Abstract

The neutron transport equation can be used to model the physics of the nuclear reactor core. Its solution depends on several variables and requires a lot of high precision computations. One can simplify this model to obtain the SPN equation for a generalized eigenvalue problem. In order to solve this eigenvalue problem, we usually use the inverse power iteration by solving a source problem at each iteration. Classically, this problem can be recast in a mixed variational form, and then discretized by using the Raviart-Thomas-Nédélec Finite Element. In this article, we focus on the steady-state diffusion equation with heterogeneous coefficients discretized on Cartesian meshes. In this situation, it is expected that the solution has low regularity. Therefore, it is necessary to refine at the singular regions to get better accuracy. The Adaptive Mesh Refinement (AMR) is one of the most effective ways to do that and to improve the computational time. The main ingredient for the refinement techniques is the use of a posteriori error estimates, which gives a rigorous upper bound of the error between the exact and numerical solution. This indicator allows to refine the mesh in the regions where the error is large. In this work, some mesh refinement strategies are proposed on the Cartesian mesh for the source problem. Moreover, we numerically investigate an algorithm which combines the AMR process with the inverse power iteration to handle the generalized eigenvalue problem.

Highlights

  • Numerical simulations of nuclear reactor core are generally expensive as they require the exact solution of the neutron transport equation

  • We focus on the development of the project APOLLO3, a shared platform among CEA, FRAMATOME and EDF, which includes different deterministic solvers for the neutron transport equation

  • We focus on the solvers which use the structured meshes like the MINOS solver

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Summary

Introduction

Numerical simulations of nuclear reactor core are generally expensive as they require the exact solution of the neutron transport equation. These simulations are computationally expensive since one has to deal with many variables such as the neutron position in space, the motion direction and neutron energy. In the time independent case, the multi-group SPN equation corresponds to a generalized eigenvalue problem: To p + grad (Hφ) = 0, in R, H div (p) + Te φ 1 keff Mf φ, in R, (1). Let G be the number of energy group and N an odd number which represents for the order of the SPN equation.

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