Value added biodiesel for corrosion inhibition

Abstract

Biodiesel is one of the prospective fuels, potentially capable of substituting petroleum fuel. Nevertheless, systems using this bioenergy resource are prone to corrosion than conventional fuels. Here, corrosion of copper metal in biodiesel with value added green coffee bean inhibitor has been evaluated by weight loss method, which produced 95.92% inhibition efficiency. Theoretically, corrosion is evaluated by artificial intelligence. The images of the surface obtained using CCD are augmented to 699 image samples. These augmented images are fed to back-propagation based neural network system for training, validation and classification for prediction of corrosion behaviour of copper in biodiesel with and without inhibitor. The neural network system has training, validation & testing prediction accuracies of 97.1%, 96.2% & 98.1%, respectively, and an overall accuracy of 97.1%. The proposed tool can be used to assess the corrosion behaviour dynamically in real time for futuristic prediction of corrosion behaviour of various metals including copper.