Large-Eddy Simulation on the Effect of Droplet Size Distribution on Mixing of Passive Scalar in a Spray

A two-staged swirling burner is numerically simulated using Large Eddy Simulation (LES). This combustor uses two types of injection: a multipoint system that consists in 10 holes in a crossflow configuration, and a pilot system that uses a pressure-swirl atomizer. The relation between the rate of fuel injected from each injection system was found to be related with flame shape transition and hysteresis phenomena[4]. Also, the pilot spray was found to have a major role on these transitons, so it is of paramount importance to correctly reproduce its behavior on the numerical modeling, if one is interested in simulating these flame bifurcations. To describe the spray, a point-droplet approximation is used in a Lagrangian framework with the FIM-UR model [1], that has already proven its accuracy for several configurations. However, in this application it fails to reproduce the droplet size distribution, especially in the Central Recirculation Zone (CRZ), as it uses an arbitrary expression to impose the spray opening limits (which are not input parameters). In the present work, the input parameters of the FIM-UR model are modified to enable the recovery of the right droplet size distribution and improve the description of the liquid velocity field, resulting in a better numerical representation of the experimental results, essential for further studies.

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A population balance model for large eddy simulation of polydisperse droplet evolution

Journal of Fluid Mechanics ◽

10.1017/jfm.2019.649 ◽

2019 ◽

Vol 878 ◽

pp. 700-739 ◽

Cited By ~ 10

Author(s):

A. K. Aiyer ◽

D. Yang ◽

M. Chamecki ◽

C. Meneveau

Keyword(s):

Large Eddy Simulation ◽

Size Distribution ◽

Droplet Size ◽

Droplet Breakup ◽

Dispersed Phase ◽

Size Distributions ◽

Oil Droplets ◽

One Dimensional ◽

Eddy Simulation ◽

Large Eddy

In the context of many applications of turbulent multi-phase flows, knowledge of the dispersed phase size distribution and its evolution is critical to predicting important macroscopic features. We develop a large eddy simulation (LES) model that can predict the turbulent transport and evolution of size distributions, for a specific subset of applications in which the dispersed phase can be assumed to consist of spherical droplets, and occurring at low volume fraction. We use a population dynamics model for polydisperse droplet distributions specifically adapted to a LES framework including a model for droplet breakup due to turbulence, neglecting coalescence consistent with the assumed small dispersed phase volume fractions. We model the number density fields using an Eulerian approach for each bin of the discretized droplet size distribution. Following earlier methods used in the Reynolds-averaged Navier–Stokes framework, the droplet breakup due to turbulent fluctuations is modelled by treating droplet–eddy collisions as in kinetic theory of gases. Existing models assume the scale of droplet–eddy collision to be in the inertial range of turbulence. In order to also model smaller droplets comparable to or smaller than the Kolmogorov scale we extend the breakup kernels using a structure function model that smoothly transitions from the inertial to the viscous range. The model includes a dimensionless coefficient that is fitted by comparing predictions in a one-dimensional version of the model with a laboratory experiment of oil droplet breakup below breaking waves. After initial comparisons of the one-dimensional model to measurements of oil droplets in an axisymmetric jet, it is then applied in a three-dimensional LES of a jet in cross-flow with large oil droplets of a single size being released at the source of the jet. We model the concentration fields using $N_{d}=15$ bins of discrete droplet sizes and solve scalar transport equations for each bin. The resulting droplet size distributions are compared with published experimental data, and good agreement for the relative size distribution is obtained. The LES results also enable us to quantify size distribution variability. We find that the probability distribution functions of key quantities such as the total surface area and the Sauter mean diameter of oil droplets are highly variable, some displaying strong non-Gaussian intermittent behaviour.

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Large eddy simulation of evolution of a passive scalar in plane jet

AIAA Journal ◽

10.2514/3.14895 ◽

2001 ◽

Vol 39 ◽

pp. 1509-1516 ◽

Cited By ~ 2

Author(s):

C. Le Ribault ◽

S. Sarkar ◽

S. A. Stanley

Keyword(s):

Large Eddy Simulation ◽

Passive Scalar ◽

Eddy Simulation ◽

Large Eddy ◽

Plane Jet

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Demistify: a large-eddy simulation (LES) and single-column model (SCM) intercomparison of radiation fog

Atmospheric Chemistry and Physics ◽

10.5194/acp-22-319-2022 ◽

2022 ◽

Vol 22 (1) ◽

pp. 319-333

Author(s):

Ian Boutle ◽

Wayne Angevine ◽

Jian-Wen Bao ◽

Thierry Bergot ◽

Ritthik Bhattacharya ◽

...

Keyword(s):

Large Eddy Simulation ◽

Weather Prediction ◽

Cloud Droplet ◽

Droplet Size Distribution ◽

Radiation Fog ◽

Eddy Simulation ◽

Cloud Droplet Size Distribution ◽

Large Eddy ◽

Single Column ◽

Les Model

Abstract. An intercomparison between 10 single-column (SCM) and 5 large-eddy simulation (LES) models is presented for a radiation fog case study inspired by the Local and Non-local Fog Experiment (LANFEX) field campaign. Seven of the SCMs represent single-column equivalents of operational numerical weather prediction (NWP) models, whilst three are research-grade SCMs designed for fog simulation, and the LESs are designed to reproduce in the best manner currently possible the underlying physical processes governing fog formation. The LES model results are of variable quality and do not provide a consistent baseline against which to compare the NWP models, particularly under high aerosol or cloud droplet number concentration (CDNC) conditions. The main SCM bias appears to be toward the overdevelopment of fog, i.e. fog which is too thick, although the inter-model variability is large. In reality there is a subtle balance between water lost to the surface and water condensed into fog, and the ability of a model to accurately simulate this process strongly determines the quality of its forecast. Some NWP SCMs do not represent fundamental components of this process (e.g. cloud droplet sedimentation) and therefore are naturally hampered in their ability to deliver accurate simulations. Finally, we show that modelled fog development is as sensitive to the shape of the cloud droplet size distribution, a rarely studied or modified part of the microphysical parameterisation, as it is to the underlying aerosol or CDNC.

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