A comparative study on deep learning models for condition monitoring of advanced reactor piping systems-Reference-Cited by-同舟云学术

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A comparative study on deep learning models for condition monitoring of advanced reactor piping systems

Published:2024-03 Issue: Volume:209 Page:111091
ISSN:0888-3270
Container-title:Mechanical Systems and Signal Processing
language:en
Short-container-title:Mechanical Systems and Signal Processing

Author:

Sandhu Harleen Kaur^ORCID,Bodda Saran Srikanth,Yan Erin,Sabharwall Piyush,Gupta Abhinav

Funder

U.S. Department of Energy

Advanced Research Projects Agency - Energy

NC State University Center for Nuclear Energy Facilities and Structures

North Carolina State University

Publisher

Elsevier BV

Reference51 articles.

1. Digital-twin-based improvements to diagnosis, prognosis, strategy assessment, and discrepancy checking in a nearly autonomous management and control system;Lin;Ann. Nucl. Energy,2022

2. Preference-based multi-robot planning for nuclear power plant online monitoring and diagnostics;Alan Hesu;Nucl. Sci. Eng.,2023

3. Artificial Intelligence Based Condition Monitoring of Nuclear Piping-Equipment Systems;Sandhu,2021

4. Autonomous control model for emergency operation of small modular reactor;Saeed;Ann. Nucl. Energy,2023

5. Engineering demonstration reactors: A stepping stone on the path to deployment of advanced nuclear energy in the United States;Brown;Energy,2022

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