Estudo da difusão turbulenta empregando modelos estocásticos Lagrangeanos

Abstract

In this work, the Lagrangian stochastic particle model LAMBDA is utilized to simulate the dispersion and the transport of contaminants under different atmospheric conditions. The analysis employs three different field experiments of atmospheric diffusion: the Copenhagen experiment, which was accomplished in unstable conditions, the Prairie Grass experiment in which was considered only neutral stability cases (mean wind velocity higher than 6ms-1) and the INEL experiment occurring in low wind stable conditions and presenting wind meandering phenomenon. LAMBDA is a tridimensional model to simulate the pollutants dispersion over flat terrain. The model solves the generalized form the Langevin Equation and it can use the higher moments of Eulerian probability density function of the wind velocity fluctuations. The main aim of this work is to test a new parameterization for the parameters p and q which represent the frequency associated to the meandering phenomenon. The new parameterization is expressed in terms of m , a non-dimensional quantity that controls the meandering oscillation frequency, and T , a time scale associated to the coherent structures in a fully developed turbulence. The simulations show that the LAMBDA model incorporating this new parameterization reproduces correctly the enhanced diffusion of passive scalars in a low wind speed stable atmospheric boundary layer.