We are building a multi-faceted framework that incorporates Generative AI into multidisciplinary design. The goal is to introduce automation and traceability into complex design processes. Automation will allow for deeper design-space exploration while allowing human engineers to focus their efforts on less repetitive and potentially human-error-prone tasks.
Our recent work on generative design includes the creation of an Agentic-Based Aircraft Optimization Framework (Lee et al, 2025). This study utilized LLM to transform a design task formulated in common language into a structured script that could be run by OpenAeroStruct, a multidisciplinary wing design and optimization tool. The user inputs a wing design task with various requirements, and the LLM creates corresponding code for OpenAeroStruct to run and create an optimized wing. The LLM then creates a formal report based on the OpenAeroStruct output including optimization results and analysis.
Dillon Agrawal
Research Assistant
Dillon Agrawal is a senior pursuing a B.S.E. in Aerospace Engineering (minor in Computer Science) at the University of Michigan.
Conan Lee
Undergraduate Research Assistant
Conan Lee is a third-year undergraduate exchange student from the Hong Kong University of Science.
Triết Hồ
PhD student and Graduate Research Assistant
Triet is a PhD student in the Aerospace Engineering department at the University of Michigan.
