Heavy container trailers emit substantial quantities of tyre wear particles (TWPs) due to long-distance transportation, increasing ownership, and higher payloads. Owing to their multi-axle layouts, short-wheelbase and dual-tyre arrangement, these container trailers generate complex aerodynamic interactions that significantly influence TWPs dispersion, posing considerable challenges for efficient collection within such intricate flow fields. To address this issue, a comprehensive investigative framework and a novel collection strategy were both proposed. The Eulerian-Lagrangian approach, integrated with the Discrete Phase Model, was computationally implemented to validate the effectiveness and feasibility of the collection strategy. Equally important, a novel test rig was developed to conduct scaled-down experiments, along with a 3D-printed model, to validate the numerical model and simulation outcomes. To improve TWPs’ collection efficiency, two collection channels and a rectification chamber were proposed to reconfigure the airflow and form TWPs-enriched passages, integrating porous filters for collection. The optimal placement and geometric arrangement of these channels were determined, with inlet angles of 70° and 80° for the first and second channels, respectively, and a 60° triangular-shaped inlet for the third channel. The results show that a collection ratio exceeding 50% was achieved at a speed of 80 km/h in both laboratory experiments and numerical simulations. The maximum deviation between the simulation and experimental data was less than 6%, indicating high accuracy. These findings contribute to a better understanding of particulate matter dispersion and collection in a complicated flow field. In addition, this study provides valuable insights for policymakers, environmental researchers, trailer manufacturers, and tyre manufacturers in developing regulations and effective strategies to reduce TWPs’ emissions.
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Weisong Wang
Hui Shi
Weiqi Jiang
SHILAP Revista de lepidopterología
Engineering Applications of Computational Fluid Mechanics
Ningbo University
Chinese Research Academy of Environmental Sciences
China Railway Group (China)
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Wang et al. (Mon,) studied this question.
www.synapsesocial.com/papers/69d8930e6c1944d70ce04199 — DOI: https://doi.org/10.1080/19942060.2026.2654924
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