Assessment of the Applicability of Reduced-Order Models to Simulate Corrosion Processes and Protection Mechanisms

Corrosion is a complex phenomenon that involves coupled electrochemical, chemical, and mass transport processes interacting with the complexities of material metallurgy and microstructure. The intricate interdependence between the variables and processes makes the prediction of corrosion damage very challenging. To gain knowledge about the underlying mechanisms, advanced characterization and electrochemical methods, and computational models are used. Experimental techniques and computational models can work synergistically to improve the fundamental understanding of corrosion processes. The use of reduced-order models for simulating potential, current density, and species distribution in an electrolyte are attractive due to the high computational costs required to solve the intricate set of highly nonlinear partial differential equations and boundary conditions characteristic of electrochemistry problems.
Aluminum alloys utilized in the aerospace industry are susceptible to localized corrosion due to their heterogeneous microstructure. In airframe components, these alloys are also susceptible to galvanic corrosion at joint locations, where the Al panels are joined together by fasteners made of dissimilar, more noble alloys. To protect these structures, organic coatings with inhibiting pigments are commonly used, such as Mg-rich primers. These primers can provide protection to Al alloys via galvanic and chemical mechanisms. The means and effectiveness of the protection mechanisms depend on a myriad of parameters; thus, a large volume of experimental work is necessary to unravel individual and synergistic effects between the variables, and the development of models that describe such mechanisms can be used to efficiently screen the large parameter space.
In this work, the applicability of reduced-order models in simulating complex interdependent mechanisms occurring in galvanic systems was tested. The work focused on developing computational models that simulate galvanic and chemical processes important for the corrosion and corrosion protection mechanisms of aerospace Al alloys. The impact of the governing equations utilized to describe the transport of ionic species in a galvanic cell was investigated. The Laplace, Nernst-Planck solved with the electroneutrality condition, and Nernst-Planck-Poisson equations were utilized to solve the potential, current density, and species spatiotemporal distributions in the electrolyte. In addition, a modified Laplace approach was developed, in which the mass and charge transport equations were partially decoupled; the Laplace equation was utilized to solve for charge conservation, while Nernst-Planck equations were utilized to solve for mass transport and calculate the electrolyte conductivity at each position and time-step. The importance of each term that describes the mass and charge transport in the electrolyte in varying supporting electrolyte concentrations was discussed. It was found that the reduced-order models saved substantial computational time without significant loss in accuracy for electrolyte concentrations typical of most environments of interest in corrosion and electrochemistry.
Reduced-order models were applied to model corrosion and corrosion protection mechanisms relevant to aerospace aluminum alloys. The applicability of the Laplace equation to model the galvanic coupling of aluminum alloy 7050 (AA7050) and stainless-steel type 316 (SS316) was assessed. The Scanning Vibrating Electrode Technique (SVET) was utilized to measure the current density distribution across the Al alloy and the SS316 electrodes, and the measurements were compared with the calculated results. The validated finite element model was used to investigate the impact of the SVET experimental limitations in measuring the current density at the electrode/electrolyte interface.
The Laplace equation was complemented by the addition of the transport of minor species and homogeneous reactions in the electrolyte to model conditions in which the evolving electrolyte chemistry plays an important role in the corrosion behavior of an Al alloy. A comprehensive framework was developed to model the chemical and electrochemical mechanisms offered by Mg-based organic coatings. Chemistry-dependent boundary conditions were developed to simulate the change in the corrosion behavior of an aluminum alloy 2024 (AA2024) when exposed to a solution containing Mg-based pigments. The model predicted the change in the corrosion potential of AA2024 as a function of pH, water layer thickness, chloride concentration, and the inhibition of oxygen reduction reaction. The pH in the solution was calculated taking into account Mg dissolution, precipitation of Mg(OH)2, Al(OH)3 dissolution, and hydrolysis of Al3+ ions. The predicted critical pH at which the corrosion potential of AA2024-T351 sharply decreases to values below pitting and repassivation potentials under full immersion conditions was in accordance with experimental observations performed in varying sodium chloride concentrations. In higher sodium chloride concentrations, the critical pH decreases due to the reduced concentration of dissolved oxygen and the higher passive current density in higher sodium chloride concentrations.
In the study of the cathodic protection mechanism offered by Mg-rich primers, the galvanic coupling between the aluminum alloy 2024 and the Mg pigments was modeled as a function of coating resistance, water layer thickness, and electrolyte chemistry. The impact of the coating resistance on the galvanic coupling was also simulated experimentally by coupling the Al alloy and Mg electrodes and resistors of varying resistances via a zero resistance ammeter. Good agreement was found between the modeled and experimentally-determined coupled potential and current for all the resistances evaluated. Finally, the phenomenon of Al dissolution under cathodic polarization was modeled utilizing the developed pH-dependent electrochemical kinetics. The modeling results qualitatively agree with experimental data reported in the literature.
The comprehensive framework developed in this work was utilized to assess the parameter space. The impact of environmental and coating parameters on the corrosion and corrosion protection mechanisms of Al alloys was investigated. The conditions under which the protection mechanisms are hampered were highlighted and discussed. The robustness of reduced-order models was increased by the development of chemistry-dependent boundary conditions that were adaptive to changes in the electrolyte composition.