SYMPOSIA PAPER Published: 05 June 2020

Probabilistic Framework for Defect Tolerant Fatigue Assessment of Additively Manufactured Parts Applied to a Space Component


The ability to predict the fatigue resistance of parts produced by additive manufacturing (AM) is a current and relevant open issue. Material fatigue resistance often is characterized by large scatter and poor repeatability, mostly because of the presence of manufacturing defects. Although industries would obtain a great benefit from the application of AM to structural and critical parts, the current lack of knowledge, standards, acceptability criteria, and software available hinder most of these applications. In this work, the fracture mechanics-based software ProFACE (Probabilistic Fatigue Assessment of Components with Defects) has been applied to a space component, demonstrating its capability to analyse typical AM issues in light of a robust fatigue assessment for design and qualification, and discussing the impact of the most relevant variables on the reliability of the part.

Author Information

Romano, Simone
Politecnico di Milano, Milan, IT
Beretta, Stefano
Politecnico di Milano, Milan, IT
Miccoli, Stefano
Politecnico di Milano, Milan, IT
Gschweitl, Michael
RUAG Space, Zurich, CH
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Developed by Committee: F42
Pages: 526–539
DOI: 10.1520/STP162020180112
ISBN-EB: 978-0-8031-7687-4
ISBN-13: 978-0-8031-7686-7