Abstract
Crenellation is a promising technique to effectively improve the fatigue life of fuselage panels. It systematically varies the thickness of the fuselage skin at a constant structural weight. In the design of the crenellation patterns, the schemes of redistributing the skin material between different thickened and thinned regions can be innumerable. In order to select the optimum design from the huge searching space, a genetic algorithm was used in this study, which was coupled with FEM simulations used to predict the fatigue life of different crenellation designs. To accelerate the optimization process, a progressively refined searching approach and an old-individual-filtering technique were used. The suggested approach leads to both a reduced computational cost and improved solution quality.