A MESOSCOPIC OXIDE FUEL CLUSTERING AND ITS GLOBAL PERFORMANCE

Obninsk Institute for Nuclear Power Engineering of the National Research Nuclear University MEPhI, Russia
Institut de Radioprotection et de Sûreté Nucléaire (IRSN), BP 17, 92262 Fontenay-aux-Roses Cedex, France

shaginian@iate.obninsk.ru
kolesov@iate.obninsk.ru
evgeny.ivanov@irsn.fr

Published online: 22 February 2021

Abstract

Transient fuel behavior in a Light Water-cooled Reactor core depends on nuclear properties (Doppler broadening, moderation ratio, and, sometimes, neutron gas temperature etc.) and on variations of thermal-physics parameters (temperature distributions, fuel elongation and moderator density).

Usually, in a rough reactor analysis one ignores the very details of temperature distributions largely staying in a frame of so-called adiabatic assumptions (when temperature and density distribution are changing in sync keeping given spatial shapes).

In majority of practical applications the radially distributed temperature fields are represented as monotonically smeared ones as if fissile and other materials are homogeneously mixed.

Moreover, no one measurement technique allows counting precise correlation between reactivity feedback and in-pellet temperature and materials space-time distributions.

However, if fuel is made of Mixed Oxide Plutonium-Uranium compound the behavior of Light Water Reactor would be impacted by an appearance of Pu-rich agglomerates that could be large enough to change physical processes.

In such case the fuel reacts on power and temperature variations no more as a homogeneous but a heterogeneous media (on a mesoscopic scale, of course).

It leads to changes in a fission product distributions, a fission gas release and, even, to an appearance of multiple components in a Fuel Temperature Coefficient and in a Power Reactivity feedback.

These components would depend non-linearly on power, power rate and on some details of a heat transfer.

This paper is the only first step of a broad research program where we are estimating the relevant phenomena just by an order of magnitude.