  Identification of crystallographic slip in metals and alloys is crucial to
understand and improve their mechanical behavior. 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 that
exploits the full deformation kinematics. Using microstructure-correlated
deformation 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 applied and demonstrated to be
successful on virtual and experimental case studies of FCC and BCC metals.
However, for more advanced and anisotropic HCP crystal structures the complete
identification of all slip systems was found to be more challenging, posing
limitations on automation and flexibility. Here, we propose a significant
extension to the SSLIP framework with the aim of automated slip system
identification of HCP. The main extensions of the SSLIP method, hereinafter
referred to as the +SSLIP method, include (i) a pre-selection of slip systems
using a Radon transform, (ii) robustness to measured rigid body rotation by
simultaneous identification of the local elastic rotation field, (iii)
identification of the two best matching slip systems for each data point, and
(iv) a procedure to deal with slip systems with in-plane displacement gradient
tensors that cannot be discriminated, yielding the full slip system activity
maps with all slip systems for each grain. The resulting objective
identification method does not rely on, e.g., 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.
