Additive manufacturing (AM) is revolutionizing manufacturing, allowing complex parts to be constructed that are not readily fabricated by traditional techniques. Although there has been significant interest and investment in AM, the fraction of this investment devoted to modeling and simulation is relatively small and is not focused on developing high-fidelity predictive models but instead on reduced-order models for industry use. The Exascale Additive Manufacturing project (ExaAM) represents a unique opportunity to use exascale simulation to enable the design of AM components with location-specific properties and the acceleration of performance certification.

Project Details

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 physical processes involved in AM are similar to those of welding—a field with decades’ worth of experimental, modeling, simulation, and characterization research. Although calibrated and approaching predictive capability, the simulation tools developed for welding and other similar processes are unfortunately inadequate for AM processes, as demonstrated by the inability to predict the failure rate for new AM parts, which can be as high as 80%. This is believed to be largely because the process-structure-property-performance relationship is traditionally modeled in an uncoupled manner, relying on tabular databases that cannot adequately capture the implicit, dynamic, nonequilibrium nature of AM processes.

One goal of ExaAM is to remove those limitations by integrating high-fidelity mesoscale simulations within continuum process simulations to determine the microstructure and properties by using local conditions. Sub-mesoscale physics is upscaled from detailed science simulations. Typically, thermomechanical finite element models are employed at the macroscopic part scale; finite volume or finite element models are used at millimeter scales for fluid dynamics and heat transfer to capture the melt pool dynamics and solidification; mesoscale approaches (e.g., discrete elements, cellular automata, kinetic Monte Carlo, or phase-field models) are used at the micron scale to simulate melting, solidification, and microstructure formation; and polycrystal plasticity models are used to develop the microscale mechanical property relationships.

The ExaAM IPAMS suite is a collection of simulation capabilities for performing process-aware performance modeling of additively manufactured parts by using locally accurate properties predicted from microstructures that develop based on local processing conditions. ExaAM will demonstrate this capability by simulating the complex bridge structure developed for the 2018 National Institute of Standards and Technology AM-Bench Conference, known as AMB2018-01. The simulation will be performed where experimental observations were taken (e.g., “cut locations” for transverse and longitudinal scanning electron microscope [SEM] specimens for microstructure images).

This challenge problem will be demonstrated on the exascale computer as a workflow involving three stages. First, a continuum powder layer melt-refreeze model, AdditiveFOAM, is used to simulate the laser scan pattern for several layers at a particular location within the part. Next, the resulting thermal histories at this location are used by ExaCA to drive simulations of the microstructure evolution. These microstructures, unique to the AM process and requiring careful validation with experimental observations, are then used by ExaConstit, a finite element crystal plasticity model which resolves the grain structure and behavior of individual grains to predict localized, continuum-scale stress-strain responses.  The demonstration of this process-to-structure-to-properties workflow is a key enabler for accelerating the certification of parts produced with an AM process.

Principal Investigator(s):

Matt Bement, Oak Ridge National Laboratory; James Belak, Lawrence Livermore National Laboratory; Chris Newman, Los Alamos National Laboratory


Oak Ridge National Laboratory; Lawrence Livermore National Laboratory; Los Alamos National Laboratory; National Institute of Standards and Technology; University of Tennessee, Knoxville; Purdue University; Georgia Institute of Technology, University of South Carolina, Penn State University; University of California, Davis; University of California, Los Angeles

Progress to date

  • Created several new exascale-ready open-source simulation capabilities for modeling the AM process leveraging other Exascale Computing Project (ECP) projects, including polycrystal plasticity (ExaConstit) built on MFEM and using RAJA, a new material point method capability for powder dynamics (PicassoMPM) built on CoPA/Cabana, and a new cellular automata capability for microstructure development during solidification (ExaCA) using Kokkos.
  • Predictions of melt pool geometry from AdditiveFOAM, microstructure evolution from ExaCA, and constitutive response have been validated using NIST AMBench 2018-01 experimental data.
  • Integrated workflow using EnTK has been demonstrated on Summit and Crusher (and soon Frontier)
  • ExaAM components are being adopted by the Advanced Materials and Manufacturing Technologies Office (AMMTO) Digital Factory efforts at ORNL’s Manufacturing Demonstration Facility, as well as by NNSA projects at LLNL.

ExaAM is integrating multiple physics applications to enable an exascale-capable, multiscale, multiphysics simulation tool kit that can be used to accelerate the certification of AM processes.

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