Void Fraction and Wake Analysis of a Gas-Liquid Two-Phase Cross-Flow

Hanafizadeh, Pedram; Momenifar, Mohammadreza; Geimassi, A. Nouri; Ghanbarzadeh, Soheil

doi:10.1615/multscientechn.v26.i4.10

Cited by 9 publications

(5 citation statements)

References 22 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Turbulent multiphase flows have been the subject of a numerous studies for many years because of their broad range of applications in nature and industrial contexts such as distribution of greenhouse gases [1], cloud formation [2], volcanic eruptions [3], contaminant transport [4], heat exchangers [5], boiling heat transfer [6], combustion processes [7], air-lift pumps [8], cavitating flows [9], sedimentation process in settling tanks [10], thermosyphons [11] and fluidized bed reactors [12] to name a few. The present work explores the class of multi-phase flows involving the motion of small, settling inertial particles in turbulent flows.…”

Section: Introductionmentioning

confidence: 99%

Local analysis of the clustering, velocities, and accelerations of particles settling in turbulence

Momenifar

Bragg

2020

Phys. Rev. Fluids

Self Cite

View full text Add to dashboard Cite

Using 3D Voronoï analysis, we explore the local dynamics of small, settling, inertial particles in isotropic turbulence using Direct Numerical Simulations (DNS). We independently vary the Taylor Reynolds number R λ ∈ [90, 398], Froude number F r ≡ a η /g ∈ [0.052, ∞] (where a η is the Kolmogorov acceleration, and g is the acceleration due to gravity), and Kolmogorov scale Stokes number St ≡ τ p /τ η ∈ [0, 3]. In agreement with previous results using global measures of particle clustering, such as the Radial Distribution Function (RDF), we find that for small Voronoï volumes (corresponding to the most clustered particles), the behavior is strongly dependent upon St and F r, but only weakly dependent upon R λ , unless St > 1. However, larger Voronoï volumes (void regions) exhibit a much stronger dependence on R λ , even when St ≤ 1, and we show that this, rather than the behavior at small volumes, is the cause of the sensitivity of the standard deviation of the Voronoï volumes that has been previously reported. We also show that the largest contribution to the particle settling velocities is associated with increasingly larger Voronoï volumes as the settling parameter Sv ≡ St/F r is increased.Our local analysis of the acceleration statistics of settling inertial particles shows that clustered particles experience a net acceleration in the direction of gravity, while particles in void regions experience the opposite. The particle acceleration variance, however, is a convex function of the Voronoï volumes, with or without gravity, which seems to indicate a non-trivial relationship between the Voronoï volumes and the sizes of the turbulent flow scales. Results for the variance of the fluid acceleration at the inertial particle positions are of the order of the square of the Kolmogorov acceleration and depend only weakly on Voronoï volumes. These results call into question the "sweep-stick" mechanism for particle clustering in turbulence which would lead one to expect that clustered particles reside in the special regions where the fluid acceleration is zero (or at least small).We then consider the properties of particles in clusters, which are regions of connected Voronoï cells whose volume is less than a certain threshold. The results show self-similarity of the clusters, and that the statistics of the cluster volumes depends only weakly on St, with a stronger dependance on F r and R λ . Finally, we compare the average settling velocities of all particles in the flow with those in clusters, and show that those in the clusters settle much faster, in agreement with previous work. However, we also find that this difference grows significantly with increasing R λ and exhibits a non-monotonic dependence on F r. The kinetic energy of the particles, however, are almost the

show abstract

Section: Introductionmentioning

confidence: 99%

Local analysis of the clustering, velocities, and accelerations of particles settling in turbulence

Momenifar

Bragg

2020

Phys. Rev. Fluids

Self Cite

View full text Add to dashboard Cite

show abstract

“…Multiphase turbulent flows have attracted substantial interest for many years both because of the intellectually stimulating challenges associated with understanding them, and also because of their practical importance to a wide range of applications. Examples include the interaction between multiple flowing fluids such as is found in oilrefrigerant mixtures for refrigeration systems (Borghi & Anselmet (2013); Kolev & Kolev (2005); Momenifar et al (2015)), and the transport of bubbles in liquids such as occur in airlift pumps (Brennen & Brennen (2005); Prosperetti & Tryggvason (2009); Hanafizadeh et al (2014)). The class of multiphase flows involving the motion of small suspended particles in turbulent flows is of particular interest to the present work, being important for environmental sciences (atmospheric pollution transport, sea spray, and cloud formation), astrophysics (protoplanetary disks, and the atmospheres of planets and dwarf stars) and industrial processes (turbulent combustion, spray nozzles, fluidized bed reactors).…”

