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Volume 116
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Parameter optimization of static mixers to enhance mixing performance
Libo Li a, Rui Tan a, Bei Wu a b *, Zixiao Shi a, Zihao Ou a, Yangbiao Huang a, Xu Li a b, Bang Ji a b, Dawei Liu a b, Fangping Xie a b, Ping Jiang a b
a College of Mechanical and Electrical Engineering, Hunan Agricultural University, Changsha, 410128, China
b Hunan Key Laboratory of Intelligent Agricultural Machinery and Equipment, Changsha, 410128, China
10.1016/j.partic.2026.06.008
Volume 116, September 2026, Pages 87-99
Received 24 March 2026, Revised 16 May 2026, Accepted 7 June 2026, Available online 12 June 2026, Version of Record 22 June 2026.
E-mail: wubei@hunau.edu.cn
Highlights

• Separating/blending angles and focal distance govern particle flow trajectories.

• RSM optimized angles (46.85°, 30.73°) and focal distance (−17.5 mm) for best mixing.

• Optimized design lowered experimental RSD to 7.87%, an 11.57% drop vs. preoptimization.


Abstract

Efficient and homogeneous mixing of granular ingredients is critical for product quality and cost-effectiveness in the food and feed industries. Although wedge-block static mixers offer a promising solution, the specific influence of their geometric parameters on mixing performance remains underexplored. This study integrates Discrete Element Method (DEM) simulations with Response Surface Methodology (RSM) to optimize a wedge-block static mixer for blending mung beans and brown rice. Single-factor DEM analyses identified key structural variables, which were subsequently optimized via RSM and validated through bench-scale experiments. Results indicate that the apex angles of the separating and blending wedges, along with the inter-group focal distance, significantly govern particle trajectories and diffusion rates. The optimal configuration-comprising a separating wedge angle of 46.85°, a blending wedge angle of 30.73°, and a focal distance of −17.5 mm-yielded a Relative Standard Deviation (RSD) of 2.29% in simulations and 7.87% in experiments. Notably, the optimized design reduced the experimental RSD by 11.57% compared to the pre-optimized design, demonstrating a substantial enhancement in mixing uniformity. The close agreement between DEM predictions and experimental data validates the proposed approach. These findings provide a robust theoretical basis and practical guidelines for designing high-efficiency static mixers tailored for granular food processing.

Graphical abstract
Keywords
Static mixer; Granular food mixing; Discrete element method (DEM); Response surface methodology (RSM); Granular mixing; Mixing uniformity
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