Analysis of Combustion CI Engine Fuelled with Algae Biofuel Blends using ANN

Abstract

Due to its potential for high yield, quicker rate of growth, biocompatible, non toxicity, dioxide, low emission profile, and use of non arable land and non potable water with less publicity and resource consumption, algae based biofuels are the most effective lengthy solutions to the energy crisis and global warming. In this research, a biofuel made by transformed into chlorella algae oil was used. M oreover, fuel and algae were mixed to produce bio fuels blends on a volumetric basis for a net unit volume. By providing a comprehensive database of the characteristics of algal biofuel blends as next generation biofuel and their use in a current diesel engine without modification, this thesis attempts to provide the necessary facts in the field of biofuel technology. Future biofuel research will be made easier by the research technique and computer model built in this study, which can be used for extende d validation and prediction reasons. In order to determine whether algae based biofuel is suitable to replace conventional fuel and thus satisfy all of our transport fuel needs, the key findings of this research are expected to serve as the foundation for future developments in the use of algae based biofuel as a feedstock for commercial large scale production of biofuels in an economically effective, technically feasible, and environmentally friendly manner.

Keywords: Biofuel, Algae oil, Artificial Neural Network, Compression Ratio, Back Propagation

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