Reduced-Order Modelling Applied to the Multigroup Neutron Diffusion Equation Using a Nonlinear Interpolation Method for Control-Rod Movement

Claire E. Heaney, Andrew G. Buchan, Christopher C. Pain and Simon Jewer
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Claire E. Heaney: Applied Modelling and Computation Group, South Kensington, Imperial College London, London SW7 2AZ, UK
Andrew G. Buchan: School of Engineering and Materials Science, Queen Mary University of London, London E1 4NS, UK
Christopher C. Pain: Applied Modelling and Computation Group, South Kensington, Imperial College London, London SW7 2AZ, UK
Simon Jewer: Defence Academy, HMS Sultan, Gosport PO12 3BY, UK

Energies, 2021, vol. 14, issue 5, 1-27

Abstract: Producing high-fidelity real-time simulations of neutron diffusion in a reactor is computationally extremely challenging, due, in part, to multiscale behaviour in energy and space. In many scientific fields, including nuclear modelling, the application of reduced-order modelling can lead to much faster computation times without much loss of accuracy, paving the way for real-time simulation as well as multi-query problems such as uncertainty quantification and data assimilation. This paper compares two reduced-order models that are applied to model the movement of control rods in a fuel assembly for a given temperature profile. The first is a standard approach using proper orthogonal decomposition (POD) to generate global basis functions, and the second, a new method, uses POD but produces global basis functions that are local in the parameter space (associated with the control-rod height). To approximate the eigenvalue problem in reduced space, a novel, nonlinear interpolation is proposed for modelling dependence on the control-rod height. This is seen to improve the accuracy in the predictions of both methods for unseen parameter values by two orders of magnitude for k eff and by one order of magnitude for the scalar flux.

Keywords: reduced-order modelling; model order reduction; proper orthogonal decomposition; multigroup neutron diffusion; eigenvalue problem; reactor criticality (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2021
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (2)

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