+SSLIP: Automated Radon-Assisted and Rotation-Corrected Identification of Complex HCP Slip System Activity Fields from DIC Data

Identification of crystallographic slip in metals and alloys is crucial to understand and improve their mechanical behaviour. Recently, a novel slip system identification framework, termed SSLIP (for slip system–based local identification of plasticity), was introduced to leap from conventional trace-based identification to automated, point-by-point identification, exploiting the full deformation kinematics. Using sub-micron-scale digital image correlation (DIC) deformation fields aligned to electron backscatter diffraction (EBSD) data, SSLIP matches the measured in-plane displacement gradient tensor to the kinematics of the optimal combination of multiple slip system activities, at each DIC datapoint. SSLIP was demonstrated to be successful on virtual and experimental case studies of FCC and BCC metals. However, for more challenging HCP crystal structures, the complete identification of all slip systems was found to be more challenging, posing limitations on automation and flexibility. To extend the capabilities of SSLIP, we propose an extended framework, hereinafter referred to as the +SSLIP method, which includes (i) a preselection of slip systems using a Radon transform, (ii) robustness to measured rigid body rotation by simultaneous identification of the local rotation field, (iii) identification of the two best matching slip systems for each data point and (iv) a procedure to determine groups of slip systems with in-plane displacement gradient tensors that cannot be discriminated. This procedure yields the full (HCP) slip system activity maps for every slip system in each grain. The resulting objective identification method does not rely on the Schmid factor to select which slip system is active at each point. We show how slip systems from multiple slip families are successfully identified on virtual and real experiments on a Zn polycrystalline coating.