Waste tyre pyrolysis oil-hemp biodiesel ternary blends with graphene oxide and thermal barrier coating: CI engine...

This research investigates the synergistic effects of the 10% waste tyre pyrolysis oil, 10% hemp seed biodiesel, and 80% diesel blend in addition to graphene oxide nano additive (25, 50, 75, 100 ppm) and a partially stabilised zirconia thermal barrier coating on a Kirloskar TV1 single-cylinder, four-stroke CI engine (5.2 kW, CR 17.5:1, 1500 rpm). Six response variables were investigated: brake thermal efficiency (BTE), brake-specific fuel consumption (BSFC), unburned hydrocarbons (HC), carbon monoxide (CO), nitrogen oxides (NO_x), and smoke opacity at a load of 0% to 100%. The B20GO50 has peaked in BTE at 35.36% with an increase of 4.12% against diesel and a BSFC of 0.25 kg/kWh, which is lesser by 7.4%. The B20GO50 + TBC configuration achieved a BTE of 36.22% (+ 6.65%), CO of 0.15% (- 40%), HC of 32 ppm (- 25.6%) and around a 20% reduction in smoke. NO_x emission was maintained at 1010 ppm, which shows an increment of 2.4% compared to the neat diesel at full load. The dataset was partitioned into 80% training (n = 58) and 20% testing (n = 14) subsets using stratified random sampling. Nine regression algorithms were evaluated under five-fold cross-validation with systematic hyperparameter tuning. Nine regression algorithms in ML were trained on a dataset that contained ten distinctive features. The algorithm set includes XGBoost, Gradient Boosting (GB), Random Forest (RF), Linear Regression, Ridge, Lasso, Elastic Net, Support Vector Regression (SVR) and K-Nearest Neighbours (KNN). The highest R² across all models was 0.9905 (RMSE = 7.05) for XGBoost, followed by GB with R² = 0.9888 and RF with R² = 0.9714. SHAP analysis indicated that engine load was by far the most predominant feature affecting BTE, BSFC and the CO and NO_x emissions. GO and TBC were the main determining variables for HC and smoke. Overall, the results prove XGBoost as the most efficient multi-output model for characterisation of CI engines, particularly in terms of complex interactions involved between fuel, additives, and hardware. The B20GO50 + TBC configuration achieved a BTE of 36.22%, an absolute gain of 6.65% points over neat diesel at full load, yielding an estimated fuel cost saving of INR 6000-7800 per 1000 operating hours at current diesel prices. Concurrently, CO was reduced by 40% and HC by 25.6%, demonstrating regulatory compliance potential under BS-VI emission norms without engine hardware modification.