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arXiv · 2410.09213

iFANnpp: Nuclear Power Plant Digital Twin for Robots and Autonomous Intelligence

Youndo Do·Marc Zebrowitz·Jackson Stahl·Fan Zhang
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Abstract

Robotics has gained attention in the nuclear industry due to its precision and ability to automate tasks. However, there is a critical need for advanced simulation and control methods to predict robot behavior and optimize plant performance, motivating the use of digital twins. Most existing digital twins do not offer a total design of a nuclear power plant. Moreover, they are designed for specific algorithms or tasks, making them unsuitable for broader research applications. In response, this work proposes a comprehensive nuclear power plant digital twin designed to improve real-time monitoring, operational efficiency, and predictive maintenance. A full nuclear power plant is modeled in Unreal Engine 5 and integrated with a high-fidelity Generic Pressurized Water Reactor Simulator to create a realistic model of a nuclear power plant and a real-time updated virtual environment. The virtual environment provides various features for researchers to easily test custom robot algorithms and frameworks.

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Youndo Do, Marc Zebrowitz, Jackson Stahl, Fan Zhang. 2024-10-11. iFANnpp: Nuclear Power Plant Digital Twin for Robots and Autonomous Intelligence. https://doi.org/10.1016/j.anucene.2025.111993

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