FLUTTER DERIVATIVES IDENTIFICATION TO PREDICT FLUTTER SPEED OF 2 DOFS SECTIONAL MODEL OF LONG SPAN BRIDGES

• Main Author: DWI SAPUTRA , ANGGA
• Format: Theses
• Language: Indonesia
• Online Access: https://digilib.itb.ac.id/gdl/view/62035
• Institution: Institut Teknologi Bandung

The long span bridges are critical to support national transport and logistic process, opening access to remote areas. Hence, it provides beneficial contribution to enable nationwide economic equality. The long span bridges, despite their lightweight structure and elegant design, possess high flexibility and low damping properties. Thus, concerning structural interaction with the winds, the long span bridges are known to experience a so-called aeroelastic phenomenon. The interaction between aerodynamic forces and structural deflections becomes a crucial issue in the design phase. Flutter is one of the most notable aeroelastic phenomenons occured in long span bridges. Flutter instability needs to be evaluated carefully as it might cause catastrophic structural failure. Numerical and experimental methods can be used to investigate flutter on a deck bridge. However, the numerical methods used for lifting structure, i.e., aircraft wing, could be inaccurate for a complex-shaped deck, such as a deck equipped with railings and bluff cross section bridges. Therefore, experimental methods using wind tunnel are more convenient to validate flutter phenomenon on a bridge deck. Full model test is the most accurate method to analyze flutter, unfortunately, it is the most expensive one. The sectional model test is the most efficient in term of cost and time as it uses a much simpler shape, i.e., two degree of freedoms (2 DoFs) test model. In the present study, a flutter testing procedure for the 2DoFs sectional model of long span bridge deck is developed. The identification of the flutter derivatives is the key procedure in the current study. The proposed method constructs a hybrid numerical procedure, combining a wind tunnel test to identify the flutter derivatives coefficients and a numerical method to determine the flutter speed limit. The sensitivity analysis of input parameters was carried out to identify the parameters that significantly influence the model output. The sensitivity coefficient of each parameter input was used to determine the uncertainty of critical flutter speed