Advanced composite wing design for next-generation military UAVs: A progressive numerical optimization framework

The design of unmanned aerial vehicles (UAVs) revolves around the careful selection of materials that are both lightweight and robust. Carbon fiber-reinforced polymer (CFRP) emerged as an ideal option for wing construction, with its mechanical qualities thoroughly investigated. In this study, we developed and optimized a conceptual UAV wing to withstand structural loads by establishing progressive composite stacking sequences, and we conducted a series of experimental characterizations on the resulting material. In the optimization phase, the objective was defined as weight reduction, while the Hashin damage criterion was established as the constraint for the optimization process. The optimization algorithm adaptively monitors regional damage criterion values, implementing necessary adjustments to facilitate the mitigation process in a cost-effective manner. Optimization of the analytical model using Simulia Abaqus™ and a Python-based user-defined sub-routine resulted in a 34.7% reduction in the wing's structural weight after 45 iterative rounds. Then, the custom-developed optimization algorithm was compared with a genetic algorithm optimization. This comparison has demonstrated that, although the genetic algorithm explores numerous possibilities through hybridization, the custom-developed algorithm is more result-oriented and achieves optimization in a reduced number of steps. To validate the structural analysis, test specimens were fabricated from the wing's most critically loaded segment, utilizing the identical stacking sequence employed in the optimization studies. Rigorous mechanical testing revealed unexpectedly high compressive strength, while tensile and bending strengths fell within expected ranges. All observed failure loads remained within the established safety margins, thereby confirming the reliability of the analytical predictions.