Andrea Amicarelli

Sensitivity analysis of a concentration fluctuation model to dissipation rate estimates

Lagrangian dispersion models require estimates of the local dissipation rate ( e ) of turbulent kinetic energy ( k ). In this study, we evaluate the sensitivity of a Lagrangian model to different estimates of e in simulating passive scalar dispersion in a turbulent boundary layer over a rough surface. Two different estimates of e are used to simulate pollutant dispersion emitted by a linear elevated source with a Lagrangian model which integrates a macromixing and a micromixing scheme. Comparison between numerical and experimental results allows us to discuss the performance of the model and to define its sensitivity to e .

A comparison between IECM and IEM Lagrangian models

A three-dimensional Lagrangian stochastic model to evaluate pollutant dispersion in terms of both mean and fluctuating concentration fields has been developed. The mean concentration field is predicted by using a macromixing model, while the micromixing scheme IECM (Interaction by Exchange with the Conditional Mean) is adopted to determine the moments of concentration. The results agree with experimental data and with other numerical studies found in literature. The performance of a second micromixing scheme, namely, the IEM (Interaction by Exchange with the Mean), is tested. Some inaccuracies of the IEM model are evaluated by comparison against measurements and IECM results.

LAGFLUM, a stationary 3D Lagrangian stochastic numerical micromixing model for concentration fluctuations: validation in canopy turbulence, on the MUST wind tunnel experiment

A stationary three-dimensional Lagrangian stochastic numerical model, LAGrangian FLUctuation Model (LAGFLUM), was developed by coupling a macromixing with a micromixing scheme, to determine the mean and the variance of concentration for a passive scalar in 3D turbulent flows. The model was tested by comparison with the (MUST) Mock Urban Setting Test wind tunnel experiment, where the dispersion of a passive tracer in a 3D stationary flow field, in the presence of obstacles, was analysed. The means and the standard deviations of concentration reproduced by LAGFLUM were compared with the available measurements. The results show a good performance of the model.

A stochastic Lagrangian micromixing model for the dispersion of reactive scalars in turbulent flows: role of concentration fluctuations and improvements to the conserved scalar theory under non-homogeneous conditions

Several reaction schemes, based on the conserved scalar theory, are implemented within a stochastic Lagrangian micromixing model to simulate the dispersion of reactive scalars in turbulent flows. In particular, the formulation of the reaction-dominated limit (RDL) reaction scheme is here extended to improve the model performance under non-homogeneous conditions (NHRDL scheme). The validation of the stochastic model is obtained by comparison with the available measurements of reactive pollutant concentrations in a grid-generated turbulent flow. This test case describes the dispersion of two atmospheric reactant species (NO and O3) and their reaction product (NO2) in an unbounded turbulent flow. Model inter-comparisons are also assessed, by considering the results of state-of-the-art models for pollutant dispersion. The present validation shows that RDL reaction scheme provides a systematic overestimation (relative error of ca. 85% around the centreline) in computing the local reactant consumption/production rate, whereas the NHRDL scheme drastically reduces this gap (relative error lower than 5% around the centreline). In terms of NO2 production (or reactant consumption), neglecting concentration fluctuations determines overestimations of the product mean of around 100% and a NO2 local production of one order of magnitude higher than the reference simulation. In terms of standard deviations, the concentration fluctuations of both the passive and reactive scalars are generally of the same order of magnitude or up to 1 or 2 orders of magnitudes higher than the corresponding ensemble mean values, except for the background reactant close to the plume edges. The study highlights the importance of modelling pollutant reactions depending on the instantaneous instead of the mean concentrations of the reactants, thus quantifying the role of the turbulent fluctuations of concentration, in terms of scalar statistics (mean, standard deviation, intensity of fluctuations, skewness and kurtosis of concentration, segregation coefficient, simulated reaction rate). This stochastic particle method represents an efficient numerical technique to solve the convection–diffusion equation for reactive scalars and involves several application fields: micro-scale air quality (urban and street-canyon scales), accidental releases, impact of odours, water quality and fluid flow industrial processes (e.g. combustion).

Lagrangian micromixing modelling of reactive scalar statistics: scalar mixing layer in decaying grid turbulence

A Lagrangian micro-mixing numerical model estimates the concentration statistics of reactive pollutants (NO, O3 and NO2) of a scalar mixing layer in decaying grid turbulence. A stochastic macro-mixing scheme computes the fluid particle trajectories, which describe the turbulent flow (Lagrangian turbulence), whereas the micro-mixing scheme interaction by the exchange with the conditional mean (IECM), implementing a new formulation for the mixing time, represents the dissipation of concentration turbulent fluctuations due to molecular diffusion. The non-homogeneous reaction-dominated limit (NHRDL) of the conserved scalar theory simulates chemical reactions. The numerical model integrates these three schemes and is validated by comparison with experimental and direct numerical simulation (DNS) data, whereas inter-comparisons with other numerical models are also reported. The study focuses on the reliability of Lagrangian stochastic models in representing micro-scale pollutant dispersion (air quality) and the importance of representing chemical reactions depending on instantaneous concentrations rather than their means.

Next-generation Multi-mechanics Simulation Engine in a Highly Interactive Environment

We describe the development of a highly interactive approach to simulation of engineering multi-mechanics problems, using the smoothed particle hydrodynamics mesh-free method as the computational engine, for applications including ship survival, medical devices and Pelton turbines.

An urban scale model for pollutant dispersion in Rome

A Gaussian model software (Atmospheric Dispersion Model System?ADMS-Urban) is used to forecast the carbon monoxide concentrations in the Urban Boundary Layer (UBL) of the city of Rome, Italy. The simulations refer to 14 days during 2002. Two data set inputs were considered in order to evaluate the urban background concentration and the effects of the main roads surrounding the monitoring stations. Results show that the background concentration plays a fundamental role in the whole balance of the pollution and that sometimes it overcomes the level associated to the local emissions. Finally, the background concentration appears to be strongly non-homogeneous within the urban area.

Analytical Solutions of the Balance Equation for the Scalar Variance in One-Dimensional Turbulent Flows under Stationary Conditions

This study presents 1D analytical solutions for the ensemble variance of reactive scalars in one-dimensional turbulent flows, in case of stationary conditions, homogeneous mean scalar gradient and turbulence, Dirichlet boundary conditions, and first order kinetics reactions. Simplified solutions and sensitivity analysis are also discussed. These solutions represent both analytical tools for preliminary estimations of the concentration variance and upwind spatial reconstruction schemes for CFD (Computational Fluid Dynamics)—RANS (Reynolds-Averaged Navier-Stokes) codes, which estimate the turbulent fluctuations of reactive scalars.