2022
DOI: 10.1016/j.ijheatmasstransfer.2021.122492
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Investigation of temperature distribution and solidification morphology in multilayered directed energy deposition of Al-0.5Sc-0.5Si alloy

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Cited by 20 publications
(11 citation statements)
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“…where G is the temperature gradient, R is the solidification rate, N 0 is the number of available nucleation sites, and a and n are material-dependent constants that describe the relation between solidification rate and undercooling. The typical G and R for the DED process were reported to be in the ranges of 10 4 - 10 7 K/m and 10 −4 -10 −1 m/s, respectively [119][120][121][122]. Equation (5) indicates that the combination of low G and high R, together with the abundance of the nucleation sites, could promote the formation of randomly oriented equiaxed grains, which is illustrated by the solidification diagram displayed in Figure 4(b) [117].…”
Section: Grain Morphologymentioning
confidence: 98%
See 1 more Smart Citation
“…where G is the temperature gradient, R is the solidification rate, N 0 is the number of available nucleation sites, and a and n are material-dependent constants that describe the relation between solidification rate and undercooling. The typical G and R for the DED process were reported to be in the ranges of 10 4 - 10 7 K/m and 10 −4 -10 −1 m/s, respectively [119][120][121][122]. Equation (5) indicates that the combination of low G and high R, together with the abundance of the nucleation sites, could promote the formation of randomly oriented equiaxed grains, which is illustrated by the solidification diagram displayed in Figure 4(b) [117].…”
Section: Grain Morphologymentioning
confidence: 98%
“…Aside from the residual stress-based studies, significant attention has been given to the numerical methods that provide the predictive capability of the microstructural evolution in AB DED samples, especially the grain morphologies [114,121,[327][328][329]. This is achieved through the coupling of temperature field evolution in the simulated melt pool to reliable criteria [118,123] on CET in metallic melts.…”
Section: Modelling and Simulation Studies On Dedmentioning
confidence: 99%
“…A proposed fin modeling-based temperature distribution prediction developed by Basil J. Paudel et al [24] can anticipate the onset of the substrate-affected zone during the DED process. Amit Kumar Singh et al [25] and Claire Bruna-Rosso et al [26] computed the thermal cycle and melt pool size for different laser parameters and verified by experiment. Their model can fairly predict the transition in the melt pool with varying input parameters.…”
Section: Introductionmentioning
confidence: 96%
“…Nevertheless, the poor printability of Al is related to the inherent characteristics of Al alloy and the LAM process (e.g. high thermal conductivity and high laser reflectivity, strong oxidizing sensitivity, high hydrophilicity, poor powder fluidity, high thermal expansivity and high cooling rate [31][32][33]). The near-eutectic Al-Si alloy is relatively mature and reliable for LAM processing due to its outstanding printability [34][35][36].…”
Section: Introductionmentioning
confidence: 99%