Monte Carlo Power Iteration Algorithms: Convergence, Analysis and Application to Reactor Criticality Calculations
Alexander M. G. Cox, Tom Davis, Julian Hofstadler, Andreas E. Kyprianou
Source abstract
We study Monte Carlo power iteration algorithms in the context of reactor criticality simulations. Under mild conditions on the underlying physical system and the algorithmic structure, we derive explicit error bounds, which are to the best of our knowledge the first rigorous results for such methods which are ubiquitous in nuclear engineering. This is done by exploiting connections to Sequential Monte Carlo algorithms, and extending recent developments about stochastic neutron transport. We demonstrate the applicability of our results by considering a concrete version of the Monte Carlo power iteration algorithm as well as variance reduction schemes.
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