vibration displacement or velocity. Based on the equivalent nonlinear equation approach, the probability density function (PDF) of displacement can be given in terms of damping model parameters, which generally follows a hardening non-Gaussian distribution. It is proposed to identify the damping model parameters by curve-fitting displacement PDF determined from the response data using a nonlinear least-square optimization technique. Firstly, the stochastic response of a tall building with a known nonlinear aerodynamic model is simulated and the performance of the proposed approach is investigated. This method is then applied to a square-shaped tall building model and a bridge deck section using wind tunnel measured data. Finally, it is used for a traffic-signal-support structure using field measurement response data. The results are also compared with those from other existing approaches. The proposed approach permits determination of nonlinear aerodynamic damping from single stochastic response history and is very easy to use in practice.