  We consider Global Sensitivity Analysis for Monte Carlo radiation transport
applications. GSA is usually combined with Uncertainty Quantification, where
the latter quantifies the variability of a model output in the presence of
uncertain inputs and the former attributes this variability to the inputs. The
additional noise inherent to MC RT solvers due to the finite number of particle
histories presents an additional challenge to GSA and UQ, which are
well-established for deterministic solvers. In this contribution, we apply
variance deconvolution to the Saltelli method to address MC RT solver noise
without having to over-resolve the MC RT simulation.
