STUDY OF CHARACTERISTIC AERODYNAMIC-STRUCTURE INTERACTION ON 2DOF SECTIONAL MODEL OF THE LONG-SPAN BRIDGE DECKS USING ANSYS SOFTWARE

• Main Author: Sulistiya
• Format: Theses
• Language: Indonesia
• Online Access: https://digilib.itb.ac.id/gdl/view/62372
• Institution: Institut Teknologi Bandung

Aeroelastic is phenomena of interaction between fluid and structure. Flutter is one of the most notable aeroelastic phenomena that occur in long-span bridges that may cause catastrophic structural failure. Flutter instability can be investigated by using numerical and experimental methods. Experimental methods using wind tunnel are being considered the most effective method. However, a wind tunnel testing is more expensive than a numerical simulation. Even though the numerical method can not replace the experimental method completely, the numerical approach is considered an alternative method to evaluate aeroelastic phenomena.. It also provides additional data in the design phase of long-span bridges. In this study, simulation of fluid-structure interaction (FSI) was used to analyze the critical flutter speed for the 2DoFs sectional model of the long-span bridge decks using Ansys software. The computation of FSI simulated a wind tunnel testing using the free vibration technique. In order to identify the influence of the deck’s shape on the flutter instability mechanisms, the numerical computations were carried on various cross-section shape decks. Afterward, the computations, the dynamic response from the numerical computation were identified to extract the dynamic parameters and flutter derivatives (FDs) coefficients by using Modified Ibrahim Time-Domain Method (MITD) According to the current study, the rectangular cross-section deck (bluff body) with low ratios B/D is more susceptible to the instability flutter than streamlined decks. In the bluff body, it is probably to experience a torsional flutter mechanism. In comparison, the streamlined decks tend to experience coupling flutter. The turbulence models would not influence the result of the flutter predictions and dynamic parameter identifications.