Top

Integrating Materials and Manufacturing Innovation

Published in:

03-06-2021 | Thematic Section: Metal Additive Manufacturing Modeling Challenge Series 2020

AFRL Additive Manufacturing Modeling Challenge Series: Overview

Authors: Marie E. Cox, Edwin J. Schwalbach, Ben J. Blaiszik, Michael A. Groeber

Published in: Integrating Materials and Manufacturing Innovation | Issue 2/2021

Activate our intelligent search to find suitable subject content or patents.

search-config

AI-assisted search

Off

Abstract

The Air Force Research Laboratory Additive Manufacturing Modeling Challenge series launched in November 2019 was devised as a means to assess the Additive Manufacturing modeling community’s ability to predict, in a locally resolved fashion, details of the structure and subsequent mechanical performance of metallic materials fabricated with a laser powder bed fusion process. This communication gives a general overview of the challenge series implementation, results, and workshop.

next article AFRL Additive Manufacturing Modeling Series: Challenge 4, 3D Reconstruction of an IN625 High-Energy Diffraction Microscopy Sample Using Multi-modal Serial Sectioning

Available only for authorised users

Groeber M, Schwalbach E, Musinski W, Shade P, Donegan S, Uchic M, Daniel S, Turner T, Miller J (2018) A preview of the US air force research laboratory additive manufacturing modeling challenge series. JOM 70:441–444CrossRef

Chuang AC, Park J-S, Shade PA, Schwalbach EJ, Groeber MA, Musinski WD AFRL additive manufacturing modeling series: challenge 1, characterization of residual strain distributions in additively-manufactured metal parts using energy dispersive diffraction. Integr Mater Manuf Innov (In review)

Schwalbach EJ, Chapman MG, Groeber MA AFRL additive manufacturing modeling series: challenge 2, microscale process to structure data description. Integr Mater Manuf Innov (In review)

Musinski W et al AFRL additive manufacturing modeling series: challenge 3, macroscale structure to properties data description. Integr Mater Manuf Innov (In review)

Menasche DB, Musinski WD, Obstalecki M, Shah MN, Donegan SP, Bernier JV, Kenesei P, Park J-S, Shade PA AFRL additive manufacturing modeling series: challenge 4, microscale structure to properties data description—high energy diffraction microscopy. Integr Mater Manuf Innov (In review)

Chapman MG, Shah MN, Donegan SP, Scott JM, Menasche DB, Uchic MD AFRL additive manufacturing modeling series: challenge 4, 3D reconstruction of an IN625 high-energy diffraction microscopy sample using multi-modal serial sectioning. Integr Mater Manuf Innov (In review)

Shade PA, Blank B, Schuren JC, Turner TJ, Kenesei P, Goetze K, Suter RM, Bernier JV, Li SF, Lind J, Lienert U, Almer J (2015) A rotational and axial motion system load frame insert for in situ high energy x-ray studies. Rev Sci Instrum 86:093902. https://doi.org/10.1063/1.4927855CrossRef

Uchic M, Groeber M, Shah M, Callahan P, Shiveley A, Scott M, Chalman M, Spowart J (2012) An automated multi-modal serial sectioning system for characterization of grain scale microstructures in engineering materials. In: proceedings of the 1st international conference on 3d materials science. https://doi.org/10.1007/978-3-319-48762-5_30

Musinski WD, Shade PA, Park J-S, Chuang AC, Schwalbach EJ, Miller JD, Groeber MA, Cox ME (2019) AFRL AM modeling challenge series: challenge 1 data package. Mater Data Facility. https://doi.org/10.18126/8jfl-i4d8CrossRef

10.

Groeber MA, Schwalbach EJ, Donegan SP, Uchic MD, Shade PA, Musinski WD, Miller J, Turner TJ, Sparkman D, Cox ME (2018) AFRL AM modeling challenge series: challenge 2 data package. Mater Data Facility. https://doi.org/10.18126/M27H1ZCrossRef

11.

Groeber M, Schwalbach E, Donegan S, Uchic M, Shade P, Musinski W, Miller J, Turner T, Sparkman D, Cox M (2019) AFRL AM modeling challenge series: challenge 3 data package. Mater Data Facility. https://doi.org/10.18126/M26639CrossRef

12.

Shade PA, Muskinski WD, Shah MN, Uchic MD, Donegan SP, Chapman MG, Park J-S, Bernier JV, Kenesei P, Menasche DB, Obstalecki M, Schwalbach EJ, Miller JD, Groeber MA, Cox ME (2019) AFRL AM modeling challenge series: challenge 4 data package. Mater Data Facility. https://doi.org/10.18126/K5R2-32IUCrossRef

13.

Cox M (2019) Air force research laboratory (AFRL) additive manufacturing (AM) modeling challenge series. Available: https://materials-data-facility.github.io/MID3AS-AM-Challenge/

14.

Blaiszik B, Ward L, Schwarting M, Gaff J, Chard R, Pike D, Chard K, Foster I (2019) A data ecosystem to support machine learning in materials science. MRS Commun 9(4):1125–1133. https://doi.org/10.1557/mrc.2019.118CrossRef

15.

Blaiszik B, Chard K, Ananthakrishnan R, Tueke S, Foster I (2016) The materials data facility: data services to advance materials science research. JOM 8(68):2045–2052. https://doi.org/10.1007/s11837-016-2001-3CrossRef

16.

America Makes (2019) America makes and air force research laboratory announce an additive manufacturing modeling challenge series. Available: https://www.americamakes.us/america-makes-and-afrl-announce-am-modeling-challenge/. Accessed 25 Jan 2021

17.

America Makes (2020) AFRL AM challenge series improved understanding of the internal structure and resultant performance of metallic components produced by AM. Available: https://www.americamakes.us/america-makes-and-air-force-research-laboratory-announce-awardees-of-the-additive-manufacturing-modeling-challenge-series/. Accessed 25 Jan 2021

Title: AFRL Additive Manufacturing Modeling Challenge Series: Overview
Authors: Marie E. Cox
Edwin J. Schwalbach
Ben J. Blaiszik
Michael A. Groeber
Publication date: 03-06-2021
Publisher: Springer International Publishing
Published in: Integrating Materials and Manufacturing Innovation / Issue 2/2021
Print ISSN: 2193-9764
Electronic ISSN: 2193-9772
DOI: https://doi.org/10.1007/s40192-021-00215-6

Springer Professional

AFRL Additive Manufacturing Modeling Challenge Series: Overview

Abstract

Premium Partners

Springer Professional

Abstract

Please log in to get access to your license.

Other articles of this Issue 2/2021

Microstructure Image Classification: A Classifier Combination Approach Using Fuzzy Integral Measure

The AFRL Additive Manufacturing Modeling Challenge: Predicting Micromechanical Fields in AM IN625 Using an FFT-Based Method with Direct Input from a 3D Microstructural Image

A Comparative Study of Layer Heating and Continuous Heating Methods on Prediction Accuracy of Residual Stresses in Selective Laser Melted Tube Samples

An Active Learning Approach for the Design of Doped LLZO Ceramic Garnets for Battery Applications

An Open Combinatorial Diffraction Dataset Including Consensus Human and Machine Learning Labels with Quantified Uncertainty for Training New Machine Learning Models

Integrated Computational Design of Three-Phase Mo–Si–B Alloy Turbine Blade for High-Temperature Aerospace Applications

Premium Partners