Atmospheric corrosion represents an annual multi-billion dollar cost burden for the aerospace and defense sectors. For many aircraft, particularly those operating in marine environments, up to ninety percent of corrosion is due to galvanic interactions at dissimilar metal couples. As new materials are introduced with the acquisition of more advanced aircraft, galvanic corrosion is likely to remain a concern. The ability to model galvanic corrosion accurately holds the promise of being able to both predict the performance of new material combinations to guide material selection and predict corrosion damage for maintenance planning. Such models often utilize data collected under immersion test conditions that are not representative of the thin-film electrolytes that are relevant to atmospheric corrosion and may diminish model accuracy and utility. In this work, an atmospheric cell is presented that allows for measurements of corrosion kinetics using thin-film electrolytes. It is observed that the limiting oxygen reduction current density on various alloys is increased several orders of magnitude over immersion results. A segmented, galvanic sensor is presented that enables the experimental quantification of spatial distributions of galvanic current under thin film conditions that is compared to model predictions for verification of the suitability of immersion and thin-film electrolyte polarization data inputs.
Corrosion represents a significant risk and cost burden for the aerospace and defense industry. For example, atmospheric corrosion of U.S. Navy and Marine Corps aircraft, alone, results in costs of approximately $2.6 billion each year. The primary atmospheric degradation mode for aircraft is galvanic corrosion at dissimilar metal couples (e.g. between non-aluminum metallic fasteners and the aluminum structure) . This problem will become even more pronounced as new material combinations are introduced in advanced aircraft. Current maintenance practices are schedule-based leading to either unnecessary over-inspection or worse, unplanned and costly downtime when excessive corrosion is observed. There exists a need for advanced tools and methods to both improve the prediction of material performance at galvanic couples and corrosion damage under atmospheric conditions. With better predictive capabilities, maintenance and sustainment of aircraft can be optimized to decrease costs and increase aircraft availability. Computational models offer a solution to help address this need; however, current predictive models of material performance at galvanic couples are based upon data collected in non-representative conditions. This may diminish the accuracy and utility of the models to guide corrosion resistant material selection during acquisition and corrosion prediction throughout the aircraft’s lifetime.