Development of a multi-zone fuel loading model for scenario studies involving ASTRID-like SFRs with the CLASS code

Many scenario studies conducted by several countries consider the progressive deployment of low void effect Sodium-cooled Fast Reactor (SFR) [1]. Different options are investigated regarding the deployment time of this kind of Generation IV reactor, depending on the global nuclear energy development and the national energy mix strategies. In France, the SFR core design often used in this type of scenario is based on the 600 MWe ASTRID concept developed by the CEA and its industrial partners [2]. To reach a negative void coefficient, the core is divided in two radial parts: an inner and an outer core, which alternate different fertile and fissile zones.One challenge to simulate fuel cycle with fuel reprocessing is to consider the evolution of the materi-als to be recycled over time. Indeed, spent fuel compositions vary at each reprocessing as it de-pends of each fuel history (in which reactor it has been irradiated, burn-up achieved, cooling time…). Hence, to build a fresh fuel adapted to one reactor specificities, the CLASS (Core Library for Ad-vanced Scenario Simulation) software [3], a dynamic fuel cycle simulation code developed by CNRS in collaboration with IRSN, uses dedicated fuel loading models. In the case of this SFR, the aim is to keep the fuel heterogeneity of the core. To do that, the devel-opment of a new dedicated fresh fuel loading model taking into account the different fuel zones of the reactor was needed. This model is based on the reactor's neutron characteristics and it is usable for a wide variability of spent fuels to be recycled. In this way, for a given isotopic composition, the Pu contents of both the inner and the outer core are iteratively adjusted to reach a target power distri-bution in the core and a target multiplication factor (keff) at the beginning of cycle. An analysis of this SFR behavior during irradiation shows a relation between the power distribution and the ratio of Pu contents, between the inner and outer core. This relation is used by the model to calculate the initial Pu contents for a given isotopic composition assuring the target power distribu-tion. Then, to determine the keff associated to that specific fresh fuel composition, the model uses Artificial Neural Network (ANN) trained on a corresponding databank. This databank is composed of 1000 full core depletion Monte Carlo simulations generated with the VESTA code [4], in which MCNP is used as the transport solver. Each calculation differs from the other by the initial fresh fuel sam-pled in the parameter space of compositions covering many potential SFR fuel management strate-gies. This new model completes the implementation of a previous multi-zone fuel irradiation model devel-oped for this SFR [5]. Thanks to these two multi-zone models, the simulation of scenarios integrating multi-zone SFR with the code CLASS shows that the plutonium breeder, break-even or burner SFR property is highly dependent on its fresh fuel composition

Editorial: Fuel Cycle Simulation TWoFCS 2021

International audienc

Development of a multi-zone fuel loading model for scenario studies involving ASTRID-like SFRs with the CLASS code

Many scenario studies conducted by several countries consider the progressive deployment of low void effect Sodium-cooled Fast Reactor (SFR) [1]. Different options are investigated regarding the deployment time of this kind of Generation IV reactor, depending on the global nuclear energy development and the national energy mix strategies. In France, the SFR core design often used in this type of scenario is based on the 600 MWe ASTRID concept developed by the CEA and its industrial partners [2]. To reach a negative void coefficient, the core is divided in two radial parts: an inner and an outer core, which alternate different fertile and fissile zones.One challenge to simulate fuel cycle with fuel reprocessing is to consider the evolution of the materi-als to be recycled over time. Indeed, spent fuel compositions vary at each reprocessing as it de-pends of each fuel history (in which reactor it has been irradiated, burn-up achieved, cooling time…). Hence, to build a fresh fuel adapted to one reactor specificities, the CLASS (Core Library for Ad-vanced Scenario Simulation) software [3], a dynamic fuel cycle simulation code developed by CNRS in collaboration with IRSN, uses dedicated fuel loading models. In the case of this SFR, the aim is to keep the fuel heterogeneity of the core. To do that, the devel-opment of a new dedicated fresh fuel loading model taking into account the different fuel zones of the reactor was needed. This model is based on the reactor's neutron characteristics and it is usable for a wide variability of spent fuels to be recycled. In this way, for a given isotopic composition, the Pu contents of both the inner and the outer core are iteratively adjusted to reach a target power distri-bution in the core and a target multiplication factor (keff) at the beginning of cycle. An analysis of this SFR behavior during irradiation shows a relation between the power distribution and the ratio of Pu contents, between the inner and outer core. This relation is used by the model to calculate the initial Pu contents for a given isotopic composition assuring the target power distribu-tion. Then, to determine the keff associated to that specific fresh fuel composition, the model uses Artificial Neural Network (ANN) trained on a corresponding databank. This databank is composed of 1000 full core depletion Monte Carlo simulations generated with the VESTA code [4], in which MCNP is used as the transport solver. Each calculation differs from the other by the initial fresh fuel sam-pled in the parameter space of compositions covering many potential SFR fuel management strate-gies. This new model completes the implementation of a previous multi-zone fuel irradiation model devel-oped for this SFR [5]. Thanks to these two multi-zone models, the simulation of scenarios integrating multi-zone SFR with the code CLASS shows that the plutonium breeder, break-even or burner SFR property is highly dependent on its fresh fuel composition

