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2024 article
A comparative study on deep learning models for condition monitoring of advanced reactor piping systems
Sandhu, H. K., Bodda, S. S., Yan, E., Sabharwall, P., & Gupta, A. (2024, March 1). MECHANICAL SYSTEMS AND SIGNAL PROCESSING, Vol. 209.
2023 review
A Future with Machine Learning: Review of Condition Assessment of Structures and Mechanical Systems in Nuclear Facilities
[Review of ]. ENERGIES, 16(6).
2023 journal article
Condition Monitoring of Nuclear Equipment-Piping Systems Subjected to Normal Operating Loads Using Deep Neural Networks
JOURNAL OF PRESSURE VESSEL TECHNOLOGY-TRANSACTIONS OF THE ASME, 145(4).
2023 journal article
Post-hazard condition assessment of nuclear piping-equipment systems: Novel approach to feature extraction and deep learning
INTERNATIONAL JOURNAL OF PRESSURE VESSELS AND PIPING, 201.
2022 journal article
Computer-Vision-Based Vibration Tracking Using a Digital Camera: A Sparse-Optical-Flow-Based Target Tracking Method
SENSORS, 22(18).
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