[Paper Review] Automated Identification of Slip System Activity Fields from Digital Image Correlation Data

Tijmen Vermeij, R.H.J. Peerlings+2 more|arXiv (Cornell University)|Jul 26, 2022

Orthopedic Infections and Treatments4 citations

TL;DR

This paper presents SSLIP, a novel framework for automated, full-field identification of slip system activity from SEM-DIC displacement gradient data. By solving a local optimization problem at each data point to match measured kinematics to theoretical slip system kinematics, SSLIP enables robust identification of discrete, diffuse, and cross-slip mechanisms—even with up to 48 slip systems—demonstrated on HCP, FCC, and BCC metals with high accuracy and validation via virtual and experimental case studies.

ABSTRACT

Crystallographic slip system identification methods are widely employed to characterize the fine scale deformation of metals. While powerful, they usually rely on the occurrence of discrete slip bands with clear slip traces and can struggle when complex mechanisms such as cross-slip, curved slip, diffuse slip and/or intersecting slip occur. This paper proposes a novel slip system identification framework, termed SSLIP (for Slip Systems based Local Identification of Plasticity), in which the measured displacement gradient fields (from Digital Image Correlation) are locally matched to the kinematics of one or multiple combined theoretical slip systems, based on the measured crystal orientations. To identify the amounts of slip that conforms to the measured kinematics, an optimization problem is solved for every datapoint individually, resulting in a slip activity field for every considered slip system. The identification framework is demonstrated and validated on an HCP virtual experiment, for discrete and diffuse slip, incorporating 24 slip systems. Experimental case studies on FCC and BCC metals show how full-field identification of discrete slip, diffuse slip and cross-slip becomes feasible, even when considering 48 slip systems for BCC. Moreover, the methodology is extended into a dedicated cross-slip identification method, which directly yields the orientation of the local slip plane trace orientation, purely based on the measured kinematics and on one or two chosen slip directions. For even more challenging cases revealing a persistent uncertainty in the slip identification, a two-step identification approach can be employed, as is demonstrated on a highly challenging HCP virtual experiment.

Motivation & Objective

• To address the limitations of existing slip system identification methods that rely on sharp, discrete slip traces and fail under complex deformation mechanisms such as diffuse slip, cross-slip, and curved slip.
• To develop a method that enables full-field quantification of slip activity across multiple slip systems, even when slip features are not visually resolvable due to limited spatial resolution.
• To extend identification capability to cross-slip by directly determining the local slip plane trace orientation from kinematic data.
• To provide a robust solution for highly complex cases involving overlapping slip systems, where standard identification becomes underdetermined and ambiguous.
• To enable integration with additional data sources such as 3D DIC and in-situ EBSD to improve accuracy and robustness in challenging experimental conditions.

Proposed method

• The method uses measured displacement gradient tensors from SEM-DIC as input, combined with crystallographic orientation data from EBSD to define the theoretical kinematics of candidate slip systems.
• For each data point, an optimization problem is solved to determine the slip activity (amplitude) of each candidate slip system by minimizing the difference between measured and predicted displacement gradients.
• The optimization is based on a linear combination of theoretical slip system kinematics, where the slip activity field for each system is computed independently per point.
• A dedicated cross-slip identification extension is introduced, which fixes known slip directions and directly identifies the slip plane trace orientation via an alternative optimization scheme.
• For complex cases with overlapping slip systems, a two-step approach is employed: first identifying dominant single-slip regions, then using only those to perform a full multi-slip identification.
• The framework is robust to missing data, such as in regions of large deformation, and can be extended to incorporate 3D displacement gradients from Digital Height Correlation or lattice rotation data from in-situ EBSD.

Experimental results

Research questions

• RQ1 Can slip system activity be accurately identified in the presence of diffuse, overlapping, or curved slip, where traditional methods relying on visible slip traces fail?
• RQ2 How can cross-slip be identified directly from displacement gradient data without requiring prior knowledge of the slip plane?
• RQ3 What is the performance of the method when multiple slip systems are active simultaneously, especially in complex HCP materials with high symmetry?
• RQ4 Can the method be extended to include 3D displacement data or lattice rotation information to improve identification accuracy?
• RQ5 How can underdetermined identification problems in highly complex slip scenarios be resolved without introducing bias or error?

Key findings

• The SSLIP framework successfully identified slip activity fields for up to 24 slip systems in a virtual HCP experiment with discrete and diffuse slip, demonstrating high accuracy even under added experimental noise.
• In an experimental FCC Ni-based superalloy, SSLIP correctly resolved complex mechanisms including discrete slip, diffuse slip, cross-slip, and overlapping slip, with indirect validation via isolated slip bands.
• For a BCC ferrite single crystal, SSLIP accurately identified diffuse slip using 48 slip systems simultaneously, confirming the method’s capability in high-degree-of-freedom systems.
• The dedicated cross-slip identification module correctly determined the local slip plane trace orientation in the virtual HCP case, validating its ability to resolve non-parallel slip plane geometries.
• In a highly challenging HCP case with four overlapping slip systems, the two-step identification approach—first identifying dominant single-slip regions—yielded the correct solution, overcoming the limitations of underdetermined optimization.
• The method remains robust to missing DIC data, such as in regions of large strain, and can be enhanced by integrating additional data sources like 3D DIC or in-situ EBSD for improved accuracy.