https://doi.org/10.1051/epjconf/202124715019
EXPLORING TRANSIENT, NEUTRONIC, REDUCED-ORDER MODELS USING DMD/POD-GALERKIN AND DATA-DRIVEN DMD
Department of Mechanical and Nuclear Engineering, Kansas State University 3002 Rathbone Hall, Manhattan, KS 66506, US
rababelzohery@ksu.edu
jaroberts@ksu.edu
Published online: 22 February 2021
There is growing interest in the development of transient, multiphysics models for nuclear reactors and analysis of uncertainties in those models. Reduced-order models (ROMs) provide a computationally cheaper alternative to compute uncertainties. However, the application of ROMs to transient systems remains a challenging task. Here, a 1-D, twogroup, time-dependent, diffusion model was used to explore the potential of three different ROMs: the intrusive POD-Galerkin and DMD-Galerkin methods and the purely datadriven DMD. For the problem studied, POD-Galerkin exhibited by far the best accuracy and was selected for further application to uncertainty propagation. Perturbations were introduced to the initial condition and to the cross-section data. A greedy-POD sampling procedure was used to construct a reduced space that captured much of the variation in the uncertain these parameters. Results indicate that relatively few samples of the uncertain parameters are needed to produce a basis for POD-Galerkin that leads to distributions of the quantities of interest that match well with those obtained from the full-order model using brute-force, forward sampling.
Key words: ROM / UQ / Galerkin projection / DMD
© 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.