Semantic Segmentation of Micrographs for Nuclear Fuel Analysis and Degradation Quantification
Author:
Affiliation:
1. Department of Computer Science, The University of Texas at San Antonio (UTSA), San Antonio, TX, USA
2. Department of Physics and Astronomy, The University of Texas at San Antonio (UTSA), San Antonio, TX, USA
Funder
Department of Energy
U.S. Department of Energy Idaho National Laboratory (DOE INL) Nuclear Energy University Program
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Subject
General Engineering,General Materials Science,General Computer Science,Electrical and Electronic Engineering
Link
https://ieeexplore.ieee.org/ielam/6287639/10005208/10287929-aam.pdf
Reference30 articles.
1. Optimization of the TRISO fuel particle distribution based on octahedral and icosahedral-based segmentation methods in the pebble-bed nuclear core
2. Bringing nuclear materials discovery and qualification into the 21st century
3. Fault diagnosis of manufacturing systems using data mining techniques
4. A LSTM-RNN method for the lithuim-ion battery remaining useful life prediction
5. Characterization of radiation damage in 3D printed SiC
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