Numerical analyses of maize particle dispersion dynamics in air-sieve cleaning systems: CFD–DEM modeling integrated with standard deviation

• Revealing particle dispersion mechanisms in coupled airflow-comb tooth systems. • Evaluation models for particle dispersion coefficients have been constructed. • Exploring dynamic responses of comb-tooth variables to maize dispersal. • Comb-tooth sieves reduce grain loss rate and system energy consumption. This study investigates maize particle dispersion kinetics on a comb-tooth sieve to reduce grain loss and energy consumption during maize harvesting. Specifically, a spatiotemporal particle dispersion model is developed by integrating the computational fluid dynamics–discrete element method with a standard deviation–based approach. The model elucidates the manner in which the inclined angle, length, and spacing of the comb teeth collectively regulate particle dispersion perpendicular to and along the sieve surface. Moreover, the particle aggregation and dispersion mechanisms are analyzed through comparisons of the transient, regional, and total dispersion coefficients under different comb-tooth parameters. These insights guide the identification of the optimal comb-tooth sieve configuration, namely, 60° inclination, 70-mm length, and 10-mm spacing, under which impurities are effectively thrown toward the posterior sieve region, reducing their carrying effect on the grains. Additionally, more grains pass through the gaps between the comb teeth and migrate onto the sieve surface, increasing the likelihood of penetration through the holes. Ultimately, relative to traditional plane sieves, the optimized comb-tooth sieve enables 32.6% lesser grain loss and 26.4% lower energy consumption. Thus, this study establishes a response mechanism linking dispersion behavior to cleaning performance, supporting precision design of grain cleaning systems.