Communication Dans Un Congrès Année : 2019

Reliability of the Data-Driven Identification algorithm with respect to incomplete input data

Résumé

This work focuses on the influence of the input parameters of the Data-Driven Identification algorithm developed by Leygue et al. (2018) on the results obtained. This algorithm allows to measure stresses, from displacement fields and forces applied to a structure; the particularity is the absence of underlying constitutive equation. In the case of real experiments, the data are incomplete; but it is proven here that with appropriate data handling, stress fields can be identified in a robust manner. The incompleteness of input data is twofold: some missing displacement values (close to the edges or in a noise-affected area) and also a partial force information. The study proves that recovering those missing data has to be done smartly so that no assumptions except the balance equation is made.

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Dates et versions

hal-05273631 , version 1 (23-09-2025)

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Marie Dalémat, Michel Coret, Adrien Leygue, Erwan Verron. Reliability of the Data-Driven Identification algorithm with respect to incomplete input data. 11th European Conference on Constitutive Models for Rubber (ECCMR 2019), Jun 2019, Nantes, France. pp.311-316, ⟨10.1201/9780429324710-55⟩. ⟨hal-05273631⟩
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