Autonomous Kinetic Modeling of Biomass Pyrolysis using Chemical Reaction Neural Networks

Understand

Modeling the burning processes of biomass such as wood, grass, and crops is crucial for the modeling and prediction of wildland and urban fire behavior.

• Despite its importance, the burning of solid fuels remains poorly understood, which can be partly attributed to the unknown chemical kinetics of most solid fuels.
• Most available kinetic models were built upon expert knowledge, which requires chemical insights and years of experience.
• This work presents a framework for autonomously discovering biomass pyrolysis kinetic models from thermogravimetric analyzer (TGA) experimental data using the recently developed chemical reaction neural networks (CRNN).