An experiment-informed discrete element modelling study of knife milling for flexural biomass feedstocks

Journal Article · 06 November 2023 · Biosystems Engineering

DOI: https://doi.org/10.1016/j.biosystemseng.2023.10.008 · OSTI ID:2283681

Xia, Yidong  ^[1]; Klinger, Jordan Lee  ^[1]; Bhattacharjee, Tiasha ^[1]; Aston, John  ^[1]; Small, Mark ^[1]; Thompson, Vicki  ^[1]

---

1. Idaho National Laboratory (INL), Idaho Falls, ID (United States)

A discrete element method (DEM) based approach is used to study the relationships between material attributes (MAs), processing parameters (PPs), and quality attributes (QAs) for the knife milling of maize stalks. An approximate DEM shape model was conceptualized based on real maize stalks and calibrated based on experimental bending test data for flexural properties (elastic bending stiffness, elastic bending angle limit, elastoplastic ratio, etc.). DEM simulations of maize stalk comminution in a Jordan Reduction Solutions (“JRS”) knife mill were performed to investigate the relationships between the MAs (maize stalk size and breakage stress limit), PPs (impeller rotational speed), and QAs (mass throughput and output particle size distribution (PSD)). The DEM results suggest that stalk length has little influence on mass throughput and PSD, whilst stalks with larger cross sections tend to generate larger sizes of milled particles given the same breakage stress limit. Both the DEM and experimental results show that faster impeller rotation (or higher power) does not necessarily generate higher throughput or smaller output PSD, especially for maize stalks of higher breakage stress limit. The correlations between these MAs, PPs and QAs are found highly stochastic, though breakage stress limit dictates mass throughput, regardless of stalk size. The DEM-predicted output particle size tended to match the experimental data with coarse PSDs based on sieve size but showed weakened fidelity with finer material, indicating the potential for further model improvement.

• Research Organization: Idaho National Laboratory (INL), Idaho Falls, ID (United States)
• Sponsoring Organization: USDOE Office of Energy Efficiency and Renewable Energy (EERE), Office of Sustainable Transportation. Bioenergy Technologies Office (BETO)
• Grant/Contract Number: AC07-05ID14517
• OSTI ID: 2283681
• Report Number(s): INL/JOU-24-76070-Rev000; TRN: US2408852
• Journal Information: Biosystems Engineering, Vol. 236, Issue -; ISSN 1537-5110
• Publisher: ElsevierCopyright Statement
• Country of Publication: United States
• Language: English