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

TL;DR

This paper introduces a comprehensive digital twin of a nuclear power plant using Unreal Engine 5 and a high-fidelity simulator, enabling advanced testing, monitoring, and predictive maintenance for robotics in nuclear industry.

Contribution

It presents a novel, full-scale digital twin of a nuclear power plant that supports broad research and real-time testing of robotic algorithms and operational strategies.

Findings

Realistic virtual environment for nuclear plant simulation

Supports testing of custom robot algorithms

Enhances real-time monitoring and predictive maintenance

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.