Reduced-order modeling of neutron transport separated in axial and radial space by Proper Generalized Decomposition with applications to nuclear reactor physics
Kurt A. Dominesey, Wei Ji

TL;DR
This paper introduces a novel PGD-based reduced-order modeling approach for neutron transport in nuclear reactors, enabling efficient and accurate 2D/1D approximations without simplifying assumptions.
Contribution
The study develops general PGD models for neutron transport that separate axial and polar dimensions, improving upon existing 2D/1D methods with arbitrary-rank decompositions and no leakage approximations.
Findings
PGD ROMs are convergent on reactor benchmarks.
Axial-polar ROMs are often more economical than axial-only.
Models show potential for improved accuracy and efficiency in reactor simulations.
Abstract
In this article, we demonstrate the novel use of Proper Generalized Decomposition (PGD) to separate the axial and, optionally, polar dimensions of neutron transport. Doing so, the resulting Reduced-Order Models (ROMs) can exploit the fact that nuclear reactors tend to be tall, but geometrically simple, in the axial direction , and so the 3D neutron flux distribution often admits a low-rank "2D/1D" approximation. Through PGD, this approximation is computed by alternately solving 2D and 1D sub-models, like in existing 2D/1D models of reactor physics. However, the present methodology is more general in that the decomposition is arbitrary-rank, rather than rank-one, and no simplifying approximations of the transverse leakage are made. To begin, we derive two original models: that of axial PGD -- which separates only and the sign of the polar angle -- and…
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Taxonomy
TopicsNuclear reactor physics and engineering · Nuclear Engineering Thermal-Hydraulics · Model Reduction and Neural Networks
