While several papers in the literature have demonstrated uncertainty propagation for radiation damage calculations, it is not a straightforward process and requires significant expertise and specialized access to data in order to carry out. In this task, we will incorporate functionality in OpenMC for randomly sampling radiation damage model parameters based on their underlying uncertainties in order to provide propagated uncertainties on resulting damage energy and dpa estimates.
While several papers in the literature have demonstrated uncertainty propagation for radiation damage calculations, it is not a straightforward process and requires significant expertise and specialized access to data in order to carry out. In this task, we will incorporate functionality in OpenMC for randomly sampling radiation damage model parameters based on their underlying uncertainties in order to provide propagated uncertainties on resulting damage energy and dpa estimates.