Simulating nuclear fuel inspections: Enhancing reliability through synthetic data

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F67985556%3A_____%2F25%3A00618107" target="_blank" >RIV/67985556:_____/25:00618107 - isvavai.cz</a>

Nalezeny alternativní kódy

RIV/26722445:_____/25:N0000093

Výsledek na webu

<a href="https://www.sciencedirect.com/science/article/pii/S1738573325001391" target="_blank" >https://www.sciencedirect.com/science/article/pii/S1738573325001391</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1016/j.net.2025.103571" target="_blank" >10.1016/j.net.2025.103571</a>

Jazyk výsledku

angličtina

Název v původním jazyce

Simulating nuclear fuel inspections: Enhancing reliability through synthetic data

Popis výsledku v původním jazyce

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.

Název v anglickém jazyce

Simulating nuclear fuel inspections: Enhancing reliability through synthetic data

Popis výsledku anglicky

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.

Druh

J_imp - Článek v periodiku v databázi Web of Science

CEP obor

—

OECD FORD obor

20206 - Computer hardware and architecture

Projekt

—

Návaznosti

I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace

Rok uplatnění

2025

Kód důvěrnosti údajů

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Název periodika

Nuclear Engineering and Technology

ISSN

1738-5733

e-ISSN

1738-5733

Svazek periodika

57

Číslo periodika v rámci svazku

8

Stát vydavatele periodika

KR - Korejská republika

Počet stran výsledku

9

Strana od-do

103571

Kód UT WoS článku

001467697500001

EID výsledku v databázi Scopus

2-s2.0-105000260002