Using Nanoparticles as a new generation of diesel fuel additives. Exprimental and numerical consideration, with the aid of artificial neural network

      Аннотация: Reduction of exhaust emission and fuel consumption is one of the most important challenges in the engine communities. One of the methods to overcome the issue is improving fuel by modification or reformulation of its composition. To this end, the experiments were conducted such that the power, emissions, and fuel consumption on a CI diesel engine were altered using fuel blend of diesel with nanoparticles. Decrease in the fuel consumption and lower amounts of NOx, HC, and CO emissions than that of base fuel are the results of using nano additive. An alternative method for analysis and predictions in engineering area especially in internal combustion engines [55-58], is using of Artificial Neural Network (ANN). ANN simulation has gained ground in many engineering applications due to its simplicity, accuracy, and convergence rate in comparison with numerical means particularly while dealing with fuzzy and complicated database. ANN modeling was adopted to predict a correlation between brake power, fuel consumption, HC, CO, NOx using different amounts of nanoparticles and speeds as input data.

Ключевые слова: Additive, artificial neural network, Emissions, energy crisis, Environmental Problems, Fuel consumption, IC Engine, Nanoparticles, performance