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The influence of energy density on the low cycle fatigue behaviour of laser powder bed fused stainless steel 316L

RORY DOUGLAS, William Beard, Nick Barnard, Seungjong Lee, Shuai Shao Orcid Logo, Nima Shamsaei, Thomas Jones, Robert Lancaster Orcid Logo

International Journal of Fatigue, Volume: 181, Start page: 108123

Swansea University Authors: RORY DOUGLAS, Nick Barnard, Robert Lancaster Orcid Logo

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DOI (Published version): 10.1016/j.ijfatigue.2023.108123

Abstract

Laser powder bed fusion (LPBF) is an additive manufacturing (AM) process capable of single-step fabrication of intricate and complex structures. However, there are multiple engineering challenges associated with the introduction of AM based parts into functional industrial applications due to the la...

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Published in: International Journal of Fatigue
ISSN: 0142-1123 1879-3452
Published: Elsevier BV 2024
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URI: https://cronfa.swan.ac.uk/Record/cronfa65414
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However, there are multiple engineering challenges associated with the introduction of AM based parts into functional industrial applications due to the lack of understanding of the role that process parameters have on the structural integrity of additively manufactured (AM) components and the subsequent effect this has on the mechanical behaviour of such materials when subjected to cyclic loading conditions. The present work will investigate the low cycle fatigue (LCF) behaviour of LPBF stainless steel 316L components manufactured with different process parameters sets and how this effects the material built in different orientations and the resulting impact this has on the material’s resistance to cyclic deformation. The LCF results are supported by microstructural, fractographic and advanced surface profilometry assessments to investigate the key parameters that control the resulting fatigue performance across three different build orientations. 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spelling v2 65414 2024-01-05 The influence of energy density on the low cycle fatigue behaviour of laser powder bed fused stainless steel 316L 59f8c32d9bf3812751bbc5fe73630457 RORY DOUGLAS RORY DOUGLAS true false dc4a58e614bc6a1d99812a3acfdd9034 Nick Barnard Nick Barnard true false e1a1b126acd3e4ff734691ec34967f29 0000-0002-1365-6944 Robert Lancaster Robert Lancaster true false 2024-01-05 Laser powder bed fusion (LPBF) is an additive manufacturing (AM) process capable of single-step fabrication of intricate and complex structures. However, there are multiple engineering challenges associated with the introduction of AM based parts into functional industrial applications due to the lack of understanding of the role that process parameters have on the structural integrity of additively manufactured (AM) components and the subsequent effect this has on the mechanical behaviour of such materials when subjected to cyclic loading conditions. The present work will investigate the low cycle fatigue (LCF) behaviour of LPBF stainless steel 316L components manufactured with different process parameters sets and how this effects the material built in different orientations and the resulting impact this has on the material’s resistance to cyclic deformation. The LCF results are supported by microstructural, fractographic and advanced surface profilometry assessments to investigate the key parameters that control the resulting fatigue performance across three different build orientations. Finally, the generated mechanical data has also been interpreted through empirical fatigue lifing models, and the various data sets have been successfully correlated to enable an estimation of longer fatigue lives. Journal Article International Journal of Fatigue 181 108123 Elsevier BV 0142-1123 1879-3452 Laser Powder Bed Fusion (LPBF), Low Cycle Fatigue (LCF), Stainless steel 316L, Energy density, Surface roughness, Build orientation 1 4 2024 2024-04-01 10.1016/j.ijfatigue.2023.108123 COLLEGE NANME COLLEGE CODE Swansea University SU Library paid the OA fee (TA Institutional Deal) The current research was funded under the EPSRC Industrial Case Award EP/T517537/1. The provision of a research bursary, materials, and supporting information from Rolls-Royce plc. is gratefully acknowledged. 