PROMOTING ACCESS TO AFRICAN RESEARCH

Journal of Applied Sciences and Environmental Management

The AJOL site is currently undergoing a major upgrade, and there will temporarily be some restrictions to the available functionality.
-- Users will not be able to register or log in during this period.
-- Full text (PDF) downloads of Open Access journal articles will be available as always.
-- Full text (PDF) downloads of subscription based journal articles will NOT be available
We apologise for any inconvenience caused. Please check back soon, as we will revert to usual policy as soon as possible.





Development of twelve parameter prediction model for examining the under-pipe corrosion deposit condition of localized carbon steel in acidic media

M Obaseki

Abstract


This paper presents an under deposit condition of localized carbon steel in acidic gas solutions by developing and using a twelve parameters condition prediction model. The proposed analytical model was tested against De Waard models, neural network model and experimental result and found to have an accuracy of 82.4% against 23%, 53.3%, 95.6% of De Waard Lotz and Milliams models and NN mode and was found to give reasonably accurate results. It had root mean square error (RMSE) of 0.024, mean absolute error (MAE) 0.019, scattered index (SI) 0.371 and with coefficient of determination (R2) of 82.4% in the validation series. The method is useful for introducing nonlinear conditions prediction in undergraduate/postgraduate engineering with manual computation coupled with lesser error and very simple method in application for better corrosion management than the existing manual traditional models.

Keywords: Model, under-deposit, Carbon steel, Corrosion management




http://dx.doi.org/10.4314/jasem.v23i6.4
AJOL African Journals Online