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Comparison between Fractal and Statistical Approaches to Model Size Effects in VHCF

Authors: Stefano Invernizzi; Davide Paolino; Francesco Montagnoli; Andrea Tridello; Alberto Carpinteri;

Comparison between Fractal and Statistical Approaches to Model Size Effects in VHCF

Abstract

Size effects concern the anomalous scaling of relevant mechanical properties of materials and structures over a sufficiently wide dimensional range. In the last few years, thanks to technological advances, such effects have been experimentally detected also in the very high cycle fatigue (VHCF) tests. Research groups at Politecnico di Torino are very active in this field, observing size effects on fatigue strength, fatigue life and fatigue limit up to the VHCF regime for different metal alloys. In addition, different theoretical models have been put forward to explain these effects. In the present paper, two of them are introduced, respectively based on fractal geometry and statistical concepts. Furthermore, a comparison between the models and experimental results is provided. Both models are able to predict the decrement in the fatigue life and in the conventional fatigue limit.

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Italy
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Keywords

statistical models of fatigue, Mining engineering. Metallurgy, very high cycle fatigue, fractals, TN1-997, very high cycle fatigue; size effects; fractals; statistical models of fatigue, size effects

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This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
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popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
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influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
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impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
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