Parametric model-order reduction for radiation transport using multi-resolution proper orthogonal decomposition

Behne, Patrick; Ragusa, Jean C.

doi:10.1016/j.anucene.2022.109432

Title: Parametric model-order reduction for radiation transport using multi-resolution proper orthogonal decomposition

Journal Article · 23 September 2022 · Annals of Nuclear Energy

DOI: https://doi.org/10.1016/j.anucene.2022.109432 · OSTI ID:2418284

Behne, Patrick ^[1];

^[2]

Texas A & M Univ., College Station, TX (United States); OSTI
Texas A & M Univ., College Station, TX (United States)

For parametric high-fidelity simulations, it is often desirable to utilize a reduced-order model (ROM) to emulate, at a reduced computational cost, parametric solutions of the governing partial differential equations (PDEs) for unseen parameter values. One commonly employed option is to utilize a data-driven, projection-based ROM supplemented with subspace identification via proper orthogonal decomposition (POD). POD discovers the ROM subspace by computing the singular value decomposition (SVD) of a set of training data from the full-order model (FOM). In streaming-dominated radiation transport simulations with localized sources, solutions often greatly vary over the spatial domain by many orders of magnitude. In such cases, machine-precision arithmetic can be insufficient to obtain an accurate SVD, resulting in a poorly performing ROM. We present a method called multiresolution POD (mrPOD) that mitigates these inaccuracies. The mrPOD method works by decomposing the spatial domain into regions and performing proper orthogonal decomposition on the training dataset separately in each region. In conclusion, mrPOD is tested on single energy group and multigroup atmospheric shielding transport problems and is shown to outperform classic POD.

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Research Organization:: Texas A & M Univ., College Station, TX (United States). Texas A & M Engineering Experiment Station

Sponsoring Organization:: Defense Threat Reduction Agency (DTRA); USDOE; USDOE Office of Nuclear Energy (NE)

Grant/Contract Number:: NE0000112

OSTI ID:: 2418284

Journal Information:: Annals of Nuclear Energy, Journal Name: Annals of Nuclear Energy Journal Issue: C Vol. 180; ISSN 0306-4549

Publisher:: ElsevierCopyright Statement

Country of Publication:: United States

Language:: English

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Related Subjects

42 ENGINEERING
local proper orthogonal decomposition
model-order reduction
multi-resolution POD
parametric surrogate model
radiation transport
reduced-order model

Title: Parametric model-order reduction for radiation transport using multi-resolution proper orthogonal decomposition

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