Project

Assessment of a slow biomass pyrolysis technology using the artificial neural network model (ANN)

Goal: The project describes the application of the Artificial Neural Network (ANN) in a technical-scale reactor plant (pyrolyzer) to predict the behavioural activities of the combustible effects of temperature and other selected parameters, gas yield and the formation of biochar. The importance of this project is to develop an evaluative model for a slow pyrolyzer to attain high energy efficiency and less energy consumption. Therefore, the scientific aim is to find out if the artificial neural network is an alternative means to significantly improve data quality, combustion process and energy supply for the reactor under research level.

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Alex Tagbo
added a research item
This is a typical example showing an interesting trend in the application of neural network in the field of renewable energy and biomass over the last decades.
Alex Tagbo
added an update
My update so far: After series of discussions from past seminars, I have focused my attention first on biochar production from the slow pyrolysis process (due to its slower heating rate and longer residence time capacity) with influencing parameters that ensures a highly rich carbonaceous product. For this purpose, it has driven my interest towards agriculture for soil amelioration. Based on this development, the points listed are currently ongoing: 1) Systematic study of pyrolytic parameters influencing the enrichment of the soil 2) Review of a selected neural network model (method) for training accuracy (performance). A technical report (installation and application of method) has successfully been prepared and; 3) Data collection from pyrolysis experiments for training the model.
 
Alex Tagbo
added a project goal
The project describes the application of the Artificial Neural Network (ANN) in a technical-scale reactor plant (pyrolyzer) to predict the behavioural activities of the combustible effects of temperature and other selected parameters, gas yield and the formation of biochar. The importance of this project is to develop an evaluative model for a slow pyrolyzer to attain high energy efficiency and less energy consumption. Therefore, the scientific aim is to find out if the artificial neural network is an alternative means to significantly improve data quality, combustion process and energy supply for the reactor under research level.