Experimental investigation on dispersing graphene-oxide in biodiesel/diesel/ higher alcohol blends on diesel engine using response surface methodology

Lower alcohols have long been the figureheads of diesel/biodiesel additives in characterizing renewable fuels. Next-generation alcohol like n-octanol occupied the reified position due to their better fuel properties. In this paper, combustion, performance and, emission of different graphene-oxide nanoparticles (nanoGO) added jatropha biodiesel, n-octanol and petrodiesel blends are investigated in a 4-stroke DI diesel engine. This article also aims to optimize the engine inputs accountable for better performance and emission characteristics of a diesel engine running with nanoGO dispersed biodiesel/diesel/higher alcohol blends. Full Factorial Design-based Response Surface Methodology (RSM) is utilized to model the experiments using Design-Expert software to optimize engine responses. Validation of the developed model is carried out using sophisticated error and performance metrics, namely, TheilU2, Kling-Gupta Efficiency (K-G Eff), and Nash-Sutcliffe coefficient of efficiency (N-S Eff) along with the conventional statistical database. The model optimized engine inputs of 3.898% n-Octanol, and 49.772 ppm nanoGO at 99.2% load with a desirability index of 0.997 as the optimum engine parameters. The experimental validation revealed that the model optimized blend at full load witnessed a reduction of 15.6% CO, 21.78% HC.u, and 3.26% NOx emission compared to petrodiesel. However, a slight increase in brake specific energy consumption (2.95%) is also recorded because of the lower heating value of the blend.