Data-driven rate-dependent fracture mechanics

https://doi.org/10.1016/j.jmps.2021.104559Get rights and content
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Highlights

  • A new model-free data-driven approach for rate-dependent fracture is presented.

  • The approach is also extended to fatigue.

  • Results of rate-independent fracture are encompassed as special case.

  • Examples using noisy or noiseless data imitating different models are presented.

  • Reference results adopting classical analytical models are correctly reproduced.

Abstract

We extend the model-free data-driven paradigm for rate-independent fracture mechanics proposed in Carrara et al. (2020), to rate-dependent fracture and sub-critical fatigue. The problem is formulated by combining the balance governing equations stemming from variational principles with a set of data points that encodes the fracture constitutive behavior of the material. The solution is found as the data point that best satisfies the meta-stability condition as given by the variational procedure and following a distance minimization approach based on closest-point-projection. The approach is tested on different setups adopting different types of rate-dependent fracture and fatigue models affected or not by white noise.

Keywords

Data-driven computational mechanics
Fatigue
Fracture mechanics
Rate-dependent fracture

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