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    Probabilistic Printability Maps for Laser Powder Bed Fusion Via Functional Calibration and Uncertainty Propagation 

    Source: Journal of Computing and Information Science in Engineering:;2024:;volume( 024 ):;issue: 011:;page 111001-1
    Author(s): Wu, Nicholas; Whalen, Brendan; Ma, Ji; Balachandran, Prasanna V.
    Publisher: The American Society of Mechanical Engineers (ASME)
    Abstract: In this work, we develop an efficient computational framework for process space exploration in laser powder bed fusion (LPBF) based additive manufacturing technology. This framework aims to find suitable processing conditions ...
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    Bayesian Calibration and Uncertainty Quantification for a Physics-Based Precipitation Model of Nickel–Titanium Shape-Memory Alloys 

    Source: Journal of Manufacturing Science and Engineering:;2017:;volume( 139 ):;issue: 007:;page 71002
    Author(s): Tapia, Gustavo; Johnson, Luke; Franco, Brian; Karayagiz, Kubra; Ma, Ji; Arroyave, Raymundo; Karaman, Ibrahim; Elwany, Alaa
    Publisher: The American Society of Mechanical Engineers (ASME)
    Abstract: Uncertainty quantification (UQ) is an emerging field that focuses on characterizing, quantifying, and potentially reducing, the uncertainties associated with computer simulation models used in a wide range of applications. ...
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