Transferability of anomaly data to fatigue properties of PBF-LB AlSi10Mg parts with different volumes

IF 5.7 2区材料科学 Q1 ENGINEERING, MECHANICAL International Journal of Fatigue Pub Date : 2025-02-10 DOI:10.1016/j.ijfatigue.2025.108852

G. Minerva , M. Awd , A. Koch , F. Walther , S. Beretta

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Abstract

Fatigue of metallic materials produced by Laser Powder Bed Fusion has been extensively studied for both standard testing specimens and application relevant components. However, fatigue properties of specimens and components suffer from large scatter, mainly due to the presence of volumetric anomalies, residual stresses and surface roughness. Therefore, the transferability from specimens to components is still an open point that must be addressed. In this work, fatigue properties of notched components are investigated and compared with the standard specimens. Then, the properties of the components are inferred from the standard specimens’ data using simple models. The maxima anomalies’ distributions are estimated with a competing risk approach using Machine learning-assisted Extreme Value Statistics. Finally, the S-N curves of the investigated components, predicted employing the Shiozawa model for finite life and the El-Haddad model for the fatigue limit, closely matched the experimental results.

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来源期刊

International Journal of Fatigue 工程技术-材料科学：综合

CiteScore

10.70

自引率

21.70%

发文量

619

审稿时长

58 days

期刊介绍： Typical subjects discussed in International Journal of Fatigue address: Novel fatigue testing and characterization methods (new kinds of fatigue tests, critical evaluation of existing methods, in situ measurement of fatigue degradation, non-contact field measurements) Multiaxial fatigue and complex loading effects of materials and structures, exploring state-of-the-art concepts in degradation under cyclic loading Fatigue in the very high cycle regime, including failure mode transitions from surface to subsurface, effects of surface treatment, processing, and loading conditions Modeling (including degradation processes and related driving forces, multiscale/multi-resolution methods, computational hierarchical and concurrent methods for coupled component and material responses, novel methods for notch root analysis, fracture mechanics, damage mechanics, crack growth kinetics, life prediction and durability, and prediction of stochastic fatigue behavior reflecting microstructure and service conditions) Models for early stages of fatigue crack formation and growth that explicitly consider microstructure and relevant materials science aspects Understanding the influence or manufacturing and processing route on fatigue degradation, and embedding this understanding in more predictive schemes for mitigation and design against fatigue Prognosis and damage state awareness (including sensors, monitoring, methodology, interactive control, accelerated methods, data interpretation) Applications of technologies associated with fatigue and their implications for structural integrity and reliability. This includes issues related to design, operation and maintenance, i.e., life cycle engineering Smart materials and structures that can sense and mitigate fatigue degradation Fatigue of devices and structures at small scales, including effects of process route and surfaces/interfaces.