Yassin A. Hassan

A two-equation turbulence model of turbulent bubbly flows

Abstract A two-fluid model of turbulent, adiabatic bubbly flow was implemented in the computational fluid dynamics (CFD) CFX4.2 program and validated. Turbulence in the dispersed (bubble) phase was neglected. Liquid turbulence was modeled through a two-phase extension of the single-phase standard k–e model. Conservation equations of turbulent scales contain single-phase and interfacial terms. A closure for the interfacial turbulence terms was proposed based on the assumption of low-bubble inertia and neglecting surface tension. The interfacial turbulence terms account for additional pseudoturbulence in liquid created by bubble-induced mixing. The proposed turbulence model contained the single empirical constant in the modeled dissipation rate balance. The model was implemented in the CFX4.2 commercial CFD solver. Comparing numerical predictions to the experimental data the value of the model constant was estimated. Model predictions were compared to other bubbly flows to prove the universality of the model constant. The comparison showed that the constant has a certain generality. A new, two-phase logarithmic wall law was also implemented and validated. The derivation of the new law was based on an assumption of the additional eddy diffusivity due to the bubble-induced stirring in the boundary layer. An improved wall friction prediction was achieved with the new wall law over conventional single-phase law. The improvement was especially noticeable for the low-liquid flow rates when bubble-induced pseudoturbulence plays a significant role. The ability of the model to account for bubble size effect was also studied.

SIMULTANEOUS VELOCITY MEASUREMENTS OF BOTH COMPONENTS OF A TWO-PHASE FLOW USING PARTICLE IMAGE VELOCIMETRY

Abstract The study undertaken is an examination of a two-phase dispersed air bubble mixing flow within a rectangular vessel. The technique of particle image velocimetry (PIV) is utilized in order to obtain non-invasive velocity measurements of the resulting bubbly flow field and its induced effects upon a surrounding liquid medium. The method provides not only a visualization of the various patterns and structures of a given flow field, but also yields quantitative full-field instantaneous velocity data from both phases of a two-phase system in a concurrent manner. PIV is a rapidly advancing flow visualization technique in which the instantaneous velocity profile of a given flow field is determined by photographically recording tracer particle and/or bubble images within the flow at discrete instances in time, and then conducting computational analysis of the digitized data. The use of developed analysis algorithms, which perform a point-by-point matching of particle and bubble images from one digital image frame to the next, subsequently allows reconstruction of the respective instantaneous velocity profiles. The ability to simultaneously measure the velocity fields of both components of a two-phase flow is an important contribution toward the goal of developing improved correlations for flow regime determination as well as improved model for key two-phase flow parameters such as the interfacial drag. In this work, results were obtained which indicate that the described PIV method is an effective tool in the study of the specific interactions which occur between components in a wide variety of multiphase systems.

Approximation of turbulent conditional averages by stochastic estimation

Conditional averages of turbulent flow quantities can be approximated in terms of unconditional correlation data by means of stochastic estimation. The validity and accuracy of this procedure are investigated by comparing stochastic estimates to conditional averages measured in four turbulent flows: grid turbulence, the axisymmetric shear layer of a round jet, a plane shear layer, and pipe flow. Comparisons are made for quantities that are separated from the conditional data in time or space, and for turbulent pressures, as well as turbulent velocities. In each case, the linear estimate accurately represents large scale structure. Nonlinear quadratic estimation shows little improvement over linear estimation, because the second‐order terms are small for probable values of the turbulent fluctuations.

New tracking algorithm for particle image velocimetry

The cross correlation tracking technique is widely used to analyze image data, in Particle Image Velocimetry (PIV). The technique assumes that the fluid motion, within small regions of the flow field, is parallel over short time intervals. However, actual flow fields may have some distorted motion, such as rotation, shear and expansion. Therefore, if the distortion of the flow field is not negligible, the fluid motion can not be tracked well using the cross correlation technique. In this study, a new algorithm for particle tracking, called the Spring Model technique, has been proposed. The algorithm can be applied to flow fields which exhibit characteristics such as rotation, shear and expansion.The algorithm is based on pattern matching of particle clusters between the first and second image. A particle cluster is composed of particles which are assumed to be connected by invisible elastic springs. Depending on the deformation of the cluster pattern (i.e., the particle positions), the invisible springs have some forces. The smallest force pattern in the second image is the most probable pattern match to the correspondent original pattern in the first image. Therefore, by finding the best matches, particle movements can be tracked between the two images. Three-dimensional flow fields can also be reconstructed with this technique.The effectiveness of the Spring Model technique was verified with synthetic data from both a two-dimensional flow and three-dimensional flow. It showed a high degree of accuracy, even for the three-dimensional calculation. The experimental data from a vortex flow field in a cylinder wake was also measured by the Spring model technique.

Full-field bubbly flow velocity measurements using a multiframe particle tracking technique

The study is an examination of two-phase dispersed air bubble flow about a cylindrical conductor emitting a constant heat flux. The technique of Particle Image Velocimetry is utilized in order to obtain a full-field non-invasive measurement of the resulting bubbly flow velocity field. The employed approach utilizes a flow visualization technique in which the instantaneous velocity profile of a given flow field is determined by digitally recording particle or bubble images within the flow over multiple successive video frames and then conducting a completely computational analysis of the data. The use of particle tracking algorithms which perform a point-by-point matching of seed images from one frame to the next allows construction of particle or bubble pathlines and instantaneous velocity field. Results were initially obtained for a synthetically created flow field and a single phase liquid convective field seeded with flow-following tracer particles. The method was additionally extended to measurements within a gas/liquid system in which bubble rise velocities over a substantial two-dimensional flow area were determined in order to demonstrate the effectiveness of the developed digital data acquisition and analysis methodology.

