Propagation of uncertainties in basic nuclear reaction data to uncertainties in the parameters of primary radiation damage by neutrons

The primary radiation damage formation in materials subjected to neutron radiation is very sensitive to the energy spectra of primary knock-on atoms (PKAs) and their collision cascade in the crystal lattice. The estimated values of the primary radiation damage metrics, such as displacements per atom (dpa) cross sections, integrated dpa, PKA spectrum and spectrum averaged PKA energy are uncertain because of uncertainties present in both the basic nuclear reaction data and the displacement damage model parameters. The Total Monte Carlo (TMC) methodology, which uses the random evaluated nuclear data files for nuclides, is well recognized to propagate the uncertainties in basic nuclear data to the derived quantities in nuclear reactor physics. The uncertainties in the above mentioned primary radiation damage parameters are obtained in this study by propagating the uncertainties in basic evaluated nuclear data, following the TMC methodology. The knowledge of uncertainties in the spectrum averaged PKA energies also enables us to ascertain the uncertainties in the production of vacancies through self-ion simulations using SRIM-2013 code. The present study is an outcome of our systematic approach towards establishing the procedure. This includes pre-processing a large number of TENDL nuclear data random files using NJOY-2016, developing an indigenous code CRaD for handling these point and multigroup data libraries and computing primary radiation damage metrics and their associated uncertainties including energy-energy and nuclear reaction channel-channel correlation matrices. The uncertainties in dpa cross sections and PKA spectra due to uncertainties in basic nuclear data are found to be comparatively larger than the uncertainties in respective integrated parameters; viz. dpa and average PKA energy. This study also confirms the non-Gaussian distributions of derived primary radiation damage parameters.