(119c) Experimental Extraction of Lignocellulosic Biomass Morphological Characteristics for Realistic Representation in Superquadratic Discrete Element Computational Models

The morphological characteristics of lignocellulosic biomass particles, e.g., wood, agricultural residues, and grasses, play an important role in the accuracy of discrete element simulations of the flow behavior of these materials. However, the estimation of morphological parameters is often challenging due to the inherent variability of the size, shape, and distribution of these biological materials. In this study, we propose a rational approach to determine important morphological parameters as inputs in discrete element modeling (DEM) and examine the validity of our proposed approach using an angle of repose case study.

We selected switchgrass ground and sieved through 40 mesh (425 μm) screen as the lignocellulosic biomass sample in this study. We determined the shape parameters and size distributions of the switchgrass sample using a dynamic particle image analysis process. We then qualitatively and quantitively analyzed the switchgrass surface roughness characteristics by digital scanning, scanning electron microscopy (SEM), and atomic force microscopy (AFM) techniques. We generated polydisperse, superquadratic particle assemblies in the open-source DEM package LIGGGHTS using the extracted morphological parameters in the previous step. Furthermore, we implemented the angle of repose study using the hollow cylinder method in the DEM environment and designed validation experiments with a geometrically identical angle of repose test system. We measured the angle of repose and the associated coefficient of friction of the resulting pile for the experiments and simulations and compared our results for validation.