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Volume 116
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Elucidating the mesoscopic kinetics of seed pelleting via a moisture-driven dynamic cohesion DEM model
Zilong Jia a, Ziyuan Fang a, Weiqi Lu a, Youming Yang a, Yubin Bi a b, Yuxiang Huang a b *
a College of Mechanical and Electronic Engineering, Northwest A&F University, Yangling, 712100, China
b Hainan Institute of Northwest A&F University, Sanya, 572000, China
10.1016/j.partic.2026.06.024
Volume 116, September 2026, Pages 188-201
Received 7 April 2026, Revised 3 June 2026, Accepted 19 June 2026, Available online 27 June 2026, Version of Record 3 July 2026.
E-mail: hyx@nwsuaf.edu.cn
Highlights

• A novel moisture-driven dynamic cohesion DEM model for seed pelleting is proposed.

• Cohesion is self-adaptively updated via API based on time-varying moisture.

• Mesoscopic kinetics of nucleation, growth, and consolidation are characterized.

• Radial distribution deviation provides structural evidence for densification.


Abstract

Seed pelleting is essential for precision agriculture, but DEM simulation remains challenging because wet-powder cohesion evolves with moisture rather than remaining constant. This study developed a moisture-driven dynamic cohesion DEM framework based on an experimental-to-numerical inversion strategy. During physical pelleting, the time-varying moisture content of the coating powder, was measured by oven drying and mapped onto the compressed DEM timescale. At representative moisture levels, angle-of-repose tests were performed and corresponding DEM simulations were inversely calibrated to back-calculate the equivalent cohesive energy density, yielding a time-dependent cohesion function. This function was implemented in EDEM through a customized C++ API to update contact cohesion automatically. A Bond-number-conserved differential coarse-graining strategy was also introduced to reduce computational cost while preserving cohesive similarity. The model was validated under different operating conditions. The simulated inter-pellet coefficient of variation in coating mass was strongly and negatively correlated with the experimental qualification rate (R2 = 0.89). Under optimized conditions of 918 rpm pan speed, 1.94 g powder feed, and 0.53 g liquid supply, the qualification rate reached 94.8%, with a relative prediction error of 2.4%. Mesoscopically, the model reproduced primary adhesion, secondary layering, and refining-induced densification.

Graphical abstract
Keywords
Discrete element method (DEM); Seed pelleting; Coarse-graining scaling; Moisture-driven cohesion model; Mesoscopic consolidation mechanism
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