Predicting image processing-normalized DL-EPRT performance from Rudimentary Cihal method-based counterpart

Abstract

Conventional DL-EPRT was extrapolated into accounting for inherent inconsistencies amongst grain boundary (GB) dimensions whilst correlating two distinct methods of ir/ia normalization, namely the approximate Cihal method (CM) and the relatively involved image processing (IP). Inasmuch as facilitating the forecast of IP- from CM-based normalizations, the full spectrum of plausible predictive models was subjected to cross validations that revealed those emanating from GB length-based endeavors to be quadratic with R2 and mean error (E) of 0.9215 and 0.5769, respectively. Meanwhile, GB area normalizations succumbed to a linear polynomial yielding R2 and E values of 0.8795 and 0.3664, respectively.

Keywords

• Degree of sensitization
• Double loop electrochemical potentiokinetic reactivation
• Normalization
• Cihal method
• Image processing