PM10 Dispersion Modeling by Means of CFD 3D and Eulerian–Lagrangian Models: Analysis and Comparison with Experiments. (November 2016)

• Record Type: Journal Article
• Authors: Brusca, S.; Famoso, F.; Lanzafame, R.; Mauro, S.; Messina, M.; Strano, S.
• Is Part Of: Energy procedia. Volume 101(2016)
• Page Start: 329
• Page End: 336
• Publication Date: 2016-11
• Subjects: 3D CFD model -- Eulerian/Lagrangian particle dispersion model -- air pollution -- aerosol particles; Power resources -- Congresses; Power resources -- Periodicals; Power resources; Conference proceedings; Periodicals; 333.7905
• DOI: 10.1016/j.egypro.2016.11.042
• Languages: English
• ISSNs: 1876-6102

Abstract

Abstract: This research deals with the analysis of the dispersion of PM10 by using fluid-dynamic simulation framework. Firstly, an experimental campaign was made in a wind tunnel. A cylindrical emitter of PM10 was characterized in terms of PM10 mass flow rate and outlet velocity. It was positioned in the wind tunnel chamber where several sensors were also placed downwind. The use of different sensor configurations allowed the evaluation of the PM10 concentrations in several locations. The experimental campaign was reproduced in ANSYS-Fluent, by recreating in Design-Model, a 3D geometries of the test case. Different calculation grids were tested in order to find the proper balance between computing time and accuracy. The CFD 3D model was based on the Eulerian approach for the continuous phase and Lagrangian approach for the dispersion phase setting the DPM for the evaluation and dispersion of particulate matters. The turbulence was solved by using a k-ɛ RANS approach and a quite advanced unsteady DES model. Several simulations were carried out by varying the flow inlet velocities in configurations with and without obstacles. The results obtained from the post-processing phase were then compared with the experimental campaign. With obstacles a PM concentration increment is observed at all imposed air velocity because of recirculation phenomena generated around the obstacles.