Estimation of the vitrified canister production for a PWR fleet with the CLASS code

This article presents an assessment of fuel cycle parameter impact on waste production through the prism of vitrified container and minor actinide masses, using a scenario simulated with the CLASS code. The number of canister introduces a new focus on waste production estimation for a nuclear fleet, as it helps to set the repository size for deep geological disposal of high level waste. To evaluate the number of canisters, dedicated developments to model a simplified waste vitrification unit in the CLASS package are presented. It relies on artificial neural network estimations of decay heat, α radiation and mass content, for different material flow coming from reprocessing and sent to vitrification. Then, the studied scenario considers a transition from a PWRs plutonium mono-recycling fleet to a plutonium multi-recycling fleet. Vitrified waste container production is calculated as a function of different material reprocessing options. Simulations shows that up to 19% variation may be observed (in 2060) in canisters’ total number depending on the different assumptions. Impact of vitrification parameters such as the size of buffer before vitrification is also analysed and the importance of mixing material coming from MOX and MIX spent fuels with material from UOX spent fuels is clearly established

Robustness Study of Electro-Nuclear Scenario under Disruption

As the future of nuclear power is uncertain, only choosing one development objective for the coming decades can be risky; while trying to achieve several possible objectives at the same time may lead to a deadlock due to contradiction among them. In this work, we study a simple scenario to illustrate the newly developed method of robustness study, which considers possible change of objectives. Starting from the current French fleet, two objectives are considered regarding the possible political choices for the future of nuclear power: A. Complete substitution of Pressurized Water Reactors by Sodium-cooled Fast Reactors in 2180; B. Minimization of all potential nuclear wastes without SFR deployment in 2180. To study the robustness of strategies, the disruption of objective is considered: the objective to be pursued is possibly changed abruptly from A into B at unknown time. To minimize the consequence of such uncertainty, the first option is to identify a robust static strategy, which shows the best performance for both objectives A and B in the predisruption situation. The second option is to adapt a trajectory which pursues initially objective A, for objective B in case of the disruption. To identify and to analyze the adaptively robust strategies, outcomes of possible adaptations upon a given trajectory are compared with the robust static optimum. The temporality of adaptive robustness is analyzed by investigating different adaptation times

Analysis of transition scenario from a PWR to a SFR fleet simulated with the class code

International audienceOne evolution envisaged in France for electronuclear fleets considers the deployment of ASTRID-like Sodium Fast Reactor (SFR). Fuel cycle prospective studies involving this SFR integrated into a Pressurized Water Reactor (PWR) fleet is one way to evaluate such strategies. This paper presents two scenario analysis exploring effects on in-cycle plutonium quantity and quality of ASTRID-like reactor parameters and cycle parameters such as SFR spent fuel reprocessing. On one hand, under specific conditions, cycle strategies impact ASTRID-like behavior, however, on the other hand, the fuel cycle is also strongly dependent on ASTRID-like operation

Analysis of transition scenario from a PWR to a SFR fleet simulated with the class code

International audienceOne evolution envisaged in France for electronuclear fleets considers the deployment of ASTRID-like Sodium Fast Reactor (SFR). Fuel cycle prospective studies involving this SFR integrated into a Pressurized Water Reactor (PWR) fleet is one way to evaluate such strategies. This paper presents two scenario analysis exploring effects on in-cycle plutonium quantity and quality of ASTRID-like reactor parameters and cycle parameters such as SFR spent fuel reprocessing. On one hand, under specific conditions, cycle strategies impact ASTRID-like behavior, however, on the other hand, the fuel cycle is also strongly dependent on ASTRID-like operation