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Licensed Unlicensed Requires Authentication Published by De Gruyter April 14, 2022

Safety analysis for integrity enhancement in nuclear power plants (NPPs) in case of seashore region site

  • Tae Ho Woo EMAIL logo , Chang Hyun Baek and Kyung Bae Jang
From the journal Kerntechnik


It is investigated for the seismic consequences in the nuclear power plant (NPP) where the radiological hazard could be one of critical issues when the safety system is in failure. The artificial learning is done during the calculations of each time step. There are the simulations for the artificial neural networking (ANN) as the precision, sensitivity (recall value), specificity, and accuracy which are 21.48%, 50.53%, 25.47%, and 32.68% respectively. Likewise, the recurrent neural network (RNN) modeling has 23.64%, 54.53%, 25.56%, and 34.17% respectively. In the comparisons for ANN and RNN, the values of ANN’s parameters are lower than those of RNN in all values of precision, recall, specificity, and accuracy. As the designed factors for the nuclear matters increase, the estimations could be better in considering the conditional situations.

Corresponding author: Tae Ho Woo, Department of Mechanical and Control Engineering, The Cyber University of Korea, 106 Bukchon-ro, Jongno-gu, Seoul 03051, Republic of Korea, E-mail:

Funding source: The Cyber University of Korea

  1. Author contributions: All the authors have accepted responsibility for the entire content of this submitted manuscript and approved submission.

  2. Research funding: This study was supported by a grant of the Cyber University of Korea.

  3. Conflict of interest statement: The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.


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Received: 2022-02-09
Published Online: 2022-04-14
Published in Print: 2022-06-27

© 2022 Walter de Gruyter GmbH, Berlin/Boston

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