Abstract
This micro-article introduces a method for integrating Large Language Models with geometry/mesh generation software and multiphysics solvers, aimed at streamlining physics-based simulations. Users provide simulation descriptions in natural language, which the language model processes for geometry/mesh generation and physical model definition. Initial results demonstrate the feasibility of this approach, suggesting a future where non-experts can conduct advanced multiphysics simulations by simply describing their needs in natural language, while the code autonomously handles complex tasks like geometry building, meshing, and setting boundary conditions.
Original language | English |
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Article number | 101721 |
Journal | Results in Engineering |
Volume | 21 |
Early online date | 30 Dec 2023 |
DOIs | |
Publication status | Published - 1 Mar 2024 |
Keywords
- Multiphysics software
- Physics-informed machine learning
- Computational fluid dynamics software
- Coupling large language models with Physics-based simulations
- Generative AI in engineering
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From Text to Tech notebooks
Alexiadis, A. (Creator), University of Birmingham, 8 Dec 2023
DOI: 10.25500/edata.bham.00001032
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