Uncertainty Quantification in Computational Electromagnetics: The stochastic approach
type: Dataset
description: 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
issued: 2026-05-10T18:24:25.237106
language: en
modified: 2026-05-10T18:24:25.237111
contact point: Organization
  fn: CCSD
keyword: computationnal-electromagnetics
keyword: electrical-machine
keyword: electromagnetism
keyword: finite-element-method
keyword: infoeu-reposemanticsarticle
keyword: journal-articles
keyword: manufacturing-process
keyword: spielecengineering-sciences-physicselectromagnetism
keyword: spinrjengineering-sciences-physicselectric-power
keyword: statmestatistics-statmethodology-statme
keyword: stochastic-modelling
keyword: uncertainty-quantification
landing page: 1026-0854

Uncertainty Quantification in Computational Electromagnetics: The stochastic approach
type: Distribution
format: HTML
issued: 2026-05-10T18:24:25.239024
modified: 2026-05-10T18:24:25.223418
access URL: https://hal.science/hal-00833122

test_moissonnage_selune
type: Agent