Data-driven computation for history-dependent materials
2019
Abstract This paper introduces a new vision of data-driven structure computation taking advantage of Material Science, especially for highly nonlinear and time-dependent material behaviours. Technical solutions are also derived, in order to build internal hidden variables defining the so-called “Experimental Constitutive Manifold”.
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