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arxiv: 2409.06122 · v1 · pith:PVHFMJEI · submitted 2024-09-10 · cs.AI · cs.SE

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
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Talita Perciano Syun'ichi Shiraiwa \'Alvaro S\'anchez Villar Greg Wallace John C. Wright
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classification cs.AI cs.SE
keywords genaicaseenergyfusionmodelsresultssurrogatesai-based
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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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