Comparison of two approaches to compute magnetic field in problems with random domains
Article dans une revue avec comité de lecture
Date
2012Journal
IET Science Measurement and TechnologyAbstract
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 on the magnetic field distribution in the stochastic dimension can arise in a problem with uncertainties on the geometry. The basis functions (polynomial chaos) usually used to approximate the unknown fields in the random dimensions are no longer suited. One possibility proposed in the literature is to introduce additional functions (enrichment function) to tackle the problem of discontinuity. In this study, the authors focus on the method of random mappings and they show that in this case the discontinuity are naturally taken into account and that no enrichment function needs to be added.
Files in this item
Related items
Showing items related by title, author, creator and subject.
-
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 ...
-
Article dans une revue avec comité de lectureMAC, Duy Hung; MIPO, Jean-Claude; MOREAU, Olivier; CLENET, Stephane (Institute of Electrical and Electronics Engineers, 2010)A method to solve stochastic partial differential equations on random domains consists in using a one-to-one random mapping function which transforms the random domain into a deterministic domain. With this method, the ...
-
Article dans une revue avec comité de lectureMAC, Duy Hung; MIPO, Jean-Claude; TSUKERMAN, Igor; CLENET, Stephane (Institute of Electrical and Electronics Engineers, 2013)To solve stochastic problems with geometric uncertainties, one can transform the original problem in a domain with stochastic boundaries and interfaces to a problem defined in a deterministic domain with uncertainties in ...
-
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 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 ...