Case Study: Leveraging GenAI to Build AI-based Surrogates and Regressors for Modeling Radio Frequency Heating in Fusion Energy Science

E. Wes Bethel, Vianna Cramer, Alexander del Rio, Lothar Narins, Chris Pestano, Satvik Verma, Erick Arias, Nicola Bertelli, Talita Perciano, Syun'ichi Shiraiwa, Álvaro Sánchez Villar, Greg Wallace, John C. Wright
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Abstract

This work presents a detailed case study on using Generative AI (GenAI) to develop AI surrogates for simulation models in fusion energy research. The scope includes the methodology, implementation, and results of using GenAI to assist in model development and optimization, comparing these results with previous manually developed models.
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案例研究:利用 GenAI 构建基于人工智能的替代物和回归因子,为聚变能科学中的射频加热建模
这项工作介绍了在聚变能源研究中使用生成式人工智能(GenAI)为仿真模型开发人工智能代理的详细案例研究。研究范围包括使用 GenAI 协助模型开发和优化的方法、实施和结果,并将这些结果与之前人工开发的模型进行比较。
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