Error estimation of a proper orthogonal decomposition reduced model of a permanent magnet synchronous machine
Communication avec acte
Abstract
Model order reduction methods, like the proper orthogonal decomposition (POD), enable to reduce dramatically the size of a finite element (FE) model. The price to pay is a loss of accuracy compared with the original FE model that should be of course controlled. In this study, the authors apply an error estimator based on the verification of the constitutive relationship to compare the reduced model accuracy with the full model accuracy when POD is applied. This estimator is tested on an example of a permanent magnet synchronous machine.
Files in this item
Related items
Showing items related by title, author, creator and subject.
-
Article dans une revue avec comité de lectureMAC, Hung; BEDDEK, Karim; KORECKI, Julien; MOREAU, Olivier; CHEVALLIER, Loic; THOMAS, Pierre; CLENET, Stephane (Wiley, 2013)In this paper, we analyze the influence of the uncertainties on the behavior constitutive laws of ferromagnetic materials on the behavior of a turboalternator. A simple stochastic model of anhysteretic nonlinear B(H) curve ...
-
Article dans une revue avec comité de lectureIn this paper, we propose an a posteriori error estimator for the numerical approximation of a stochastic magnetostatic problem, whose solution depends on the spatial variable but also on a stochastic one. The spatial ...
-
Article dans une revue avec comité de lectureLIU, Sijun; MAC, Hung; MIPO, Jean-Claude; COOREVITS, Thierry; CLENET, Stephane (Institute of Electrical and Electronics Engineers, 2015)In mass production, fabrication processes of electrical machines are not perfectly repeatable with time, leading to dispersions on the dimensions which are not equal to their nominal values. The issue is then to link the ...
-
Article dans une revue avec comité de lectureMAC, Duy Hung; CLENET, Stephane; MIPO, Jean-Claude (Institution of Engineering and Technology, 2012)Methods are now available to solve numerically electromagnetic problems with uncertain input data (behaviour law or geometry). The stochastic approach consists in modelling uncertain data using random variables. Discontinuities ...
-
Article dans une revue avec comité de lectureMAC, Duy Hung; CLENET, Stephane; MIPO, Jean-Claude (Institute of Electrical and Electronics Engineers, 2011)The numerical solution of partial differential equations onto random domains can be done by using a mapping transforming this random domain into a deterministic domain. The issue is then to determine this one to one random ...