Issue |
EPJ Web Conf.
Volume 247, 2021
PHYSOR2020 – International Conference on Physics of Reactors: Transition to a Scalable Nuclear Future
|
|
---|---|---|
Article Number | 03001 | |
Number of page(s) | 8 | |
Section | Deterministic Transport | |
DOI | https://doi.org/10.1051/epjconf/202124703001 | |
Published online | 22 February 2021 |
https://doi.org/10.1051/epjconf/202124703001
COMPARISON OF CHEBYSHEV AND ANDERSON ACCELERATIONS FOR THE NEUTRON TRANSPORT EQUATION
1 DEN - Service d’études des réacteurs et de mathématiques appliquées (SERMA) CEA, Université Paris-Saclay, F-91191 Gif-sur-Yvette, France
2 DEN - DTN/STMA/LMAG CEA Cadarache, F-13108 Saint-Paul-lez-Durance, France
3 EDF R&D/PERICLES Lab Paris-Saclay 7, boulevard Gaspard Monge, F-91120 Palaiseau, France, EDF
ansar.calloo@cea.fr
romain.le-tellier@cea.fr
david.couyras@edf.fr
Published online: 22 February 2021
This work focuses on the k-eigenvalue problem of the neutron transport equation. The variables of interest are the largest eigenvalue (keff) and the corresponding eigenmode is called the fundamental mode. Mathematically, this problem is usually solved using the power iteration method. However, the convergence of this algorithm can be very slow, especially if the dominance ratio is high as is the case in some reactor physics applications. Thus, the power iteration method has to be accelerated in some ways to improve its convergence. One such acceleration is the Chebyshev acceleration method which has been widely applied to legacy codes. In recent years, nonlinear methods have been applied to solve the k-eigenvalue problem. Nevertheless, they are often compared to the unaccelerated power iteration. Hence, the goal of this paper is to apply the Anderson acceleration to the power iteration, and compare its performance to the Chebyshev acceleration.
Key words: Power iteration / k-eigenvalue / Chebyshev acceleration / Anderson acceleration
© The Authors, published by EDP Sciences, 2021
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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