CFD prediction of convective heat transfer and pressure drop of pigs in group using virtual wind tunnels: Influence of grid resolution and turbulence modelling

Abstract

Ventilation for the animal house is important since it is highly linked with the convective heat removal from animals. In this context, the animals as obstacles affect the ventilation airflow and consequently the air distribution within Animal Occupied Zone (AOZ). To study the convective heat transfer (CHT) of animals and the pressure drop (PD) resulting from the animals, computational fluid dynamics (CFD) can be an efficient tool, particularly in comparison with experimental methods. However, simulation accuracy is influenced by grid treatment and the choice of turbulence models. To reveal the grid effects on CHT and PD, fifteen 3D meshes with different facial grids sizes (0.04 m, 0.02 m, and 0.008 m) and prismatic layer thicknesses (PLT) (0 m, 0.0015 m, 0.009 m, 0.02 m, 0.04 m) were tested based on staggered tube bundle models representing simplified bluff bodies using virtual wind tunnels. Then, four commonly used turbulence models, namely, standard k–ɛ, realisable k–ɛ, standard k–ω, and SST k–ω, together with two wall treatments were evaluated and compared with the empirical calculation. The evaluation of turbulence models and wall treatment was then carried out based on grouped pig models using virtual wind tunnels. The results showed that the PLT could be an important influence on the stability of the simulation with varied facial grid sizes. The k–ω models performed better than the k–ɛ models on the predictions of both the CHT and the PD based on the tube bundle model. Wall function provided acceptable results on CHT, however, significant flaws on the PD on both tube bundles and pig models.