Numerical simulation of turbulent airflow, tracer gas diffusion, and particle dispersion in a mockup aircraft cabin

Abstract

In order to study the capability of computational methods in investigating the mechanisms associated with disease and contaminants transmission in aircraft cabins, the Computational Fluid Dynamics (CFD) models are used for the simulation of turbulent airflow, tracer gas diffusion, and particle dispersion in a generic aircraft cabin mockup. The CFD models are validated through comparisons of the CFD predictions with the corresponding experimental measurements. It is found that using Large Eddy Simulation (LES) with the Werner-Wengle wall function, one can predict unsteady airflow velocity field with relatively high accuracy. However in the middle region of the cabin mockup, where the recirculation of airflow takes place, the accuracy is not as good as that in other locations. By examining different k-ε models, the current study recommends the use of the RNG k-ε model with the non-equilibrium wall function as a Reynolds Averaged Navier Stokes (RANS) model for predicting the steady-state airflow velocity data. It is also found that changing the cabin air-inlet nozzle height has a significant effect on the flow behavior in the middle and upper part of the cabin, while the flow pattern in the lower part is not affected as much. Through the use of LES and species transport model in simulating tracer gas diffusion, very good agreement between predicted and measured tracer gas concentration data is observed for some monitoring locations, but the agreement level is not uniform for all the sampling point locations. The reasons for the deviations between predictions and measurements for those locations are discussed. The Lagrange-Euler approach is invoked in the particle dispersion simulations. In this approach, the equation of motion for the discrete phase is coupled with the continuous phase governing equations through the calculation of drag and buoyancy forces acting on particles. The continuous phase flow is turbulent and RANS is employed in order to calculate the continuous phase velocity field. A complete study on grid dependence for RANS simulation is performed through a controllable regional mesh refinement scheme. The grid dependence study shows that using unstructured grid with tetrahedral and hybrid elements in the refinement region are more efficient than using structured grid with hexahedral elements. The effect of turbulence on the particle dispersion is taken into account by using a stochastic tracking method (Discrete Random Walk model). One of the significant features of this study is the investigation of the effect of the number of tries on the accuracy of particle concentration predictions when Discrete Random Walk is used to model turbulent distribution of particles. Subsequently, the optimum number of tries to obtain the most accurate predictions is determined. In accordance with the corresponding experimental data, the effect of particle size on particle distribution is also studied and discussed through the simulation of two different sizes of mono-disperse particles in the cabin with straight injection tube, i.e., 3µm and 10µm. Due to the low particle loading, neglecting the effect of particles motion on the continuous phase flow-field seems to be a reasonable, simplifying assumption in running the simulations. However, this assumption is verified through the comparison of the results from 1-way and 2-way coupling simulations. Eventually through the simulations for the particle injection using the cone diffuser, the effects of cabin pressure gradient as well as the particle density on particles dispersion behavior are studied and discussed. In the last part of this dissertation, the turbulent airflow in a full-scale Boeing 767 aircraft cabin mockup with eleven rows of seats and manikins is simulated using steady RANS method. The results of this simulation cannot only be used to study the airflow pattern, but also can be used as the initial condition for running the tracer gas diffusion and particle dispersion simulations in this cabin mockup.