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(110b) Discrete Element Modeling of Irregular-Shaped Switchgrass Particles for Integrated Process Optimization

Chen, Q. - Presenter, Clemson University
Tasnim, Z., Clemson University
Guo, Y., Clemson University
Xia, Y., Idaho National Laboratory
Mohammad, R., Idaho National Laboratory
Eksioglu, S., University of Arkansas
Switchgrass is a perennial herbaceous plant that is regarded as a biomass energy crop for its high adaptability and yield potential. Mechanical preprocessing and handling of switchgrass are challenging due to the erratic mechanical and flow behavior originating from its intrinsic particulate properties. In this work, we present our recent efforts in developing and validating a discrete element model (DEM) to simulate and predict the bulk behavior of switchgrass particles in support of integrated process optimization. The DEM model can capture three distinct particle characteristics of switchgrass, i.e., fibrous particle shapes, a wide range of particle size (both width and length) distribution, and high particle deformability. Particle shape templates were designed and generated based on results from image analysis of real switchgrass particles. Contact parameters of the numerical model were calibrated using data of a uniaxial compression test and Schulze ring shear test on both chopped and grinded switchgrass specimens. This numerical model was used to simulate and predict the bulk properties of switchgrass particles with a wide range of mean particle sizes, particle size distributions, and moisture contents. Furthermore, preprocessing tests of switchgrass bales were conducted using the Process Demonstration Unit at Idaho National Laboratory. The generated data were used to validate the developed DEM model. Validation shows the DEM model predicts the bulk densities of switchgrass with a high accuracy. Finally, the simulation results were compiled and integrated as mathematical regression models correlating particle bulk density to the particle size parameters as well as the moisture content, which is used in a system model developed to optimize the system performance.