arXiv Open Access 2024

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

Youndo Do Marc Zebrowitz Jackson Stahl Fan Zhang
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Abstrak

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.

Topik & Kata Kunci

Penulis (4)

Y

Youndo Do

M

Marc Zebrowitz

J

Jackson Stahl

F

Fan Zhang

Format Sitasi

Do, Y., Zebrowitz, M., Stahl, J., Zhang, F. (2024). iFANnpp: Nuclear Power Plant Digital Twin for Robots and Autonomous Intelligence. https://arxiv.org/abs/2410.09213

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2024
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en
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arXiv
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