Uncertainty Quantification of Powder Bed Fusion process simulation

Uncertainty Quantification for Additive Manufacturing of metals are the key to producing objects with complex geometries and with remarkably high mechanical performance. Only a few examples have been reported in the literature on UQ in AM and are mostly based on production level experiments, but the interest of UQ technology for validation of computational models is rapidly growing. The complexities of using UQ analysis for AM based on a computational model are linked to unknown and uncertain parameters and to the intrinsic uncertainty of the computational model. The aim of this work is the estimation of unknown or uncertain process parameters Powder Bed Fusion Additive Manufacturing (PBF-AM) by means of UQ techniques of a computational model of beam in Inconel 625, using a coupled thermo-mechanical analysis in which it is conducted the structural analysis, for each phase, at the end of the thermal analysis.  To this end, three levels of meshes have been used (Coarse, Medium and Fine) for the thermo-mechanical analyses. For uncertainty quantification analysis a surrogate model calibrated by L. Tamellini and C. Piazzola was used, which is recommended to validate the response of the thermo-mechanical model of the beam.  For the FEM simulation of the PBF process the Ansys Additive Wizard extension was used; precisely the Mechanical and Workbench applications of Ansys® 2021-R2 were used for our goal. Numerical results are compared with the AM-Bench experimental data from the National Institute of Standards and Technologies (NIST). To further reduce the time required to complete the high number of FEM simulations required to perform a thorough UQ analysis, we have installed Ansys on an HPC server form A3cube S.r.l. provided with AMD EPYC 7702 @ 1.67GHz and 376GB di RAM.

March 3, 2022

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