Arumugasamy S., Selvarajoo A., 2015, Feedforward Neural Network Modeling of Biomass Pyrolysis Process for Biochar Production, Chemical Engineering Transactions, 45, 1681-1686.
Growing energy needs and increasing environmental issues are creating awareness for alternative energy which substitutes the non-renewable and polluting fossil fuels. Biomass is a good feedstock for biochar production through the pyrolysis process. There is potential to generate solid fuel from biomass, as there are large quantities of agricultural wastes available in Malaysia. This paper outlines the experimental study on the pyrolysis of durian rinds in Thermogravimetric Analyzer (TGA). The effects of temperatures on the yield of biochar from the durian rinds were investigated. Increasing temperature resulted in increasing weight loss of the biomass sample. The total weight loss at the end of 920 °C was 86.9 %. This corresponds to the loss of water and volatile matter from the durian rinds. A multilayer feed-forward neural network (FANN) model was trained with an error back-propagation algorithm. Reaction time, temperature were used as the input parameters and weight loss was the output for the study. A FANN model with modeling performance of 2-20-1 was obtained for the study.
