1. Study of non-intrusive model order reduction of neutron transport problems
- Author
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Quan Yan, Yang Di, Gong Helin, Zhang Chunyu, Xia Bangyang, Chen Wei, Wang Lianjie, and Zhang Junjie
- Subjects
Model order reduction ,Neutron transport ,Speedup ,020209 energy ,02 engineering and technology ,01 natural sciences ,010305 fluids & plasmas ,Nuclear Energy and Engineering ,Orders of magnitude (time) ,Kriging ,Neutron flux ,0103 physical sciences ,0202 electrical engineering, electronic engineering, information engineering ,Applied mathematics ,Multiplication ,Mathematics ,Interpolation - Abstract
Model order reduction is one important technique to speed up the solution of large-scale problems. Two model order reduction techniques, i.e., the proper orthogonal decomposition with interpolation and the Gaussian process regression, are investigated to compute the neutron flux and the effective multiplication factor. Two reduced order models are constructed and it is shown that a speedup of 3 ~ 4 orders of magnitude is achieved with guaranteed accuracy. The Gaussian process regression model can predict the mean value of k e f f and more importantly, the uncertainty of the predicted value can be analyzed as well.
- Published
- 2021