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Communication Dans Un Congrès Année : 2017

BAYESIAN FORMULATIONS FOR FORCE RECONSTRUCTION PROBLEMS

Résumé

To identify mechanical sources acting on a structure, Tikhonov-like regularizations are generally used. These approaches, however, only provide point estimates, meaning that the uncertainty about the regularized solution is not quantified. In practice, such information is essential to guarantee the quality of reconstructed sources. In this contribution, three possible Bayesian formulations of the source identification problem are presented and their limitations discussed. To assess the posterior uncertainty on the parameters appearing in each formulation given a simulated vibration field and a mechanical model, a Gibbs sampler is implemented. The proposed numerical validations highlight the practical interest of these formulations in terms of parameters estimations and posterior uncertainty quantification.
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Dates et versions

hal-02068535 , version 1 (15-03-2019)

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  • HAL Id : hal-02068535 , version 1

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Mathieu Aucejo, Olivier de Smet. BAYESIAN FORMULATIONS FOR FORCE RECONSTRUCTION PROBLEMS. 2nd International Conference on Uncertainty Quantification in Computational Sciences and Engineering, UNCECOMP 2017, Jun 2017, Rhodes Island, Greece. ⟨hal-02068535⟩
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