Advances and Perspectives in Nuclear Thermal Hydraulics and Nuclear Safety
A special issue of Applied Sciences (ISSN 2076-3417). This special issue belongs to the section "Applied Thermal Engineering".
Deadline for manuscript submissions: 20 November 2026 | Viewed by 339
Special Issue Editors
Interests: CFD; turbulence; nuclear safety; atmospheric dispersion
Special Issues, Collections and Topics in MDPI journals
Interests: liquid metals; turbulence model for liquid metals; heat exchange; fission and fusion reactors; finite element method; optimal control theory
Special Issues, Collections and Topics in MDPI journals
Interests: control theory; fluid mechanics; numerical analysis; modeling and simulation; computational fluid dynamics; numerical simulation engineering; applied and computational mathematics; numerical modeling; CFD simulation; engineering thermodynamics
Special Issue Information
Dear Colleagues,
Significant advancements in nuclear thermal hydraulics and safety have been achieved in recent years by introducing novel computational techniques. These include methodologies such as Computational Fluid Dynamics (CFD), uncertainty quantification, and artificial intelligence.
CFD produces high-fidelity results that enhance the understanding of flow configuration and heat exchange, ultimately allowing for reduced safety margins. These capabilities have been integrated with state-of-the-art system thermal hydraulic codes to improve the prediction of system transients and accident scenarios.
Uncertainty quantification has become increasingly important for assessing the reliability of models and simulations. By accounting for uncertainties, engineers can better predict reactor behavior under various conditions, thereby improving safety and design robustness.
Artificial Intelligence (AI) has emerged as a powerful tool in nuclear thermal hydraulics, enhancing predictive capabilities and optimizing reactor operations and safety assessments. Machine learning algorithms analyze vast datasets to improve simulation accuracy and the efficiency of reactor simulation tools. AI-driven models can forecast potential issues before they arise, significantly boosting safety and operational reliability.
These advanced tools have been successfully integrated into studies of operational and developmental fission reactors, as well as in the design of novel next-generation fission and fusion reactor technologies.
Dr. Antonio Cervone
Prof. Dr. Sandro Manservisi
Dr. Giorgio Bornia
Guest Editors
Manuscript Submission Information
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Keywords
- CFD
- uncertainty quantification
- artificial intelligence
- system thermal hydraulics
- nuclear safety
- IV-gen nuclear reactors
- fusion reactors
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