Abstract: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… Show more
“…The relative difference in the Stokes numbers for the two particle sizes are nearly the same for the three Reynolds numbers (as shown in Table 1), nevertheless, the difference between the dispersion of the two particle sizes decreases as Re increases. This is due to the increase in the magnitude of the Stokes numbers, which decreases the magnitude of the dispersion, as noted above, an effect previously documented with ODT particle modeling [34]. In the previous subsection, the power law scaling of the velocity with x/D was observed to approach similarity differently with increasing Reynolds numbers when comparing the measurements and the ODT predictions; the relative differences in dispersion observed here are consistent with those differences in the velocity evolution.…”
“…In the Type-C interaction, Figure 4: Type-I vs. Type-C particle-eddy interaction. Shadow boxes represent the eddy effect over the spatial domain [y 0 , y + L] and temporal period βpτe; single solid lines represent the particle trajectory; the dashed line represents the particle "interaction" trajectory due to the particle-velocity history in the Type-I interaction [34].…”
Section: Instantaneous and Continuous Particle-eddy Interactionmentioning
confidence: 99%
“…This decreases the particle residence time in the flow. The higher St at higher Re also contributes to the crossing-trajectory effect, which decreases dispersion, when particles exit an eddy prior to the eddy lifetime [34,38,32].…”
“…Punati [25], and Goshayeshi and Sutherland [10,9] studied coal combustion and particle laden jets using ODT (using a version of the Type-C model noted below). In our previous study, one version of the ODT multiphase interaction model using an instantaneous (referred to as Type-I) particle-eddy interaction (PEI) model was presented to investigate particle transport and crossing-trajectory effects in homogeneous turbulence [34]. Here, we extend this previous ODT study to shear flows and present two new PEI models to analyze the behavior of individual particles in jets at high Reynolds numbers (Re).…”
mentioning
confidence: 97%
“…ODT has been applied to many different homogeneous and shear-dominating reacting [8,12,13,26,25,21] and nonreacting [16,18,2,34] flows including homogeneous turbulence, channel flow, jets, mixing layers, buoyant plumes, and wall fires.…”
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.
“…The relative difference in the Stokes numbers for the two particle sizes are nearly the same for the three Reynolds numbers (as shown in Table 1), nevertheless, the difference between the dispersion of the two particle sizes decreases as Re increases. This is due to the increase in the magnitude of the Stokes numbers, which decreases the magnitude of the dispersion, as noted above, an effect previously documented with ODT particle modeling [34]. In the previous subsection, the power law scaling of the velocity with x/D was observed to approach similarity differently with increasing Reynolds numbers when comparing the measurements and the ODT predictions; the relative differences in dispersion observed here are consistent with those differences in the velocity evolution.…”
“…In the Type-C interaction, Figure 4: Type-I vs. Type-C particle-eddy interaction. Shadow boxes represent the eddy effect over the spatial domain [y 0 , y + L] and temporal period βpτe; single solid lines represent the particle trajectory; the dashed line represents the particle "interaction" trajectory due to the particle-velocity history in the Type-I interaction [34].…”
Section: Instantaneous and Continuous Particle-eddy Interactionmentioning
confidence: 99%
“…This decreases the particle residence time in the flow. The higher St at higher Re also contributes to the crossing-trajectory effect, which decreases dispersion, when particles exit an eddy prior to the eddy lifetime [34,38,32].…”
“…Punati [25], and Goshayeshi and Sutherland [10,9] studied coal combustion and particle laden jets using ODT (using a version of the Type-C model noted below). In our previous study, one version of the ODT multiphase interaction model using an instantaneous (referred to as Type-I) particle-eddy interaction (PEI) model was presented to investigate particle transport and crossing-trajectory effects in homogeneous turbulence [34]. Here, we extend this previous ODT study to shear flows and present two new PEI models to analyze the behavior of individual particles in jets at high Reynolds numbers (Re).…”
mentioning
confidence: 97%
“…ODT has been applied to many different homogeneous and shear-dominating reacting [8,12,13,26,25,21] and nonreacting [16,18,2,34] flows including homogeneous turbulence, channel flow, jets, mixing layers, buoyant plumes, and wall fires.…”
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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