Evaluation of a Modified Void Descriptor Function to Uniquely Characterize Pore Networks and Predict Fracture Location in Additively Manufactured Metals

Published

November 15, 2021

Author(s)

Dillon Watring, Jake Benzing, Orion Kafka, Li-Anne Liew, Newell Moser, John Erickson, Nik Hrabe, Ashley Spear

Abstract

Variations in additive manufacturing (AM) processing parameters can lead to variations in porosity, making it challenging to predict pore- or void-sensitive mechanical response in AM metals. A recently developed pore metric, the void descriptor function (VDF)—which accounts for pore locations, sizes (assuming spherical pores), and distances to the nearest free surface—was shown to improve the predictive capabilities of fracture location in ductile porous metals compared to predictions based on cross-section area reduction and maximum pore size. This work expands upon the original VDF by incorporating terms to account for non-spherical pore shapes and pore-pore interactions. The modified VDF is then validated against 120 computational fracture simulations of laser powder bed fused (L-PBF) 17-4 PH stainless steel tensile specimens and six mesoscale tensile specimens machined from L-PBF IN718. For the simulations, the modified VDF accurately predicts fracture location (within ±5 % tolerance) for 96 out of 120 specimens, representing a 5.5 % increase in accurate predictions compared to using the original VDF, a 65.5 % increase in accurate predictions compared to using the maximum cross-section area reduction, and a 62.7 % increase in accurate predictions compared to using the largest-pore location. In the experimental data set, the modified VDF accurately predicts the location of fracture (within ±5 % tolerance) in four out of six specimens compared to two out of six accurate predictions using the original VDF, maximum cross-section area reduction, or largest pore. Furthermore, the maximum VDF shows strong correlations with post-yield mechanical properties, suggesting that it could serve as a promising metric to assist with property predictions in AM metals.

Citation

ACTA Materialia

Volume

223

Issue

15

Pub Type

Journals

Download Paper

https://doi.org/10.1016/j.actamat.2021.117464

Local Download

Keywords

Inconel 718, Laser powder bed fusion, Ductile fracture, Tensile testing, X-Ray computed tomography, Porosity

Citation

Watring, D. , Benzing, J. , Kafka, O. , Liew, L. , Moser, N. , Erickson, J. , Hrabe, N. and Spear, A. (2021), Evaluation of a Modified Void Descriptor Function to Uniquely Characterize Pore Networks and Predict Fracture Location in Additively Manufactured Metals, ACTA Materialia, [online], https://doi.org/10.1016/j.actamat.2021.117464, https://tsapps.nist.gov/publication/get_pdf.cfm?pub_id=932308 (Accessed October 27, 2025)