AI-Based Preliminary Modeling for Failure Prediction of Reactor Protection System in Nuclear Power Plants

Hye Jo, Ho Lee, Ji Park, Man Gyun Na

2024

Abstract

Nuclear power plants (NPPs), which generate electricity through nuclear fission energy, are crucial for safe operation due to the potential risk of exposure to radioactive materials. NPPs contain a variety of safety systems, and this study aims to develop an artificial intelligence-based failure prediction model that can predict and prevent potential failures in advance by targeting the reactor protection system (RPS). Currently, failure data for RPS are being collected through a testbed, so we conducted preliminary modeling using open-source data due to insufficient data acquisition. The applied open-source data are the accelerated aging data of insulated gate bipolar transistors (IGBTs), and the remaining useful life of IGBT was predicted using long short-term memory and Monte Carlo dropout technology. Also, physical rules were applied to improve their prediction performance and their applicability was confirmed through performance evaluation. Through performance evaluation of the developed prediction models, we explored the optimal model and confirmed the applicability of the applied methodologies and technologies.

Paper Citation

in Harvard Style

Jo H., Lee H., Park J. and Gyun Na M. (2024). AI-Based Preliminary Modeling for Failure Prediction of Reactor Protection System in Nuclear Power Plants. In Proceedings of the 16th International Joint Conference on Computational Intelligence - Volume 1: NCTA; ISBN 978-989-758-721-4, SciTePress, pages 593-599. DOI: 10.5220/0013006000003837

in Bibtex Style

@conference{ncta24,
author={Hye Jo and Ho Lee and Ji Park and Man Gyun Na},
title={AI-Based Preliminary Modeling for Failure Prediction of Reactor Protection System in Nuclear Power Plants},
booktitle={Proceedings of the 16th International Joint Conference on Computational Intelligence - Volume 1: NCTA},
year={2024},
pages={593-599},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0013006000003837},
isbn={978-989-758-721-4},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 16th International Joint Conference on Computational Intelligence - Volume 1: NCTA
TI - AI-Based Preliminary Modeling for Failure Prediction of Reactor Protection System in Nuclear Power Plants
SN - 978-989-758-721-4
AU - Jo H.
AU - Lee H.
AU - Park J.
AU - Gyun Na M.
PY - 2024
SP - 593
EP - 599
DO - 10.5220/0013006000003837
PB - SciTePress