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The DOI matches its Crossref record; 19 of the 19 references it cites were found in a registry or an index.

A framework to model the fatigue behavior of brittle materials based on a variational phase-field approach

Open access
Carrara, P., Ambati, M., Alessi, R., De Lorenzis, L.·2020·Computer Methods in Applied Mechanics and Engineering

Abstract

Abstract A novel variational framework to model the fatigue behavior of brittle materials based on a phase-field approach to fracture is presented. The standard regularized free energy functional is modified introducing a fatigue degradation function that effectively reduces the fracture toughness as a proper history variable accumulates. This macroscopic approach allows to reproduce the main known features of fatigue crack growth in brittle materials. Numerical experiments show that the Wohler curve, the crack growth rate curve and the Paris law are naturally recovered, while the approximate Palmgren–Miner criterion and the monotonic loading condition are obtained as special cases.

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Metadata

Authors
Carrara, P., Ambati, M., Alessi, R., & De Lorenzis, L.
Venue
Computer Methods in Applied Mechanics and Engineering
Publisher
Elsevier BV
Published
2020-04
Volume
361
Pages
112731
ISSN
0045-7825 (ISSN-L)
OpenAlex
W2899766161
Cited by
404
References
19
FWCI
15.74
Type
journal article
Language
en
Open access
green

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CoChat. (2026). Citation check: A framework to model the fatigue behavior of brittle materials based on a variational phase-field approach. https://app.cochat.ai/papers/10.1016/j.cma.2019.112731
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Carrara, P., Ambati, M., Alessi, R., & De Lorenzis, L. (2020). A framework to model the fatigue behavior of brittle materials based on a variational phase-field approach. Computer Methods in Applied Mechanics and Engineering. https://doi.org/10.1016/j.cma.2019.112731

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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.