RAYLEIGH QUOTIENT ITERATION IN 3D, DETERMINISTIC NEUTRON TRANSPORT

TL;DRAbstract

Today’s “grand challenge” neutron transport problems require 3-D meshes with billions of cells,<br>hundreds of energy groups, and accurate quadratures and scattering expansions. Leadership-class<br>computers provide platforms on which high-fidelity fluxes can be calculated. However, appropriate<br>methods are needed that can use these machines effectively. Such methods must be able to to use<br>hundreds of thousands of cores and have good convergence properties. Taking advantage of the<br>multigroup Krylov solver that scales to hundreds of thousands of cores, Rayleigh quotient iteration<br>(RQI) is an eigenvalue solver that has been added to the S N code Denovo to address convergence.<br>Rayleigh quotient iteration is an optimal shifted inverse iteration method. RQI should converge in<br>fewer iterations than the more common power method and other shifted inverse iteration methods<br>for many problems of interest. Denovo’s RQI uses a new multigroup Krylov solver for the fixed<br>source

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