Linkage Learning Optimization of Aeroelastic and Structural Behavior of Composite Wings

The paper aims to develop a systematic numerical design for composite wings optimization subject to aerodynamic loading and to assess the aeroelastic and structural performance of the optimized composite wing. Aeroelastic tailoring is a powerful method for utilizing the anisotropic features of composite materials used in lightweight aerospace structures. The present proposed methodology combines three different analysis tools: a commercial FE software commonly used in industry, an in-house reduced order aeroelastic framework for aeroelastic analyses with tailoring capabilities, LLGA, in-house linkage-learning genetic algorithms for optimization of stacking sequences. As a multidisciplinary problem where structural and aeroelastic behaviors are interacted, developed multi-level optimization scenario in this research converges to the optimal design in a very short time. The proposed methodology implemented as a computer code can effectively be applied to any arbitrary air vehicle's composite wing by changing input data.

Automated summary

The paper presents a systematic numerical design for optimizing composite wings under aerodynamic loading and evaluates their aeroelastic and structural performance. By utilizing the anisotropic features of composite materials, a method called aeroelastic tailoring is proposed. The methodology combines three different analysis tools: a commercial FE software, an in-house reduced order aeroelastic framework, and in-house linkage-learning genetic algorithms for optimization. The proposed methodology can be effectively applied to any arbitrary air vehicle's composite wing by changing input data.