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Recalage stochastique robuste d'un modèle d'aube de turbine composite à matrice céramique

Abstract : This work is focused on the stochastic updating of ceramic matrix composite turbine blade model. They arepart of the uncertainty quantification framework for model validation. The aim is to enhance the existing toolused by the industrial decision makers. Indeed, consequent dispersion was measured during the experimentalcampaigns preventing the use of deterministic approaches. The first part of this thesis is dedicated to therelationship between mechanical science and uncertainty. Thus, Verification and Validation was introduced asthe processes by which credibility in numerical models is established. Then two stochastic updatingtechniques, able to handle statistic distribution, were compared through an academic example. Nevertheless,taking into account uncertainties doesn’t remove potential compensating effects between parameters.Therefore, criteria were developed in order to detect these disturbing phenomena. Info-gap theory wasemployed as a mean to model these lack of knowledge. Paired with the stochastic updating method, a robuststochasticapproach has been proposed. Results demonstrate a trade-off relationship between the model’sfidelity and robustness. The developed tools were applied on a ceramic matrix composite turbine blade finiteelement model.
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Submitted on : Monday, August 27, 2018 - 4:19:09 PM
Last modification on : Tuesday, October 27, 2020 - 2:34:20 PM
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  • HAL Id : tel-01862730, version 1

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Paul Lepine. Recalage stochastique robuste d'un modèle d'aube de turbine composite à matrice céramique. Génie mécanique [physics.class-ph]. Université Bourgogne Franche-Comté, 2017. Français. ⟨NNT : 2017UBFCD051⟩. ⟨tel-01862730⟩

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