A phase field formulation for dissolution-driven stress corrosion cracking
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Abstract (arXiv)
We present a new theoretical and numerical framework for modelling mechanically-assisted corrosion in elastic-plastic solids. Both pitting and stress corrosion cracking (SCC) can be captured, as well as the pit-to-crack transition. Localised corrosion is assumed to be dissolution-driven and a formulation grounded upon the film rupture-dissolution-repassivation mechanism is presented to incorporate the influence of film passivation. The model incorporates, for the first time, the role of mechanical straining as the electrochemical driving force, accelerating corrosion kinetics. The computational complexities associated with tracking the evolving metal-electrolyte interface are resolved by making use of a phase field paradigm, enabling an accurate approximation of complex SCC morphologies. The coupled electro-chemo-mechanical formulation is numerically implemented using the finite element method and an implicit time integration scheme; displacements, phase field order parameter and concentration are the primary variables. Five case studies of particular interest are addressed to showcase the predictive capabilities of the model, revealing an excellent agreement with analytical solutions and experimental measurements. By modelling these paradigmatic 2D and 3D boundary value problems we show that our formulation can capture: (i) the transition from activation-controlled corrosion to diffusion-controlled corrosion, (ii) the sensitivity of interface kinetics to mechanical stresses and strains, (iii) the role of film passivation in reducing corrosion rates, and (iv) the dependence of the stability of the passive film to local strain rates. The influence of these factors in driving the shape change of SCC defects, including the pit-to-crack transition, is a natural outcome of the model, laying the foundations for a mechanistic assessment of engineering materials and structures.
Key facts. Cited by 3 papers in the map (data through 7 Oct 2026). First posted on arXiv 24 Nov 2020.
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Citing papers per year: 2025: 2; 2026: 1.
3 papers.
- 2025Sharp-PINNs: staggered hard-constrained physics-informed neural networks for phase field modelling of corrosioncited by 4
- 2025Enforcing hidden physics in physics-informed neural networkscited by 3
- 2026Physics-informed neural operator for parametric phase-field modelling of interfacial degradation and microstructural evolutioncited by 1
- 2026Physics-informed neural operator for parametric phase-field modelling of interfacial degradation and microstructural evolution10 Mar 2026
- 2025Enforcing hidden physics in physics-informed neural networks18 Nov 2025
- 2025Sharp-PINNs: staggered hard-constrained physics-informed neural networks for phase field modelling of corrosion17 Feb 2025