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  5. Post-fire behaviour of wire arc additively manufactured ER70S-6 steel
 
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Post-fire behaviour of wire arc additively manufactured ER70S-6 steel
File(s)
Li et al. (2025) - Post-fire behaviour of wire arc additively manufactured ER70S-6 steel.pdf (3.34 MB)
Accepted version
Author(s)
Li, Jin
Jiang, Ke
Chen, Man-Tai
Zhao, Ou
Gardner, Leroy
Type
Journal Article
Abstract
Wire arc additive manufacturing (WAAM) is a metal 3D printing technique through which parts are built up in a layer-upon-layer fashion using metal wire and a welding arc. This paper presents an experimental programme to investigate the residual mechanical properties of WAAM ER70S-6 steel after exposure to elevated temperatures. A total of thirty-six tensile coupons were extracted from as-built WAAM plates fabricated using ER70S-6 feedstock wire, with two nominal thicknesses of 3 mm and 8 mm, two coupon extraction orientations (i.e. parallel and perpendicular to the layer deposition direction) and eight exposure temperatures ranging from 300 °C to 1000 °C. The geometric features of the WAAM steel coupons were captured via 3D scanning, while their stress–strain curves and residual material properties after exposure to elevated temperatures were obtained through tensile testing. Scanning Electron Microscopy (SEM) was used to investigate the fracture surfaces of the tested coupons with different plate thicknesses and exposure temperatures. On the basis of the experimental results, a new set of retention factor curves was proposed to predict the post-fire material properties of WAAM ER70S-6 steel and shown to result in accurate predictions of Young’s modulus, yield stress, ultimate stress, ultimate strain and fracture strain.
Date Issued
2025-07-01
Date Acceptance
2025-03-01
Citation
Engineering Structures, 2025, 334
URI
https://hdl.handle.net/10044/1/119760
URL
https://doi.org/10.1016/j.engstruct.2025.120192
DOI
https://www.dx.doi.org/10.1016/j.engstruct.2025.120192
ISSN
0141-0296
Publisher
Elsevier
Journal / Book Title
Engineering Structures
Volume
334
Copyright Statement
© 2025 Elsevier Ltd. All rights are reserved, including those for text and data mining, AI training, and similar technologies. This is the author’s accepted manuscript made available under a CC-BY licence in accordance with Imperial’s Research Publications Open Access policy (www.imperial.ac.uk/oa-policy)
License URL
https://creativecommons.org/licenses/by/4.0/
Publication Status
Published
Article Number
120192
Date Publish Online
2025-04-01
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