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A novel pathway for efficient characterisation of additively manufactured thermoplastic elastomers

Adams, Rhosslyn, Soe, Shwe P., Santiago, Rafael, Robinson, Michael, Hanna, Benjamin, McShane, Graham, Alves, Marcílio, Burek, Roy and Theobald, Peter ORCID: https://orcid.org/0000-0002-3227-7130 2019. A novel pathway for efficient characterisation of additively manufactured thermoplastic elastomers. Materials and Design 180 , 107917. 10.1016/j.matdes.2019.107917

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Abstract

Thermoplastic elastomers (TPE) are commonly used to fabricate structures for application in repeatable, energy absorption environments. The emergence of additive manufacturing (AM) means scope now exists to design and build complex TPE components that can mechanically outperform traditionally manufactured equivalents. The ability to efficiently characterize these new TPE AM materials is, however, a barrier preventing wider industrial uptake. This study aims to establish a novel pathway for efficiently characterizing materials used in transient, dynamic applications, to ultimately enable accurate finite element (FE) simulation. A laser sintered TPE powder was characterised by performing low, intermediate and high rate uniaxial tension tests, plus planar and equibiaxial loading states. These data demonstrated significantly different behaviour across strain rates and deformation modes, necessitating fit of an augmented hyperelastic and linear viscoelastic model. FE software was then used to calibrate material model coefficients, with their validity evaluated by comparing the simulated and experimental behaviour of the material in isolated (uniaxial tensile) and mixed modal (lattice-based impact) deformation states. Close correlation demonstrated this novel approach efficiently generated valid material model coefficients, removing a barrier to industry adopting these materials. This creates opportunity to exploit these new technologies for the design optimization and fabrication of high-performance components

Item Type: Article
Date Type: Publication
Status: Published
Schools: Advanced Research Computing @ Cardiff (ARCCA)
Engineering
Additional Information: This is an open access article under the terms of the CC-BY Attribution 4.0 International license.
Publisher: Elsevier
ISSN: 0261-3069
Date of First Compliant Deposit: 7 June 2019
Date of Acceptance: 4 June 2019
Last Modified: 05 Jan 2024 02:15
URI: https://orca.cardiff.ac.uk/id/eprint/123300

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