Gas Dispersion Properties Research Articles

Effect of Gas Dispersion Properties and Bias in Scheelite Column Flotation

Effect of Gas Dispersion Properties and Bias in Scheelite Column Flotation

Hydrodynamics in a Bubble Column – Part 1: Two‐Phase Flow

AbstractMultiphase computational fluid dynamics (CFD) simulation is a useful tool to study the hydrodynamics in a bubble column if appropriate closure models are known. Systematic assessment of different models is an ongoing venture that benefits from improved validation data. The present study accumulates a database on two‐phase flow experiments in a bubble column. This is achieved by using a combination of particle image velocimetry and shadowgraphy to measure the liquid velocity field and gas dispersion properties simultaneously. This methodology is applied for different needle diameters and gas flow rates. The experimental data are compared with CFD simulations which show good predictions. A systematic investigation of the three‐phase flow in the bubble column will appear as a sequel.

CFD-modelling of large-scale LH2 release and explosion experiments

As a part of zero emission ambitions within the maritime, aviation and elsewhere, liquid hydrogen (LH2) will increasingly be used as an energy carrier and fuel in the coming years. It is therefore important to understand safety aspects of LH2, including gas dispersion and explosion properties. In the process of building the world’s first ferry using LH2 as fuel the Norwegian Public Roads Administration commissioned large-scale LH2 release tests to study dispersion and explosion properties relevant for the design and approval processes. Experiments with LH2 releases both indoor and outdoor were performed. In this article these experiments are described and compared to simulations with the CFD-model FLACS. The aim of the modelling is both to better understand the experiments performed, and to demonstrate that important phenomena and physics related to LH2 safety assessments for approval processes can be simulated and predicted with confidence.

Flotation Performance and Gas Dispersion Properties in a Laboratory Flotation Cell

Flotation is a complex process that exhibits high dimensionality which makes modeling and optimization very challenging. One technique to alleviate the dimensionality problem is to combine variables together into more informative ones. Bubble surface area flux and air recovery are examples of dimensionality reduction. Gas holdup also captures the effect of a plurality of variables including gas rate, bubble size, surfactant type, and concentration. This work makes use of a dual flotation–conductivity cell to explore the relationship between gas dispersion properties, including frother concentration and flotation performance. Results demonstrate that gas holdup effectively captured the effect of gas rate and frother concentration and better correlates to flotation performance.

The effects of froth depth and impeller speed on gas dispersion properties and metallurgical performance of an industrial self-aerated flotation machine

In self-aerated flotation machines, the gas rate depends on operational variables (e.g. froth depth and impeller speed), pulp properties (e.g. solid content and viscosity), and reagent addition (e.g. type and concentration of frother). The gas rate has a strong correlation with the flotation performance by influencing the gas dispersion properties and froth retention time. A factorial experimental design was used to study how the gas dispersion properties, the froth retention time, and the flotation performance respond to changes in froth depth and impeller speed (as the most common operational variables). An in-depth understanding of the effects of impeller speed and froth depth on the gas dispersion properties, especially the bubble surface area flux and froth retention time, is necessary to improve operating strategies for self-aerated flotation machines. All experiments were carried out in a 50 m(3) self-aerated flotation cell in an iron ore processing plant. The results showed that the froth depth affected the metallurgical performance mostly via changing the froth retention time. The impeller speed had two important impacts on the metallurgical performance via varying both the froth retention time and the bubble surface area flux in the froth and pulp zones, respectively. The interaction effects of the froth depth and impeller speed were also established. This allowed us to develop a strategy for operating self-aerated flotation machines based on varying the froth depth and impeller speed with regard to the cell duty.

