Optimization of Roasted Green Tea Winnowing via Fluid-Solid Interaction Experiments and Simulations.

Area of Science:

• Agricultural Engineering
• Food Processing Technology
• Computational Fluid Dynamics

Background:

• Achieving high winnowing accuracy in tea production is challenging due to complex tea leaf shapes and unpredictable airflow.
• Determining precise wind selection parameters is crucial for efficient tea sorting and quality control.

Purpose of the Study:

• To determine accurate wind selection parameters for tea winnowing through simulation.
• To enhance the precision and efficiency of tea wind sorting processes.

Main Methods:

• Developed a high-precision 3D simulation model for dry tea sorting using fluid-solid interaction.
• Validated the simulation model through experimental comparison of tea particle velocity and trajectory.
• Utilized weight-to-area ratio, discrete degree, drift limiting velocity, stratification height, and drag force for evaluation.

Main Results:

• Identified wind speed, distribution, and direction as key factors influencing winnowing efficacy.
• Determined optimal wind sorting parameters: 12 m/s wind speed, 45% distribution, and 10° wind direction angle.
• Established that a larger difference in weight-to-area ratios between tea leaves and stems improves sorting optimization.

Conclusions:

• The optimized parameters provide a theoretical foundation for designing advanced wind-based tea-sorting structures.
• Simulation-based parameter optimization significantly improves the precision of tea wind selection.
• This approach offers a pathway to higher quality tea production through enhanced sorting.