Additive Manufacturing Benchmarks 2022 (AM-Bench 2022): Melt-Pool Scale I
Program Organizers: Brandon Lane, National Institute of Standards and Technology; Lyle Levine, National Institute of Standards and Technology
Tuesday 3:30 PM
August 16, 2022
Room: Regency Ballroom I & II
Location: Hyatt Regency Bethesda
Session Chair: Jordan Weaver, National Institute Of Standards And Technology
3:30 PM Invited
Optical Metrology of Laser-matter Interactions in LPBF: Challenges and Opportunities: David Deisenroth1; 1National Institute of Standards and Technology
Recent studies in optical metrology of laser powder bed fusion (LPBF) indicate that there remains insufficient understanding of the optical phenomena that occur during laser-matter interaction, which limits the accuracy of non-contact measurements for multiphysics model validation applications. The primary causes of measurement inaccuracy appear to be related to the interaction of process byproducts (including metal vapor, condensate, and ejecta) with light propagating to and from the melt pool. To better understand, quantify, and mitigate the deleterious effects of LPBF byproducts on the melting process and optical measurements thereof, a highly configurable benchtop setup is under development in conjunction with the NIST Additive Manufacturing Metrology Testbed. The new experimental setup additionally aims to advance research in laser coupling, laser spot size metrology, and the effects of shield gas flow distributions. This presentation outlines the known challenges and opportunities while inviting feedback from the modeling community.
4:00 PM
Simultaneous Computational Fluid and Particle Dynamics Simulation for Laser Powder Bed Fusion: Wenda Tan1; 1The University of Michigan
Laser Powder Bed Fusion is a mainstream Additive Manufacturing process for metals. The process is dynamics with diverse physics involved in a fully coupled manner. To quantitatively capture the dynamic phenomena in the process, a multi-physics model has been established. A Computational Fluid Dynamics (CFD) module is included to concurrently treat the compressible/incompressible flows in the gas region and the melt pool, and a Computational Particle Dynamics module based on the Discrete Element Method is included to track the powder motion as driven by the gas-powder and powder-powder interaction forces. The model predictions of keyhole dimension and powder speed are found to be consistent with the measurements via the synchrotron X-ray imaging results. The simulation results of the laser absorption, mechanical driving forces, vapor gas flow structure, and powder status are further leveraged to understand the complex physics during the process.
4:20 PM
X-ray Image Based Ray-tracing Model for Absorption Prediction in Laser Melting: Zhengtao Gan1; 1Northwestern University
Leveraging in-situ synchrotron x-ray imaging measurements of vapor depression in laser-based additive manufacturing, we develop an image-based multiphysics model, which promises to evaluate laser energy absorptivity directly using x-ray images as input. A deep learning algorithm is used to automatically extract the liquid-gas interface from the x-ray images. A ray-tracing method is then used to predict the laser absorptivity based on the detected liquid-gas interface. The predicted results are compared with real-time energy absorption measurements using in-situ integrating sphere radiometry. The developed model is beneficial to generate absorptivity data for understanding the effect of processing on energy absorption mechanisms. Moreover, the developed model can be regarded as a high-fidelity heat source model. It can be combined with other computational models for accurate simulations of melt pool dynamics, defect formation, and solidification microstructure in the additive manufacture of materials.
4:40 PM
Pseudo-function of Laser Heat Input for Computational Metal Additive Manufacturing: Hamedreza Hosseinzadeh1; Mark Horstemeyer2; 1University of South Carolina; 2Liberty University
Process modeling of metal additive manufacturing is a multiscale multiphysics simulation, and it needs a massive CPU time if physical details are involved. According to the simulation goal, we can apply some meaningful assumptions to handle the CPU usage. One of the subjects is laser heat input physics and the related physical consequences. This research has developed a pseudo-function for the laser heat input with melt-pool dynamics and metal evaporation physics analytically, meaning as a correction term to the laser heat input function. With this pseudo-function, CPU time could be dramatically reduced. The melt-pool/HAZ depth, residual stress, total deformation, and local cooling rates could be simulated without directly stimulating the melt-pool dynamics and metal evaporation effects. This function will be efficient for design proposes and accelerating technical innovations in metal additive manufacturing with the powder bed fusion method.