Design Automation techniques for the accelerated design of aerospace components

Licentiate thesis, 2025

The pace at which new technology and air transport system architectures need to be incorporated into the air fleet to compensate for its climate impact is ever increasing. Consequently, the speed at which the next generation of more sustainable products need to be designed is also increasing. Being complex and critical systems, their performance needs to be evaluated in detail, for which existing automation techniques have been traditionally applied to speed up the analysis. However, these technologies are limited by human in the automation challenges, and new techniques are required that can scale to the accelerated pace of design cycles. This research explores the different types of design automation approaches on the aerospace industry and academia, looking for strengths to build upon and challenges to avoid or consider in the next generation of automation frameworks.

Generative AI is a novel technology currently under intense development, along with high level expectations on LLM applicability into Engineering Design - yet there is no clear best practice, nor a sound theory basis available to guide developers of new/improved design methodologies and practices. Its applications for design automation opens up a new paradigm that presents both challenges and opportunities to the engineering practice and the design engineering community. This research identifies such factors through the development of use cases in collaboration with industry. In addition, it proposes models to position their novelty with respect the existing aerospace ecosystem of designers and tools, clarifying the novel technology role and contribution to the design activities.