- Nationality: Greek
PhD Thesis
Airframe Design and Manufacturing enhanced by Artificial Intelligence.
Supervisors
Andrea Cini (UC3M)
Abstract
This research focuses on developing an innovative multi-fidelity design framework to optimize the structural design of airframes for the next generation of environmentally friendly and quiet aircraft. The project leverages artificial intelligence (AI) and machine learning (ML) to enhance the accuracy of structural sizing tools, which are crucial for optimizing the internal structure and mass distribution of airframes. Various fidelity levels and optimization strategies will be explored to strike a balance between precision and computational efficiency. The research also aims to utilize advanced composite materials and multifunctional structures to minimize structural weight. Incorporating high-fidelity GFEM will further refine the design by accounting for detailed structural elements like assembly techniques and joints. The project ultimately seeks to contribute to sustainable aviation by integrating advanced materials and AI-driven optimizations into airframe design.
TIFON – Tecnologías Inteligentes para la Fabricación, el diseño y las Operaciones en entornos industriales PLEC2023-010251. This project has been granted by the CDTI, with the support of the Ministry of Science and Innovation, with file number MIG-20232039 through the TransMisiones 2023 initiative, within the scope of the “Programa Estatal para Catalizar la Innovación y el Liderazgo Empresarial del Plan Estatal de Investigación Científica y Técnica y de Innovación 2021-2023” program.
PhD in Aerospace Engineering UC3M 