Over the last decade, the importance of the Monte Carlo as a neutron transport calculation method has greatly increased. This paper describes a Monte Carlo particle transport framework SCONE, which aims to provide with easy-to-learn environment for graduate students to learn about Monte Carlo methods and explore new ideas. The paper lists the steps taken to enhance new user experience of SCONE and briefly discuses how the architecture supports its goals. The current version of the code is compared against Serpent and shown to provide with sufficient accuracy to be used for teaching and proof-of-concept applications.

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This paper investigates mixing multi-group (MG) and continuous energy (CE) representation of cross-sections depending on location of a particle in a Monte Carlo neutronic eigenvalue calculations in 1D and 2D PWR test cases with UOX and MOX fuel. Different population normalisation needs to be applied to CE and MG region to account for the difference in criticality between CE and MG representation. This normalisation procedure requires a neutron production rate ratio between CE and MG region to be known a priori. A resonance correction in energy spectrum during transition of a particle between the MG and CE region was developed based on the equivalence resonance treatment theory. With these, it was shown that it is possible to accelerate total calculation time, while introducing only a moderate error below 1% in the fission rate distribution. The magnitude of acceleration is heavily dependent on the relative size of CE and MG zones.

Neutron clustering is a recently identified problem with Monte Carlo eigenvalue calculations which can produce significantly erroneous results. Previous work by Sutton & Mittal (2017) considered neutron clustering as a problem of maintaining ‘genetic diversity’ within the neutron population. This paper proposes reducing the extent of neutron clustering by replacing fission neutrons in the source bank with uncorrelated neutrons, sampled from a uniform source distribution – effectively adding new neutron genealogies to the population. The efficacy of the method is demonstrated on a number of simple problems, showing improved behaviour of the Shannon entropy and neutron centre-of-mass. Although currently limited in scope, this paper intends to provide a route to reducing clustering effects in more general problems.

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