Abstract
The exposure of many alloys to aqueous electrolytes often leads to the formation of surface films that are more stable than the alloy itself. These films are typically considered protective (passive) due to their ability to significantly reduce the alloy’s dissolution rate even in highly aggressive environments. However, localized breakdown of these films can result in pitting corrosion-one of the most aggressive and challenging forms of corrosion to manage due to its highly dynamic and complex nature. Fundamentally an electrochemical process, understanding pitting corrosion requires a detailed analysis of the interactions between current/ potential inside the pit with the surrounding chemical and electrochemical reactions coupled with inside and outside pit mass transport processes. The intricate nature of high current densities/potentials, and the highly concentrated, evolving solution inside the pit (anode) adjacent to a passivated alloy surface (cathode), has posed a challenge for decades.
This dissertation aims to provide a quantitative analysis of critical factors influencing pitting corrosion through a combined experimental and computational approach, focusing on pit propagation and the conditions leading to repassivation. Specifically, the study investigates pitting corrosion in stainless steels (SS) 316L and 304 in chloride-containing environments. A newly developed framework integrating experimental and modeling approaches is introduced to correlate key factors in pit repassivation, including repassivation potential, repassivation current density, critical pit stability product, fraction of highly aggressive solution saturation, in-pit pH, and the ratio of local cathodic to anodic current densities. This framework is then applied to characterize variations in these critical parameters in mixtures of chloride and sulfate-containing environments, which are known for their corrosion-inhibiting properties for the SS316/L and SS304/L alloys.
In order to apply the findings to more applicable engineering scenarios, the dissertation extends, through modeling approach, the typically one-dimensionally (1D) acquired critical pitting factors into three-dimensional (3D) ones. Then, the conservativism of existing 3D pit size predictive models, such as the Chen and Kelly’s analytical model and numerical Finite Element Analysis (FEA) methods, in estimating maximum pit size for a given alloy-electrolyte system is also assessed. The dissertation concludes with an evaluation of electrochemical processes near the electrode-electrolyte interface in localized corrosion while also exploring the efficacy of the Laplace with variable conductivity (Lvk) reduced-order model (ROM) in reducing computational costs. Two additional novel ROM techniques for localized corrosion through FEA, introduced and demonstrated for the first time in this dissertation work, are shown to significantly enhance computational efficiency while maintaining very high accuracy in the obtained results.
