@article{ZHANG2026, 
author = {Ling ZHANG and Xiao LIU and Dan XIE and Chengji MI},
title = {Numerical simulation and experimental study on household waste separation and recovery using density-based air classification},
year = {2026},
journal = {Transactions of the Chinese Society of Agricultural Engineering},
volume = {42},
number = {6},
pages = {263-271},
keywords = {air classification, recyclable waste, numerical simulation, collection efficiency, optimization design},
url = {https://www.sciopen.com/article/10.11975/j.issn.1002-6819.202510081},
doi = {10.11975/j.issn.1002-6819.202510081},
abstract = {Sorting and recycling have been widely used to treat the municipal solid wastes against the ever increasing urbanization. It is often required for the overall efficiency for the long-term sustainable development. In this study, the density air classification was proposed for the household waste separation and recovery, according to the aerodynamics and fluid mechanics. Recyclable materials were selected from the urban waste stream, including ferrous iron scraps, non-ferrous aluminum products, various engineering plastics, and high-quality cellulose products. There were the density differences among these structurally diverse and heterogeneous materials. High efficient, rapid, and simultaneous separation of multiple components was conducted in complex mixed wastes. Thereby the recycling workflow was optimized to reduce the operational costs. Computational fluid dynamics (CFD) simulations and experiments were also adopted to verify the effectiveness of classification. A systematic investigation was implemented to visualize the movement patterns, dynamic motion trajectories, and sorting characteristics. Four types of recyclable wastes were selected for the dynamic air classification. Fluid flow fields were accurately simulated for the particle-particle interactions. Different materials were individually responded to the specific aerodynamic forces. Three influencing parameters were selected as the variables to optimize the separation efficiency: particle size distribution, inlet airflow velocity, and airflow angle. Meanwhile, the accurate collection rate was obtained as the primary evaluation. An orthogonal test was conducted for the optimal parameters after experimentation. The results show that the optimal combination of the parameters was achieved with the 5 mm particle size, 36 m/s inlet airflow velocity, and 14° airflow angle. The optimal collection rate reached 95.875% during simulation, indicating the excellent separation performance with the high purity in the final separated materials. Additionally, the visualization techniques—including high-resolution high-speed cameras and real-time trajectory tracking—were used to accurately record the trajectories of particle motion during separation. The empirical observations were closely aligned with the simulation to effectively validate the accuracy, reliability, and stability of the density air classification. The better performance of experiment was achieved in the collection rates of 93.300% for regularly spherical materials and 91.250% for uniformly flat materials. The structural and operational parameters were also optimized for the equipment during industrial-scale air classification. The recycling rates were continuously improved for the urban and rural household wastes. Great contribution was also gained to promote the higher levels of waste disposal for the less pollution in sustainable circular economy. Effective waste segregation can offer the valuable insights into the application of aerodynamics. More sustainable, efficient, and cost-effective waste disposal can be expected to reduce resource waste for the ecological conservation}
}