Abstract

BEGLIARDO-OLIVERO, Hugo Félix  and  BONELLI-HERNANDEZ, Matías. Plane trusses optimization by means of parametric design and genetic algorithms applying visual programming. Ing. invest. y tecnol. [online]. 2019, vol.20, n.4, 00002.  Epub Nov 15, 2019. ISSN 2594-0732.  https://doi.org/10.22201/fi.25940732e.2019.20n4.038.

The optimization of structures is a wished goal, but it is not always achieved in engineering practice, due to either the large additional effort that it demands or the lack of necessary resources to carry it out. Structural engineers usually use batch procedures, consisting of utilizing the software, in which data are input, running the analysis and evaluating the results, along which it is decided whether the design is accepted or modifications must be made, in which case the process is repeated again. The consequence of this is that the final result, normally, will always be improvable. For that reason, the field of optimization has usually been reserved to the academia. The new currents of structural engineering seek optimization by means of parametric design and evolutionary computing. As an additional contribution to the use of these resources, the objective of this work is to present an algorithm developed through visual programming for sizing, shape and topology optimization of plane trusses of the classic Howe, Pratt or Warren typologies, and to highlight the advantages that the use of this resource provides for the professional work of structural engineers, since it allows them to develop their own algorithms without the need of previous knowledge of programming, and to achieve economic and environmental benefits from saving materials. All this configures a clear transfer of the advances of computer technology to professional practice, extending the frontiers of the academic sphere. As an example of application, a truss analyzed by traditional methods, without optimizing, and the same truss optimized with the aforementioned algorithm, are compared.

Keywords : Structural optimization; plane trusses; parametric design; genetic algorithms; visual programming.

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