CFD model simulation of bubble surface area flux in flotation column reactor in presence of minerals

Bubble surface area flux (Sb) is one of the main design parameter in flotation column that typically employed to describe the gas dispersion properties, and it has a strong correlation with the flotation rate constant. There is a limited information available in the literature regarding the effect of particle type, density, wettability and concentration on Sb. In this paper, computational fluid dynamics (CFD) simulations are performed to study the gas–liquid–solid three-phase flow dynamics in flotation column by employing the Eulerian–Eulerian formulation with k-ε turbulence model. The model is developed by writing Fortran subroutine and incorporating then into the commercial CFD code AVL FIRE, v.2014. This paper studies the effects of superficial gas velocities and particle type, density, wettability and concentration on Sb and bubble concentration in the flotation column. The model has been validated against published experimental data. It was found that the CFD model was able to predict, where the response variable as indicated by R-Square value of 0.98. These results suggest that the developed CFD model is reasonable to describe the flotation column reactor. From the CFD results, it is also found that Sb decreased with increasing solid concentration and hydrophobicity, but increased with increasing superficial gas velocity. For example, approximately 28% reduction in the surface area flux is observed when coal concentration is increased from 0 to 10%, by volume. While for the same solid concentration and gas flow rate, the bubble surface area flux is approximately increased by 7% in the presences of sphalerite. A possible explanation for this might be that increasing solid concentration and hydrophobicity promotes the bubble coalescence rate leading to the increase in bubble size. Also, it was found that the bubble concentration would decrease with addition of hydrophobic particle (i.e., coal). For instance, under the same operating conditions, approximately 23% reduction in the bubble concentration is predicted when the system was working with hydrophobic particles. The results presented are useful for understanding flow dynamics of three-phase system and provide a basis for further development of CFD model for flotation column.

Predictive control of the bubble size distribution in a two-phase pilot flotation column

Among the gas dispersion properties affecting flotation column behavior, the bubble size distribution (BSD) is one of the most important. Its control could positively contribute to optimize the metallurgical performance. Experimental tests are carried out in a laboratory flotation column working with air and water. The objective is to regulate the BSD to a desired distribution set-point. BSD is measured in real-time using an image analysis method and a dynamic non-linear model (Wiener) for BSD, based on a log-normal distribution, is identified. Finally, a constrained model predictive controller is designed to control the BSD. The proposed approach leads to good control results, thus confirming the possibility to use this strategy to optimize the valuable mineral recovery by adequately selecting the BSD for a given particle size distribution.

Surface tension and gas dispersion properties of fatty acid solutions

The gas dispersion properties of aqueous solutions of fatty acids of different hydrocarbon chain lengths were assessed through measurements of average bubble size and bubble size distributions. Two mechanisms of gas dispersion were identified depending on the pH and speciation of the tested solutions. Solutions of long chain fatty acids containing colloidal precipitates at low pH exhibited low surface tensions, and only a small decrease in bubble sizes was observed for such solutions compared to bubble sizes measured in water. This relatively small change in bubble sizes could theoretically be predicted based only on the corresponding change in the surface tension of the solutions. In contrast, true solutions of long chain fatty acids affected bubble sizes to a much greater extent even though their surface tension values were higher and in some cases comparable to the surface tension of water. A combination of the surface tension and surface tension gradient effects was found to be operative in this case. Experimental results on shorter chain fatty acids strongly suggested that the associated acid species were more surface-active and more capable of reducing bubble sizes than the dissociated carboxylate anion.

Identification of a non-linear dynamic model of the bubble size distribution in a pilot flotation column

Gas dispersion properties play an important role in flotation as they partially determine the metallurgical performance. The objective of this work is to obtain a dynamic model of the bubble size distribution in a two-phase (air and water) pilot flotation column. The steps are: 1) to measure and count the bubbles from digital images taken by a camera, 2) to estimate a log–normal distribution of the bubble sizes, 3) to estimate a Wiener model whose outputs are the mean and standard deviation of the distribution while the inputs are the superficial gas velocity set-point and the superficial shearing water velocity set-point. The size and number of bubbles in each image are evaluated by a bubble detection technique based on circular Hough transform (CHT). This technique allows overcoming issues related to the detection of large single bubbles as well as clusters. Tests are carried out in the laboratory flotation column using different concentrations of frother and air flow rates. Results are compared with visual counting, as well as with a commonly used bubble detection method based on circular particle detection (CPD). The estimated number of bubbles is very similar to what is obtained with a visual count. Compared to CPD algorithm, CHT significantly improves D32 estimation (error of 3% instead of 18% with the former) with a comparable processing time. Then, the mean and standard deviation of a log–normal distribution are estimated by maximizing a likelihood function thereby leading to very good fits for the distributions. Finally, a series of model identification tests are conducted by manipulating the superficial gas velocity set-point and the superficial shearing water velocity set-point (i.e. air and shearing water flow rate set-points through the sparger). A Wiener model is then estimated to predict the corresponding mean and standard deviation of the log–normal distribution. Validation tests confirm the quality of the non-linear model.

