Evaluation of AI-enabled Digital Documented Safety Analysis

The National Reactor Innovation Center (NRIC) is leading a transformative initiative to accelerate advanced reactor deployment by fundamentally reimagining how nuclear safety basis documentation is developed, reviewed, and maintained. Traditional Documented Safety Analysis (DSA) processes for DOE-authorized facilities rely on static, document-centric workflows that consume significant time and resources, exemplified by recent major licensing efforts requiring hundreds of thousands of staff hours and millions of pages of documentation review. These conventional approaches create barriers to the rapid, cost-effective deployment of advanced reactors that America's clean energy future demands. NRIC's DOE Authorization Digital Transformation Project addresses these challenges through an innovative framework that integrates artificial intelligence (AI), digital engineering, and systems-based data management into a cohesive digital ecosystem. This white paper presents NRIC's methodology for evaluating AI-enabled document generation capabilities within this broader digital infrastructure, using the Demonstration of Microreactor Experiments (DOME) facility as a pilot case study. The evaluation will assess an AI tool's ability to generate a Preliminary Documented Safety Analysis (PDSA) through progressive integration stages—from standalone document processing to full digital thread connectivity—while maintaining rigorous verification, validation, and regulatory acceptance standards. By establishing dynamic, traceable connections between design data and safety documentation, NRIC's approach has the potential to reduce both document development time and regulatory review cycles by as much as 50%, while simultaneously improving accuracy, consistency, and traceability. This initiative represents a critical step toward establishing reusable digital infrastructure that reactor developers can leverage to accelerate their path from concept to commercial operation, directly su. Authors: Sinha Roy, Sonali [Idaho National Laboratory] (ORCID:0009000034860285); Sandhu, Harleen Kaur [Idaho National Laboratory] (ORCID:0000000255951351); Petrovic, Angelica M [Idaho National Laboratory]; Suyderhoud, Peter Anton [Idaho National Laboratory] (ORCID:0009000957296520); Rymer, Jake [Idaho National Laboratory]. DOE Contract: AC07-05ID14517. Subjects: 22 - GENERAL STUDIES OF NUCLEAR REACTORS; 42 - ENGINEERING; 97 - MATHEMATICS AND COMPUTING; AI; Autonomous Design; Digital Engineering; Digital Thread; GenAI; Licensing; LLM; Nuclear; Permitting