Spatial adaptivity of the SAAF and Weighted Least Squares (WLS) forms of the neutron transport equation using constraint based, locally refined, isogeometric analysis (IGA) with dual weighted residual (DWR) error measures
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Accepted version
Author(s)
Latimer, Charles
Kophazi, Joszef
Eaton, Matthew
McClarren, Ryan
Type
Journal Article
Abstract
This paper describes a methodology that enables NURBS (Non-Uniform Rational B-spline) based Isogeometric Analysis (IGA) to be locally refined. The methodology is applied to continuous Bubnov-Galerkin IGA spatial discretisations of second-order forms of the neutron transport equation. In particular this paper focuses on the self-adjoint angular flux (SAAF) and weighted least squares (WLS) equations. Local refinement is achieved by constraining degrees of freedom on interfaces between NURBS patches that have different levels of spatial refinement. In order to effectively utilise constraint based local refinement, adaptive mesh refinement (AMR) algorithms driven by a heuristic error measure or forward error indicator (FEI) and a dual weighted residual (DWR) or goal-based error measure (WEI) are derived. These utilise projection operators between different NURBS meshes to reduce the amount of computational effort required to calculate the error indicators. In order to apply the WEI to the SAAF and WLS second-order forms of the neutron transport equation the adjoint of these equations are required. The physical adjoint formulations are derived and the process of selecting source terms for the adjoint neutron transport equation in order to calculate the error in a given quantity of interest (QoI) is discussed. Several numerical verification benchmark test cases are utilised to investigate how the constraint based local refinement affects the numerical accuracy and the rate of convergence of the NURBS based IGA spatial discretisation. The nuclear reactor physics verification benchmark test cases show that both AMR algorithms are superior to uniform refinement with respect to accuracy per degree of freedom. Furthermore, it is demonstrated that for global QoI the FEI driven AMR and WEI driven AMR produce similar results. However, if local QoI are desired then WEI driven AMR algorithm is more computationally efficient and accurate per degree of freedom.
Date Issued
2021-02-01
Date Acceptance
2020-10-19
Citation
Journal of Computational Physics, 2021, 426, pp.1-31
ISSN
0021-9991
Publisher
Elsevier
Start Page
1
End Page
31
Journal / Book Title
Journal of Computational Physics
Volume
426
Copyright Statement
© 2021 Elsevier Ltd. All rights reserved. This manuscript is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International Licence http://creativecommons.org/licenses/by-nc-nd/4.0/
Sponsor
Engineering & Physical Science Research Council (EPSRC)
Engineering & Physical Science Research Council (E
Engineering & Physical Science Research Council (E
Engineering and Physical Sciences Research Council
Rolls-Royce Plc
Identifier
https://www.sciencedirect.com/science/article/pii/S0021999120307154?via%3Dihub
Grant Number
EP/J002011/1
EP/K503733/1
EP/R511547/1
EP/M507878/1
PO 5001626145
Subjects
Science & Technology
Technology
Physical Sciences
Computer Science, Interdisciplinary Applications
Physics, Mathematical
Computer Science
Physics
Nuclear physics
Neutron transport
Isogeometric analysis
Adjoint
Adaptive mesh refinement
Local refinement
01 Mathematical Sciences
02 Physical Sciences
09 Engineering
Applied Mathematics
Publication Status
Published
Date Publish Online
2020-10-22