A Probabilistic Fatigue Strength Assessment in AlSi-Cast Material by a Layer-Based Approach

Matthias Oberreiter, Stefan Fladischer, Michael Stoschka, Martin Leitner

Research output: Contribution to journalArticleResearchpeer-review


An advanced lightweight design in cast aluminium alloys features complexly shaped geometries with strongly varying local casting process conditions. This affects the local microstructure in terms of porosity grade and secondary dendrite arm spacing distribution. Moreover, complex service loads imply changing local load stress vectors within these components, evoking a wide range of highly stressed volumes within different microstructural properties per load sequence. To superimpose the effects of bulk and surface fatigue strength in relation to the operating load sequence for the aluminium alloy EN AC 46200, a layer-based fatigue assessment concept is applied in this paper considering a non-homogeneous distribution of defects within the investigated samples. The bulk fatigue property is now obtained by a probabilistic evaluation of computed tomography results per investigated layer. Moreover, the effect of clustering defects of computed tomography is studied according to recommendations from the literature, leading to a significant impact in sponge-like porosity layers. The highly stressed volume fatigue model is applied to computed tomography results. The validation procedure leads to a scattering of mean fatigue life from −2.6% to 12.9% for the investigated layers, inheriting strongly varying local casting process conditions.
Original languageEnglish
Article number784
Number of pages22
Issue number5
Publication statusPublished - 30 Apr 2022

Bibliographical note

Publisher Copyright: © 2022 by the authors. Licensee MDPI, Basel, Switzerland.


  • aluminium casting
  • local fatigue assessment
  • shrinkage porosity
  • probability distribution
  • extreme value statistics
  • computed tomography

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