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Nuclear Technology

For a Special Issue on

Advancements in Uncertainty and Sensitivity Analyses: Current Status and Prospective

Manuscript deadline
16 March 2025

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Special Issue Editor(s)

Fulvio Mascari, National Agency for New Technologies, Energy and Sustainable Economic Development (ENEA)
[email protected]

Fabrizio Gabrielli, Karlsruhe Institute of Technology (KIT)
[email protected]

David Luxat, Sandia National Laboratories (SNL)
[email protected]

Luis Enrique Herranz, Centro de Investigaciones Energéticas, Medioambientales y Tecnológicas (CIEMAT)
[email protected]

Tatjana Jevremovic, [email protected]

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Advancements in Uncertainty and Sensitivity Analyses: Current Status and Prospective

The Best-Estimate Plus Uncertainty (BEPU) methodology is internationally recognized in the assessment of safety margins for deterministic safety analyses. It has increasingly been adopted by the international nuclear safety community to characterize safety margins and remove analysis conservatisms. Several initiatives to realistically characterize Design Basis Accident (DBA) safety margin have been performed. More recently, the application of the BEPU methodology to deterministic and source term analysis for Severe Accidents (SA) is in progress and several research activities in national and international frameworks are currently in progress extending BEPU application to revolutionizing the assessment of SAs. The challenges of assessing complex and long accident progression issues (DBA and extension to SA) has motivated the application of novel methods utilizing artificial intelligence, machine learning, surrogate modeling and pattern recognition methods/algorithms to provide a novel and innovative gateway for computationally affordable and accurate methodologies for uncertainty quantification and sensitivity analysis.  The ambition of this special issue is to collect the main outcomes of the current key research activities developed in different initiatives about uncertainty application in deterministic safety analyses, providing the current state-of-art and identifying research gaps and needs.