Section: Introductionmentioning

confidence: 99%

Influence of Reynolds number on the motion of settling, bidisperse inertial particles in turbulence

2019

Self Cite

View full text Add to dashboard Cite

Using Direct Numerical Simulations (DNS), we examine the effects of Taylor Reynolds number, R λ , and Froude number, F r, on the motion of settling, bidisperse inertial particles in isotropic turbulence. Particle accelerations play a key role in the relative motion of bidisperse particles, and we find that reducing F r leads to an enhancement of the accelerations, but a suppression of their intermittency. For Stokes numbers St > 1, the effect of R λ on the accelerations is enhanced by gravity, since settling causes the particle accelerations to be affected by a larger range of flow scales. The results for the Probability Density Function (PDF) of the particle relative velocities show that for bidisperse particles, decreasing F r leads to an enhancement of their relative velocities in both the vertical (parallel to gravity) and horizontal directions. Importantly, our results show that even when the particles are settling very fast, turbulence continues to play a key role in their vertical relative velocities, and increasingly so as R λ is increased. This occurs because although the settling velocity may be much larger than typical velocities of the turbulence, due to intermittency, there are significant regions of the flow where the turbulence contribution to the particle motion is of the same order as that from gravitational settling. Increasing R λ enhances the non-Gaussianity of the relative velocity PDFs, while reducing F r has the opposite effect, and for fast settling particles, the PDFs become approximately Gaussian. Finally, we observe that low-order statistics such as the Radial Distribution Function (RDF) and the particle collision kernel, are strongly affected by F r and St, and especially by the degree of bidispersity of the particles. Indeed, even when the difference in the value of St of the two particles is ≪ 1, the results can differ strongly from the monodisperse case, especially when F r ≪ 1. However, we also find that these low-order statistics are very weakly affected by R λ when St O(1), irrespective of the degree of bidispersity. Therefore, although the mechanisms controlling the collision rates of monodisperse and bidisperse particles are different, they share the property of a weak sensitivity to R λ when St O(1).

show abstract

“…In the third method, the adaptive thresholding algorithm is utilized to distinguish between the background and desired foreground image objects based on the differences in pixel intensities of each region [8,9]. The threshold is based on the range of intensity values within a specific region, rather than a singular threshold value for the entire image [8], [9]. This makes it possible to identify an image with non-uniform illumination.…”

Section: Adaptive Thresholding Algorithmmentioning

confidence: 99%

Evaluating Two-Phase Flow Patterns in Airlift pumps Using Image Processing Technique

Fadlalla¹,

Ahmed²,

Weales³

et al. 2023

Proceedings of the 10th International Conference on Fluid Flow, Heat and Mass Transfer (FFHMT 2023)

View full text Add to dashboard Cite

One of the most important criteria in determining the performance of airlift pumps is to determine the two-phase flow characteristics in the pump riser. These include the determining the average void fraction and both the slug velocity and frequency of the two-phase flow in the vertical pipe. In the current work, three image processing methods were examined to describe the two-phase hydrodynamic parameters as they relate to the pump performance. Experiments were carried out using Xanthan Gum-water solutions with varying XG concentrations between 0.05-0.25 wt% in a pump riser of 31.75 mm in diameter. High-speed camera with 3000 f/s capabilities was used to obtain the flow visualisation images for the two-phase flow distribution downstream of the pump injector. The preliminary results suggested that the image processing technique using background subtraction algorithm can be an effective approach in evaluating the flow structure and consequently can be used to determine void fraction and slug characteristics.

show abstract

Void Fraction and Wake Analysis of a Gas-Liquid Two-Phase Cross-Flow

Cited by 9 publications

References 22 publications

Local analysis of the clustering, velocities, and accelerations of particles settling in turbulence

Local analysis of the clustering, velocities, and accelerations of particles settling in turbulence

Influence of Reynolds number on the motion of settling, bidisperse inertial particles in turbulence

Evaluating Two-Phase Flow Patterns in Airlift pumps Using Image Processing Technique

Contact Info

Product

Resources

About