Multiscale simulation of powder-bed fusion processing of metallic alloys

We present a computational framework for the simulations of powder-bed fusion of metallic alloys, which combines: (1) CalPhaD calculations of temperature-dependent alloy properties and phase diagrams, (2) macroscale finite element (FE) thermal simulations of the material addition and fusion, and (3)...

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Bibliographic Details
Main Authors: Boukellal, A.K (Author), Elahi, S.M (Author), Isensee, T. (Author), Romero, I. (Author), Tavakoli, R. (Author), Tourret, D. (Author)
Format: Article
Language:English
Published: Elsevier B.V. 2022
Subjects:
Online Access:View Fulltext in Publisher
LEADER 02662nam a2200457Ia 4500
001 10.1016-j.commatsci.2022.111383
008 220425s2022 CNT 000 0 und d
020 |a 09270256 (ISSN) 
245 1 0 |a Multiscale simulation of powder-bed fusion processing of metallic alloys 
260 0 |b Elsevier B.V.  |c 2022 
856 |z View Fulltext in Publisher  |u https://doi.org/10.1016/j.commatsci.2022.111383 
520 3 |a We present a computational framework for the simulations of powder-bed fusion of metallic alloys, which combines: (1) CalPhaD calculations of temperature-dependent alloy properties and phase diagrams, (2) macroscale finite element (FE) thermal simulations of the material addition and fusion, and (3) microscopic phase-field (PF) simulations of solidification in the melt pool. The methodology is applied to simulate the selective laser melting (SLM) of an Inconel 718 alloy using realistic processing parameters. We discuss the effect of temperature-dependent properties and the importance of accounting for different properties between the powder bed and the dense material in the macroscale thermal simulations. Using a two-dimensional longitudinal slice of the thermal field calculated via FE simulations, we perform an appropriately-converged PF solidification simulation at the scale of the entire melt pool, resulting in a calculation with over one billion grid points, yet performed on a single cluster node with eight graphics processing units (GPUs). These microscale simulations provide new insight into the grain texture selection via polycrystalline growth competition under realistic SLM conditions, with a level of detail down to individual dendrites. © 2022 Elsevier B.V. 
650 0 4 |a Calphad 
650 0 4 |a CalPhaD 
650 0 4 |a Computational modeling 
650 0 4 |a Computational modelling 
650 0 4 |a Computer graphics 
650 0 4 |a Finite element method 
650 0 4 |a Finite elements 
650 0 4 |a Graphics processing unit 
650 0 4 |a Macroscales 
650 0 4 |a Melt pool 
650 0 4 |a Metallic alloys 
650 0 4 |a Phase fields 
650 0 4 |a Phase-field 
650 0 4 |a Powder bed 
650 0 4 |a Powder-bed fusion 
650 0 4 |a Powder-bed fusion 
650 0 4 |a Program processors 
650 0 4 |a Selective laser melting 
650 0 4 |a Selective laser melting 
650 0 4 |a Solidification 
650 0 4 |a Textures 
650 0 4 |a Thermal simulations 
700 1 |a Boukellal, A.K.  |e author 
700 1 |a Elahi, S.M.  |e author 
700 1 |a Isensee, T.  |e author 
700 1 |a Romero, I.  |e author 
700 1 |a Tavakoli, R.  |e author 
700 1 |a Tourret, D.  |e author 
773 |t Computational Materials Science