AI-Augmented Design

Sat, 18 Oct 2025 00:00:00 +0000

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.

Multi-agent LLM framework for OpenAeroStruct.

Full workflow illustrating subprocesses and information transfer.

LLM | IDEAS Lab at University of Michigan

AI-Augmented Design