Prediction of Efficiency of Water Hyacinth as Corrosion Inhibitor of Steel in Marine Environment Using Multiple Linear Regression

Corrosion of steel structures in marine environments is a critical issue affecting infrastructure integrity and maintenance costs worldwide. Generally, inhibitors have proven to reduce the corrosion rate to the barest minimum than other methods. The inhibitors are produced using the experimental method which is time consuming and costly. This necessitate the development of models for the quick assessment of the efficiency of the inhibitor. This research focused on the prediction of corrosion inhibitory efficiency of water hyacinth on mild steel in marine environment using multiple linear regression (MLR) method. Various concentrations (5 ml, 10 ml, 15 ml, 20 ml and 25 ml) were added to the samples immersed in seawater and a sample without the addition of the inhibitor was used as the control for a period of 30 days. The study was carried out using weight loss method and the corrosion rate as well as the inhibition efficiency were calculated. Phytochemical analysis and atomic absorption spectroscopic were carried out on the inhibitor while Scanning Electron Microscopy and Energy Display X-ray Spectroscopy were used to analyze the steel sample. The analysis of the result showed that the best inhibition efficiency obtained was 90% and this was achieved with 15% concentration of the inhibitor. Multiple linear regression model was developed to predict the inhibitor’s efficiency. The predicted efficiency with the MLR model was compared with that of the experimentally obtained efficiency and the outcome shows a conformity between the experimental and the predicted value. It would therefore be recommended to rely on multiple linear regression in predicting the efficiency of water hyacinth for corrosion control of mild steel in marine environment based on the closeness of the predicted values to the experimental values.