Optimum Design of Cold-Formed Steel Purlins Using Genetic Algorithms;Doctoral thesis

摘要

An important advantage of cold-formed steel is the great flexibility of cross-sectional shapes and sizes available to the structural steel designer. However, the lack of standard optimized shapes makes the selection of the most economical shape very difficult. This task is further complicated by the complex and highly nonlinear nature of the rules that govern their designs. In this thesis, genetic algorithms are used to carry out the optimization of cold-formed steel purlins, which are assumed to be continuous over two spans subjected to a gravity load. A genetic algorithm based optimum design method for cold-formed steel purlins is developed first. This method obtains the optimum dimensions for purlins with the highest load efficiency subjected to the geometrical and strength constraints provided in Eurocode 3, Part 1.3, and fabrication constraints. The design of cold-formed steel purlins is based on Eurocode 3, Part 1.3.