Since 2012, CLASS is developed CNRS/IN2P3 (Centre National de la Recherche Scientifique / Institut National de Physique Nucléaire et de Physique des Particules) with initial support from IRSN (Institut de Radioprotection et de Sûreté Nucléaire). It is a package with libraries written in C++, in which the instances of facilities and other physics models can be created and plugged together to simulate different fuel cycle transitions. The facilities to be simulated include fabrication plant, enrichment plant, reactor, cooling pool, separation plant and interim storage.

Mass flow management in CLASS

A specific module, called time vector in CLASS, is dedicated to the automatic creation of the time schedule as well as the designation of material transportation.

The progression of simulations is driven by this time vector. First, the time of fresh fuels loading and spent fuels discharge can be deduced from the start time of reactors and the time of each irradiation cycle. The times of fresh fuel transportation can then be decided by considering the time of fresh fuel loading and the time of fabrication; the times that move spent fuels from the pools to interim storage can be decided by considering the time of discharge and the time of cooling. With iteration, the time vector can be pre-built to manage the mass flows in simulation.

One should note that any modification of operational parameters for a reactor, e.g. the power level and the burn-up of fuels, respects the irradiation cycle. In other words, if the parameters of a reactor need to be modified when the fuel depletion is not yet finished, the modifications will only be applied at the start of next irradiation phase. This hypothesis makes sense in reality, but it also desynchronizes some timing of interest. In the analyses of subsequent chapters, this desynchronization will be frequently highlighted when the results of robustness assessment are interpreted.

Physics modeling in CLASS

The simplest method to consider fuel loading and depletion calculation in scenario study is the use of recipes. This method uses one or several representative fuel evolutions that have been pre-calculated by reactor simulations. Each depletion in the scenario is then only a re-normalization of the recipe to match the installed capacity of reactors. This method does not need complex calculations of depletion or criticality verification during the scenario simulation, and thus the simulation can be very fast. Nonetheless, the number of recipes is usually limited and cannot be sufficiently representative when the variability of fuel cycle parameters or recycled plutonium isotopy is relatively.

In CLASS, the physics modeling of irradiation consists of two parts: the Fuel Loading Model, and the irradiation model which includes a cross-section model and a solver of Bateman equations. Once the time-dependent cross-sections are known, the Bateman equations are solved by the Runge-Kutta fourth-order method. The prediction of fresh fuels is far more complex, and CLASS uses artificial neural network in order to achieve reasonable computational cost with acceptable precision.