4 papers
AutoSAM: an Agentic Framework for Automating Input File Generation for the SAM Code with Multi-Modal Retrieval-Augmented Generation
Zaid Abulawi, Zavier Ndum Ndum, Eric Cervi +2
In the design and safety analysis of advanced reactor systems, constructing input files for system-level thermal-hydraulics codes such as the System Analysis Module (SAM) remains a…
RADIANT-LLM: an Agentic Retrieval Augmented Generation Framework for Reliable Decision Support in Safety-Critical Nuclear Engineering
Zavier Ndum Ndum, Jian Tao, John Ford +2
Reliable decision support in nuclear engineering requires traceable, domain-grounded knowledge retrieval, yet safety and risk analysis workflows remain hampered by fragmented docum…
An AI-Driven Thermal-Fluid Testbed for Advanced Small Modular Reactors: Integration of Digital Twin and Large Language Models
Doyeong Lim, Yang Liu, Zavier Ndum Ndum +2
This paper presents a multipurpose artificial intelligence (AI)-driven thermal-fluid testbed designed to advance Small Modular Reactor technologies by seamlessly integrating physic…
AutoFLUKA: A Large Language Model Based Framework for Automating Monte Carlo Simulations in FLUKA
Zavier Ndum Ndum, Jian Tao, John Ford +1
Monte Carlo (MC) simulations, particularly using FLUKA, are essential for replicating real-world scenarios across scientific and engineering fields. Despite the robustness and vers…