Optimum design of steel frames with semi-rigid connections and composite beams
In this paper, an optimization process using Genetic Algorithm (GA) that mimics biological processes is presented for optimum design of planar frames with semi-rigid connections by selecting suitable standard sections from a specified list taken from American Institute of Steel Construction (AISC). The stress constraints as indicated in AISC-LRFD (American Institute of Steel Construction - Load and Resistance Factor Design), maximum lateral displacement constraints and geometric constraints are considered for optimum design. Two different planar frames with semi-rigid connections taken from the literature are carried out first without considering concrete slab effects in finite element analyses and the results are compared with the ones available in literature. The same optimization procedures are then repeated for full and semi rigid planar frames with composite (steel and concrete) beams. A program is developed in MATLAB for all optimization procedures. Results obtained from this study proved that consideration of the contribution of the concrete on the behavior of the floor beams provides lighter planar frames. © 2015 Techno-Press, Ltd.
SourceStructural Engineering and Mechanics
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The optimization of multi-storey composite steel frames with genetic algorithm including dynamic constraints [Çok katli kompozit çelik çerçevelerin genetik algoritma ile dinamik sinirlayicin optimizasyonu] Optimum design of the structures, in other words designing the structures with minimum weight is one of the major research areas in structural engineering. The priority during optimization process is to ensure whether the ...
Optimum design of composite steel frames with semi-rigid connections and column bases via genetic algorithm A genetic algorithm-based minimum weight design method is presented for steel frames containing composite beams, semi-rigid connections and column bases. Genetic Algorithms carry out optimum steel frames by selecting ...
This paper presents an optimization process using Genetic Algorithm (GA) for minimum weight by selecting suitable standard sections from a specified list taken from American Institute of Steel Construction (AISC). The ...