  In the present work, a rate-dependent cohesive zone model for the fracture of
polymeric interfaces is presented. Inverse calibration of parameters for such
complex models through trial and error is computationally tedious due to the
large number of parameters and the high computational cost associated. The
obtained parameter values are often non-unique and the calibration inherits
higher uncertainty when the available experimental data is limited. To
alleviate these difficulties, a Bayesian calibration approach is used for the
proposed rate-dependent cohesive zone model in this work. The proposed cohesive
zone model accounts for both reversible elastic and irreversible rate-dependent
separation sliding deformation at the interface. The viscous dissipation due to
the irreversible opening at the interface is modeled using elastic-viscoplastic
kinematics that incorporates the effects of strain rate. To quantify the
uncertainty associated with the inverse parameter estimation, a modular
Bayesian approach is employed to calibrate the unknown model parameters,
accounting for the parameter uncertainty of the cohesive zone model. Further,
to quantify the model uncertainties, such as incorrect assumptions or missing
physics, a discrepancy function is introduced and it is approximated as a
Gaussian process. The improvement in the model predictions following the
introduction of a discrepancy function is demonstrated justifying the need for
a discrepancy term. Finally, the overall uncertainty of the model is quantified
in a predictive setting and the results are provided as confidence intervals. A
sensitivity analysis is also performed to understand the effect of the
variability of the inputs on the nature of the output.
