Demonstration of combined reduced order model and deep neural network for emulation of a time-dependent reactor transient

In this paper, a Reduced-Order Model (ROM) was constructed to approximate nuclear reactor neutronic transient behaviour. The ROM was developed by first using the Principal-Component Analysis (PCA) to reduce the output space of the response of interest, i.e, the time-dependent reactor power. A Deep-Neural Network (DNN) is then employed to build a surrogate model that maps the model inputs, i.e, the kinetic data, to the reduced-order output. …