Bridging experiments and defects' mechanics: a data-driven toolbox for configurational force analysis.

Area of Science:

• Materials Science
• Computational Mechanics
• Solid Mechanics

Background:

• Predicting material failure requires understanding mechanical behavior of defects.
• Traditional fracture mechanics relies on assumptions often unmet in experimental settings.

Purpose of the Study:

• To develop a computational toolbox for extracting configurational forces and mixed-mode stress intensity factors (SIFs) from experimental data.
• To enable geometry-independent characterization of defect behavior in complex materials.

Main Methods:

• A MATLAB-based toolbox implementing path-independent energy integrals (J- and M-integrals).
• Novel mode decomposition for isolating mode I-III SIFs contributions.
• Direct analysis of experimentally measured displacement or deformation gradient fields (e.g., DIC, H-EBSD).

Main Results:

• Demonstrated robust, geometry-independent characterization of microcracks, dislocations, and fatigue cracks.
• Successfully applied to anisotropic and complex materials.
• Framework is material-agnostic and operates directly on experimental fields.

Conclusions:

• The toolbox facilitates data-driven analysis of defect behavior, overcoming limitations of traditional methods.
• Applicable to linear and anisotropic elastic/elastoplastic materials (metals, ceramics) under small-strain kinematics.
• Enables advanced understanding of material failure and performance enhancement.