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Uncertainty Quantification in Computational Electromagnetics: The stochastic approach

Article dans une revue sans comité de lecture
Auteur
ccCLENET, Stephane
13338 Laboratoire d’Électrotechnique et d’Électronique de Puissance - ULR 2697 [L2EP]

URI
http://hdl.handle.net/10985/7134
Date
2013
Journal
International Compumag society Newsletters

Résumé

Models in electromagnetism are more and more accurate. In some applications, the gap between the experience and the model comes from the deviation on input data of the model which are not perfectly known. The stochastic approach can be used to quantify the effect of these input data uncertainties on the outputs of the model. In this article, the application of such approach in computational electromagnetics is presented. The four steps development of the model, characterization and modeling of the input data variability, uncertainty quantification, postprocessing (sensitivity analysis) are described and illustrated by an example of electrical machine with uncertain dimensions

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  • Laboratoire d'Electrotechnique et d'Electronique de Puissance (L2EP) de Lille

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  • Multirate coupling of controlled rectifier and non-linear finite element model based on Waveform Relaxation Method 
    Article dans une revue avec comité de lecture
    HENNERON, Thomas; PIERQUIN, Antoine; BRISSET, Stéphane; ccCLENET, Stephane (Institute of Electrical and Electronics Engineers, 2016)
    To study a multirate system, each subsystem can be solved by a dedicated sofware with respect to the physical problem and the time constant. Then, the problem is the coupling of the solutions of the subsystems. The Waveform ...
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    Article dans une revue avec comité de lecture
    PIERQUIN, Antoine; BRISSET, Stéphane; HENNERON, Thomas; ccCLENET, Stephane (Institute of Electrical and Electronics Engineers, 2014)
    We present an optimization problem that requires to model a multirate system, composed of subsystems with different time constants. We use waveform relaxation method in order to simulate such a system. But computation time ...
  • Model-Order Reduction of Magnetoquasi-Static Problems Based on POD and Arnoldi-Based Krylov Methods 
    Communication avec acte
    PIERQUIN, Antoine; HENNERON, Thomas; BRISSET, Stéphane; ccCLENET, Stephane (IEEE, 2015)
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  • Enhanced Meta-model Based Optimization under Constraints using Parallel Computations 
    Article dans une revue avec comité de lecture
    EL BECHARI, Reda; BRISSET, Stéphane; MIPO, Jean-Claude; ccCLENET, Stephane (Institute of Electrical and Electronics Engineers, 2017)
    Meta-models proved to be a very efficient strategy for optimization of expensive black-box models, e.g. Finite Element simulation for electromagnetic devices. It enables to reduce the computational burden for optimization ...

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