Influence of the initial droplet distribution on the prediction of spray dynamics in Eulerian-Lagrangian simulations

Gerbino, Filippo; Tretola, Giovanni; Morgan, Rod; Atkins, Penny; Vogiatzaki, Konstantina

doi:10.1016/j.ijmultiphaseflow.2021.103642

Cited by 10 publications

(4 citation statements)

References 24 publications

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“…As an example, Gerbino et al [15] performed E-L simulations to predict the dynamics of a spray due to the initial distribution of droplets, providing a reasonable prediction (Fig. 1).…”

Section: Eulerian-lagrangian Approachmentioning

confidence: 92%

An Overview of Multi-Phase Flow Numerical Methods

2023

International Conference on Innovative Academic Studies

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Numerical simulation of multi-phase flows is complicated and time-intensive. Many investigators have utilized different numerical approaches to describe multi-phase flows in various practical problems, including sprays, cyclones, stratification, etc. This review paper introduces four numerical schemes, including Eulerian-Lagrangian (E-L), Eulerian-Eulerian (E-E), Volume of Fluid (VOF), and front tracking (FT), employed to simulate multi-phase flows. Some advances in the field are introduced and some main characteristics are compared. It is demonstrated that the selection of an appropriate approach depends on the major hydrodynamic properties of the problem.

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“…As an example, Gerbino et al [15] performed E-L simulations to predict the dynamics of a spray due to the initial distribution of droplets, providing a reasonable prediction (Fig. 1).…”

Section: Eulerian-lagrangian Approachmentioning

confidence: 92%

An Overview of Multi-Phase Flow Numerical Methods

2023

International Conference on Innovative Academic Studies

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“…The droplet velocity distribution is globally symmetrical up to D = 18 μm in Fig. 2a, while the larger droplets have increasingly higher velocities due to overshooting (Gerbino et al, 2021;Wu et al, 2022). It means that large droplets accelerate slowly in the high-velocity gas stream, while their momentum decays slower than that of the gas jet.…”

Section: Determining the Critical Droplet Diametermentioning

confidence: 92%

“…An empirical estimation for the time scale can be derived from the turbulent kinetic energy and the dissipation rate (Sommerfeld and Kussin, 2003), needing Particle Image Velocimetry, PIV, measurements (Li et al, 2021;Xu and Chen, 2013). There is an example for using the cell size as a characteristic length (Gerbino et al, 2021); however, it makes Stk a mesh-dependent quantity.…”

Section: Introductionmentioning

confidence: 99%

Gas-phase velocity estimation in practical sprays by Phase-Doppler technique

Rácz

Malý

Jedelský

et al. 2022

International Journal of Multiphase Flow

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“…The latest and recommended experimental data have been updated on the ECN website (ECN, 2022b). The numerical approaches available in the literature, which validated with the old data on spray penetrations (Manin et al, 2015), are using tuning parameters (Saha et al, 2017;Paredi et al, 2018;di Ilio et al, 2019;Gerbino et al, 2021), which may not be physically correct. To elaborate on this aspect, the following Table 1 shows the comparison of the published literature on Spray G to emphasize the relevance of the current work.…”

Section: Introductionmentioning

confidence: 99%

On Modeling of Spray G ECN Using ROI-Based Eulerian-Lagrangian Simulation

Ailaboina

Saha

2022

Front. Mech. Eng.

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A numerical study has been carried out to understand the effects of Unsteady Reynolds Averaged Navier-Stokes (standard k ― ε and RNG k ― ε model) and large eddy simulations (LES) on a multi-hole gasoline direct injection (GDI) system. The fuel injector considered in this study is the Spray G nozzle from the Engine Combustion Network (ECN). A blob injection model, based on empirical rate of injection (ROI) profile, is considered in this study. The latest data on spray penetrations from Engine Combustion Network is used for model validation along with experimental findings on suction velocity and local droplet diameter. The spray breakup is simulated by using the KH-RT breakup length model. The turbulence model constant Cε1, is tuned to match with the experimental data of liquid and vapor penetrations in simulations while using the standard k-ε turbulence model. On the other hand, the Kelvin-Helmholtz breakup model time constant (B1) and Rayleigh Taylor breakup length constant (Cbl) are tuned for the RNG k ― ε turbulence model. From this work it is observed that by increasing the breakup length model constants (Cbl), the radial dispersion of the spray increases, and the extent of breakup is lowered. The set of optimized model parameters used with RNG k - ε is also used for LES modeling studies with different sub-grid models. The spray penetrations with standard k ― ε turbulence (Cε1=1.44) model are reported underpredicting, and the RNG k ― ε and LES sub-grid models predicted well with the latest and recommended data from ECN. In terms of gas axial velocity comparison, the standard k-ε(Cε1=1.44) simulation setup does not perform as well as the simulation setups using RNG k-ε and LES turbulence models (with breakup parameters: Cbl = 16 and B1 = 32). However, the standard k-ε(Cε1=1.44) simulation setup perform better than the simulation setups using RNG k-ε and LES turbulence models (with breakup parameters: Cbl = 16 and B1 = 32) when it comes to predicting local droplet diameter at 15 mm downstream of the injector tip. A parametric study is also performed considering the geometry of the stepped holes in the computational domain. The rate of injection based simulation is initiated at the end of the smaller hole. The case including the stepped holes led to over-prediction compared to the case with the usual computational domain (i.e., without the stepped holes), in terms of spray penetrations, but exhibited higher levels of fluctuations in the spray morphology. Finally, parametric studies were carried out to understand the relative importance of the individual spray sub-models (breakup, evaporation and collision) and the results are conclusive that for a spray simulation the breakup models are the dominant factors.

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Influence of the initial droplet distribution on the prediction of spray dynamics in Eulerian-Lagrangian simulations

Cited by 10 publications

References 24 publications

An Overview of Multi-Phase Flow Numerical Methods

An Overview of Multi-Phase Flow Numerical Methods

Gas-phase velocity estimation in practical sprays by Phase-Doppler technique

On Modeling of Spray G ECN Using ROI-Based Eulerian-Lagrangian Simulation

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