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

[摘要] 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.

[发布机构] LMT (ENS Cachan/CNRS/Paris-Saclay University), 61 Avenue du Président Wilson, Cachan; 94230, France^1;SAFRAN TECH, 1 Rue Geneviéve Aubé, CS 80112, Magny les Hameaux; 78772, France^2

[效力级别] 计算机科学 [学科分类] 计算机科学（综合）

[关键词] Constitutive Relation Errors;Identification strategies;Kalman filtering algorithms;Model reduction method;Proper generalized decompositions;Real-time identification;Time-dependent boundary conditions;Time-dependent systems