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    Data-Driven Upscaling of Orientation Kinematics in Suspensions of Rigid Fibres

    Adrien Scheuer1, 3, *, Amine Ammar2, Emmanuelle Abisset-Chavanne3, Elias Cueto4, Francisco Chinesta5, Roland Keunings1, Suresh G. Advani6

    CMES-Computer Modeling in Engineering & Sciences, Vol.117, No.3, pp. 367-386, 2018, DOI:10.31614/cmes.2018.04278

    Abstract Describing the orientation state of the particles is often critical in fibre suspen-sion applications. Macroscopic descriptors, the so-called second-order orientation tensor (or moment) leading the way, are often preferred due to their low computational cost. Clo-sure problems however arise when evolution equations for the moments are derived from the orientation distribution functions and the impact of the chosen closure is often unpre-dictable. In this work, our aim is to provide macroscopic simulations of orientation that are cheap, accurate and closure-free. To this end, we propose an innovative data-based approach to the upscaling of orientation kinematics in the context of fibre… More >

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