Accurate numerical estimation of interphase momentum transfer in Lagrangian–Eulerian simulations of dispersed two-phase flows

Garg, Rahul; Narayanan, Chidambaram; Lakehal, Djamel; Subramaniam, Shankar

doi:10.1016/j.ijmultiphaseflow.2007.06.002

Cited by 89 publications

(85 citation statements)

References 20 publications

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“…• multi-phase flows [119,[166][167][168][169][170][171][172][173][174], • coastal hydrodynamics including water wave impact, dam break, sloshing and overtopping [112,, • environmental and geophysical flows including flood and river dynamics, landslide, flow in fractures and porous media, seepage, soil mechanics and mudflow [117,, • heat and/or mass conduction [53,[222][223][224][225][226][227], • ice and cohesive grains [228][229][230][231][232][233][234], • microfluidics and/or micro drop dynamics [123,152,169,[235][236][237][238][239][240][241][242][243][244][245][246], • high explosive detonation and explosion [55,125,143,[247][248]…”

Section: Applicationsmentioning

confidence: 99%

Smoothed Particle Hydrodynamics (SPH): an Overview and Recent Developments

Liu

2010

Arch Computat Methods Eng

1,478

682

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Smoothed particle hydrodynamics (SPH) is a meshfree particle method based on Lagrangian formulation, and has been widely applied to different areas in engineering and science. This paper presents an overview on the SPH method and its recent developments, including (1) the need for meshfree particle methods, and advantages of SPH, (2) approximation schemes of the conventional SPH method and numerical techniques for deriving SPH formulations for partial differential equations such as the Navier-Stokes (N-S) equations, (3) the role of the smoothing kernel functions and a general approach to construct smoothing kernel functions, (4) kernel and particle consistency for the SPH method, and approaches for restoring particle consistency, (5) several important numerical aspects, and (6) some recent applications of SPH. The paper ends with some concluding remarks.

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Section: Applicationsmentioning

confidence: 99%

Smoothed Particle Hydrodynamics (SPH): an Overview and Recent Developments

Liu

2010

Arch Computat Methods Eng

1,478

682

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“…Sauter mean diameter, droplet volume flux, and droplet axial and radial mean and fluctuating velocities. The numerical convergence and accuracy of Eulerian-Lagrangian simulations of two-phase flows have been discussed in many studies [22,23] A higher number of particles per cell is required for an accurate estimation of the interphase momentum transfer term. In the present computation, the sensitivity of computed droplet mean properties to the initial number of droplet trajectories at the inlet were tested in the range of 5,000 to 20,000, and a total number of 10,000 parcels with constant statistical weight is found to be suitable.…”

Section: Resultsmentioning

confidence: 99%

Transported Joint Probability Density Function Modeling of Turbulent Dilute Spray Flows

Gutheil

2014

Eur Chem Tech J

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A transported joint probability density function (PDF) model for turbulent spray flows is presented, where a one-point one-time statistical description of the gas-phase mixture fraction and the gas velocity is used. This approach requires the closure of the molecular mixing, which is achieved through use of the extended interaction-by-exchange-with-the-mean (IEM) model and a simplified Langevin model for the closure of the gas velocity both of which are extended through additional terms accounting for spray evaporation. These equations require the solution of the turbulent time scales and the mean pressure field through a Eulerian description. The numerical approach includes a Lagrangian Monte Carlo method for the solution of modeled joint PDF equation with a Eulerian finite-volume algorithm to determine the turbulent time scale and the mean pressure field. For the dispersed liquid phase, Lagrangian equations are used to describe the droplet heating, evaporation, and motion in the framework of a discrete droplet model. The convective droplet evaporation model is employed, and the infinite conductivity model with consideration of non-equilibrium effects based on the Langmuir-Knudsen law is used. The droplet turbulent dispersion is modeled with two different Lagrangian stochastic models. The resulting spray evolution equations are solved by a Lagrangian discrete droplet method using the point source approximation for a dilute spray. The numerical results are compared with experimental data of Gounder et al. [1], where the experimental set B of the acetone spray flows SP2 and SP6 are simulated. Comparison of numerical and experimental results includes droplet size, liquid volume flux as well as the mean and fluctuating velocities. Generally, good agreement is achieved, although the radial droplet dispersion is somewhat under-predicted by the computations. The droplet fluctuating velocities show sensitivity to the different dispersion models.

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“…The normalization parameter A is given by A −1 = +k 2 σ −k 2 σ exp(−x 2 /σ 2 ) dx. We have chosen k 1 = σ / * = 0.5 and k 2 = 3 by comparing with other projection schemes (Garg et al 2007). Moreover it was checked that, as long as * > Δ > d p , the results are independent of the spatial resolution.…”

Section: Computational Approachmentioning

confidence: 99%

Turbulent thermal convection driven by heated inertial particles

et al. 2016

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This is an author-deposited version published in: http://oatao.univ-toulouse.fr/ Eprints ID: 18470Open Archive Toulouse Archive Ouverte (OATAO) OATAO is an open access repository that collects the work of Toulouse researchers and makes it freely available over the web where possible. The heating of particles in a dilute suspension, for instance by radiation, chemical reactions or radioactivity, leads to local temperature fluctuations in the fluid due to the non-uniformity of the disperse phase. In the presence of a gravity field, the fluid is set in motion by the resulting buoyancy forces. When the particle density is different than that of the fluid, the fluid motion alters the spatial distribution of the particles and possibly strengthens their concentration inhomogeneities. This in turn causes more intense local heating. Direct numerical simulations in the Boussinesq limit show this feedback loop. Various regimes are identified depending on the particle inertia. For very small particle inertia, the macroscopic behaviour of the system is the result of many thermal plumes that are generated independently of each other. For significant particle inertia, clusters of particles are observed and their dynamics controls the flow. The emergence of very intermittent turbulent fluctuations shows that the flow is influenced by the larger structures (turbulent convection) as well as by the small-scale dynamics that affect particle segregation and thus the flow forcing. Assuming thermal equilibrium between the particles and the fluid (i.e. infinitely fast thermal relaxation of the particle), we investigate the evolution of statistical observables with the change of the main control parameters (namely the particle number density, the particle inertia and the domain size), and propose a scaling argument for these trends. Concerning the energy density in the spectral space, it is observed that the turbulent energy and temperature spectra follow a power law, the exponent of which varies continuously with the Stokes number. Furthermore, the study of the spectra of the temperature and momentum forcing (and thus of the concentration/temperature and velocity/temperature correlations) gives strong support to the proposed feedback loop mechanism. We then discuss the intermittency of the flow, and analyse the effect of relaxing some of the simplifying assumptions, thus assessing the relevance of the original studied configuration. To cite this version:

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Accurate numerical estimation of interphase momentum transfer in Lagrangian–Eulerian simulations of dispersed two-phase flows

Cited by 89 publications

References 20 publications

Smoothed Particle Hydrodynamics (SPH): an Overview and Recent Developments

Smoothed Particle Hydrodynamics (SPH): an Overview and Recent Developments

Transported Joint Probability Density Function Modeling of Turbulent Dilute Spray Flows

Turbulent thermal convection driven by heated inertial particles

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