A methodology for performing sensitivity analysis in dynamic fuel cycle simulation studies applied to a PWR fleet simulated with the CLASS tool

Abstract

Fuel cycle simulators are used worldwide to provide scientific assessment to fuel cycle future strategies. Those tools help understanding the fuel cycle physics and determining the most impacting drivers at the cycle scale. A standard scenario calculation is usually based on a set of operational assumptions, such as reactor Burn-Up, deployment history, cooling time, etc. Scenario output is then the evolution of isotopes mass in the facilities that composes the nuclear fleet. The increase of computing capacities and the use of neutron data fast predictors provide new opportunities in nuclear scenario studies. Indeed, a very high number of calculations is possible, which allows testing a high number of operational assumptions combinations. The global sensitivity analysis (GSA) formalism is specifically well adapted for this kind of problem. In this new framework, a scenario study is based on the sampling of operational data, which become input variables. A first result of a scenario study is the highlight of relations between operational input data and outputs. Input variable subspace that satisfy optimization criteria on an output, such as plutonium incineration or stabilization, can also be determined. In this paper, a focus is made on the methodology based on GSA. This innovative methodology is presented and applied to a simple fleet simulation composed of a PWR-UOx fuel and a PWR-MOx fuel. Calculations are done with the fuel cycle simulator CLASS developed by the CNRS/IN2P3 in collaboration with IRSN. The design of experiment is built from five fuel cycle input sampled variables. Sensitivity indices have been calculated on plutonium and minor actinide (MA) production. It shows that the PWR-UOx Burn-Up and the fraction of PWR-MOx fuel are the most important input variables that explain the plutonium production. For the MA production, main drivers depend strongly on isotopes. Sensitivity analysis also reveals input variable subspace responsible of simulation crash, what led to an important improvement of the model algorithms. An equilibrium condition on the plutonium mass in the stockpile used for building MOx fuel has been applied. The solution is represented as a subspace in the PWR-UOx Burn-Up and PWR-MOx fraction input space. For instance, achieving a plutonium equilibrium in a stockpile fed by a PWR-UOx that operates at 40 GWd/t requires a PWR-MOx fraction between 9 and 14%. This study also provides data related to plutonium incineration induced by the utilization of the MOx.

Assessment of strategy robustness under disruption of objective in dynamic fuel cycle studies

“…3177 are valid without the Pu shortage for MOX fabrication before 2090. The problem of Pu shortage is well studied in [16], and in our work those invalid trajectories are not of interest. For each valid trajectory characterized by eight input variables, the outputs R Subs and TRU tot in 2090 are calculated.…”

Robustness Study of Electro-Nuclear Scenario under Disruption

“…Brown points denote the trajectories with Pu shortages for MOX fuel fabrication before 2180. The Pu shortage is well studied in [12]. In this work, the trajectories with Pu shortages are considered invalid.…”

Assessment of plutonium inventory management in the french nuclear fleet with the fuel cycle simulator CLASS

“…This definition clearly excludes plutonium from nuclear waste categories since plutonium is currently used in PWR as MOX fuel and since plutonium incineration in SFR was planned. Plutonium inventory is increasing and the stockpiled mass in the current French fuel cycle is around 350 tons [13].…”