Data-Driven Identification of Composites Permeability from Flow Patterns
Abstract
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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