Particle transport and clustering in wind turbine wake under sand-laden environment

The potential for wind farms installed in arid and semi-arid regions (like deserts and gobi) has gained increasing attention, making the study of particle transport in wind turbine wake particularly relevant. In this work, we investigate the transport and distribution of sand-grain particles with different Stokes numbers ($St$) in a wind turbine wake by large-eddy simulation for the gas phase and the Eulerian–Lagrangian method for the solid phase. The simulation results reveal a strong correlation between particle transport and particle inertia characterized by $St$. As $St$ increases, the particle transport transits from a tracer-like state dominated by the flow to ballistic motions. A nonmonotonic relationship between local particle clustering and $St$ is discovered using the box-counting method. The local particle clustering is found to be strongest at $St$ = 1, which is independent of cell box size. A threshold for the clustering of particles in the turbine wake is proposed based on flow parameters and Voronoï cell area. Furthermore, we found that gravity enhances clustering for low-inertia particles, while weakening it for high-inertia particles, and it reduces particle clustering in straining regions. This study is expected to provide essential insights for the evaluation and prediction of sand-grain particle transport in wind turbine wake.