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RISBayesian Calibration of Multiple Coupled Simulation Models for Metal Additive Manufacturing: A Bayesian Network Approach
Publisher: The American Society of Mechanical Engineers (ASME)
Abstract: Modeling and simulation for additive manufacturing (AM) are critical enablers for understanding process physics, conducting process planning and optimization, and streamlining qualification and certification. It is often ...
Uncertainty Propagation Analysis of Computational Models in Laser Powder Bed Fusion Additive Manufacturing Using Polynomial Chaos Expansions
Publisher: The American Society of Mechanical Engineers (ASME)
Abstract: Computational models for simulating physical phenomena during laser-based powder bed fusion additive manufacturing (L-PBF AM) processes are essential for enhancing our understanding of these phenomena, enable process ...
Bayesian Calibration and Uncertainty Quantification for a Physics-Based Precipitation Model of Nickel–Titanium Shape-Memory Alloys
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. ...
On the Fabrication of Defect-Free Nickel-Rich Nickel–Titanium Parts Using Laser Powder Bed Fusion
Publisher: The American Society of Mechanical Engineers (ASME)
Abstract: Laser powder bed fusion (L-PBF) additive manufacturing (AM) is an effective method of fabricating nickel–titanium (NiTi) shape memory alloys (SMAs) with complex geometries, unique functional properties, and tailored material ...