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Numerical modeling of large spherical microplastics transport and deposition using CFD-DEM
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A computer model was used to simulate how round microplastic particles move and settle in flowing water under different conditions, such as water speed, depth, and channel shape. The model matched lab measurements with over 63% accuracy and showed that results depended strongly on friction settings and the number of particles used in the simulation.
The transport and deposition patterns of microplastics (MPs) in water are significantly influenced by the hydraulic characteristics of the surrounding fluid flow, including the water level, flow velocity, and the bathymetric and geometric conditions of the water bodies. Accordingly, this study aims to employ an Eulerian-Lagrangian numerical modeling approach to illuminate spherical MPs transport and deposition patterns by comparing different scenarios applied to flow and channel geometry. Various test scenarios were simulated to assess the impact of various variables, including the flow velocity ( u f ), depth of turbulent flows ( w ), deepening of the channel bed ( d ), and slopes applied to the bottom of the channel bed ( s ). The utilized numerical model is based on the unresolved computational fluid dynamics (CFD) model coupled with discrete element method (DEM) solver, which was validated against laboratory experimental measurements. The results demonstrated that the CFD-DEM could simulate MPs transport and deposition with an accuracy of over 63 %. Additionally, the model effectively captured the effects of hydraulic parameters ( w, u f , d , and s ) on MPs deposition. It was concluded that CFD-DEM model is highly sensitive to the values of the sliding and rolling friction coefficients, and the number of particles considered for running simulations. Furthermore, the demonstrated sensitivity of the model to specific parameters offers a foundation for optimizing future modeling efforts and enhancing predictive capabilities in environmental and hydraulic engineering applications.
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