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AI InsightThe results indicated that is more efficient using GA than ES since the former requires the analysis of a lesser amount of cases in order to determine the optimal geometric configuration; there being reductions of up to 47,09% on the number of simulations.
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Özet
This work is a feasibility study of a Genetic Algorithm (GA) based geometric optimization of stiffened plates subjected to transverse loads. For that, the Constructal Design method was used in order to define the search space, aiming to minimize the stiffened plate’s central deflection, while keeping the total volume of material constant. The number of longitudinal Nls and transverse Nts stiffeners and the relation hs/ts, the ratio between the height and the thickness of the ribs, were considered as degrees of freedom of the studied optimization problem. In order to estimate the displacement field of the plate reinforced with stiffeners, the Finite Element Method (FEM) was used through the ANSYS® Mechanical APDL software. For the verification, the results obtained in the present study were compared with those obtained by Troina (2017), which used Exhaustive Search (ES) as optimization technique. The results indicated that is more efficient using GA than ES since the former requires the analysis of a lesser amount of cases in order to determine the optimal geometric configuration; there being reductions of up to 47,09% on the number of simulations.