Research and Prototyping Study of an LLM-Based Chatbot for Electromagnetic Simulations
This addresses the time-consuming setup of electromagnetic simulations for engineers or researchers, but it is incremental as it applies existing LLM methods to a new domain-specific workflow.
This work tackles the problem of reducing electromagnetic simulation setup time by developing an LLM-based chatbot that automatically generates and solves 2D finite element eddy current models, with case studies showing functional enhancements like custom post-processing and model summaries.
This work addresses the question of how generative artificial intelligence can be used to reduce the time required to set up electromagnetic simulation models. A chatbot based on a large language model is presented, enabling the automated generation of simulation models with various functional enhancements. A chatbot-driven workflow based on the large language model Google Gemini 2.0 Flash automatically generates and solves two-dimensional finite element eddy current models using Gmsh and GetDP. Python is used to coordinate and automate interactions between the workflow components. The study considers conductor geometries with circular cross-sections of variable position and number. Additionally, users can define custom post-processing routines and receive a concise summary of model information and simulation results. Each functional enhancement includes the corresponding architectural modifications and illustrative case studies.