Theoretical And Experiment Study On Identification Of Aerodynamic Derivatives Of Bridge Decks

Aerodynamic derivatives are important parameters to characterize the aerodynamic property of bridge structures. Refined research concerning bridge wind-resistant analysis needs better identification precision in the aerodynamic derivatives of bridge deck. So how to obtain these parameters accurately and effectively is one of main concerns in wind-resistant study of long-span bridges. Motivated with this necessity, this dissertation focuses on theoretical and experimental approaches to the identification of aerodynamic derivatives. The main contents are as following:1. Based on Iterative Least Square (ILS) method, the Subsection Extended Order Iterative Least Square algorithm (SEO-ILS) for system identification in time domain is presented firstly. The SEO-ILS algorithm is able to directly identify system matrix from free vibration data of bridge deck sectional model via wind tunnel test. By using the SEO-ILS algorithm, complex and real mode parameters may also be obtained simultaneously. The numerical simulation results indicate that the proposed method performs comparably with the traditional ILS method in identifying stiffness coefficients while provides better performance in identifying damping coefficients. The SEO-ILS algorithm is finally applied to identify the stiffness and damping matrix of an elastically-suspended sectional model by using the wind tunnel testing data.2. The measurement noise in wind tunnel testing data is detrimental to achieve a better identification results. A technique based on wavelet technique and low-pass filter is examined to preprocess measurement data and eliminate the measurement noise in data. High-frequency noise is firstly eliminated from the testing data by using the wavelet reconstruction and decomposition technique, and a zero-phase low-pass filter is then applied to the reconstructed data. The numerical results show that the noise-elimination method effectively improves the identified accuracy when performed in conjunction with the SEO-ILS algorithm.3. The equations of motion for bridge deck section model elastically suspended in wind tunnel are formulated about mass center of the system using the Lagrangian approach, accommodating both the elasticity eccentricity and damping eccentricity in the formulation. With this formulation, the SEO-ILS algorithm is applied in the state space for direct identification of the system matrix from free vibration data of section model obtained from wind tunnel testing. This formulation complements the existing theory concerning the basic formulation of bridge flutter derivatives identification to consider the unexpected eccentricities in model testing.4. The SEO-ILS algorithm is applied to identify aerodynamic derivatives by using wind tunnel testing data. A thin plate model was tested in wind tunnel and the eight aerodynamic derivatives were estimated by SEO-ILS algorithm. The reliability and effectiveness of SEO-ILS method are demonstrated by comparing the experimentally obtained aerodynamic derivatives of thin plate with theoretical values. The test of bridge deck sections model in wind tunnel indicate that parameter identification of the SEO-ILS method has higher precision, stability and repeatability are better as well as. Considering eccentricities influence for bridge deck is shown to improve the identification precisions of aerodynamic derivatives.5. Aerodynamic derivatives characteristic of bridges both streamlined and bluff decks were discussed thoroughly. Identification precisions and variability of aerodynamic derivatives were investigated by changing hyper-parameters of SEO-ILS algorithm. The results indicate that obtained aerodynamic derivatives by SEO-ILS method are stability and reliability, and variability of aerodynamic derivatives are very small at higher reduced wind speed.