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Open AccessJournal ArticleDOI

Uncertainty Analysis of Microsegregation during Laser Powder Bed Fusion

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TLDR
In this article, the authors identify the uncertainty sources and frequency densities of the quantity of interest in the solidification regime relevant to additive manufacturing and use correlation, regression, and surrogate model analyses to quantify the contribution of different sources of uncertainty to the QoI variability.
Abstract
Quality control in additive manufacturing can be achieved through variation control of the quantity of interest (QoI). We choose in this work the microstructural microsegregation to be our QoI. Microsegregation results from the spatial redistribution of a solute element across the solid-liquid interface that forms during solidification of an alloy melt pool during the laser powder bed fusion process. Since the process as well as the alloy parameters contribute to the statistical variation in microstructural features, uncertainty analysis of the QoI is essential. High-throughput phase-field simulations estimate the solid-liquid interfaces that grow for the melt pool solidification conditions that were estimated from finite element simulations. Microsegregation was determined from the simulated interfaces for different process and alloy parameters. Correlation, regression, and surrogate model analyses were used to quantify the contribution of different sources of uncertainty to the QoI variability. We found negligible contributions of thermal gradient and Gibbs-Thomson coefficient and considerable contributions of solidification velocity, liquid diffusivity, and segregation coefficient on the QoI. Cumulative distribution functions and probability density functions were used to analyze the distribution of the QoI during solidification. Our approach, for the first time, identifies the uncertainty sources and frequency densities of the QoI in the solidification regime relevant to additive manufacturing.

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Journal ArticleDOI

Metal Additive Manufacturing: A Review

TL;DR: The state-of-the-art of additive manufacturing (AM) can be classified into three categories: direct digital manufacturing, free-form fabrication, or 3D printing as discussed by the authors.
Book

Applied Statistics and Probability for Engineers

TL;DR: Montgomery and Runger's Engineering Statistics text as discussed by the authors provides a practical approach oriented to engineering as well as chemical and physical sciences by providing unique problem sets that reflect realistic situations, students learn how the material will be relevant in their careers.
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Bayesian Calibration of computer models

TL;DR: A Bayesian calibration technique which improves on this traditional approach in two respects and attempts to correct for any inadequacy of the model which is revealed by a discrepancy between the observed data and the model predictions from even the best‐fitting parameter values is presented.
Journal ArticleDOI

Additive manufacturing of metals

TL;DR: In this paper, the authors describe the complex relationship between additive manufacturing processes, microstructure and resulting properties for metals, and typical microstructures for additively manufactured steel, aluminium and titanium are presented.
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Stability of a Planar Interface During Solidification of a Dilute Binary Alloy

TL;DR: In this article, the stability of a moving planar liquid-solid interface during unidirectional freezing of a dilute binary alloy is theoretically investigated by calculating the time dependence of the amplitude of a sinusoidal perturbation of infinitesimal amplitude introduced into the planar shape.
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