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2023 (English)In: Materials, E-ISSN 1996-1944, Vol. 16, no 3, article id 923Article in journal (Refereed) Published
Abstract [en]
A mechanistic model of atmospheric bimetallic corrosion with a simplified empirical approach to the onset of localized corrosion attacks is presented. The model was built for a typical bimetallic sample containing aluminum alloy 1050 and stainless steel 316L sheets. A strategy was developed that allowed the model to be calibrated against the measured galvanic current, geometrical corrosion attack properties, and corrosion products. The pitting-onset simplification sets all pits to be formed at a position near the nobler metal and treated all pits as being of the same shape and size. The position was based on the location of the highest pitting events and the pit attributes on an average of the deepest pits. For 5 h exposure at controlled RH (85%, 91%, and 97%) and salt load (86 μg NaCl/cm2), the model was shown to be promising: both for analysis of local bimetallic corrosion chemistry, such as pH and corrosion products, and for efficient assessment of pitting damage by computing a single largest pit depth. Parametric studies indicated that the pitting-onset approximation deviated the most at the beginning of exposure and when RH was below 91%. © 2023 by the authors.
Place, publisher, year, edition, pages
MDPI, 2023
Keywords
AA 1050, aluminum, bimetallic corrosion, galvanic corrosion, lightweight, modeling, pitting, simulation, stainless steel, Aluminum alloys, Aluminum corrosion, Atmospheric chemistry, Atmospheric corrosion, Damage detection, Sodium chloride, Steel corrosion, Corrosion attack, Corrosion products, Mechanistic models, Pittings
National Category
Engineering and Technology
Identifiers
urn:nbn:se:ri:diva-64101 (URN)10.3390/ma16030923 (DOI)2-s2.0-85147850777 (Scopus ID)
Note
Correspondence Address: Zavalis Tommy, RISE Research Institutes of Sweden, Sweden; email: tommy.zavalis@ri.se; Funding details: VINNOVA, 2018-0288; Funding text 1: This work was funded by LIGHTer, a strategic innovation program within the Swedish innovation agency (VINNOVA) grant number 2018-0288.
2023-02-282023-02-282024-08-13Bibliographically approved