Probabilistic prediction of fatigue life scatter from surface and subsurface defect populations in additively manufactured metals

Aleksander Karolczuk

doi:10.1016/j.addma.2026.105236

Probabilistic prediction of fatigue life scatter from surface and subsurface defect populations in additively manufactured metals

2026-05-08

0

PRE

AI

A

Aleksander Karolczuk *

M

Marta Kurek

M

Mihiretu Gezahagn Ganta

A

Aleksander Hebda

P

P. Skubisz

M

M. Witkowska

DOI：10.1016/j.addma.2026.105236

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Abstract

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Fatigue life scatter in additively manufactured (AM) metals is controlled by competing crack initiation mechanisms associated with surface and subsurface defects. This work presents a probabilistic fatigue framework that predicts fatigue life distributions directly from measured defect populations, without introducing empirical life-scatter terms or predefined fatigue-active volumes. Surface and subsurface defects are modeled as independent Poisson point processes, and the upper tails of their size distributions are described using Generalized Pareto distributions fitted to X-ray computed tomography and optical profilometry data.

Keywords:

fatigue life scatter

additively manufactured metals

defect populations

probabilistic framework

crack initiation

Probabilistic prediction of fatigue life scatter from surface and subsurface defect populations in additively manufactured metals

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