Neutron multiplication in random media: Reactivity and kinetics parameters. (January 2018)

• Record Type: Journal Article
• Authors: Larmier, Coline; Zoia, Andrea; Malvagi, Fausto; Dumonteil, Eric; Mazzolo, Alain
• Is Part Of: Annals of nuclear energy. Volume 111(2018)
• Page Start: 391
• Page End: 406
• Publication Date: 2018-01
• Subjects: Random media -- Monte Carlo -- Tripoli-4® -- Kinetics parameters -- Markov tessellations -- Poisson -- Voronoi; Nuclear energy -- Periodicals; Nuclear engineering -- Periodicals; 621.4805
• DOI: 10.1016/j.anucene.2017.09.006
• Languages: English
• ISSNs: 0306-4549

Abstract

Highlights: We use stochastic tessellations to model severe accidents with fuel degradation. We perform particle transport in various stochastic tessellation models. We compute the distribution of multiplication factor and kinetics parameters. Abstract: Eigenvalue problems for neutron transport in random geometries are key for many applications, ranging from reactor design to criticality safety. In this work we examine the behaviour of the reactivity and of the kinetics parameters (the effective delayed neutron fraction and the effective neutron generation time) for three-dimensional UOX and MOX assembly configurations where a portion of the fuel pins has been randomly fragmented by using various mixing statistics. For this purpose, we have selected stochastic tessellations of the Poisson, Voronoi and Box type, which provide convenient models for the random partitioning of space, and we have generated an ensemble of assembly realizations; for each geometry realization, criticality calculations have been performed by using the Monte Carlo code Tripoli-4 ®, developed at CEA. We have then examined the evolution of the ensemble-averaged observables of interest as a function of the average chord length of the random geometries, which is roughly proportional to the correlation length of the fuel fragmentation. The methodology proposed in this work is fairly general and could be applied, e.g., to the assessment of re-criticality probability following severe accidents.