Abstract
Abstract: The objective of this research is to create a software to optimize choice variables adopted by an engineer in a structural system with steel-concrete composite beams and steel decks, such as: beam shape, composite slab sheeting, number and spacing of beams, slab thickness and interaction ratio between beam and slab. To accomplish this, a program that uses the Genetic Algorithm optimization tool provided by Matlab R2015a was developed. To meet safety requirements, restrictions on the Ultimate Limit State were implemented in the code, following the normative requirements of ABNT NBR 8800: 2008. Case studies of a problem found in the literature and another of a real structure, are presented to serve as references for software evaluation. Results indicate that the use of optimization processes is fundamental to design increasingly cost-effective structures.
Highlights
Structural optimization is a method aimed at reducing the construction cost of a given structural design as much as possible, without detriments to structural safety
To simplify the design optimization, Fakury, Silva and Caldas [24] adopt the lowest possible thickness of steel sheeting, that is, 0.8 mm and subsequently the following criteria: 1) use the shortest total beam length, regardless of the profiles to be adopted; 2) seek the lowest weight of the slab, which generally corresponds to the slab with the lowest concrete weight
Results obtained from the application of the developed software to proposed problems indicate that the program is an efficient tool for optimization of structural systems composed of steel-concrete composite beams and slabs
Summary
Structural optimization is a method aimed at reducing the construction cost of a given structural design as much as possible, without detriments to structural safety. A good optimization process is one in which the modelled structure and considerations regarding chosen design variables closely resemble actual service conditions. Among the optimization methods currently available, Genetic Algorithms (GA) stand out due to the possibility of working with discrete variables, making GA the recommended approach for optimizing structural systems featuring.
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