Towards a Lagrangian CFD Model for Aerosol Resuspension in Turbulent Flow

Aerosol resuspension is a key vector for introducing particles into the atmosphere and is driven by a wide range of natural and other external forces capable of detaching particles from surfaces. Its impact spans diverse fields - including industry, ventilation, healthcare, farming, transportation, and nuclear safety - yet it remains underrepresented in aerosol transport and dispersion modelling due to a lack of understanding of the complexity of its underlying physics. Several mechanistic, probabilistic, and semi-empirical models have already been developed, but are constrained by simplistic assumptions, sometimes resulting in significant discrepancies between predicted and observed data, thus limiting their predictive accuracy and applicability.<br/>This research aims to further understand the dynamics of aerosol resuspension by developing a high-resolution CFD-based model that captures the fundamental physics more comprehensively than current approaches. Specifically, we investigate how aerodynamic forces, variability in particle-surface adhesion and morphology affect rolling or sliding thresholds and influence resuspension rates under realistic atmospheric conditions. The model is implemented in Siemens Simcenter StarCCM+ v2302, employing a three-dimensional Lagrangian approach with six-degree-of-freedom (6 DoF) particle displacement within turbulent flow (Stokes regime, Re ≈ 1). Particular emphasis is placed on near-surface interactions, integrating Dynamic Fluid-Body Interaction (DFBI), boundary layer theory and turbulent eddy behaviour, detailed contact mechanics, and adhesive/repulsive force distributions to maximise the completeness of the model. The framework is designed to be flexible, accommodating a broad range of particle sizes, shapes, surface topologies, and flow boundary conditions, thereby enabling the simulation of complex, real-world scenarios. Currently, the model features operational boundary layer and contact mechanics modules, supporting variable particle morphologies being re-entrained on flat surfaces. Significant challenges were encountered while accurately modelling particle-surface contact with suitable mesh and temporal resolutions, quantifying the forces influencing detachment, and limiting the evolving computational costs associated with high-fidelity simulations.<br/>Once completed, the model will be validated against experimental trajectory and detachment rates data and benchmarked against established Eulerian resuspension models. Ultimately, improving the capabilities for the prediction of aerosol resuspension addresses a critical health and safety concern as it helps anticipate hazards and supports better risk mitigation strategies for harmful aerosols in the environment.