bibtype J - Journal Article
ARLID 0618107
utime 20250324095527.5
mtime 20250317235959.9
DOI 10.1016/j.net.2025.103571
title (primary) (eng) Simulating nuclear fuel inspections: Enhancing reliability through synthetic data
specification
page_count 9 s.
media_type E
serial
ARLID cav_un_epca*0344765
ISSN 1738-5733
title Nuclear Engineering and Technology
volume_id 57
publisher
name Korean Nuclear Society
keyword Synthetic data
keyword Nuclear fuel inspection
keyword Visual inspection
keyword Fuel assembly inspection
keyword Photogrammetry
keyword Inspection algorithms
author (primary)
ARLID cav_un_auth*0446610
name1 Knotek
name2 Jaroslav
institution UTIA-B
full_dept (cz) Zpracování obrazové informace
full_dept (eng) Department of Image Processing
department (cz) ZOI
department (eng) ZOI
country CZ
share 80
fullinstit Ústav teorie informace a automatizace AV ČR, v. v. i.
author
ARLID cav_un_auth*0254045
name1 Blažek
name2 Jan
institution UTIA-B
full_dept (cz) Zpracování obrazové informace
full_dept Department of Image Processing
department (cz) ZOI
department ZOI
country CZ
share 10
garant S
fullinstit Ústav teorie informace a automatizace AV ČR, v. v. i.
author
ARLID cav_un_auth*0446609
name1 Kopeć
name2 M.
country CZ
source
url http://library.utia.cas.cz/separaty/2025/ZOI/knotek-0618107.pdf
source
url https://www.sciencedirect.com/science/article/pii/S1738573325001391
cas_special
project
project_id OP TAK
agency GA MPO
country CZ
ARLID cav_un_auth*0485131
project
project_id StrategieAV21/1
agency AV ČR
country CZ
ARLID cav_un_auth*0328930
abstract (eng) Visual inspection of nuclear fuel assemblies is critical for assessing fuel reliability and ensuring safe operation. However, the sensitivity of real inspection data, along with its inflexibility and high collection costs, limits its use for research and development (R&D) tasks. These challenges hinder the ability to test and validate new inspection methodologies, making innovation slow and expensive. To address these limitations, we propose the development of synthetic nuclear fuel datasets that simulate fuel assembly inspections. These data sets replicate various defects and degradations in fuel assemblies, providing a controlled environment for hypothesis testing, operator training, and the evaluation of automated inspection techniques. Unlike real-world data, synthetic data offers the advantage of known ground-truth parameters, allowing for rigorous testing and validation. This approach enables the continuous development of inspection technologies, regardless of hardware availability and operational outages in nuclear facilities. By reducing the reliance on costly real-world experiments, synthetic data offers a scalable and flexible solution for the advancement of nuclear fuel inspection methods.
result_subspec WOS
RIV IN
FORD0 20000
FORD1 20200
FORD2 20206
reportyear 2026
num_of_auth 3
inst_support RVO:67985556
permalink https://hdl.handle.net/11104/0365155
cooperation
ARLID cav_un_auth*0470336
name Centrum výzkumu Řež s.r.o., Hlavní 130, Řež, 25068 Husinec, Czech Republic
country CZ
confidential S
article_num 103571
mrcbT16-e NUCLEARSCIENCETECHNOLOGY
mrcbT16-j 0.522
mrcbT16-s 0.693
mrcbT16-D Q1
mrcbT16-E Q3
arlyear 2025
mrcbU02 J
mrcbU14 SCOPUS
mrcbU24 PUBMED
mrcbU34 WOS
mrcbU63 cav_un_epca*0344765 Nuclear Engineering and Technology 57 8 2025 1738-5733 1738-5733 Korean Nuclear Society