Inverse identification of wind loads on structures.

For slender structures with a low eigenfrequency wind loading often constitutes the critical design load. Reliable information on dynamic wind pressures, however, is difficult to obtain. Design codes provide wind pressures for a restricted class of structures with a simple geometry. Design pressures for many critical structures have to be obtained from wind tunnel tests or computational fluid dynamics (CFD). Upscaling of the experiments or adequate modelling of turbulence and boundary conditions are sources of uncertainty, however. Within the frame of this project, it will be investigated how time-varying wind loads on structures can be inferred from in situ vibration response data using inverse methods. The proposed methodology is complementary to wind tunnel tests and CFD simulations, as the results can be used to verify commonly made assumptions about wind pressure distributions. In this way, the results of this study can be used to improve future analyses and design procedures for structures. The methodology will be validated by extensive wind tunnel tests and demonstrated by an in situ test on a real structure.

Keywords:Optimal sensor location, Bayesian infererence, Random vibration, Input estimation, Kalman filter, Inverse problem, Structural dynamics, Dynamic wind loads

Disciplines:Building engineering