Modelagem e simulação da estratificação térmica na camada limite atmosférica

Abstract

Simulations of wind flow in the atmospheric boundary layer currently carried out, despite being well developed, often disregard effects such as the different thermal stratification conditions, in order to simplify the models. Thermal stratification, however, has a significant impact on the results obtained by the simulation, especially in places where there is great daily or annual temperature variation. Thus, this research sought to develop a CFD model to better represent the flow in the atmospheric boundary layer simulated in a wind tunnel under thermal stratification conditions. To this end, the commercial software ANSYS Fluent was used, applying the large eddy simulation methodology (LES - Large Eddy Simulation), with the dynamic Smagorinsky sub-grid model, as well as the classical modeling of turbulence (RANS - Reynolds Averaged Navier-Stokes). The Boussinesq approximation was used to represent natural convection and the effects of atmospheric stratification in the vertical profiles of flow velocity and temperature were introduced through the Monin-Obukhov Similarity Theory. The developed model was applied in the simulation of flow over a steep hill, and the results obtained were compared to data from wind tunnel experiments found by Ross et al. (2004), in addition to being applied to the flow over the reduced model of a wind turbine, for a qualitative analysis of the impacts of atmospheric stratification on flow velocity and turbulence. In general, the model behaved well, and was able to satisfactorily represent the general effects induced by thermal stratification, being possible to identify variations in the velocity profile for the different cases of stratification, in addition to the impacts of the temperature gradient on the turbulent intensity of the flow. The results obtained indicate that atmospheric stability is an important factor for the flow in the atmospheric boundary layer, and should be taken into account for a better planning of wind farms.