Non-equilibrium Wall Deposition of Inertial Particles in Turbulent Flow

Schmidt, John R.; Wendt, Jost O.L.; Kerstein, Alan R.

doi:10.1007/s10955-009-9844-8

Cited by 14 publications

(16 citation statements)

References 24 publications

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“…Dispersive transport property statistics of particles are obtained by computing a statistically significant ensemble of flow realizations and particle trajectories. Schmidt [28] proposed several particle models that are similar in nature to the ones here, and implemented the Type-I model to study particle behavior in a different context [31,30]. A version of the Type-C model was used by Punati [25] and by Goshayeshi and Sutherland [10,9].…”

Section: Lagrangian Particle Modelmentioning

confidence: 99%

“…The eddy box is advected in the x and z directions using the x and z gas velocity components at the initial particle location for Type-I and Type-C models. Schmidt et al used the eddy-averaged x and z gas velocities for their Type-I simulations [31,29,30]. While there is some appeal in using an eddy-average velocity, there are inconsistencies that arise in certain cases.…”

Section: Instantaneous and Continuous Particle-eddy Interactionmentioning

confidence: 99%

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Evaluation of stochastic particle dispersion modeling in turbulent round jets

Sun

Hewson

Lignell

2017

International Journal of Multiphase Flow

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ODT (one-dimensional turbulence) simulations of particle-carrier gas interactions are performed in the jet flow configuration. Particles with different diameters are injected onto the centerline of a turbulent air jet. The particles are passive and do not impact the fluid phase. Their radial dispersion and axial velocities are obtained as functions of axial position. The time and length scales of the jet are varied through control of the jet exit velocity and nozzle diameter. Dispersion data at long times of flight for the nozzle diameter (7 mm), particle diameters (60 and 90 µm), and Reynolds numbers (10000 to 30000) are analyzed to obtain the Lagrangian particle dispersivity. Flow statistics of the ODT particle model are compared to experimental measurements. It is shown that the particle tracking method is capable of yielding Lagrangian prediction of the dispersive transport of particles in a round jet. In this paper, three particle-eddy interaction models (Type-I,-C, and-IC) are presented to examine the details of particle dispersion and particle-eddy interaction in jet flow.

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Section: Lagrangian Particle Modelmentioning

confidence: 99%

Section: Instantaneous and Continuous Particle-eddy Interactionmentioning

confidence: 99%

Evaluation of stochastic particle dispersion modeling in turbulent round jets

Sun

Hewson

Lignell

2017

International Journal of Multiphase Flow

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“…[15][16][17][18][19] However, very limited work has been performed with ODT in multiphase flow: Schmidt et al studied wall deposition of inertial particles in channel flow using ODT. 20 In order to apply the ODT model to the study of a broader range of multi-phase flows, a validation and characterization of the model behavior is required. The goal of the present work is to evaluate the performance of ODT with particles in relatively simple homogeneous isotropic turbulence and to fully describe the sensitivity of predictions to a parameter that appears in the model.…”

Section: Introductionmentioning

confidence: 99%

Particle dispersion in homogeneous turbulence using the one-dimensional turbulence model

et al. 2014

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Lagrangian particle dispersion is studied using the one-dimensional turbulence (ODT) model in homogeneous decaying turbulence configurations. The ODT model has been widely and successfully applied to a number of reacting and nonreacting flow configurations, but only limited application has been made to multiphase flows. Here, we present a version of the particle implementation and interaction with the stochastic and instantaneous ODT eddy events. The model is characterized by comparison to experimental data of particle dispersion for a range of intrinsic particle time scales and body forces. Particle dispersion, velocity, and integral time scale results are presented. The particle implementation introduces a single model parameter β p , and sensitivity to this parameter and behavior of the model are discussed. Good agreement is found with experimental data and the ODT model is able to capture the particle inertial and trajectory crossing effects. These results serve as a validation case of the multiphase implementations of ODT for extensions to other flow configurations.

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“…The PEI model in this study was developed by Schmidt et al [9,10] as a so-called instantaneous PEI model (noted as type-I) and governs the radial displacement due to an eddy event. Each particle obeys the model if they are located in the sampled eddy region.…”

Section: Particle-eddy Interaction Modelmentioning

confidence: 99%

Numerical studies of turbulent particle-laden jets using spatial approach of one-dimensional turbulence

Fistler¹,

Lignell²,

Kerstein³

et al. 2017

Proceedings ILASS–Europe 2017. 28th Conference on Liquid Atomization and Spray Systems

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To challenge one of the major problems for multiphase flow simulations, namely computational costs, a dimensionreduced model is used with the goal to predict these types of flow more efficiently. One-dimensional turbulence (ODT) is a stochastic model simulating turbulent flow evolution along a notional one-dimensional line of sight by applying instantaneous maps that represent the effect of individual turbulent eddies on property fields. As the particle volume fraction is in an intermediate range above 10 −5 for dilute flows and under 10 −2 for dense ones, turbulence modulation is important and can be sufficiently resolved with a two-way coupling approach, which means the particle phase influences the fluid phase and vice versa. For the coupling mechanism the ODT multiphase model is extended to consider momentum transfer and energy in the deterministic evolution and momentum transfer during the particle-eddy interaction. The changes of the streamwise velocity profiles caused by different solid particle loadings are compared with experimental data as a function of radial position. Additionally, streamwise developments of axial RMS and mean gas velocities along the centerline are evaluated as functions of axial position. To achieve comparable results, the spatial approach of ODT in cylindrical coordinates is used here. The investigated jet configuration features a nozzle diameter of 14.22 cm and a Reynolds number of 8400, which leads to a centerline inlet velocity of 11.7 m/s. The particles used are glass beads with a density of 2500 kg/m 3 . Two different particle diameters (25 and 70 µm) were tested for an evaluation of the models capability to capture the impact of a varying Stokes number and also two different particle solid loadings (0.5 and 1.0) were evaluated. It is shown that the model is capable of capturing turbulence modulation of particles in a round jet. KeywordsJet, particle-laden flows, turbulence modulation, one-dimensional turbulence Introduction Turbulent particle-laden jets play a major role in a wide range of industrial applications and natural phenomena. Especially the effect of particles on the gas-phase, named turbulence modulation, is of particular interest. Several experimental studies, e.g. Schreck and Kleis [11], Geiss et al. [4] and Budilarto [1], have shown the large influence of high particle concentrations on the turbulence level. To investigate this type of flow experimentally and to understand the physical fundamentals is still very challenging, because only a few advanced techniques to obtain spatially resolved unsteady data exist today. CFD (computational fluid dynamics) proved to be a powerful tool to investigate particle-laden flows and to acquire detailed flow information. Many CFD approaches for these flow types have limited predictive capabilities or rely on many assumptions, which affects the accuracy and restrict that generality. Even with access to a high-performance computational infrastructure direct numerical simulation (DNS) studies for particle-laden flow are...

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Non-equilibrium Wall Deposition of Inertial Particles in Turbulent Flow

Cited by 14 publications

References 24 publications

Evaluation of stochastic particle dispersion modeling in turbulent round jets

Evaluation of stochastic particle dispersion modeling in turbulent round jets

Particle dispersion in homogeneous turbulence using the one-dimensional turbulence model

Numerical studies of turbulent particle-laden jets using spatial approach of one-dimensional turbulence

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