The parameter identification problem of the gradient-enhanced continuum damage model is solved using tools of the inverse problems theory. Particularly, the K-Nearest Neighbors (KNN) technique and the Kalman Filter (KF) method are adopted in cascade to identify the length scale…
The parameter identification problem of the gradient-enhanced continuum damage model is solved using tools of the inverse problems theory. Particularly, the K-Nearest Neighbors (KNN) technique and the Kalman Filter (KF) method are adopted in cascade to identify the length scale parameter and the parameter governingthesofteningbranchofthematerialconstitutivelaw. Twoexperimentaldataseriesareused, concern- ing different sizes and loading conditions, in order to investigate the influence of the involved experimental data in the parameter estimates and the predictive capabilities of the considered model. The inverse problem results to be ill-posed if only force-deformation data are used in the parameter identification procedure. Additional data related to the evolution of the width of the damaged zone during the fracture process are adopted in order to recover the well-posedness of the inverse problem.