Automatic control of bubble size in a laboratory flotation column

Gas dispersion properties play an important role on determining the metallurgical performance of flotation processes. Indeed, bubble surface area flux (Sb) has been found to correlate with the collection zone flotation rate constant and is therefore a potential variable to regulate in order to achieve a target performance. Sb can be calculated as a combination of two other gas dispersion properties, namely, gas superficial velocity and the Sauter bubble mean diameter. This communication describes the design and implementation of a feedback control system for the Sauter bubble mean diameter in an attempt towards controlling Sb. In order to track changes on bubble size, the Sauter bubble mean diameter was derived from an adaptive bubble size probability density function (PDF). A Gaussian mixture model was used to represent the bubble size PDF and its parameters were updated on-line and in real-time by a dedicated computer from sequentially incoming images. To improve bubble size controllability, a frit-and-sleeve sparging device was installed. This device allows modifying bubble size by manipulating the water flow rate circulating through a sleeve surrounding a porous ring (shear water). A Wiener model is used to represent the dynamic relationship between the shear water flow rate and the Sauter bubble mean diameter. A nonlinear control, based on the internal model control (IMC) structure, was designed and implemented. Tracking and regulation performance against gas velocity and unmeasured frother concentration variations were then successfully evaluated in a two-phase system.

Influence of impeller diameter on overall gas dispersion properties in a sparged multi-impeller stirred tank

The impeller configuration with a six parabolic blade disk turbine below two down-pumping hydrofoil propellers, identified as PDT+2CBY, was used in this study. The effect of the impeller diameter D, ranging from 0.30T to 0.40T (T as the tank diameter), on gas dispersion in a stirred tank of 0.48m diameter was investigated by experimental and CFD simulation methods. Power consumption and total gas holdup were measured for the same impeller configuration PDT+2CBY with four different D/T. Results show that with D/T increases from 0.30 to 0.40, the relative power demand (RPD) in a gas–liquid system decreases slightly. At low superficial gas velocity VS of 0.0078m·s−1, the gas holdup increases evidently with the increase of D/T. However, at high superficial gas velocity, the system with D/T=0.33 gets a good balance between the gas recirculation and liquid shearing rate, which resulted in the highest gas holdup among four different D/T. CFD simulation based on the two-fluid model along with the Population Balance Model (PBM) was used to investigate the effect of impeller diameter on the gas dispersion. The power consumption and total gas holdup predicted by CFD simulation were in reasonable agreement with the experimental data.

Influence of impeller diameter on local gas dispersion properties in a sparged multi-impeller stirred tank

Vertical distributions of local void fraction and bubble size in air–water dispersion system were measured with a dual conductivity probe in a fully baffled dished base stirred vessel with the diameter T of 0.48m, holding 0.134m3 liquid. The impeller combination with a six parabolic blade disk turbine below two down-pumping hydrofoil propellers, identified as PDT+2CBY, was used in this study. The effects of the impeller diameter D, ranging from 0.30T to 0.40T (corresponding to D/T from 0.30 to 0.40), on the local void fraction and bubble size were investigated by both experimental and CFD simulation methods. At low superficial gas velocity VS of 0.0077m·s−1, there is no obvious difference in the local void fraction distribution for all systems with different D/T. However, at high superficial gas velocity, the system with a D/T of 0.30 leads to higher local void fraction than systems with other D/T. There is no significant variation in the axial distribution of the Sauter mean bubble size for all the systems with different D/T at the same gas superficial velocity. CFD simulation based on the two-fluid model along with the population balance model (PBM) was used to investigate the effect of the impeller diameter on the gas–liquid flows. The local void fraction predicted by the numerical simulation approach was in reasonable agreement with the experimental data.

