America Makes and Air Force Research Laboratory Name Awardees of Additive Manufacturing Challenge

The goal of the Challenge Series was to improve the accuracy of model predictions for metal AM, using INCONEL nickel-chromium alloy 625.

The goal of the Challenge Series was to improve the accuracy of model predictions for metal AM, using INCONEL nickel-chromium alloy 625.

America Makes and Air Force Research Laboratory, Materials & Manufacturing Directorate Structural Materials, Metals Branch (AFRL/RXCM), announce the awardees of the additive manufacturing (AM) Modeling Challenge Series with $235K to be divided among the awardees.

Launched in November 2019 and comprised of four individual challenges, the AFRL AM Modeling Challenge Series represented another innovative approach America Makes and AFRL are taking to advance the AM industry, the organizations note. The goal of the Challenge Series was to improve the accuracy of model predictions for metal AM, using INCONEL® nickel-chromium alloy 625 (IN625). Challenge participants were provided calibration and validation data sets needed to develop new models as it directly related to predicting the internal structure and resultant performance of AM metallic components.

“Going into the AFRL AM Modeling Challenge Series, we knew that the outcomes would potentially lead to significantly improved predictability and accuracy of models and simulations, and the qualification of AM process and materials,” says America Makes Executive Director John Wilczynski. “The awardees of these four challenges certainly made solid contributions. They improved our understanding of the micro- and macro-structure level variability that was needed to advance the accuracy of modeling and simulation for AM metal. We thank all those who participated and extend our congratulations to the awardees.”

The AFRL AM Modeling Challenge Series project team awardees are:

  • Challenge 1: Macro-scale Process-to-Structure Predictions
  • Dassault Systems Government Solutions Corp.
  • Challenge 2: Micro-scale Process-to-Structure Predictions
  • The Wing Kam Liu Group at Northwestern University
  • Challenge 3: Macro-scale Structure-to-Properties Predictions
  • QuesTek Innovations LLC
  • Challenge 4: Micro-scale Structure-to-Properties Predictions
  • University of Utah, Carnegie Mellon University, and Los Alamos National Laboratory

Sources: Press materials received from the company and additional information gleaned from the company’s website.

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