The attributes of renewability and environmental friendliness have made ethanol a preferable alternative to methanol in the production of biodiesel from lipid feedstocks. For the first time, this study adopted Response Surface Methodology (RSM) and Artificial Neural Network (ANN) to model coconut oil ethyl ester (CNOEE) yield. Transesterification parameters such as reaction temperature and ethanol/coconut oil molar ratio and catalyst dosage were varied. Maximum CNOEE yield of 96.70% was attained at 73 °C reaction temperature, 11.9:1 molar ratio, and catalyst dosage of 1.25 wt. %. The experimental yield was in agreement with the predicted yield. Central Composite Design was adopted to develop the RSM while feed-forward back propagation neural network algorithm was employed for the ANN model. Statistical indices were employed to compare the models. The computed coefficient of determination (R²) of 0.9564, root-mean-squarce-error (RMSE) of 0.72739, standard error of prediction (SEP) of 0.008021, mean average error (MAE) of 0.612, and average absolute deviation (AAD) of 0.674901 for RSM model compared to those of R² (0.9980), RMSE (0.68615), SEP (0.007567), MAE (0.325), and AAD (0.3877) for ANN indicated the superiority of the ANN model over the RSM model. The key fuel properties of the CNOEE met with those of biodiesel international standards.

Biodiesel has recently received increasing attention because of many advantages such as higher cetane number and flash point compared to diesel fuel. However, corrosion of engine parts exposed to biodiesel or biodiesel-diesel fuel blends is still a critical challenge in the biodiesel industry. In the existing literature, there is still a lack of systematic studies including corrosion process in light alloy and changes in mechanical and fuel properties of engine parts (such as brass) after exposure to biodiesel. Therefore, in this study, (1) waste sunflower oil biodiesel (WSOB, B100) was supplied and blended with diesel fuel (B0) at the volume ratios of 10%, 20%, and 40 , which are called as B10, B20, and B40, as usual. The important fuel properties of the biodiesel-diesel fuel blends were also analyzed using ASTM test methods. (2) Corrosion characteristics of brass exposed to the biodiesel-diesel fuel blends were determined by means of a static immersion method at room temperature. (3) Mechanical properties of brass were investigated before and after the corrosion test. Finally, (4) variations in surface morphologies of the brass coupons were researched. According to the experimental results, the corrosion rate (0.3810 mpy) of brass exposed to B100 was found to be higher than that of brass exposed to B0 (0.1330 mpy) for the exposure duration of 960 hours. The Brinell hardness numbers (BHN) were determined as 406.265, 477.713, 541.983, 579.448, and 636.602 N/mm² while the tensile strengths (TS) were 1381.30, 1624.22, 1842.743, 1970.13, and 2164.45 MPa for B0, B10, B20, B40, and B100, respectively. BHN and TS values of B10 were closer to that of B0. Therefore, B10 was found to be a more suitable alternative to diesel fuel in terms of fuel property and corrosion characteristic. The results of this study can promote thermo-physical property collection for biofuels and guide for corrosion studies related to the industrial applications of diesel-biodiesel blends and pure biodiesel.