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Bending properties and numerical modelling of cellular panels manufactured from wood fibre/PLA biocomposite by 3D printing
NTNU, Norway.
RISE Research Institutes of Sweden, Bioeconomy and Health, Material and Surface Design.ORCID iD: 0000-0002-6183-2017
NTNU, Norway.
2023 (English)In: Composites. Part A, Applied science and manufacturing, ISSN 1359-835X, E-ISSN 1878-5840, Vol. 165, article id 107368Article in journal (Refereed) Published
Abstract [en]

The major advantage of cellular structures is the saving of material, energy, cost, and weight. Biocomposites are strong, lightweight materials and offer a high degree of design freedom. The purpose of this study was to characterise and compare the bending properties of various cellular structures for utilisation in panels made of a wood fibre/PLA biocomposite. Material extrusion (MEX) 3D printing is a highly flexible manufacturing method and well-suited for prototyping. Hence, MEX was applied to manufacture five different cell configurations that were mechanically tested. Additionally, numerical simulations were carried out to present a tool for optimising the structures for future requirements. Two material modelling approaches, a hyperelastic and a linear elastic, bimodular model were created and validated based on 3-point-bending tests. It is shown that a linear elastic, bimodular and perfectly plastic material model can adequately capture the elastic/plastic bending behaviour of the corresponding 3D-printed sandwich panels. © 2022 The Author(s)

Place, publisher, year, edition, pages
Elsevier Ltd , 2023. Vol. 165, article id 107368
Keywords [en]
3-D printing, Biocomposites, Finite element analysis (FEA), Sandwich structures, 3D printers, Bending tests, Cellular automata, Composite materials, Honeycomb structures, Numerical models, Wood products, 3D-printing, Bending properties, Biocomposite, Cellular structure, Finite element analyse, Linear elastic, Material modeling, Woodfiber, Finite element method
National Category
Composite Science and Engineering
Identifiers
URN: urn:nbn:se:ri:diva-62357DOI: 10.1016/j.compositesa.2022.107368Scopus ID: 2-s2.0-85144457624OAI: oai:DiVA.org:ri-62357DiVA, id: diva2:1730268
Note

Funding details: Norges Forskningsråd, 282310; Funding text 1: The Research Council of Norway and the companies supporting the ALLOC project (Grant no. 282310) are thanked for funding.

Available from: 2023-01-24 Created: 2023-01-24 Last updated: 2023-05-17Bibliographically approved

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Chinga-Carrasco, Gary

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