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Using modeling and microfabrication for insights into factors controlling the location of crevice attack

Posted on:2012-05-11Degree:Ph.DType:Dissertation
University:University of VirginiaCandidate:Lee, Jason SFull Text:PDF
GTID:1468390011961269Subject:Engineering
Abstract/Summary:
Microfabrication techniques and computational modeling were employed to examine the factors controlling the spatial distribution of crevice corrosion of 316L stainless steel in ferric chloride environments. Historically, in the interest of reducing calculation time, most computational models of crevice corrosion have used idealized crevice geometries. The idealization has been achieved by assuming that the crevice does not have any irregularities in its dimensions. However, this approach does not allow accurate comparison with results obtained from crevices found in practice or crevices formed using conventional multiple crevice assemblies (MCA) as these have surface roughness that, in conjunction with that of the metal, create irregular crevice gaps. Microfabrication techniques were used to bridge the gap between experimental and model results. Instead of using separate substrates and formers like those used in MCA studies, structural formers were fabricated directly onto 316L substrates. Crevice fabrication consisted of a structural material surrounding a sacrificial material, the latter of which was selectively etched to form a rigorously defined hollow structure over the 316L substrate. Microfabricated crevices with gaps as small as 28 nm were exposed to 6% ferric chloride solutions resulted in intermediate crevice corrosion. For crevice gaps below 3 microns, the site of greatest attack down the crevice length was independent of gap size. A novel multivariable boundary surface was used to accurately model the variations in the electrochemical boundary condition (current/potential relationship) as a function of chloride concentration. Modeling results qualitatively predicted the location of attack and that neither ohmic drop nor chemistry change models are suitable for austenitic stainless in acidic chloride environments. Instead, results showed that a chemistry dependent potential-current behavior is the factor that controls the spatial distribution of crevice corrosion attack in this system.
Keywords/Search Tags:Crevice, Modeling, Attack, 316L, Using
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