Abstract
Modelling and enhancing the production of green diesel in biodiesel industries have been hampered by the failure of the conventional approach to pursue space with continuous convergence velocity, being entombed in local minima, and maintaining unwavering resolutions. The study presented for the first time the optimization protocol for the development of biodiesel production from tobacco seed oil (TSO) on the batch reactor aided by the unique Grey Wolf Optimizer-Response Surface Methodology-Artificial Neural Network (GWO-RSM-ANN) techniques. Lower calorific value (LCV), higher calorific value (HCV), and specific heat capacity (Cp) correlations were postulated for tobacco seed oil methyl ester (TSOME/B100/TSOB) and diesel blends. RSM, ANN, and GWO approaches were used to model TSOME's main production yield. The ASTM test methods were used to examine the significant basic properties of the fuel categories, while the LCV and HCV were detected using standard procedures. Maximum TSOME yield (90.2%) was obtained at methanol/TSO molar ratio of 5.95, KOH content of 1.15 wt. %, and methylic duration of 77.6 min. The ANN model configuration (3-15-1) that was developed showed more adaptability and nonlinearity. The estimated coefficient of determination (R-2) of 0.9999, mean average error (MAE) of 0.00035, and RMSE of 0.00105 for the GWO model compared to those of R-2 of 0.9825, MAE of 1.3145, and RMSE of 1.7087 for RSM model; and R-2 of 0.9976, MAE of 0.2405, and RMSE of 0.6381 for ANN model vindicate the superiority of GWO model over the RSM and ANN models. The major fuel properties agreed with the ranges of the ASTMD6751 and EN 14214 specifications. The LCV, HCV, and Cp are also correlated with the TSOME fraction through the linear equations. There were excellent correlations between the analyzed and calculated values for the LCVs and HCVs. The maximum absolute error between the measured and estimated LCV and HCV are 0.108% for 20%TSOME (20% TSOME +80% diesel fuel), and 0.17% for pure diesel, respectively. The model and correlations can offer biodiesel and automobile industries with database information.