Investigation of Microbubble Boundary Layer Using Particle Tracking Velocimetry

Particle tracking velocimetry has been used to measure the velocity fields of both continuous phase and dispersed microbubble phase, in a turbulent boundary layer, of a channel flow. Hydrogen and oxygen microbubbles were generated by electrolysis. The average size of the microbubbles was 15μm in radius. Drag reductions up to 40% were obtained, when the accumulation of microbubbles took place in a critical zone within the buffer layer. It is confirmed that a combination of concentration and distribution of microbubbles in the boundary layer can achieve high drag reduction values. Microbubble distribution across the boundary layer and their influence on the profile of the components of the liquid mean velocity vector are presented. The spanwise component of the mean vorticity field was inferred from the measured velocity fields. A decrease in the magnitude of the vorticity is found, leading to an increase of the viscous sublayer thickness. This behavior is similar to the observation of drag reduction by polymer and surfactant injection into liquid flows. The results obtained indicate that drag reduction by microbubble injection is not a simple consequence of density effects, but is an active and dynamic interaction between the turbulence structure in the buffer zone and the distribution of the microbubbles.

Large eddy simulation of turbulent crossflow in tube bundles

Abstract Flow characteristics have been examined in non-staggered and staggered tube bundles using the large eddy simulation method. The simulations use two subgrid scale closure models that are compared to available experimental data in the form of power spectral densities and bound spectra of lift and drag forces. In large eddy simulation, the large scale motions are explicitly resolved while the small scale motions are modeled. The simulations have been performed adopting the large eddy simulation computer code GUST. Rigid two-dimensional tube bundle arrays are considered with staggered and non-staggered geometries. Non-staggered array simulations are carried out for a deep bundle case (100 × 100 grid) and an inflow/outflow case (400 × 160 grid). A deep bundle staggered array simulation (154 × 178 grid) is also performed. Power spectral densities of lift and drag forces correlate well with the experimental data. Correlation functions are used to describe turbulence characteristics. Flow visualization has enabled the distinction of different characteristics within the flow, such as switching effects within a tube bank and in the wake of the bundle flow. These are similar observations as in experimental findings. Comparison of the power spectral densities to bound spectra shows good agreement. The results indicate that the large eddy simulation technique is capable of turbulence prediction in complex geometries and may be used as a viable engineering tool with the careful consideration of the subgrid scale closure model.

PIV flow visualisation using particle tracking techniques

The practical use of particle image velocimetry (PIV) requires the use of fast, reliable, computer-based methods for tracking numerous particles suspended in a fluid flow. Two methods for performing tracking are presented. One method tracks a particle through multiple, sequential images (minimum of four required) by prediction and verification of particle displacement and direction. The other method, requiring only two sequential images, uses a dynamic, binary, spatial, cross-correlation technique. The algorithms were tested on both synthetic data and experimental data which were obtained with traditional PIV methods. This allowed error analysis and testing of the algorithms on real engineering flows.

Interfacial Complexation Explains Anomalous Diffusion in Nanofluids

A recent report describing dramatic anomalous enhancement in mass transport properties of nanofluids (>1000% increase in tracer dye diffusivity) has excited intense interest, but the findings have yet to be conclusively confirmed or explained. Here we investigate these phenomena using a microfluidic approach to directly probe tracer diffusion so that interactions between the suspensions principle components (nanoparticles, surfactant, and dye) can be clearly identified. Under conditions matching previously reported studies, we unexpectedly observe spontaneous formation of highly focused and intensely fluorescent plumes at the interface between fluid streams, suggesting strong complexation interactions between the dye and nanoparticles. These phenomena, driven by competition between the rates at which free tracer molecules are transported into the interfacial zone subsequently consumed by dye-nanoparticle complexation, have likely been incorrectly interpreted as anomalous diffusion enhancement. These interactions are important to consider when devising tracer-based studies of nanoparticle suspensions and may lay a foundation for new adsorption-based analytical methods.

The effect of lattice models within the lattice Boltzmann method in the simulation of wall-bounded turbulent flows

This study investigated the effect of 3D lattice models (D3Q19 and D3Q27 lattices) on the simulation results of wall-bounded turbulent flows in a circular pipe and in a square duct. The LES with the Smagorinsky subgrid-scale (SGS) model was adopted for the turbulence simulation. To improve the credibility of our results on the lattice model effect, a comprehensive sensitivity study was performed of boundary treatment techniques and collision models, as well as grid sizes in the simulation of the turbulent pipe flows. Through the turbulent circular pipe flow simulation, it was discovered that the D3Q27 lattice model could achieve the rotational invariance in terms of long-time-averaged turbulence statistics and generated the results comparable to the DNS data, while the D3Q19 lattice model broke the rotational invariance and produced unreasonable data. In the turbulent square duct flow simulation, the rotational invariance was evaluated by comparing the results before and after rotating the geometry by 45^o about a center. As in the circular pipe flow simulation, the D3Q19 lattice model could not achieve the rotational invariance while the D3Q27 lattice model could. The D3Q19 lattice model also produced poor results compared to those from the D3Q27 lattice model. These defects of the D3Q19 lattice model could be explained by the planes consisting of 2D lattices with five velocities (called defective planes in this study) in the D3Q19 lattice model, based on White and Chongs [14] hypothesis. The defective planes had a deficiency in the momentum transfer of flow and turbulence, thus breaking the rotational invariance and causing the inaccurate results for tested problems.