Coupling Modified Constitutive Relation Error, Model Reduction and Kalman filtering algorithms for Real-Time Parameters Identification

Abstract : In this work we propose a new identification strategy based on the coupling between a probabilistic data assimilation method and a deterministic inverse problem approach using the modified Constitutive Relation Error energy functional. The idea is thus to offer efficient identification despite of highly corrupted data for time-dependent systems. In order to perform real-time identification, the modified Constitutive Relation Error is here associated to a model reduction method based on Proper Generalized Decomposition. The proposed strategy is applied to two thermal problems with identification of time-dependent boundary conditions, or material parameters.
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Poster
5th International Workshop on New Computational Methods for Inverse Problems, 2015, Cachan, France
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Contributeur : Basile Marchand <>
Soumis le : samedi 22 octobre 2016 - 20:24:26
Dernière modification le : samedi 23 mars 2019 - 01:29:47

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  • HAL Id : hal-01386133, version 1

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Basile Marchand, Ludovic Chamoin, Christian Rey. Coupling Modified Constitutive Relation Error, Model Reduction and Kalman filtering algorithms for Real-Time Parameters Identification. 5th International Workshop on New Computational Methods for Inverse Problems, 2015, Cachan, France. 〈hal-01386133〉

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