A semi-stochastic approach for point-particle dispersion in Wall-Modeled Large Eddy Simulation of particle-laden turbulent flows

This study investigates the integration of a semi-stochastic model, based on the Langevin equations with drift-correction, into the Wall-Modeled Large-Eddy Simulation (WM-LES) framework for simulating particle-laden turbulent channel flows in one-way coupling conditions. Various velocity statistics are presented for both the carrier and dispersed phases. The results confirm that the proposed approach accurately reproduces particle dynamics across a range of Reynolds and Stokes numbers when compared with reference data from Direct Numerical Simulations. The model effectively captures key aspects of particle behavior, including velocity fluctuations, accurate near-wall particle velocities and the expected logarithmic profile of the axial velocity in the logarithmic region. Additionally, it successfully replicates the trends in particle concentration both near the wall and throughout the bulk region of the flow. The findings highlight the potential of the proposed semi-stochastic WM-LES framework to enhance the accuracy and efficiency of particle-laden flow simulations. The proposed approach provides valuable insights into turbulent particulate transport modeling and may benefit applications in engineering and environmental sciences, such as sediment transport, pollutant dispersion, and industrial mixing. • This work presents a novel semi-stochastic modeling approach integrated into the Wall-Modeled Large-Eddy Simulation (WM-LES) framework to simulate particle-laden turbulent flows with improved accuracy and reduced computational cost. • The proposed method accurately captures essential particle dynamics, such as velocity fluctuations and near-wall behavior, reproducing expected flow features like the logarithmic velocity profile and turbophoretic accumulation. • The model demonstrates strong predictive capabilities across a range of Reynolds and Stokes numbers, offering consistent results in both near-wall and bulk regions of the flow. • This framework provides a promising tool for the simulation of complex multiphase flows and is applicable to various engineering and environmental scenarios, including pollutant dispersion, sediment transport, and industrial particulate processes.