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(144a) A Nano-CT Informed Polyhedral Discrete Element Modeling Approach for Flow of Complex-Shaped Granular Woody Biomass

Authors: 
Xia, Y. - Presenter, Idaho National Laboratory
Chen, F., Clemson University
Klinger, J., Idaho National Laboratory
Kane, J., Idaho National Laboratory
Bhattacharjee, T., Idaho National Laboratory
Seifert, R., Idaho National Laboratory
Ajayi, O., Argonne National Laboratory
Chen, Q., Clemson University
The design of handling equipment for granular biomass primarily requires experiments. Discrete element models (DEM) can provide designers with detailed insight into the behavior of granular materials. However, granular biomass comprising complex-shaped particles is difficult to model with DEM. A tomography-informed DEM approach and an exhaustive assessment of the ability of the approach to predict the bulk behavior of milled pines using experimental data is presented. Nano-CT scan was conducted to obtain 3D particle surface geometries as the basis for particle shape approximation by a polyhedral model and a sphero-polyhedral model. These models were applied in the simulation of a compressibility test. Our parametric study showed that particle Young’s modulus and restitution coefficient are the two main properties influencing the simulated bulk behavior of the DEM particles and that the level of approximating DEM particle shape for real particles is critical for accurately replicating the bulk behavior of milled pines. The polyhedral model demonstrated better suitability than its sphero-polyhedral counterpart for modeling pine particles. The polyhedral model calibrated in a compressibility test was then applied in the simulations of a friction test without additional parameter tuning. Interlocking was dominant in the shear of bulk pine particles. Remarkably, the polyhedral model predicted the frictional behavior of the pine particles when compared to the experimental results. The limitations of the model, as well as possible ways for enhancement, are discussed. This work provided novel insights into the suitability of complex-shaped DEM models for granular woody biomass.