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dc.contributor.authorXavier, MS
dc.contributor.authorYang, S
dc.contributor.authorComte, C
dc.contributor.authorBab-Hadiashar, A
dc.contributor.authorWilson, N
dc.contributor.authorCole, I
dc.date.accessioned2020-07-16T22:29:27Z
dc.date.available2020-07-16T22:29:27Z
dc.date.issued2020
dc.identifier.issn0268-3768
dc.identifier.doi10.1007/s00170-019-04597-y
dc.identifier.urihttp://hdl.handle.net/10072/395521
dc.description.abstractMetal additive manufacturing (MAM) has found emerging application in the aerospace, biomedical and defence industries. However, the lack of reproducibility and quality issues are regarded as the two main drawbacks to AM. Both of these aspects are affected by the distribution of defects (e.g. pores) in the AM part. Computed tomography (CT) allows the determination of defect sizes, shapes and locations, which are all important aspects for the mechanical properties of the final part. In this paper, data-constrained modelling (DCM) with multi-energy synchrotron X-rays is employed to characterise the distribution of defects in 316L stainless steel specimens manufactured with laser metal deposition (LMD). It is shown that DCM offers a more reliable method to the determination of defect levels when compared to traditional segmentation techniques through the calculation of multiple volume fractions inside a voxel, i.e. by providing sub-voxel information. The results indicate that the samples are dominated by a high number of small light constituents (including pores) that would not be detected under the voxel size in the majority of studies reported in the literature using conventional thresholding methods.
dc.description.peerreviewedYes
dc.languageEnglish
dc.language.isoeng
dc.publisherSpringer Science and Business Media LLC
dc.relation.ispartofpagefrom1601
dc.relation.ispartofpageto1615
dc.relation.ispartofissue5-6
dc.relation.ispartofjournalInternational Journal of Advanced Manufacturing Technology
dc.relation.ispartofvolume106
dc.subject.fieldofresearchMathematical Sciences
dc.subject.fieldofresearchInformation and Computing Sciences
dc.subject.fieldofresearchEngineering
dc.subject.fieldofresearchcode01
dc.subject.fieldofresearchcode08
dc.subject.fieldofresearchcode09
dc.titleNondestructive quantitative characterisation of material phases in metal additive manufacturing using multi-energy synchrotron X-rays microtomography
dc.typeJournal article
dc.type.descriptionC1 - Articles
dcterms.bibliographicCitationXavier, MS; Yang, S; Comte, C; Bab-Hadiashar, A; Wilson, N; Cole, I, Nondestructive quantitative characterisation of material phases in metal additive manufacturing using multi-energy synchrotron X-rays microtomography, International Journal of Advanced Manufacturing Technology, 2020, 106 (5-6), pp. 1601-1615
dcterms.licensehttp://creativecommons.org/licenses/by/4.0/
dc.date.updated2020-07-16T22:27:41Z
dc.description.versionVersion of Record (VoR)
gro.rights.copyright© The Author(s) 2019. his article is distributed under the terms of the Creative Commons Attribution 4.0 International License, which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.
gro.hasfulltextFull Text
gro.griffith.authorCole, Ivan


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