  We extend the model-free data-driven paradigm for rate-independent fracture
mechanics proposed in Carrara et al. (2020), Data-driven Fracture Mechanics,
Comp. Meth. App. Mech. Eng., 372 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.
