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

Fuente: arXiv
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Main Authors: Piwonski, Albert, Hadžiefendić, Mirsad
Format: Preprint
Published: 2025
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author Piwonski, Albert
Hadžiefendić, Mirsad
author_facet Piwonski, Albert
Hadžiefendić, Mirsad
contents 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.
format Preprint
id arxiv_https___arxiv_org_abs_2511_17680
institution arXiv
publishDate 2025
record_format arxiv
spellingShingle Research and Prototyping Study of an LLM-Based Chatbot for Electromagnetic Simulations
Piwonski, Albert
Hadžiefendić, Mirsad
Computational Engineering, Finance, and Science
Artificial Intelligence
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.
title Research and Prototyping Study of an LLM-Based Chatbot for Electromagnetic Simulations
topic Computational Engineering, Finance, and Science
Artificial Intelligence
url https://arxiv.org/abs/2511.17680