Abstract
Naphthenic acid corrosion has been investigated since the 1950s, owing to its economic impact on refining operations. Although some significant advances in corrosion control, the best practice is still to blend or neutralise crude oil. Better understanding of the corrosion mechanism in the presence of naphthenic acids is necessary. This paper describes the preliminary evaluation of a neural network approach for rapid prediction of the naphthenic acid corrosion performance of carbon and stainless steels in a crude oil distillation unit.
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