Elumalai Arulkumar

Improving the efficiency and emission characteristics of biodiesel fueled CI engine remains challenging due to limitations in fuel reactivity and combustion behavior. This study investigates the combined effect of dimethyl carbonate (DMC) and cobalt chromite nanoparticles on engine performance and emissions, supported by machine learning-based prediction. Experiments were carried out on a single-cylinder diesel engine using five fuel blends including diesel, J20, J20D10, J20D10C50, and J20D10C100 across the full load range. The J20D10C100 blend delivered the highest BTE of 29.67%, showing improvements of 13.57% over diesel and 20.78% over the J20 blend. Brake specific fuel consumption decreased to 0.375 kg per kWh, corresponding to reductions of 5.44% and 6.38% compared with diesel and the J20 blend. At full load, CO decreased from 0.53% to 0.454%, HC reduced by 14.6%, and nitrogen oxides decreased from 1070 ppm to 990 ppm. Smoke opacity showed a reduction from 67.21% to 65.19%. Among the predictive models, gradient boosting achieved the highest accuracy with an R ² of 0.965, followed closely by random forest with 0.964. The results confirm that the proposed fuel formulation enhances engine performance while reducing emissions, which supports reliable predictive modeling.

Renewable fuels and advanced nanomaterials are being investigated to address the growing demand for sustainable energy and reduced diesel engine emissions. Biodiesel blends and nanocomposite additives can improve CI engine efficiency and emission characteristics. This research investigates the combined use of hydrogen enrichment and a multifunctional CuO‐WO ₃ ‐g‐C ₃ N ₄ (CWOGCN) ternary nanocomposite to improve the performance and emission characteristics of a CI engine fueled with a 20% honge oil methyl ester blend (H20). The developed CWOGCN nanocomposite was characterized using XRD, SEM–EDX with elemental mapping, FTIR, and XPS analyses. The results confirmed the crystallinity, surface morphology, elemental composition, chemical states, and uniform elemental distribution of the synthesized nanocomposite. Engine experiments were conducted using 50 and 100 ppm CWOGCN nanocomposites with 10 LPM hydrogen enrichment under varying engine load conditions. The highest brake thermal efficiency (BTE) of 30.16% was obtained at 4.78 kW, while the lowest brake specific fuel consumption (BSFC) was 0.446 kg/kWh. Compared with diesel operation, the hydrocarbon emission was reduced to 38 ppm, carbon monoxide emission decreased to 0.12%, NO _x emission was limited to 842 ppm, and smoke opacity was reduced to 42%. The RSM models showed high predictive capability ( R ² = 0.991), while machine learning models, particularly Gradient Boosting, showed superior nonlinear prediction performance. The combined experimental, RSM, and machine learning analysis demonstrated that H20CWOGCN100H provided improved thermal efficiency and reduced exhaust emissions, highlighting the potential of hydrogen‐enriched ternary nanocomposite biodiesel blends for cleaner and more efficient CI engine operation.

This study investigates the synergistic effects of oxygenated additives and ammonia enrichment on the performance, combustion, and emission characteristics of Juliflora methyl ester blends in a single‐cylinder CI engine. DIPE and pentanol were each blended with JFME (10% vol) and further enriched with ammonia at a constant flow rate of 10 lpm. Results, showed that the BTE of JFME is 26.93% which was 4.7% lower than that of diesel (28.26%). However, JD10 and JP10 blends improved BTE by 2.4% and 4.6% over diesel, respectively. With ammonia enrichment, BTE further increased to 29.98% for JD10A10 and 30.46% for JP10A10, showing up to 7.8% improvement over diesel. Combustion analysis showed peak in‐cylinder pressures of 61.75 bar and 63.75 bar by JP10A10 blend, both higher than diesel and JFME. A maximum HRR of 54.23 J/°CA was observed for JP10A10. Emissions of HC and CO were significantly reduced, with JP10A10 achieving 56.8% and 47.6% reductions as compared to diesel. NO _x and smoke emissions were also reduced with the ammonia‐enriched blends. RSM was used to optimize the engine operating parameters, specifically engine load and fuel blend %. Under the optimum operating conditions corresponding to a 51.12% engine load the JP10A10 blend engine produced 23.09% BTE, 0.2791 kg/kWh BSFC, 19.606 ppm HC, 0.1465% CO, 1099 ppm NO _x and 21.48 ppm smoke. These findings highlight the potential of JFME‐based dual‐fuel strategies using reactive oxygenates and ammonia to enhance efficiency and reduce emissions in CI engines.