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Article Dans Une Revue Journal of Rubber Research Année : 2021

Inverse-Pagerank-particle swarm optimisation for inverse identification of hyperelastic models: a feasibility study

Résumé

In this study, the Finite-Element Model Updating (FEMU) technique is used to identify hyperelastic parameters from only one heterogeneous test. A residual considering measured and identified stretches as well as the global reaction force of the specimen is built. The originality of this paper is to investigate the feasibility of the resolution of this minimisation problem using the Inverse-PageRank-particle swarm optimisation (PSO) for identifying hyperelastic parameters. For that purpose, the so-called PSO technique has been enriched with a PageRank algorithm to adapt iteratively the PSO parameters. As the paper examines whether Inverse-PageRank-PSO is adapted or not to the minimisation of the objective function in the present case, only two basic hyperelastic models have been considered.
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Dates et versions

hal-03330326 , version 1 (03-06-2022)

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Paternité - Pas d'utilisation commerciale

Identifiants

Citer

Guilherme Bastos, Leonardo Sales, Noëlie Di Cesare, Adel Tayeb, Jean-Benoit Le Cam. Inverse-Pagerank-particle swarm optimisation for inverse identification of hyperelastic models: a feasibility study. Journal of Rubber Research, 2021, 24 (3), pp.447-460. ⟨10.1007/s42464-021-00113-8⟩. ⟨hal-03330326⟩
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