EPJ Web Conf.
Volume 247, 2021PHYSOR2020 – International Conference on Physics of Reactors: Transition to a Scalable Nuclear Future
|Number of page(s)||8|
|Section||Sensitivity & Uncertainty Methods|
|Published online||22 February 2021|
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
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
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