Application of Statistical Analysis on the Bubble Surface Area Flux in a Column Flotation Cell

Flotation is a widely used separation process with applications from mineral separation to de-inking of recycled paper, waste water treatment, and solid remediation. In flotation column, bubble surface area flux (Sb) has been reported to describe the gas dispersion properties, and it has a strong correlation with the flotation rate constant. No information is available regarding Sb for coal flotation in column cell. This paper describes the effects of hydrodynamic parameters on Sb by means of a 23 factorial experimental design in designed flotation column using coal slurry. The results showed that Sb increased with increasing superficial gas velocity and frother concentration, but decreased with increasing solid concentration. The main and interaction effects of operating parameters on Sb were evaluated using Yates’ analysis. The statistical model was developed to predict Sb in column flotation cell using experimental data. This paper also presents the development of the statistical model and the validation using a number of additional data sets. There is a good agreement between experimental results and predicted results from the developed model.

Foaming and gas dispersion properties of non-ionic frothers in the presence of hydrophobized submicron particles

Foams represent an important area of research due to their relevance in many industrial processes. In many systems, particulates and surfactants co-exist and can largely define the stability of the foam. A typical example is froth flotation where hydrophobic particles and frothers are essential to maintain a stable froth. Grinding operations may yield a product containing submicron-size particles, which can affect the flotation process. The present study compares the foaming and gas dispersion properties of the non-ionic surfactants 1-pentanol, tri(propylene glycol) methyl ether, and poly(propylene glycol) 425 in the presence of hydrophobic colloidal silica particles in a column. In all cases, it has been found that the gas holdup increases proportionally with the increase in the concentration of particles in the system although an initial decrease may be observed. The effect of particles on the foaminess seems to be dependent upon the surfactant. With the 1-pentanol, the addition of particles systematically decreased the foaminess of the solutions. This is in contrast to poly(propylene glycol) solutions, which exhibited an increase. Interestingly, low concentrations of particles appeared to improve the foaminess of tri(propylene glycol) methyl ether; however, the froth became less stable with further increases in the number of particles in the column. Visual observation showed that the colloidal particles play a crucial role in defining the quality of the structure of the froth.

Measuring gas dispersion parameters: Selection of sampling points

Bubble surface area flux has proven to be a key operational variable in flotation machines not only for diagnosis but also for optimization purposes. It is calculated as a combination of two gas dispersion properties, superficial gas velocity and bubble Sauter mean diameter. Since gas is not necessarily distributed evenly over the cross sectional area of a cell the sampling point where gas dispersion properties are measured must be carefully selected. This article illustrates that a radial parabolic gas velocity profile exists in mechanical cells, in some cases with significant variation in gas velocity as a function of radial distance from the center. An optimal sampling location for single point gas dispersion measurements in mechanical flotation machines is proposed.

Foaming and gas dispersion properties of non-ionic surfactants in the presence of an inorganic electrolyte

Foams represent an important area of research due to their relevance in many industrial processes. Where there are geographical constraints, which can limit access to fresh water, there is an economic incentive in using recycled water, bore water and even seawater for industrial purposes. This creates a growing interest in determining the effect of inorganic electrolytes on foaming and gas dispersion properties of non-ionic surfactant solutions. The present study compares the foaming and gas dispersion properties of the non-ionic surfactants 1-pentanol, tri(propylene glycol) methyl ether, and poly(propylene glycol) 425. For all surfactants, the stabilisation mechanism was influenced by the concentration of surfactant and the presence of salt with PPG being affected to a lesser extent. Sodium chloride was observed to have a detrimental effect on foaming at higher surfactant concentrations but improved foaming at low surfactant concentrations. At low surfactant concentrations, the addition of salt improved foaminess by dampening the hydrophobic force. An increase in gas holdup with increasing surfactant concentration was observed and was attributed to a decrease in bubble size. For poly(propylene glycol) an initial decrease in gas holdup was observed at very low concentrations. Salt mainly affected gas dispersion properties at a higher concentration.

