Global optimization using a deflation-based method for the design of composite structures

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Composite structures are rapidly transforming the aerospace industry, driven by continuous advancements in manufacturing methods capable of producing optimized structures with variable stiffness that enables the creation of increasingly complex and efficient structures. This project focuses on the development of a global optimization method that applies the innovative concept of deflation to the design of optimized composite structures.

This project aims at developing a method for global optimization by applying the concept of deflation for the design of optimized composite structures. Gradient-based optimization is known for its accuracy in identifying local optima, although heavily depends on initial starting points in non-convex design spaces. By incorporating deflation, gradient-based optimizers can obtain multiple local optima even when starting from the same point in the design space. This approach not only offers alternate minima for assessing design feasibility but also highlights the importance of having a universally applicable method for existing optimization schemes.

The methodology herein proposed establishes a gradient-based optimization framework that is used to develop and test the developed deflation constraint. The novel deflation constraint can be integrated into any optimization method supporting constrained optimization, either gradient-based or heuristics-based. The developed deflation method is tested on various case studies related to composite structure optimization, showcasing its promising applications in the aerospace industry and beyond.