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About this Abstract
Meeting 2026 TMS Annual Meeting & Exhibition
Symposium Verification, Calibration, and Validation Approaches in Modeling the Mechanical Performance of Metallic Materials
Presentation Title 2025 NIST Additive Manufacturing Benchmark Fatigue Challenge to Improve Computational Prediction Techniques: Prediction Trends
Author(s) Newell Moser, Jake Benzing, Nicholas Derimow, Orion Kafka, Alec Saville, Edward Glaessgen, John Newman, Sai Yeratapally, Joshua Pribe, George Weber, Sang-Hyon Chu, Richard Rogers, Cassidy Allen, Edwin Glaubitz, Nik Hrabe
On-Site Speaker (Planned) Newell Moser
Abstract Scope AM Bench is a series of additive manufacturing (AM) benchmark measurements and challenge problems with the primary goal of enabling modelers to test their simulations against rigorous AM benchmark data. This talk will present a summary of the submissions and findings from the AMB2025-03 challenge, a novel component of the AM Bench 2025 program that explored the prediction of fatigue-related properties in Ti-6Al-4V. Rotating bending fatigue specimens were manufactured via laser powder bed fusion (PBF-LB); half of them underwent non-standard hot isostatic pressing (nicknamed 800HIP) while the other half followed the same heat treatment but in a vacuum (nicknamed 800VAC). Participants were asked to predict fatigue properties of the 800VAC specimens given fatigue information of the 800HIP specimens. Furthermore, certain measurement data related to both conditions were made available, including details about the microstructure and internal porosity.
Proceedings Inclusion? Planned:
Keywords Additive Manufacturing, Modeling and Simulation, Titanium

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2025 NIST Additive Manufacturing Benchmark Fatigue Challenge to Improve Computational Prediction Techniques: Measurement Description
2025 NIST Additive Manufacturing Benchmark Fatigue Challenge to Improve Computational Prediction Techniques: Prediction Trends
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