Data-Driven Identification of Composites Permeability from Flow Patterns - l'unam - université nantes angers le mans
Communication Dans Un Congrès Année : 2019

Data-Driven Identification of Composites Permeability from Flow Patterns

Résumé

Fast, reliable and easy measurement of preform permeability is a crucial need for composite manufacturing by liquid molding. This paper proposes a data-driven method to identify permeability by tracking flow front information. We combine the data-driven computational mechanics scheme [6] along with the data-driven identification [8] and add necessary self-consistent corrections on the algorithms’ parameters for the characterization of isotropic, orthotropic and general anisotropic permeability.
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hal-04824580 , version 1 (07-12-2024)

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  • HAL Id : hal-04824580 , version 1

Citer

Elie Eid, Adrien Leygue, Christophe Binetruy, Suresh Advani. Data-Driven Identification of Composites Permeability from Flow Patterns. 14ème Colloque National en Calcul de Structures (CSMA 2019), CSMA, LEM3, MSME, Université de Lorraine, Arts et Métiers, CNRS, May 2019, Hyères, France. ⟨hal-04824580⟩
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