Submission Deadline: January 31, 2020

Air Force Research Laboratory (AFRL)
Additive Manufacturing Modeling Challenge Series

Four Challenges to Predict the Internal Structure and
Resultant Performance of Metallic Components Produced by AM

America Makes and Air Force Research Laboratory, Materials & Manufacturing Directorate Structural Materials, Metals Branch (AFRL/RXCM), proudly announce an additive manufacturing (AM) Modeling Challenge series, comprised of four individual Challenges, with a total of $150K to be divided among awardees.

For Complete Details Visit the Challenge Website on GitHub

Challenge Data

For each challenge listed below, there are links to the Problem Statement, Dataset, and Answer Template. The Dataset must be accessed through Globus where individual files from the dataset can be transferred to a location of your choice. If the Dataset link below takes you to ‘Error Fetching Search Record’ page, make sure you are signed into Globus AND click the Login link in the upper right hand corner to sign in using your Globus account information.

To access the datasets, click the “Globus” link under the “Get the Data” section, which should redirect you to Globus’ web application. Data may be transferred from Globus to your computer by setting up an endpoint. Documentation on establishing a Globus endpoint for each operating system is found here: MacOsLinuxWindows. Once an enpoint is established, the Globus web application is used to conduct the download. Information on transferring data from Globus is found here.

Get Started

Step 1
Create a Globus Account

Create a free Globus account using institutional credentials, Google ID or ORCID. Globus is required to access the datasets.

Step 2
Join Globus Group

Join the Globus Group to gain access to the AFRL AM Modeling Challenge Series data packages. Joining the group does not obligate you to participate in the challenge, but is required to obtain the data packages.

Step 3
Subscribe for Updates

Subscribe here to receive email updates about the AFRL AM Modeling Challenge Series – including information on dataset availability. (Contact information collected here will only be used to send pertinent updates for the challenges.)

For Complete Details Visit the Challenge Website on GitHub