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Assimilation de données et recalage rapide de modèles mécaniques complexes

Abstract : For several years, the considerable changes that have occurredin computing tools have led to new practices in the simulation of mechanical structures. Among them, the motivation for this work is the Dynamic Data Driven Application Systems paradigm (DDDAS). The founding idea of this approach is to establish a dialogue between a physical system and its numericalmodel. The objective is then to (i) allow a calibration of the numerical model by means of measurements performed on the physical system; (ii) control the evolution of the physical system using theprediction given by numerical simulation. The major difficulty is to realize this dialogue in real time. This work focuses on the model updating step of the DDDAS paradigm. The problem is then to develop methods and tools to solve inverse problems taking into account various constraints, namely: (i) robustness with respect to corrupted data; (ii) genericity for considering a wide variety of problems and mechanical models; (iii) a reduced computation time in order to tend towards a real-time model updating.The starting point of this work is the modified Constitutive Relation Error, an energetic approach dedicated to the solution of inverse problems in mechanics, notably illustrated by its robustness with respect to measurement noises. First, in order to guarantee a fast identification process, we have coupled the modified Constitutive Relation Error with the PGD model reduction in the linear model framework, thus enabling a fast and automatic identification process. Then, in order to be applied to the DDDAS paradigm, we have developed an identification method based on a data assimilation process (the Kalman filter) and using the modified Constitutive Relation Error as an observer alwayswithin the framework of linear problems. We have then extended this data assimilation approach to the problem of the identification of parameter fields by introducing a separation of the spatial discretizations and by introducing tools resulting from the mesh adaptation framework. We have then addressed the problem of non-linear mechanical models, through damage and visco-plasticitymodels. To this end, we have first recast and extended the concept of the modified Constitutive Relation Error to this nonlinear material framework and we have implemented a dedicated resolution process, based on the LaTIn method. Finally, we have introduced this reformulation of the modified Constitutive Relation Error in the previously data assimilation method in order to process the model updating of nonlinear models.
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Submitted on : Tuesday, January 9, 2018 - 6:02:28 PM
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  • HAL Id : tel-01679295, version 1


Basile Marchand. Assimilation de données et recalage rapide de modèles mécaniques complexes. Mécanique des solides [physics.class-ph]. Université Paris-Saclay, 2017. Français. ⟨NNT : 2017SACLN053⟩. ⟨tel-01679295⟩



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