Research and Prototyping Study of an LLM-Based Chatbot for Electromagnetic Simulations

TL;DR

This study develops a large language model-based chatbot that automates electromagnetic simulation model setup, execution, and analysis, significantly reducing manual effort and enabling customizable workflows.

Contribution

Introduces a novel LLM-based chatbot for automating electromagnetic simulation workflows with functional enhancements and architectural modifications.

Findings

Automates 2D finite element eddy current models generation and solving.

Enables user-defined post-processing routines and summaries.

Demonstrates efficiency improvements in electromagnetic simulation setup.

Abstract

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.