NSF award 2612716 · Johns Hopkins University

GOALI: Machine Learning Enabled Multiscale Modeling Platform and Virtual Sensing Digital Twin for Fatigue in Metals Additive Manufacturing (MAM)

Final report due

29 December 2030

in 1,533 days · The award ends on 31 August 2030.

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Extension request17 Jul 2030in 1368 days
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PAPPG 24-1: “at least 45 days prior to the end date”
No-cost extension notice21 Aug 2030in 1403 days
award ending 2030-08-31 · Research.gov
PAPPG 24-1: “at least ten calendar days prior to the end date”
Final report due29 Dec 2030in 1533 days
award ending 2030-08-31 · Research.gov
PAPPG 24-1: “no later than 120-days following the end date of the award”
Project outcomes report due29 Dec 2030in 1533 days
award ending 2030-08-31 · Research.gov
PAPPG 24-1: “no later than 120 days following the end date”
Award is closed out29 Dec 2030in 1533 days
award ending 2030-08-31 · Research.gov
PAPPG 24-1: “financially closed out 120 days after their expiration date”

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So the final report is due by 29 December 2030.

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Award card

Award number: 2612716
Period of support: 1 Sep 2026 – 31 Aug 2030
Amount: $900,000
Awardee: Johns Hopkins University, Baltimore, MD
Program: Special Initiatives, Mechanics of Materials and Str, AM-Advanced Manufacturing
Directorate: ENG

Abstract

Metal additive manufacturing (MAM), particularly laser-based powder bed fusion (L-PBF), has demonstrated significant potential for producing complex, high-performance components, yet its widespread industrial adoption remains constrained by challenges in qualification and certification (Q&C). These challenges arise from uncertainties in fatigue performance caused by process-induced variability in microstructure and…

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