Main Research Interest / Name of Research Project
- Forming process modelling
- Ductile damage modelling
- Inverse analysis / Optimisation
The goal of the MEGaFiT project is to construct a real-time control for a metal forming process, aiming to reduce the amount of erroneous products. The control strategy is based on process knowledge obtained through numerical modeling. Within MEGaFiT, two demonstrator projects will be built and controlled as a proof-of-concept. We contribute to MEGaFiT in the field of numerical modeling, metamodeling and robust optimization.
Recent jobsCEMEF - Mines ParisTech
Post-doc, European project PACROLP II: The prediction and avoidance of cracking in long product hot rolling. Main contributions: Development of a finite element model for ductile damage understanding at the micro scale.
Abstract: This study deals with the development of a numerical strategy dedicated to mechanical joining processes optimisation and to parameters identification by inverse analysis. The first part is dedicated to the definition and development of an optimisation and inverse analysis platform. This platform is adapted to finite element computations. An optimisation algorithm with a kriging meta-model has been developed and included in the platform. In order to deal with time consuming computation a parallel version of this algorithm, based on kriging properties, has been developed. Significant acceleration of the parallel algorithm has been observed, leading to a decrease in time of the resolution of the optimisation issue. In the second part of this work an optimisation methodology has been carried out for mechanical joining processes. This procedure enables to optimize a global simulation chain, including both the joining process and the mechanical strength analysis of the joined component. This procedure is applied to the clinching joining process and gives rise to an 13% increase of the mechanical strength of the component. The third part of this work deals with a parameter identification study of an elastic-plastic law coupled with a ductile damage model. The identification procedure is based on a tensile test. A power hardening law and a Lemaitre model are chosen respectively for the elastic-plastic behaviour and for ductile damage. Three different observables have been taken into account: the load/displacement curve, the necking measurement, and displacement fields. Displacement fields are measured by full field measurement methods. It is shown how the enrichment of the observables database improves the definition of the inverse problem and decreases correlation issues between parameters.
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