Abstract
Triaxial weave fabrics are increasingly used in ultralight structures, such as the wings of unmanned aerial vehicles (UAVs) and deployable antenna on spacecraft. The tensile strength to stiffness ratio for these applications is important, requiring an optimal weave pattern; in this paper Genetic Algorithms are used to improve these designs. The mechanical response is obtained using the minimum total complementary potential energy principle where the yarns are approximated as curved beams in a micromechanical unit cell. Leading Genetic Algorithms are benchmarked to determine which perform best. The results form a disconnected Pareto front where the left hand part can be used for flexible structures but is difficult to find. An overall improvement in strength to stiffness ratio of 1191% is made with 643 designs found better than a current example. The selection of the Genetic Algorithm is shown to be crucial with only MLSGA-NSGAII regularly finding the entire Pareto front.
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