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dc.contributor.authorO'Toole, PI
dc.contributor.authorPatel, MJ
dc.contributor.authorTang, C
dc.contributor.authorGunasegaram, D
dc.contributor.authorMurphy, AB
dc.contributor.authorCole, IS
dc.date.accessioned2021-11-02T04:18:24Z
dc.date.available2021-11-02T04:18:24Z
dc.date.issued2021
dc.identifier.issn2214-8604en_US
dc.identifier.doi10.1016/j.addma.2021.102353en_US
dc.identifier.urihttp://hdl.handle.net/10072/409663
dc.description.abstractAt present, most multiscale simulation approaches to model the temperature evolution of the molten pool, and the resulting microstructure evolution for selective laser melting, assume an equilibrium freezing range and steady state solidification conditions. This is despite the solidification conditions being observed to be highly unsteady and non-equilibrium. These two assumptions lead to inaccurate predictions of the temperature evolution of the molten pool and thus microstructure predictions. To demonstrate this, an approach to scale-bridging computational models of the laser additive manufacturing process is presented, in which the temperature history is passed from a macroscale molten pool simulation to a microscale phase-field simulation. This linkage is achieved by volume mapping of the temperature field from the grid of the molten pool simulation to the grid of the microstructure simulation. To describe the system evolution at the scale of the molten pool, a computational fluid dynamics (CFD) method that captures the laser–metal interaction, vapour production, gas recoil pressure, fluid flow, surface tension, Marangoni flow, and heat conduction, convection, and radiation is applied. To capture the chemical kinetics of the phase-transition, a non-equilibrium CALPHAD-integrated phase-field (PF) model is applied. The discrepancy between the predictions of the solid front isotherm is quantified as ⩾100K for an Al-10Si alloy under the large observed cooling rate. This leads to a spatial discrepancy in the solidification front between the CFD model, which assumes equilibrium freezing behaviour, and the PF model, which does not, of approximately 10µm over 50µs in the present case. Under these conditions, present formulations of multiphase CFD cannot accurately predict the solidification behaviour because of the assumption of equilibrium at the solid–liquid interface. Strategies for reconciling this discrepancy for materials that exhibit rapid solidification under large thermal undercooling will need to be developed for multiscale simulation of additive manufacturing to advance.en_US
dc.description.peerreviewedYesen_US
dc.languageenen_US
dc.publisherElsevier BVen_US
dc.relation.ispartofpagefrom102353en_US
dc.relation.ispartofjournalAdditive Manufacturingen_US
dc.relation.ispartofvolume48en_US
dc.subject.fieldofresearchManufacturing engineeringen_US
dc.subject.fieldofresearchcode4014en_US
dc.titleMultiscale simulation of rapid solidification of an aluminium–silicon alloy under additive manufacturing conditionsen_US
dc.typeJournal articleen_US
dc.type.descriptionC1 - Articlesen_US
dcterms.bibliographicCitationO'Toole, PI; Patel, MJ; Tang, C; Gunasegaram, D; Murphy, AB; Cole, IS, Multiscale simulation of rapid solidification of an aluminium–silicon alloy under additive manufacturing conditions, Additive Manufacturing, 2021, 48, pp. 102353en_US
dc.date.updated2021-10-25T22:21:50Z
gro.hasfulltextNo Full Text
gro.griffith.authorCole, Ivan


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