A Statistical/Computational/Experimental Approach to Study the Microstructural Morphology of Damage

Abstract

The fractural behavior of multi-phase materials is not well understood. Therefore, a statistic study of micro-failures is conducted to deepen our insights on the failure mechanisms. We systematically studied the influence of the morphology of dual phase (DP) steel on the fracture behavior at the onset in two ways: (i) in a numerical setting by statistically averaging over the micro-structural arrangements around the damage sites in no less than 400 randomly-generated idealized microstructural models loaded in pure shear; and (ii) in an experimental setting by statistically averaging, similar to the numerical simulations, over the damage sites found in a large collection of large field-of-view SEM images of DP steel deformed in uniaxial tension, where deliberately-overexposed backscattered electron images sharply mark the damage location, while simultaneously-recorded secondary electron images are used to identify the material phases. The numerical and experimental analyses were validated and tested for accuracy. Application of both techniques to DP showed a similar single topological feature to be most sensitive to damage: a small region of soft matrix material with hard inclusion particles on opposing sides. These results are representative for and yield insight in damage evolution in a wide variety of multi-phase materials.