| Owing to their excellent structural characteristics, aesthetic appearance, low maintenance cost, and efficient use of structural materials, cable-stayed bridges have gained much popularity in recent decades. Stay cables of a cable stayed bridge are post-tensioned to counteract the effect of the bridge dead load. The solution for an optimum distribution of post-tensioning cable forces is considered one of the most important and difficult tasks in the design of cable-stayed bridges. A novel approach that utilizes the finite element method, B-spline curves, and real coded genetic algorithm to determine the global optimum post-tensioning cable forces is developed. The effect of geometric nonlinearity on the determination of the post-tensioning cable forces is assessed. The study is further extended to develop the first surrogate polynomial functions that can be used to evaluate the post-tensioning cable forces in semi-fan cable stayed bridges. The developed post-tensioning functions are then used to investigate the optimal geometric configurations, which lead to the most uniform distribution of the post-tensioning cable forces. Details of an optimization code developed in-house specifically to optimize the design of composite cable-stayed bridges with semi-fan cable arrangement are then reported. The optimization design code integrates a finite element model, the real coded genetic algorithm, the post-tensioning polynomial functions, and the design provisions provided by the Canadian Highway Bridge Design Code. An extensive parametric study is then conducted using this optimization code to develop a database for the optimum design of semi-fan cablestayed bridges. The database covers bridge lengths ranging from 250 m to 700 m. It describes the variations of the optimum design parameters, such as the main span length, height of the pylon, number of stay cables, and cross-sectional dimensions with the total length of the bridge.;KEYWORDS: Cable-Stayed Bridge, Semi-Fan Cable-Stayed Bridge, Finite Element, Real Coded Genetic Algorithms, Genetic Algorithms, B-spline Function, Post-Tensioning Cable Forces, Optimization, Optimum Design, Preliminary Design, Cost minimization, Design Constraints. |
