Predicting Conversion from Pyrolysis of Pongmia

Abstract

Abstract This research demonstrates the technique of predicting pyrolysis of lignocellulosic biomass. Modeling of pyrolysis of biomass is complex and challenging because of short reaction times, temperatures as high as a thousand degrees Celsius, and biomass of varying or unknown chemical compositions. As such a deterministic model is not capable of representing the pyrolysis reaction system. To be able to predict a pyrolysis reaction of an unknown lignocellulosic biomass without an experimental data support or data fitting is an even more challenging work. In this research, we are trying to predict pyrolysis of Pongmia in Nitrogen to demonstrate that our technique is useful for predicting pyrolysis reaction of other biomass source. There are three main chemical compositions in lignocellulosic biomass which are cellulose, hemicellulose and lignin. We are considering that the total pyrolysis reaction is affected by the reaction of three main compositions. However, these three main chemical compositions of biomass is vary not only by type of biomass but also by other things such as where it is grown or even which part of biomass since the chemical compositions in the leaf can be different from the trunk. Our propose method is an extending study of our previous paper “pyrolysis of biomass – fuzzy modeling”. Our model successfully gives a good predicting result. The result shows that our model can predict 91.82% of pyrolysis of Pongmia in Nitrogen correctly without any data from the experiment. Therefore, we could use this method to predict other lignocellulosic biomass before we perform an experiment.