Joint PDF modelling of turbulent flow and dispersion in an urban street canyon

The joint probability density function (PDF) of turbulent velocity and concentration of a passive scalar in an urban street canyon is computed using a newly developed particle-in-cell Monte Carlo method. Compared to moment closures, the PDF methodology provides the full one-point one-time PDF of the underlying fields containing all higher moments and correlations. The small-scale mixing of the scalar released from a concentrated source at the street level is modelled by the interaction by exchange with the conditional mean (IECM) model, with a micro-mixing time scale designed for geometrically complex settings. The boundary layer along no-slip walls (building sides and tops) is fully resolved using an elliptic relaxation technique, which captures the high anisotropy and inhomogeneity of the Reynolds stress tensor in these regions. A less computationally intensive technique based on wall functions to represent boundary layers and its effect on the solution are also explored. The calculated statistics are compared to experimental data and large-eddy simulation. The present work can be considered as the first example of computation of the full joint PDF of velocity and a transported passive scalar in an urban setting. The methodology proves successful in providing high level statistical information on the turbulence and pollutant concentration fields in complex urban scenarios.Comment: Accepted in Boundary-Layer Meteorology, Feb. 19, 200

Convergence to a model in sparse-lagrangian FDF simulations

This work investigates the problem of distinguishing modelling assumptions and numerical errors in sparse-Lagrangian FDF (Filtered Density Function) methods. A new interpretation of sparse modelling with Curl’s mixing, which does not require an additional observation scale nor filtering, is given. The diffusion effects induced by mixing, which were previously interpreted as numerical errors, are now treated as modelling instruments. This ability of controlling numerical errors with the purpose of modelling physical quantities is one of the advantages of Lagrangian particle methods in turbulent reacting flows. The development of stochastic methods which use Lagrangian particles has been ongoing for many years, although the exact interpretation of the nature of such particles varies within the literature. Here we briefly discuss these interpretations and introduce the new term—“Pope particles”— to unify terminology used for the particle simulations of turbulent reacting flows. © Springer Science+Business Media B.V