The phenomenon of aerosol transport in turbulent flows has been studied extensively over the past few decades. Traditional methods for simulation and modeling of aerosol deposition in turbulent boundary layers rely on the solution of the Reynolds averaged Navier-Stokes (RNS) equations. The difficulty with these methods is that they rely on the Gradient Transport hypothesis, which does not accurately model aerosol transport, especially near a wall. A more sophisticated approach for accurately modelling aerosol transport in a turbulent flow is direct numerical simulation (DNS). In DNS, the Navier-Stokes equations are solved without approximations (other than those associated with the numerical method). DNS has been successfully employed in a number of aerosol deposition studies, but its primary drawback is that it remains restricted to relatively low Reynolds number flows.
One of the most useful DNS approaches is Lagrangian simulation. Lagrangian simulations of aerosols in turbulent flows have provided much information regarding aerosol deposition to surfaces and aerosol-turbulence interactions. Because individual aerosol trajectories are calculated in Lagrangian simulations, details of aerosol motion are accessible that are unattainable by experiment, thus making Lagrangian Modelling a highly powerful tool in aerosol transport simulation. However, there are a number of limiting assumptions that have been characteristic of the Lagrangian method, for example, boundary walls are assumed to be smooth and also to be perfect aerosol particle sinks. In addition, aerosol concentrations are assumed to be low enough (practically, this means the particle volume fraction should not exceed 10-12%) to allow aerosol-aerosol interactions to be neglected.
Recent computational developments have allowed a new approach to Lagrangian aerosol tracking to be developed as described below; this approach is robust and flexible and allows many of the aforementioned limitations to be overcome.