Professor of Mechanical Engineering and Smart Structures, School of Computing Engineering and Mathematics, Western Sydney University, Australia. His research interests cover Industry 4.0, Additive Manufacturing, Advanced Engineering Materials and Structures (Metals and Composites), Multi-scale Modelling of Materials and Structures, Metal Forming and Metal Surface Treatment.
Abstract—The objective of this paper is to determine the optimal concentration of three types of nanoparticles (aluminium oxides, carbon nanotubes and silicone oxide) blended in diesel fuel. The fuel blends test was done with YANMAR TF120M single cylinder direct injection four stroke compression ignition engine. The experimental results of the brake specific fuel consumption (BSFC), exhaust gas temperature (EGT), carbon monoxides (CO), carbon dioxides (CO2), hydrocarbons (HC) and nitrogen oxides (NOx) were the analyzed by using Box-Behnken’s response surface methodology (RSM). The RSM was implemented with four variables such as concentration of nanoparticles and engine loads. The model evaluates using ANOVA and the model was used for optimization with the objective of reducing the fuel consumption, NOx and HC emissions. From this approach, Al2O3 of 45.82 ppm give the highest desirability of 0.9778 at 50% engine load.
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