AI for Interpreting Nuclear Power Plant Documents for Power Uprates

Conference · Mon Jul 07 00:00:00 EDT 2025

OSTI ID:3024448

Mapes, John Norman ^[1]; Giraud, Kellen McKay ^[1]; Wilcken, Brian M ^[1]; Al Rashdan, Ahmad Y ^[1]; De Queiroz, Marcio ^[1]

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1. Idaho National Laboratory

To reduce the cost and time needed for regulatory compliance, nuclear power plants (NPPs) can utilize artificial intelligence (AI) to assist in interpreting complex and voluminous documents that typically span thousands of pages. Usually, the process of interpreting a plant’s technical specifications (TSs) and associated documents is labor intensive. This study aims to understand what processes state-of-the-art large language models (LLMs) can automate and to identify the pitfalls associated with using LLMs to reduce human labor costs and time. This research uses a recent AI technology called retrieval augmented generation (RAG), which retrieves pages of information from TSs and associated documents to assist with NPP power uprates (cleared to produce more power). LLMs are integral to RAG because they create human-like responses based on the retrieved information, aiding in the interpretation and application processes. A baseline case demonstrates how LLMs can operate successfully for a power uprate application. Then five use cases show five types of potential failures: (1) RAG retrieving the incorrect information, (2) RAG misinterpreting the retrieved information, (3) RAG relying on knowledge not contained in the retrieved information, (4) RAG hallucinating, and (5) RAG refusing to answer. The results of the five use cases suggest that automating the human interpretation of TSs and associated documents with AI should be approached with caution. A subject-matter expert reviewed the AI outputs from the five use cases and concluded that an LLM can produce technical information that is needed to produce power uprate applications in certain instances.

• Research Organization: Idaho National Laboratory (INL), Idaho Falls, ID (United States)
• Sponsoring Organization: USDOE Office of Nuclear Energy (NE); USDOE Office of Nuclear Energy (NE)
• DOE Contract Number: AC07-05ID14517
• OSTI ID: 3024448
• Report Number(s): INL/CON-25-83082
• Resource Type: Conference proceedings
• Conference Information: 14th International Topical Meeting on Nuclear Plant Instrumentation, Control & Human-Machine Interface Technologies (NPIC&HMIT 2025), Chicago, IL, 06/15/2025 - 06/18/2025
• Country of Publication: United States
• Language: English

Related Subjects

21 - SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS
Generative AI Automation
NRC Regulatory Compliance
Nuclear Power Plant Power Uprate
Nuclear Power Plant Technical Specifications
Retrieval Augmented Generation