4.4 Article

Evaluation of the Revised Lagrangian Particle Model GRAL Against Wind-Tunnel and Field Observations in the Presence of Obstacles

Journal

BOUNDARY-LAYER METEOROLOGY
Volume 155, Issue 2, Pages 271-287

Publisher

SPRINGER
DOI: 10.1007/s10546-014-9993-4

Keywords

Building downwash; Graz Lagrangian model; Lagrangian particle model; Reynolds-averaged Navier-Stokes equations; Wind-tunnel data

Ask authors/readers for more resources

A revised microscale flow field model has been implemented in the Lagrangian particle model Graz Lagrangian Model (GRAL) for computing flows around obstacles. It is based on the Reynolds-averaged Navier-Stokes equations in three dimensions and the widely used standard turbulence model. Here we focus on evaluating the model regarding computed concentrations by use of a comprehensive wind-tunnel experiment with numerous combinations of building geometries, stack positions, and locations. In addition, two field experiments carried out in Denmark and in the U.S were used to evaluate the model. Further, two different formulations of the standard deviation of wind component fluctuations have also been investigated, but no clear picture could be drawn in this respect. Overall the model is able to capture several of the main features of pollutant dispersion around obstacles, but at least one future model improvement was identified for stack releases within the recirculation zone of buildings. Regulatory applications are the bread-and-butter of most GRAL users nowadays, requiring fast and robust modelling algorithms. Thus, a few simplifications have been introduced to decrease the computational time required. Although predicted concentrations for the two field experiments were found to be in good agreement with observations, shortcomings were identified regarding the extent of computed recirculation zones for the idealized wind-tunnel building geometries, with approaching flows perpendicular to building faces.

Authors

I am an author on this paper
Click your name to claim this paper and add it to your profile.

Reviews

Primary Rating

4.4
Not enough ratings

Secondary Ratings

Novelty
-
Significance
-
Scientific rigor
-
Rate this paper

Recommended

No Data Available
No Data Available