Advances in Predictive Modeling of Nuclear Energy Systems

Dear Colleagues,

This Special Issue presents advances in predictive modeling and its applications to nuclear energy. Predictive modeling includes the following elements: (i) computation of model response sensitivities to model parameters; (ii) quantification of the uncertainties in model responses caused by uncertainties in the model parameters and by insufficient knowledge of the processes being modeled; (iii) developing “validation metrics” for quantifying the degree to which a model represents reality (“model validation”); (iv) integration (“assimilation”) of computational and experimental information for improving the model’s parameters (“model calibration”) and producing optimally predicted results with reduced predicted uncertainties. The applications of predictive modeling to nuclear energy includes sensitivity analysis and uncertainty quantification in reactor physics and thermal-hydraulics, reducing the uncertainties in reactor design margins, reprocessing, and waste disposal, non-proliferation and safeguards.

Prof. Dan Gabriel Cacuci
Guest Editors

Manuscript Submission Information

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