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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Clenet, S. Henneron, T. Ida, N. |
| Copyright Year | 1965 |
| Abstract | Model order reduction methods enable reduction of the computation time when dealing with parametrized numerical models. Among these methods, the proper orthogonal decomposition method seems to be a good candidate because of its simplicity and its accuracy. In the literature, the offline/online approach is generally applied but is not always required especially if the study focuses on the device without any coupling with others. In this paper, we propose a method to adaptively construct the reduced model while it limits the evaluation of the full model when appropriate. A stochastic magnetostatic example with 14 uncertain parameters is studied by applying the Monte Carlo simulation method to illustrate the proposed procedure. In that case, it appears that the complexity of this method does not depend on the number of input parameters and so is not affected by the curse of dimensionality. |
| Sponsorship | IEEE Magnetics Society |
| Starting Page | 1 |
| Ending Page | 4 |
| Page Count | 4 |
| File Size | 734338 |
| File Format | |
| ISSN | 00189464 |
| Volume Number | 52 |
| Issue Number | 3 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2016-01-01 |
| Publisher Place | U.S.A. |
| Access Restriction | One Nation One Subscription (ONOS) |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | Iron Mathematical model Computational modeling Adaptation models Uncertainty Standards Numerical models Uncertainty Quantification Error estimation Finite Element Method (FEM) Model Order Reduction (MOR) Proper Orthogonal Decomposition (POD) |
| Content Type | Text |
| Resource Type | Article |
| Subject | Electronic, Optical and Magnetic Materials Electrical and Electronic Engineering |
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