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

Abstract

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.

Effect of Surface Finishing State on Fatigue Strength of Cast Aluminium and Steel Alloys

“…Computed tomography investigations were conducted only for the aluminium series, applying a threshold-based image post processing of the raw data, as detailed in a previous study of the authors [ 94 ]. A clustering of interacting porosity networks was incorporated following the proposal of Åman et al [ 147 ].…”

“…For applications in practice, the size of the fatigue critical layer is not known in advance. One can choose the highly stressed volume (HSV) for CT scan as well, but the statistical size effect has to be considered accordingly [ 94 ]. Incorporating all defects of the specimens’ cross section results in distributions as depicted in Figure 15 b.…”

“…As depicted in the experimental work, the effect of vibratory finishing versus manual polishing depends on the locally applicable residual stress ratio for each material, as the defect distribution itself is not changed by the surface treatment process itself. Thus, the key part of this work focusses on the extension of layer-based fatigue assessment tool, as previously introduced for cast aluminium alloys [ 94 ], towards consideration of the effective residual stress state for each extremal defect. This section deals with the predicted stability of the residual stress state in the surface layer during fatigue loading by simulation.…”

“…Maierhofer et al [ 92 ] recommends describing the crack extension from the intrinsic short crack threshold up to the long crack threshold by Equation ( 8 ) as functions of the predominant closure mechanisms i . Regarding the in-depth influence of microstructure on crack growth parameters and the effect of the highly stressed volume, the authors refer to previous investigations [ 93 , 94 ] for Al–Si cast alloys. with …”

“…Five specimen series were taken from these materials, each of them in polished and vibratory finished condition to enable a direct comparison of the fatigue properties. After a detailed description of the experimental framework, the layer-based fatigue assessment concept, originally published by the authors in [ 94 ] is extended with regard to the effective residual stress state within the surface layer evoked by vibratory finishing. The residual stress state in the surface layer is measured using X-ray diffraction.…”