LAUSR

Abstract An unfolding method based on sparse representation is proposed and applied to unfolding problem of multiple activation foils measurement. The Online Dictionary Learning (ODL) algorithm is applied for sparse representation. The algorithm LARS-EN is used for reconstruction. The Akaike’s Information Criterion (AIC) is applied to select the best coefficient path. Nuclear reactor of Qinshan phase II nuclear power plant (NPP) is considered as the study object and training samples are generated by Monte Carlo code MCNP. By using the unfolding method proposed in this paper, two sets of neutron spectrums are unfolded successfully with acceptable accuracies. The first set contains 4 neutron spectrums of different shapes; and the second set contains 4 neutron spectrums at different positions of the radiation surveillance capsule. Moreover, neutron spectrums of the radiation surveillance capsule can also be unfolded with acceptable accuracies with fewer equations while the two fission detectors 238U and 237Np are removed.