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Crack Propagation by Activated Avalanches during Creep and Fatigue from Elastic Interface Theory

  • National Centre for Nuclear Research

Research output: Contribution to journal › Article › Scientific › peer-review

6 Citations (Web of Science)
112 Downloads (Pure)

Abstract

The growth of cracks combines materials science, fracture mechanics, and statistical physics. The importance of fluctuations in the crack velocity is fundamental since it signals that the crack overcomes local barriers such as tough spots by avalanches. In ductile materials the omnipresent plasticity close to the crack tip influences the growth by history effects, which we here study in polymethylmetacrylate by various fatigue and creep protocols. We show how the crack tip local history may be encompassed in a time- and protocol-dependent length scale, which allows us to apply a statistical fracture description to the time-dependent crack growth rate, resolving the well-known paradox why fatigue cracks grow faster if the stress during a cycle is let to relax more from the peak value. The results open up novel directions for understanding fracture by statistical physics.

Original languageEnglish
Article number098202
Pages (from-to)1-7
Number of pages7
JournalPhysical Review Letters
Volume134
Issue number9
DOIs
Publication statusPublished - 7 Mar 2025
MoE publication typeA1 Journal article-refereed

Funding

M. J. A. acknowledges support from the European Union Horizon 2020 research and innovation programme under Grant Agreement No. 857470 and from European Regional Development Fund via Foundation for Polish Science International Research Agenda PLUS programme Grant No. MAB PLUS/2018/8. M. J. A. acknowledges support from the Academy of Finland (Center of Excellence program, 278367 and 317464) and the Finnish Cultural Foundation. J. K. acknowledges the funding from Academy of Finland (308235) and Business Finland (211715). I. V. L. acknowledges the funding from Academy of Finland (341440 and 346603). T. M., L. T., J. L., J. K., and M. J. A. acknowledge the support from FinnCERES flagship (Grant No. 151830423), Business Finland (Grants No. 211835, No. 211909, and No. 211989), and Future Makers programs. The authors acknowledge the computational resources provided by the Aalto University School of Science “Science-IT” project.

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