Machine Learning Constitutive Model for Granular Biomass Material

Granular biomass materials sourced from forest or agricultural residuals show great promise as a renewable and eco-friendly energy source. Nevertheless, effectively feeding and managing granular biomass for biorefineries presents challenges due to its intricate mechanical properties. This project's primary goal is to develop a machine learning constitutive model that can grasp the inherent stress-strain relationship, significantly surpassing current numerical models in terms of speed while offering deeper insights into the materials' mechanical behavior.