Data driven modelling of biomass pyrolysis
Access Status
Open access
Authors
Sawant, Ruturaj Jayant
Date
2024Supervisor
Pareek, Vishnu
Gale, Julian
Rohl, Andrew
Type
Thesis
Award
PhD
Metadata
Show full item recordFaculty
Science and Engineering
School
WA School of Mines: Minerals, Energy and Chemical Engineering
Collection
Abstract
A set of experiments to determine the composition of biomass samples were performed. Conversion profiles and rate of reaction profiles for biomass samples at different heating rates were studied. Existing kinetic methods were used to study the reaction kinetics of biomass pyrolysis. A novel predictive modelling approach was developed for biomass pyrolysis. Artificial neural networks were used to develop models capable of predicting conversion and rate of reaction profiles for unknown biomass samples. This approach has the potential for dynamic control of heterogenous feedstock and is applicable over wider heating rate range.
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