Modern Systems for Nuclear Fuel Storage and Monitoring: An Analysis of Technological Trends, Challenges, and Future Perspectives

Bogdan-Teodor Godea, Ana Gogorici, Daniela-Monica Iordache (), Adriana-Gabriela Șchiopu, Daniel-Constantin Anghel and Mariea Deaconu
Additional contact information
Bogdan-Teodor Godea: Faculty of Mechanics and Technology, National University of Science and Technology Politehnica Bucharest, 060042 Bucharest, Romania
Ana Gogorici: Faculty of Mechanics and Technology, National University of Science and Technology Politehnica Bucharest, 060042 Bucharest, Romania
Daniela-Monica Iordache: Faculty of Mechanics and Technology, National University of Science and Technology Politehnica Bucharest, 060042 Bucharest, Romania
Adriana-Gabriela Șchiopu: Faculty of Mechanics and Technology, National University of Science and Technology Politehnica Bucharest, 060042 Bucharest, Romania
Daniel-Constantin Anghel: Faculty of Mechanics and Technology, National University of Science and Technology Politehnica Bucharest, 060042 Bucharest, Romania
Mariea Deaconu: The Institute for Nuclear Research Pitești (Mioveni Branch)–RATEN ICN, 115400 Mioveni, Romania

Energies, 2025, vol. 18, issue 18, 1-24

Abstract: The storage and monitoring of nuclear fuel, whether spent or fresh, are key components of the nuclear energy life cycle, with significant implications for safety and sustainability. With the global focus on carbon neutrality, interest in advanced management solutions is rising. This paper provides a comprehensive analysis of modern technologies for the design, storage, and monitoring of nuclear fuel, highlighting current trends and future challenges. The study encompasses both spent and fresh nuclear fuel, with a focus on radiological safety, structural integrity, and digital monitoring. Data were organized into the following categories: storage types (wet/dry), monitored parameters, surveillance technologies (sensors, AI, IoT, and Digital Twin), simulation models, and emerging directions. A comparison between fresh and spent fuel shows a clear shift toward intelligent systems using non-invasive sensors, deep-learning algorithms, and decentralized architectures (e.g., blockchain-IoT). Despite progress, challenges remain, such as limited interoperability across system generations and insufficient experimental validation. This paper provides a solid foundation for researchers, suggesting future directions that include the full integration of AI in monitoring, broader numerical simulations for reliability, and the standardization of digital interfaces. These measures could significantly enhance the safety and efficiency of nuclear fuel storage systems.

Keywords: spent nuclear fuel storage; dry cask technology; digital twin; artificial intelligence; blockchain applications (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2025
References: Add references at CitEc
Citations:

Downloads: (external link)
https://www.mdpi.com/1996-1073/18/18/5030/pdf (application/pdf)
https://www.mdpi.com/1996-1073/18/18/5030/ (text/html)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:gam:jeners:v:18:y:2025:i:18:p:5030-:d:1754900

Access Statistics for this article

Energies is currently edited by Ms. Cassie Shen

More articles in Energies from MDPI
Bibliographic data for series maintained by MDPI Indexing Manager ().