Large Language Models (LLM) for Automated Finite Element Analysis

This is a Self-Funded project - please only apply if you have funding to undertake this project

Large Language Models such as Chat GPT3 represent a significant development in artificial intelligence and its impact on society. Trained on a huge amount of data and able to a generate useful responses to complex and multi-layered questions, it is potentially the most useful tool available for handling structural engineering tasks. However, it's results are not always completely accurate and sometimes completely incorrect, though delivered with authority.

This project will develop a computational interface to a leading LLM (such as the latest Chat GPT) through its API to assess the capability of the model to develop finite element models, run them and summarise results in a manner similar to a human analyst.

The research will aim to identify the following:

1. The limits of the models understanding of structural engineering concepts through its ability to answer complex technical questions correctly.
2. The use of the LLM for automating the development of finite element models for a range of analyses such as stress, heat and modal response. The models will be developed to solve specific questions and may include complex and nonlinear physics.
3. Integration of methods such as Monte Carlo simulation for assessing the uncertainty in the analyses.
4. Generation of automated technical reports that summarise the results of the analyses in a human readable format, including relevant screenshots, technical descriptions, motivation and diagrams and suggest follow on analyses where necessary. A wide range of automated tests such as unit testing, integration testing, functional testing and acceptance testing will need to be developed to determine the LLM's ability as a design assistant.

The output of the research will be a computational interface to a LLM which can operate as a structural engineering design assistant to automatically develop comprehensive finite element models that solve complex engineering challenges and summarise the outputs in the form of technical reports.

This project will require familiarity with programming languages such as Java, C++, Python or similar as well as an understanding of structural engineering design.

The successful applicant will join the Centre for AI: Social and Digital Innovation, which has more than 15 PhD researchers working in the field of computer vision, robotics, drones and includes a newly fitted artificial intelligence and robotics lab.

Brunel offers a number of funding options to research students that help cover the cost of their tuition fees, contribute to living expenses or both. See more information here: https://www.brunel.ac.uk/research/Research-degrees/Research-degree-funding. The UK Government is also offering Doctoral Student Loans for eligible students, and there is some funding available through the Research Councils. Many of our international students benefit from funding provided by their governments or employers. Brunel alumni enjoy tuition fee discounts of 15%.