Researchers at Oak Ridge National Laboratory (ORNL) and Lawrence Livermore National Laboratory, with collaborators from Los Alamos National Laboratory, National Institute of Standards and Technology and the University of Tennessee, Knoxville, are advancing the Exascale Additive Manufacturing project (ExaAM). ExaAM seeks to use exascale simulation to enable the design of additive manufacturing (AM) components with location-specific properties and the acceleration of performance.
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ExaAM aims to develop the Integrated Platform for Additive Manufacturing Simulation (IPAMS), a suite of exascale-optimized capabilities that directly incorporate microstructure evolution and the effects of microstructure within AM process simulation.
In AM, a geometric description of the part is processed into 2D slices. A feedstock material is melted, and the part is built layer by layer. In metal AM, the feedstock is often in wire or powder form, and the energy source is a laser or electron beam.
ExaAM focuses on powder bed processes in which each layer is approximately 50 µm. For example, a part that is 1 cm tall would require 200 layers, each requiring the spreading of new feedstock powder and one or more passes of the laser or electron beam to sinter and/or melt the powder in appropriate locations.
The ExaAM team has developed the ExaAM tool set to provide insights into how metals behave throughout the AM process (i.e., melting, solidifying) and how they perform—critical information for designing new parts as well as gauging their reliability and functionality.
The purpose of ExaAM is to model the AM manufacturing process—you’ve got heat being deposited, metal melting, metal solidifying, and then you’re going to the next layer with more metal remelting and then solidifying. So, you get all this thermal cycling, which makes for a very complicated process.
Being able to understand how that process gives you a microstructure and what that microstructure tells you about its properties—that’s what we’re trying to do. If you can do that accurately, then you could start printing 3D parts and qualify them for critical missions because you really do understand what it is you just made.
—Matt Bement, head of ORNL’s Scalable Algorithms and Coupled Physics group and ExaAM’s principal investigator
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