Fatigue as a mode of failure becomes increasingly relevant with age in tissues that experience repeated fluctuations in loading. While there has been a growing focus on the mechanics of networks of collagen fibers, which are recognized as the predominant mechanical components of soft tissues, the network’s fatigue behavior has received less attention. Specifically, it must be asked (1) how the fatigue of networks differs from that of its component fibers, and (2) whether this difference in fatigue behaviors is affected by changes in the network’s architecture. In the present study, we simulated cyclic uniaxial loading of Voronoi networks to model fatigue experiments performed on reconstituted collagen gels. Collagen gels were cast into dog-bone shape molds and were tested on a uniaxial machine under a tension-tension cyclic loading protocol. Simulations were performed on networks modeled as trusses of, on average, 600 nonlinear elastic fibers connected at freely rotating pin-joints. We also simulated fatigue failure of Delaunay, and Erdős–Rényi networks, in addition to Voronoi networks, to compare fatigue behavior among different architectures. The uneven distribution of stresses within the fibers of the unstructured networks resulted in all three network geometries being more endurant than a single fiber or a regular lattice under cyclic loading. Among the different network geometries, for low to moderate external loads, the Delaunay networks showed the best fatigue behavior, while at higher loads, the Voronoi networks performed better.
Bibliographical noteFunding Information:
The authors gratefully acknowledge financial support from the National Institutes of Health (R01-EB005813). We also thank the Minnesota Supercomputing Institute (MSI) for providing the computing resources used to carry out this work.
Acknowledgements The authors gratefully acknowledge financial support from the National Institutes of Health (R01-EB005813). We also thank the Minnesota Supercomputing Institute (MSI) for providing the computing resources used to carry out this work.
© 2018, Springer-Verlag GmbH Germany, part of Springer Nature.
- Collagen gel fatigue
- Fiber network mechanics
- Network fatigue