We investigate the reliability of a meandering plume model in reproducing the passive scalar concentration statistics due to a continuous release in a turbulent boundary layer. More specifically, we aim to verify the physical consistency of the parametrizations adopted in the model through a systematic comparison with experimental data. In order to perform this verification, we take advantage of the velocity and concentration measurements presented in part I of the present study (Nironi et al., Boundary-Layer Meteorol, 2015) particularly concerning estimates of the Eulerian integral length scales and the higher order moments of the concentration probability density function. The study is completed by a sensitivity analysis in order to estimate the effects of the variations of the key parameter to the model results. In the light of these results, we discuss the benefits and shortcomings of this modelling approach and its suitability for operational purposes.

Dispersion of a Passive Scalar Fluctuating Plume in a Turbulent Boundary Layer. Part II: Analytical Modelling / Marro, M.; Nironi, C.; Salizzoni, P.; Soulhac, L.. - In: BOUNDARY-LAYER METEOROLOGY. - ISSN 0006-8314. - 156:3(2015), pp. 447-469. [10.1007/s10546-015-0041-9]

Dispersion of a Passive Scalar Fluctuating Plume in a Turbulent Boundary Layer. Part II: Analytical Modelling

Marro M.;Salizzoni P.;
2015

Abstract

We investigate the reliability of a meandering plume model in reproducing the passive scalar concentration statistics due to a continuous release in a turbulent boundary layer. More specifically, we aim to verify the physical consistency of the parametrizations adopted in the model through a systematic comparison with experimental data. In order to perform this verification, we take advantage of the velocity and concentration measurements presented in part I of the present study (Nironi et al., Boundary-Layer Meteorol, 2015) particularly concerning estimates of the Eulerian integral length scales and the higher order moments of the concentration probability density function. The study is completed by a sensitivity analysis in order to estimate the effects of the variations of the key parameter to the model results. In the light of these results, we discuss the benefits and shortcomings of this modelling approach and its suitability for operational purposes.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11583/3011119