2024-03-21T14:50:48.7230187 2024-01-05T12:22:59.8365736 Faculty of Science and Engineering School of Engineering and Applied Sciences - Materials Science and Engineering RORY DOUGLAS 1 William Beard 2 Nick Barnard 3 Seungjong Lee 4 Shuai Shao 0000-0002-4718-2783 5 Nima Shamsaei 6 Thomas Jones 7 Robert Lancaster 0000-0002-1365-6944 8 65414__29392__904dc39181ef45cfad97dd99b45a6d8d.pdf 65414.VOR.pdf 2024-01-05T12:38:33.0274922 Output 19824537 application/pdf Version of Record true © 2023 The Authors. Published by Elsevier Ltd. Distributed under the terms of a Creative Commons Attribution 4.0 International License (CC BY 4.0). true eng https://creativecommons.org/licenses/by/4.0/
title The influence of energy density on the low cycle fatigue behaviour of laser powder bed fused stainless steel 316L
spellingShingle The influence of energy density on the low cycle fatigue behaviour of laser powder bed fused stainless steel 316L
RORY DOUGLAS
Nick Barnard
Robert Lancaster
title_short The influence of energy density on the low cycle fatigue behaviour of laser powder bed fused stainless steel 316L
title_full The influence of energy density on the low cycle fatigue behaviour of laser powder bed fused stainless steel 316L
title_fullStr The influence of energy density on the low cycle fatigue behaviour of laser powder bed fused stainless steel 316L
title_full_unstemmed The influence of energy density on the low cycle fatigue behaviour of laser powder bed fused stainless steel 316L
title_sort The influence of energy density on the low cycle fatigue behaviour of laser powder bed fused stainless steel 316L
author_id_str_mv 59f8c32d9bf3812751bbc5fe73630457
dc4a58e614bc6a1d99812a3acfdd9034
e1a1b126acd3e4ff734691ec34967f29
author_id_fullname_str_mv 59f8c32d9bf3812751bbc5fe73630457_***_RORY DOUGLAS
dc4a58e614bc6a1d99812a3acfdd9034_***_Nick Barnard
e1a1b126acd3e4ff734691ec34967f29_***_Robert Lancaster
author RORY DOUGLAS
Nick Barnard
Robert Lancaster
author2 RORY DOUGLAS
William Beard
Nick Barnard
Seungjong Lee
Shuai Shao
Nima Shamsaei
Thomas Jones
Robert Lancaster
format Journal article
container_title International Journal of Fatigue
container_volume 181
container_start_page 108123
publishDate 2024
institution Swansea University
issn 0142-1123
1879-3452
doi_str_mv 10.1016/j.ijfatigue.2023.108123
publisher Elsevier BV
college_str Faculty of Science and Engineering
hierarchytype
hierarchy_top_id facultyofscienceandengineering
hierarchy_top_title Faculty of Science and Engineering
hierarchy_parent_id facultyofscienceandengineering
hierarchy_parent_title Faculty of Science and Engineering
department_str School of Engineering and Applied Sciences - Materials Science and Engineering{{{_:::_}}}Faculty of Science and Engineering{{{_:::_}}}School of Engineering and Applied Sciences - Materials Science and Engineering
document_store_str 1
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description Laser powder bed fusion (LPBF) is an additive manufacturing (AM) process capable of single-step fabrication of intricate and complex structures. However, there are multiple engineering challenges associated with the introduction of AM based parts into functional industrial applications due to the lack of understanding of the role that process parameters have on the structural integrity of additively manufactured (AM) components and the subsequent effect this has on the mechanical behaviour of such materials when subjected to cyclic loading conditions. The present work will investigate the low cycle fatigue (LCF) behaviour of LPBF stainless steel 316L components manufactured with different process parameters sets and how this effects the material built in different orientations and the resulting impact this has on the material’s resistance to cyclic deformation. The LCF results are supported by microstructural, fractographic and advanced surface profilometry assessments to investigate the key parameters that control the resulting fatigue performance across three different build orientations. Finally, the generated mechanical data has also been interpreted through empirical fatigue lifing models, and the various data sets have been successfully correlated to enable an estimation of longer fatigue lives.
published_date 2024-04-01T14:50:49Z
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score 11.012924

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