Machine Learning and Artificial Intelligence for Reactor Physics: III

Predicting the Asymptotic State of Reactor Transients Using Supervised Learning

H. Tohver (Univ. Tartu), R. de Oliveira (National Institute of Chemical Physics and Biophysics), J. Pata (National Institute of Chemical Physics and Biophysics), M. Jeltsov (National Institute of Chemical Physics and Biophysics)

Evolution of Fuel Cycle Reload Safety Analysis with Machine Learning -- Illustration on the Rod Ejection Accident

R. Spaggiari (Framatome), M. Segond (Framatome), L. Lefebvre (Framatome)

Using Physics-Informed Neural Networks to Solve a System of Coupled Nonlinear ODEs for a Reactivity Insertion Accident

Alexandra Akins (NCSU), Xu Wu (NCSU)

Improving the Predictivity of a Steam Generator Clogging Numerical Model by Global Sensitivity Analysis and Bayesian Calibration Techniques

L. Lefebvre (Framatome), M. Segond (Framatome), R. Spaggiari (Framatome), L. Le Gratiet (EDF), E. Deri (EDF), B. Iooss (EDF), G. Damblin (CEA)