NOTICE: this is the author’s version of a work that was accepted for publication in Composite Structures. Changes resulting from the publishing process, such as peer review, editing, corrections, structural formatting, and other quality control mechanisms may not be reflected in this document. Changes may have been made to this work since it was submitted for publication. A definitive version was subsequently published in Composite Structures 220, 2019, 64-80, doi:10.1016/j.compstruct.2019.03.066
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[en] We present a stochastic approach combining Bayesian Inference (BI) with homogenization theories in order to identify, on the one hand, the parameters inherent to the model assumptions
and, on the other hand, the composite material constituents behaviors, including their variability.
In particular, we characterize the model parameters of a Mean-Field Homogenization (MFH) model and the elastic matrix behavior, including the inherent dispersion in its Young's modulus, of non-aligned Short Fibers Reinforced Polymer (SFRP) composites. The inference is achieved by considering as observations experimental tests conducted at the SFRP composite coupons level.
The inferred model and material law parameters can in turn be used in Mean-Field Homogenization
(MFH)-based multi-scale simulations and can predict the confidence range of the composite
material responses.
H2020 - 685451 - M-ERA.NET 2 - ERA-NET for materials research and innovation
Name of the research project :
The research has been funded by the Walloon Region under the agreement no 1410246 - STOMMMAC (CT-INT2013-03-28) in the context of the M-ERA.NET Joint Call 2014.
Funders :
Service public de Wallonie : Direction générale opérationnelle de l'économie, de l'emploi et de la recherche - DG06 CE - Commission Européenne [BE]
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