Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/106758
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dc.contributorDepartment of Mechanical Engineeringen_US
dc.creatorZhang, Qen_US
dc.creatorLuan, Xen_US
dc.creatorDhawan, Sen_US
dc.creatorPolitis, DJen_US
dc.creatorDu, Qen_US
dc.creatorFu, MWen_US
dc.creatorWang, Ken_US
dc.creatorGharbi, MMen_US
dc.creatorWang, Len_US
dc.date.accessioned2024-06-03T02:24:13Z-
dc.date.available2024-06-03T02:24:13Z-
dc.identifier.issn0749-6419en_US
dc.identifier.urihttp://hdl.handle.net/10397/106758-
dc.language.isoenen_US
dc.publisherPergamon Pressen_US
dc.rights© 2019 Elsevier Ltd. All rights reserved.en_US
dc.rights© 2019. This manuscript version is made available under the CC-BY-NC-ND 4.0 license http://creativecommons.org/licenses/by-nc-nd/4.0/.en_US
dc.rightsThe following publication Zhang, Q., Luan, X., Dhawan, S., Politis, D. J., Du, Q., Fu, M. W., ... & Wang, L. (2019). Development of the post-form strength prediction model for a high-strength 6xxx aluminium alloy with pre-existing precipitates and residual dislocations. International Journal of Plasticity, 119, 230-248 is available at https://doi.org/10.1016/j.ijplas.2019.03.013.en_US
dc.subjectAge-hardening behaviouren_US
dc.subjectConstitutive modellingen_US
dc.subjectPre-existing precipitatesen_US
dc.subjectResidual dislocationsen_US
dc.subjectUltra-fast heatingen_US
dc.titleDevelopment of the post-form strength prediction model for a highstrength 6xxx aluminium alloy with pre-existing precipitates and residual dislocationsen_US
dc.typeJournal/Magazine Articleen_US
dc.identifier.spage230en_US
dc.identifier.epage248en_US
dc.identifier.volume119en_US
dc.identifier.doi10.1016/j.ijplas.2019.03.013en_US
dcterms.abstractThe applications of lightweight and high strength sheet aluminium alloys are increasing rapidly in the automotive industry due to the expanding global demand in this industrial cluster. Accurate prediction of the post-form strength and the microstructural evolutions of structural components made of Al-alloys has been a challenge, especially when the material undergoes complex processes involving ultra-fast heating and high temperature deformation, followed by multi-stage artificial ageing treatment. In this research, the effects of pre-existing precipitates induced during ultra-fast heating and residual dislocations generated through high temperature deformation on precipitation hardening behaviour have been investigated. A mechanism-based post-form strength (PFS) prediction model, incorporating the flow stress model and age-hardening model, was developed ab-initio to predict strength evolution during the whole process. To model the stress-strain viscoplastic behaviour and represent the evolution of dislocation density of the material in forming process, constitutive models were proposed and the related equations were formulated. The effect of pre-existing precipitates was considered in the age-hardening model via introducing the complex correlations of microstructural variables into the model. In addition, an alternative time-equivalent method was developed to link the different stages of ageing and hence the prediction of precipitation behaviours in multi-stage ageing was performed. Furthermore, forming tests of a U-shaped component were performed to verify the model. It was found that the model is able to accurately predict the post-form strength with excellent agreement with deviation of less than 5% when extensively validated by experimental data. Therefore, the model is considered to be competent for predicting the pre-empting material response as well as a powerful tool for optimising forming parameters to exploit age hardening to its maximum potential in real manufacturing processes.en_US
dcterms.accessRightsopen accessen_US
dcterms.bibliographicCitationInternational journal of plasticity, Aug. 2019, v. 119, p. 230-248en_US
dcterms.isPartOfInternational journal of plasticityen_US
dcterms.issued2019-08-
dc.identifier.scopus2-s2.0-85064540201-
dc.description.validate202405 bcwhen_US
dc.description.oaAccepted Manuscripten_US
dc.identifier.FolderNumberME-0425-
dc.description.fundingSourceOthersen_US
dc.description.fundingTextInstitute of Automation Heilongjiang Academy of Sciencesen_US
dc.description.pubStatusPublisheden_US
dc.identifier.OPUS55329992-
dc.description.oaCategoryGreen (AAM)en_US
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