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.

翻译：本研究探讨了如何利用生成式人工智能减少电磁仿真模型建立所需时间。提出了一种基于大型语言模型的聊天机器人，能够自动生成具备多种功能增强的仿真模型。基于Google Gemini 2.0 Flash大型语言模型的聊天机器人驱动工作流，可自动生成并利用Gmsh与GetDP求解二维有限元涡流模型。Python用于协调并自动化工作流各组件间的交互。研究考虑了具有可变位置和数量的圆形截面导体几何结构。此外，用户可自定义后处理程序，并获得模型信息与仿真结果的简明摘要。每项功能增强均包含相应的架构修改说明及示例案例研究。