GAS ABSORPTION IN STIRRED GAS-LIQUID-LIQUID SYSTEMS: EFFECT OF TRANSFERRED SOLUTE SOLUBILITY AND OIL PHASE SPREADING CHARACTERISTICS

The effect on gas-liquid mass transfer of dispersing an oil phase in water in an aerated stirred tank is not predictable, because the mechanisms involved are not well understood. To try to elucidate these mechanisms, a set of experiments was carried out that included: (i) measurement of the effect of oil addition on gas dispersion properties, (ii) quantification of mass transfer of two solutes (heptane and oxygen) with very different solubilities in the liquid phases, and (iii) variation of the spreading characteristics of the oil phase, which consisted of mixtures of dodecane and heptane in varying concentrations. It was found that in the case of heptane mass transfer, when the oil spreading coefficient S changes from negative to positive, the outlet gas becomes practically saturated, corresponding to a several-fold increase in mass transfer coefficient. In the case of oxygen mass transfer, the effect of S is not as dramatic, but it is also quite significant. For a spreading oil phase (S > 0), the mass transfer coefficient decreases upon trace oil addition, going through a minimum as oil holdup increases, and then increasing steadily. In the case of a non-spreading oil phase, mass transfer coefficient initially increases with oil holdup increase, going through a maximum and then decreasing. Comparison between mass transfer coefficients for the two solutes indicates that kLa for heptane is larger than that of oxygen by a margin not explainable through the difference in diffusivities, which is evidence for a difference in transfer paths/mechanisms. A physical interpretation compatible with these results is offered.

A stochastic approach for measuring bubble size distribution via image analysis

Gas dispersion properties are key parameters in flotation performance. Flotation rate constant has been reported to be strongly influenced by the bubble surface area flux (Sb). In order to determine Sb, both superficial gas velocity (Jg) and the bubble size distribution (BSD) have to be measured. The superficial gas velocity can be easily measured using the inverted probe method. On the other hand, measuring the bubble size distribution is an intricate process. Among the available methods for measuring BSD, image analysis is the most popular; nevertheless, it has some limitations, especially when bubbles appear touching each other in the image (bubble clusters). From a classical image analysis point of view, it is usually assumed that bubble clusters occur as a non-selective process and that not considering them does not bias the measurement.In this work, an alternative method for measuring BSD is presented. The image is represented as a coverage stochastic process, namely a Boolean model with circular objects, which allows determining statistical diameters, d10 and d32, and the complete BSD directly from the binary image. Both the classical image analysis and the Boolean modelling were tested first with a series of images generated at a laboratory flotation cell, and later with a series of simulated images where the actual BSD was known. In both cases, the stochastic approach proved to be better than classical image analysis in the determination of BSD and statistical diameters. The results show that even if bubble clusters are non-selective (which was imposed on the simulated images) large bubbles are more likely to be in a cluster, which implies that clusters must be considered in the measurement to avoid biased estimations.

The Empirical Prediction of Gas Dispersion Parameters on Mechanical Flotation Cells

Gas dispersion properties include bubble size ( ), gas holdup ( ) and bubble surface area flux ( ) and input power ( ) are effective parameters on flotation performance. During the last 10 years, some investigations have been carried out to measure these parameters in mechanical flotation cells. In this research, some models are created to estimate gas dispersion properties and input power by experimental data. Variables of models are impeller peripheral speed ( ), superficial gas velocity ( ) and pulp density ( ) and final form of models are , , and . According to these equations, most effective variables are , and , respectively.

Nonlinear control of bubble size in a laboratory flotation column

Gas dispersion properties have proven to be key variables of the flotation process. Among them, bubble surface area flux (BSAF) has been reported to linearly correlate with the flotation rate constant; therefore, it is a potential variable to achieve a desired metallurgical performance. BSAF can be represented as a combination of two other gas dispersion properties: superficial gas velocity and Sauter mean bubble diameter. Thus, controlling BSAF implies controlling bubble size and superficial gas velocity. This work focuses on the nonlinear control of the Sauter mean bubble diameter. Sauter bubble mean diameter was indirectly calculated from the bubble size distribution, estimated by using a Gaussian mixture model. To improve controllability, a so-called frit-and-sleeve sparger was installed to regulate bubble size independently from superficial gas velocity. With this device, the bubble size can be modified by manipulating the water flow rate circulating through the sleeve that surrounds the porous ring. A Wiener model is used to represent the dynamic relationship between the sleeve water flow rate and Sauter mean diameter. Wiener models consist of a linear system in series with a memory-less (static) nonlinear element. An IMC controller based on the identified Wiener model was implemented in a laboratory flotation column. Tracking performance and rejection of gas velocity and unmeasured frother concentration variations were then successfully evaluated.