The natural convection boundary layer ( δ n c ) and its influence on cathodic current in a galvanic couple under varying electrolytes as a function of concentration (1 − 5.3 M NaCl) and temperature (25 °C−45 °C) were understood. Polarization scans were obtained under quiescent conditions and at defined boundary layer thicknesses using a rotating disk electrode on platinum and stainless steel 304L (SS304L); these were combined to determine δ n c . With increasing chloride concentration and temperature, δ n c decreased. Increased mass transport (Sherwood number) results in a decrease in δ n c , providing a means to predict this important boundary. Using Finite Element Modeling, the cathodic current was calculated for an aluminum alloy/SS304L galvanic couple as a function of water layer (WL) thickness and cathode length. Electrolyte domains were delineated, describing (i) dominance of ohmic resistance over mass transport under thin WL, (ii) the transition from thin film to bulk conditions at δ n c , and (iii) dominance of mass transport under thick WL. With increasing chloride concentration, cathodic current decreased due to decreases in mass transport. With increasing temperature, increased cathodic current was related to increases in mass transport and solution conductivity. This study has implications for sample sizing and corrosion prediction under changing environments.

Aerospace structures often involve dissimilar materials to optimize structural performance and cost. These materials can then lead to the formation of galvanic couples when moisture is present. Specifically, noble metal fasteners (such as SS316) are often used in aluminum alloy load-bearing structures, which can lead to accelerated, localized corrosion attack of the aluminum alloy due to the cathodic current supplied by the SS316 fastener. This localized attack is difficult to predict, and tests are often expensive, so modeling of these galvanic couples could be of great utility. The work reported here focuses on the galvanic coupling between fasteners installed in a panel test assembly, and the resultant corrosion damage down the fastener holes. This arrangement is a common assembly geometry in aerospace applications. A specific sol-gel coating was applied to the fasteners, to determine its effectiveness on mitigating galvanic corrosion; bare fasteners were also tested, to investigate a worst-case scenario. Geometric constraints in the model were made to match those of an experimental test panel, which was exposed to ASTM B117 salt fog for 504 h. The electrochemical boundary conditions were generated in solutions appropriate to the material and environment to which it would be exposed. Anodic charge passed during exposure was calculated from image analyses of the corrosion damage in the experimental test, and the results were compared with the model. The Laplacian-based model provides a very good first approximation for predicting the damage within the fastener hole. Validation was provided by both experimental results generated in this study as well as comparison to results in the literature that used similar, but not identical, conditions.

Aluminum alloy panels joined with stainless steel fasteners have been known to occur in aerospace structures, due to their respective optimized mechanical properties. When connected via a conductive solution, a high-driving force for galvanic corrosion is present. The combination of the dissimilar materials, indicating galvanic corrosion, and complex geometry of the occluded fastener hole, indicating crevice corrosion, leads to the detrimental combined effect of galvanic-induced crevice corrosion, as investigated previously in Part I. The present work extends the validated finite element method (FEM) model to predict the current distribution and magnitude in a variety of geometric and environmental conditions, with the goal of preventing corrosion damage within the highly-susceptible fastener hole. Specifically, water layer thicknesses ranging from bulk full-immersion (800 μm) to atmospheric (89 μm) conditions was investigated, as well as the impact of external scribe dimensions. Two avenues for mitigation were determined, 1) to force the majority of current away from the fastener hole and onto the bulk surface of the panel, and 2) to lower the overall galvanic coupling current. A random forest machine learning algorithm was developed to generalize the FEM predictions and create an open-source applicable prediction tool.