Friction and roughness induced closure effects on shear-mode crack growth and branching mechanisms
Source abstract
Abstract
Abstract The understanding of shear-mode crack growth mechanisms and crack branching phenomena is of great interest for a variety of practical engineering situations. Despite this fact, relatively little research is available regarding these topics. Of the studies that have been performed, few provide a means of quantifying such effects and most consider crack growth starting from a precrack. The current study is aimed at trying to fill some of the research voids in these areas by investigating the effects of microcrack coalescence, loading level, and superimposed normal stresses on the shear-mode crack behavior of naturally initiated fatigue cracks. Based on the experimental results and subsequent analyses, it was determined that microcrack networks and coalescence have little to no effect on the experimentally observed crack paths, regardless of the applied loading level. Instead, the preferred crack growth mode was shown to have a dependence on the applied shear stress magnitude and stress normal to the crack plane, indicating a significant role of fiction and roughness induced crack closure in the crack growth process. A simple model was then proposed to quantify these effects based on the idea that crack face interaction reduces the effective shear-mode driving force by allowing a portion of the nominally applied loading to be transferred through a crack. Crack growth predictions based on the model were compared to experimental results with respect to both crack branching and crack growth rate. The model was found to agree well, both qualitatively and quantitatively, with experimentally observed trends for a variety of multiaxial loading conditions.
Source: openaire · Quality: candidate unverified · Source record ↗
Research context
OpenAlex topics: Fatigue and fracture mechanics · Structural Health Monitoring Techniques · Ultrasonics and Acoustic Wave Propagation
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
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