Optimum design of a composite drone component using slime mold algorithm

Abstract

Composite materials have a wide range of applications in many industries due to their manufacturability, high strength values, and light filling. The sector where composite materials are mostly used is the aviation industry. Today, as a result of the development of aviation systems, drones have started to be actively used, and many studies have started to be carried out to mitigate them. In this study, the subcarrier part, which is part of the drone, was designed using glass and carbon fiber-reinforced composite materials. Using the data obtained at the end of the analysis, the stacking angle with the optimal displacement and stress value was determined by using the genetic algorithm (GA), gray wolf algorithm (GWO), and slime mold optimization (SMO) techniques in order to develop a carrier with a minimum displacement and stress value of more than 60 MPa. As a result of the optimization, it was determined that artificial intelligence algorithms could be used effectively in determining the stacking angle of composite materials, and the optimum values were determined in the slime mold algorithm.