2023
DOI: 10.21203/rs.3.rs-2909509/v1
|View full text |Cite
Preprint
|
Sign up to set email alerts
|

A Fine Pore-preserved Deep Neural Network for Porosity Analytics of a High Burnup U-10Zr Metallic Fuel

Abstract: U-10 wt.% Zr (U-10Zr) metallic fuel is the leading candidate for next-generation sodium-cooled fast reactors. Porosity is one of the most important factors that impacts the performance of U-10Zr metallic fuel. The pores generated by the fission gas accumulation can lead to changes in thermal conductivity, fuel swelling, Fuel-Cladding Chemical Interaction (FCCI) and Fuel-Cladding Mechanical Interaction (FCMI). Therefore, it is crucial to accurately segment and analyze porosity to understand the U-10Zr fuel syst… Show more

Help me understand this report
View published versions

Search citation statements

Order By: Relevance

Paper Sections

Select...

Citation Types

0
0
0

Publication Types

Select...

Relationship

0
0

Authors

Journals

citations
Cited by 0 publications
references
References 35 publications
0
0
0
Order By: Relevance

No citations

Set email alert for when this publication receives citations?