Data assimilation and application in radiation physics and shielding

1. Develop and test new, efficient sensitivity techniques in SCONE on high-fidelity problems, demonstrating their speed-up over naïve approaches.
2. Apply this sensitivity analysis to a representative problem of interest for Rolls Royce. This may include obtaining sensitivities to material boundaries, for which some work has been performed in the eigenvalue context [3].
3. Combine the obtained sensitivities with experimental measurements in a data assimilation framework in order to minimise uncertainties or calibrate uncertain model inputs.
4. Generate higher-order sensitivities for the problems of interest, allowing use of more sophisticated data assimilation approaches where, e.g., the covariance of the model inputs is
known. This allows for relaxing the assumption that the response distribution is Gaussian in the input parameters and better characterising the true distribution.
5. Explore accelerated weight-window generating through hybrid multi-group and continuous energy calculations.