构建可实时更新的核电站数字孪生，支持机器人算法测试与运维优化。
iFANnpp: Nuclear Power Plant Digital Twin for Robots and Autonomous Intelligence
- 基于UE5与压水堆仿真器构建全厂级数字孪生。
- 实现核电站实时虚拟环境，支持机器人行为预测与维护优化。
- 专为研究者设计，适配自定义机器人算法测试场景。
机器人在核工业中因其高精度和自动化能力受到关注。然而，亟需先进的仿真与控制方法来预测机器人行为并优化电站性能，这推动了数字孪生的应用。现有数字孪生大多未涵盖完整核电站设计，且仅针对特定算法或任务，难以用于广泛研究。为此，本文提出一个全面的核电站数字孪生系统，旨在提升实时监控、运行效率与预测性维护能力。整个核电站模型在Unreal Engine 5中构建，并集成高保真通用压水堆仿真器，形成真实感强、可实时更新的虚拟环境。该环境为研究人员提供多种功能，便于测试自定义机器人算法与框架。
原文摘要 · Abstract (English)
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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