Title : Prediction and characteristics optimization of a DI-CI engine fueled with pyrolysis oil-diesel blends doped with nano fuel additives using artificial intelligence
Abstract:
The depletion of fossil fuels, strict pollution regulations, rising energy costs, and fluctuating petroleum product prices in India have made alternative fuels for diesel engines essential. Finding substitute fuels is critical to solving this issue. The primary goal of this research is to clarify the significance of pyrolysis oil as a diesel engine substitute fuel.
In this regard, there has been an increase in interest in pyrolysis oil. In a four-stroke, single-cylinder, water-cooled compression ignition engine, the characteristics of the engine, including combustion, performance, and emissions of pyrolysis oil dopped with nano additive, are to be studied without any engine adjustments. Additionally, the prediction and characteristics optimization by RSM has been validated by experimental results and further authenticated with ANN. The research was conducted with the twin goal of reducing environmental effects while prioritizing economic sustainability.
This research will also concentrate on the idea that engine overall performance estimation benefits from higher accuracy certainty from ANN models. It gives positive indications for using the ANN to predict engine operating behavior in the future. The innovative technique of using artificial neural networks (ANNs) to predict and optimize characteristics for pyrolysis oil diesel blended fuel in DI CI engines promotes a healthier, more economical, and cleaner environment.
