Aerodynamic Shape Optimization of Long-Span Bridges

This work develops an optimization algorithm to select the most optimal section for a long-span bridge in terms of the minimum section weight by limiting the flutter limit. Parametric variations in the depth and width of the fairing shape are introduced as variables in the optimization process. Several methods for prediction, namely Polynomial, Extreme machine Learning, and Gaussian Process, are used to build the response surface model, to ensure that the design is reliable enough to always be on the safe side with the uncertainty in design variables, reliability-based design optimization (RBDO) is also introduced.