Proximal Galerkin for Phase Field Fracture

TL;DR

This paper introduces the proximal Galerkin method as a robust numerical framework for phase-field fracture modeling, effectively enforcing physical constraints and handling both static and dynamic problems.

Contribution

The proximal Galerkin approach reformulates constrained optimization into saddle-point problems, improving numerical stability and constraint enforcement in phase-field fracture simulations.

Findings

Accurately reproduces theoretical and experimental results.

Effectively enforces irreversibility and boundedness constraints.

Applicable to both static and dynamic fracture problems.

Abstract

The phase-field method has emerged as a powerful tool for simulating fracture mechanics, yet it presents significant numerical challenges, particularly regarding the enforcement of physical constraints such as irreversibility and boundedness of the phase-field variable. This work proposes the proximal Galerkin (PG) methodology as a robust and efficient framework for solving phase-field fracture problems. By reformulating the inequality-constrained optimization problem into a sequence of saddle-point problems involving latent variables, the PG method rigorously enforces the physical bounds of the phase-field variable and naturally handles the irreversibility condition. This approach is directly applicable to both static and dynamic phase-field fracture problems. The numerical results demonstrate that the PG framework accurately reproduces theoretical predictions and experimental observations, while offering a unified, mathematically consistent treatment of the constraints inherent to phase-field fracture modeling.