4.6 Article

Metallic stacked origami cellular materials: Additive manufacturing, properties, and modelling

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出版社

PERGAMON-ELSEVIER SCIENCE LTD
DOI: 10.1016/j.ijsolstr.2019.09.007

关键词

Additive manufacturing; Selective laser melting; Cellular materials; Origami; Auxetic

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  1. AWE

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Stacking layers of Miura-folded origami sheets has been shown to create a cellular material with attractive properties. It has a rich array of geometric parameters that allow its elastic properties and compressive collapse response to be varied over a wide range, at fixed relative density. It displays tunable anisotropy and auxetic behaviour, and can also be easily conformed to curved surfaces. Because of these attributes, metallic stacked origami materials have shown promise for applications such as impact energy absorption and blast mitigation. However, to date, manufacturability challenges have yet to be adequately solved. Sensitivity to dimensional tolerance, and challenges of layer interfaces, make the material difficult to manufacture via sheet metal forming routes. However, additive manufacturing (AM) techniques offer a route to overcoming these challenges. In this investigation, we use a selective laser melting (SLM) process to allow metallic stacked origami materials to be assessed experimentally for the first time. The as-manufactured characteristics of these cellular materials were investigated via X-ray tomography and microstructural inspection. For comparison, tensile coupons were also fabricated in different orientations with respect to the build plane, in order to investigate material anisotropy resulting from the AM process. Scaling effects, both in terms of manufacturability and mechanical response, were investigated with cellular specimens fabricated with different cell sizes and cell wall thicknesses. The origami specimens were tested under quasi-static compression to provide an assessment of their as-manufactured energy absorbing properties. Finally, a finite element analysis is carried out, in order to assess its predictive accuracy and sensitivity to key modelling decisions. (C) 2019 Published by Elsevier Ltd.

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