Optimization Analysis of a Compression Ignition Engine Running with Silver Oxide and Titanium Dioxide Nanoparticles Blended into Canola Biodiesel and Pure Diesel Using Taguchi Technique
نویسندگان
1 Mechanical Engineering Department, Faculty of Engineering, Karabük University, Karabük, Turkey.
2 Department of Mechanical Engineering, Ferdowsi University of Mashhad, Mashhad, Iran.
3 Nigde Vocational School of Technical Sciences, Nigde Ömer Halisdemir University, Nigde, Turkey.
4 Department of Mechanical Engineering, Ferdowsi University of Mashhad, Mashhad, Iran.
doi
10.22059/jchpe.2024.374752.1500چکیده
The present experimental investigation examines the impact of adding silver oxide and titanium dioxide nanoparticles as fuel additives to diesel and canola biodiesel upon a diesel engine's exhaust emission and performance parameters. Titanium dioxide and silver oxide nano-additives were dispersed in canola and diesel at 50 and 75 ppm concentrations. The results indicate that adding silver oxide and titanium dioxide nanoparticles into diesel and canola enhanced the brake thermal efficiency and reduced the brake-specific fuel consumption. The findings also reveal that adding nanoparticles significantly reduced CO and smoke emissions, whilst NOx emissions increased. At 40 Nm load condition, adding 75 ppm titanium dioxide to canola leads to a 6.5% reduction of brake-specific fuel consumption, 6.2% improvement in brake thermal efficiency, 24% CO emissions reduction, 16% increase in NOx emission, and a 39.1% smoke emission reduction. Moreover, dispersing 75 ppm silver oxide into canola under 40 Nm engine load results in a 4.4% decrease in brake-specific fuel consumption, a 4.1% brake thermal efficiency enhancement, a 16.4% reduction of CO, a 7.5% increment in NOx emission, and an 18.5% smoke emission reduction. According to the Taguchi analysis, the overall optimum condition is obtained when the engine is fueled with 75 ppm silver oxide nano-diesel at 10 Nm engine load. Consequently, although the desired system output conditions are associated with different input parameters based on the findings, applying the Taguchi method enables us to identify the specific conditions under which optimal system performance is attained.