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Statistical effects of surface preparation and coating type on the corrosion protection performance of repair coatings for offshore wind power constructions
Author(s) -
Momber Andreas W.,
Buchbach Sascha,
Plagemann Peter,
Marquardt Tom,
Winkels Irmgard,
Viertel Johannes
Publication year - 2018
Publication title -
materials and corrosion
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.487
H-Index - 55
eISSN - 1521-4176
pISSN - 0947-5117
DOI - 10.1002/maco.201709765
Subject(s) - coating , corrosion , materials science , rust (programming language) , response surface methodology , statistical analysis , design of experiments , composite material , metallurgy , computer science , mathematics , statistics , machine learning , programming language
Three surface preparation methods, namely dry blast‐cleaning, grinding, and impact brushing, are applied for the preparation of steel substrates prior to the application of four different repair coating systems. The relationship between surface preparation method, coating type, coating thickness, and corrosion protection are systematically investigated with statistical methods. DoE (design of experiments) and ANOVA (analysis of variance) are used to rank the parameter effects. The repaired systems are exposed to the cyclic offshore aging test according to ISO 20340. Response parameters are rust creep and pull‐off strength. Coating system as well as surface preparation method show extreme statistical significance and have a high influence on the rust creep as well as on the pull‐off strength. Extremely significant interaction between the two factors could be found for the pull‐off strength only. Optimization calculations based on a desirability function approach (DFA) reveal that a combination of dry blast‐cleaning and lower coating thickness provided the best protection performance. If dry blast‐cleaning is not feasible, a higher coating thickness is recommended in order to maximize the corrosion protection performance.