| The goal of the research is to develop and implement a methodology for automated design of structural systems. The major thrust is to include as many of the structural parameters as candidate design variables. While existing design methodologies have addressed the automated design issue in the past, the applicability of the methodologies is severely limited due to the inherent limitations of the techniques used. Genetic Algorithm (GA) has shown tremendous potential in tackling engineering design problems such as design of steel frames, where meeting design code requirements in the most cost-effective manner is nontrivial.; The research is aimed at utilizing GA's as the design tool. Several key enhancements are made to the simple GA in order to increase the efficiency and robustness of the design methodology. The analysis tool used is the finite element method. The design codes that are used to illustrate the design methodology include the AISC ASD and the AISI LRFD design codes that are commonly applicable to design of steel structures. Small as well as large scale problems are solved to illustrate the developed methodologies. Simultaneous sizing, shape and topology optimal designs of structural framed systems subjected to static and dynamic loads are considered.; Results indicate the enhancements made to the GA do indeed make the design system more efficient and robust than the simple GA. Comparisons with previously published problems solved using other optimization techniques indicate similar results. Unresolved challenges include strategies to reduce the number of function evaluations, and solving very large scale design problems in a timely manner. |
