The study of the corrosion inhibition of mild steel in sulphuric acid (H2SO4) by the leaf pastes of Sida Acuta was probed using the weight-loss technique. The highest inhibition efficiency of 91.46% with a reduction in corrosion rate from 3.1338mg.cm-2.h-1 to 0.2825mg.cm-2.h-1 was achieved by the addition of the leaf pastes of Sida Acuta at 30g per litre of 1.2M H2SO4. The prediction obtained using the artificial neural network gave the least error and was closer to the experimental corrosion rate value in comparison with the prediction by multiple regression.
Published in | Journal of Civil, Construction and Environmental Engineering (Volume 2, Issue 5) |
DOI | 10.11648/j.jccee.20170205.11 |
Page(s) | 123-133 |
Creative Commons |
This is an Open Access article, distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution and reproduction in any medium or format, provided the original work is properly cited. |
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Copyright © The Author(s), 2017. Published by Science Publishing Group |
Corrosion Rate, Leaf-Pastes of Sida Acuta, Artificial Neural Network, Multiple Regression, Mild Steel, Sulphuric Acid (H2SO4)
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APA Style
Agha Inya Ndukwe, Charles Nwachukwu Anyakwo. (2017). Predictive Corrosion-Inhibition Model for Mild Steel in Sulphuric Acid (H2SO4) by Leaf-Pastes of Sida Acuta Plant. Journal of Civil, Construction and Environmental Engineering, 2(5), 123-133. https://doi.org/10.11648/j.jccee.20170205.11
ACS Style
Agha Inya Ndukwe; Charles Nwachukwu Anyakwo. Predictive Corrosion-Inhibition Model for Mild Steel in Sulphuric Acid (H2SO4) by Leaf-Pastes of Sida Acuta Plant. J. Civ. Constr. Environ. Eng. 2017, 2(5), 123-133. doi: 10.11648/j.jccee.20170205.11
@article{10.11648/j.jccee.20170205.11, author = {Agha Inya Ndukwe and Charles Nwachukwu Anyakwo}, title = {Predictive Corrosion-Inhibition Model for Mild Steel in Sulphuric Acid (H2SO4) by Leaf-Pastes of Sida Acuta Plant}, journal = {Journal of Civil, Construction and Environmental Engineering}, volume = {2}, number = {5}, pages = {123-133}, doi = {10.11648/j.jccee.20170205.11}, url = {https://doi.org/10.11648/j.jccee.20170205.11}, eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.jccee.20170205.11}, abstract = {The study of the corrosion inhibition of mild steel in sulphuric acid (H2SO4) by the leaf pastes of Sida Acuta was probed using the weight-loss technique. The highest inhibition efficiency of 91.46% with a reduction in corrosion rate from 3.1338mg.cm-2.h-1 to 0.2825mg.cm-2.h-1 was achieved by the addition of the leaf pastes of Sida Acuta at 30g per litre of 1.2M H2SO4. The prediction obtained using the artificial neural network gave the least error and was closer to the experimental corrosion rate value in comparison with the prediction by multiple regression.}, year = {2017} }
TY - JOUR T1 - Predictive Corrosion-Inhibition Model for Mild Steel in Sulphuric Acid (H2SO4) by Leaf-Pastes of Sida Acuta Plant AU - Agha Inya Ndukwe AU - Charles Nwachukwu Anyakwo Y1 - 2017/10/09 PY - 2017 N1 - https://doi.org/10.11648/j.jccee.20170205.11 DO - 10.11648/j.jccee.20170205.11 T2 - Journal of Civil, Construction and Environmental Engineering JF - Journal of Civil, Construction and Environmental Engineering JO - Journal of Civil, Construction and Environmental Engineering SP - 123 EP - 133 PB - Science Publishing Group SN - 2637-3890 UR - https://doi.org/10.11648/j.jccee.20170205.11 AB - The study of the corrosion inhibition of mild steel in sulphuric acid (H2SO4) by the leaf pastes of Sida Acuta was probed using the weight-loss technique. The highest inhibition efficiency of 91.46% with a reduction in corrosion rate from 3.1338mg.cm-2.h-1 to 0.2825mg.cm-2.h-1 was achieved by the addition of the leaf pastes of Sida Acuta at 30g per litre of 1.2M H2SO4. The prediction obtained using the artificial neural network gave the least error and was closer to the experimental corrosion rate value in comparison with the prediction by multiple regression. VL - 2 IS - 5 ER -