Additive Manufacturing Benchmarks 2022 (AM-Bench 2022): Monday Plenary
Program Organizers: Brandon Lane, National Institute of Standards and Technology; Lyle Levine, National Institute of Standards and Technology
Monday 8:00 AM
August 15, 2022
Room: Regency Ballroom I & II
Location: Hyatt Regency Bethesda
Session Chair: Gregory Wagner, Northwestern University
8:00 AM Introductory Comments
8:30 AM Plenary
The ExaAM Challenge Problem: AM Process Modeling at the Fidelity of the Microstructure: James Belak1; John Turner2; 1Lawrence Livermore National Laboratory; 2UT-Battelle / Oak Ridge National Lab
With the Exascale computers arriving at the DOE facilities, the ExaAM project will soon run its challenge problem. The ExaAM challenge problem is based on the NIST AMBench experimental builds and further characterization. These experiments both guide the model development and provide validation for the simulations. The project includes an integration of all the computational components of the AM process, where each component itself is an exascale simulation. What has emerged is that Exascale Computing will enable AM process modeling at the fidelity of the microstructure. This means tight coupling of Process-Structure-Property calculations. Macroscopic continuum codes (OpenFOAM) are used to simulation the metal melt-refreeze, within which mesoscopic codes (ExaCA, PFM) are used to simulate the development of material microstructure. This microstructure is then used by crystal plasticity codes (ExaConstit) to calculate local material properties. We present our coupled exascale simulation environment for additive manufacturing and its application to AM builds.
9:00 AM Plenary
Combining Modeling & Measurement in Metals Additive: Anthony Rollett1; Joseph Pauza1; Carter Cocke2; Ricardo Lebensohn3; Ashley Spear2; 1Carnegie Mellon University; 2University of Utah; 3Los Alamos National Laboratory
Building workflows to predict outcomes in additive manufacturing requires simulation methods that accept input that is known to affect the outcome and run in a reasonable time. An example will be discussed for predicting the microstructure that is formed in powder bed fusion printing. Validating the results against experimental data required judgment about which measures of grain shape and orientation are reasonable statistical measures to use because of the variability of outcome in both experiment and simulation. In another example, the Air Force Simulation Challenges in which predicted (tensor) elastic strain values in certain grains via use of a crystal plasticity spectral code showed excellent agreement for the elastic portion but widening disagreement for the plastic part. The sample was printed in alloy 625 and the experimental data was a combination of stress-strain and high energy diffraction microscopy (HEDM). Reduced order models will be discussed briefly.
9:30 AM Plenary
Energy Efficiency of Polymer Additive Manufacturing by Material Extrusion: David Kazmer1; Amy Peterson1; Austin Colon1; 1UMass Lowell
The energy efficiency of material extrusion processes used in polymer additive manufacturing is characterized and compared to the theoretical minimum specific energy required for polymer processing. While AM is believed to provide improved environmental sustainability relative to conventional net shape manufacturing processes, energy efficiencies are shockingly low, less than 10% relative to the theoretical minimum. Power and energy usage is acquired for both filament-based and pellet-based extruders producing tensile specimens with process plans based on concentric in-fills and a hybrid molding/printing process referred to as injection printing. Variance analysis is performed explaining the sources of inefficiency and the need for improved melting capacity and process planning. The results are also compared to cold runner and hot runner injection molding of tensile bars indicating preferred sustainability strategies.
10:00 AM Break